CN-122001014-A - Scheduling method and device for power distribution network resources and nonvolatile storage medium

CN122001014ACN 122001014 ACN122001014 ACN 122001014ACN-122001014-A

Abstract

The invention discloses a scheduling method and device of power distribution network resources and a nonvolatile storage medium. The method comprises the steps of obtaining equipment output data and load demand data of a county power distribution network, constructing an optimization model based on a master-slave game theory, wherein the objective of the optimization model comprises maximization of the income of the county power distribution network, maximization of the income of an energy storage service provider and minimization of electricity consumption cost, setting electricity price of the county power distribution network according to the equipment output data and the load demand data, collecting electricity consumption behavior feedback of a user, solving the optimization model by adopting an iterative algorithm based on the electricity consumption behavior feedback of the user to obtain an optimization solving result, and scheduling resources in the county power distribution network according to the optimization solving result. The invention solves the technical problems that the current power distribution network is subjected to resource shortage compensation through the generator sets which can be started quickly, however, the generator sets have higher running cost generally, and the relationship between the cost and the resource scheduling is difficult to balance.

Inventors

JU LI
LI WEI
ZHANG HUAN
SHUAI MENG
YU WENXI
XU HUIHUA
SONG ZEYUAN

Assignees

国网北京市电力公司
北京电力经济技术研究院有限公司

Dates

Publication Date: 20260508
Application Date: 20260121

Claims (11)

1. The scheduling method of the power distribution network resources is characterized by comprising the following steps of: acquiring equipment output data and load demand data of a county power distribution network, wherein the equipment output data comprises output data of photovoltaic equipment and an operation state of a flexible generator set; based on a master-slave game theory, an optimization model is established, wherein the objective of the optimization model comprises maximization of the income of the county power distribution network, maximization of the income of an energy storage service provider and minimization of electricity cost; Setting the electricity price of the county power distribution network according to the equipment output data and the load demand data, wherein the electricity price comprises a real-time electricity price and a peak electricity price; collecting user electricity consumption behavior feedback, wherein the user electricity consumption behavior feedback comprises real-time electricity consumption and demand response capability of a user; Based on the user electricity behavior feedback, solving the optimization model by adopting an iterative algorithm to obtain an optimization solving result; and scheduling the resources in the county power distribution network according to the optimized solution result.
2. The method of claim 1, wherein the constructing an optimization model based on master-slave gaming theory comprises: based on the master-slave game theory, determining the county power distribution network as a leader, the energy storage service provider and the user as followers and constructing a master-slave game expression; setting an objective function and constraint conditions for the county power distribution network, the energy storage service provider and the user respectively; And constructing the optimization model based on the master-slave game expression, the county power distribution network, the energy storage service provider and the objective function and constraint conditions corresponding to the user respectively.
3. The method according to claim 2, wherein the objective function corresponding to the county distribution network is as follows: , Wherein, the For the benefits of the county distribution network, And The selling price and the purchasing price of the distribution network of the county distribution network at the moment t are respectively, And And respectively transmitting power to the outside of the county power distribution network and power input to the county power distribution network at the moment T, wherein T is the number of times of day.
4. The method of claim 2, wherein the master-slave gaming expression is as follows: , wherein M is the leader of the leader, And Policies of the leader and the follower respectively for the nth time, Characterizing the leader based on policy in the nth game And the policy of the follower To maximize the corresponding objective function , Characterizing policies taken by the leader And the policy of the follower Meets the constraint conditions corresponding to the county power distribution network, the energy storage service provider and the user respectively, Characterizing policies taken by the leader And the policy of the follower The energy conservation is satisfied and the energy conservation is realized, An nth policy generated for the leader based on the nth-1 game of the follower.
5. The method of claim 1, wherein setting the electricity price based on the plant output data and the load demand data comprises: inputting the equipment output data and the load demand data into a preset prediction model to obtain power prediction supply and demand conditions; Setting the real-time electricity price based on the electricity forecast supply and demand conditions; determining a power usage peak period based on the load demand data; determining the peak electricity price based on the real-time electricity price and the electricity consumption peak period; the electricity rate is set based on the real-time electricity rate and the peak electricity rate.
6. The method of any one of claims 1 to 5, wherein the iterative algorithm comprises a gradient descent algorithm, a lagrangian multiplier algorithm, and a genetic algorithm.
7. The method of claim 6, wherein the solving the optimization model by using an iterative algorithm based on the user electricity behavior feedback to obtain an optimization solution result comprises: determining an initial decision and an initial Lagrangian multiplier based on the user electricity behavior feedback, wherein the initial decision characterization sets the electricity price; constructing a Lagrangian function based on the optimization model and the initial Lagrangian multiplier; Solving extreme points of the Lagrangian function by a numerical method to obtain an optimized decision; Based on the optimized decision, adjusting the electricity price and collecting electricity consumption behavior feedback of the user again; repeating the steps until the Lagrangian multiplier and the decision meet the preset conditions, and obtaining the optimized solving result.
8. A power distribution network resource scheduling device, comprising: the device comprises an acquisition module, a control module and a control module, wherein the acquisition module is used for acquiring device output data and load demand data of a county power distribution network, and the device output data comprises output data of photovoltaic devices and operation states of a flexible generator set; The construction module is used for constructing an optimization model based on a master-slave game theory, wherein the targets of the optimization model comprise the county power distribution network profit maximization, the energy storage service provider profit maximization and the electricity consumption cost minimization; The setting module is used for setting the electricity price of the county power distribution network according to the equipment output data and the load demand data, wherein the electricity price comprises a real-time electricity price and a peak electricity price; The system comprises an acquisition module, a control module and a control module, wherein the acquisition module is used for acquiring user electricity consumption behavior feedback, and the user electricity consumption behavior feedback comprises real-time electricity consumption and demand response capability of a user; The solving module is used for solving the optimization model by adopting an iterative algorithm based on the user electricity behavior feedback to obtain an optimization solving result; and the scheduling module is used for scheduling the resources in the county power distribution network according to the optimization solving result.
9. A non-volatile storage medium, characterized in that the non-volatile storage medium comprises a stored program, wherein the program, when run, controls a device in which the non-volatile storage medium is located to perform the scheduling method of the power distribution network resource according to any one of claims 1 to 7.
10. A computer device is characterized by comprising a memory and a processor, The memory stores a computer program; The processor configured to execute a computer program stored in the memory, the computer program when executed causing the processor to perform the scheduling method of power distribution network resources according to any one of claims 1 to 7.
11. A computer program product comprising a computer program, characterized in that the computer program, when executed by a processor, implements the scheduling method of power distribution network resources of any one of claims 1 to 7.

Description

Scheduling method and device for power distribution network resources and nonvolatile storage medium Technical Field The invention relates to the technical field of power distribution networks, in particular to a power distribution network resource scheduling method and device and a nonvolatile storage medium. Background Current county-area distribution network resource scheduling methods generally rely on traditional scheduling strategies, which tend to focus on optimization of a single objective, such as minimizing power generation costs or maximizing system stability. However, with the widespread use of distributed energy sources (e.g., photovoltaic devices) and energy storage systems, the operating environment of the distribution network becomes more complex, and single-objective optimization methods have been difficult to meet current demands. At present, scheduling of distributed energy sources such as photovoltaic and an energy storage system is often considered independently, and an effective cooperative control mechanism is lacked, so that the resource utilization rate is low, and the economic benefit of a power distribution network is not maximized. In view of the above problems, no effective solution has been proposed at present. Disclosure of Invention The embodiment of the invention provides a scheduling method and device for power distribution network resources and a nonvolatile storage medium, which at least solve the technical problems that the current power distribution network is subjected to resource shortage compensation through generator sets which can be started quickly, however, the generator sets are usually high in running cost, and the relationship between the cost and resource scheduling is difficult to balance. According to one aspect of the embodiment of the invention, a scheduling method of power distribution network resources is provided, which comprises the steps of obtaining equipment output data and load demand data of a county power distribution network, wherein the equipment output data comprise output data of photovoltaic equipment and operation states of a flexible generator set, constructing an optimization model based on a master-slave game theory, wherein targets of the optimization model comprise county power distribution network gain maximization, energy storage service provider gain maximization and electricity consumption cost minimization, setting electricity prices of the county power distribution network according to the equipment output data and the load demand data, wherein the electricity prices comprise real-time electricity prices and peak electricity prices, collecting user electricity consumption behavior feedback, wherein the user electricity consumption behavior feedback comprises user real-time electricity consumption amount and demand response capability, solving the optimization model by adopting an iterative algorithm based on the user electricity consumption behavior feedback, obtaining an optimization solution result, and scheduling resources in the county power distribution network according to the optimization solution result. The optimization model is constructed based on the master-slave game theory, and comprises the steps of determining a county power distribution network as a leader, an energy storage service provider and a user as followers and constructing master-slave game expressions based on the master-slave game theory, setting objective functions and constraint conditions for the county power distribution network, the energy storage service provider and the user respectively, and constructing the optimization model based on the objective functions and the constraint conditions corresponding to the master-slave game expressions, the county power distribution network, the energy storage service provider and the user respectively. Optionally, the objective function corresponding to the county distribution network is as follows: , Wherein, the For the benefits of a county distribution network,AndThe selling price and the purchasing price of the distribution network in the county at the moment t are respectively,AndThe power transmitted outwards by the county power distribution network at the time T and the power input into the county power distribution network are respectively, and T is the time of day. Alternatively, the master-slave gaming expression is as follows: , wherein M is a leader, N is a follower, AndPolicies of nth leader and follower respectively,Characterizing a leader policy-based in an nth gameAnd follower policyTo maximize the corresponding objective function,Characterizing policies taken by a leaderAnd follower policyMeets the constraint conditions corresponding to the county power distribution network, the energy storage service provider and the user,Characterizing policies taken by a leaderAnd follower policyThe energy conservation is satisfied and the energy conservation is realized,An nth policy generated for the