Day-ahead scheduling of microgrid with hydrogen energy considering economic and environmental objectives
Guangzhe Jin, Kaixin Huang, Chen Yang, Jingxiang Xu
Abstract
Conventional microgrids face challenges such as high costs, waste heat, and significant polluting emissions. Hydrogen energy systems can reduce costs and produce zero emissions. Therefore, this paper proposes a co-scheduling method for power and equipment waste heat to address the economic and environmental dispatch (EED) problem of hydrogen microgrids. Firstly, this paper establishes a co-scheduling model for power and heat in hydrogen microgrids without thermal storage. Then, in terms of optimization methods, this study introduces the Improved Honey Badger Algorithm (IHBA), which incorporates piecewise mapping initialization and a segmented optimal decreasing Levy flight strategy. Sensitivity analysis is employed to optimize the parameters of the IHBA and to compare its performance with other methods. Additionally, this paper presents a comparison framework based on the Technique for Order Preference by Similarity to Ideal Solution (TOPSIS) model to identify algorithms that achieve an optimal balance of solution quality and efficiency for the EED problem in hydrogen microgrids. The combined cost of the hydrogen microgrid is reduced by 16.47 % compared to a conventional microgrid. Moreover, the IHBA algorithm reduces the combined cost of the hydrogen microgrid by 5.5 % compared to the standard HBA algorithm.