CN-121984192-A - Intelligent solar comprehensive remote control system

CN121984192ACN 121984192 ACN121984192 ACN 121984192ACN-121984192-A

Abstract

The invention relates to the technical field of intelligent control of solar power supply and energy storage systems, in particular to an intelligent solar comprehensive remote control system which comprises a multi-dimensional state acquisition unit, a coupling modeling unit, a health state prediction unit, a prospective correction unit, a risk and benefit evaluation unit and a grading decision unit, wherein the multi-dimensional state acquisition unit is used for acquiring solar irradiance and environmental temperature of a solar power supply system, acquiring internal temperature and charge state of a battery energy storage system and receiving a task opportunity window, the coupling modeling unit is used for determining maximum allowable instantaneous charging current and task opportunity quantitative value, the health state prediction unit is used for calculating ideal charging current and determining comprehensive health loss factors, the prospective correction unit is used for generating candidate charging current, the risk and benefit evaluation unit is used for determining damage risk indexes and risk and benefit comprehensive indexes, and the grading decision unit is used for generating opportunistic fast charging instructions, balanced charging instructions or protective slow charging instructions.

Inventors

ZHOU XUEHUI
ZHANG PENG
Qin Wenshi

Assignees

广西工业职业技术学院
广西再发能源科技有限公司

Dates

Publication Date: 20260505
Application Date: 20260213

Claims (8)

1. An intelligent solar energy integrated remote control system, comprising: The multi-dimensional state acquisition unit is used for acquiring solar irradiance and environmental temperature of the solar power supply system, acquiring internal temperature and state of charge of the battery energy storage system, and receiving a task opportunity window, task priority and energy required by a single task of the task scheduling system; The coupling modeling unit is used for carrying out dynamic safety boundary quantitative analysis based on the internal temperature and the state of charge so as to determine the maximum allowable instantaneous charging current, and carrying out task value coupling modeling analysis based on the task priority, the energy required by a single task and a task opportunity window so as to determine the task opportunity quantitative value; the health state prediction unit is used for calculating ideal charging current according to the energy required by a single task and a task opportunity window, carrying out health state evolution deduction based on the ideal charging current, and determining a comprehensive health loss factor; the prospective correction unit is used for combining the ideal charging current and the comprehensive health loss factor to generate candidate charging current; The risk benefit evaluation unit is used for determining a damage risk index based on the candidate charging current, and is also used for determining a risk benefit comprehensive index by combining the task opportunity quantitative value and the damage risk index; The grading decision unit is used for generating an opportunistic fast charging instruction, a balanced charging instruction or a protective slow charging instruction according to the risk and income comprehensive index and the damage risk index and combining a preset threshold value.
2. The intelligent solar energy integrated remote control system according to claim 1, wherein the process of determining the maximum allowable instantaneous charging current by the coupling modeling unit comprises: Based on the internal temperature and the real-time state of charge of the battery energy storage system, and by combining with a preset reference maximum charging current, a reference temperature, a temperature attenuation coefficient and a state of charge suppression index, the calculation is performed through a dynamic safety boundary quantization equation.
3. The intelligent solar energy integrated remote control system of claim 1, wherein the process of determining the task opportunity quantification value by the coupled modeling unit comprises: Based on the task priority, the energy required by a single task, the rated total energy of a battery, the residual effective time window of the task, a preset reference time window and a time sensitivity coefficient are calculated through a task opportunity window value evaluation equation.
4. The intelligent solar energy integrated remote control system of claim 1, wherein the process of determining the integrated health loss factor by the health status prediction unit comprises: Predicting cumulative thermal aging factors and cumulative lithium-precipitation risk factors; the cumulative thermal aging factor and the cumulative lithium risk factor are weighted summed to generate the integrated health loss factor.
5. The intelligent solar energy integrated remote control system according to claim 4, wherein the cumulative thermal aging factor is characterized by a cumulative chemical side reaction amount generated by high temperature calculated by the arrhenius equation according to a predicted battery temperature curve during a prediction period.
6. The intelligent solar comprehensive remote control system according to claim 4, wherein the accumulated lithium precipitation risk factor is characterized in that in a prediction period, when the predicted battery temperature is lower than a preset lithium precipitation critical temperature, the accumulated lithium precipitation damage amount is calculated according to the ratio of the charging current scheduled to be executed to the dynamic safety current at the corresponding moment.
7. The intelligent solar energy integrated remote control system of claim 1, wherein the risk and benefit assessment unit determines the damage risk index comprises: comparing the candidate charging current with the maximum allowable instantaneous charging current, and comparing the internal temperature of the battery with a preset upper limit of the safe temperature of the battery; And then combining the temperature risk scale factor, the current risk scale factor and the corresponding weight coefficient, and calculating through a charging damage risk quantization equation.
8. The intelligent solar energy integrated remote control system of claim 1, wherein the step of generating instructions by the hierarchical decision unit comprises: when the risk and benefit comprehensive index is larger than a preset risk and benefit threshold value and the damage risk index is not larger than a preset maximum damage threshold value, generating an opportunistic quick charging instruction; When the risk benefit comprehensive index is not greater than a preset risk benefit threshold value and the damage risk index is not greater than a preset maximum damage threshold value, generating an equalizing charge instruction; and when the damage risk index is larger than a preset maximum damage threshold value, generating a protective slow charging instruction.

Description

Intelligent solar comprehensive remote control system Technical Field The invention relates to the technical field of intelligent control of solar power supply and energy storage systems, in particular to an intelligent solar comprehensive remote control system. Background In the application scene which highly depends on solar power supply and has strong task timeliness, such as an unmanned aerial vehicle airport, the traditional battery charging strategy faces core technical problems, the traditional scheme generally adopts a fixed charging mode or simply controls according to a single battery state threshold value; The method and the device have the advantages that fundamental contradiction is caused, the aggressive charging strategy can meet the urgent nature of the task, but can accelerate the irreversible loss of the energy storage battery and shorten the service life of the energy storage battery, while the conservative strategy can protect the battery, but often misses a high-value task window, the prior art is difficult to carry out data-driven dynamic balance between the task execution efficiency and the battery health cost, therefore, a comprehensive decision model which can integrate task requirements, energy states and battery health evolution prediction is established, the dynamic optimization of the charging strategy is realized, and the task supporting capability is maximized on the premise of guaranteeing the long-term safety and the service life of the energy storage system, so that the method and the device become the technical problem to be solved urgently. Disclosure of Invention In order to solve the technical problems, the invention provides an intelligent solar comprehensive remote control system, which comprises the following technical scheme: The multi-dimensional state acquisition unit is used for acquiring solar irradiance and environmental temperature of the solar power supply system, acquiring internal temperature and state of charge of the battery energy storage system, and receiving a task opportunity window, task priority and energy required by a single task of the task scheduling system; The coupling modeling unit is used for carrying out dynamic safety boundary quantitative analysis based on the internal temperature and the state of charge so as to determine the maximum allowable instantaneous charging current, and carrying out task value coupling modeling analysis based on the task priority, the energy required by a single task and a task opportunity window so as to determine the task opportunity quantitative value; the health state prediction unit is used for calculating ideal charging current according to the energy required by a single task and a task opportunity window, carrying out health state evolution deduction based on the ideal charging current, and determining a comprehensive health loss factor; the prospective correction unit is used for combining the ideal charging current and the comprehensive health loss factor to generate candidate charging current; The risk benefit evaluation unit is used for determining a damage risk index based on the candidate charging current, and is also used for determining a risk benefit comprehensive index by combining the task opportunity quantitative value and the damage risk index; The grading decision unit is used for generating an opportunistic fast charging instruction, a balanced charging instruction or a protective slow charging instruction according to the risk and income comprehensive index and the damage risk index and combining a preset threshold value. Preferably, the process of determining the maximum allowable instantaneous charging current by the coupling modeling unit includes: Based on the internal temperature and the real-time state of charge of the battery energy storage system, and by combining with a preset reference maximum charging current, a reference temperature, a temperature attenuation coefficient and a state of charge suppression index, the calculation is performed through a dynamic safety boundary quantization equation. Preferably, the process of determining the task opportunity quantization value by the coupling modeling unit includes: Based on the task priority, the energy required by a single task, the rated total energy of a battery, the residual effective time window of the task, a preset reference time window and a time sensitivity coefficient are calculated through a task opportunity window value evaluation equation. Preferably, the process of determining the integrated health loss factor by the health status prediction unit includes: Predicting cumulative thermal aging factors and cumulative lithium-precipitation risk factors; the cumulative thermal aging factor and the cumulative lithium risk factor are weighted summed to generate the integrated health loss factor. Preferably, the cumulative thermal aging factor characterizes the cumulative chemical side reaction due to high temperature calcu