Abstract
The microgrid environmental governance problem is a single objective function, and the biogeography algorithm traditionally used for the calculation has significant shortcomings. The algorithm has a limited search range at the beginning of the iteration and tends to fall into a local optimum at the end. In addition, it is slow to converge and poor in finding the best solution when solving microgrid scheduling optimization problems. In this paper, we adopt a typical microgrid environmental management framework model and use a stochastic ranking evolutionary strategy algorithm with high performance. The objective function is to minimize the ecological management cost and optimize the rational dispatch of electricity to gas and energy storage devices. The case study proves that the stochastic ranking evolutionary strategy algorithm is more efficient and converges faster. This algorithm can effectively solve the energy dispatching optimization problem in microgrids.
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