Two-stage Multi-objective Optimization and Decision-making Method for Integrated Energy System Under Wind Generation Disturbances

作     者：Bin Deng Xiaosheng Xu Mengshi Li Tianyao Ji Q.H.Wu 

作者机构：School of Electric Power EngineeringSouth China University of TechnologyGuangzhou 510640China 

出 版 物：《CSEE Journal of Power and Energy Systems》 (中国电机工程学会电力与能源系统学报（英文）)

年 卷 期：2024年第10卷第6期

页      面：2564-2576页

核心收录：

学科分类：08[工学] 0807[工学-动力工程及工程热物理] 

主　　题：Decision making integrated energy systems(IES) two-stage algorithm wind generation disturbances 

摘      要：Although integrated energy systems(IES)are currently modest in size,their scheduling faces strong challenges,stemming from both wind generation disturbances and the system’s complexity,including intrinsic heterogeneity and pronounced *** this reason,a two-stage algorithm called the Multi-Objective Group Search Optimizer with Pre-Exploration(MOGSOPE)is proposed to efficiently achieve the optimal solution under wind generation *** optimizer has an embedded trainable surrogate model,Deep Neural Networks(DNNs),to explore the common features of the multiscenario search space in advance,guiding the population toward a more efficient search in each ***,a multiscenario Multi-Attribute Decision Making(MADM)approach is proposed to make the final decision from all alternatives in different wind *** reflects not only the decisionmaker’s(DM)interests in other indicators of IES but also their risk preference for wind generation disturbances.A case study conducted in Barry Island shows the superior convergence and diversity of MOGSOPE in comparison to other optimization *** respect to numerical performance metrics HV,IGD,and SI,the proposed optimizer exhibits improvements of 3.1036%,4.8740%,and 4.2443%over MOGSO,and 4.2435%,6.2479%,and 52.9230%over NSGAII,***’s more,the effectiveness of the multi-scenario MADM in making final decisions under uncertainty is demonstrated,particularly in optimal scheduling of IES under wind generation disturbances.