| 摘要: |
| 为绘制高效可靠的水库运行调度图，以平衡保证出力保证率与发电量矛盾的惩罚系数为优化变量、以保证出力设计保证率满足条件下发电量最大为目标函数，综合集成以黄金分割法为时段决策优选法的随机动态规划核心模型，以及评估调度方案优劣时历法长系列模拟计算模块，利用遗传算法的并行计算能力，结合电站调度方案制定与有效性检验，构建水电站水库长期优化调度模型。应用结果表明：所建模型具有不受年调节和多年调节库容机械划分约束、快速获得满足发电保证率所要求的优化调度图的优秀特性；较之常规调度方法，可增发电量2.0%以上，保证率更高，决策信息更丰富。 |
| 关键词: 水资源管理 水库优化调度 随机动态规划 遗传算法 调度图 |
| DOI： |
| 分类号:TV697.1 |
| 基金项目:国家自然科学基金资助项目（51279223，51479119); 水利部公益性行业科研专项经费项目（201301003,201501054）； 国家重点研发计划课题（2016YC0400906） |
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| Long-term reservoir optimal operation model and operation curves for hydropower based on genetic algorithm and stochastic dynamic programming |
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WANG Zong-zhi1, WANG Wei2, LIU Ke-lin1, CHENG Liang1
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1.State Key Laboratory of Hydrology-Water Resources and Hydraulic Engineering, Nanjing Hydraulic Research Institute, Nanjing;2.Management Department of Foziling Reservoir, Lu'an
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| Abstract: |
| Owing to uncertainties of hydrological forecast and directives, the operation rules play a very important role in managing reservoirs, and are the most commonly used and effective tools for the reservoir dispatching operation of hydropower stations, though the real time optimal operation based on mid- and long-term hydrological forecasting information which has been studied for many years. So the development of the reservoir optimal operation model for formulating operation rules has always been a research hotspot in the relevant field. A model named long-term reservoir optimal operation model for hydropower, based on genetic algorithm and stochastic dynamic programming (hereafter referred to as LROOH) is established, which couples the stochastic dynamic programming and the real coding accelerating genetic algorithm. This model solves the difficult problem with a satisfied scheme, via building the objective function and minimizing the absolute values of the difference between the calculation reliability of the guaranteed capability and its target reliability, with penalty coefficient as an independent variable, and making full use of the parallel computing ability of genetic algorithm. And then the LROOH becomes much easier to have access to the global optimal solution by using the real coding accelerating genetic algorithm instead of 0.618 methods that are usually used before to improve the computing efficiency. As an example, the LROOH is applied to an annual regulation of a reservoir of the hydropower station. The research results show that the model is effective, with some excellent properties that are without any constraint of annual and multi-year regulating storage, and that the optimal rules can meet the requirements of the guaranteed reliability and increase output by more than 2.0% with a higher reliability. |
| Key words: water resource management reservoir optimal operation stochastic dynamic programming genetic algorithm operation curves |
