CN-121981481-A - Energy storage resource cross-network demand response scheduling method, system, equipment, medium and product

CN121981481ACN 121981481 ACN121981481 ACN 121981481ACN-121981481-A

Abstract

The invention relates to the technical field of power systems, and discloses a method, a system, equipment, a medium and a product for energy storage resource cross-network demand response scheduling, wherein the method comprises the steps of taking maximization of natural gas response resource quantity and minimization of natural gas supply cost as a first optimization target, constructing a natural gas response optimization model according to the constraint of natural gas operation balance as the first optimization target, determining the maximum surplus air quantity optimization quantity and the maximum air supply quantity optimization quantity, taking maximization of the storage capacity of an energy storage power station as a second optimization target, and the boundary constraint is carried out on the storage capacity of the energy storage power station according to the maximum surplus air quantity and the air supply quantity, the energy storage capacity configuration optimization model is updated through the maximum surplus air quantity optimization quantity and the air supply quantity optimization quantity, and the optimal energy storage capacity is determined through the updated energy storage capacity configuration optimization model, so that the maximization of the natural gas response resource quantity and the configuration of the natural gas supply cost are realized, the effective utilization rate of resources is improved, and the resource waste is avoided.

Inventors

FU ZHENGXIN
TANG QI
CAO DEFA
CHEN ZHIPING
LI HUI
HU ZHIPENG
DONG DI
LI XIN
FAN XINMING

Assignees

广东电网有限责任公司佛山供电局

Dates

Publication Date: 20260505
Application Date: 20260127

Claims (10)

1. The energy storage resource cross-network demand response scheduling method is characterized by comprising the following steps of: The natural gas response resource quantity maximization and the natural gas supply cost minimization are taken as a first optimization target, and a natural gas response optimization model is constructed according to the constraint of natural gas operation balance as the first optimization target; Based on the obtained maximum surplus gas and gas supply of the surplus natural gas resource, combining the natural gas response optimization model to determine the maximum surplus gas optimization quantity and gas supply optimization quantity; maximizing the storage capacity of an energy storage power station as a second optimization target, and carrying out boundary constraint on the storage capacity of the energy storage power station according to the maximum surplus air and the air supply amount to construct an energy storage capacity configuration optimization model; Updating the energy storage capacity configuration optimization model according to the maximum surplus air quantity optimization quantity and the air supply quantity optimization quantity, and determining the optimal energy storage capacity according to the updated energy storage capacity configuration optimization model.
2. The energy storage resource cross-network demand response scheduling method of claim 1, wherein the first objective function of the first optimization objective is expressed as: In the formula, Is the maximum surplus air weight coefficient, To be at the moment To the "gas-to-electricity" energy converter, The cost weight coefficient is reached for the surplus natural gas resources, For a virtual natural gas well supply, The unit gas supply cost for the virtual natural gas well is represented by R, which is the index of the virtual natural gas and R is the quantity of the virtual natural gas.
3. The energy storage resource cross-network demand response scheduling method according to claim 1 or 2, wherein the first constraint condition of the natural gas response optimization model comprises a natural gas network balance constraint, a residual power generation capacity limit constraint of a gas-electricity converter gas unit after a previous-stage power market, a gas supply capacity limit constraint of a virtual natural gas well, a natural gas network residual transmission capacity limit constraint after the previous-stage power market and a residual natural gas source region division limit constraint.
4. The energy storage resource cross-network demand response scheduling method of claim 1, wherein the second objective function of the second optimization objective is expressed as: In the formula, For the moment of the energy storage power station Is a storage capacity of the storage medium.
5. The energy storage resource cross-network demand response scheduling method of claim 1, wherein the second constraint condition of the energy storage capacity configuration optimization model comprises a surplus power generation output limit constraint converted by surplus natural gas, an electric power system power balance constraint, a gas turbine set output limit constraint, a storage capacity limit constraint, a charging power limit constraint and an energy storage injection limit constraint.
6. The energy storage resource cross-network demand response scheduling method according to claim 1, wherein determining the optimal energy storage capacity by the updated energy storage capacity configuration optimization model comprises: and optimizing and solving the updated energy storage capacity configuration optimization model through a mathematical programming solver, and determining the optimal energy storage capacity according to the optimal solution.
7. An energy storage resource cross-network demand response scheduling system, comprising: The natural gas response optimization module is used for maximizing natural gas response resource quantity and minimizing natural gas supply cost to form a first optimization target, and constructing a natural gas response optimization model according to the constraint of natural gas operation balance to the first optimization target; The gas supply optimization module is used for determining the maximum surplus gas amount optimization quantity and the gas supply amount optimization quantity based on the obtained maximum surplus gas amount and the gas supply amount of the surplus natural gas resource and combining the natural gas response optimization model; The capacity configuration optimization module is used for maximizing the storage capacity of the energy storage power station as a second optimization target, and carrying out boundary constraint on the storage capacity of the energy storage power station according to the maximum surplus air and the air supply amount to construct an energy storage capacity configuration optimization model; The energy storage capacity optimizing module is used for updating the energy storage capacity configuration optimizing model according to the maximum surplus residual capacity optimizing quantity and the air supply quantity optimizing quantity, and determining the optimal energy storage capacity according to the updated energy storage capacity configuration optimizing model.
8. An electronic device comprising a memory and a processor, wherein the memory stores a computer program that, when executed by the processor, causes the processor to perform the steps of the energy storage resource cross-network demand response scheduling method of any one of claims 1-6.
9. A computer readable storage medium having stored thereon a computer program, wherein the computer program when executed implements the steps of the energy storage resource cross-network demand response scheduling method of any of claims 1-6.
10. A computer program product comprising a computer program stored on a non-transitory computer readable storage medium, the computer program comprising program instructions, wherein the program instructions, when executed by a computer, cause the computer to perform the steps of the energy storage resource cross-network demand response scheduling method of any one of claims 1-6.

Description

Energy storage resource cross-network demand response scheduling method, system, equipment, medium and product Technical Field The invention relates to the technical field of power systems, in particular to a method, a system, equipment, a medium and a product for scheduling energy storage resource cross-network demand response. Background Surplus resources refer to the amount of resources that a principal owns, exceeds its actual needs and has ownership. In the daily operation of a natural Gas network, a phenomenon of natural Gas rich Gas is often generated due to estimated deviation in a planned reporting mechanism and the wide application of a new energy Power generation+p2g (Power-to-Gas) technology. Currently, for this part of surplus gas, the prior art converts the surplus gas into surplus power generation capacity through a gas generator set so as to cope with the urgent need of the power grid. However, the power grid load demand has obvious randomness and volatility, so that when surplus gas occurs, the corresponding load demand does not necessarily exist, and therefore, the gas discarding phenomenon may be caused, effective utilization of resources is difficult to realize, and resource waste is caused. Disclosure of Invention In view of the above, the invention provides a method, a system, equipment, a medium and a product for scheduling energy storage resource cross-network demand response, which solve the technical problem that effective utilization of resources is difficult to realize and resource waste is caused. The first aspect of the invention provides a method for scheduling energy storage resource cross-network demand response, which comprises the following steps: The natural gas response resource quantity maximization and the natural gas supply cost minimization are taken as a first optimization target, and a natural gas response optimization model is constructed according to the constraint of natural gas operation balance as the first optimization target; Based on the obtained maximum surplus gas and gas supply of the surplus natural gas resource, combining the natural gas response optimization model to determine the maximum surplus gas optimization quantity and gas supply optimization quantity; maximizing the storage capacity of an energy storage power station as a second optimization target, and carrying out boundary constraint on the storage capacity of the energy storage power station according to the maximum surplus air and the air supply amount to construct an energy storage capacity configuration optimization model; Updating the energy storage capacity configuration optimization model according to the maximum surplus air quantity optimization quantity and the air supply quantity optimization quantity, and determining the optimal energy storage capacity according to the updated energy storage capacity configuration optimization model. Preferably, the first objective function of the first optimization objective is expressed as: In the formula, Is the maximum surplus air weight coefficient,To be at the momentTo the "gas-to-electricity" energy converter,The cost weight coefficient is reached for the surplus natural gas resources,For a virtual natural gas well supply,The unit gas supply cost for the virtual natural gas well is represented by R, which is the index of the virtual natural gas and R is the quantity of the virtual natural gas. Preferably, the first constraint condition of the natural gas response optimization model comprises a natural gas network balance constraint, a residual power generation capacity limit constraint of a gas-electricity converter gas unit after a previous-stage power market, a gas supply capacity limit constraint of a virtual natural gas well, a residual transmission capacity limit constraint of a natural gas network after the previous-stage power market and a surplus natural gas source region division limit constraint. Preferably, the second objective function of the second optimization objective is expressed as: In the formula, Energy storage power station momentIs a storage capacity of the storage medium. Preferably, the second constraint condition of the energy storage capacity configuration optimization model includes a surplus power generation output limit constraint, an electric power system power balance constraint, a gas unit output limit constraint, a storage capacity limit constraint, a charging power limit constraint and an energy storage injection limit constraint, wherein the surplus power generation output limit constraint is converted by surplus natural gas. Preferably, determining the optimal energy storage capacity by the updated energy storage capacity configuration optimization model comprises: and optimizing and solving the updated energy storage capacity configuration optimization model through a mathematical programming solver, and determining the optimal energy storage capacity according to the optimal solution. In a second aspect