As global attention on renewable and clean energy grows, the research and implementation of microgrids become paramount. This paper delves into the methodology of exploring the relationship between the operational and environmental costs of microgrids through multi-objective optimization models. By integrating various optimization algorithms like Genetic Algorithm, Simulated Annealing, Ant Colony Optimization, and Particle Swarm Optimization, we propose an integrated approach for microgrid optimization. Simulation results depict that these algorithms provide different dispatch results under economic and environmental dispatch, revealing distinct roles of diesel generators and micro gas turbines in microgrids. Overall, this study offers in-depth insights and practical guidance for microgrid design and operation.

翻译：随着全球对可再生能源与清洁能源关注度的提升，微电网的研究与实施变得至关重要。本文深入探讨了通过多目标优化模型探索微电网运行成本与环境成本关系的方法。通过集成遗传算法、模拟退火算法、蚁群优化算法和粒子群优化算法等多种优化算法，提出了一套微电网优化综合方案。仿真结果表明，这些算法在经济调度与环境调度下呈现出不同的调度结果，揭示了柴油发电机与微型燃气轮机在微电网中的不同作用。总体而言，本研究为微电网的设计与运行提供了深入见解与实践指导。