| 引用本文: | 代 江,田年杰,姜有泉,等.考虑天然来水随机性的水火电系统机组检修计划[J].电力系统保护与控制,2022,50(12):45-53.[点击复制] |
| DAI Jiang,TIAN Nianjie,JIANG Youquan,et al.Generator maintenance schedule of hydro-thermal power systems consideringrandomness of natural water inflow[J].Power System Protection and Control,2022,50(12):45-53[点击复制] |
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| 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。 |
| 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 |
| DOI：DOI: 10.19783/j.cnki.pspc.211035 |
| 投稿时间：2021-08-05修订日期：2021-09-23 |
| 基金项目: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) |
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| Generator maintenance schedule of hydro-thermal power systems consideringrandomness of natural water inflow |
| DAI Jiang,TIAN Nianjie,JIANG Youquan,ZHENG Zhijia,LIU Mingbo,XIE Min |
| (1. Electric Power Dispatching and Control Center of Guizhou Power Grid Co., Ltd., Guiyang 550000, China;
2. School of Electric Power Engineering, South China University of Technology, Guangzhou 510640, China) |
| Abstract: |
| 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.
This work is supported by the National Natural Science Foundation of China (No. 52077083). |
| Key words: hydro-thermal power system generator maintenance schedule scenario-based method nonanticipative constraints multi-disciplinary collaborative optimization |
