黄景光a,b,c,吴巍a,b,程璐瑶a,于楠a,c,陈波a,c,张雪映a,b.基于水循环算法的梯级水电站短期优化调度[J].水电能源科学,2019,37(1):65-69
基于水循环算法的梯级水电站短期优化调度
Short-term Optimal Scheduling of Cascade Hydropower Stations Based on Water Cycle Algorithm
  
DOI:
中文关键词:  梯级水电站  分时电价  水循环算法  短期优化调度  发电效益
英文关键词:cascade hydropower station  time-of-use tariff  water cycle algorithm  short-term optimal scheduling  power generation benefit
基金项目:国家自然科学基金项目(51477090)
作者单位
黄景光a,b,c,吴巍a,b,程璐瑶a,于楠a,c,陈波a,c,张雪映a,b 三峡大学 a. 电气与新能源学院 b. 梯级水电站运行与控制湖北省重点实验室 c. 新能源微电网湖北省协同创新中心 湖北 宜昌 443002 
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中文摘要:
      鉴于梯级水电站优化运行的高复杂度、强非线性、多约束等特点,构建了基于峰谷分时电价下的梯级水电站日最大发电效益模型。针对遗传算法(GA)等传统智能算法对复杂模型求解易陷入局部最优的问题,提出一种水循环算法(WCA)与水位廊道约束耦合、降低约束复杂度、规范寻优空间的方法,并以湖北某梯级短期优化调度为背景进行建模仿真,将计算结果分别与GA和粒子群算法(PSO)所得结果进行比较。实例研究表明,WCA计算的总效益在丰、平、枯典型日分别比GA和PSO计算值约高5.65%、3.15%、0.80%,迭代收敛速度更快,求解能力更强,为解决梯级水电站优化调度问题提供了新思路。
英文摘要:
      In view of the characteristics of optimal operation of cascade hydropower stations, such as high complexity, strong non-linearity and multiple constraints, taking peak-load regulation and time-of-use tariff as research background, this paper established a daily scheduling model of cascade hydropower stations. At the same time, the traditional intelligent algorithms can easily trap into local extremum for solving complex models, water cycle algorithm (WCA) coupled with water level corridor constraint was proposed to reduce the constraint complexity and standardize the optimization space. The method was applied to short-term optimal scheduling of cascade hydropower station in Hubei. The calculation results are compared with the results obtained by GA and particle swarm optimization (PSO). The case study shows that the total benefit by WCA in the typical day of abundant water period, average water period and dry period is respectively larger 5.65%, 3.15%, and 0.80% than that of GA and PSO; Convergence speed of the iteration is faster, and its solving ability is stronger, which provides a new idea for solving the optimal scheduling problem of cascade hydropower stations.
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