Design of performance evaluation system for electrochemical energy storage power plants based on NSGA-II

Energy storage power stations can ensure the stability of wind and photovoltaic distribution networks, but the evaluation algorithms for measuring their reliability and economy are not comprehensive. The study proposes a performance evaluation system for electrochemical energy storage power plants based on an improved non-dominated sorting genetic algorithm. The experiment showed that compared with multi-objective particle algorithm and second-generation strength Pareto evolutionary algorithm, the research method had a better global optimisation level. The algorithm has been improved to increase its running and convergence speed by 3-5 times. An evaluation of the economic and reliability of the distribution network for a specific energy storage power station has been conducted. The annual return rates considering economy, reliability, and comprehensive coordinated investment were 13.05%, 9.05%, and 10.35%, respectively. This algorithm shows good reference value in terms of economic cost and technical reliability.