CN-120855513-B - Generating capacity prediction method suitable for virtual power plant

CN120855513BCN 120855513 BCN120855513 BCN 120855513BCN-120855513-B

Abstract

The invention discloses a generating capacity prediction method suitable for a virtual power plant, and relates to the technical field of virtual power plants. According to the method, the predicted energy supply data and the real-time energy supply data of each power generation end are obtained, the generated energy of the power generation end is preliminarily estimated, the difference between the actual energy supply data and the predicted energy supply data is judged according to the estimated result, so that the influence of the energy supply data on the predicted result is reduced, on the premise that the influence of the energy supply data on the predicted result is based, the influence of equipment on the predicted result is obtained by combining the difference between the theoretical generated energy of the power generation end and the actual generated energy, and the prediction of the generated energy of the virtual power plant which is closer to the true value is obtained.

Inventors

LIANG YONGQIANG
SHI LEI
GUAN TAO
HAN FEI
GUO JUNFENG
AN HAIWANG
ZHANG PENG
LIANG JUN

Assignees

国能(陕西)能源销售有限公司

Dates

Publication Date: 20260508
Application Date: 20250623

Claims (5)

1. A method for predicting power generation capacity suitable for a virtual power plant, comprising: basic equipment parameters of the distributed power supply are obtained, and a corresponding virtual power plant is constructed according to the basic equipment parameters of the distributed power supply; Acquiring predicted energy supply data and real-time energy supply data of a distributed power supply, generating a corresponding simulated generating capacity curve according to the obtained predicted energy supply data, and generating a corresponding real-time predicted generating capacity curve according to the real-time energy supply data; Acquiring the actual power generation amount of the distributed power supply, generating an actual power generation amount curve, acquiring a corresponding energy supply influence residual value based on the generated simulated power generation amount curve and the real-time predicted power generation amount curve, and acquiring a device performance influence residual value according to the energy supply influence residual value and the actual power generation amount curve; Predicting the power generation capacity of the virtual power plant according to the energy supply influence residual value and the equipment performance influence residual value; Evaluating the power generation efficiency of each power generation end according to the predicted power generation amount of the virtual power plant, and generating corresponding early warning information according to the power generation efficiency evaluation result; the process for obtaining the basic equipment parameters of the distributed power supply and constructing the corresponding virtual power plant according to the basic equipment parameters of the distributed power supply comprises the following steps: acquiring the position of each power generation end and the composition of power generation equipment forming a distributed power supply, and acquiring equipment parameters of the power generation equipment of the power generation end, wherein the equipment parameters comprise equipment type, equipment specification and energy conversion rate; Constructing corresponding virtual power generation nodes according to each power generation end, associating the virtual power generation nodes with the power generation ends, and constructing a data uploading link for linking the virtual power generation nodes and the power generation ends; summarizing all the virtual power generation nodes and the data uploading links to complete the construction of the virtual power plant; The process for obtaining the predicted energy supply data of the position of the distributed power supply and generating the corresponding simulated generating capacity curve according to the obtained predicted energy supply data comprises the following steps: according to the equipment type of the power generation equipment at the power generation end, acquiring an energy item for generating power corresponding to the power generation equipment, and acquiring predicted energy supply data of the energy item, wherein the predicted energy supply data comprises a predicted energy supply value and energy supply time; Generating a corresponding predicted energy supply curve according to the predicted energy supply data; generating a corresponding simulated generating capacity curve according to the energy conversion rate of the generating equipment; The process for obtaining real-time energy supply data of the position of the distributed power supply and generating a corresponding real-time predicted generating capacity curve according to the real-time energy supply data comprises the following steps: acquiring a real-time energy supply value of an energy item corresponding to a power generation end, and generating a corresponding real-time energy supply curve; Generating a corresponding real-time predicted generating capacity curve according to the energy conversion rate and the real-time energy supply curve of the generating equipment at the generating end; The process for obtaining the energy supply influence residual value corresponding to the power generation end comprises the following steps: Constructing two-dimensional coordinate systems, wherein each two-dimensional coordinate system is associated with one power generation end; mapping the generated predicted energy supply curve, simulated generating capacity curve, real-time energy supply curve and real-time predicted generating capacity curve into a two-dimensional coordinate system; Acquiring the actual power generation amount of a power generation end, generating an actual power generation amount curve, and mapping the generated actual power generation amount curve into a corresponding two-dimensional coordinate system; The energy conversion rate of the power generation equipment is recorded as K; Setting a monitoring period; marking each curve in the monitoring period, and obtaining the energy supply influence residual value Gc of the power generation end according to the marked curve part.
2. A method of predicting power generation in a virtual power plant according to claim 1, wherein the step of obtaining the plant performance affecting residuals from the energy affecting residuals and the actual power generation profile comprises: and acquiring a real-time power generation amount corresponding to the current moment on the actual power generation amount curve, and acquiring the equipment performance influence residual value Sc according to the obtained energy supply influence residual value and the real-time power generation amount.
3. A method of predicting power generation in a virtual power plant as claimed in claim 2, wherein predicting power generation in the virtual power plant based on the energy supply influencing residuals and the plant performance influencing residuals comprises: Marking a predicted energy supply curve and an analog generating capacity curve from the current time t to the ending time t2 of the monitoring period; updating the energy conversion rate of the power generation equipment at the power generation end according to the obtained equipment performance influence residual value: the prediction function curve between the current time t0 and the ending time t2 of the monitoring period is adjusted through energy supply influence residual values, and then the simulation generating capacity curve between the current time t0 and the ending time t2 of the monitoring period is updated according to the adjusted prediction function curve and the updated energy conversion rate; And obtaining the predicted total power generation amount Yz of the virtual power plant according to the updated simulated power generation amount curve of each power generation end.
4. A method for predicting power generation capacity for a virtual power plant as claimed in claim 3, wherein the process of evaluating the power generation efficiency of each power generation end based on the power generation capacity predicted by the virtual power plant comprises: Setting a dynamic early warning threshold Z0 of the total power generation amount; When Yz is more than or equal to Z0, the total power generation amount of the distributed power supply reaches the expectation, otherwise, the total power generation amount of the distributed power supply does not reach the expectation, and if the total power generation amount of the distributed power supply does not reach the expectation, the power generation missing proportion of the corresponding power generation end is obtained; sequencing from high to low according to the power generation missing proportion, and generating corresponding early warning information according to the sequencing result.
5. The method for predicting the power generation capacity of a virtual power plant according to claim 4, wherein the setting process of the dynamic early warning threshold of the total power generation amount is as follows: and obtaining an early warning threshold of the generated energy corresponding to each generating end according to the predicted energy supply value and the energy conversion rate corresponding to the predicted energy supply curve t2 moment of the generating equipment of each generating end in the monitoring period, and obtaining a dynamic early warning threshold of the corresponding total generated energy according to the equipment specification of the generating equipment of each generating end.

Description

Generating capacity prediction method suitable for virtual power plant Technical Field The invention relates to the technical field of virtual power plants, in particular to a power generation amount prediction method suitable for a virtual power plant. Background With the development of global energy transformation and power systems to be intelligent, virtual power plants have been created as an innovative model for integrating distributed energy resources. The distributed power supply, the energy storage system, the controllable load and the like are aggregated, unified management and scheduling are realized, and it is important to accurately predict the generated energy of the virtual power plant; In practical situations, factors influencing the accuracy of the power generation amount prediction result of the virtual power plant are usually energy sources and equipment, and how to reduce the influence of energy supply and equipment factors on the prediction result error is a problem to be solved. Disclosure of Invention The invention aims to provide a power generation amount prediction method suitable for a virtual power plant. The invention aims at realizing the following technical scheme that the power generation amount prediction method suitable for the virtual power plant comprises the following steps: basic equipment parameters of the distributed power supply are obtained, and a corresponding virtual power plant is constructed according to the basic equipment parameters of the distributed power supply; Acquiring predicted energy supply data and real-time energy supply data of a distributed power supply, generating a corresponding simulated generating capacity curve according to the obtained predicted energy supply data, and generating a corresponding real-time predicted generating capacity curve according to the real-time energy supply data; Acquiring the actual power generation amount of the distributed power supply, generating an actual power generation amount curve, acquiring a corresponding energy supply influence residual value based on the generated simulated power generation amount curve and the real-time predicted power generation amount curve, and acquiring a device performance influence residual value according to the energy supply influence residual value and the actual power generation amount curve; Predicting the power generation capacity of the virtual power plant according to the energy supply influence residual value and the equipment performance influence residual value; And evaluating the power generation efficiency of each power generation end according to the power generation amount predicted by the virtual power plant, and generating corresponding early warning information according to the power generation efficiency evaluation result. Further, the process of obtaining the basic equipment parameters of the distributed power supply and constructing the corresponding virtual power plant according to the basic equipment parameters of the distributed power supply includes: acquiring the position of each power generation end and the composition of power generation equipment forming a distributed power supply, and acquiring equipment parameters of the power generation equipment of the power generation end, wherein the equipment parameters comprise equipment type, equipment specification and energy conversion rate; Constructing corresponding virtual power generation nodes according to each power generation end, associating the virtual power generation nodes with the power generation ends, and constructing a data uploading link for linking the virtual power generation nodes and the power generation ends; And summarizing all the virtual power generation nodes and the data uploading links to complete the construction of the virtual power plant. Further, the process of obtaining the predicted energy supply data of the position of the distributed power supply and generating the corresponding simulated generating capacity curve according to the obtained predicted energy supply data comprises the following steps: according to the equipment type of the power generation equipment at the power generation end, acquiring an energy item for generating power corresponding to the power generation equipment, and acquiring predicted energy supply data of the energy item, wherein the predicted energy supply data comprises a predicted energy supply value and energy supply time; Generating a corresponding predicted energy supply curve according to the predicted energy supply data; And generating a corresponding simulated generating capacity curve according to the energy conversion rate of the generating equipment. Further, the process of obtaining real-time energy supply data of the position of the distributed power supply and generating a corresponding real-time estimated generating capacity curve according to the real-time energy supply data comprises the following steps: acquiring a real-time energy su