CN-122026441-A - Hybrid energy storage joint scheduling method in new energy consumption scene

CN122026441ACN 122026441 ACN122026441 ACN 122026441ACN-122026441-A

Abstract

The invention relates to the technical field of data processing, in particular to a hybrid energy storage joint scheduling method in a new energy consumption scene. The method comprises the steps of collecting multi-source monitoring data and current absorption rate, determining the residual energy storage capacity of the energy storage device and the switching times of historical energy storage modes based on the multi-source monitoring data, determining a mode switching threshold between compressed air energy storage and electrochemical energy storage according to the absorption rate, determining a real-time load intensity index and charging and discharging frequency of the electrochemical energy storage according to the multi-source monitoring data, predicting a load intensity index of future electrochemical energy storage according to a predicted state of charge influence coefficient of a battery, correcting the mode switching threshold according to the predicted load intensity index of the future electrochemical energy storage, completing joint scheduling of the compressed air energy storage and the electrochemical energy storage, and executing preset absorption ending operation after the joint scheduling is finished. The invention ensures the long-term stable operation capability of the charge-discharge system.

Inventors

XU QISHAN
FAN GUANGYING
MA XIAOJIU
ZHANG FENG
TENG WEIJUN
Hu Junshui
LIU YANG
WANG JINGGANG
LIU ZHE
HU PENG

Assignees

国网河南省电力公司信阳供电公司

Dates

Publication Date: 20260512
Application Date: 20260116

Claims (10)

1. The hybrid energy storage joint scheduling method in the new energy consumption scene is characterized by being applied to a system comprising energy storage equipment, and comprises the following steps of: Collecting multisource monitoring data and the current digestion rate; determining the residual energy storage capacity of the energy storage device and the switching times of the historical energy storage modes based on the multi-source monitoring data, and determining a mode switching threshold between compressed air energy storage and electrochemical energy storage by combining the consumption rate; determining a real-time load intensity index and charging and discharging frequency of the electrochemical energy storage based on the multi-source monitoring data, and predicting the load intensity index of the electrochemical energy storage in the future by combining the predicted state of charge influence coefficient of the battery; Correcting the mode switching threshold according to the predicted load intensity index of the future electrochemical energy storage, and completing the joint scheduling of the compressed air energy storage and the electrochemical energy storage; after the joint scheduling is finished, executing a preset digestion ending operation.
2. The hybrid energy storage joint scheduling method in a new energy consumption scenario of claim 1, wherein the multi-source monitoring data comprises new energy side data, electrochemical energy storage data, compressed air energy storage data, regional environment data and regional power grid data.
3. The hybrid energy storage joint scheduling method in the new energy consumption scene according to claim 1, wherein the determining method of the current consumption rate comprises: determining real-time output data of new energy equipment based on new energy side data in the multi-source monitoring data; determining real-time electricity demand data of the regional power grid based on the regional power grid data in the multi-source monitoring data; and comparing the difference between the real-time output data and the real-time power demand data to determine the current digestion rate.
4. The hybrid energy storage joint scheduling method in a new energy consumption scenario of claim 1, wherein the energy storage device comprises an electrochemical energy storage device and a compressed air energy storage device: The collecting multisource monitoring data includes collecting electrochemical energy storage data based on the electrochemical energy storage device and collecting compressed air energy storage data based on the compressed air energy storage device.
5. The hybrid energy storage joint scheduling method in a new energy consumption scene according to claim 4, wherein the determining the switching times of the residual energy storage capacity and the historical energy storage mode of the energy storage device based on the multi-source monitoring data, and determining the mode switching threshold between the compressed air energy storage and the electrochemical energy storage in combination with the consumption rate includes: determining real-time state of charge data of the electrochemical energy storage device based on the electrochemical energy storage data, and determining the residual energy storage capacity of the electrochemical energy storage device during history mode switching according to the real-time state of charge data; counting the switching times between the compressed air energy storage mode and the electrochemical energy storage mode from the historical operation record of the energy storage equipment; Acquiring the digestion rate data corresponding to the history mode switching; And calculating a mode switching threshold based on the switching times between the compressed air energy storage mode and the electrochemical energy storage mode and combining the residual energy storage capacity and the corresponding absorption rate of the electrochemical energy storage equipment during the history mode switching.
6. The hybrid energy storage joint scheduling method in a new energy consumption scenario according to claim 5, wherein the real-time load intensity index of the electrochemical energy storage is determined by: determining device temperature data for the electrochemical energy storage device based on the electrochemical energy storage data; Determining the real-time remaining energy storage capacity of the electrochemical energy storage device; And calculating the real-time load intensity index of the electrochemical energy storage according to the equipment temperature data and the real-time residual energy storage capacity.
7. The hybrid energy storage joint scheduling method in a new energy consumption scenario according to claim 3, wherein the charge-discharge frequency is determined by: determining real-time output data of new energy equipment and real-time power consumption demand data of a regional power grid; determining an influence coefficient of the regional environment on the new energy output based on regional environment data in the multi-source monitoring data; collecting future meteorological data, and predicting new energy output at each moment in the future by combining the influence coefficient of the regional environment on the new energy output; Calculating an energy storage demand index at each moment by combining the predicted new energy output and the regional power demand at the corresponding moment, and determining an energy storage demand change curve based on the energy storage demand index at each moment; And analyzing the energy storage demand change curve to identify the charge-discharge period of the electrochemical energy storage, and calculating the charge-discharge frequency of the electrochemical energy storage according to the average time interval of the charge-discharge period.
8. The hybrid energy storage joint scheduling method in a new energy consumption scenario of claim 7, wherein the predicting the load intensity index of the future electrochemical energy storage in combination with the predicted state of charge influence coefficient of the battery comprises: acquiring the determined charging and discharging frequency of the electrochemical energy storage; Calculating charge-discharge amplitude indexes of each predicted charge-discharge process of the electrochemical energy storage according to the energy storage demand change curve, and determining a state of charge influence coefficient of the battery based on the charge-discharge amplitude indexes; Calculating a predicted load intensity component according to the charge-discharge frequency and the charge state influence coefficient; And predicting the load intensity index of the electrochemical energy storage in the future by combining the real-time load intensity index of the electrochemical energy storage and the predicted load intensity component.
9. The hybrid energy storage joint scheduling method in a new energy consumption scenario of claim 8, wherein after determining the mode switching threshold between compressed air energy storage and electrochemical energy storage, further comprising: comparing the predicted energy storage demand index with the actual energy storage demand in the same time period, and calculating a predicted error index in the same time period; Calculating an energy storage pressure index of the electrochemical energy storage device according to the real-time residual energy storage capacity and the real-time energy storage requirement of the electrochemical energy storage device; Predicting an energy storage change coefficient of new energy output based on the energy storage demand index, and calculating the necessity of energy storage mode switching at the current moment by combining the energy storage change coefficient of new energy output and the energy storage pressure index; and constructing an adjustment coefficient aiming at the mode switching threshold by combining the energy storage mode switching necessity and the prediction error index, and carrying out first correction on the mode switching threshold based on the adjustment coefficient.
10. The hybrid energy storage joint scheduling method in a new energy consumption scenario according to claim 1, wherein the modifying the mode switching threshold according to the predicted load intensity index of the future electrochemical energy storage comprises: Acquiring a mode switching threshold value at the current moment; Acquiring a predicted load intensity index of future electrochemical energy storage; And determining a correction coefficient according to the load intensity index of the electrochemical energy storage in the future, correcting the mode switching threshold value at the current moment by using the correction coefficient, and taking the mode switching threshold value after correction as a final mode switching threshold value.

Description

Hybrid energy storage joint scheduling method in new energy consumption scene Technical Field The invention relates to the technical field of data processing, in particular to a hybrid energy storage joint scheduling method in a new energy consumption scene. Background The new energy consumption refers to the whole process of effectively digesting and utilizing the renewable energy sources such as wind energy, solar energy, water energy, biomass energy and the like, namely the closed loop of power generation and power consumption by a power system or an end user through modes such as grid-connected transmission, local use, energy storage and the like. When new energy power generation is performed, the new energy power generation has strong fluctuation, intermittence and randomness, so that the new energy power generation cannot be controlled as stably as the conventional thermal power generation means, nuclear power generation means and other power generation means, and in order to ensure the stability of a power grid system, the power fluctuation needs to be smoothed through a digestion means, and the power consumption needs need to be matched. In order to solve the problem that a single energy storage method cannot cope with the complex new energy output in the new energy consumption process, the existing method combines new energy storage methods with different characteristics, such as compressed air energy storage and electrochemical energy storage. The existing joint scheduling method mainly comprises the steps of (charging stage) electrochemical energy storage and priority rapid charging, compressed air energy storage is carried out after a lithium battery is fully charged, then (discharging stage) electrochemical energy storage provides initial power, compressed air energy storage provides stable power, and electrochemical energy storage assists in adjusting fluctuation in the process. However, in the process of compressed air energy storage and electrochemical energy storage, the existing method is extremely dependent on real-time monitoring of two energy storage states, and when a monitoring signal is delayed, an overcharge or overdischarge phenomenon can occur, and when the monitoring signal is serious, equipment is damaged. Meanwhile, the electrochemical energy storage is always subjected to starting and adjusting tasks in the existing scheduling method, so that the consumption of an electrochemical energy storage system is far greater than that of compressed air energy storage, the load difference of different systems is obvious, and the long-term operation of the systems is not facilitated. Disclosure of Invention In order to solve the technical problems that in the related art, electrochemical energy storage always bears the tasks of starting and adjusting in the existing scheduling method, so that the consumption of an electrochemical energy storage system is far greater than that of compressed air energy storage, and the load difference of different systems is obvious, and the long-term operation of the systems is not facilitated, the invention aims to provide a hybrid energy storage joint scheduling method in a new energy consumption scene, and the adopted technical scheme is as follows: in a first aspect, an embodiment of the present invention provides a hybrid energy storage joint scheduling method in a new energy consumption scenario, where the hybrid energy storage joint scheduling method is applied to a system including energy storage equipment, and the method includes the following steps: Collecting multisource monitoring data and the current digestion rate; determining the residual energy storage capacity of the energy storage device and the switching times of the historical energy storage modes based on the multi-source monitoring data, and determining a mode switching threshold between compressed air energy storage and electrochemical energy storage by combining the consumption rate; determining a real-time load intensity index and charging and discharging frequency of the electrochemical energy storage based on the multi-source monitoring data, and predicting the load intensity index of the electrochemical energy storage in the future by combining the predicted state of charge influence coefficient of the battery; Correcting the mode switching threshold according to the predicted load intensity index of the future electrochemical energy storage, and completing the joint scheduling of the compressed air energy storage and the electrochemical energy storage; after the joint scheduling is finished, executing a preset digestion ending operation. In some embodiments, the multi-source monitoring data includes new energy side data, electrochemical energy storage data, compressed air energy storage data, regional environment data, and regional grid data. In some embodiments, the determining the current rate of consumption includes: determining real-time output data of new energy equipment