Optimal placement and capacity sizing of energy storage systems via NSGA-II in active distribution network

In recent years, with the rapid development of renewable energy, penetration rate energy generation in active distribution network (ADN) has increased. Because instability generation, operation stability ADN decreased. Due to ability cut peak load and fill valley load, battery storage systems (BESSs) can enhance electric system. However, placement capacity BESSs connected are extremely significant, otherwise, it will lead a further decline ADN. To ensure effectiveness grid, this work uses fuzzy kernel C-means (FKCM) method for scene clustering. Meanwhile, multi-objective optimization model BESS configuration is established objective cost, voltage fluctuation, solved by non-dominated sorting genetic algorithm-II (NSGA-II). work, grey target decision based on entropy weight (EWM) used obtain optimal compromise solution from Pareto set. Moreover, proposed tested verified extended IEEE-33 node system IEEE-69 The results show that scheme obtained NSGA-II effectively reduce fluctuation improve operation.