边缘计算使能的分布式微电网资源交易策略  

Edge Computing Enabled Distributed Microgrids Resources Trading Strategy

作　　者：麦尚柯 刘义[1] MAI Shangke;LIU Yi(Guangdong University of Technology,Guangzhou 510006,China)

机构地区：[1]广东工业大学,广州510006

出　　处：《新能源进展》2023年第5期484-490,共7页Advances in New and Renewable Energy

基　　金：国家自然科学基金项目(61773126)。

摘　　要：针对分布式微电网节点中边缘计算服务器的能源损耗问题,以及微电网的计算资源受限问题,提出一种边缘计算使能的多微电网节点的资源交易策略。对搭载着边缘计算服务器的多微电网模型中的能源交易、计算资源交易进行计算,使得多微电网社区运营成本的最小化(MIN)问题得到最优策略。结果表明,改进的非支配排序遗传算法(NSGA-Ⅱ)中,适应度评价函数呈逐渐收敛趋势,得到帕累托前沿上的最优解集为多微电网节点之间资源交易的最优策略,相比单个微电网节点的运行成本更低。A resource trading strategy for edge computing enabled multi-microgrid nodes was proposed for the energy loss problem of edge computing servers in distributed microgrid nodes and the computing resources constraint problem of microgrids.Energy trading and computing resources trading in the microgrid model with edge computing server were computed so that the optimal strategy was obtained for the minimization(MIN)problem of multi-microgrid community operation cost.The results showed that the fitness evaluation function in the improved non-dominated sorting genetic algorithm(NSGA-II)showed a gradual convergence trend,and the optimal set of solutions on the Pareto front was obtained as the optimal strategy for resource trading among multi-microgrid nodes,which had a lower operating cost compared to a single microgrid node.

关 键 词：微电网 边缘计算 分布式 资源交易 遗传算法 

分 类 号：TK02[动力工程及工程热物理] TK89