Large-scale hydropower system optimization using dynamic programming and object-oriented programming: the case of the Northeast China Power Grid

被引：15

作者：

Li, Ji-Qing ^{[1
]}

Zhang, Yu-Shan ^{[2
]}

Ji, Chang-Ming ^{[1
]}

Wang, Ai-Jing ^{[1
]}

Lund, Jay R. ^{[3
]}

机构：

[1] North China Elect Power Univ, Renewable Energy Sch, Natl Engn Lab Biomass Power Generat Equipment, Beijing 102206, Peoples R China

[2] Project Commiss State Council, Off South To North Water Div, Beijing 100053, Peoples R China

[3] Univ Calif Davis, Davis, CA 95616 USA

来源：

WATER SCIENCE AND TECHNOLOGY | 2013年 / 68卷 / 11期

基金：

中国国家自然科学基金;

关键词：

discrete differential dynamic programming; long-term optimal scheduling model; object-oriented programming; parallel and serial hydroelectric power stations; MULTIRESERVOIR SYSTEMS; RESERVOIR MANAGEMENT; OPERATION; DECOMPOSITION; MODELS;

D O I：

10.2166/wst.2013.528

中图分类号：

X [环境科学、安全科学];

学科分类号：

08 ; 0830 ;

摘要：

This paper examines long-term optimal operation using dynamic programming for a large hydropower system of 10 reservoirs in Northeast China. Besides considering flow and hydraulic head, the optimization explicitly includes time-varying electricity market prices to maximize benefit. Two techniques are used to reduce the 'curse of dimensionality' of dynamic programming with many reservoirs. Discrete differential dynamic programming (DDDP) reduces the search space and computer memory needed. Object-oriented programming (OOP) and the ability to dynamically allocate and release memory with the C++ language greatly reduces the cumulative effect of computer memory for solving multi-dimensional dynamic programming models. The case study shows that the model can reduce the 'curse of dimensionality' and achieve satisfactory results.

引用

页码：2458 / 2467

页数：10

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