Energy scheduling system and method based on green certificate and carbon transaction mechanism

Abstract

The invention discloses an energy scheduling system and method based on a green certificate and carbon transaction mechanism, and relates to the technical field of energy scheduling, and the system comprises an operation cost objective function construction module and an operation scheme determination module. The operation cost objective function construction module is used for constructing an operation cost objective function of the regional integrated energy system; the regional integrated energy system is a renewable energy complementary regional integrated energy system, and the regional integrated energy system comprises a green certificate transaction mechanism and a carbon transaction mechanism; and the operation scheme determination module is used for solving the operation cost objective function by taking operation cost minimization as an objective to obtain an operation scheme of the regional integrated energy system. The energy utilization rate can be improved.

Description

Technical Field

[0001] The present application relates to the field of energy dispatching technology, and in particular to an energy dispatching system and method based on green certificates and carbon trading mechanisms. Background Art

[0002] At present, the global climate problem is becoming increasingly severe. Modern energy systems face many challenges in improving the capacity of renewable energy consumption, smoothing fluctuating loads, and controlling carbon emissions. Multi-energy complementary optimization scheduling and comprehensive demand response technology are the key to solving these problems. In the comprehensive demand response technology of energy trading, most of them adopt a single energy load optimization method, which fails to optimize the multi-energy coupling system of electricity, heat and cold at the same time, and the energy utilization rate still needs to be improved. Summary of the invention

[0003] The purpose of this application is to provide an energy scheduling system and method based on green certificates and carbon trading mechanisms, which can improve energy utilization.

[0004] To achieve the above objectives, this application provides the following solutions:

[0005] In the first aspect, the present application provides an energy dispatching system based on green certificates and carbon trading mechanisms, including: an operation cost objective function building module and an operation plan determination module;

[0006] The operating cost objective function construction module is used to construct the operating cost objective function of the regional integrated energy system; the regional integrated energy system is a regional integrated energy system with complementary renewable energy, and the regional integrated energy system includes green certificate trading and carbon trading mechanisms;

[0007] The operation plan determination module is used to solve the operation cost objective function with the goal of minimizing the operation cost, and obtain the operation plan of the regional integrated energy system.

[0008] In the second aspect, the present application provides an energy dispatching method based on green certificates and carbon trading mechanisms, including:

[0009] Constructing an operating cost objective function of a regional integrated energy system; the regional integrated energy system is a regional integrated energy system with complementary renewable energy, and the regional integrated energy system includes green certificate trading and carbon trading mechanisms;

[0010] The operation cost objective function is solved with the goal of minimizing the operation cost to obtain an operation plan for the regional integrated energy system.

[0011] According to the specific embodiments provided in this application, this application discloses the following technical effects:

[0012] The present application provides an energy dispatching system and method based on green certificate and carbon trading mechanism, constructs an operating cost objective function of a regional integrated energy system (RIES) based on green certificate trading and carbon trading mechanism, and solves an operating plan that minimizes operating costs under the condition of complementary multiple renewable energy sources, avoiding the problem of lack of synergy of traditional single optimization in multi-energy systems, greatly reducing the operating cost and carbon emissions of the system, and improving energy utilization. BRIEF DESCRIPTION OF THE DRAWINGS

[0013] In order to more clearly illustrate the embodiments of the present application or the technical solutions in the prior art, the drawings required for use in the embodiments will be briefly introduced below. Obviously, the drawings described below are only some embodiments of the present application. For ordinary technicians in this field, other drawings can be obtained based on these drawings without paying creative work.

[0014] Figure 1 A schematic diagram of the structure of an energy dispatching system based on green certificates and carbon trading mechanism provided in one embodiment of the present application;

[0015] Figure 2 A framework diagram of an energy dispatching system based on green certificates and carbon trading mechanisms provided in one embodiment of the present application;

[0016] Figure 3 A piecewise linearized gas turbine fuel consumption curve provided in one embodiment of the present application;

[0017] Figure 4 A schematic diagram of wind power and photovoltaic output prediction results provided in an embodiment of the present application;

[0018] Figure 5 A schematic diagram of the prediction results of cooling, heating and electricity loads provided in an embodiment of the present application;

[0019] Figure 6 A schematic diagram of peak-valley time-of-use electricity prices, time-of-use gas prices and on-grid electricity prices provided in one embodiment of the present application. DETAILED DESCRIPTION

[0020] The following will be combined with the drawings in the embodiments of the present application to clearly and completely describe the technical solutions in the embodiments of the present application. Obviously, the described embodiments are only part of the embodiments of the present application, not all of the embodiments. Based on the embodiments in the present application, all other embodiments obtained by ordinary technicians in this field without creative work are within the scope of protection of this application.

[0021] In order to make the above-mentioned objects, features and advantages of the present application more obvious and easy to understand, the present application is further described in detail below with reference to the accompanying drawings and specific implementation methods.

[0022] This application provides an energy dispatching system based on green certificates and carbon trading mechanisms, such as Figure 1 The energy dispatching system based on green certificates and carbon trading mechanism shown in the figure includes: an operation cost objective function building module and an operation plan determination module.

[0023] The operating cost objective function construction module is used to construct the operating cost objective function of the regional integrated energy system; the regional integrated energy system is a regional integrated energy system with complementary renewable energy, and the regional integrated energy system includes green certificate trading and carbon trading mechanisms.

[0024] The operation plan determination module is used to solve the operation cost objective function with the goal of minimizing the operation cost, and obtain the operation plan of the regional integrated energy system.

[0025] This application constructs an operating cost objective function for a regional integrated energy system based on green certificate trading and carbon trading mechanisms, and solves an operating plan that minimizes operating costs under the condition of complementary multiple renewable energy sources, avoiding the problem of lack of synergy in traditional single optimization in multi-energy systems, greatly reducing the system's operating costs and carbon emissions, and improving energy utilization.

[0026] In an exemplary embodiment, the regional integrated energy system includes a power supply system, a heating system and a cooling system. Figure 2 As shown, the hardware equipment in the regional integrated energy system includes energy equipment such as photovoltaic (PV) generator sets, wind turbines (WT), micro-gas turbines (GT), gas boilers (GB), and thermal energy storage equipment such as energy storage devices (ES) and heat storage tanks (HS), as well as energy conversion equipment such as waste heat boilers (WHB), absorption refrigerators (AR), air conditioning machines (AC), and heat exchangers (HE).

[0027] The operation scheme of the regional integrated energy system is the working power of each hardware device in the regional integrated energy system.

[0028] The power supply system is used to provide electrical load through external power grid, renewable energy and gas turbine power generation. The heating system is used to provide heat load through gas boiler and waste heat boiler. The cooling system is used to provide cooling load through absorption refrigerator and electric refrigerator. At the same time, the energy storage device (including power storage device and heat storage device) realizes flexible storage and release of energy. The power storage device includes battery energy storage.

[0029] The constraints of the operating cost objective function include gas turbine constraints, absorption chiller constraints, electric chiller constraints, battery constraints, thermal storage tank constraints, external distribution network constraints, electric load demand response constraints, and hot and cold load demand response constraints.

[0030] Natural gas power consumed by gas turbine and output power The relationship between can be expressed as:

[0031] in, is the start-up and shutdown status flag of the gas turbine in period t, which is 1 when it is in the start-up state and 0 when it is in the shutdown state; z and b are both fuel consumption coefficients, Represents the output power of the gas turbine during period t.

[0032] In order to facilitate rapid calculation and accurately reflect the actual operating status of GT, this application uses a piecewise linearization method to process formula (1), such as Figure 3 As shown. The slopes of the three segments after segmentation are:

[0033]

[0034] Among them, j1, j2, j3 and j4 are the GT electric power curve parameters after piecewise linearization; j4 and j1 are the maximum and minimum output values ​​of the GT electric power, respectively, so formula (1) can be rewritten as:

[0035]

[0036] in, is the lower limit of natural gas power consumed by GT, It is the start and stop status symbol of the gas turbine in period t, r i represents the slope of the curve in period i, j i represents the electric power curve parameter for period i, J i+1 It represents the electric power curve parameters of the i+1 period. The reference coordinate system of t is the optimization time of the entire system. The reference coordinate system of i and j is the gas turbine, which represents the period from the start of the gas turbine to the end, 0≤i≤t, 0≤j≤t.

[0037] When GT is running, the high-temperature flue gas discharged provides heat load to users through WHB. Its heating characteristic model is:

[0038]

[0039] in, and denote the thermal power output of GT at period t and the thermal power output of WHB at period t respectively; and They represent GT output electric-to-thermal power ratio and heat recovery efficiency respectively.

[0040] When GT is running, power generation constraints and ramp rate constraints must be considered, namely:

[0041]

[0042] in, and They are the upper and lower limits of the GT’s climbing rate respectively; and are the maximum output power and minimum output power of GT respectively, represents the output power of the gas turbine during period t-1, It represents the start and stop status of the gas turbine in period t.

[0043] Gas boilers generate heat by burning natural gas, which can compensate for the heat when WHB is insufficient. The relationship between its output power and the input natural gas power is:

[0044]

[0045] Among them, η gb is the heat generation efficiency of GB; is the gas consumption during period t; is the upper limit of output thermal power, is the output thermal power during the period t.

[0046] The absorption chiller uses liquid chiller to gasify and refrigerate under low pressure and low temperature conditions. The cooling capacity output in the period t is And the output thermal power must meet the following constraints:

[0047]

[0048] in, and η ar Represent AR output thermal power and energy efficiency ratio, It represents the cooling power output by the absorption chiller during the period t.

[0049] The electric refrigerator consumes electric energy to cool down. The relationship between the input electric power and the output cooling capacity in the period t and the corresponding constraints are:

[0050]

[0051] Among them, η ac is the energy efficiency ratio of AC; is the upper limit of AC output power, represents the cooling power output by the electric refrigerator during the period t, Represents the output power of the electric refrigerator during period t.

[0052] Considering the battery life, the remaining charge should be kept within the safety constraint range, which must meet the state of charge constraint, charge and discharge power, frequency constraint, mutual exclusion constraint and climbing rate constraint, namely:

[0053]

[0054] in, and are the charging power and discharging power in time period t respectively; and They are the upper / lower limits of battery charge / discharge power respectively; and The flag bit of the battery's charge / discharge status in period t, which is a 0-1 variable; is the remaining state of charge of the battery during period t, The remaining state of charge of the battery during period t-1; and The upper / lower limit of the remaining battery charge; η bt.chr and η bt.dis are the battery charge and discharge efficiency respectively; and are the minimum / maximum climbing rate of the battery under charging / discharging state, respectively, Δt is the time difference between the two periods, Indicates the climbing rate when the battery is charged. Indicates the climbing rate when the battery is discharged.

[0055] HS operates in a similar way to batteries. It stores heat when there is a surplus of thermal energy and releases heat when there is a large demand for heat. It needs to meet capacity constraints, storage / release power constraints, and ramp rate constraints, namely:

[0056]

[0057] Where: is the heat storage / release of HS in period t; and are the heat storage / release power of HS in period t respectively;h is the HS energy self-loss coefficient, η tst.chr and η tst.dis are heat storage / release efficiency, respectively; and are the upper and lower limits of heat storage / release of HS respectively; and is the heat storage / release status flag of HS in period t, which is a 0-1 variable and satisfies the mutual exclusion constraint; and They are the upper and lower limits of HS heat storage and release power, and They are the upper and lower limits of HS heat storage / release ramp rate respectively.

[0058] In order to ensure the safe operation of the distribution network, the integrated energy system can maintain the balance of the power load in the system by purchasing or selling electricity from the external distribution network. However, in order to avoid affecting the stable operation of the distribution network, the integrated energy system cannot purchase and sell electricity from the grid at the same time, and the upper limit of its interaction power with the distribution network must comply with regulations within a certain range. The constraints are expressed as:

[0059]

[0060]

[0061] in, and is a 0-1 variable, indicating the state of RIES’s electricity purchase and sale in period t; and To buy / sell electric power; The upper limit of the power for purchasing and selling electricity.

[0062] The free carbon emission quota of RIES is determined through the baseline method, which considers that the carbon emission rights allocation in RIES mainly includes CCHP, GB and conventional power generation units.

[0063] C p =C h +C GB +C CCHP (twenty one)

[0064]

[0065] Among them, C h , C GB and C CCHP They are the free carbon emission quotas for external power grid purchase, GB and combined cooling, heating and power (CCHP); C pis the total RIES carbon emission allocation; N is the total number of carbon emission equipment; σ p and σ h are the electricity purchased per unit of electricity from the power grid and the carbon emission allocation per unit of heat in GB, σ p and σ h Take 0.728t / (MWh) and 0.102t / (GJ) respectively, F buy The amount of electricity purchased for external grid; is the conversion factor of power generation into heat supply, is the thermal power output of the waste heat boiler in period t.

[0066] The carbon trading cost of the regional integrated energy system is expressed as:

[0067]

[0068] Among them, c c is the carbon emission rights trading price; C p The carbon emission quota for the regional integrated energy system; E c is the actual carbon emissions of the regional comprehensive energy system, μ is the reward coefficient of different step-type carbon emission intervals, λ is the penalty coefficient of different step-type carbon emission intervals; h is the length of the value interval of different carbon emissions.

[0069] The carbon emissions of GB and CCHP are 0.065t / (GJ); the carbon emissions of coal-fired power plants are 1.08t / (MWh). In the model, several carbon emission intervals are defined. When it is negative, it means that the actual carbon emissions during this period are less than the allocated quota, and the energy supply company can sell the surplus carbon emission quota and obtain economic subsidies; When it is positive, it means that the actual carbon emissions during this period exceed the allocated quota, and the energy supply company needs to purchase the excess carbon emission quota to further limit carbon emissions. The larger the total carbon emissions range, the higher the carbon trading cost.

[0070] This application constructs an electricity-heat-cold integrated demand response model. The traditional demand response model only adjusts the electricity load curve, and generally stimulates users to change their electricity usage habits by adjusting price signals. In the RIES system, the loads are in various forms such as electricity, cold, and heat. Thermal energy and cold energy have temperature change lags and system inertia. Cold loads and hot loads can also participate in demand response optimization and regulation. In addition, in RIES, while electricity, cold, and heat loads are optimized and regulated in their own forms, coupled substitution can be achieved through energy conversion devices. The demand response model in this article first optimizes and adjusts the user's transferable load based on the adjustability of the three loads. Afterwards, the energy conversion device in RIES is used to achieve coupling and complementarity between electricity load, heat load, and cold load.

[0071] Electric load demand response, this application adopts price-based demand response to achieve load transfer, guides user-side electricity consumption in the form of time-of-use electricity prices, smoothes the load curve, achieves peak shaving and valley filling, and improves RIES operation reliability. The electricity quantity and price elasticity matrix method is the most widely used price-based IDR modeling method. The rate of change of electricity load and electricity price is expressed by the electricity quantity and price elasticity index, namely:

[0072]

[0073] Among them, m is the elasticity coefficient index of electricity quantity and price; L and c p are the electricity consumption and electricity price before demand response respectively; ΔL is the relative increase of electricity consumption L; Δc p The electricity price c p relative increase.

[0074] According to the ratio of time-of-use electricity price to fixed electricity price, the electricity quantity and price elasticity matrix τ is constructed. e .

[0075]

[0076] Where: τ mm and τ mn are the self-elastic coefficient and the cross-elastic coefficient respectively; L m and ΔL m is the response power and its relative increment in period m; c pm , Δc pm and c pn , Δc pn are the electricity prices and their relative increments in time periods m and n respectively. m and n are both power response times, 0≤m≤t, 0≤n≤t.

[0077] Flexible load is a transferable load, which means that the load can be transferred within a specified time according to the power demand of the user side. t The user-side electric load includes fixed electric load and transferable electric load, which can be expressed as:

[0078]

[0079] in: is the fixed load in period t, which has high reliability requirements and cannot be transferred; The load can be shifted during time period t. Users can adjust the power consumption and time according to the electricity price information, and the following constraints must be met:

[0080]

[0081] Where: is the upper limit of the transferable electric load at time t; R selThe total amount of transferable load in T time periods during the response period, that is, the total amount of transferable load is equal before and after the demand response. Due to the large change in load, the transferable load in this application is set to 20% of the total load.

[0082] Heat / cold load demand response, heat load has perception fuzziness and time delay, demand response mainly considers hot water load. Temperature is the main adjustment scale of heat load, users are less sensitive to it, changing temperature during the comfort period does not have much impact on users, and the acceptable range of water temperature is expressed as. Therefore, the demand response of controlling heat load is kept within a specific range [θ h,max ,θ h,min ],Right now:

[0083]

[0084] Where: Q t is the heat load power in period t; and are the upper and lower limits of the heat load power in the period t; α is the specific heat capacity of water, ρ w is the density of water; is the volume of cold water injected during period t; ε h,in The initial water temperature is 15℃, ε h,min is the lower limit of water temperature for heat load, ε h,max is the upper limit of water temperature for heat load, ρ w Represents the density of water.

[0085] The demand response principle of cooling load is similar to that of heating load. Considering the user's sensitivity to cooling load, the acceptable range of room temperature control is [ε c,max ,ε c,min ] Therefore, the demand response for controlling cooling load should also be kept within the characteristic range, which can be expressed as:

[0086]

[0087] Where W t is the cooling load power within t; and are the upper and lower limits of cooling load power in period t; is the outdoor temperature during period t; R d is the thermal resistance, take 18℃ / kW. c,max is the upper limit of room temperature for cooling load, ε c,min It is the lower limit of room temperature for cooling load.

[0088] The flexible heat / cooling load of this application is a transferable load. The user heat / cooling load includes fixed heat / cooling load and transferable heat / cooling load, which is expressed as:

[0089]

[0090] Where: Q t is the heat load in period t, W t is the cooling load in period t, and is the fixed heating / cooling load in period t; and is the transferable heat / cooling load within period t, satisfying the constraints:

[0091]

[0092]

[0093] Where: and is the upper limit of the transferable heat / cooling load within period t, R h,shl and R q,shl The total amount of heat / cooling load that can be transferred in T time periods, that is, the total amount of transferable load before and after the demand response is required to remain unchanged. Due to the high reliability requirements of heat / cooling load, the transferable load in this application is set to 10% of the total load.

[0094] Considering the green certificate-carbon trading mechanism and the multi-energy complementary optimization model of comprehensive demand response, by considering various energy storage modes, energy conversion models and multi-energy complementary characteristics, the optimal output plan of each co-production is jointly formulated from both the supply and demand sides. The RIES planning model of this application is a mixed integer linear programming problem, and the operating cost objective function is expressed as:

[0095]

[0096] Among them, F is the operating cost objective function value, V grid is the electricity purchase cost of the regional integrated energy system, V ng is the power generation cost of the gas turbine, V e is the battery charge and discharge loss cost, V b is the gas boiler operating cost, V d is the equipment operation and maintenance cost, V gc is the transaction cost of green certificates, is the carbon trading cost of the regional integrated energy system.

[0097] The electricity purchase cost is expressed as:

[0098] in, is the power purchased by the regional integrated energy system during period t, It is the unit electricity purchase price of the regional comprehensive energy system during the period t.

[0099] The power generation cost of the gas turbine is expressed as:

[0100] in, is the unit purchase price of natural gas in period t, is the natural gas power consumed by the gas turbine during period t, LHV gas It is the low calorific value of natural gas, generally 9.78kWh / m3.

[0101] The battery charge and discharge loss cost is expressed as:

[0102] in, represents the unit damage cost of the battery in period t, Indicates the battery charging status flag in period t. Indicates the discharge status flag of the battery in period t.

[0103] The gas boiler operating cost is expressed as:

[0104] in, represents the thermal power output of the gas turbine during period t, η gt Represents the thermal efficiency of the internal combustion turbine.

[0105] The equipment operation and maintenance cost is expressed as:

[0106] Among them, KV i′ is the unit operation and maintenance cost of equipment i′, It is the input power of device i' in period t. The devices include WHB, AR, AC, ES, HS, PV, WT, GT, GB, etc.

[0107] When the system's renewable energy power consumption responsibility weight is lower than the required value, the consumption responsible entity can purchase green certificates from the green certificate market to supplement the consumption volume. When the consumption responsibility weight is higher than the required value, the green certificates can be sold to earn profits.

[0108] The green certificate transaction cost is expressed as: V gc =v gc W gc (44)

[0109] Among them, v gc is the market price of green certificates, when W gc When W is positive gc is the amount of green certificates purchased, when W gc When W is negative gcis the amount of green certificates sold. Based on the historical transaction data of the green certificate subscription trading platform, considering the purchase and sale of wind power green certificates, the green certificate price is 0.1286 yuan / kWh (i.e. 128.6 yuan / piece), and the minimum consumption responsibility weight of renewable energy power is 12.5%.

[0110] The constraints of the operating cost objective function also include electric power balance constraints, thermal power balance constraints and cooling power balance constraints.

[0111] The electric power balance constraint is:

[0112]

[0113] in, is the electric power output of the wind turbine generator set during period t, is the electric power output by GT during period t, is the discharge power in period t, is the electric power output by the photovoltaic generator set during the period t, is the output power of the electric refrigerator during period t, is the power purchased in period t, is the electricity sold in period t, is the fixed load during period t, is the load shifted during period t, is the charging power during period t.

[0114] The thermal power balance constraint is:

[0115]

[0116] in, is the thermal power output of the waste heat boiler during period t, is the thermal power output of the gas boiler during period t, is the thermal power output of the absorption refrigerator during period t, is the heat release power output by the heat storage tank during period t, It represents the thermal storage power output by the thermal storage tank during the period t, represents the fixed heat load during the period t, It indicates the heat load that can be transferred during the period t.

[0117] The cooling power balance constraint is:

[0118]

[0119] in, represents the cooling power output by the absorption chiller during the period t, represents the cooling power output by the electric refrigerator during the period t, is the fixed cooling load in period t, is the transferable cooling load within period t.

[0120] The constraints of the operating cost objective function also include the renewable energy power consumption responsibility weight constraint. Considering the renewable energy power consumption responsibility weight constraint, the total amount of renewable energy power consumption and green certificate trading volume of the system should not be less than the total power consumption of the system under the consumption responsibility weight regulation. The formula is as follows:

[0121] C re +W gc ≥ω·C total (48)

[0122]

[0123] Where: ω is the responsibility weight of renewable energy power consumption; C total , C re They are the total system power and the power of renewable energy consumed (kWh), Contribute to the scenery.

[0124] Finally, this application proposes the following integrated model, which uses RIES multi-energy complementary optimization scheduling, called GC-CT-DR. The integrated model includes system equipment component constraint formula (1)-formula (20), carbon trading constraint formula (21)-formula (25), electricity-heat-cooling comprehensive demand response constraint formula (26)-formula (37), transmission constraint formula (45)-formula (47), and green certificate trading constraint formula (48)-formula (50).

[0125]

[0126] In order to verify the advantages of the RIES optimization scheduling model proposed in this application in terms of operation, improving the utilization rate of renewable energy, and smoothing the load curve under the comprehensive demand response and reward-penalty ladder carbon trading mechanism, this embodiment selected the energy system collection data of an enterprise cluster in a certain area of ​​Guangzhou, China in June 2023, including supply and demand data, unit equipment parameters, and load data, and performed a case simulation. Among them, the wind power and photovoltaic forecast data were re-forecasted using relevant models for the wind power and photovoltaic data in June 2023. The forecast output curve is as follows Figure 4 As shown. Figure 4 It can be seen that photovoltaic and wind power show complementary characteristics on a long time scale.

[0127] The user's cooling, heating and electricity loads use the prediction results provided by the park system, such as Figure 5The technical and cost parameters of each RIES device are shown in Table 1; the parameters of the energy storage system are shown in Table 2; and the carbon emission coefficients of related equipment are shown in Table 3. The peak and valley time-of-use electricity prices, time-of-use gas prices, and grid-connected electricity prices are based on data collected in a certain city in 2023, as shown in Table 1. Figure 6 shown.

[0128] Table 1 Technical and cost parameters of each equipment

[0129] Device Type Power upper and lower limits / kW Energy efficiency Unit operation and maintenance cost / (yuan / kW) gas turbine 0 / 1000 0.3 0.040 Waste heat boiler 0 / 1000 0.8 0.025 Gas boiler 0 / 1000 0.9 0.020 Absorption Chiller 0 / 800 1.2 0.025 Electric Refrigerator 0 / 1000 4 0.025 Fan —— 0.018 Photovoltaic —— 0.016 Purchase / sell electricity 0 / 1500 ——

[0130] Table 2 Energy storage system parameters

[0131]

[0132] Table 3 Carbon emission coefficients of relevant equipment

[0133] Device Type Carbon emission coefficient / (kg / kWh) gas turbine 0.7182 Gas boiler 0.359 Online electricity purchase 0.889

[0134] This application constructs a multi-energy complementary optimization scheduling model that takes into account green certificate-carbon trading and comprehensive demand response mechanism. It comprehensively considers the impact of factors such as renewable energy consumption responsibility weight constraints, green certificate trading, carbon emissions on system operation and the complex coupling relationship of multiple energy sources, and establishes a multi-energy complementary optimization model for electricity, gas, heat and cold. It also introduces a reward and punishment ladder carbon trading mechanism and a comprehensive demand response model to limit the system's carbon emissions, reduce operating costs, and improve energy utilization.

[0135] Based on the same inventive concept, the embodiment of the present application also provides an energy dispatching method based on green certificates and carbon trading mechanisms for realizing the energy dispatching system based on green certificates and carbon trading mechanisms involved above. The implementation scheme for solving the problem provided by this method is similar to the implementation scheme recorded in the above method, so the specific limitations in one or more embodiments of energy dispatching methods based on green certificates and carbon trading mechanisms provided below can be referred to the limitations on energy dispatching devices above, and will not be repeated here.

[0136] In an exemplary embodiment, the present application provides an energy scheduling method based on green certificates and carbon trading mechanisms, including:

[0137] Step 101: construct an operating cost objective function of a regional integrated energy system; the regional integrated energy system is a regional integrated energy system with complementary renewable energy sources, and the regional integrated energy system includes green certificate trading and carbon trading mechanisms.

[0138] Step 102: solving the operating cost objective function with the goal of minimizing the operating cost to obtain an operating plan for the regional integrated energy system.

[0139] The technical features of the above embodiments may be combined arbitrarily. To make the description concise, not all possible combinations of the technical features in the above embodiments are described. However, as long as there is no contradiction in the combination of these technical features, they should be considered to be within the scope of this specification.

[0140] This article uses specific examples to illustrate the principles and implementation methods of this application. The description of the above embodiments is only used to help understand the method and core ideas of this application. At the same time, for those skilled in the art, according to the ideas of this application, there will be changes in the specific implementation methods and application scope. In summary, the content of this specification should not be understood as limiting this application.

Claims

1. An energy dispatching system based on green certificates and carbon trading mechanism, characterized in that: The energy dispatching system based on green certificate and carbon trading mechanism includes: an operation cost objective function building module and an operation plan determination module; The operating cost objective function construction module is used to construct the operating cost objective function of the regional integrated energy system; the regional integrated energy system is a regional integrated energy system with complementary renewable energy, and the regional integrated energy system includes green certificate trading and carbon trading mechanisms; The operation plan determination module is used to solve the operation cost objective function with the goal of minimizing the operation cost, and obtain the operation plan of the regional integrated energy system.

2. The energy dispatching system based on green certificate and carbon trading mechanism according to claim 1 is characterized in that: The operating cost objective function is expressed as: Among them, F is the operating cost objective function value, V grid is the electricity purchase cost of the regional integrated energy system, V ng is the power generation cost of the gas turbine, V e is the battery charge and discharge loss cost, V b is the gas boiler operating cost, V d is the equipment operation and maintenance cost, V gc is the transaction cost of green certificates, is the carbon trading cost of the regional integrated energy system.

3. The energy dispatching system based on green certificate and carbon trading mechanism according to claim 2 is characterized in that: The electricity purchase cost is expressed as: in, is the power purchased by the regional integrated energy system during period t, is the unit electricity purchase price of the regional integrated energy system in the period t; The power generation cost of the gas turbine is expressed as: in, is the unit purchase price of natural gas in period t, is the natural gas power consumed by the gas turbine during period t, LHV gas It is the low calorific value of natural gas; The battery charge and discharge loss cost is expressed as: in, represents the unit damage cost of the battery in period t, Indicates the battery charging status flag in period t. Indicates the discharge status flag of the battery in period t; The gas boiler operating cost is expressed as: in, represents the thermal power output of the gas turbine during period t, η gt It represents the thermal efficiency of the internal gas turbine; The equipment operation and maintenance cost is expressed as: Among them, KV i is the unit operation and maintenance cost of equipment i, is the input power of device i during period t.

4. The energy dispatching system based on green certificate and carbon trading mechanism according to claim 2 is characterized in that: The green certificate transaction cost is expressed as: V gc =v gc W gc ; Among them, v gc is the market price of green certificates, when W gc When W is positive gc is the amount of green certificates purchased, when W gc When W is negative gc The amount of green certificates sold.

5. The energy dispatching system based on green certificate and carbon trading mechanism according to claim 2 is characterized in that: The carbon trading cost of the regional integrated energy system is expressed as: Among them, c c is the carbon emission rights trading price, C p The carbon emission quota for the regional integrated energy system; E c is the actual carbon emissions of the regional comprehensive energy system, μ is the reward coefficient of different step-type carbon emission intervals, λ is the penalty coefficient of different step-type carbon emission intervals; h is the length of the value interval of different carbon emissions.

6. The energy dispatching system based on green certificate and carbon trading mechanism according to claim 2 is characterized in that: The constraints of the operating cost objective function include gas turbine constraints, absorption chiller constraints, electric chiller constraints, battery constraints, thermal storage tank constraints, external distribution network constraints, electric load demand response constraints, and hot and cold load demand response constraints.

7. The energy dispatching system based on green certificate and carbon trading mechanism according to claim 6 is characterized in that: The constraints of the operating cost objective function also include electric power balance constraints, thermal power balance constraints and cooling power balance constraints.

8. The energy dispatching system based on green certificate and carbon trading mechanism according to claim 7 is characterized in that: The electric power balance constraint is: in, is the electric power output of the wind turbine generator set during period t, is the electric power output by GT during period t, is the discharge power in period t, is the electric power output by the photovoltaic generator set during the period t, is the output power of the electric refrigerator during period t, is the power purchased in period t, is the electricity sold in period t, is the fixed load during period t, is the load shifted during period t, is the charging power in period t; The thermal power balance constraint is: in, is the thermal power output of the waste heat boiler during period t, is the thermal power output of the gas boiler during period t, is the thermal power output of the absorption refrigerator during period t, is the heat release power output by the heat storage tank during period t, It represents the thermal storage power output by the thermal storage tank during the period t, represents the fixed heat load during the period t, represents the transferable heat load during period t; The cooling power balance constraint is: in, represents the cooling power output by the absorption chiller during the period t, represents the cooling power output by the electric refrigerator during the period t, is the fixed cooling load in period t, is the transferable cooling load within period t.

9. The energy dispatching system based on green certificate and carbon trading mechanism according to claim 1 is characterized in that: The regional integrated energy system includes a power supply system, a heating system and a cooling system; The power supply system is used to supply electric loads through external power grid, renewable energy and gas turbine power generation; The heating system is used to provide heat load through a gas boiler and a waste heat boiler; The cooling system is used to provide cooling load through an absorption refrigerator and an electric refrigerator.

10. An energy dispatching method based on green certificates and carbon trading mechanism, characterized in that: The energy dispatching method based on green certificates and carbon trading mechanism includes: Constructing an operating cost objective function of a regional integrated energy system; the regional integrated energy system is a regional integrated energy system with complementary renewable energy, and the regional integrated energy system includes green certificate trading and carbon trading mechanisms; The operation cost objective function is solved with the goal of minimizing the operation cost to obtain an operation plan for the regional integrated energy system.

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