改进多目标布谷鸟算法的梯级水电站优化调度

发布时间：2018-06-15 12:48

本文选题：梯级水电站 + 优化调度　；参考：《水力发电学报》2017年03期

【摘要】：为有效求解梯级水电站多目标联合优化问题,充分发挥水电的发电效益和容量效益,提出一种新型的改进多目标布谷鸟算法(IMOCS)。针对传统布谷鸟算法存在收敛速度慢的问题,将动态发现概率和步长融入到算法中,并结合非支配排序遗传算法(NSGA-II)的非支配排序思想以及拥挤距离维护外部档案集策略,提出IMOCS;通过测试函数验证了所提算法的有效性。将IMOCS应用到乌江梯级水电站多目标优化调度中,得到了分布均匀的非劣调度方案集。最后通过模糊决策模型,主客观确定目标权重法,从非劣解集中选择一个折中方案,得到各水电站发电用水过程。结果表明,调度方案合理、可靠,且均能满足各项约束条件。梯级水电站优化调度采用IMOCS具有较大的实用意义。
[Abstract]:In order to effectively solve the multi-objective joint optimization problem of cascade hydropower stations and give full play to the benefit of hydropower generation and capacity, a new improved multi-objective Cuckoo algorithm (IMOCSS) is proposed. In order to solve the problem of slow convergence in traditional Cuckoo algorithm, dynamic discovery probability and step size are incorporated into the algorithm, combined with the idea of non-dominated sorting of genetic algorithm NSGA-IIand the strategy of maintaining the external file set in crowded distance. IMOCS is proposed, and the validity of the proposed algorithm is verified by testing function. The IMOCS is applied to the multi-objective optimal operation of Wujiang cascade hydropower station, and the set of non-inferior dispatching schemes with uniform distribution is obtained. Finally, through fuzzy decision model, objective and subjective determination of objective weight method, a compromise scheme is selected from the non-inferior solution set to obtain the process of generating water for each hydropower station. The results show that the scheduling scheme is reasonable, reliable and can meet all the constraints. It is of great practical significance to adopt IMOCS for optimal dispatching of cascade hydropower stations.
【作者单位】：西安理工大学水利水电学院;
【基金】：国家自然科学基金(91325201) 水利部公益性行业科研专项经费项目(201501058) 陕西省教育厅重点实验室项目(13JS069)
【分类号】：TV737;TP18

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