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Optimal Coordination of Source‐Load in Microgrid Based on Improved NSGA‐III Algorithm
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Optimal Coordination of Source‐Load in Microgrid Based on Improved NSGA‐III Algorithm
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Journal Article
Optimal Coordination of Source‐Load in Microgrid Based on Improved NSGA‐III Algorithm
2025
Overview
In view of the problem of weak source‐load matching and insufficient optimisation capability of multi‐objective solution methods in microgrids, an improved reference point non‐dominated sorting genetic algorithm (NSGA‐III) is proposed for the optimal configuration of interconnected multi‐source microgrids. Firstly, considering the demand response (DR) of user load, the load curve is optimised and the real‐time electricity price curve is obtained. Based on the information obtained from DR, an optimisation and scheduling model for a wind‐solar‐microturbine‐storage‐diesel microgrid is established with the objectives of minimising economic cost and the minimum emission of pollutants. The improved entropy formula is used to determine the switching timing of evolution strategies, and the NSGA‐III algorithm improved by differential evolution (DE) is used to solve the microgrid optimisation problem. Furthermore, the technique for order of preference by similarity to ideal solution (TOPSIS) is employed to determine the weight of the two objectives, and a compromise solution is selected from the Pareto front (PF). Finally, the case study is conducted to demonstrate that the introduction of DR strategies can effectively improve the load curve, and the improved NSGA‐III algorithm can further enhance the diversity of the population, validating the rationality and feasibility of the proposed method. An improved reference point NSGA‐III is proposed for the optimal configuration of interconnected multi‐source microgrids. Considering the DR of user load, the load curve is optimised and the real‐time electricity price curve is obtained. An optimisation and scheduling model for a wind‐solar‐microturbine‐storage‐diesel microgrid is established with the objectives of minimising economic cost and the minimum emission of pollutant.
Publisher
Wiley
