Abstract
Valve-controlled battery is the main component of DC power supply system in mainstream substation. The method of determining the inconsistency of battery banks by measuring the capacity of independent charge and discharge experiments has some limitations, and the single battery needs to be separated independently, which is not suitable for the DC battery system running in series online. Aiming at this problem, an inconsistency evaluation model of battery banks for DC power system based on the combination of comprehensive weighting method and grey clustering is constructed. Firstly, entropy weight method and analytic hierarchy process (AHP) were used to obtain the subjective and objective weights of the battery performance parameters, and then the comprehensive weights of the judgment indicators were obtained. Grey clustering was used to comprehensively evaluate the inconsistency of each performance index, and the evaluation model was verified by online detection of battery performance parameters in substation. The evaluation model can evaluate the inconsistency of battery banks under multiple indexes, which provides a practical method and theoretical basis for online screening of backward batteries and ensuring the stable operation of DC battery system.
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