Research on node voltage indices for battery storage management through fuzzy decision making in power distribution networks

Abstract

This paper presents research on power management of a battery storage system (With the aim of reducing system losses) Without information about loads in a power distribution network with installed renewable energy sources and distributed generation. The poWer management of the storage system used in the research is based on a fuzzy inference system to define the input or output poWer of the battery storage system. The optimization procedure to determine the optimal parameters of the power management system is also provided. Except for the optimal allocation of the battery storage and distributed generation systems, the optimization of the parameters is performed along with the allocation optimization. The whole optimization problem is solved for the annual data of load and generation profiles of renewable sources using hourly values, i.e., the optimization is solved simultaneously for 8760 load and generation data. The optimization problem is solved by co-simulation using the metaheuristic optimization technique. Since the method is based on the use of fuzzy systems and metaheuristic optimization, it represents the implementation of computer intelligence for optimal allocation and energy management problems. The presented method is applied to the test distribution system IEEE with 37 nodes. The achieved reduction in annual energy losses is about 40 % of the losses in the power system without the distributed generation units and the battery storage system.