Regional integrated energy system scheduling method and system considering carbon tax and carbon transaction

Abstract

The invention discloses a regional integrated energy system scheduling method and system considering carbon tax and carbon transaction, and relates to the technical field of integrated energy system optimization scheduling, and the method comprises the steps: building an upper-layer energy supplier low-carbon economic scheduling model based on the carbon emission cost and the energy cost by considering the stepped carbon tax and the fluctuating carbon transaction price for a regional IES; the lower-layer inter-region low-carbon economic dispatching model and the multi-park cooperative game dispatching model based on the operation cost and the power interaction cost are synthesized to obtain a double-layer dispatching model; configuring carbon capture equipment and an energy storage power station for an upper-layer energy supplier of the system, optimizing carbon emission and energy volatility of the double-layer scheduling model, and constructing a carbon capture constraint condition and an energy storage constraint condition; and solving by taking the lowest cost as an optimization target of the double-layer scheduling model in combination with constraint conditions, and optimizing operation of the scheduling integrated energy system according to a solving result. According to the invention, the regional low-carbon cooperative scheduling of the IES and the cooperative scheduling among the IES parks are realized.

Description

Technical Field

[0001] The present invention relates to the technical field of integrated energy system optimization and scheduling, and in particular to a regional integrated energy system scheduling method and system taking into account carbon tax and carbon trading. Background Art

[0002] With the proposal of the dual carbon goals, the penetration rate of renewable energy in the power system has increased significantly, and the energy industry has gradually transformed towards a low-carbon and clean economy. As the current carbon regulation intensity increases, the appropriate timing of the carbon tax mechanism can achieve the "double dividend" effect of carbon tax; the carbon tax mechanism can effectively alleviate "carbon leakage" and play a key role in total carbon emissions control and energy structure adjustment. When the carbon tax rate increases, supply chain companies will accelerate the adoption of low-carbon technologies to reduce the amount of carbon tax paid.

[0003] As an important energy management technology, the Integrated Energy System (IES) can couple multiple energy forms and improve the overall energy utilization efficiency. It is one of the important means to promote low-carbon goals. Considering the emission reduction effect of fixed carbon tax prices and carbon trading prices on the integrated energy system, determining the optimal carbon tax price and carbon trading cost price for the integrated energy system will be the focus of the next research work. The existing research schemes include: introducing a step-by-step carbon tax in the construction of the carbon tax cost calculation model, and charging a step-by-step carbon tax on the carbon emissions of the system that exceed the initial quota, so as to fully tap the system's low-carbon emission reduction potential; constructing integrated energy suppliers and multi-park low-carbon scheduling models respectively, and characterizing the cooperative game between parks based on Nash negotiation, reducing carbon emissions and improving social benefits through power mutual assistance between parks.

[0004] However, the above existing schemes still have certain problems, resulting in the final dispatching strategy being not optimal, including: (1) The current IES dispatching mostly focuses on the optimization dispatching within a single system, lacks research on the coordinated dispatching optimization model between multiple integrated energy systems with cross-regional energy interactions, and is difficult to achieve the low-carbon economic benefits of multiple IES; (2) When considering the constraints of carbon policies, the existing dispatching models often ignore the interactive effects of carbon taxes and carbon trading, and cannot accurately simulate the dispatching impacts of multiple carbon policies in the real market; (3) Considering the complex game relationship between power interactions among multiple parks, there is a problem of interest redistribution in power interactions. Energy sellers hope that the energy price is as high as possible, while buyers want the opposite. Unreasonable interest distribution may lead to the breakdown of negotiations. The existing low-carbon dispatching strategy lacks an effective design of such an incentive mechanism among multiple parks.

[0005] In addition, as an important power source option in the future, the operating performance and adjustment capabilities of carbon capture power plants will have a significant impact on the safety and efficiency of power grid operation. The existing dispatching strategy does not consider the impact of adding carbon capture equipment on the optimized dispatching strategy. Summary of the invention

[0006] In order to solve the deficiencies of the above-mentioned prior art, the present invention provides a regional integrated energy system scheduling method and system taking into account carbon tax and carbon trading. Aiming at the regional collaborative optimization problem of IES, the low-carbon energy consumption enthusiasm of IES is improved through step-type carbon tax incentives, and the scheduling impact of multiple carbon policies in reality is accurately simulated by combining carbon tax and carbon trading mechanism to achieve low-carbon collaborative scheduling of regional integrated energy system; introduce carbon capture and energy storage technology to cope with carbon emissions and energy fluctuations, and enhance the flexibility and low-carbon economy of system operation; design a multi-IES park cooperative game scheduling model in the scheduling process, achieve low-carbon benefit win-win among IES parks, and achieve collaborative scheduling among IES parks to improve the low-carbon efficiency of the overall system.

[0007] In a first aspect, the present invention provides a method for dispatching a regional integrated energy system taking into account carbon tax and carbon trading.

[0008] A regional integrated energy system dispatching method taking into account carbon tax and carbon trading, comprising:

[0009] For the regional integrated energy system, according to the additional carbon emissions of the system, considering the tiered carbon tax and fluctuating carbon trading prices, the additional carbon emission costs are determined, and a low-carbon economic dispatch model of the upper energy supplier based on carbon emission costs and energy costs is constructed; at the same time, based on the fluctuations of carbon trading prices, the interaction power between each park and the upper energy supplier and between the parks is optimized, and a low-carbon economic dispatch model between the lower regions and a multi-park cooperative game dispatch model based on operating costs and power interaction costs is constructed;

[0010] Integrate the dispatch models of the upper and lower layers of the system to build a two-layer dispatch model for the regional integrated energy system;

[0011] Configure carbon capture equipment and energy storage power stations for upper-level energy suppliers in the system, optimize carbon emissions and energy volatility in the two-tier dispatch model, and establish carbon capture constraints and energy storage constraints;

[0012] The optimization goal of the two-layer scheduling model is to minimize cost, and the solution is calculated based on the constraints. The operation of the integrated energy system is optimized and scheduled according to the solution results.

[0013] A further technical solution is to construct a low-carbon economic dispatch model for energy suppliers, including:

[0014] For the regional integrated energy system, obtain the system's initial carbon emission quota and calculate the system's total carbon emissions;

[0015] Based on the initial carbon emission quota and total carbon emissions, determine the additional carbon emissions of the system during the current scheduling cycle and calculate the carbon emission cost of the additional carbon emissions;

[0016] Taking the operating costs of CHP units, thermal power units and wind turbines in the upper-level energy suppliers of the system and the cost of purchasing electricity from the external power grid as the energy cost, the carbon emission cost is jointly calculated to construct a low-carbon economic dispatch model for the upper-level energy suppliers.

[0017] A further technical solution is that the carbon emission cost includes the carbon tax cost and the carbon trading cost, and the additional carbon emissions are divided into carbon emissions used to pay the carbon tax and carbon emissions used to purchase carbon emission permits, and the carbon tax cost and carbon trading cost are calculated separately.

[0018] In a further technical solution, the calculation of the carbon tax cost includes: constructing a stepped carbon tax model based on the carbon tax transaction base price and the step change rate; using the stepped carbon tax model, combined with the carbon emissions used to pay the carbon tax, to calculate the carbon tax cost;

[0019] The calculation of the carbon trading cost includes: using a random scenario method in combination with historical carbon price data, using Monte Carlo simulation technology, to generate a variety of carbon price change scenarios, and constructing a carbon trading cost function for each scenario; based on the carbon trading cost function, combined with the carbon emissions used to purchase carbon emission permits, calculate the carbon trading cost for each scenario; and comprehensively analyze the carbon trading costs under all scenarios to obtain the final carbon trading cost.

[0020] A further technical solution is to construct the inter-regional low-carbon economic dispatch model, including:

[0021] For each park in the lower layer of the regional integrated energy system, the power of electric heat purchased by the park from the energy supplier and the electric heat exchange power with other parks are calculated based on the price of electric heat purchased by the park from the energy supplier and the electric heat exchange price with other parks. The power exchange cost is the energy transaction cost.

[0022] Taking the sum of the park's energy purchase cost from energy suppliers and the energy transaction cost between the park and other parks as the park's operating cost, an inter-regional low-carbon economic scheduling model is constructed.

[0023] A further technical solution is to construct the multi-park cooperative game scheduling model, including:

[0024] The Nash negotiation theory is used to describe the game relationship in the power interaction process between parks, and the game relationship is converted into a Nash negotiation problem, and a multi-park cooperative game scheduling model is constructed. Among them, the Nash negotiation problem is equivalent to the sub-problem of minimizing the park power interaction cost and the sub-problem of maximizing the park payment benefit by using the mean inequality.

[0025] In a further technical solution, the carbon capture constraints include carbon capture level constraints and carbon dissolved solution volume constraints;

[0026] The energy storage constraints include energy storage power station charging and discharging power constraints, energy storage power station capacity constraints, and initial and final energy storage energy balance constraints.

[0027] In a second aspect, the present invention provides a regional integrated energy system scheduling system that takes into account carbon tax and carbon trading.

[0028] A regional integrated energy system dispatching system taking into account carbon tax and carbon trading, comprising:

[0029] The scheduling model building module is used to determine the additional carbon emission costs for the regional integrated energy system based on the additional carbon emissions of the system, taking into account the tiered carbon tax and fluctuating carbon trading prices, and to build a low-carbon economic scheduling model for the upper-level energy supplier based on carbon emission costs and energy costs; at the same time, based on the fluctuations of carbon trading prices, optimize the interaction power between each park and the upper-level energy supplier and between the parks, and build a lower-level inter-regional low-carbon economic scheduling model and a multi-park cooperative game scheduling model based on operating costs and power interaction costs; integrate the scheduling models of the upper and lower levels of the system to build a two-level scheduling model for the regional integrated energy system;

[0030] The constraint building module is used to configure carbon capture equipment and energy storage power stations for the upper-level energy suppliers of the system, optimize the carbon emissions and energy volatility of the two-tier dispatch model, and build carbon capture constraints and energy storage constraints;

[0031] The optimization scheduling module is used to take the lowest cost as the optimization goal of the two-layer scheduling model, solve it in combination with the constraints, and optimize the operation of the scheduling integrated energy system according to the solution results.

[0032] In a third aspect, the present invention further provides an electronic device comprising a memory and a processor, and computer instructions stored in the memory and executed on the processor, wherein when the computer instructions are executed by the processor, the steps of the method described in the first aspect are completed.

[0033] In a fourth aspect, the present invention further provides a computer-readable storage medium for storing computer instructions, which, when executed by a processor, complete the steps of the method described in the first aspect.

[0034] One or more of the above technical solutions have the following beneficial effects:

[0035] 1. The present invention provides a regional integrated energy system scheduling method and system taking into account carbon tax and carbon trading, which improves the low-carbon energy consumption enthusiasm of IES through step-type carbon tax incentives, and accurately simulates the scheduling impact of multiple carbon policies in reality by combining carbon tax and carbon trading mechanisms, and constructs a low-carbon scheduling model combining carbon tax and carbon trading mechanisms to ensure the carbon emission reduction efficiency of the system under the constraints of dual carbon policies, thereby achieving low-carbon coordinated scheduling among various IES and improving the low-carbon efficiency of the overall system.

[0036] 2. In the method proposed in the present invention, carbon capture and energy storage technology is introduced to cope with the fluctuations in carbon emissions and new energy, achieve an economic balance between new energy consumption and carbon emission reduction, and enhance the flexibility and low-carbon economy of system operation; in addition, in the scheduling process, a multi-IES park cooperative game scheduling model is designed to improve the low-carbon participation of each park, achieve low-carbon benefit win-win among various IES parks, and achieve coordinated scheduling among various IES parks, so as to effectively improve the low-carbon efficiency of the overall system. BRIEF DESCRIPTION OF THE DRAWINGS

[0037] The accompanying drawings in the specification, which constitute a part of the present invention, are used to provide a further understanding of the present invention. The exemplary embodiments of the present invention and their descriptions are used to explain the present invention and do not constitute improper limitations on the present invention.

[0038] Figure 1 It is an overall block diagram of the regional integrated energy system scheduling method taking into account carbon tax and carbon trading according to an embodiment of the present invention;

[0039] Figure 2 This is a flow chart of a regional integrated energy system scheduling method considering carbon trading costs in an embodiment of the present invention. DETAILED DESCRIPTION

[0040] It should be noted that the following detailed descriptions are exemplary only, are intended to describe specific embodiments, are intended to provide further explanation of the present invention, and are not intended to limit exemplary embodiments according to the present invention. Unless otherwise specified, all technical and scientific terms used herein have the same meanings as those of ordinary skill in the art to which the present invention belongs. In addition, it should also be understood that when the terms "comprising" and / or "including" are used in this specification, it indicates the presence of features, steps, operations, devices, components and / or combinations thereof.

[0041] Embodiment 1

[0042] This embodiment provides a regional integrated energy system scheduling method taking into account carbon tax and carbon trading, such as Figure 1 As shown, the specific steps include:

[0043] Step S1: For the regional integrated energy system, according to the additional carbon emissions of the system, taking into account the tiered carbon tax and the fluctuating carbon trading price, the additional carbon emission cost is determined, and a low-carbon economic dispatch model of the upper-level energy supplier based on the carbon emission cost and the energy cost is constructed; at the same time, based on the fluctuation of the carbon trading price, the interaction power between each park and the upper-level energy supplier and between each park is optimized, and a lower-level inter-regional low-carbon economic dispatch model and a multi-park cooperative game dispatch model based on the operating cost and power interaction cost are constructed.

[0044] Step S2, integrating the scheduling models of the upper and lower layers of the system to construct a two-layer scheduling model for the regional integrated energy system;

[0045] Step S3: configure carbon capture equipment and energy storage power stations for upper-level energy suppliers of the system, optimize carbon emissions and energy volatility of the two-layer scheduling model, and construct carbon capture constraints and energy storage constraints;

[0046] Step S4: Taking the lowest cost as the optimization goal of the two-layer scheduling model, solving it in combination with the constraints, and optimizing the operation of the scheduling integrated energy system according to the solution results.

[0047] The following content provides a more detailed introduction to the regional integrated energy system scheduling method taking into account carbon tax and carbon trading proposed in this embodiment.

[0048] In steps S1 and S2, a two-layer dispatching model of a regional integrated energy system based on a carbon tax and carbon trading mechanism is first constructed. Specifically, the regional integrated energy system includes an upper-layer energy supplier and a lower-layer multi-park (such as a living park, an industrial park, a commercial park, etc.). The two-layer dispatching model built for the regional integrated energy system has an upper-layer low-carbon economic dispatching model for energy suppliers of the integrated energy system and a lower-layer low-carbon economic dispatching model between regions. In the upper-layer model, the energy supplier of the integrated energy system aims to minimize costs, and the lower-layer model aims to minimize the energy-carbon costs paid by the integrated energy supplier and the interaction costs with other parks.

[0049] Step S1.1, construct the upper model: low-carbon economic dispatch model of energy suppliers in the integrated energy system.

[0050] Integrated energy suppliers directly participate in the carbon market, establish a dispatch model based on tiered carbon taxes and fluctuating carbon trading prices, and simulate the uncertainty of carbon trading market prices through random scenario methods, thereby ensuring the economic adaptability and carbon emission reduction effect of the system in a volatile carbon market environment. Figure 1 As shown, the integrated energy supplier realizes carbon income or pays carbon costs by selling or purchasing carbon quotas from external carbon trading centers.

[0051] Step S1.1.1: For the regional integrated energy system, obtain the initial carbon emission quota of the system, as shown in the following formula:

[0052] E s =E e +E gt +E gb

[0053]

[0054] In the formula, E s Allocate a quota for the total initial carbon emissions of the system, kg; E e 、E gt 、E gb is the initial free quota for carbon emissions from purchased electricity, CHP units and thermal power units, kg; δ e is the emission quota per unit of electric power, kg / kWh; T is the dispatch period, 24h; P e,t , P gte,t , P gbh,t is the power purchased by the system from the upper grid in the tth period, the power generated by the CHP unit and the thermal power unit, kW; Δt is a unit dispatching cycle, 1h; δ h is the emission quota per unit thermal power, kg / KWh; Q is the conversion factor of electrical power into thermal power; gth,t is the thermal power generated by the CHP unit in the tth period, kW.

[0055] In this embodiment, assuming that all the electricity purchased from the power grid comes from thermal power generation, the calculation formula for the total carbon emissions in the system is:

[0056]

[0057] In the formula, E a is the total carbon emissions of the system; c g 、c b 、c CHP are the carbon emission coefficients of thermal power units, large power grids, and CHP units respectively; P g,t and P b,t , are the output of thermal power units and the power purchased by the large power grid at time t respectively; G CHP,t is the natural gas intake power of the CHP unit; Δt is the time interval; T is the scheduling time set.

[0058] Step S1.1.2: Determine the additional carbon emissions of the system during the current scheduling period based on the initial carbon emission quota and the total carbon emissions, and calculate the carbon emission cost of the additional carbon emissions.

[0059] When the carbon emissions generated by the power system in a dispatch cycle exceed the initial carbon emission quota, additional carbon emissions will be generated. At this time, the system needs to choose to purchase carbon emission permits in the carbon trading market or pay carbon taxes for part of the carbon emissions, thereby generating additional carbon emission costs. That is, the carbon emission costs include carbon tax costs and carbon trading costs, and the additional carbon emissions are divided into carbon emissions used to pay carbon taxes and carbon emissions used to purchase carbon emission permits, as shown in the following formula:

[0060] E a =E s +E TA +E TR

[0061] E TR =μ(E a -E s )

[0062] C T =C TA +C TR

[0063] In the formula, E TA E is the carbon emissions that the system allocates to pay the carbon tax; TR is the carbon emission amount allocated to the purchase of carbon emission permits; μ is the substitution coefficient; C T is the total carbon emission cost; C TA , C TR They are carbon tax cost and carbon trading cost respectively.

[0064] On the basis of the above, the carbon tax cost and carbon trading cost are calculated respectively. First, the calculation of carbon trading cost includes:

[0065] The geometric Brownian motion has the best fit to the uncertainty of carbon price, which can be expressed as follows:

[0066] dP ctra (t) = ρP ctra (t)dt+σP ctra (t)dB(t)

[0067] Where, dP ctra (t) is the uncertainty of carbon price; ρ is the expected growth rate of carbon price; P ctra (t) is the carbon price at time t; dt is the time increment; σ represents the volatility of carbon emission rights trading prices; B(t) is the standard Wiener process, and dB(t) is the increment of the standard Wiener process.

[0068] Based on the above analysis, in fact, carbon price fluctuations are uncertain. Considering the uncertainty of carbon market price fluctuations and the large amount of reliable historical data available for reference, which mainly affects the evaluation of system economic benefits, this embodiment adopts a random simulation method to deal with the uncertainty of carbon prices. Figure 2 As shown, the random scenario method is combined with historical carbon price data, and the Monte Carlo simulation technology is used to generate a variety of carbon price change scenarios to depict the potential situation of carbon price uncertainty, thereby generating a carbon trading cost function under each scenario. Then, based on the carbon trading cost function, combined with the carbon emissions used to purchase carbon emission permits, the carbon trading cost under each scenario is calculated, as shown in the following formula;

[0069]

[0070] In the formula, scenario ω corresponds to a specific carbon price And the probability of the scene occurring π ω ; is the carbon trading cost under scenario ω; is the substitution coefficient μ under scenario ω ω The rounded-up value of TR,m The basic transaction fee of the carbon trading market is the carbon emissions allocated to the purchase of carbon emission permits under scenario ω; Ω is the set of scenarios.

[0071] Secondly, the calculation of carbon tax cost includes: In order to improve the low-carbon awareness of regional integrated energy systems, this embodiment constructs a stepped carbon tax model based on the carbon tax transaction base price and the step change rate, in which the more carbon quotas purchased, the higher the selling price in the corresponding range. On this basis, the carbon tax cost adopts the stepped carbon tax model, combined with the carbon emissions used to pay the carbon tax, to calculate the carbon tax cost, as shown in the formula:

[0072]

[0073] In the formula, C TA The carbon tax cost for integrated energy suppliers; E TA is the carbon emissions allocated by the system to pay carbon tax; λ is the basic price of carbon tax transaction; σ is the step change rate; E1 and E2 are the step interval lengths.

[0074] Step S1.1.3, taking the operating costs of CHP units, thermal power units and wind turbines in the upper-level energy supplier of the system and the cost of purchasing electricity from the external power grid as the energy cost, jointly calculate the obtained carbon emission cost, and build a low-carbon economic dispatch model for the upper-level energy supplier. Based on this model, low-carbon economic dispatch is carried out, and the dispatch goal is to minimize the cost of purchasing energy from the external power grid and gas grid and the carbon trading cost and carbon tax cost from the external carbon trading market. The model can be expressed as:

[0075]

[0076] In the formula, C I and are the total cost and energy cost of the integrated energy supplier, respectively; p b,t 、p CHP 、p g,t They are the power purchase price of the power grid, the output price of the CHP unit, and the output price of the thermal power unit.

[0077] Step S1.2, construct the lower-level model: inter-regional low-carbon economic scheduling model and multi-park cooperative game scheduling model.

[0078] The lower layer of the regional comprehensive scheduling model includes the inter-regional low-carbon economic scheduling model and the multi-park cooperative game scheduling model. Based on the fluctuation of carbon trading market prices, the interaction power between each park and the upper-level energy supplier and between each park is optimized to minimize the overall low-carbon cost. In this embodiment, each park is a comprehensive energy user, equipped with small distributed wind turbines, photovoltaics, energy storage, electric boilers and other equipment, and energy transmission between parks can be achieved through interconnection lines.

[0079] Specifically, for each park in the upper and lower layers of the regional integrated energy system, the cost of purchasing energy from the energy supplier and the cost of power interaction with other parks are calculated based on the power of electric heat purchased by the park from the energy supplier and the power of electric heat exchange with other parks, combined with the price of electric heat purchased by the park from the energy supplier and the price of electric heat exchange with other parks. The power interaction cost is the energy transaction cost. Finally, the sum of the cost of energy purchased from the energy supplier and the energy transaction cost of interaction with other parks is taken as the operating cost of the park, and a regional low-carbon economic scheduling model is constructed.

[0080] The optimization goal of the constructed inter-regional low-carbon economic dispatch model is to achieve the lowest operating cost, that is, to reduce the energy-carbon fee (i.e., energy purchase cost) paid to the integrated energy supplier and the power interaction cost with other parks as much as possible. The model can be expressed as:

[0081]

[0082] In the formula, is the operating cost of park n; is the cost of park n participating in inter-park energy trading; is the energy purchase cost of park n from suppliers, p e,m→n,t and p h,m→n is the electricity price and heat price of the interactive power between park m and park n; p e,n,t and p h,n,t The electricity and heat prices of park n; Pm→n,t and H h,m→n Supplying electrical power and thermal power to park n for park m; and They are respectively the power of electricity and heat purchased by park n from the integrated energy supplier at time t.

[0083] In the above model, considering that each park in the multi-park system is an independent and rational individual, a complex game relationship is formed in the process of power interaction: on the one hand, the multi-park system as a whole reduces costs through internal power mutual assistance and achieves win-win results; on the other hand, power interaction brings about the problem of interest redistribution. The seller hopes to increase the price of energy, while the buyer hopes to reduce costs. Unreasonable interest distribution may lead to the breakdown of negotiations. Therefore, this embodiment designs a reasonable transaction mechanism and constructs a multi-park cooperative game scheduling model, which can not only increase the overall benefits of the multi-park system, but also fairly distribute the benefits.

[0084] Specifically, considering that the Nash negotiation theory can describe the cooperative game of multiple subjects, so that the choice of each subject becomes the best response to the strategies of other subjects, thereby finally achieving a stable equilibrium, therefore, in this embodiment, the Nash negotiation theory is used to describe the game relationship in the power interaction process between the parks, and the game relationship is converted into a Nash negotiation problem, and a multi-park cooperative game scheduling model is constructed, which can be expressed as:

[0085]

[0086] In the formula, is the cost of each park not participating in power interaction.

[0087] Furthermore, by using the mean inequality, the above Nash negotiation problem is equivalent to the sub-problem of minimizing the park power interaction cost and the sub-problem of maximizing the park payment benefit. Among them, the sub-problem of minimizing the park power interaction cost aims to make the park interaction costs offset each other, which can be expressed as:

[0088]

[0089] Using the solution of the park power interaction cost minimization sub-problem, combined with the park's minimum energy purchase cost, the park payment benefit maximization sub-problem is solved, which can be expressed as:

[0090]

[0091] In the formula, represents the energy purchase cost of the park from the supplier obtained by solving the sub-problem of minimizing the power interaction cost of the park, Indicates the power exchange price between campuses.

[0092] In the above-mentioned solution process, due to the sub-problem of minimizing the power interaction cost of the park, even if the interaction costs between parks offset each other, the interaction cost between parks is 0, and then the minimum operating cost of each park can be solved (equivalent to the energy purchase cost of the park from the supplier), which is a constant in the sub-problem of maximizing the payment benefit of the park; on this basis, the energy purchase cost and the cost of each park not participating in power interaction are constants, so as to solve the payment benefit maximization problem, and then the minimum power interaction price between parks can be solved.

[0093] By solving the above formula, the power interaction price between parks can be obtained. On the one hand, the multi-park system as a whole can reduce costs and achieve a win-win situation through internal power interaction. On the other hand, power interaction brings about the problem of benefit redistribution. Sellers hope to increase the price of energy, while buyers hope to reduce costs. Unreasonable distribution of benefits may lead to the breakdown of negotiations. Therefore, constructing a multi-park cooperative game scheduling model can not only increase the overall benefits of the multi-park system, but also fairly distribute the benefits, and then reduce the operating costs of the parks in the inter-regional low-carbon economic scheduling model, thereby optimizing the inter-regional low-carbon economic scheduling model with the goal of minimizing power interaction costs.

[0094] Preferably, to ensure the fairness of transactions between parks, information interaction between parks is transmitted through a virtual power plant (VPP), that is, each park transmits its desired energy interaction volume and price to the VPP, which is then forwarded to the corresponding park by the VPP, thereby realizing interaction between multi-park systems.

[0095] In step S3, carbon capture equipment and energy storage power stations are configured for the upper-level energy suppliers of the system, the carbon emissions and energy volatility of the two-layer scheduling model are optimized, and carbon capture constraints and energy storage constraints are constructed.

[0096] Carbon capture equipment and energy storage stations are configured in the integrated energy system. Through the capture and storage functions of carbon capture equipment, the system's carbon emissions are reduced from the source, achieving joint optimization with renewable energy; the energy storage system is used to balance the volatility of new energy and the peak shifting of load demand, further improving the carbon emission reduction effect and energy utilization. By rationally configuring carbon capture and energy storage devices, the system can better balance carbon emissions and the volatility of new energy. The carbon capture device can effectively reduce the total carbon emissions of the system, while the energy storage system plays a key role in peak-valley regulation to achieve overall low-carbon economic benefits.

[0097] Step S3.1: Construction of carbon capture configuration and its constraints.

[0098] Thermal power units and CHP units can be equipped with carbon capture devices to form carbon capture power plants, which can capture and store carbon dioxide after the combustion of coal and natural gas, and avoid the integrated energy system from emitting carbon dioxide into the atmosphere during carbon peak periods. This embodiment uses carbon capture equipment with flexible capture levels and is equipped with a liquid storage tank to reduce the operating cost of the system by time-shifting the operating energy consumption of the equipment. The total energy consumption of the carbon capture equipment consists of fixed energy consumption and operating energy consumption, where the operating energy consumption is related to the amount of carbon dioxide captured by the analysis and compression of the carbon capture equipment, as shown in the following formula:

[0099]

[0100] In the formula, are the total energy consumption, fixed energy consumption and operating energy consumption of carbon capture equipment j at time t under scenario w, respectively; is the operating state of the carbon capture equipment; W j The operating energy consumption required for the carbon capture equipment j to process a unit of carbon dioxide; is the amount of carbon dioxide captured by carbon capture device j at time t under scenario ω.

[0101] Furthermore, since the system is equipped with carbon capture equipment, the carbon emission coefficient is reduced, and the power injected into the system by the thermal power unit and CHP unit will also be reduced. The output power of the thermal power unit and CHP unit is partially consumed by the carbon capture equipment. Therefore, the total output power of the carbon capture power plant is:

[0102]

[0103] In the formula, is the power injected into the system by the carbon capture power plant j at time t under scenario ω, which can be used to calculate the power actually injected into the system by the thermal power plant and CHP unit equipped with carbon capture in the above supplier's low-carbon economic dispatch model (i.e., the electric power generated by the above CHP unit and thermal power unit); is the output of carbon capture power plant j at time t under scenario ω.

[0104] Based on the operating energy consumption in the above formula, the following carbon capture level constraints are analyzed and determined. Specifically, the carbon capture equipment adopts a flexible capture level and is equipped with a liquid storage tank. The amount of carbon dioxide captured consists of two parts: one is the carbon emissions absorbed from the combustion of coal in the thermal power unit, and the other is the carbon emissions released or stored in the liquid storage tank, as shown in the formula:

[0105]

[0106] In the formula, is the flue gas split ratio of carbon capture equipment j; is the capture level of carbon capture equipment j at time t under scenario ω; is the carbon emission of the thermal power unit connected to the carbon capture device j at time t under scenario ω; are the carbon emissions stored and released in the liquid storage tank in carbon capture equipment j, respectively.

[0107] In order to maintain the stability of the carbon capture equipment during operation, it is necessary to set the minimum and maximum values ​​of the capture level, as shown in the following formula:

[0108]

[0109] In the formula, They are the minimum and maximum capture levels of carbon capture equipment respectively.

[0110] Based on the above analysis, a carbon capture level constraint was constructed. On this basis, considering that the carbon capture equipment is also equipped with a liquid storage tank, the carbon capture equipment can use solvents such as ethanolamine to dissolve part of the carbon dioxide and temporarily store it in a rich liquid tank (ie, liquid storage tank). For this purpose, a carbon dissolved solution volume constraint was also designed to constrain the carbon storage situation.

[0111] Specifically, during the period of low power demand, the equipment sends the solution in the rich liquid tank to the gas stripping tower for carbon dioxide release and capture, thereby transferring part of the capture energy consumption during the period of high power demand to the period of low power demand, thereby improving the flexibility of system operation. This embodiment uses ethanolamine solution as the solvent of the storage tank, and the volume of solution required for unit carbon dioxide dissolution is shown in the following formula:

[0112]

[0113] In the formula, are the volumes of solutions in the rich liquid tank and the lean liquid tank respectively; The upper and lower limits of the volume of the lean liquid tank solution; The upper and lower limits of the solution volume in the rich liquid tank.

[0114] Step S3.2: Construction of energy storage power station configuration and its constraints.

[0115] In this embodiment, the energy storage constraint conditions include energy storage power station charge and discharge power constraint, energy storage power station capacity constraint, and energy storage energy balance constraint. Among them, the energy storage power station charge and discharge power constraint is:

[0116]

[0117] In the formula, are the charging and discharging power of energy storage station s respectively; They are respectively the charging and discharging states of the energy storage power station s; They are the upper and lower limits of the charging and discharging power of the energy storage power station, respectively.

[0118] The capacity constraint of the energy storage system is:

[0119]

[0120] In the formula, E s,tω is the energy storage state of the energy storage power station s at time t under scenario ω; ε is the self-consumption rate of the energy storage power station; η C is the charging efficiency; E A is the total capacity of the energy storage power station; E max 、E min The upper and lower limits of the capacity status.

[0121] The energy balance constraint is:

[0122] ∣E s,Tω -E s,0ω ∣≤ΔE

[0123] Where: E s,Tω 、E s,0ω Represents the capacity status of the energy storage power station s at the initial and final moments; ΔE is the capacity deviation value allowed at the initial and final moments.

[0124] In step S4, based on the above-constructed model and constraint set, all carbon price scenarios are integrated, and the optimization goal of the two-layer scheduling model is minimized, and the constraint conditions are combined to solve. In this embodiment, for the upper model in step S1.1.3, the goal is to minimize the cost of purchasing energy from the external power grid and gas grid and the carbon trading cost and carbon tax cost from the external carbon trading market. At the same time, for the lower model in step S1.2, the goal is to minimize the operating cost, that is, to minimize the energy-carbon fee (i.e., the energy purchase cost) paid to the integrated energy supplier and the power interaction cost with other parks. The solution is obtained to obtain the total cost, carbon trading cost and carbon tax cost of the integrated energy supplier, as well as the energy-carbon fee (i.e., the energy purchase cost) paid by the park to the integrated energy supplier and the power interaction cost with other parks.

[0125] Furthermore, according to the solution results, a purchase plan for the carbon trading market within the current scheduling cycle is formulated to optimize the operation of the scheduling integrated energy system, achieve coordinated scheduling among various IES and achieve low-carbon win-win benefits among various IES parks, and effectively improve the low-carbon efficiency of the overall system.

[0126] Embodiment 2

[0127] This embodiment proposes a regional integrated energy system dispatching system taking into account carbon tax and carbon trading, the system comprising:

[0128] The scheduling model building module is used to determine the additional carbon emission costs for the regional integrated energy system based on the additional carbon emissions of the system, taking into account the tiered carbon tax and fluctuating carbon trading prices, and to build a low-carbon economic scheduling model for the upper-level energy supplier based on carbon emission costs and energy costs; at the same time, based on the fluctuations of carbon trading prices, optimize the interaction power between each park and the upper-level energy supplier and between the parks, and build a lower-level inter-regional low-carbon economic scheduling model and a multi-park cooperative game scheduling model based on operating costs and power interaction costs; integrate the scheduling models of the upper and lower levels of the system to build a two-level scheduling model for the regional integrated energy system;

[0129] The constraint building module is used to configure carbon capture equipment and energy storage power stations for the upper-level energy suppliers of the system, optimize the carbon emissions and energy volatility of the two-tier dispatch model, and build carbon capture constraints and energy storage constraints;

[0130] The optimization scheduling module is used to take the lowest cost as the optimization goal of the two-layer scheduling model, solve it in combination with the constraints, and optimize the operation of the scheduling integrated energy system according to the solution results.

[0131] Embodiment 3

[0132] This embodiment provides an electronic device, including a memory and a processor, and computer instructions stored in the memory and running on the processor. When the computer instructions are executed by the processor, the steps in the regional integrated energy system scheduling method taking into account carbon tax and carbon trading as described above are completed.

[0133] Embodiment 4

[0134] This embodiment also provides a computer-readable storage medium for storing computer instructions, which, when executed by a processor, complete the steps in the regional integrated energy system scheduling method taking into account carbon tax and carbon trading as described above.

[0135] The steps involved in the above embodiments 2 to 4 correspond to the method embodiment 1, and the specific implementation methods can refer to the relevant description part of embodiment 1. The term "computer-readable storage medium" should be understood as a single medium or multiple media including one or more instruction sets; it should also be understood to include any medium that can store, encode or carry an instruction set for execution by a processor and enable the processor to execute any method in the present invention.

[0136] Those skilled in the art should understand that the modules or steps of the present invention described above can be implemented by a general-purpose computer device, or alternatively, they can be implemented by a program code executable by a computing device, so that they can be stored in a storage device and executed by the computing device, or they can be made into individual integrated circuit modules, or multiple modules or steps therein can be made into a single integrated circuit module for implementation. The present invention is not limited to any specific combination of hardware and software.

[0137] The above description is only a preferred embodiment of the present invention. Although the specific implementation mode of the present invention is described in conjunction with the accompanying drawings, it is not a limitation of the protection scope of the present invention. Those skilled in the art should understand that on the basis of the technical solution of the present invention, various modifications or variations that can be made by those skilled in the art without creative work are still within the protection scope of the present invention.

Claims

1. A regional integrated energy system scheduling method taking into account carbon tax and carbon trading, characterized in that: include: For the regional integrated energy system, according to the additional carbon emissions of the system, considering the tiered carbon tax and fluctuating carbon trading prices, the additional carbon emission costs are determined, and a low-carbon economic dispatch model of the upper energy supplier based on carbon emission costs and energy costs is constructed; at the same time, based on the fluctuations of carbon trading prices, the interaction power between each park and the upper energy supplier and between the parks is optimized, and a low-carbon economic dispatch model between the lower regions and a multi-park cooperative game dispatch model based on operating costs and power interaction costs is constructed; Integrate the dispatch models of the upper and lower layers of the system to build a two-layer dispatch model for the regional integrated energy system; Configure carbon capture equipment and energy storage power stations for upper-level energy suppliers in the system, optimize carbon emissions and energy volatility in the two-tier dispatch model, and establish carbon capture constraints and energy storage constraints; The optimization goal of the two-layer scheduling model is to minimize cost, and the solution is calculated based on the constraints. The operation of the integrated energy system is optimized and scheduled according to the solution results.

2. A regional integrated energy system scheduling method taking into account carbon tax and carbon trading as claimed in claim 1, characterized in that: The construction of the low-carbon economic dispatch model of the energy supplier includes: For the regional integrated energy system, obtain the system's initial carbon emission quota and calculate the system's total carbon emissions; Based on the initial carbon emission quota and total carbon emissions, determine the additional carbon emissions of the system during the current scheduling cycle and calculate the carbon emission cost of the additional carbon emissions; Taking the operating costs of CHP units, thermal power units and wind turbines in the upper-level energy suppliers of the system and the cost of purchasing electricity from the external power grid as the energy cost, the carbon emission cost is jointly calculated to construct a low-carbon economic dispatch model for the upper-level energy suppliers.

3. A regional integrated energy system scheduling method taking into account carbon tax and carbon trading as claimed in claim 2, characterized in that: The carbon emission cost includes carbon tax costs and carbon trading costs. The additional carbon emissions are divided into carbon emissions used to pay carbon taxes and carbon emissions used to purchase carbon emission permits, and the carbon tax costs and carbon trading costs are calculated separately.

4. A regional integrated energy system scheduling method taking into account carbon tax and carbon trading as claimed in claim 3, characterized in that: The calculation of the carbon tax cost includes: constructing a stepped carbon tax model based on the carbon tax transaction base price and the step change rate; using the stepped carbon tax model, combined with the carbon emissions used to pay the carbon tax, to calculate the carbon tax cost; The calculation of the carbon trading cost includes: using a random scenario method in combination with historical carbon price data, using Monte Carlo simulation technology, to generate a variety of carbon price change scenarios, and constructing a carbon trading cost function for each scenario; based on the carbon trading cost function, combined with the carbon emissions used to purchase carbon emission permits, calculate the carbon trading cost for each scenario; and comprehensively analyze the carbon trading costs under all scenarios to obtain the final carbon trading cost.

5. A regional integrated energy system scheduling method taking into account carbon tax and carbon trading as claimed in claim 1, characterized in that: The construction of the inter-regional low-carbon economic dispatch model includes: For each park in the lower layer of the regional integrated energy system, the power of electric heat purchased by the park from the energy supplier and the electric heat exchange power with other parks are calculated based on the price of electric heat purchased by the park from the energy supplier and the electric heat exchange price with other parks. The power exchange cost is the energy transaction cost. Taking the sum of the park's energy purchase cost from energy suppliers and the energy transaction cost between the park and other parks as the park's operating cost, an inter-regional low-carbon economic scheduling model is constructed.

6. A regional integrated energy system scheduling method taking into account carbon tax and carbon trading as claimed in claim 1, characterized in that: The construction of the multi-park cooperative game scheduling model includes: The Nash negotiation theory is used to describe the game relationship in the power interaction process between parks, and the game relationship is converted into a Nash negotiation problem, and a multi-park cooperative game scheduling model is constructed. Among them, the Nash negotiation problem is equivalent to the sub-problem of minimizing the park power interaction cost and the sub-problem of maximizing the park payment benefit by using the mean inequality.

7. A regional integrated energy system scheduling method taking into account carbon tax and carbon trading as claimed in claim 1, characterized in that: The carbon capture constraints include carbon capture level constraints and carbon dissolved solution volume constraints; The energy storage constraints include energy storage power station charging and discharging power constraints, energy storage power station capacity constraints, and initial and final energy storage energy balance constraints.

8. A regional integrated energy system dispatching system taking into account carbon tax and carbon trading, characterized in that: include: The scheduling model building module is used to determine the additional carbon emission costs for the regional integrated energy system based on the additional carbon emissions of the system, taking into account the tiered carbon tax and fluctuating carbon trading prices, and to build a low-carbon economic scheduling model for the upper-level energy supplier based on carbon emission costs and energy costs; at the same time, based on the fluctuations of carbon trading prices, optimize the interaction power between each park and the upper-level energy supplier and between the parks, and build a lower-level inter-regional low-carbon economic scheduling model and a multi-park cooperative game scheduling model based on operating costs and power interaction costs; integrate the scheduling models of the upper and lower levels of the system to build a two-level scheduling model for the regional integrated energy system; The constraint building module is used to configure carbon capture equipment and energy storage power stations for the upper-level energy suppliers of the system, optimize the carbon emissions and energy volatility of the two-tier dispatch model, and build carbon capture constraints and energy storage constraints; The optimization scheduling module is used to take the lowest cost as the optimization goal of the two-layer scheduling model, solve it in combination with the constraints, and optimize the operation of the scheduling integrated energy system according to the solution results.

9. An electronic device, characterized in that: The method comprises a memory and a processor and computer instructions stored in the memory and executed on the processor. When the computer instructions are executed by the processor, the steps of a regional integrated energy system scheduling method taking into account carbon tax and carbon trading are completed as described in any one of claims 1 to 7.

10. A computer-readable storage medium, characterized in that: Used to store computer instructions, which, when executed by a processor, complete the steps of a regional integrated energy system scheduling method taking into account carbon tax and carbon trading as described in any one of claims 1-7.

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