CN-121998388-A - Low-carbon operation optimization method and system for electric power system

CN121998388ACN 121998388 ACN121998388 ACN 121998388ACN-121998388-A

Abstract

The invention discloses a low-carbon operation optimization method and system of an electric power system, wherein the method comprises the steps of constructing a price type demand response model capable of reducing load and transferring load and a substitution type demand response model for mutual conversion of electric energy and heat energy based on a comprehensive energy management system architecture; the method comprises the steps of establishing an energy supply side multi-energy coupling equipment operation model, introducing a green certificate and stepped carbon transaction mutual recognition mechanism, establishing a green certificate-stepped carbon transaction mathematical model, establishing a demand response optimization scheduling model of a comprehensive energy system under the green certificate-stepped carbon transaction mechanism by taking the minimum total cost of system operation as a target, and carrying out optimization solution on the model to obtain a multi-target collaborative power system operation optimal scheme. The invention realizes the cooperative optimization of demand response, green evidence and carbon transaction mechanism, effectively cuts peaks and fills valleys, reduces the system operation cost and carbon emission, and provides decision support for low-carbon operation of a novel power system.

Inventors

LI JIA
XU TIANFU
RAO ZHEN
HE WEI
WEI ZETAO
HE HAO

Assignees

国网江西省电力有限公司电力科学研究院

Dates

Publication Date: 20260508
Application Date: 20260410

Claims (10)

1. A method for optimizing low-carbon operation of an electric power system, comprising: constructing a comprehensive energy management system architecture considering load side demand response; Based on the comprehensive energy management system architecture, taking the behavior characteristics of a load side user into consideration, constructing a price type demand response model capable of reducing load and transferring load and a substitution type demand response model for mutual conversion of electric energy and heat energy; Based on a price type demand response model and a substitution type demand response model, an energy supply side equipment operation model is established, and based on the energy supply side equipment operation model, a mutual recognition mechanism of green certificate and step carbon transaction is introduced, and a green certificate-step carbon transaction mathematical model is established; Based on the green evidence-step carbon transaction mathematical model, taking the minimum total cost of system operation as a target, and taking power balance, upper and lower equipment operation limits, climbing constraint and energy storage equipment dynamic feasibility domain constraint into consideration, constructing a demand response optimization scheduling model of the comprehensive energy system under the green evidence-step carbon transaction mechanism; and carrying out optimization solution on the demand response optimization scheduling model to obtain a multi-objective collaborative power system operation optimal scheme.
2. The method for optimizing low-carbon operation of an electric power system according to claim 1, wherein the constructing an integrated energy management system architecture taking into account load-side demand response comprises: the comprehensive energy management system framework comprising an energy supply side, an energy storage side, a load side and an external energy network is constructed, wherein the energy supply side comprises a cogeneration device, a gas boiler, a heat pump and a kalina cycle, the energy storage side comprises electric energy storage and thermal energy storage, the load side comprises electric load and thermal load, and the external energy network comprises an upper power grid and an upper air network.
3. The method of optimizing low-carbon operation of an electrical power system of claim 1, wherein the price-type demand response model comprises a load-reducible model and a load-transferable model, wherein the load-reducible model satisfies a capacity-reducing constraint, a cumulative attenuation constraint, and a continuous reduction constraint; the expression of the load shedding model is as follows: , , in the formula, For the load-reducible actual power consumption after the period t is reduced, Reference electric power that can cut down the load for the period t, The load reduction amount for the period t of time that can be reduced, The price response coefficient of the load can be cut down for the time period t, For a real-time electricity price of time period t, As the reference electricity price for the time period t, In order to cut down the price sensitive index of the load, The maximum reducible amount by which the load can be reduced for the time period t; The expression of the transferable load model is as follows: , , , in the formula, For a period t the actual power used by the load can be transferred, Reference power for the period t for which the load can be transferred, For transferable load power in which period t transitions from another period, For transferable load power that is diverted from other periods for period t, To be a price response coefficient for transferable loads, for characterizing load transfer intensity, For the average power rate over the scheduling period.
4. The method of optimizing low-carbon operation of an electrical power system of claim 1, wherein the surrogate demand response model satisfies a maximum surrogate load amount constraint; the expression of the alternative demand response model is as follows: , , in the formula, As an alternative to the amount of electrical load, For the electric heat substitution coefficient, In order to be able to replace the amount of heat load, Is the unit heat value of the electric energy, Is the energy utilization rate of the electric energy, Is the unit heat value of the heat energy, The energy utilization rate of the heat energy; The expression of the maximum replaceable load constraint is: , in the formula, 、 Respectively the minimum substitution amount and the maximum substitution amount of the replaceable electric load, 、 The minimum substitution amount and the maximum substitution amount of the replaceable heat load are respectively.
5. The low-carbon operation optimization method of an electric power system according to claim 1, wherein the energy supply side equipment operation model comprises an electric output power model and a heat output power model of a gas turbine in a cogeneration unit, and the expression is: , , in the formula, For the power generation efficiency of the gas turbine under the rated working condition, For the gas input power of the gas turbine during the time period t, For the maximum gas input power of the gas turbine, Is the exhaust waste heat proportionality coefficient of the gas turbine under the rated working condition, For the electrical output power of the gas turbine, And The partial load correction coefficients of the electromechanical efficiency of the gas turbine are respectively, For the heat output of the gas turbine, And Partial load correction coefficients of exhaust waste heat of the gas turbine are respectively obtained; The energy supply side equipment operation model also comprises an energy distribution model of a gas turbine after introducing kalina circulation and a heat pump, and the expression is as follows: , in the formula, Is that The electric power flowing into the heat pump unit by the gas turbine at the moment, Is a gas turbine The electrical power flowing to the electrical energy subsystem at the moment, Is that The thermal power input into the waste heat boiler by the gas turbine at any time, Is a gas turbine The thermal power of the kalina cycle is input at the moment; The energy supply side equipment operation model also comprises an electric output power model and a heat output power model of the cogeneration unit after the kalina cycle and the heat pump are introduced, and the expression is as follows: , in the formula, For supplying energy to side cogeneration unit The electric and thermal output power at the moment, Is a kalina cycle The electric power output at the moment of time, For supplying energy to side cogeneration unit The electric and thermal output power at the moment, Is a waste heat boiler The thermal power output at the moment of time, Is a heat pump The thermal power output at the moment; the energy supply side equipment operation model also comprises an energy conversion model of a kalina cycle, a waste heat boiler, a heat pump and a gas boiler, and the expression is as follows: , , , , , , , in the formula, Is that Low-temperature waste heat discharged by the kalina cycle at the moment, Is a kalina cycle waste heat proportionality coefficient, Is the kalina cycle thermoelectric conversion efficiency, Is that Waste heat entering the waste heat boiler at any time, Is that The steam output by the waste heat boiler at any time, Is the heat exchange efficiency of the waste heat boiler, Is that The heat power output by the heat pump unit at the moment, Is the coefficient of performance of the heat pump unit, Is that The electric power consumed by the heat pump unit at the moment, Is that The heat power output by the gas boiler at the moment, Is the heat efficiency of the gas-fired boiler, Is that Consumption of natural gas of the gas boiler at any moment; the energy supply side equipment operation model also comprises an electric energy storage model and a thermal energy storage model, and the expression is as follows: , , in the formula, The energy of charge and discharge at the time t, For the self-discharge rate of the electricity storage device, The charge and discharge energy at the time t-1, For the charging efficiency of the electricity storage device, For the charging power of the electricity storage device, For the discharge power of the electricity storage device, For the discharge efficiency of the electricity storage device, For the heat storage energy at the time t, For the rate of loss of heat storage, The energy is stored at the time t-1, For the input conversion rate of the heat storage device, For the input thermal power of the heat storage device, For the output thermal power of the heat storage device, The output conversion rate of the heat storage equipment.
6. The low-carbon operation optimization method of a power system according to claim 1, wherein the green evidence-ladder carbon transaction mathematical model comprises a carbon emission right quota submodel under a ladder carbon transaction mechanism, an actual carbon emission submodel and a carbon emission transaction submodel, and the expression of the carbon emission right quota submodel is: , in the formula, To integrate the carbon emission allowance of the energy system, In order to schedule the cycle to be performed, For the carbon emission allowance of the superior electricity purchase, For the carbon emission allowance of the cogeneration plant, Is the carbon emission allowance of the gas boiler, Carbon emission allowance for unit power consumption of coal-fired units, For the superior electricity purchasing quantity in the t period, For the electricity purchasing efficiency of the power grid, Is a carbon emission factor of the electric network, For the carbon emission correction factor of the electrical network, Carbon emission allowance for unit natural gas consumption of the natural gas-fired unit, For the electric power output from the cogeneration device at the moment t, For the electricity output efficiency of the cogeneration plant, For the electricity carbon emission factor of the cogeneration unit, For the thermal power output from the cogeneration device at the moment t, For the heat output efficiency of the cogeneration unit, Is the carbon emission factor of natural gas of the cogeneration device, For the rated efficiency of the cogeneration plant, For the carbon emission correction factor of the cogeneration plant, Is the heat energy output by the gas boiler in the t period, Is the thermal efficiency of the gas-fired boiler, Is the natural gas carbon emission factor of the gas boiler, Is the rated efficiency of the gas boiler, The carbon emission correction coefficient of the gas boiler; the expression of the actual carbon emission submodel is as follows: , in the formula, To integrate the actual total carbon emissions of the energy system, For the actual carbon emissions of the superior electricity purchase, For the total actual carbon emissions of the cogeneration plant and the gas boiler, 、、 And 、、 The parameters are calculated for the carbon emissions of the coal-fired unit and the gas turbine respectively, For the superior electricity purchasing quantity in the t period, 、 Respectively the adjustment coefficients taking into account the influence of temperature on the carbon emissions, As a temperature factor at the time t, The output power of the heat and power cogeneration device, the gas boiler and the like in the period t, For the electricity-heat conversion coefficient of the cogeneration plant, For the electric power output from the cogeneration device at the moment t, For the thermal power output from the cogeneration device at the moment t, The output power of the gas boiler at the moment t; the expression of the carbon emission transaction submodel is as follows: , , in the formula, In the light of the cost of carbon trade, The price is traded for the carbon in the market, The price increase amplitude for the carbon trade is, To synthesize the carbon emission right trade amount actually participated by the energy system, For a set length of the carbon emission interval, To integrate the carbon emission allowance of the energy system, Carbon emissions offset by green evidence.
7. The low-carbon operation optimization method of a power system according to claim 1, wherein the objective function expression of the demand response optimization scheduling model is: , , , in the formula, In order to integrate the overall cost of the energy system, Is the natural gas consumption of the cogeneration unit, Is the natural gas consumption of the gas boiler unit, As a total number of energy types, As a total number of types of energy storage devices, In order to purchase the cost of electricity, In the light of the cost of carbon trade, In order to be able to carry out the maintenance costs, For the purpose of green evidence of transaction costs, To integrate the time-of-use electricity prices of the energy management system, In order to be able to purchase the cost, Is the unit price of the natural gas, Is prepared from natural gas with low heat value, Is the first The operation and maintenance cost coefficient of the energy-like conversion equipment, Is the first The output power of the energy-like conversion device, A cost factor is maintained for the operation of the energy storage device, Is the first The charging power of the energy storage device is similar to that of the energy storage device, Is the first The discharging power of the class energy storage device.
8. A low-carbon operation optimization system for an electric power system, comprising: The first construction module is configured to construct a comprehensive energy management system framework considering load side demand response; the second construction module is configured to construct a price type demand response model which can reduce load and transfer load and a substitution type demand response model for mutual conversion of electric energy and heat energy based on the comprehensive energy management system framework and considering the behavior characteristics of a load side user; The third construction module is configured to establish an energy supply side equipment operation model based on the price type demand response model and the substitution type demand response model, and introduce a mutual recognition mechanism of green certificate and step type carbon transaction based on the energy supply side equipment operation model to construct a green certificate-step type carbon transaction mathematical model; The fourth construction module is configured to construct a demand response optimization scheduling model of the comprehensive energy system under the green evidence-step carbon transaction mechanism based on the green evidence-step carbon transaction mathematical model and taking the minimum total cost of system operation as a target, and taking power balance, upper and lower equipment operation limits, climbing constraint and dynamic feasibility domain constraint of the energy storage equipment into consideration; And the solving module is configured to perform optimization solving on the demand response optimization scheduling model to obtain a multi-objective collaborative power system operation optimal scheme.
9. An electronic device comprising at least one processor and a memory communicatively coupled to the at least one processor, wherein the memory stores instructions executable by the at least one processor to enable the at least one processor to perform the method of any one of claims 1-7.
10. A computer readable storage medium, on which a computer program is stored, characterized in that the program, when being executed by a processor, implements the method of any of claims 1 to 7.

Description

Low-carbon operation optimization method and system for electric power system Technical Field The invention belongs to the technical field of comprehensive energy system operation optimization, and particularly relates to a low-carbon operation optimization method and system for an electric power system. Background Traditional power system optimization methods focus mainly on supply-demand balance and cost minimization, however, modern power systems need to consider more factors, mainly including renewable energy integration, load-side demand response, green license-carbon trading, and the like. Load side demand response is a method of managing power system loads by adjusting the end user's energy usage behavior to respond to changes in system demand to balance the difference between supply and demand. Green certificates and carbon trading, on the other hand, are important mechanisms for reducing greenhouse gas emissions. The green certification regime encourages the system to consume a proportion of the green electricity by giving the renewable energy generator a certain number of certificates. Carbon trade is a market mechanism for realizing the aim of reducing emission of greenhouse gases by trading carbon dioxide emission credit. However, most of the existing studies consider the demand response separately from the green evidence-carbon transaction mechanism, failing to fully exert the synergistic effect of both. In addition, in modeling of an energy supply side, the fine modeling of multi-energy coupling equipment such as a cogeneration unit, a heat pump, a kalina cycle and the like is insufficient, and it is difficult to accurately describe the energy conversion relation of the system. In the aspect of energy storage equipment constraint, the traditional fixed capacity constraint can not reflect the dynamic characteristics of the energy storage equipment in actual operation, and the accuracy of an optimization result is affected. Therefore, there is a need for a low-carbon operation optimization method for an electric power system that can comprehensively consider the load-side demand response, the green license-carbon transaction mechanism, and the dynamic characteristics of the energy-supply-side multi-energy coupling device. Disclosure of Invention The invention aims to overcome the defects of the prior art and provide a low-carbon operation optimization method and system for a power system, which are realized by constructing a load side multi-type demand response behavior model and an energy supply side multi-energy coupling equipment operation model, introducing a mutual recognition mechanism and a cooperative constraint relation of green certificate and step-type carbon transaction, and establishing a unified optimization scheduling model. In a first aspect, the present invention provides a low-carbon operation optimization method for an electric power system, including: constructing a comprehensive energy management system architecture considering load side demand response; Based on the comprehensive energy management system architecture, taking the behavior characteristics of a load side user into consideration, constructing a price type demand response model capable of reducing load and transferring load and a substitution type demand response model for mutual conversion of electric energy and heat energy; Based on a price type demand response model and a substitution type demand response model, an energy supply side equipment operation model is established, and based on the energy supply side equipment operation model, a mutual recognition mechanism of green certificate and step carbon transaction is introduced, and a green certificate-step carbon transaction mathematical model is established; Based on the green evidence-step carbon transaction mathematical model, taking the minimum total cost of system operation as a target, and taking power balance, upper and lower equipment operation limits, climbing constraint and energy storage equipment dynamic feasibility domain constraint into consideration, constructing a demand response optimization scheduling model of the comprehensive energy system under the green evidence-step carbon transaction mechanism; and carrying out optimization solution on the demand response optimization scheduling model to obtain a multi-objective collaborative power system operation optimal scheme. In a second aspect, the present invention provides a low-carbon operation optimization system for an electric power system, comprising: The first construction module is configured to construct a comprehensive energy management system framework considering load side demand response; the second construction module is configured to construct a price type demand response model which can reduce load and transfer load and a substitution type demand response model for mutual conversion of electric energy and heat energy based on the comprehensive energy management system framework