CN-121417241-B - Frequency modulation and peak shaving method, device, system, equipment and storage medium for virtual power plant

CN121417241BCN 121417241 BCN121417241 BCN 121417241BCN-121417241-B

Abstract

The application provides a frequency modulation and peak shaving method of a virtual power plant, which comprises the steps of obtaining a wind-solar load prediction curve, market price prediction information and a power grid next day peak shaving demand curve, establishing a first planning model to obtain a controllable resource base point power plan and an energy storage SOC plan of each preset time period in the next day, executing every preset time period after the next day, obtaining short-term wind-solar load prediction data, actual running states of each resource and market price real-time information, establishing a second planning model to correct each controllable resource base point power plan and energy storage SOC plan of the current time period, determining frequency modulation parameters of the current time period, indicating corresponding equipment to execute according to each corrected controllable resource base point power plan and energy storage SOC plan of the current time period, and adjusting the output of frequency modulation resources according to the frequency modulation parameters of the current time period if a power grid frequency modulation instruction is received. The method solves the problem of limitation of the virtual power plant in frequency modulation and peak shaving.

Inventors

YANG PING
QIU HAITAO
LIU ZEJIAN
ZHANG PENG
XIAO HUANGQING

Assignees

华南理工大学

Dates

Publication Date: 20260508
Application Date: 20251230

Claims (7)

1. The utility model provides a virtual power plant frequency modulation peak shaving method which is characterized by comprising the following steps: Acquiring a wind-solar load prediction curve, market price prediction information and a power grid next-day peak regulation demand curve, and establishing a first planning model to obtain a controllable resource base point power plan and an energy storage SOC plan of each preset time period of the next day; Acquiring short-term wind-solar load prediction data, actual running states of all resources and real-time information of market price, establishing a second planning model to correct all controllable resource base point power plans and energy storage SOC plans in the current time period, and determining frequency modulation parameters in the current time period; According to the corrected controllable resource base point power plan and energy storage SOC plan of the current time period, the corresponding equipment is instructed to execute; the determining the frequency modulation parameter of the current time period comprises the following steps: If the current S0C of the energy storage system is smaller than the energy storage SOC plan of the corrected current time period, averaging the current S0C of the energy storage system and the energy storage SOC plan of the corrected current time period, and determining the upper limit of the frequency modulation power according to the average value and the preset lower limit of the energy storage SOC; if the current S0C of the energy storage system is larger than or equal to the energy storage SOC plan of the corrected current time period, determining an upper limit of the frequency modulation power according to the energy storage SOC plan of the corrected current time period and a preset lower limit of the energy storage SOC; Determining a first frequency modulation parameter of the energy storage system according to the upper limit of the frequency modulation power, so as to determine a second frequency modulation parameter of the gas turbine, wherein the sum of the first frequency modulation parameter and the second frequency modulation parameter is one; and if the current SOC of the energy storage system exceeds a preset threshold value, adding a preset trimming amount to the first frequency modulation parameter of the energy storage system.
2. The method for frequency modulation and peak shaving of a virtual power plant according to claim 1, wherein the steps of obtaining a wind-light load prediction curve, market price prediction information and a power grid next-day peak shaving demand curve, and establishing a first planning model to obtain a controllable resource base point power plan and an energy storage SOC plan of each preset time period of the next day comprise the following steps: setting an objective function of the first planning model as a profit maximization, adding a power balance constraint, an energy storage SOC dynamic constraint, a gas turbine climbing rate constraint, a gas turbine start-stop constraint and a peak regulation standby capacity constraint, setting a time scale of the first planning model as 24 hours, setting granularity as the preset time period, and setting decision variables as controllable resources; Inputting the wind-solar load prediction curve, market price prediction information and the power grid next-day peak regulation demand curve into the first planning model so that the first planning model solves according to an objective function and constraint; after the solving is completed, obtaining a power plan and an energy storage SOC plan of each resource base point in each preset time period in the next day; and/or the number of the groups of groups, The obtaining of short-term wind-solar load prediction data, actual running states of various resources and real-time market price information, and the establishment of a second planning model to correct various controllable resource base point power plans and energy storage SOC plans in the current time period comprise the following steps: setting an objective function of the second planning model as a benefit maximization, adding a power balance constraint, an energy storage SOC dynamic constraint, a gas turbine climbing rate constraint, a gas turbine start-stop constraint and a peak regulation standby capacity constraint, setting a time scale of the second planning model as 4 hours, setting granularity as the preset time period, and setting decision variables as controllable resources; inputting the short-term wind-solar load prediction data, actual running states of all resources and real-time market price information into the second planning model so that the second planning model solves according to an objective function and constraints; And after the solving is completed, obtaining an output result of the current time period, and correcting each controllable resource base point power plan and the energy storage SOC plan of the current time period according to the output result.
3. The method for frequency modulation and peak shaving in a virtual power plant according to claim 1, wherein if the power grid frequency modulation command is received, adjusting the output of the frequency modulation resource according to the frequency modulation parameter in the current time period comprises: if a power grid frequency modulation instruction is received, determining frequency modulation power; Adjusting the output of the energy storage system according to the product result of the first frequency modulation parameter and the frequency modulation power; and adjusting the output of the gas turbine according to the product result of the second frequency modulation parameter and the frequency modulation power.
4. A virtual power plant frequency modulation peak shaving apparatus, comprising: The day-ahead peak regulation planning layer is used for acquiring a wind-light load prediction curve, market price prediction information and a power grid next day peak regulation demand curve, and establishing a first planning model to obtain a controllable resource base point power plan and an energy storage SOC plan of each preset time period of the next day; The daily rolling planning layer is used for acquiring short-term wind-solar load prediction data, actual running states of all resources and real-time information of market price every other preset time period after the next day, establishing a second planning model to correct all controllable resource base point power plans and energy storage SOC plans in the current time period, and determining frequency modulation parameters in the current time period; The real-time frequency modulation control layer is used for indicating corresponding equipment to execute according to the corrected controllable resource base point power plan and the energy storage SOC plan of the current time period; the determining the frequency modulation parameter of the current time period comprises the following steps: If the current S0C of the energy storage system is smaller than the energy storage SOC plan of the corrected current time period, averaging the current S0C of the energy storage system and the energy storage SOC plan of the corrected current time period, and determining the upper limit of the frequency modulation power according to the average value and the preset lower limit of the energy storage SOC; if the current S0C of the energy storage system is larger than or equal to the energy storage SOC plan of the corrected current time period, determining an upper limit of the frequency modulation power according to the energy storage SOC plan of the corrected current time period and a preset lower limit of the energy storage SOC; Determining a first frequency modulation parameter of the energy storage system according to the upper limit of the frequency modulation power, so as to determine a second frequency modulation parameter of the gas turbine, wherein the sum of the first frequency modulation parameter and the second frequency modulation parameter is one; and if the current SOC of the energy storage system exceeds a preset threshold value, adding a preset trimming amount to the first frequency modulation parameter of the energy storage system.
5. A virtual power plant frequency and peak shaving system comprising a data acquisition and communication device, a resource agent control unit, and a virtual power plant frequency and peak shaving device as claimed in claim 4.
6. The virtual power plant frequency modulation peak shaving equipment is characterized by comprising a processor and a memory; the memory is used for storing a computer program; the processor is configured to execute the computer program and implement the virtual power plant frequency modulation peak shaving method according to any one of claims 1 to 3 when the computer program is executed.
7. A computer readable storage medium, characterized in that the computer readable storage medium stores a computer program which, when executed by a processor, causes the processor to implement the virtual power plant frequency modulation peak shaving method according to any one of claims 1 to 3.

Description

Frequency modulation and peak shaving method, device, system, equipment and storage medium for virtual power plant Technical Field The application relates to the technical field of virtual power plants, in particular to a frequency modulation and peak shaving method, device, system, equipment and storage medium for a virtual power plant. Background As new energy sources (e.g., photovoltaic, wind power, etc.) are increasingly connected to the power grid, the randomness and fluctuation of the output of the new energy sources may cause the frequency and load fluctuation of the power grid to be aggravated. In order to improve the capacity of the power grid for absorbing high-proportion new energy and the operation stability of the power grid, a virtual power plant (VirtualPowerPlant, VPP) is generally adopted to achieve the technical purpose. The virtual power plant integrates a source, a network, a load and a storage, wherein the source refers to a distributed power source (such as a photovoltaic power source, a wind power source and a gas turbine), the network refers to a power grid, the load refers to a flexible load (such as an interruptible load and an adjustable load), the storage refers to an energy storage system (such as battery energy storage), and the integration refers to the aggregate management of the dispersed resources and the cooperative response of the power grid requirement. It can be seen that the virtual power plant can be used as a special power plant to participate in peak shaving and frequency modulation of the power grid. The existing virtual power plant has certain limitations in frequency modulation and peak shaving, such as mismatching of resource characteristics and service requirements, difficulty in considering frequency modulation instantaneity and peak shaving economy, insufficient global economy optimization, weak uncertainty coping capability and the like. Disclosure of Invention In order to solve the technical problem that the virtual power plant has limitation in frequency modulation and peak shaving, the application provides a method, a device, a system, equipment and a storage medium for frequency modulation and peak shaving of the virtual power plant. In a first aspect, the present application provides a frequency modulation peak shaving method for a virtual power plant, including: Acquiring a wind-solar load prediction curve, market price prediction information and a power grid next-day peak regulation demand curve, and establishing a first planning model to obtain a controllable resource base point power plan and an energy storage SOC plan of each preset time period of the next day; Acquiring short-term wind-solar load prediction data, actual running states of all resources and real-time information of market price, establishing a second planning model to correct all controllable resource base point power plans and energy storage SOC plans in the current time period, and determining frequency modulation parameters in the current time period; and if the power grid frequency modulation instruction is received, adjusting the output of the frequency modulation resource according to the frequency modulation parameter of the current time period. In a second aspect, the present application provides a frequency modulation peak shaving device for a virtual power plant, including: The day-ahead peak regulation planning layer is used for acquiring a wind-light load prediction curve, market price prediction information and a power grid next day peak regulation demand curve, and establishing a first planning model to obtain a controllable resource base point power plan and an energy storage SOC plan of each preset time period of the next day; The daily rolling planning layer is used for acquiring short-term wind-solar load prediction data, actual running states of all resources and real-time information of market price every other preset time period after the next day, establishing a second planning model to correct all controllable resource base point power plans and energy storage SOC plans in the current time period, and determining frequency modulation parameters in the current time period; And the real-time frequency modulation control layer is used for indicating corresponding equipment to execute according to the corrected controllable resource base point power plans and the energy storage SOC plans in the current time period, and adjusting the output of the frequency modulation resources according to the frequency modulation parameters in the current time period if the power grid frequency modulation instruction is received. In a third aspect, the present application provides a virtual power plant frequency and peak shaving system, which includes a data acquisition and communication device, a resource agent control unit, and a virtual power plant frequency and peak shaving device as described in the second aspect. In a fourth aspect, the application provides a virtual power