Energy storage power station battery compartment battery fault pre-judging and positioning method

Abstract

The invention discloses an energy storage power station battery compartment battery fault pre-judgment and positioning method, which comprises the steps of conducting single battery health degree analysis, battery performance change trend prediction and battery fault accurate pre-judgment and positioning, and obtaining battery operation parameter upper and lower limit thresholds and a battery health state in a current state by analyzing the single battery health degree; and predicting a battery performance change trend in a future period of time based on historical data in the past period of time, and pre-judging and positioning possible faults in the future in combination with upper and lower limit thresholds. Meanwhile, if it is detected that a certain or some properties of a single battery, a battery pack or a battery cluster may change suddenly in an extremely short time, possible faults in a short time can be predicted through a battery fault accurate pre-judgment and positioning function, and corresponding faults are positioned and identified through a fault expert database. Through comprehensive implementation of the method, the operation and maintenance technical support level and the system safety and stability level of the energy storage power station can be obviously improved.

Description

technical field [0001] The invention relates to a method for handling electrochemical energy storage faults, in particular to a method for predicting and locating battery faults in a battery compartment of an energy storage power station. Background technique [0002] With the continuous expansion of the scale and application scope of energy storage power stations, accidents of power stations using lithium-ion batteries for construction and operation occur from time to time. Lithium-ion energy storage batteries have high energy density and high risk of thermal runaway. It is extremely difficult to extinguish fire after a fire occurs, which will cause serious direct and indirect losses. Therefore, it is urgent to develop the fire warning function of energy storage power stations. Early detection and timely treatment can greatly reduce the possibility and harm of fires. At the same time, as the number of battery cycles increases, the consistency of the battery decreases, and ...

AI Technical Summary

Problems solved by technology

At the same time, as the number of battery cycles increases, the consistency of the battery decreases, and at the same time, the electrical, thermal, and mechanical properties of the battery are attenuated.

Therefore, timely and effective prediction, location, and source tracing of battery failures in energy storage power stations are key. However, at present, energy storage power stations lack an effective active prediction system for battery failures.

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