CCHP-Type Micro-Grid Scheduling Optimization Based on Improved Multi-Objective Grey Wolf Optimizer  

作　　者：Yu Zhang Sheng Wang Fanming Zeng Yijie Lin 

机构地区：[1]College of Mechanical and Control Engineering,Guilin University of Technology,Guilin,541006,China

出　　处：《Energy Engineering》2025年第3期1137-1151,共15页能源工程(英文)

基　　金：supported by the Open Fund of Guangxi Key Laboratory of Building New Energy and Energy Conservation(Project Number:Guike Energy 17-J-21-3).

摘　　要：With the development of renewable energy technologies such as photovoltaics and wind power,it has become a research hotspot to improve the consumption rate of new energy and reduce energy costs through algorithm improvement.To reduce the operational costs of micro-grid systems and the energy abandonment rate of renewable energy,while simultaneously enhancing user satisfaction on the demand side,this paper introduces an improvedmultiobjective Grey Wolf Optimizer based on Cauchy variation.The proposed approach incorporates a Cauchy variation strategy during the optimizer’s search phase to expand its exploration range and minimize the likelihood of becoming trapped in local optima.At the same time,adoptingmultiple energy storage methods to improve the consumption rate of renewable energy.Subsequently,under different energy balance orders,themulti-objective particle swarmalgorithm,multi-objective grey wolf optimizer,and Cauchy’s variant of the improvedmulti-objective grey wolf optimizer are used for example simulation,solving the Pareto solution set of the model and comparing.The analysis of the results reveals that,compared to the original optimizer,the improved optimizer decreases the daily cost by approximately 100 yuan,and reduces the energy abandonment rate to zero.Meanwhile,it enhances user satisfaction and ensures the stable operation of the micro-grid.

关 键 词：MULTI-OBJECTIVE optimization algorithm hybrid energy storage MICRO-GRID CCHP 

分 类 号：O17[理学—数学]