区域综合能源系统两阶段鲁棒优化实验案例教学  

Two-stage robust optimization experimental case teaching of regional integrated energy systems

作　　者：邵振国[1] 林勇棋 陈煜超 陈飞雄 SHAO Zhenguo;LIN Yongqi;CHEN Yuchao;CHEN Feixiong(College of Electrical Engineering and Automation,Fuzhou University,Fuzhou 350108,China;Putian Power Supply Company of State Grid Fujian Power Co.,Ltd.,Putian 351100,China;Zhangzhou Power Supply Company of State Grid Fujian Power Co.,Ltd.,Zhangzhou 363000,China)

机构地区：[1]福州大学电气工程与自动化学院,福建福州350108 [2]国网福建省电力有限公司莆田供电公司,福建莆田351100 [3]国网福建省电力有限公司漳州供电公司,福建漳州363000

出　　处：《实验技术与管理》2024年第8期175-181,共7页Experimental Technology and Management

基　　金：福建省本科高校研究生教育教学改革研究项目“双碳目标下能源动力专业学位研究生培养模式探索与实践”(FBJG202120348);福建省数字能源产教融合研究生联合培养基地;福建省一流本科课程-电力系统继电保护基础;福州大学一流本科课程建设项目-电力系统继电保护基础/系统建模与仿真技术。

摘　　要：两阶段鲁棒优化可根据不确定性变化动态调整决策,有效改善日前决策保守性,从而为解决新能源不确定性的优化调度问题提供一种方案选择。由于区域综合能源系统两阶段鲁棒优化方法前沿性强、内容复杂度高、学习难度大,传统教学方法难以有效传达其核心概念和应用,无法很好地达到教学目的。为解决这一教学挑战,该文构建了区域综合能源系统仿真实验教学平台,提出了区域综合能源系统两阶段鲁棒优化实验方案,并设计了三个仿真实验案例。通过实验平台建设和案例设计,提升了学生对区域综合能源系统两阶段鲁棒优化方法相关理论知识的理解和认识,增强了学生的综合分析能力和工程实践能力。[Objective]As one of many uncertain optimization methods,the robust optimization method does not need a specific probability distribution function.Instead,it only needs to master the range of uncertainty to realize the reliable operation of a system.Two-stage robust optimization dynamically adapts decisions in response to evolving uncertainties.This approach significantly enhances the conservative nature of day-ahead decisions,providing an effective scheme to solve the problem of the optimal scheduling of new energy uncertainty.Nonetheless,the advanced and intricate nature of two-stage robust optimization for regional integrated energy systems(RIESs)makes its fundamental principles and practical applications difficult to impart through conventional teaching methods.Its complexity and steep learning curve hinder the effective fulfillment of teaching aims.[Methods]To address this pedagogical challenge,this study develops a simulation experimental teaching platform tailored for RIES.It introduces an experimental scheme based on two-stage robust optimization for such systems.The first optimization stage accounts for the costs associated with starting and stopping units.It aims to optimize both the start–stop cycles of equipment and the energy interactions within the system,thereby establishing the operational states and energy exchanges of the units.Subsequently,the second optimization stage refines the equipment output based on the first stage's scheduling outcomes,seeking the most adverse scenario amidst the fluctuations of uncertain variables.Ultimately,the column-and-constraint generation algorithm is employed iteratively to resolve the two-stage conundrum,deriving the optimal resolution for the original problem.This ensures the system's optimal performance,even when faced with variable uncertainties.[Results]The RIES two-stage robust optimization experiment shows the following:1)Implementing virtual heat storage within the system yields a 4.3%cost reduction compared with systems lacking this feature.The heat p

关 键 词：区域综合能源系统 仿真实验教学平台 案例教学 两阶段鲁棒优化 

分 类 号：TM771[电气工程—电力系统及自动化]