County area energy supply configuration optimization method and system considering urbanization value

Abstract

The embodiment of the invention provides a county area energy supply configuration optimization method and system considering urbanization value, and the method comprises the steps: constructing an urbanization green energy utilization value index according to a modern energy system planning target and the relation between the energy demand and supply in an urbanization process; based on the urbanization green energy consumption value index and an energy supply equipment model in the county development process, taking the minimum county energy supply operation cost as an objective function, and constructing an electricity-gas-cold / heat multi-energy complementary county energy supply configuration optimization model; and solving the county energy supply configuration optimization model by constructing a constraint condition so as to obtain an optimal solution of a county energy supply configuration strategy. According to the method, the influence of urbanization value on county energy supply configuration optimization is considered, an electricity-gas-cold / hot county energy supply structure is optimized, the energy consumption cost is reduced, meanwhile, the proportion of clean energy is increased, reasonable configuration of multiple kinds of energy in the county can be achieved, and support is provided for urbanization promotion and energy structure optimization in the county.

Description

Technical Field

[0001] This document relates to the field of energy supply technology, and in particular to a method and system for optimizing county energy supply configuration taking into account the value of urbanization. Background Art

[0002] At present, there have been some studies on energy supply configuration optimization at home and abroad: Xie Min et al. proposed a low-carbon optimization scheduling method for urban integrated energy systems considering electricity-hydrogen-HCNG coupling and demand response under the framework of source-grid-load-hydrogen coordinated optimization; Zhang Xuan et al. proposed a transmission and distribution coordinated unit combination model considering the electricity-gas-heat integrated energy system, which fully tapped the flexible complementary potential of electricity, gas, and heat, and improved the energy utilization efficiency and the level of wind power consumption; Zhou et al. proposed a flexibility quantification framework customized for regional integrated energy systems participating in demand response, revealing the impact characteristics of system type and capacity on flexibility, and analyzing the sensitivity of flexibility to various uncertainty parameters. Although the existing results have proposed some methods for optimizing energy supply configuration, they are mainly aimed at energy configuration problems in rural or urban areas, and there is still a gap in energy configuration optimization for county areas. Summary of the invention

[0003] One or more embodiments of this specification provide a method for optimizing county energy supply configuration taking into account urbanization value, including:

[0004] According to the planning objectives of the modern energy system and the relationship between energy demand and supply in the urbanization process, the urbanization green energy value index is constructed;

[0005] Based on the urbanization green energy value index and the energy supply equipment model in the county development process, with the minimum county energy supply operation cost as the objective function, a county energy supply configuration optimization model with electricity-gas-cold / heat multi-energy complementarity is constructed;

[0006] The county energy supply configuration optimization model is solved by constructing constraint conditions to obtain the optimal solution of the county energy supply configuration strategy.

[0007] Furthermore, the specific method for constructing the urbanization green energy value index according to the planning objectives of the modern energy system and the relationship between energy demand and supply in the urbanization process is as follows:

[0008] Taking the minimum carbon emissions as an indicator, establish the objective function:

[0009]

[0010] in, and They are the electricity and gas purchases respectively;

[0011] Introduce a carbon emission penalty factor to convert carbon emissions into carbon emission penalty fees, as follows:

[0012]

[0013] Where f1 is the carbon emission penalty fee; G c (t) is the carbon emission of the system during period t; is the carbon emission penalty factor.

[0014] Furthermore, the energy supply equipment includes: CCHP units, boiler equipment, fuel cells, energy storage equipment and electric refrigerators; the energy supply equipment is modeled respectively as follows:

[0015] Modeling a CCHP unit:

[0016]

[0017] In the formula, λ CCHP (t) is the start / stop status of the CCHP unit, which takes the value of 1 or 0, 1 for start and 0 for stop; are the power generation, heating, cooling efficiency and heat self-dissipation rate of CCHP units respectively; LHV is the lower calorific value of natural gas, which is 9.7 (kW·h) / (N·m 3 ); The thermal power output of the waste heat boiler in the CCHP unit;

[0018] Modeling boiler equipment:

[0019]

[0020] In the formula, is the gas-heat conversion efficiency coefficient of the gas boiler; EB (t) is the start and stop status of the electric boiler; is the electric-to-heat conversion efficiency;

[0021] Modeling a fuel cell:

[0022]

[0023] In the formula, λ FC (t) is the start and stop state of the fuel cell; For the efficiency of power generation in the fuel pool;

[0024] Model energy storage devices, including electricity storage, heat storage, cold storage, and gas storage devices:

[0025]

[0026] Where N SOC∈{e,h,c,g}; The energy stored in the energy storage system during the period t, including electricity, heat, cold and gas; are the charging and discharging power of the energy storage in period t respectively; They are respectively the charging and discharging efficiency of energy storage;

[0027] Model an electric refrigerator:

[0028]

[0029] Where COP is the energy efficiency coefficient of the electric refrigerator.

[0030] Furthermore, the county energy supply operation cost includes the construction and operation cost of the power subsystem, thermal subsystem, cooling subsystem, and gas supply subsystem.

[0031] Furthermore, based on the urbanization green energy value index and the energy supply equipment model in the county development process, with the minimum county energy supply operation cost as the objective function, a county energy supply configuration optimization model with electricity-gas-cold / heat multi-energy complementarity is constructed as follows:

[0032] minF=ω1f1+ω2f2;

[0033]

[0034] C(t)=C e (t)+C h (t)+C c (t)+C g (t);

[0035] In the formula, f1 and f2 are urbanization value indicators, namely carbon emission penalty costs and construction and operation cost functions; ω1 and ω2 are weight coefficients of the two; C e (t), C h (t), C c (t), C g (t) are the construction and operation costs of the power subsystem, thermal subsystem, cooling subsystem, and gas supply subsystem respectively.

[0036] Furthermore, the constructed constraints include: subsystem energy balance constraints, equipment output constraints, equipment ramping constraints, energy storage constraints, and CCHP unit constraints;

[0037] When the energy supply system is running, it needs to meet the energy balance constraints of the four subsystems of electricity, heat, cooling and gas:

[0038]

[0039] Where: The power purchased from the large power grid for the county area; They are the actual outputs of photovoltaic, wind, fuel cell, CCHP unit, gas boiler, electric boiler and electric refrigerator; are the power consumption of electric refrigerator and electric boiler respectively; and They are the charging power and discharging power of various energy storage devices respectively; is the electricity, heating and cooling load demand. The above models are all in kW; The amount of natural gas purchased from the natural gas pipeline network in the county area; Gas consumption for fuel cells, gas boilers, and CCHP units; and They are the filling and deflation volumes of the gas storage equipment respectively; is the gas load demand; the unit is m 3 ;

[0040] The output of all devices in the system needs to meet the upper and lower output constraints, namely:

[0041]

[0042] Where, is the actual output value of the i-th type of equipment; P i min and P i max are the minimum and maximum output values ​​of the i-th type of equipment respectively;

[0043] All equipment in the system must meet the upper and lower output limits when climbing:

[0044] -r i,D Δt≤P i (t)-P i (t-1)≤r i,U Δt;

[0045] Where: r i,D and r i,U They are the rate limits for load shedding and loading of controllable output units respectively;

[0046] Electricity storage, heat storage, cold storage, and gas storage equipment meet the upper and lower limits of storage energy capacity:

[0047]

[0048] The cooling power output of CCHP unit is less than the heating power output of waste heat boiler:

[0049]

[0050] In the formula, and are the continuous start-up and shutdown time of the CCHP unit before the time period, respectively; and They are the minimum continuous startup and shutdown times required for CCHP units respectively.

[0051] Furthermore, the specific method for solving the county energy supply configuration optimization model is as follows:

[0052] The relevant parameters of the county energy supply equipment are input, and the county energy supply configuration optimization model is solved by calling CPLEX to obtain the optimal solution of the county energy supply configuration strategy.

[0053] One or more embodiments of this specification provide a county energy supply configuration optimization system taking into account urbanization value, including:

[0054] Index construction module: used to construct urbanization green energy value indicators based on the planning objectives of the modern energy system and the relationship between energy demand and supply in the urbanization process;

[0055] Model building module: used to build a county energy supply configuration optimization model with electricity, gas, cold / heat multi-energy complementation based on the urbanization green energy value index and the energy supply equipment model in the county development process, with the goal of minimizing the county energy supply operation cost;

[0056] Configuration optimization module: used to solve the county energy supply configuration optimization model by constructing constraint conditions, so as to obtain the optimal solution of the county energy supply configuration strategy.

[0057] Furthermore, the indicator construction module is specifically used for:

[0058] Taking the minimum carbon emissions as an indicator, establish the objective function:

[0059]

[0060] in, and They are the electricity and gas purchases respectively;

[0061] Introduce a carbon emission penalty factor to convert carbon emissions into carbon emission penalty fees, as follows:

[0062]

[0063] Where f1 is the carbon emission penalty fee; G c (t) is the carbon emission of the system during period t; is the carbon emission penalty factor.

[0064] Furthermore, the energy supply equipment includes: CCHP units, boiler equipment, fuel cells, energy storage equipment and electric refrigerators; the energy supply equipment is modeled respectively as follows:

[0065] Modeling a CCHP unit:

[0066]

[0067] In the formula, λ CCHP (t) is the start / stop status of the CCHP unit, which takes the value of 1 or 0, 1 for start and 0 for stop; are the power generation, heating, cooling efficiency and heat self-dissipation rate of CCHP units respectively; LHV is the lower calorific value of natural gas, which is 9.7 (kW·h) / (N·m 3 ); The thermal power output of the waste heat boiler in the CCHP unit;

[0068] Modeling boiler equipment:

[0069]

[0070] In the formula, is the gas-heat conversion efficiency coefficient of the gas boiler; EB (t) is the start and stop status of the electric boiler; is the electric-to-heat conversion efficiency;

[0071] Modeling a fuel cell:

[0072]

[0073] In the formula, λ FC (t) is the start and stop state of the fuel cell; For the efficiency of power generation in the fuel pool;

[0074] Model energy storage devices, including electricity storage, heat storage, cold storage, and gas storage devices:

[0075]

[0076] Where N SOC ∈{e,h,c,g}; The energy stored in the energy storage system during the period t, including electricity, heat, cold and gas; are the charging and discharging power of the energy storage in period t respectively; They are respectively the charging and discharging efficiency of energy storage;

[0077] Model an electric refrigerator:

[0078]

[0079] Where COP is the energy efficiency coefficient of the electric refrigerator.

[0080] Furthermore, the county energy supply operation cost includes the construction and operation cost of the power subsystem, thermal subsystem, cooling subsystem, and gas supply subsystem.

[0081] Furthermore, the county energy supply configuration optimization model of electricity-gas-cold / heat multi-energy complementarity constructed by the model building module is as follows:

[0082] minF=ω1f1+ω2f2;

[0083]

[0084] C(t)=C e (t)+C h (t)+C c (t)+C g (t);

[0085] In the formula, f1 and f2 are urbanization value indicators, namely carbon emission penalty costs and construction and operation cost functions; ω1 and ω2 are weight coefficients of the two; C e (t), C h (t), C c (t), C g (t) are the construction and operation costs of the power subsystem, thermal subsystem, cooling subsystem, and gas supply subsystem respectively.

[0086] Furthermore, the constraints include: subsystem energy balance constraints, equipment output constraints, equipment ramp constraints, energy storage constraints, and CCHP unit constraints;

[0087] When the energy supply system is running, it needs to meet the energy balance constraints of the four subsystems of electricity, heat, cooling and gas:

[0088]

[0089] Where: The power purchased from the large power grid for the county area; They are the actual outputs of photovoltaic, wind, fuel cell, CCHP unit, gas boiler, electric boiler and electric refrigerator; are the power consumption of electric refrigerator and electric boiler respectively; and They are the charging power and discharging power of various energy storage devices respectively; is the electricity, heating and cooling load demand. The above models are all in kW; The amount of natural gas purchased from the natural gas pipeline network in the county area; Gas consumption for fuel cells, gas boilers, and CCHP units; and They are the filling and deflation volumes of the gas storage equipment respectively; is the gas load demand; the unit is m 3 ;

[0090] The output of all devices in the system needs to meet the upper and lower output constraints, namely:

[0091]

[0092] Where, is the actual output value of the i-th type of equipment; P i min and P i max are the minimum and maximum output values ​​of the i-th type of equipment respectively;

[0093] All equipment in the system must meet the upper and lower output limits when climbing:

[0094] -r i,D Δt≤P i (t)-P i (t-1)≤r i,U Δt;

[0095] Where: r i,D and r i,U They are the rate limits for load shedding and loading of controllable output units respectively;

[0096] Electricity storage, heat storage, cold storage, and gas storage equipment meet the upper and lower limits of storage energy capacity:

[0097]

[0098] The cooling power output of CCHP unit is less than the heating power output of waste heat boiler:

[0099]

[0100] In the formula, and are the continuous start-up and shutdown time of the CCHP unit before the time period, respectively; and They are the minimum continuous startup and shutdown times required for CCHP units respectively.

[0101] Furthermore, the configuration optimization module is specifically used for:

[0102] The relevant parameters of the county energy supply equipment are input, and the county energy supply configuration optimization model is solved by calling CPLEX to obtain the optimal solution of the county energy supply configuration strategy.

[0103] One or more embodiments of the present specification provide an electronic device, including:

[0104] processor; and,

[0105] A memory arranged to store computer executable instructions, which, when executed, cause the processor to implement the steps of the above-mentioned county energy supply configuration optimization method based on urbanization value.

[0106] One or more embodiments of the present specification provide a storage medium for storing computer-executable instructions, which, when executed, implement the steps of the above-mentioned method for optimizing county energy supply configuration taking into account urbanization value.

[0107] By adopting the embodiment of the present invention, the impact of urbanization value on the optimization of county energy supply configuration is taken into account, the county energy supply structure of electricity-gas-cold / heat is optimized, the energy cost is reduced while the proportion of clean energy is increased, and the reasonable configuration of multiple energy sources such as electricity, gas, cold and heat loads in the county can be achieved to promote the urbanization process of the county, and provide support for promoting urbanization and energy structure optimization in the county area.

[0108] The above description is only an overview of the technical solution of the present invention. In order to more clearly understand the technical means of the present invention, it can be implemented according to the contents of the specification. In order to make the above and other purposes, features and advantages of the present invention more obvious and easy to understand, the specific implementation methods of the present invention are listed below. BRIEF DESCRIPTION OF THE DRAWINGS

[0109] In order to more clearly illustrate one or more embodiments of this specification or the technical solutions in the prior art, the drawings required for use in the embodiments or the description of the prior art will be briefly introduced below. Obviously, the drawings described below are only some embodiments recorded in this specification. For ordinary technicians in this field, other drawings can be obtained based on these drawings without paying creative labor.

[0110] Figure 1 A schematic diagram of a county energy supply system provided for one or more embodiments of this specification;

[0111] Figure 2 A flowchart of a method for optimizing county energy supply configuration taking into account urbanization value provided for one or more embodiments of this specification;

[0112] Figure 3 A schematic diagram of the composition of a county energy supply configuration optimization system taking into account urbanization value provided in one or more embodiments of this specification;

[0113] Figure 4A schematic diagram of the structure of an electronic device provided for one or more embodiments of this specification. DETAILED DESCRIPTION

[0114] In order to enable those skilled in the art to better understand the technical solutions in one or more embodiments of this specification, the following will be combined with the drawings in one or more embodiments of this specification to clearly and completely describe the technical solutions in one or more embodiments of this specification. Obviously, the described embodiments are only part of the embodiments of this specification, not all of the embodiments. Based on one or more embodiments of this specification, all other embodiments obtained by ordinary technicians in this field without creative work should fall within the scope of protection of this document.

[0115] Method Embodiment

[0116] According to the embodiment of the present invention, a method for optimizing the configuration of county energy supply taking into account the value of urbanization is provided, which reasonably configures multiple energy sources such as electricity, gas, cooling and heat loads in the county, promotes the urbanization process of the county, and optimizes the energy structure of the county area. The county energy supply system generally uses electricity and natural gas as the dominant energy sources, and can input energy through large power grids and natural gas pipelines. On the demand side, electricity, gas, cooling and heat loads are the main ones. The specific system framework is as follows: Figure 1 As shown, at the input end, electricity and natural gas are mainly input through the power grid and natural gas official website, and part of the electricity can also be input through distributed photovoltaic and decentralized wind power; at the conversion end, fuel cells and gas turbines can convert natural gas into electricity and thermal energy respectively. The CCHP system realizes the supply of electricity, thermal energy and cold energy through gas turbines, waste heat boilers and absorption refrigerators. Electric refrigerators, electric boilers and power-to-gas equipment can directly convert electricity into cold energy, thermal energy and natural gas energy respectively. Energy storage equipment includes electricity storage, heat storage, cold storage and gas storage equipment, which charge and discharge electricity, heat, cold and gas respectively, and have the function of energy caching; at the load end, it is the energy consumption link in the county. The needs of residents, industries and other users are mainly electricity, gas, cold and heat.

[0117] Figure 2 A flowchart of a county energy supply configuration optimization method taking into account urbanization value provided in one or more embodiments of this specification, such as Figure 2 As shown, the county energy supply configuration optimization method taking into account urbanization value according to an embodiment of the present invention specifically includes:

[0118] S1. Construct urbanization green energy value indicators based on the planning objectives of the modern energy system and the relationship between energy demand and supply in the urbanization process.

[0119] With the advancement of urbanization, the demand for energy has become more diversified and complex, which requires the energy system to not only meet the growing energy demand, but also to ensure the green, low-carbon and efficient use of energy to support the sustainable development of urbanization. Therefore, it is necessary to construct the urbanization green energy value index based on the planning goals of the modern energy system and the relationship between energy demand and supply in the urbanization process, considering that the emissions of the county energy system are mainly CO2, and taking the minimum carbon emissions as an indicator, establish the objective function:

[0120]

[0121] in, and They are the electricity and gas purchases respectively;

[0122] Considering the large amount of calculation required for solving multiple objectives, this embodiment introduces a carbon emission penalty factor to convert carbon emissions into carbon emission penalty fees, and converts carbon emission targets into economic targets, that is, converting multiple objectives into a single objective problem for solution. The specific calculation method for carbon penalty fees is:

[0123]

[0124] Where f1 is the carbon emission penalty fee, i.e., the system environmental cost; G c (t) is the carbon emission of the system during period t; is the carbon emission penalty factor, which is 0.028 yuan / kg.

[0125] S2. Based on the above-mentioned green energy value index of urbanization and the energy supply equipment model in the process of county development, with the minimum operation cost of county energy supply as the objective function, a county energy supply configuration optimization model with electricity, gas, cold / heat multi-energy complementarity is constructed.

[0126] By optimizing the scheduling of electricity, heat, cooling and gas systems in the energy system to coordinate the resources on the power generation side, while meeting the energy needs of users in the region and the various constraints in the system, various types of energy conversion and storage equipment are enabled to participate together, with the goal of minimizing the operating cost of county energy supply in the county energy system, which will also include the county urbanization value index converted into carbon penalty fees, and optimize the scheduling of the system.

[0127] It can be seen from the framework of the county energy supply system that the county energy supply and the mutual conversion between electricity, gas, cold and heat need to rely on various energy supply equipment, including: CCHP units, boiler equipment, fuel cells, energy storage equipment and electric refrigerators; the energy supply equipment is modeled separately, as follows:

[0128] Modeling a CCHP unit:

[0129]

[0130] In the formula, λ CCHP (t) is the start / stop status of the CCHP unit, which takes the value of 1 or 0, 1 for start and 0 for stop; are the power generation, heating, cooling efficiency and heat self-dissipation rate of CCHP units respectively; LHV is the lower calorific value of natural gas, which is 9.7 (kW·h) / (N·m 3 ); The thermal power output of the waste heat boiler in the CCHP unit;

[0131] Modeling boiler equipment:

[0132]

[0133] In the formula, is the gas-heat conversion efficiency coefficient of the gas boiler; EB (t) is the start and stop status of the electric boiler; is the electric-to-heat conversion efficiency;

[0134] Modeling a fuel cell:

[0135]

[0136] In the formula, λ FC (t) is the start and stop state of the fuel cell; For the efficiency of power generation in the fuel pool;

[0137] Model energy storage devices, including electricity storage, heat storage, cold storage, and gas storage devices:

[0138]

[0139] Where N SOC ∈{e,h,c,g}; The energy stored in the energy storage system during the period t, including electricity, heat, cold and gas; are the charging and discharging power of the energy storage in period t respectively; They are respectively the charging and discharging efficiency of energy storage;

[0140] Model an electric refrigerator:

[0141]

[0142] Where COP is the energy efficiency coefficient of the electric refrigerator.

[0143] The county energy supply operation cost includes the construction and operation cost of the power subsystem, thermal subsystem, cooling subsystem, and gas supply subsystem. Based on the urbanization green energy value index and the energy supply equipment model in the county development process, with the minimum county energy supply operation cost as the objective function, the county energy supply configuration optimization model with electricity-gas-cooling / heat multi-energy complementarity is constructed as follows:

[0144] minF=ω1f1+ω2f2;

[0145]

[0146] C(t)=C e (t)+C h (t)+C c (t)+C g (t);

[0147] In the formula, f1 and f2 are urbanization value indicators, namely carbon emission penalty costs and construction and operation cost functions; ω1 and ω2 are weight coefficients of the two; C e (t), C h (t), C c (t), C g (t) are the construction and operation costs of the power subsystem, thermal subsystem, cooling subsystem, and gas supply subsystem respectively. The specific calculation methods for the construction and operation costs of the power subsystem, thermal subsystem, cooling subsystem, and gas supply subsystem are as follows:

[0148] 1) Power subsystem

[0149] The total cost of the power system is composed of the initial construction cost depreciation, operation and maintenance costs, unit start-up and shutdown costs, and the cost of purchasing electricity from the external main grid during the dispatch period of wind and solar clean energy units, fuel cells, CCHP units, and power storage equipment:

[0150] C e (t) = C C / e (t)+C M / e (t)+C S / e (t)+C B / e (t);

[0151]

[0152] Where: N is the number of devices; C C,n , C λ,n , T n 、V n , C n , P n (t), C SS,nare the initial investment cost per unit capacity, capacity, lifespan, residual value, operation and maintenance cost coefficient per unit output, power generation, and start-up and shutdown cost coefficient of the nth equipment; U n is the start / stop status of the device, which can be 1 or 0, 1 means the device is in operation, and 0 means it is in shutdown; c e (t) is the external main grid electricity sales price during the period.

[0153] 2) Thermal subsystem

[0154] The total cost of the thermal system is composed of the initial construction cost depreciation, operation and maintenance costs, and unit start-up and shutdown costs of gas boilers, CCHP units, electric boilers, and heat storage equipment during the dispatch period:

[0155] C h (t) = C C / h (t)+C M / h (t)+C S / h (t);

[0156] Where: C C / h (t), C M / h (t), C S / h (t) are the depreciation of the initial construction cost, operation and maintenance cost, unit start-up and shutdown cost, and external heat purchase cost of the thermal system. The calculation formulas for the depreciation of the initial construction cost, operation and maintenance cost, and unit start-up and shutdown cost are similar to those of the power system.

[0157] 3) Cooling subsystem

[0158] The total cost of the cooling system is composed of the initial construction cost depreciation, operation and maintenance costs, and unit start-up and shutdown costs of the CCHP units, electric refrigeration units, and cold storage equipment during the dispatch period:

[0159] C c (t) = C C / c (t)+C M / c (t)+C S / c (t);

[0160] Where: C C / c (t), C M / c (t), C S / c (t) are the depreciation of the initial construction cost, operation and maintenance cost, and start-up and shutdown cost of the cooling system. The calculation formula is similar to that of the power system.

[0161] 4) Air supply subsystem

[0162] The total cost of the gas supply system is composed of the depreciation of the initial construction cost of the power-to-gas equipment and gas storage equipment during the scheduling period, the operation and maintenance cost, the unit start-up and shutdown cost, and the cost of purchasing gas from the external gas network. The cost of purchasing gas from the external gas network is determined by the gas load of county users and the gas load of energy conversion equipment using gas as fuel in the integrated energy system.

[0163] C g (t) = C C / g (t)+C M / g (t)+C S / g (t)+C B / g (t);

[0164] Where: C C / g (t), C M / g (t), C S / g (t), C B / g (t) are the depreciation of the initial construction cost, operation and maintenance cost, unit start-up and shutdown cost, and external gas purchase cost of the gas supply system. The calculation formulas for the initial construction cost, operation and maintenance cost, and unit start-up and shutdown cost are analogous to those of the power system.

[0165]

[0166] Where: c g (t) is the natural gas price.

[0167] S3. Solve the county energy supply configuration optimization model by constructing constraint conditions to obtain the optimal solution of the county energy supply configuration strategy.

[0168] The constraints constructed include: subsystem energy balance constraints, equipment output constraints, equipment ramp constraints, energy storage constraints, and CCHP unit constraints;

[0169] Subsystem energy balance constraints:

[0170] When the energy supply system is running, it needs to meet the energy balance constraints of the four subsystems of electricity, heat, cooling and gas:

[0171]

[0172] Where: The power purchased from the large power grid for the county area; They are the actual outputs of photovoltaic, wind, fuel cell, CCHP unit, gas boiler, electric boiler and electric refrigerator; are the power consumption of electric refrigerator and electric boiler respectively; and They are the charging power and discharging power of various energy storage devices respectively; is the electricity, heating and cooling load demand; the unit of the above models is kW; The amount of natural gas purchased from the natural gas pipeline network in the county area; Gas consumption for fuel cells, gas boilers, and CCHP units; and They are the filling and deflation volumes of the gas storage equipment respectively; is the gas load demand; the unit is m 3 .

[0173] Equipment output constraints:

[0174] The output of all devices in the system needs to meet the upper and lower output constraints, namely:

[0175]

[0176] Where, is the actual output value of the i-th type of equipment; P i min and P i max are the minimum and maximum output values ​​of the i-th type of equipment respectively.

[0177] Equipment climbing constraints:

[0178] All equipment in the system must meet the upper and lower output limits when climbing:

[0179] -r i,D Δt≤P i (t)-P i (t-1)≤r i,U Δt;

[0180] Where: r i,D and r i,U They are the rate limits for load shedding and loading of controllable output units respectively.

[0181] Energy storage constraints:

[0182] In order to ensure the normal operation of energy storage equipment, electricity storage, heat storage, cold storage, and gas storage equipment are required to meet the upper and lower limits of storage energy capacity:

[0183]

[0184] CCHP unit constraints:

[0185] The cooling power output of the CCHP unit is generated by the conversion of the waste heat of the gas turbine through the absorption chiller, so the cooling power output must be less than the heat power output of the waste heat boiler:

[0186]

[0187] In the formula, and are the continuous start-up and shutdown time of the CCHP unit before the time period, respectively; and They are the minimum continuous start-up and shutdown times required for the CCHP unit, respectively, which are set to 3h in this embodiment.

[0188] The county energy supply configuration optimization model is solved by the following method:

[0189] The relevant parameters of the county energy supply equipment are input, and the county energy supply configuration optimization model is solved by calling CPLEX to obtain the optimal solution of the county energy supply configuration strategy.

[0190] The decision variables for optimizing the operation configuration of the county energy supply system include continuous variables and 0-1 variables, which is a mixed integer optimization problem. The real-time output of the unit is the decision variable. Since the relationship between the real-time output of the gas unit and the gas turbine and the natural gas energy consumption is a quadratic function, the optimization model includes quadratic constraint programming, which is a mixed integer quadratic constraint programming problem. The present invention divides the energy consumption function into multiple segments, uses a linear function to represent the energy consumption function, and converts the quadratic optimization into a linear optimization problem. Through linearization processing, the integer quadratic constraint programming problem can be converted into a mixed integer programming (Mixed integer programming, MIP) problem, and the CPLEX solver in the Matlab software is used to quickly solve it. The specific solution process is as follows:

[0191] Step 1: Input data. Based on the light intensity and wind speed, combined with the power generation model, the typical day maximum output of the clean energy power generation system is obtained; at the same time, combined with the actual load data of the county, the typical day demand of various types of loads in the county is predicted, and the basic data such as the basic electricity and natural gas prices, the clean energy cost per kilowatt-hour and the subsidy cost are obtained by comprehensive conversion based on the external market price.

[0192] Step 2: Set the objective function and constraints. In the county energy supply system, the total system cost is minimized, the total cost and total benefit of the power subsystem, thermal subsystem, cooling subsystem and gas supply subsystem are considered, and the electricity, gas, cooling / heating load balance constraints, energy storage equipment constraints and other related constraints are set.

[0193] Step 3: Call CPLEX for solving. CPLEX is a mathematical optimization technology that can express complex business problems as mathematical programming models and solve them to improve efficiency, quickly implement strategies, and increase profitability.

[0194] Step 4: Find the energy configuration and operation optimization strategy of the county energy supply system.

[0195] The beneficial effects of the present invention are as follows:

[0196] The present invention takes into account the impact of urbanization value on the optimization of county energy supply configuration, optimizes the county energy supply structure of electricity-gas-cold / heat, reduces energy costs while increasing the proportion of clean energy, and can achieve reasonable configuration of multiple energy sources such as county electricity, gas, cold and heat loads to promote the county urbanization process, providing support for promoting urbanization and energy structure optimization in county areas.

[0197] System Example

[0198] According to an embodiment of the present invention, a county energy supply configuration optimization system taking into account urbanization value is provided. Figure 3 A schematic diagram of a county energy supply configuration optimization system taking into account urbanization value provided in one or more embodiments of this specification, such as Figure 3 As shown, the county energy supply configuration optimization system taking into account urbanization value according to an embodiment of the present invention specifically includes:

[0199] Indicator construction module 30: used to construct urbanization green energy value indicators based on the planning objectives of the modern energy system and the relationship between energy demand and supply in the urbanization process;

[0200] Model building module 32: used to build a county energy supply configuration optimization model with electricity-gas-cold / heat multi-energy complementation based on the urbanization green energy value index and the energy supply equipment model in the county development process, with the goal of minimizing the county energy supply operation cost;

[0201] Configuration optimization module 34: used to solve the county energy supply configuration optimization model by constructing constraint conditions, so as to obtain the optimal solution of the county energy supply configuration strategy.

[0202] The embodiment of the present invention is a system embodiment corresponding to the above-mentioned method embodiment. The specific operations of each module can be understood by referring to the description of the method embodiment, which will not be repeated here.

[0203] Device Example 1

[0204] An embodiment of the present invention provides an electronic device, such as Figure 4 As shown, it includes: a memory 40, a processor 42, and a computer program stored in the memory 40 and executable on the processor 42. When the computer program is executed by the processor 42, the following method steps are implemented:

[0205] S1. Construct the urbanization green energy value index based on the planning objectives of the modern energy system and the relationship between energy demand and supply in the urbanization process;

[0206] S2. Based on the urbanization green energy value index and the energy supply equipment model in the county development process, with the minimum county energy supply operation cost as the objective function, a county energy supply configuration optimization model with electricity-gas-cold / heat multi-energy complementarity is constructed;

[0207] S3. Solve the county energy supply configuration optimization model by constructing constraint conditions to obtain the optimal solution of the county energy supply configuration strategy.

[0208] Device Example 2

[0209] An embodiment of the present invention provides a computer-readable storage medium, on which a program for implementing information transmission is stored. When the program is executed by the processor 42, the following method steps are implemented:

[0210] S1. Construct the urbanization green energy value index based on the planning objectives of the modern energy system and the relationship between energy demand and supply in the urbanization process;

[0211] S2. Based on the urbanization green energy value index and the energy supply equipment model in the county development process, with the minimum county energy supply operation cost as the objective function, a county energy supply configuration optimization model with electricity-gas-cold / heat multi-energy complementarity is constructed;

[0212] S3. Solve the county energy supply configuration optimization model by constructing constraint conditions to obtain the optimal solution of the county energy supply configuration strategy.

[0213] The computer-readable storage medium in this embodiment includes, but is not limited to, ROM, RAM, magnetic disk or optical disk, etc.

[0214] Finally, it should be noted that the above embodiments are only used to illustrate the technical solutions of the present invention, rather than to limit it. Although the present invention has been described in detail with reference to the aforementioned embodiments, those skilled in the art should understand that they can still modify the technical solutions described in the aforementioned embodiments, or replace some or all of the technical features therein with equivalents. However, these modifications or replacements do not cause the essence of the corresponding technical solutions to deviate from the scope of the technical solutions of the embodiments of the present invention.

Claims

1. A county energy supply configuration optimization method taking into account urbanization value, characterized in that: include: According to the planning objectives of the modern energy system and the relationship between energy demand and supply in the urbanization process, the urbanization green energy value index is constructed; Based on the urbanization green energy value index and the energy supply equipment model in the county development process, with the minimum county energy supply operation cost as the objective function, a county energy supply configuration optimization model with electricity-gas-cold / heat multi-energy complementarity is constructed; The county energy supply configuration optimization model is solved by constructing constraint conditions to obtain the optimal solution of the county energy supply configuration strategy.

2. The method according to claim 1, characterized in that The specific method for constructing the urbanization green energy value index based on the planning objectives of the modern energy system and the relationship between energy demand and supply in the urbanization process is as follows: Taking the minimum carbon emissions as an indicator, establish the objective function: in, and They are the electricity and gas purchases respectively; Introduce a carbon emission penalty factor to convert carbon emissions into carbon emission penalty fees, as follows: Where f1 is the carbon emission penalty fee; G c (t) is the carbon emission of the system during period t; is the carbon emission penalty factor.

3. The method according to claim 2, characterized in that The energy supply equipment includes: CCHP unit, boiler equipment, fuel cell, energy storage equipment and electric refrigerator; the energy supply equipment is modeled as follows: Modeling a CCHP unit: In the formula, λ CCHP (t) is the start / stop status of the CCHP unit, which takes the value of 1 or 0, 1 for start and 0 for stop; are the power generation, heating, cooling efficiency and heat self-dissipation rate of CCHP units respectively; LHV is the lower calorific value of natural gas, which is 9.7 (kW·h) / (N·m 3 ); The thermal power output of the waste heat boiler in the CCHP unit; Modeling boiler equipment: In the formula, is the gas-heat conversion efficiency coefficient of the gas boiler; EB (t) is the start and stop status of the electric boiler; is the electric-to-heat conversion efficiency; Modeling a fuel cell: In the formula, λ FC (t) is the start and stop state of the fuel cell; For the efficiency of power generation in the fuel pool; Model energy storage devices, including electricity storage, heat storage, cold storage, and gas storage devices: Where N SOC ∈{e,h,c,g}; The energy stored in the energy storage system during the period t, including electricity, heat, cold and gas; are the charging and discharging power of the energy storage in period t respectively; are the charging and discharging efficiencies of energy storage, respectively; Model an electric refrigerator: Where COP is the energy efficiency coefficient of the electric refrigerator.

4. The method according to claim 3, characterized in that The county energy supply and operation costs include the construction and operation costs of the power subsystem, thermal subsystem, cooling subsystem, and gas supply subsystem.

5. The method according to claim 4, characterized in that Based on the urbanization green energy value index and the energy supply equipment model in the county development process, with the minimum county energy supply operation cost as the objective function, a county energy supply configuration optimization model with electricity-gas-cold / heat multi-energy complementarity is constructed as follows: minF=ω1f1+ω2f2; C(t)=C e (t)+C h (t)+C c (t)+C g (t); In the formula, f1 and f2 are urbanization value indicators, namely carbon emission penalty costs and construction and operation cost functions; ω1 and ω2 are weight coefficients of the two; C e (t), C h (t), C c (t), C g (t) are the construction and operation costs of the power subsystem, thermal subsystem, cooling subsystem, and gas supply subsystem respectively.

6. The method according to claim 1, characterized in that The constraints constructed include: subsystem energy balance constraints, equipment output constraints, equipment ramp constraints, energy storage constraints, and CCHP unit constraints; When the energy supply system is running, it needs to meet the energy balance constraints of the four subsystems of electricity, heat, cooling and gas: Where: The power purchased from the large power grid for the county area; They are the actual outputs of photovoltaic, wind, fuel cell, CCHP unit, gas boiler, electric boiler and electric refrigerator; are the power consumption of electric refrigerator and electric boiler respectively; and They are respectively the charging power and discharging power of various energy storage devices; is the electricity, heating and cooling load demand. The above models are all in kW; The amount of natural gas purchased from the natural gas pipeline network in the county area; Gas consumption for fuel cells, gas boilers, and CCHP units; and They are the filling and deflation volumes of the gas storage equipment respectively; is the gas load demand; the unit is m 3 ; The output of all devices in the system needs to meet the upper and lower output constraints, namely: Where, is the actual output value of the i-th type of equipment; P i min and P i max are the minimum and maximum output values ​​of the i-th type of equipment respectively; All equipment in the system must meet the upper and lower output limits when climbing: -r i,D Δt≤P i (t)-P i (t-1)≤r i,U Δt; Where: r i,D and r i,U They are the rate limits for load shedding and loading of controllable output units respectively; Electricity storage, heat storage, cold storage, and gas storage equipment meet the upper and lower limits of storage energy capacity: The cooling power output of CCHP unit is less than the heating power output of waste heat boiler: In the formula, and are the continuous start-up and shutdown time of the CCHP unit before the time period, respectively; and They are the minimum continuous startup and shutdown times required for CCHP units respectively.

7. The method according to claim 1, characterized in that The specific method for solving the county energy supply configuration optimization model is as follows: The relevant parameters of the county energy supply equipment are input, and the county energy supply configuration optimization model is solved by calling CPLEX to obtain the optimal solution of the county energy supply configuration strategy.

8. A county energy supply configuration optimization system taking into account the value of urbanization, characterized in that: include: Index construction module: used to construct urbanization green energy value indicators based on the planning objectives of the modern energy system and the relationship between energy demand and supply in the urbanization process; Model building module: used to build a county energy supply configuration optimization model with electricity, gas, cold / heat multi-energy complementation based on the urbanization green energy value index and the energy supply equipment model in the county development process, with the goal of minimizing the county energy supply operation cost; Configuration optimization module: used to solve the county energy supply configuration optimization model by constructing constraint conditions, so as to obtain the optimal solution of the county energy supply configuration strategy.

9. The system according to claim 8, characterized in that The indicator construction module is specifically used for: Taking the minimum carbon emissions as an indicator, establish the objective function: in, and They are the electricity and gas purchases respectively; Introduce a carbon emission penalty factor to convert carbon emissions into carbon emission penalty fees, as follows: Where f1 is the carbon emission penalty fee; G c (t) is the carbon emission of the system during period t; is the carbon emission penalty factor.

10. The system according to claim 9, characterized in that The energy supply equipment includes: CCHP units, boiler equipment, fuel cells, energy storage equipment and electric refrigerators; the energy supply equipment is modeled as follows: Modeling a CCHP unit: In the formula, λ CCHP (t) is the start / stop status of the CCHP unit, which takes the value of 1 or 0, 1 for start and 0 for stop; are the power generation, heating, cooling efficiency and heat self-dissipation rate of CCHP units respectively; LHV is the lower calorific value of natural gas, which is 9.7 (kW·h) / (N·m 3 ); The thermal power output of the waste heat boiler in the CCHP unit; Modeling boiler equipment: In the formula, is the gas-heat conversion efficiency coefficient of the gas boiler; EB (t) is the start and stop status of the electric boiler; is the electric-to-heat conversion efficiency; Modeling a fuel cell: In the formula, λ FC (t) is the start and stop state of the fuel cell; For the efficiency of power generation in the fuel pool; Model energy storage devices, including electricity storage, heat storage, cold storage, and gas storage devices: Where N SOC ∈{e,h,c,g}; The energy stored in the energy storage system during the period t, including electricity, heat, cold and gas; are the charging and discharging power of the energy storage in period t respectively; are the charging and discharging efficiencies of energy storage, respectively; Model an electric refrigerator: Where COP is the energy efficiency coefficient of the electric refrigerator.

11. The system according to claim 10, characterized in that The county energy supply and operation costs include the construction and operation costs of the power subsystem, thermal subsystem, cooling subsystem, and gas supply subsystem.

12. The system according to claim 11, characterized in that The county energy supply configuration optimization model of electricity-gas-cold / heat multi-energy complementarity constructed by the model building module is as follows: minF=ω1f1+ω2f2; C(t)=C e (t)+C h (t)+C c (t)+C g (t); In the formula, f1 and f2 are urbanization value indicators, namely carbon emission penalty costs and construction and operation cost functions; ω1 and ω2 are weight coefficients of the two; C e (t), C h (t), C c (t), C g (t) are the construction and operation costs of the power subsystem, thermal subsystem, cooling subsystem, and gas supply subsystem respectively.

13. The system according to claim 8, characterized in that The constraints include: subsystem energy balance constraints, equipment output constraints, equipment ramp constraints, energy storage constraints and CCHP unit constraints; When the energy supply system is running, it needs to meet the energy balance constraints of the four subsystems of electricity, heat, cooling and gas: Where: The power purchased from the large power grid for the county area; They are the actual outputs of photovoltaic, wind, fuel cell, CCHP unit, gas boiler, electric boiler and electric refrigerator; are the power consumption of electric refrigerator and electric boiler respectively; and They are respectively the charging power and discharging power of various energy storage devices; is the electricity, heating and cooling load demand. The above models are all in kW; The amount of natural gas purchased from the natural gas pipeline network in the county area; Gas consumption for fuel cells, gas boilers, and CCHP units; and They are the filling and deflation volumes of the gas storage equipment respectively; is the gas load demand; the unit is m 3 ; The output of all devices in the system needs to meet the upper and lower output constraints, namely: Where, is the actual output value of the i-th type of equipment; P i min and P i max are the minimum and maximum output values ​​of the i-th type of equipment respectively; All equipment in the system must meet the upper and lower output limits when climbing: -r i,D Δt≤P i (t)-P i (t-1)≤r i,U Δt; Where: r i,D and r i,U They are the rate limits for load shedding and loading of controllable output units respectively; Electricity storage, heat storage, cold storage, and gas storage equipment meet the upper and lower limits of storage energy capacity: The cooling power output of CCHP unit is less than the heating power output of waste heat boiler: In the formula, and are the continuous start-up and shutdown time of the CCHP unit before the time period, respectively; and They are the minimum continuous startup and shutdown times required for CCHP units respectively.

14. The system according to claim 8, characterized in that The configuration optimization module is specifically used for: The relevant parameters of the county energy supply equipment are input, and the county energy supply configuration optimization model is solved by calling CPLEX to obtain the optimal solution of the county energy supply configuration strategy.

15. An electronic device, characterized in that: include: processor; as well as, A memory arranged to store computer executable instructions, which, when executed, cause the processor to implement the steps of the method for optimizing county energy supply configuration taking into account urbanization value as described in any one of claims 1 to 7.

16. A storage medium, characterized in that: Used to store computer executable instructions, which, when executed, implement the steps of the county energy supply configuration optimization method taking into account urbanization value as described in any one of claims 1 to 7.

Images