摘要
如何合理安排机组检修是水火电系统调度运行中的一项重要任务。在长时间尺度下,天然来水的随机性使机组检修计划本质上成为随机优化问题,通常采用场景法描述随机性,但其形成的高维优化问题难以直接求解。建立多场景耦合的水火电系统机组检修优化模型,利用多学科协同优化(Multidisciplinary Collaborative Optimization,MCO)方法将各场景间的非预期性约束及检修变量耦合约束解耦,实现了原问题的降维,且MCO结构具有内在的并行性。此外,在基于MCO的系统级优化问题中,用绝对值惩罚项替代二次惩罚项,保证该问题是一个混合整数线性规划问题,有利于提高计算效率。最后以某省级实际水火电系统为算例进行仿真分析,验证了所提模型和算法的有效性。
How to rationally arrange maintenance of generators is an important task in the dispatch and operation of hydro-thermal power systems.On a long timescale,the randomness of natural water inflow makes the generator maintenance schedule (GMS) essentially a stochastic optimization problem.The scenario-based method is usually used to describe the randomness,but it is difficult to solve efficiently the high-dimensional optimization problem with this method.This paper establishes a coupled multi-scenario GMS model of hydro-thermal power systems,applies a multi-disciplinary collaborative optimization (MCO) method to decouple the nonanticipative and the coupling constraints on maintenance variables between scenarios.Thus,the dimension of the multi-scenario GMS model is reduced and the MCO-based structure has inherent parallelism.In addition,in the MCO-based system-level optimization problem,an absolute value penalty term is introduced to replace the quadratic penalty term to ensure that the problem is a mixed integer linear programming model.This helps improve computational efficiency.Finally,a simulation calculation on a real provincial hydro-thermal power system is carried out to verify the effectiveness of the model and algorithm proposed.
作者
代江
田年杰
姜有泉
郑志佳
刘明波
谢敏
DAI Jiang;TIAN Nianjie;JIANG Youquan;ZHENG Zhijia;LIU Mingbo;XIE Min(Electric Power Dispatching and Control Center of Guizhou Power Grid Co.,Ltd.,Guiyang 550000,China;School of Electric Power Engineering,South China University of Technology,Guangzhou 510640,China)
出处
《电力系统保护与控制》
EI
CSCD
北大核心
2022年第12期44-53,共10页
Power System Protection and Control
基金
国家自然科学基金项目资助(52077083)
贵州电网有限责任公司科技项目资助(066500KK52190008)。
关键词
水火电系统
机组检修计划
场景法
非预期性约束
多学科协同优化
hydro-thermal power system
generator maintenance schedule
scenario-based method
nonanticipative constraints
multi-disciplinary collaborative optimization
