长江科学院院报 ›› 2012, Vol. 29 ›› Issue (4): 1-6.

• 水资源与环境 •    下一篇

松江河梯级水电站短期优化调度数学模型分析

冯雁敏, 张雪源, 梁年生   

  1. 1.东北电力科学研究院有限公司,沈阳 110006; 2.东北电网有限公司, 沈阳 110180; 3.华中科技大学,  武汉 430074
  • 收稿日期:2011-03-11 出版日期:2012-04-01 发布日期:2012-06-15
  • 作者简介:冯雁敏(1984-),男,河北邢台人,工程师,硕士,主要从事水电能源优化调度等方面的应用研究

Short-Term Optimal Scheduling of Songjianghe Cascade Hydropower Stations Based on Mathematical Modeling

 FENG  Yan-Min1, ZHANG  Xue-Yuan2, LIANG  Nian-Sheng3   

  1. 1. Northeast Electric Power Research Institute Co., Ltd., Shenyang 110006, China; 2. Northeast China Grid Company, Shenyang 110180,China; 3. Huazhong University of Science & Technology, Wuhan 430074, China
  • Received:2011-03-11 Online:2012-04-01 Published:2012-06-15

摘要: 应用改进粒子群算法求解松江河梯级水电站短期优化调度问题,建立梯级电站发电量最大和发电效益最大短期优化调度数学模型。针对粒子群算法存在的后期收敛速度慢和易陷入局部最优等缺点,引入收缩因子和基于遗传思想的变异算子对其进行改进。应用改进粒子群算法对松江河梯级水电站进行短期优化调度,分别采用发电量最大和发电效益最大数学模型进行算例分析。结果表明:对梯级电站进行短期优化调度可以提高梯级电站的整体质量和效益;应用改进粒子群算法求解梯级电站短期优化调度问题在求解时间、精度上都取得了满意的效果。

关键词: 松江河梯级水电站, 短期优化调度, 粒子群算法, 发电效益最大模型

Abstract: Improved Particle Swarm Optimization (PSO) is applied to solving the short-term optimal scheduling of Songjianghe cascade hydropower stations. Two mathematic models characterized respectively by maximum  power generation and maximum  generation profit are established. Shrinkage factor and hereditary mutation operator are adopted to overcome the shortcomings of standard PSO like precocity and slow convergence in late stage. These  mathematical models are employed in the optimal scheduling analysis for Songjianghe cascade power stations, and the results show that the quality and benefit of the stations could be improved by short-term optimal scheduling. Both the calculation time and accuracy by applying the improved PSO are satisfactory.

Key words: Songjianghe cascade hydropower stations, short-term optimal scheduling, Particle Swarm Optimization, model of maximum generation profit

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