Comprehensive energy system planning and scheduling method and device considering demand side response

Abstract

The invention discloses an integrated energy system planning and scheduling method and device considering demand side response. The method comprises the following steps: establishing load models of price type demand response, excitation type demand response and alternative type demand response; establishing an initial planning scheduling model by taking the lowest annual operation cost and the lowest demand side response cost of the full-life-cycle integrated energy system as a first optimization target; solving the initial planning scheduling model in combination with operation constraint conditions and user satisfaction constraints to obtain load transfer quantity and reduction quantity after price-type demand response and excitation-type demand response, and a real-time pricing mechanism; carrying out alternative demand response based on a real-time pricing mechanism to obtain an optimized price curve and load substitution quantities of various energy sources; and solving the planning scheduling optimization model taking the lowest annual operation cost of the full-life-cycle integrated energy system as a second optimization target to obtain an optimal capacity configuration result and an operation scheduling plan of each energy device in the integrated energy system.

Description

Technical Field

[0001] The present invention relates to the technical field of integrated energy system scheduling, and in particular to an integrated energy system planning and scheduling method and device taking demand-side response into consideration. Background Art

[0002] Globally, traditional fossil energy (such as coal, oil, and natural gas) still dominates, but the non-renewable nature of these energy sources and the environmental problems caused by their use make the development and utilization of renewable energy essential. The rapid development of clean energy such as wind energy, solar energy, and biomass energy has promoted the diversification of energy system structure. Integrated Energy System (IES) is an energy system that integrates multiple energy forms and technologies to achieve efficient energy conversion, optimal utilization, and sustainable development.

[0003] Due to the lack of effective incentive mechanisms and user-friendly technical interfaces, the existing system performs poorly in mobilizing users to participate in demand-side response. Many users have limited understanding of the concept and benefits of demand-side response, resulting in low participation. In addition, complex participation processes and high-threshold technical requirements also hinder widespread user participation. This makes it difficult for the system to effectively adjust loads and shave peaks and fill valleys through demand-side response, thereby reducing the flexibility and reliability of the system. Most of the existing integrated energy systems focus on supply-side optimization, focusing on how to improve energy efficiency through multi-energy complementarity, energy storage and conversion technologies. As an innovative mechanism that can dynamically adjust energy consumption, demand-side response (DR) has not yet been fully tapped. The current system has deficiencies in integrating real-time response and flexible adjustment of user needs, making it difficult to achieve accurate matching of energy supply and demand and maximize the overall benefits of the system.

[0004] As a virtual dispatchable resource, demand-side users have been widely studied in terms of price response and incentive response. For price-based demand response, the core lies in the energy price formulation strategy, so that users can adjust their energy consumption behavior according to the energy price differences in different time periods. Therefore, it has received widespread attention. However, the price-based demand response sends the same energy price to each user, ignoring the differences between users, and it is difficult to flexibly mobilize the enthusiasm of different types of users to participate in demand response. In incentive-based demand response, load aggregators pay incentive subsidies to encourage multiple users to participate in demand response. Although incentive-based demand response has advantages in mobilizing user response enthusiasm, its reward mechanism often sacrifices energy demand, greatly reducing the comfort of user energy use. Summary of the invention

[0005] In order to address the deficiencies in the prior art, the present invention provides a comprehensive energy system planning and scheduling method and device taking demand-side response into consideration. By utilizing the complementary advantages of price-based demand response and incentive-based demand response, it is possible to increase user enthusiasm while not reducing user energy comfort, thereby achieving collaborative optimization with minimal user psychological effect and maximal supplier benefits. Alternative demand response is carried out by replacing higher-priced energy with low-priced energy, thereby achieving a balance of interests between the supply and demand sides without changing the supply-demand relationship, and ensuring the economic and safe operation of the power system.

[0006] The present invention adopts the following technical solution.

[0007] In a first aspect, the present invention provides a method for planning and scheduling an integrated energy system considering demand-side response, the method comprising the following steps:

[0008] S1. Obtain historical load data of users in the target area, historical data of wind and solar resources, technical and economic parameters of various energy equipment, and time-of-use electricity price mechanism;

[0009] S2. Establish load models for price-based demand response, incentive-based demand response, and substitution-based demand response;

[0010] S3. Taking the lowest annualized operating cost of the integrated energy system over the entire life cycle and the lowest demand-side response cost as the first optimization goal, an initial planning and scheduling model considering price-based demand response and incentive-based demand response is established;

[0011] S4. Based on the data information obtained in step S1, combined with the operation constraints of the integrated energy system and the user satisfaction constraints, the initial planning and scheduling model is solved to obtain the load transfer and reduction after the price-based demand response and the incentive-based demand response, as well as the real-time pricing mechanism;

[0012] S5. Perform alternative demand response based on real-time pricing mechanism to obtain optimized price curve and load substitution of various energy sources;

[0013] S6. Based on the optimized price curve, the load substitution of various energy sources and the acquired data information, under the operating constraints, the planning and scheduling optimization model with the lowest annualized operating cost of the integrated energy system over the entire life cycle as the second optimization goal is solved to obtain the optimal capacity configuration results and operation scheduling plan of each energy equipment in the integrated energy system.

[0014] Optionally, the energy equipment includes: photovoltaic generator sets, wind generator sets, thermal generator sets, batteries, electrolyzers, hydrogen storage tanks, carbon dioxide storage tanks, carbon capture systems, methane synthesis equipment, gas boilers, heat storage tanks and / or electric heating boilers;

[0015] The technical and economic parameters include: unit capacity investment cost of each energy equipment, unit capacity maintenance cost, carbon tax penalty, transferable load response cost, reducible load response cost, electricity demand price elasticity coefficient, gas demand price elasticity coefficient, effective calorific value conversion coefficient and time-of-use pricing.

[0016] Optionally, the price-based demand response refers to guiding the energy consumption behavior of users by formulating time-of-use electricity prices to achieve the transfer of load peaks to load valleys;

[0017] The incentive-based demand response refers to the signing of relevant economic contracts between demand response providers and users with freely controllable loads, and the reduction of corresponding user loads when the power generated by the grid side is insufficient, and economic compensation is given;

[0018] The substitution demand response refers to the user using the comprehensive price of electricity, heat and natural gas as a criterion to replace loads with each other according to the rule of replacing higher-priced energy with lower-priced energy.

[0019] Optionally, the load model of the price-based demand response includes a transferable load, and its expression is as follows:

[0020]

[0021] Wherein, d(t) represents the load after participating in demand response at time t; d0(t) represents the basic load before participating in demand response at time t; E(t, t') represents the influence of the load variable at time t on the load at time t', that is, the self-elasticity coefficient at time t; ρ(t) represents the energy price at time t; ρ0(t') represents the initial energy price before response at time t'.

[0022] Optionally, the load model of the incentive-based demand response includes curtailable loads; the curtailable loads are divided into directly interrupted loads and partially curtailed loads;

[0023] The direct interruption load model expression is as follows:

[0024]

[0025] In the formula, and They represent the user load and the direct interruption amount of load after the direct interruption of the i-th energy source at time t respectively; Direct interruption of load Initial load d i,0 (t) maximum ratio; Δd i,0 (t) represents the initial direct interruption load at time t; e, h and g represent electric energy, thermal energy and natural gas respectively;

[0026] The model expression of partial load reduction is as follows:

[0027]

[0028] In the formula, The user represents the load after the user partially reduces the i-th energy load at time t; Partial load reduction Initial load d i,0 (t) maximum ratio; represents the curtailable load factor at time t; ρ i (t) represents the price of the i-th energy after participating in the demand-side response at time t; ρ i,0 (t) represents the energy price after the i-th energy participates in the demand-side response at time t.

[0029] Optionally, the objective function with the lowest annualized operating cost of the integrated energy system over the entire life cycle and the lowest demand-side response cost as the first optimization goal is as follows:

[0030] F1=min f static +Zf IDR

[0031] Where F1 is the total cost of the integrated energy system considering price-based demand response and incentive-based demand response; Z is the number of days in the whole year for calculation; f IDR The cost of demand response on a typical day; static The annual operating cost of the integrated energy system over its entire life cycle is: static =C INV +C OM +C RT +C CE ; C OM is the system operation and maintenance cost; C RT is the resource transaction cost; C CE is the cost of carbon dioxide emissions; C INV System investment cost.

[0032] Optionally, the cost of demand response during the typical day is IDR The calculation formula is as follows:

[0033]

[0034] In the formula, and are the unit response cost of the i-th energy source at time t for the transferable load, directly interrupted load and partially reduced load respectively; and They respectively represent the amount of transferable load, directly interrupted load and partially reduced load of the i-th energy participating in the demand-side response at time t; e, h and g represent electricity, thermal energy and natural gas, respectively.

[0035] Optionally, the operating constraints of the integrated energy system include: upper and lower output constraints and ramp constraints of thermal power units, upper and lower power constraints of carbon capture systems, upper and lower power constraints of electrolyzers and ramp constraints, upper and lower output constraints of methane synthesis equipment and ramp constraints, gas storage capacity and inlet and outlet gas constraints of hydrogen storage equipment, gas storage capacity and inlet and outlet gas constraints of carbon dioxide storage equipment, equipment safe operation constraints, system energy balance constraints and material conservation constraints.

[0036] Optionally, the expression of the user satisfaction constraint is as follows:

[0037]

[0038] In the formula, Energy satisfaction index for users UNS The minimum threshold, Δd i,0 (t) represents the load of the i-th energy source before it participates in the demand-side response at time t; represents the load of the i-th energy participating in the demand-side response at time t; e, h and g represent electricity, thermal energy and natural gas, respectively.

[0039] Optionally, the step of performing alternative demand response based on the real-time pricing mechanism includes: comparing the comprehensive prices of electric energy, thermal energy and natural gas based on the real-time pricing mechanism; and performing mutual substitution between various types of loads according to the following substitution rules based on the comparison result:

[0040] Rule 1: When the comprehensive electricity price is greater than the comprehensive heat price and the comprehensive heat price is greater than the comprehensive gas price, the electricity load is replaced by the gas load and the heat load, and the heat load is replaced by the gas load;

[0041] Rule 2: When the comprehensive electricity price is greater than the comprehensive gas price and the comprehensive gas price is greater than the comprehensive heat price, the electricity load is replaced by the heat load and the gas load, and the gas load is replaced by the heat load;

[0042] Rule 3: When the comprehensive heat price is greater than the comprehensive electricity price and the comprehensive electricity price is greater than the comprehensive gas price, the heat load is replaced by the electricity load and the gas load, and the electricity load is replaced by the gas load;

[0043] Rule 4: When the comprehensive heat price is greater than the comprehensive gas price and the comprehensive gas price is greater than the comprehensive electricity price, the heat load is replaced by the gas load and the electricity load, and the gas load is replaced by the electricity load;

[0044] Rule 5: When the comprehensive gas price is greater than the comprehensive electricity price and the comprehensive electricity price is greater than the comprehensive heat price, the gas load is replaced by the electricity load and the heat load, and the electricity load is replaced by the heat load;

[0045] Rule 6: When the comprehensive gas price is greater than the comprehensive heat price and the comprehensive heat price is greater than the comprehensive electricity price, the gas load is replaced by the heat load and the electricity load, and the heat load is replaced by the electricity load.

[0046] Optionally, the load model of the alternative demand response under the above rule is as follows:

[0047]

[0048]

[0049] In the formula, and They are comprehensive electricity price, comprehensive heat price and comprehensive gas price; It represents the electric load change caused by the demand-side response at time t; represents the gas load change caused by the demand-side response at time t; represents the heat load changed by the demand-side response at time t; represents the electric load replaced by the gas load at time t; represents the electrical load replaced by the thermal load at time t; represents the heat load replaced by gas load at time t; μ eg and θ eg They represent the calorific value conversion coefficient and logic control variable of the electric load replaced by the gas load; μ hg and θ hg They represent the calorific value conversion coefficient and logic control variable of the heat load replaced by the gas load; μ eh and θ eh They represent the calorific value conversion coefficient of the electrical load replaced by the thermal load and the logical control variable respectively; among which, θ hg ,θ eg and θ hg The average value is -1; LHV NG Indicates the lower heating value of natural gas.

[0050] Optionally, the load model of the alternative demand response under Rule 2 is as follows:

[0051]

[0052]

[0053] In the formula, and They are comprehensive electricity price, comprehensive heat price and comprehensive gas price; It represents the electric load change caused by the demand-side response at time t; represents the gas load change caused by the demand-side response at time t; represents the heat load changed by the demand-side response at time t; represents the electric load replaced by the gas load at time t; represents the electrical load replaced by the thermal load at time t; represents the gas load replaced by the heat load at time t; μ eg and θ eg They represent the calorific value conversion coefficient and logic control variable of the electric load replaced by the gas load; μ gh and θ gh They represent the calorific value conversion coefficient of the gas load replaced by the heat load and the logical control variable; μ eh and θ eh They represent the calorific value conversion coefficient of the electrical load replaced by the thermal load and the logical control variable respectively; among which, θ eh and θ eg The average value is -1, θ gh The value of LHV is 1; NG Indicates the lower heating value of natural gas.

[0054] Optionally, the load model of the alternative demand response under Rule 3 is as follows:

[0055]

[0056]

[0057] In the formula, and They are comprehensive electricity price, comprehensive heat price and comprehensive gas price; It represents the electric load change caused by the demand-side response at time t; represents the gas load change caused by the demand-side response at time t; represents the heat load changed by the demand-side response at time t; represents the electric load replaced by the gas load at time t; represents the heat load replaced by the electric load at time t; represents the heat load replaced by gas load at time t; μ eg and θ eg They represent the calorific value conversion coefficient and logic control variable of the electric load replaced by the gas load; μ hg and θ hg They represent the calorific value conversion coefficient and logic control variable of the heat load replaced by the gas load; μ he and θ he They represent the calorific value conversion coefficient and logical control variable of the heat load replaced by the electric load; among them, θ hg and θ eg The average value is -1, θ he The value of LHV is 1; NGIndicates the lower heating value of natural gas.

[0058] Optionally, the load model of the alternative demand response under Rule 4 is as follows:

[0059]

[0060]

[0061] In the formula, and They are comprehensive electricity price, comprehensive heat price and comprehensive gas price; It represents the electric load change caused by the demand-side response at time t; represents the gas load change caused by the demand-side response at time t; represents the heat load changed by the demand-side response at time t; represents the gas load replaced by the electric load at time t; represents the heat load replaced by the electric load at time t; represents the heat load replaced by gas load at time t; μ ge and θ ge They represent the heat value conversion coefficient and logic control variable of the gas load replaced by the electric load; μ hg and θ hg They represent the calorific value conversion coefficient and logic control variable of the heat load replaced by the gas load; μ he and θ he They represent the calorific value conversion coefficient and logical control variable of the heat load replaced by the electric load; among them, θ he and θ he The average value is 1, θ hg The value of LHV is -1; NG Indicates the lower heating value of natural gas.

[0062] Optionally, the load model of the alternative demand response under Rule 5 is as follows:

[0063]

[0064]

[0065] In the formula, and They are comprehensive electricity price, comprehensive heat price and comprehensive gas price; It represents the electric load change caused by the demand-side response at time t; represents the gas load change caused by the demand-side response at time t; represents the heat load changed by the demand-side response at time t; represents the gas load replaced by the electric load at time t; represents the electrical load replaced by the thermal load at time t; represents the gas load replaced by the heat load at time t; μ ge and θ ge They represent the heat value conversion coefficient and logic control variable of the gas load replaced by the electric load; μ gh and θ gh They represent the calorific value conversion coefficient of the gas load replaced by the heat load and the logical control variable; μ eh and θ eh They represent the calorific value conversion coefficient of the electrical load replaced by the thermal load and the logical control variable respectively; among which, θ ge and θ gh The average value is 1, θ eh The value of LHV is -1; NG Indicates the lower heating value of natural gas.

[0066] Optionally, the load model of the alternative demand response under Rule 6 is as follows:

[0067]

[0068]

[0069] In the formula, and They are comprehensive electricity price, comprehensive heat price and comprehensive gas price; It represents the electric load change caused by the demand-side response at time t; represents the gas load change caused by the demand-side response at time t; represents the heat load changed by the demand-side response at time t; represents the gas load replaced by the electric load at time t; represents the heat load replaced by the electric load at time t; represents the gas load replaced by the heat load at time t; μ ge and θ ge They represent the heat value conversion coefficient and logic control variable of the gas load replaced by the electric load; μ gh and θ gh They represent the calorific value conversion coefficient of the gas load replaced by the heat load and the logical control variable; μ he and θ he They represent the calorific value conversion coefficient and logical control variable of the heat load replaced by the electric load; among them, θ ge ,θ he and θ gh The average value is 1; LHV NG Indicates the lower heating value of natural gas.

[0070] In a second aspect, the present invention provides a comprehensive energy system planning and scheduling device considering demand-side response, which runs the steps of any method described in the first aspect of the present invention, and the device includes:

[0071] The data acquisition module is used to obtain the historical load data of users in the target area, the historical data of wind and solar resources, the technical and economic parameters of various energy equipment, and the time-of-use electricity price mechanism;

[0072] Establish a load model module for establishing load models of price-based demand response, incentive-based demand response and alternative demand response;

[0073] Establish an initial model module to take the lowest annualized operating cost of the integrated energy system over the entire life cycle and the lowest demand-side response cost as the first optimization goal, and establish an initial planning and scheduling model that considers price-based demand response and incentive-based demand response;

[0074] An initial planning and scheduling module is used to solve the initial planning and scheduling model based on the acquired data information, combined with the operation constraints of the integrated energy system and the user satisfaction constraints, to obtain the load transfer and reduction after the price-based demand response and the incentive-based demand response, as well as the real-time pricing mechanism;

[0075] Load substitution module, which is used to perform substitution-type demand response based on real-time pricing mechanism, and obtain optimized price curves and load substitution amounts of various energy sources;

[0076] The planning and scheduling optimization module is used to solve the planning and scheduling optimization model with the lowest annualized operating cost of the integrated energy system over the entire life cycle as the second optimization goal based on the optimized price curve, the load replacement of various energy sources and the acquired data information, under the operating constraints, to obtain the optimal capacity configuration results and operation scheduling plan of each energy equipment in the integrated energy system.

[0077] In a third aspect, the present invention provides a terminal, including a processor and a storage medium;

[0078] The storage medium is used to store instructions;

[0079] The processor is used to operate according to the instructions to execute the steps of any one of the methods described in the first aspect of the present invention.

[0080] In a fourth aspect, the present invention provides a computer-readable storage medium having a computer program stored thereon, which, when executed by a processor, implements the steps of any one of the methods described in the first aspect of the present invention.

[0081] The beneficial effects of the present invention are as follows:

[0082] 1. The present invention optimizes the planning and scheduling of the integrated energy system by considering the comprehensive demand response IDR of price-based demand response, incentive-based demand response and alternative demand response. By utilizing the complementary advantages of price-based demand response and incentive-based demand response, it can improve the enthusiasm of users without reducing the energy comfort of users, thereby achieving collaborative optimization with minimal psychological effects on users and maximum benefits for suppliers, and carrying out alternative demand response by replacing high-priced energy with low-priced energy. Under the premise of not changing the supply-demand relationship, it achieves a balance of interests between the supply and demand sides, thereby ensuring the economic and safe operation of the power system.

[0083] 2. In the integrated demand response IDR, different from the load response based on the time-of-use pricing mechanism, the present invention can timely adjust the energy price according to the real-time supply and demand relationship of the integrated energy system IES by adopting a real-time pricing mechanism, which further taps the user's response potential and has better economic efficiency; the optimized real-time electricity and gas prices are updated faster than the initial prices. Overall, the real-time pricing mechanism makes most peak prices higher, valley prices lower, and normal prices appropriately adjusted according to actual conditions, which stimulates the enthusiasm and flexibility of users to participate in demand-side response to a greater extent.

[0084] 3. After considering the comprehensive demand-side response IDR, the present invention shows different degrees of "peak shaving and valley filling" phenomenon in electricity, heat and gas loads, which greatly reduces the volatility of the load side. Compared with the comprehensive energy system without considering IDR, the energy purchase cost after considering IDR is significantly reduced, and the investment cost of equipment is also reduced, thereby indirectly reducing the operation and maintenance cost and carbon emission cost of the equipment, and improving the overall economic benefits.

[0085] 4. The integration of the power-to-gas unit in the integrated system combines the carbon dioxide emitted by the thermal power units with the hydrogen obtained by electrolysis in the electrolyzer, producing high-value methane products to meet the gas load while reducing greenhouse gas emissions in the region and generating certain environmental benefits.

[0086] 5. Experimental results show that the present invention optimizes the planning and scheduling strategy of the integrated energy system by considering three types of integrated demand response IDR, which plays a positive role in promoting the consumption of renewable energy in the integrated energy system and improving the self-sufficiency of the integrated energy system. BRIEF DESCRIPTION OF THE DRAWINGS

[0087] Figure 1 It is a flow chart of a comprehensive energy system planning and scheduling method considering demand-side response in an embodiment of the present invention;

[0088] Figure 2 is a schematic diagram of the integrated demand response IDR principle in an embodiment of the present invention;

[0089] Figure 3It is a schematic diagram of the interaction between the integrated demand response IDR management system, the IES integrated energy system and the load user in an embodiment of the present invention;

[0090] Figure 4 is a schematic diagram of the structure of an integrated energy system IES in an embodiment of the present invention;

[0091] Figure 5 is the historical data of wind and solar loads on a typical day in the embodiment of the present invention;

[0092] Figure 6 It is a schematic diagram of the demand response quantity of electricity and gas load price type based on the real-time pricing mechanism and the time-sharing pricing mechanism in an embodiment of the present invention;

[0093] Figure 7 is a schematic diagram of electricity price and gas price curves before and after the implementation of the real-time pricing mechanism in an embodiment of the present invention;

[0094] Figure 8 Schematic diagram of comprehensive electricity / heat / gas prices under IDR in an embodiment of the present invention;

[0095] Fig. 9 It is a diagram showing various demand response quantities of electricity / heat / gas loads and a comparison diagram before and after the response in an embodiment of the present invention;

[0096] Fig.10 is a comparison diagram of the electric, heat and gas scheduling results with and without considering IDR in an embodiment of the present invention;

[0097] Fig.11 It is a logic block diagram of a comprehensive energy system planning and scheduling device considering demand-side response in an embodiment of the present invention. DETAILED DESCRIPTION

[0098] In order to make the purpose, technical solution and advantages of the present invention clearer, the technical solution of the present invention will be clearly and completely described below in conjunction with the drawings in the embodiments of the present invention. The embodiments described in the present invention are only part of the embodiments of the present invention, not all of the embodiments. Based on the spirit of the present invention, other embodiments obtained by ordinary technicians in this field without creative work are all within the scope of protection of the present invention.

[0099] Embodiment 1:

[0100] Reference Figure 1 The embodiment of the present invention provides a configuration optimization method for an integrated energy system considering demand-side response, which specifically includes the following steps:

[0101] S1. Obtain historical load data of users in the target area, historical data of wind and solar resources, technical and economic parameters of various energy equipment, and time-of-use electricity price mechanism;

[0102] S2. Establish load models for price-based demand response, incentive-based demand response, and substitution-based demand response;

[0103] S3. Taking the lowest annualized operating cost of the integrated energy system over the entire life cycle and the lowest demand-side response cost as the first optimization goal, an initial planning and scheduling model considering price-based demand response and incentive-based demand response is established;

[0104] S4. Based on the data information obtained in step S1, combined with the operation constraints of the integrated energy system and the user satisfaction constraints, the initial planning and scheduling model is solved to obtain the load transfer and reduction after the price-based demand response and the incentive-based demand response, as well as the real-time pricing mechanism;

[0105] S5. Perform alternative demand response based on real-time pricing mechanism to obtain optimized price curve and load substitution of various energy sources;

[0106] S6. Based on the optimized price curve, the load substitution of various energy sources and the acquired data information, under the operating constraints, the planning and scheduling optimization model with the lowest annualized operating cost of the integrated energy system over the entire life cycle as the second optimization goal is solved to obtain the optimal capacity configuration results and operation scheduling plan of each energy equipment in the integrated energy system.

[0107] Specifically, the load history data in the data information acquired in step S1 includes: wind speed meteorological data on a typical day and historical load data of electricity, heat and gas on a typical day. The historical data of wind and solar resources includes: solar radiation intensity data on a typical day. Technical and economic parameters include: unit capacity investment cost of each energy equipment, unit capacity maintenance cost, carbon tax penalty, transferable load response cost, reducible load response cost, electricity demand price elasticity coefficient, gas demand price elasticity coefficient, effective calorific value conversion coefficient and time-of-use pricing. Each energy equipment includes: photovoltaic generator set, wind generator set, thermal generator set, battery, electrolyzer, hydrogen storage tank, carbon dioxide storage tank, carbon capture system, methane synthesis equipment, gas boiler, heat storage tank and / or electric heating boiler.

[0108] In this embodiment, the comprehensive demand response IDR is divided into price-based demand response, incentive-based demand response and substitution-based demand response according to the form of participation in demand response. These three IDR types correspond to transferable load (TL), reducible load (RL) and substitute load (SL) in IES respectively; among them, price-based demand response refers to guiding the user's energy consumption behavior by formulating time-of-use electricity prices to achieve the transfer of load peaks to load valleys; incentive-based demand response refers to the signing of relevant economic contracts between demand response suppliers and users with freely controllable loads, and the reduction of corresponding user loads when the power generated by the power grid side is insufficient, and economic compensation is given; substitution-based demand response refers to the mutual substitution of loads by users based on the comprehensive price of electricity, heat and natural gas, in accordance with the rule of replacing higher-priced energy with lower-priced energy.

[0109] Reference Figure 2 , is a schematic diagram of the principle of integrated demand response IDR. Price-based demand response realizes the transfer of homogeneous loads at multiple time nodes through price guidance; incentive-based demand response realizes the reduction of homogeneous loads at multiple time nodes through signing contracts; substitution-based demand response realizes the substitution of heterogeneous loads at a single time node by comparing the comprehensive prices of heterogeneous energy. Since substitution-based demand response will not change the user's energy satisfaction and does not generate response costs, its response priority is the highest; since price-based demand response is the user's active adjustment of their own energy behavior according to the real-time energy price, it will cause a certain loss of satisfaction and generate corresponding response costs, so its response priority is second; since incentive-based demand response requires users to passively reduce their own loads according to the contract, energy satisfaction will be greatly reduced, resulting in a large response cost, so its response priority is the lowest.

[0110] It is further explained that the implementation of the three types of integrated demand response IDR in the present invention, namely price-based demand response, incentive-based demand response and alternative demand response, is based on the IDR management system. As the hub of signal interaction, the interaction principle between the IDR management system and the integrated energy management system IES and load users is as follows: Figure 3 As shown, the structure of the integrated energy system IES is as follows Figure 4As shown. The specific process of interaction is as follows: First, IES obtains price information of electricity, heat and gas from the external energy market, conducts system planning based on energy prices to obtain power dispatch plans of electricity, heat and gas that match the user load, and sends the price information and dispatch plan to the IDR management system. Secondly, the IDR management system processes the price signal sent by the upper IES, compares the comprehensive electricity price\comprehensive heat price\comprehensive gas price horizontally, and compares the real-time price of the same energy vertically, and selects the appropriate demand response strategy based on the incentive contract signed with the user, and sends it to the user together with the dispatch plan. Finally, the smart sockets used by the lower-level users can automatically control the load reduction, substitution and transfer of various devices in the corresponding time period according to the demand response strategy given by the IDR management system. Compare the load after the user's response with the power dispatch plan, and feed back the deviation between the two to the IDR management system in the form of demand response quantity signals, which are provided to the IDR management system to calculate the demand response cost. The demand response cost and the load after the response are further fed back to the upper IES as economic and technical parameters and energy balance constraints to optimize the capacity configuration and dispatch plan of IES. The above process can achieve a balance of interests between IES and users.

[0111] In this embodiment, price-based demand response guides the user's energy consumption behavior by formulating time-of-use electricity prices or real-time electricity prices, so as to transfer the load peak to the load valley, thereby reducing the peak-to-valley difference of the load. As a widely used pricing mechanism, time-of-use electricity prices are characterized by prices being set in advance and not adjusted according to actual conditions. Time-of-use electricity prices divide intraday energy prices in a large time step, usually dividing a day into only three periods: peak, valley, and flat. In contrast, the price division step of the real-time pricing mechanism is usually one hour or less, so the marginal electricity price it describes can better match the price fluctuations over time; therefore, the present invention selects a real-time pricing mechanism to guide users to effectively adjust their inherent consumption patterns.

[0112] The impact of price-based demand response on user energy consumption behavior can be described by the price elasticity coefficient, which indicates the degree of influence of price changes on load changes, as shown in the following formula:

[0113]

[0114] Where d represents the energy demand of load users [KW], ρ represents the energy price [CNY], and d0 and ρ0 correspond to the initial states before the demand side responds.

[0115] The present invention optimizes the scheduling of IES at 24 hours before the day, with a time step of 1 hour, so the elasticity coefficient matrix can be expressed as:

[0116]

[0117] In the elasticity coefficient matrix in the formula, E(t, t') represents the influence of the load variable at time t on the load at time t', that is, the self-elasticity coefficient at that moment. The diagonal elements are called self-elasticity coefficients, which represent the influence of the price at a certain moment on the load at this moment; the non-diagonal elements are called mutual elasticity coefficients, which represent the influence of the price at a certain moment on the load at other moments.

[0118] The energy consumption behavior of load users at time t responds to the change in electricity price at time t' in two ways:

[0119] (1) For some equipment that can only change the load by starting and stopping in a fixed period, load time shifting cannot be performed; this load is only sensitive to the price in a fixed period, so it is called a self-elastic response. Since the increase / decrease of energy prices in a fixed period will cause this type of load to decrease / increase in that period, the corresponding elastic coefficient is usually negative, that is, E(t,t')≤0, and is called the self-elastic coefficient (corresponding to the condition of t=t').

[0120] (2) For some equipment whose working hours can be transferred from the peak period of energy price to the trough period of energy price, they are sensitive to the prices of multiple periods, so it is called cross-elastic response. Since the increase of energy price in a certain period guides the load to the trough period of energy price, it causes the increase of load in the trough period of energy price. Therefore, the corresponding elastic coefficient is usually positive, that is, E(t,t')>0, and it is called the mutual elastic coefficient (corresponding to the condition of t≠t').

[0121] Similar to the derivation method of the single time node response model, the expression of the user load response to the energy price change under multiple time nodes is as follows, that is, the expression of the transferable load model of the price-based demand response established in step S2 is as follows:

[0122]

[0123] Wherein, d(t) represents the load after participating in demand response at time t; d0(t) represents the basic load before participating in demand response at time t; E(t, t') represents the influence of the load variable at time t on the load at time t', that is, the self-elasticity coefficient at time t; ρ(t) represents the energy price at time t; ρ0(t') represents the initial energy price before response at time t'.

[0124] In this embodiment, the incentive-based demand response is mainly implemented by demand response providers and users with freely controllable loads through signing contracts; unlike price-based demand response, which transfers a certain load at the time level, the incentive-based demand response only reduces user loads during specific time periods (load peak or emergency situations), and this load is called reducible load (RL); according to the definition of incentive-based demand response, the electricity, heat, and gas loads of the present invention are all treated as reducible loads for demand response.

[0125] As an embodiment of the present invention, the load model of the incentive-based demand response established in step S2 includes curtailable loads; curtailable loads are divided into directly interrupted loads and partially curtailed loads;

[0126] (1) When IES encounters an emergency, according to the contract, the user needs to directly interrupt its own load according to the instructions. The direct interruption load model expression is as follows:

[0127]

[0128] In the formula, and They represent the user load and the direct interruption amount of load after the direct interruption of the i-th energy source at time t respectively; Direct interruption of load Initial load d i,0 (t) maximum ratio; Δd i,0 (t) represents the initial direct interruption load at time t; e, h and g represent electric energy, thermal energy and natural gas respectively;

[0129] (2) In addition to passively interrupting loads according to contract requirements, subsidies for users who actively reduce energy consumption during peak load periods can be used as another incentive for load reduction, that is, guiding users to actively reduce part of their loads through high energy prices at a certain moment and providing economic compensation for them. This response method reduces the load at a certain moment based on the price at that moment, and does not affect the load at other moments. Therefore, the modeling method is similar to the self-elastic response method of the multi-time node response model. The elasticity coefficient matrix of partial load reduction can be expressed as follows:

[0130]

[0131] In the formula, E PRL (t,t) represents the self-elastic coefficient of the load to the reducible load at time t; E t,t The elastic modulus matrix representing the reducible load.

[0132] Furthermore, similar to the expression of the multi-time node response model, the mathematical model of partial load reduction is as follows:

[0133]

[0134] In the formula, The user represents the load after the user partially reduces the i-th energy load at time t; Partial load reduction Initial load d i,0 (t) maximum ratio; represents the curtailable load factor at time t; ρ i (t) represents the price of the i-th energy after participating in the demand-side response at time t; ρ i,0 (t) represents the energy price after the i-th energy participates in the demand-side response at time t.

[0135] As an embodiment of the present invention, the alternative demand response model established in step S2 includes:

[0136] Due to the existence of multi-energy coupling equipment such as power-to-gas units, gas boilers, and electric boilers, IES can achieve mutual substitution of electric-heat load, electric-gas load, and gas-heat load at a certain time point. For the integrated energy system, different types of energy have different calorific values, and calorific value conversion is required when each load is replaced through coupling equipment; for users, by comparing the comprehensive prices of different energy sources, they can choose the most economical load at a certain moment to meet their own energy needs. The comprehensive price is based on the electricity price, and the conversion between the comprehensive heat price and the comprehensive gas price is carried out based on the principle of calorific value equivalence, so as to serve as the economic criterion for users to replace loads, as shown in the following formula:

[0137]

[0138] Where P i * and are the comprehensive price of the i-th energy [CNY] and the market electricity price [CNY], H i and H e are the calorific value [KW] of the i-th energy and electric energy [KW] respectively; K i is the premium coefficient of the i-th energy source, R i is the value-added tax rate for the i-th energy.

[0139] As an embodiment of the present invention, the substitution type demand response based on the real-time pricing mechanism in step S5 includes: the user uses the comprehensive price of electricity, heat and gas as a criterion to perform mutual substitution between loads, and this type of load is called a replaceable load (SL). The judgment logic of the substitution type demand response is implemented through the following six situations. ijis the substitution state between the i-th energy source and the j-th energy source (i, j∈e,h,g and i≠j). When the i-th energy source is replaced by the j-th energy source, θ ij is -1; otherwise, μ ij is 1. ij . is the effective calorific value conversion coefficient of the i-th energy source to the j-th energy source, and μ ij >0.

[0140] Specifically, the comprehensive prices of electricity, heat and natural gas are compared based on the real-time pricing mechanism; and the various types of loads are substituted for each other according to the following substitution rules based on the comparison results:

[0141] Rule 1: When the comprehensive electricity price is greater than the comprehensive heat price and the comprehensive heat price is greater than the comprehensive gas price, the electricity load is replaced by the gas load and the heat load, and the heat load is replaced by the gas load; the load model of the replacement demand response under this rule is as follows:

[0142]

[0143]

[0144] In the formula, and They are comprehensive electricity price, comprehensive heat price and comprehensive gas price; It represents the electric load change caused by the demand-side response at time t; represents the gas load change caused by the demand-side response at time t; represents the heat load changed by the demand-side response at time t; represents the electric load replaced by the gas load at time t; represents the electrical load replaced by the thermal load at time t; represents the heat load replaced by gas load at time t; μ eg and θ eg They represent the calorific value conversion coefficient and logic control variable of the electric load replaced by the gas load; μ hg and θ hg They represent the calorific value conversion coefficient and logic control variable of the heat load replaced by the gas load; μ eh and θ eh They represent the calorific value conversion coefficient of the electrical load replaced by the thermal load and the logical control variable respectively; among which, θ hg ,θ eg and θ hg The average value is -1; LHV NG Indicates the lower heating value of natural gas.

[0145] Rule 2: When the comprehensive electricity price is greater than the comprehensive gas price and the comprehensive gas price is greater than the comprehensive heat price, the electricity load is replaced by the heat load and the gas load, and the gas load is replaced by the heat load; the load model of the replacement demand response under this rule is as follows:

[0146]

[0147]

[0148] In the formula, and They are comprehensive electricity price, comprehensive heat price and comprehensive gas price; It represents the electric load change caused by the demand-side response at time t; represents the gas load change caused by the demand-side response at time t; represents the heat load changed by the demand-side response at time t; represents the electric load replaced by the gas load at time t; represents the electrical load replaced by the thermal load at time t; represents the gas load replaced by the heat load at time t; μ eg and θ eg They represent the calorific value conversion coefficient and logic control variable of the electric load replaced by the gas load; μ gh and θ gh They represent the calorific value conversion coefficient of the gas load replaced by the heat load and the logical control variable; μ eh and θ eh They represent the calorific value conversion coefficient of the electrical load replaced by the thermal load and the logical control variable respectively; among which, θ eh and θ eg The average value is -1, θ gh The value of LHV is 1; NG Indicates the lower heating value of natural gas.

[0149] Rule 3: When the comprehensive heat price is greater than the comprehensive electricity price and the comprehensive electricity price is greater than the comprehensive gas price, the heat load is replaced by the electricity load and the gas load, and the electricity load is replaced by the gas load; the load model of the substitution demand response under this rule is as follows:

[0150]

[0151]

[0152] In the formula, and They are comprehensive electricity price, comprehensive heat price and comprehensive gas price; It represents the electric load change caused by the demand-side response at time t; represents the gas load change caused by the demand-side response at time t; represents the heat load changed by the demand-side response at time t; represents the electric load replaced by the gas load at time t; represents the heat load replaced by the electric load at time t; represents the heat load replaced by gas load at time t; μ eg and θ eg They represent the calorific value conversion coefficient and logic control variable of the electric load replaced by the gas load; μ hg and θ hg They represent the calorific value conversion coefficient and logic control variable of the heat load replaced by the gas load; μ he and θ he They represent the calorific value conversion coefficient and logical control variable of the heat load replaced by the electric load; among them, θ hg and θ eg The average value is -1, θ he The value of LHV is 1; NG Indicates the lower heating value of natural gas.

[0153] Rule 4: When the comprehensive heat price is greater than the comprehensive gas price and the comprehensive gas price is greater than the comprehensive electricity price, the heat load is replaced by the gas load and the electricity load, and the gas load is replaced by the electricity load; the load model of the substitution demand response under this rule is as follows:

[0154]

[0155]

[0156] In the formula, and They are comprehensive electricity price, comprehensive heat price and comprehensive gas price; It represents the electric load change caused by the demand-side response at time t; represents the gas load change caused by the demand-side response at time t; represents the heat load changed by the demand-side response at time t; represents the gas load replaced by the electric load at time t; represents the heat load replaced by the electric load at time t; represents the heat load replaced by gas load at time t; μ ge and θ ge They represent the heat value conversion coefficient and logic control variable of the gas load replaced by the electric load; μ hg and θ hg They represent the calorific value conversion coefficient and logic control variable of the heat load replaced by the gas load; μ he and θ he They represent the calorific value conversion coefficient and logical control variable of the heat load replaced by the electric load; among them, θ he and θ heThe average value is 1, θ hg The value of LHV is -1; NG Indicates the lower heating value of natural gas.

[0157] Rule 5: When the comprehensive gas price is greater than the comprehensive electricity price and the comprehensive electricity price is greater than the comprehensive heat price, the gas load is replaced by the electricity load and the heat load, and the electricity load is replaced by the heat load; the load model of the replacement demand response under this rule is as follows:

[0158]

[0159]

[0160] In the formula, and They are comprehensive electricity price, comprehensive heat price and comprehensive gas price; It represents the electric load change caused by the demand-side response at time t; represents the gas load change caused by the demand-side response at time t; represents the heat load changed by the demand-side response at time t; represents the gas load replaced by the electric load at time t; represents the electrical load replaced by the thermal load at time t; represents the gas load replaced by the heat load at time t; μ ge and θ ge They represent the heat value conversion coefficient and logic control variable of the gas load replaced by the electric load; μ gh and θ gh They represent the calorific value conversion coefficient of the gas load replaced by the heat load and the logical control variable; μ eh and θ eh They represent the calorific value conversion coefficient of the electrical load replaced by the thermal load and the logical control variable respectively; among which, θ ge and θ gh The average value is 1, θ eh The value of LHV is -1; NG Indicates the lower heating value of natural gas.

[0161] Rule 6: When the comprehensive gas price is greater than the comprehensive heat price and the comprehensive heat price is greater than the comprehensive electricity price, the gas load is replaced by the heat load and the electricity load, and the heat load is replaced by the electricity load; the load model of the replacement demand response under this rule is as follows:

[0162]

[0163]

[0164] In the formula, and They are comprehensive electricity price, comprehensive heat price and comprehensive gas price; It represents the electric load change caused by the demand-side response at time t; represents the gas load change caused by the demand-side response at time t; represents the heat load changed by the demand-side response at time t; represents the gas load replaced by the electric load at time t; represents the heat load replaced by the electric load at time t; represents the gas load replaced by the heat load at time t; μ ge and θ ge They represent the heat value conversion coefficient and logic control variable of the gas load replaced by the electric load; μ gh and θ gh They represent the calorific value conversion coefficient of the gas load replaced by the heat load and the logical control variable; μ he and θ he They represent the calorific value conversion coefficient and logical control variable of the heat load replaced by the electric load; among them, θ ge ,θ he and θ gh The average value is 1; LHV NG Indicates the lower heating value of natural gas.

[0165] In addition, the load change and load substitution of the alternative demand response model should also satisfy the constraints shown in the following formula:

[0166]

[0167] Where: is the load change Initial load d i,0 The maximum ratio of is the upper limit of load substitution.

[0168] The present invention comprehensively considers price-based, reduction-based and substitution-based demand responses, and can establish a comprehensive demand response IDR model for users, as shown in the following formula:

[0169]

[0170] Where: The load after IDR for the user [KW]; is the total load reduction that can be reduced [KW]; to ensure that the final load after the response does not reverse the peak and valley, the upper and lower limits of the load after IDR should be set When i represents electricity and natural gas, it satisfies [0.6d i,0 ,1.4d i,0 ]; when i represents thermal energy, it satisfies [0.7d i,0 ,1.3d i,0 ].

[0171] As an embodiment of the present invention, the objective function in step S3 with the lowest annualized operating cost of the integrated energy system over the entire life cycle and the lowest demand-side response cost as the first optimization goal is as follows:

[0172] F1=min f static +Zf IDR

[0173] Where F1 is the total cost of the integrated energy system considering price-based demand response and incentive-based demand response; Z is the number of days in the whole year for calculation; f IDR The cost of demand response on a typical day; static is the annualized operating cost of the integrated energy system over its entire life cycle; C INV is the system investment cost, among which the cost of replaceable loads is not taken into account due to their response characteristics.

[0174] In this example, the cost of demand response in a typical day is IDR The calculation formula is as follows:

[0175]

[0176] In the formula, and are the unit response cost of the i-th energy source at time t for the transferable load, directly interrupted load and partially reduced load respectively; and They respectively represent the amount of transferable load, directly interrupted load and partially reduced load of the i-th energy participating in the demand-side response at time t; e, h and g represent electricity, thermal energy and natural gas, respectively.

[0177] As an embodiment of the present invention, the objective function for the second optimization objective of minimizing the annualized operating cost of the integrated energy system over the entire life cycle in step S6 is as follows:

[0178] F2=min f static

[0179] In this embodiment, the annualized operating cost of the integrated energy system over its entire life cycle is static The calculation formula is as follows:

[0180] f static =C INV +C OM +C RT +C CE

[0181] In the formula, C OM is the system operation and maintenance cost; C RT is the resource transaction cost; C CEis the cost of carbon dioxide emissions; it is worth noting that the economic performance evaluation index introduces the cost of carbon dioxide emissions, which can promote carbon emission reduction of the system while ensuring the economy of IES.

[0182] System investment is often based on a long-term perspective, usually decades, while system operation and maintenance is carried out in a shorter period of time, such as one year. In order to make the investment cost and operation and maintenance cost comparable, it is necessary to consider the time value of money and express the investment cost in the form of annual value, as shown in the following formula:

[0183]

[0184] In the formula, is the unit capacity investment cost of equipment j [CNY / kW]; CRF is the capital recovery factor; r is the annual interest rate, which is 10% in this embodiment; n is the service life of the equipment, which is 20 years except for the battery and heat storage tank, which have a service life of 10 years; Y is the investment cost coefficient for replacing the equipment during the whole life cycle of the system. The present invention sets the whole life cycle of the system to 20 years, so only the replacement of the battery and the heat storage tank is considered; j,i is a 0-1 variable that determines whether equipment j has reached the end of its service life in the kth year.

[0185] The system's operation and maintenance costs depend on the operation of each device. The more power / energy consumption a device has and the longer it runs, the higher the operation and maintenance costs it incurs. The operation and maintenance costs can be calculated in a simplified form using the following formula.

[0186]

[0187] In the formula, is the unit operation and maintenance cost of equipment j [CNY / kW].

[0188] Resource transaction costs are the costs of purchasing coal required for the operation of thermal power units and the costs incurred when IES purchases energy from external source networks when its internal equipment cannot meet the energy demand, as shown in the following formula:

[0189]

[0190] In the formula, C Coal , C PG , C HG and C QG They are the cost of purchasing coal [CNY / kg], the cost of purchasing electricity from the power grid [CNY / kW], the cost of purchasing heat from the heat grid [CNY / kW], and the cost of purchasing gas from the natural gas grid [CNY / Nm 3 ]; F Coal,t 、F PG,t 、F HG,t and FQG,t They are coal price [CNY / kg], electricity price [CNY / kW], thermal energy price [CNY / kW] and natural gas price [CNY / Nm 3 ].

[0191] The cost of CO2 emissions is related to the portion of captured CO2 that is dissipated instead of being stored and utilized, as shown in the following equation:

[0192]

[0193] In the formula, Cost of carbon tax penalty [CNY / Nm 3 ].

[0194] In this embodiment, a user energy satisfaction (UNS) evaluation index is constructed. Generally speaking, the less the user changes his energy usage behavior, the higher his energy satisfaction is. Therefore, the energy satisfaction evaluation index should be kept at a high level. The expression of the user satisfaction constraint in step S4 is as follows:

[0195]

[0196] In the formula, Energy satisfaction index for users UNS The minimum threshold, Δd i,0 (t) represents the load of the i-th energy source before it participates in the demand-side response at time t; represents the load of the i-th energy participating in the demand-side response at time t; e, h and g represent electricity, thermal energy and natural gas, respectively.

[0197] Furthermore, in the embodiment of the present invention, the operating constraints of the integrated energy system include: upper and lower output constraints and ramp constraints of thermal power units, upper and lower power constraints of carbon capture systems, upper and lower power constraints of electrolyzers and ramp constraints, upper and lower output constraints of methane synthesis equipment and ramp constraints, gas storage capacity and inlet and outlet gas constraints of hydrogen storage equipment, gas storage capacity and inlet and outlet gas constraints of carbon dioxide storage equipment, equipment safe operation constraints, system energy balance constraints and material conservation constraints.

[0198] (1) The upper and lower output limits and ramp constraints of thermal power units are expressed as:

[0199]

[0200]

[0201] In the formula, is the rated power of the thermal power unit [KW]; P PGU,t and P PGU,t-1are the outputs of thermal power units at time t and time t-1 [KW] respectively;

[0202] (2) The upper and lower limits of the carbon capture system power are expressed as:

[0203]

[0204] In the formula, is the rated power of the carbon capture system [KW]; P CCS,t is the power consumption of the carbon capture system at time t [KW];

[0205] (3) The upper and lower limits of the electrolytic cell power and the ramp constraints are expressed as:

[0206]

[0207]

[0208] In the formula, is the rated capacity of the electrolytic cell [KW]; P EL,t and P EL,t-1 are the electric energy consumed by the electrolytic cell at time t and time t-1 [KW];

[0209] (4) The upper and lower output limits and ramp constraints of the methane synthesis equipment are expressed as:

[0210]

[0211]

[0212] In the formula, is the rated capacity of the methane synthesis equipment [KW]; and are the electric energy [KW] consumed by the methanogenation equipment at time t and time t-1 respectively.

[0213] (5) The gas storage capacity and inlet and outlet gas constraints of hydrogen storage equipment are expressed as:

[0214]

[0215] In the formula, and are the volume of hydrogen in the hydrogen storage tank at the current moment and the previous moment [Nm 3 ]; and are the air intake and steam extraction in the hydrogen storage tank at the last moment [Nm 3 ];

[0216] is a 0-1 variable that expresses the working state of the hydrogen storage tank, 1 represents that the hydrogen storage tank is in the intake state, and 0 represents that the hydrogen storage tank is in the exhaust state;

[0217] (6) The gas storage capacity and inlet and outlet gas constraints of the carbon dioxide storage equipment are expressed as:

[0218]

[0219] In the formula, and are the volume of carbon dioxide in the carbon storage tank at the current moment and the previous moment [Nm 3 ]; and are respectively the air intake and air extraction in the carbon storage tank at the last moment [Nm 3 ]; A 0-1 variable that expresses the working state of the carbon tank. 1 represents that the carbon tank is in the intake state, and 0 represents that the carbon tank is in the extraction state.

[0220] (7) Equipment safe operation constraints: The safe operation boundary of equipment usually depends on the size of its equipment capacity. The larger the equipment capacity, the wider the adjustable output range. However, considering factors such as equipment footprint and investment cost, the larger the equipment capacity, the better. Its capacity configuration size should also be within a reasonable range, as shown in the following formula:

[0221]

[0222] In the formula, ω j , and are the equipment capacity and its upper and lower limits respectively; since the capacity of the thermal power unit in the present invention is known and is 300MW, there is no need to configure it, so j represents any equipment in the IES system except the thermal power unit. Among them, the relationship between the safe operation boundary of different equipment and the equipment capacity can be described by the following formula:

[0223]

[0224] In the formula, is the power capacity factor; Y j,t is a 0-1 variable for controlling the start and stop of the equipment. When its value is 0, it means that the equipment is in the off state, and when its value is 1, it means that the equipment is in the on state. The present invention only considers gas boilers and electric boilers to participate in the start and stop, while Y of other equipment j,t Always takes 1; and are the upper and lower limit coefficients of the equipment respectively. Take 1, Take 0.3; and are the upper and lower limit coefficients of the equipment climbing power, respectively, and both are 0.3 in this embodiment; The maximum access depth of the storage device.

[0225] (8) System energy balance constraint: The IES system contains three forms of energy: electricity, heat, and gas. Therefore, the energy balance constraint can be divided into electricity balance constraint, heat balance constraint, and natural gas balance constraint, as shown in the following formula:

[0226]

[0227] In the formula, and are the power purchased and sold by IES from the external grid [kW] respectively; and are the maximum and minimum values ​​of the interaction between IES and grid power [kW], respectively; and are the heat purchase and sale power [kW] of IES from external heat network, respectively; and are the maximum and minimum values ​​of the interaction between IES and the heating network power [kW], respectively; and are the gas purchase and sale flows of IEPU from the external gas network [Nm 3 ]; and are the maximum and minimum values ​​of the interaction between IEPU and gas grid flow [Nm 3 ]; P load,t , H load,t and Q load,t are the electric load, thermal load and gas load [kW] on the IES demand side respectively.

[0228] (9) Material conservation constraints: IES involves the synthesis of methane, a chemical product. Depending on the different raw materials for methane synthesis, the system material conservation constraints can be divided into hydrogen conservation and carbon dioxide conservation, as shown in the formula:

[0229]

[0230] It should be noted that, when solving the initial planning and scheduling model in step S4 of this embodiment, historical data of load, wind speed, and light radiation as well as technical and economic parameters of the system are input, price-type demand response is performed based on the time-of-use pricing mechanism, load data and wind and solar power generation data under random scenarios are input, and the IES steady-state model is constructed in the MATLAB environment according to the energy conversion relationship between the devices, a mixed integer linear programming (MILP) is established, and the CPLEX solver is called to solve the load transfer and reduction after the price-type demand response and the incentive-type demand response, and the optimized real-time pricing mechanism is obtained; secondly, when solving the planning and scheduling optimization model in step S6 of this embodiment, a substitution-type demand response is performed based on the real-time pricing mechanism to obtain the optimized price curve and load substitution; finally, the final optimized load curve is obtained based on the initial load and load transfer, reduction and substitution, and the optimal capacity configuration result and operation scheduling plan are output at the same time.

[0231] Furthermore, the steady-state models of the equipment in IES are established, which are:

[0232] Renewable Energy Equipment Model

[0233] (1) Photovoltaic equipment model (PV)

[0234] Photovoltaic equipment outputs electrical power by absorbing light radiation. Its actual output (P PV,t ) is subject to its own rated power (P PV,r ) and light radiation level, which can be expressed by the following formula:

[0235]

[0236] In the formula, G t is the total horizontal radiation value of light at time t [kW / m 2 ], G ref is the standard reference value of total horizontal radiation. In this embodiment, G ref 1000W / m 2 .

[0237] Limited by the absorption capacity of IES, the real-time output of photovoltaic power PV,t Actual Utilized Power and abandoned optical power As shown below:

[0238] (2) Wind turbine model (WT)

[0239] Wind turbine equipment can realize the conversion of wind energy into mechanical energy and then into electrical energy. Its real-time output size (P WT,t ) and its own rated power (PWT,r ) is closely related to wind speed, which can be expressed by the following formula:

[0240]

[0241] In the formula, v t is the wind speed value at time t [m / s], v r In order to make the fan reach the rated wind speed [m / s] for the best output, v ci and v co They are the cut-in wind speed that starts the fan output and the cut-out wind speed that stops the fan output [m / s].

[0242] Similar to photovoltaics, the real-time output of wind turbines P WT,t It can be divided into the part consumed by IES, that is, the actual power utilization and wind power curtailment As shown below:

[0243] (3) Energy conversion equipment model: Energy conversion equipment can realize the mutual coupling among electricity, heat and gas, which is conducive to the cascade utilization and complementary assistance among energy sources, and improves the stability of IES energy supply through the mutual conversion among energy sources.

[0244] (4) Power generation unit model (PGU)

[0245] As the core equipment of coal-fired power plants, thermal power units are controllable power sources that ensure that IES can maintain stable energy supply when renewable energy fluctuates randomly. They are used to meet the basic load of the system and assist in peak load regulation with renewable energy equipment. Thermal power units consume fuel coal to supply electricity, and the waste heat they generate can be used to meet part of the heat load demand. This process can be described by the following formula:

[0246]

[0247] Where P PGU,t , and are the electric power of the thermal power unit at time t and its upper and lower limits respectively;

[0248] and are the upper and lower limits of the thermal power unit climbing power respectively; H PGU,t is the waste heat generated by the thermal power unit due to power generation at time t; is the power-to-heat efficiency of the thermal power unit, and is respectively related to the heat recovery efficiency Electrical efficiency and power loss coefficient Related; A is the amount of coal consumed by the thermal power unit to generate electricity at time t CtP,t The power supply coal consumption of thermal power units will change with the fluctuation of their electric power. The dynamic relationship between the two can be expressed by the following formula:

[0249]

[0250] In the formula, a CtP,t is the specific power supply coal consumption at time t, A CtP,r b is the reference value of coal consumption for power supply under rated conditions, and 0.31 kg / kW is selected in this embodiment; b PGU,t is the specific electrical power at time t, P PGU,r is the rated capacity of the thermal power unit.

[0251] (5) Gas boiler model (gas boiler, GB)

[0252] Gas boilers generate heat by consuming natural gas, thus realizing the coupling of the heat network and the gas network. The energy conversion process can be expressed as:

[0253]

[0254] In the formula, H GB,t , and The thermal power and upper and lower limits of the gas boiler at time t respectively;

[0255] and They are the upper and lower limits of the gas boiler's ramp power respectively; is the amount of natural gas consumed by the gas boiler at time t; LHV NG is the low calorific value of natural gas, which is 9.69 kWh / m 3 ; is the thermal efficiency of the gas boiler.

[0256] (6) Electricity boiler model

[0257] Electric boiler is a common heating equipment that converts electrical energy into thermal energy. It can realize the coupling of power grid and gas grid. Its energy conversion process can be expressed as:

[0258]

[0259] In the formula, H EB,t , and are the output thermal power of the electric boiler at time t and its upper and lower limits respectively; and are the upper and lower limits of the electric boiler climbing power respectively; PEB,t is the input power of the electric boiler at time t; It is the electricity-to-heat efficiency of the electric boiler.

[0260] (7) Carbon capture system (CCS) model

[0261] Carbon capture technology is mainly divided into pre-combustion capture technology, oxygen-enriched combustion capture technology and post-combustion capture technology. The present invention selects the more widely used post-combustion capture technology: first, the absorption tower in the carbon capture equipment captures the flue gas discharged by the thermal power unit; then it is pumped to the stripping tower, and the carbon dioxide with higher purity is separated in the stripping tower; finally, the separated carbon dioxide is stored and used for the subsequent power-to-gas synthesis of methane. The process of carbon capture equipment capturing carbon dioxide can be described by the following formula:

[0262]

[0263] In the formula, is the amount of carbon dioxide in the flue gas of the thermal power unit, which is determined by the power P of the thermal power unit. PGU,t and carbon emission intensity e PGU Decide; and are the amount of carbon dioxide captured by the carbon capture equipment, the amount of carbon dioxide actually stored and subsequently utilized, and the amount of carbon dioxide dissipated without being stored and utilized; η CCS is the capture efficiency of the carbon capture equipment; P CCS,t and are the power consumption of the carbon capture equipment and the power consumption coefficient per unit carbon capture amount; and They are the upper and lower limits of power consumption of carbon capture equipment respectively.

[0264] (8) Power-to-gas unit model

[0265] The power-to-gas unit includes an electrolyzer (EL) and a methane synthesis unit (MU). The electrolyzer mainly uses the electricity generated by photovoltaics and wind turbines to produce hydrogen, and reacts with the carbon dioxide captured by the carbon capture device in the methane synthesis device to produce green fuel methane on a large scale. The process is shown in the following formula: CO2+4H2→CH4+2H2OΔ r H 0 =-165.0kJ / mol. Among them, the power-to-gas unit not only absorbs a large amount of renewable energy through the above process, avoiding the negative impact of wind and solar fluctuations on the stable operation of IES, but also converts renewable energy into methane, a chemical product that is easy to transport, which is conducive to the cross-regional transmission and distribution of energy, and makes IES more feasible under the policy background of carbon emission reduction.

[0266] The process of electrolyzing water to produce hydrogen by consuming electrical energy can be described by the following formula:

[0267]

[0268] Where P EL,t , and are the power consumption of the electrolytic cell at time t and its upper and lower limits;

[0269] and They are the upper and lower limits of the electrolyzer climbing power respectively; The amount of hydrogen produced by electrolysis of water; is the power consumption coefficient per unit hydrogen production.

[0270] The carbon dioxide and hydrogen on the input side of the methane synthesis equipment achieve material conservation with the methane on the output side. Since the methane synthesis reaction is an exothermic reaction, the energy consumption of the process is low. The relationship between its energy consumption and materials is shown in the following formula:

[0271]

[0272] Where P MU,t , and are the power consumption of the methane synthesis equipment at time t and its upper and lower limits; and They are the upper and lower limits of the slope power of the methane synthesis equipment respectively; and They are the amount of carbon dioxide, hydrogen and methane involved in the methane synthesis reaction, and the reaction ratio of the three is 1:4:1; is the power consumption coefficient per unit methane production.

[0273] (9) Battery model (battery, BT)

[0274] Since both renewable electricity and electricity load are uncertain, during periods when the two are difficult to match, batteries are used as an auxiliary means to make up for the shortfall in electricity demand or absorb excess electricity output. The auxiliary regulation process of batteries is also applicable to other power-consuming equipment such as electrolyzers. The charging and discharging behavior of batteries can be described by the following formula:

[0275]

[0276]

[0277]

[0278]

[0279] Where P BT,t , and are the battery capacity at time t and its upper and lower limits; P BT,r is the rated power of the battery; σ BT is the self-loss coefficient of the battery; and They are real-time charge and discharge amounts; and are charge and discharge efficiency; BT,t A 0-1 variable that controls the charging and discharging behaviors so that they cannot occur simultaneously.

[0280] (10) Heat storage tank model (heat shortage, HS)

[0281] The heat storage tank is used to adjust the heat charge and discharge when the heat supply and demand are unbalanced, so as to make the thermal power return to balance, and it also promotes the waste heat recovery of the thermal power unit. The mathematical model expression of the heat storage tank is similar to that of the battery, as shown below:

[0282]

[0283]

[0284]

[0285]

[0286] In the formula, H HS,t , and are the heat storage capacity of the heat storage tank at time t and its upper and lower limits; H HS,r is the rated thermal power of the heat storage tank; HS is the self-loss coefficient of the heat storage tank; and They are real-time charging and releasing of heat; and are respectively the charging and discharging heat efficiency; HS,t A 0-1 variable to control the heat charging and discharging behaviors which cannot occur simultaneously.

[0287] (11) Hydrogen shortage model (HYS)

[0288] The hydrogen storage tank is used to process the hydrogen produced by renewable energy electrolysis and used to store the surplus hydrogen after methane synthesis, and release hydrogen for methane synthesis during the period of renewable resource scarcity to reduce the energy consumption of the electrolyzer. This paper assumes that the hydrogen storage tank has good sealing performance and ignores the loss of gas during the filling and discharging process. Therefore, the self-loss coefficient is considered to be 0 and the filling and discharging efficiency is 1. The specific process is shown in the following formula:

[0289]

[0290]

[0291]

[0292]

[0293] In the formula, and are the hydrogen storage capacity of the hydrogen storage tank at time t and its upper and lower limits respectively; is the rated hydrogen flow rate of the hydrogen storage tank; and They are the real-time hydrogen charging and discharging amounts; A 0-1 variable to control the hydrogen charging and discharging behaviors so that they cannot occur simultaneously.

[0294] (12) Carbon dioxide shortage model (CDS)

[0295] The carbon dioxide storage tank is used to temporarily store the carbon dioxide captured and separated by the carbon capture equipment, and to take it out during the methane synthesis and store the surplus after synthesis. The assumed conditions and gas filling and discharge behavior of the carbon dioxide storage tank are similar to those of the hydrogen storage tank, which can be expressed by the following formula:

[0296]

[0297]

[0298]

[0299]

[0300] In the formula, and are the carbon storage capacity and its upper and lower limits of the carbon dioxide storage tank at time t; is the rated carbon dioxide flow rate of the carbon dioxide storage tank; and They are the real-time carbon dioxide charging and releasing amounts; A 0-1 variable to control the carbon dioxide charging and discharging behaviors so that they cannot occur simultaneously.

[0301] The following is a specific experimental example to verify the effectiveness of the integrated energy system planning and scheduling method considering demand-side response provided by an embodiment of the present invention; that is, a comparative experiment considering IDR (an integrated demand response combining price-based demand response, incentive-based demand response and alternative demand response) and not considering IDR.

[0302] In the experiment of this embodiment, the historical data of load, wind speed, and light radiation input in S1 are as follows: Figure 5 As shown, Figure 5 (a) shows the sunlight radiation and wind speed curves of a typical day. The reference values ​​of the two per unit values ​​are the maximum values ​​of their respective curves, which are 0.81 Lux and 19.67 m / s respectively. Figure 5 (b) shows the load curves of electricity, heat and gas on a typical day. The reference values ​​of the three per unit values ​​are also selected as their respective maximum values, which are 190.88MW, 168.03MW and 1679.54m3 respectively. Figure 7 As shown, electricity and natural gas are time-of-use prices, and heat is a fixed price. Tables 1 and 2 show the elasticity coefficients required for the price-based demand response model for electricity load and gas load, respectively. Table 3 shows the relevant technical and economic parameters of the IDR model. The real-time pricing mechanism takes a fixed ratio of 10% as an example to implement the time-of-use pricing mechanism. The demand response model based on the price elasticity matrix, the simulation results of the real-time pricing mechanism and the time-of-use pricing mechanism are shown in Figure 6 As shown in the figure, a response value greater than 0 represents load transfer in, and a response value less than 0 represents load transfer out. Figure 7 The electricity and gas price curves before and after the implementation of the real-time pricing mechanism were plotted.

[0303] Table 1 Price elasticity coefficient of electricity demand

[0304] Time valley flat peak valley -0.1 0.01 0.012 flat 0.01 -0.1 0.016 peak 0.012 0.016 -0.1

[0305] Table 2 Gas demand price elasticity coefficient

[0306] Time valley flat peak valley -0.2 0.02 0.025 flat 0.02 -0.2 0.03 peak 0.025 0.03 -0.2

[0307] Table 3. Related technical and economic parameters of IDR

[0308]

[0309]

[0310] Table 4 Comparison of IES capacity configuration results with and without considering IDR

[0311] Equipment capacity IDR not considered Consider IDR Relative error (%) Photovoltaic (MW) 120.86 76.39 -36.79 Wind turbine(MW) 168.71 149.76 -11.23 Electric boiler (MW) 73.51 57.74 -21.45 Gas boiler (MW) 13.29 6.73 -49.36 Carbon capture equipment (MW) 3.33 2.37 -28.83 Electrolyzer (MW) 33.85 28.56 -15.63 Methane synthesis equipment (MW) 0.67 0.56 -16.42 Storage battery (MW) 0.00 0.00 — Thermal storage tank (MW) 0.00 0.00 — <![CDATA[Hydrogen storage tank (m 3 )]]> 20000.00 20000.00 — <![CDATA[Carbon dioxide storage tank (m 3 )]]> 17616.71 11948.49 -32.18

[0312] Table 5 Comparison of IES economic indicators with and without considering IDR

[0313] <![CDATA[Cost item (×10 5 yuan)]]> IDR not considered Consider IDR Relative error (%) Investment cost 579.77 454.25 -21.65 Operation and maintenance costs 222.37 174.15 -21.68 Carbon emissions costs 2485.32 2393.27 -3.70 Fuel costs 1178.58 1122.81 -4.73 Energy purchase cost 55.99 8.85 -84.19 IDR Cost 0.00 207.71 — Total Cost 4522.03 4361.04 -3.56

[0314] Among them, alternative demand response is based on the comprehensive energy price; according to the equivalent calorific value principle, the comprehensive energy price can be calculated based on the real-time pricing mechanism. The results are as follows: Figure 8 Based on the above-obtained real-time energy price and comprehensive energy price, IDR is implemented for the multi-energy load in the boundary scenario. The multi-energy load response results are shown in Fig. 9 The CPLEX solver is called in the MATLAB programming environment to solve the MILP. The capacity configuration results and economic indicators of IES with and without IDR are listed in Table 4 and Table 5 respectively. The dispatch results of electricity, heat and gas are listed in Fig.10 .

[0315] As can be seen from Table 4, when IDR is considered, the capacity of each device in the system is reduced to a certain extent compared with when IDR is not considered. Among them, the photovoltaic capacity and gas boiler capacity have decreased significantly, by 36.79% and 49.36% respectively. This is because IDR has achieved the "peak shaving and valley filling" of electricity and gas loads, smoothed their load curves, and reduced the output upper limit of the power supply and gas supply equipment in the IEPU, so the capacity required for the configuration of electricity and gas related equipment has decreased. In addition, the occurrence of load substitution and load reduction has reduced the overall level of thermal load, which will lead to a reduction in the output of heating equipment, thereby reducing its configuration capacity.

[0316] As can be seen from Table 5, compared with the IEPU without considering IDR, the various costs of the IEPU after considering IDR have been reduced to a certain extent. Among them, the energy purchase cost has been reduced by 84.19%, which is the most significant effect. This is because IDR reduces the peak value of electricity and gas loads, and reduces the possibility of IEPU itself being unable to meet the load demand and purchasing energy from the outside at certain peak moments. It also shows that considering IDR can better ensure the self-sufficiency of IEPU. In addition, the reduction in system configuration capacity directly reduces the investment cost of IEPU, and indirectly reduces the operation and maintenance cost, carbon emission cost, fuel cost and energy purchase cost of IEPU. Although an IDR cost of 2.0771×107 yuan is introduced after considering IDR, the reduction of other costs has reduced the total system cost by 3.56%, indicating that the IEPU considering IDR is more economical.

[0317] Figure 6 (a) The response of China's power load based on the real-time pricing mechanism is significantly greater than that of the time-of-use pricing mechanism; Figure 6(b) The response of the gas load based on the real-time pricing mechanism is significantly greater than that of the time-of-use pricing mechanism in most periods (1:00-10:00 and 17:00-24:00), and the opposite is true only in a few periods (11:00-16:00). On the other hand, when only the impact of IDR is analyzed, the IDR model based on the boundary scenario can be solved using a deterministic optimization method that does not consider dynamic characteristics. The results show that the optimal cost of the system life cycle under the real-time pricing mechanism and the time-of-use pricing mechanism is 436.1 million yuan and 436.6 million yuan, respectively. It can be seen that compared with the real-time pricing mechanism, the time-of-use pricing mechanism will cause the economic efficiency of IEPU to decline. The above analysis shows that the real-time pricing mechanism can adjust the energy price in time according to the real-time supply and demand relationship of energy in IEPU, which further taps the response potential of users and has better economic efficiency.

[0318] Furthermore, the electricity and gas prices before and after the implementation of the real-time pricing mechanism are compared. Figure 7 As shown. It can be seen that the optimized real-time electricity and gas prices are updated faster than the initial prices. On the whole, the real-time pricing mechanism makes most peak prices higher, valley prices lower, and normal prices appropriately adjusted according to actual conditions. The real-time electricity price increased by an average of 27.60% during peak hours and decreased by an average of 18.86% during valley hours; the real-time gas price increased by an average of 30.55% during peak hours of 11:00-13:00 and 17:00-20:00, and decreased by an average of 40.51% during valley hours of 1:00-7:00. The above phenomena have greatly stimulated the enthusiasm and flexibility of user responses, which also explains why the demand response volume of electricity and gas load price type of the real-time pricing mechanism is greater than that of the time-of-use pricing mechanism.

[0319] Price-based demand response and incentive-based demand response with partial load reduction rely on the real-time price of energy, while substitution-based demand response is based on the comprehensive energy price. According to the formula of the calorific value equivalent principle, the comprehensive energy price can be calculated based on the real-time pricing mechanism. The result is as follows: Figure 8 shown.

[0320] Based on the real-time energy price and comprehensive energy price obtained above, IDR is implemented for the multi-energy load in the boundary scenario. The response results of the multi-energy load are as follows: Fig. 9 As shown. Fig. 9 It can be seen that, overall, the proportion of replaceable loads in electricity and gas loads is the highest, followed by transferable loads, while the proportion of curtailable loads is the lowest and can be ignored; the proportion of replaceable loads in thermal loads is higher than that of curtailable loads. Figure 1The implementation priorities of various demand responses are consistent. In addition, compared with before the response, the standard deviation of the electric load curve after the response decreased by 37.66%, the standard deviation of the gas load curve decreased by 13.98%, and the standard deviation of the heat load curve decreased by 10.27%, indicating that IDR is conducive to reducing load volatility.

[0321] contrast Fig.10 (a) and (d), after considering IDR, the proportion of wind turbine and photovoltaic output on the supply side of the integrated energy system increases, and the power fluctuation is smoother. On the one hand, IDR smoothes the electric load curve, which makes the output of renewable electricity also become stable accordingly. On the other hand, IDR from 5:00 to 7:00 increases the valley value of the electric load, and the increase in electric load demand has become the main reason for promoting the proportion of wind and solar output; however, during the peak period of 12:00-14:00 and the flat valley period of 15:00-18:00, although the output pressure of thermal power units is alleviated by reducing the electric load through IDR, the space for wind and solar power consumption is reduced. Therefore, selling electricity during these periods has become the main means to promote the consumption of wind and solar power. It is worth mentioning that the reduction in the output of thermal power units is conducive to reducing the carbon emissions and fuel consumption of the system, which explains the reason why the carbon emission cost and fuel cost of the integrated energy system are reduced when IDR is considered in Tables 4 and 5.

[0322] contrast Fig.10 (b) and (e), after considering IDR, the output of electric boilers and gas boilers on the supply side of the integrated energy system, as well as the external heat purchase power and heat sale power, are reduced to a certain extent. This is because IDR reduces the load level of the heat end, and the integrated energy system can meet most of the heat load demand by using the waste heat of thermal power without over-reliance on other heating equipment and external heat energy transactions. This process not only reduces the system operation and maintenance costs and energy purchase costs, but also improves the self-sufficiency of the integrated energy system.

[0323] contrast Fig.10 (c) and (f), after considering IDR, the overall gas consumption is reduced due to the reduction of the peak-to-valley difference of the gas load curve, and the reduction of the heating capacity of the gas boiler leads to a reduction in its gas consumption, which reduces the gas supply of the power-to-gas unit accordingly.

[0324] The beneficial effects of the present invention are as follows:

[0325] 1. The present invention optimizes the planning and scheduling of the integrated energy system by considering the comprehensive demand response IDR of price-based demand response, incentive-based demand response and alternative demand response. By utilizing the complementary advantages of price-based demand response and incentive-based demand response, it can improve the enthusiasm of users without reducing the energy comfort of users, thereby achieving collaborative optimization with minimal psychological effects on users and maximum benefits for suppliers, and carrying out alternative demand response by replacing high-priced energy with low-priced energy. Under the premise of not changing the supply-demand relationship, it achieves a balance of interests between the supply and demand sides, thereby ensuring the economic and safe operation of the power system.

[0326] 2. In the integrated demand response IDR, different from the load response based on the time-of-use pricing mechanism, the present invention can timely adjust the energy price according to the real-time supply and demand relationship of the integrated energy system IES by adopting a real-time pricing mechanism, which further taps the user's response potential and has better economic efficiency; the optimized real-time electricity and gas prices are updated faster than the initial prices. Overall, the real-time pricing mechanism makes most peak prices higher, valley prices lower, and normal prices appropriately adjusted according to actual conditions, which stimulates the enthusiasm and flexibility of users to participate in demand-side response to a greater extent.

[0327] 3. After considering the comprehensive demand-side response IDR, the present invention shows different degrees of "peak shaving and valley filling" phenomenon in electricity, heat and gas loads, which greatly reduces the volatility of the load side. Compared with the comprehensive energy system without considering IDR, the energy purchase cost after considering IDR is significantly reduced, and the investment cost of equipment is also reduced, thereby indirectly reducing the operation and maintenance cost and carbon emission cost of the equipment, and improving the overall economic benefits.

[0328] 4. The integration of the power-to-gas unit in the integrated system combines the carbon dioxide emitted by the thermal power units with the hydrogen obtained by electrolysis in the electrolyzer, producing high-value methane products to meet the gas load while reducing greenhouse gas emissions in the region and generating certain environmental benefits.

[0329] 5. Experimental results show that the present invention optimizes the planning and scheduling strategy of the integrated energy system by considering three types of integrated demand response IDR, which plays a positive role in promoting the consumption of renewable energy in the integrated energy system and improving the self-sufficiency of the integrated energy system.

[0330] Embodiment 2:

[0331] like Fig.11 As shown, the present invention provides a comprehensive energy system planning and scheduling device considering demand-side response, the device is used to implement the steps of the method in the above embodiment 1, and the device specifically includes:

[0332] The data acquisition module is used to obtain the historical load data of users in the target area, the historical data of wind and solar resources, the technical and economic parameters of various energy equipment, and the time-of-use electricity price mechanism;

[0333] Establish a load model module for establishing load models of price-based demand response, incentive-based demand response and alternative demand response;

[0334] Establish an initial model module to take the lowest annualized operating cost of the integrated energy system over the entire life cycle and the lowest demand-side response cost as the first optimization goal, and establish an initial planning and scheduling model that considers price-based demand response and incentive-based demand response;

[0335] An initial planning and scheduling module is used to solve the initial planning and scheduling model based on the acquired data information, combined with the operation constraints of the integrated energy system and the user satisfaction constraints, to obtain the load transfer and reduction after the price-based demand response and the incentive-based demand response, as well as the real-time pricing mechanism;

[0336] Load substitution module, which is used to perform substitution-type demand response based on real-time pricing mechanism, and obtain optimized price curves and load substitution amounts of various energy sources;

[0337] The planning and scheduling optimization module is used to solve the planning and scheduling optimization model with the lowest annualized operating cost of the integrated energy system over the entire life cycle as the second optimization goal based on the optimized price curve, the load replacement of various energy sources and the acquired data information, under the operating constraints, to obtain the optimal capacity configuration results and operation scheduling plan of each energy equipment in the integrated energy system.

[0338] The integrated energy system planning and scheduling device considering demand-side response provided in the embodiment of the present invention and the integrated energy system planning and scheduling method considering demand-side response provided in Example 1 are based on the same technical concept, and can produce the beneficial effects as described in Example 1. For the contents not described in detail in this embodiment, please refer to Example 1.

[0339] Embodiment three:

[0340] A terminal provided by an embodiment of the present invention includes a processor and a storage medium;

[0341] The storage medium is used to store instructions;

[0342] The processor is used to operate according to the instruction to execute the steps of the method according to any one of the first embodiments.

[0343] Embodiment 4:

[0344] An embodiment of the present invention provides a computer-readable storage medium, on which a computer program is stored. When the program is executed by a processor, the steps of any method described in Embodiment 1 are implemented.

[0345] The present disclosure may be a system, a method and / or a computer program product. The computer program product may include a computer-readable storage medium carrying computer-readable program instructions for causing a processor to implement various aspects of the present disclosure.

[0346] A computer-readable storage medium may be a tangible device that can hold and store instructions used by an instruction execution device. A computer-readable storage medium may be, for example, but not limited to, an electrical storage device, a magnetic storage device, an optical storage device, an electromagnetic storage device, a semiconductor storage device, or any suitable combination of the foregoing. More specific examples of computer-readable storage media (a non-exhaustive list) include: a portable computer disk, a hard disk, a random access memory (RAM), a read-only memory (ROM), an erasable programmable read-only memory (EPROM or flash memory), a static random access memory (SRAM), a portable compact disk read-only memory (CD-ROM), a digital versatile disk (DVD), a memory stick, a floppy disk, a mechanical encoding device, such as a punch card or a raised structure in a groove on which instructions are stored, and any suitable combination of the foregoing. As used herein, a computer-readable storage medium is not to be interpreted as a transient signal per se, such as a radio wave or other freely propagating electromagnetic wave, an electromagnetic wave propagating through a waveguide or other transmission medium (e.g., a light pulse through a fiber optic cable), or an electrical signal transmitted through a wire.

[0347] The computer-readable program instructions described herein can be downloaded from a computer-readable storage medium to each computing / processing device, or downloaded to an external computer or external storage device via a network, such as the Internet, a local area network, a wide area network, and / or a wireless network. The network can include copper transmission cables, optical fiber transmissions, wireless transmissions, routers, firewalls, switches, gateway computers, and / or edge servers. The network adapter card or network interface in each computing / processing device receives the computer-readable program instructions from the network and forwards the computer-readable program instructions for storage in the computer-readable storage medium in each computing / processing device.

[0348] The computer program instructions for performing the operation of the present disclosure may be assembly instructions, instruction set architecture (ISA) instructions, machine instructions, machine-related instructions, microcode, firmware instructions, state setting data, or source code or object code written in any combination of one or more programming languages, including object-oriented programming languages, such as Smalltalk, C++, etc., and conventional procedural programming languages, such as "C" language or similar programming languages. Computer-readable program instructions may be executed completely on a user's computer, partially on a user's computer, as an independent software package, partially on a user's computer, partially on a remote computer, or completely on a remote computer or server. In the case of a remote computer, the remote computer may be connected to the user's computer via any type of network, including a local area network (LAN) or a wide area network (WAN), or may be connected to an external computer (e.g., using an Internet service provider to connect via the Internet). In some embodiments, an electronic circuit, such as a programmable logic circuit, a field programmable gate array (FPGA), or a programmable logic array (PLA), may be customized by utilizing the state information of the computer-readable program instructions, and the electronic circuit may execute the computer-readable program instructions, thereby realizing various aspects of the present disclosure.

[0349] Finally, it should be noted that the above embodiments are only used to illustrate the technical solutions of the present invention rather than to limit it. Although the present invention has been described in detail with reference to the above embodiments, ordinary technicians in the relevant field should understand that the specific implementation methods of the present invention can still be modified or replaced by equivalents, and any modifications or equivalent replacements that do not depart from the spirit and scope of the present invention should be covered within the scope of protection of the claims of the present invention.

Claims

1. A comprehensive energy system planning and scheduling method considering demand-side response, characterized in that: The method comprises the following steps: S1. Obtain historical load data of users in the target area, historical data of wind and solar resources, technical and economic parameters of various energy equipment, and time-of-use electricity price mechanism; S2. Establish load models for price-based demand response, incentive-based demand response, and substitution-based demand response; S3. Taking the lowest annualized operating cost of the integrated energy system over the entire life cycle and the lowest demand-side response cost as the first optimization goal, an initial planning and scheduling model considering price-based demand response and incentive-based demand response is established; S4. Based on the data information obtained in step S1, combined with the operation constraints of the integrated energy system and the user satisfaction constraints, the initial planning and scheduling model is solved to obtain the load transfer and reduction after the price-based demand response and the incentive-based demand response, as well as the real-time pricing mechanism; S5. Perform alternative demand response based on real-time pricing mechanism to obtain optimized price curve and load substitution of various energy sources; S6. Based on the optimized price curve, the load substitution of various energy sources and the acquired data information, under the operating constraints, the planning and scheduling optimization model with the lowest annualized operating cost of the integrated energy system over the entire life cycle as the second optimization goal is solved to obtain the optimal capacity configuration results and operation scheduling plan of each energy equipment in the integrated energy system.

2. The integrated energy system planning and scheduling method considering demand-side response according to claim 1 is characterized in that: The energy equipment includes: photovoltaic generator sets, wind generator sets, thermal generator sets, batteries, electrolyzers, hydrogen storage tanks, carbon dioxide storage tanks, carbon capture systems, methane synthesis equipment, gas boilers, heat storage tanks and / or electric heating boilers; The technical and economic parameters include: unit capacity investment cost of each energy equipment, unit capacity maintenance cost, carbon tax penalty, transferable load response cost, reducible load response cost, electricity demand price elasticity coefficient, gas demand price elasticity coefficient, effective calorific value conversion coefficient and time-of-use pricing.

3. The integrated energy system planning and scheduling method considering demand-side response according to claim 1 is characterized in that: The price-based demand response refers to guiding the energy consumption behavior of users by formulating time-of-use electricity prices to achieve the transfer of load peaks to load valleys; The incentive-based demand response refers to the signing of relevant economic contracts between demand response providers and users with freely controllable loads, and the reduction of corresponding user loads when the power generated by the grid side is insufficient, and economic compensation is given; The substitution demand response refers to the user using the comprehensive price of electricity, heat and natural gas as a criterion to replace loads with each other according to the rule of replacing higher-priced energy with lower-priced energy.

4. The integrated energy system planning and scheduling method considering demand-side response according to claim 1 or 3, characterized in that: The load model of the price-based demand response includes transferable loads, and its expression is as follows: Wherein, d(t) represents the load after participating in demand response at time t; d0(t) represents the basic load before participating in demand response at time t; E(t, t') represents the influence of the load variable at time t on the load at time t', that is, the self-elasticity coefficient at time t; ρ(t) represents the energy price at time t; ρ0(t') represents the initial energy price before response at time t'.

5. The integrated energy system planning and scheduling method considering demand-side response according to claim 1 or 3, characterized in that: The load model of the incentive-based demand response includes loads that can be cut; the loads that can be cut are divided into direct interruption loads and partial reduction loads; The direct interruption load model expression is as follows: In the formula, and They represent the user load and the direct interruption amount of load after the direct interruption of the i-th energy source at time t respectively; Direct interruption of load Initial load d i,0 (t) maximum ratio; Δd i,0 (t) represents the initial direct interruption load at time t; e, h and g represent electric energy, thermal energy and natural gas respectively; The model expression of partial load reduction is as follows: In the formula, The user represents the load after the user partially reduces the i-th energy load at time t; Partial load reduction Initial load d i,0 (t) maximum ratio; represents the curtailable load factor at time t; i (t) represents the price of the i-th energy after participating in the demand-side response at time t; i,0 (t) represents the energy price after the i-th energy participates in the demand-side response at time t.

6. The integrated energy system planning and scheduling method considering demand-side response according to claim 1 is characterized in that: The objective function with the lowest annualized operating cost of the integrated energy system over the entire life cycle and the lowest demand-side response cost as the first optimization goal is as follows: F1minf static +Zf IDR Where F1 is the total cost of the integrated energy system considering price-based demand response and incentive-based demand response; Z is the number of days in the whole year for calculation; f IDR The cost of demand response on a typical day; static The annual operating cost of the integrated energy system over its entire life cycle is: static =C INV +C OM +C RT +C CE ; C OM is the system operation and maintenance cost; C RT is the resource transaction cost; C CE is the cost of carbon dioxide emissions; C INV System investment cost.

7. The integrated energy system planning and scheduling method considering demand-side response according to claim 6 is characterized in that: The cost of demand response in a typical day is f IDR The calculation formula is as follows: In the formula, and are the unit response cost of the i-th energy source at time t for the transferable load, directly interrupted load and partially reduced load respectively; and They respectively represent the amount of transferable load, directly interrupted load and partially reduced load of the i-th energy participating in the demand-side response at time t; e, h and g represent electricity, thermal energy and natural gas, respectively.

8. The integrated energy system planning and scheduling method considering demand-side response according to claim 1 is characterized in that: The operating constraints of the integrated energy system include: upper and lower output constraints and ramp constraints of thermal power units, upper and lower power constraints of carbon capture systems, upper and lower power constraints of electrolyzers and ramp constraints, upper and lower output constraints of methane synthesis equipment and ramp constraints, gas storage capacity and inlet and outlet gas constraints of hydrogen storage equipment, gas storage capacity and inlet and outlet gas constraints of carbon dioxide storage equipment, equipment safe operation constraints, system energy balance constraints and material conservation constraints.

9. The integrated energy system planning and scheduling method considering demand-side response according to claim 1 is characterized in that: The expression of the user satisfaction constraint is as follows: In the formula, Energy satisfaction index for users UNS The minimum threshold value, d i,0 (t) represents the load of the i-th energy source before it participates in the demand-side response at time t; represents the load of the i-th energy participating in the demand-side response at time t; e, h and g represent electricity, thermal energy and natural gas, respectively.

10. The integrated energy system planning and scheduling method considering demand-side response according to claim 1, characterized in that: The step of performing substitution demand response based on the real-time pricing mechanism includes: comparing the comprehensive prices of electric energy, thermal energy and natural gas based on the real-time pricing mechanism; and performing mutual substitution between various types of loads according to the following substitution rules based on the comparison results: Rule 1: When the comprehensive electricity price is greater than the comprehensive heat price and the comprehensive heat price is greater than the comprehensive gas price, the electricity load is replaced by the gas load and the heat load, and the heat load is replaced by the gas load; Rule 2: When the comprehensive electricity price is greater than the comprehensive gas price and the comprehensive gas price is greater than the comprehensive heat price, the electricity load is replaced by the heat load and the gas load, and the gas load is replaced by the heat load; Rule 3: When the comprehensive heat price is greater than the comprehensive electricity price and the comprehensive electricity price is greater than the comprehensive gas price, the heat load is replaced by the electricity load and the gas load, and the electricity load is replaced by the gas load; Rule 4: When the comprehensive heat price is greater than the comprehensive gas price and the comprehensive gas price is greater than the comprehensive electricity price, the heat load is replaced by the gas load and the electricity load, and the gas load is replaced by the electricity load; Rule 5: When the comprehensive gas price is greater than the comprehensive electricity price and the comprehensive electricity price is greater than the comprehensive heat price, the gas load is replaced by the electricity load and the heat load, and the electricity load is replaced by the heat load; Rule 6: When the comprehensive gas price is greater than the comprehensive heat price and the comprehensive heat price is greater than the comprehensive electricity price, the gas load is replaced by the heat load and the electricity load, and the heat load is replaced by the electricity load.

11. The integrated energy system planning and scheduling method considering demand-side response according to claim 10 is characterized in that: The load model of the alternative demand response under the above rules is as follows: In the formula, and They are comprehensive electricity price, comprehensive heat price and comprehensive gas price; It represents the electric load change caused by the demand-side response at time t; represents the gas load change caused by the demand-side response at time t; represents the heat load changed by the demand-side response at time t; represents the electric load replaced by the gas load at time t; represents the electrical load replaced by the thermal load at time t; It represents the heat load replaced by the gas load at time t; eg and θ eg They respectively represent the heat value conversion coefficient and the logic control variable of the electric load replaced by the gas load; hg and θ hg The calorific value conversion coefficient and the logic control variable respectively represent the heat load replaced by the gas load; eh and eh They represent the calorific value conversion coefficient and logical control variable of the electrical load replaced by the thermal load respectively; among which, hg ,θ eg and θ hg The average value is -1; LHV NG Indicates the lower heating value of natural gas.

12. The integrated energy system planning and scheduling method considering demand-side response according to claim 10, characterized in that: The load model of alternative demand response under Rule 2 is as follows: In the formula, and They are comprehensive electricity price, comprehensive heat price and comprehensive gas price; It represents the electric load change caused by the demand-side response at time t; represents the gas load change caused by the demand-side response at time t; represents the heat load changed by the demand-side response at time t; represents the electric load replaced by the gas load at time t; represents the electrical load replaced by the thermal load at time t; represents the gas load replaced by the heat load at time t; eg and eg They represent the calorific value conversion coefficient and logic control variable of the electric load replaced by the gas load; ρ gh and θ gh respectively represent the heat value conversion coefficient and the logic control variable of the gas load replaced by the heat load; eh and eh They represent the calorific value conversion coefficient of the electrical load replaced by the thermal load and the logical control variable respectively; among which, θ eh and θ eg The value of average is -1. gh The value of LHV is 1; NG Indicates the lower heating value of natural gas.

13. The integrated energy system planning and scheduling method considering demand-side response according to claim 10, characterized in that: The load model of alternative demand response under Rule 3 is as follows: In the formula, and They are comprehensive electricity price, comprehensive heat price and comprehensive gas price; It represents the electric load change caused by the demand-side response at time t; represents the gas load change caused by the demand-side response at time t; represents the heat load changed by the demand-side response at time t; represents the electric load replaced by the gas load at time t; represents the heat load replaced by the electric load at time t; represents the heat load replaced by gas load at time t; μ eg and θ eg They represent the calorific value conversion coefficient and logic control variable of the electric load replaced by the gas load; μ hg and θ hg They represent the calorific value conversion coefficient and logic control variable of the heat load replaced by the gas load; μ he and θ he They represent the calorific value conversion coefficient and logical control variable of the heat load replaced by the electric load respectively; among which, hg and eg The value of average is -1. he The value of LHV is 1; NG Indicates the lower heating value of natural gas.

14. The integrated energy system planning and scheduling method considering demand-side response according to claim 10, characterized in that: The load model of alternative demand response under Rule 4 is as follows: In the formula, and They are comprehensive electricity price, comprehensive heat price and comprehensive gas price; It represents the electric load change caused by the demand-side response at time t; represents the gas load change caused by the demand-side response at time t; represents the heat load changed by the demand-side response at time t; represents the gas load replaced by the electric load at time t; represents the heat load replaced by the electric load at time t; It represents the heat load replaced by the gas load at time t; ge and ge They represent the calorific value conversion coefficient of the gas load replaced by the electric load and the logical control variable; ρ hg and θ hg They represent the calorific value conversion coefficient and logic control variable of the heat load replaced by the gas load; μ he and θ he They represent the calorific value conversion coefficient and logical control variable of the heat load replaced by the electric load; among them, θ he and θ he The value of average is 1. hg The value of LHV is -1; NG Indicates the lower heating value of natural gas.

15. The integrated energy system planning and scheduling method considering demand-side response according to claim 10, characterized in that: The load model of alternative demand response under Rule 5 is as follows: In the formula, and They are comprehensive electricity price, comprehensive heat price and comprehensive gas price; It represents the electric load change caused by the demand-side response at time t; represents the gas load change caused by the demand-side response at time t; represents the heat load changed by the demand-side response at time t; represents the gas load replaced by the electric load at time t; represents the electrical load replaced by the thermal load at time t; represents the gas load replaced by the heat load at time t; μ ge and θ ge They respectively represent the heat value conversion coefficient and the logic control variable of the gas load replaced by the electric load; gh and gh respectively represent the heat value conversion coefficient and the logic control variable of the gas load replaced by the heat load; eh and eh They represent the calorific value conversion coefficient and logical control variable of the electrical load replaced by the thermal load respectively; among which, ge and gh The value of average is 1. eh The value of LHV is -1; NG Indicates the lower heating value of natural gas.

16. The integrated energy system planning and scheduling method considering demand-side response according to claim 10, characterized in that: The load model of alternative demand response under Rule 6 is as follows: In the formula, and They are comprehensive electricity price, comprehensive heat price and comprehensive gas price; It represents the electric load change caused by the demand-side response at time t; represents the gas load change caused by the demand-side response at time t; represents the heat load changed by the demand-side response at time t; represents the gas load replaced by the electric load at time t; represents the heat load replaced by the electric load at time t; represents the gas load replaced by the heat load at time t; ge and θ ge They represent the heat value conversion coefficient and logic control variable of the gas load replaced by the electric load; μ gh and θ gh They represent the calorific value conversion coefficient of the gas load replaced by the heat load and the logical control variable; μ he and θ he They represent the calorific value conversion coefficient and logical control variable of the heat load replaced by the electric load; among them, θ ge ,θ he and θ gh The average value is 1; LHV NG Indicates the lower heating value of natural gas.

17. A device for planning and scheduling an integrated energy system considering demand-side response, running the method for planning and scheduling an integrated energy system considering demand-side response as claimed in any one of claims 1 to 16, characterized in that: The device includes: The data acquisition module is used to obtain the historical load data of users in the target area, the historical data of wind and solar resources, the technical and economic parameters of various energy equipment, and the time-of-use electricity price mechanism; Establish a load model module for establishing load models of price-based demand response, incentive-based demand response and alternative demand response; Establish an initial model module to take the lowest annualized operating cost of the integrated energy system over the entire life cycle and the lowest demand-side response cost as the first optimization goal, and establish an initial planning and scheduling model that considers price-based demand response and incentive-based demand response; An initial planning and scheduling module is used to solve the initial planning and scheduling model based on the acquired data information, combined with the operation constraints of the integrated energy system and the user satisfaction constraints, to obtain the load transfer and reduction after the price-based demand response and the incentive-based demand response, as well as the real-time pricing mechanism; Load substitution module, which is used to perform substitution-type demand response based on real-time pricing mechanism, and obtain optimized price curves and load substitution amounts of various energy sources; The planning and scheduling optimization module is used to solve the planning and scheduling optimization model with the lowest annualized operating cost of the integrated energy system over the entire life cycle as the second optimization goal based on the optimized price curve, the load replacement of various energy sources and the acquired data information, under the operating constraints, to obtain the optimal capacity configuration results and operation scheduling plan of each energy equipment in the integrated energy system.

18. A terminal comprising a processor and a storage medium; characterized in that: The storage medium is used to store instructions; The processor is configured to operate according to the instructions to execute the steps of the method according to any one of claims 1-16.

19. A computer-readable storage medium having a computer program stored thereon, characterized in that: When the program is executed by a processor, the steps of the method according to any one of claims 1 to 16 are implemented.

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