Mixed energy storing capacity optimization method for optimizing micro-grid call wire power

Abstract

The invention discloses a mixed energy storing capacity optimization method for optimizing micro-grid call wire power. A fitness function of a genetic algorithm is constructed through a mixed energy storing capacity optimization model and sample data of mixed energy storing total charging / discharging power is obtained; a frequency range is subjected to binary coding to generate a first-generation dividing frequency fP group; active powers PBESS and PSC of a storage battery and a super capacitor of any one individual in the first-generation group are respectively calculated according to the mixed energy storing capacity optimization model; rated capacities of the storage battery and the super capacitor are respectively calculated through the active powers PBESS and PSC of the storage battery and the super capacitor; an engineering period net present value of a mixed energy storing system, the service life of the storage battery and the service life of the super capacitor are obtained according to the rated capacities of the storage battery and the super capacitor and the active powers of the storage battery and the super capacitor; an individual with the highest fitness in the final generation is an optimal individual; and meanwhile, an optimal mixed energy storing capacity combination is obtained. An obtained capacity result is accurate and the estimation of the service life of energy storing equipment is realized.

Description

Technical field [0001] The invention relates to a method for optimizing the capacity of a hybrid energy storage system in a microgrid, and in particular to a method for optimizing a hybrid energy storage capacity for optimizing the power of a microgrid tie line. Background technique [0002] In microgrid, the output power of distributed power sources such as wind power and solar photovoltaic is intermittent and random, and load changes often reflect certain fluctuations, which brings greater challenges to the stable operation of microgrids. Energy storage systems can solve this problem. Energy storage equipment is divided into two types: power type energy storage and energy type energy storage. The energy storage system that aims to smooth the power output of distributed power sources requires fast response speed and long cycle charge and discharge life. It is suitable for the use of power-type energy storage represented by supercapacitors; energy storage systems that target pea...

AI Technical Summary

Problems solved by technology

[0005] (1) The energy storage charge and discharge efficiency and SOC (state of charge) constraints are not considered in detail, resulting in a small capacity;

[0006] (2) There is a lack of assessment of the life of energy storage equipment, and the actual operating results may greatly affect the economy because a certain energy storage equipment needs to be updated many times

Therefore, the current hybrid energy storage capacity optimization method is not deep enough and has not reached the practical level.

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