基于鸟群算法的梯级水库群长期优化调度研究
Research on Long-Term Optimal Operation of Cascade Reservoir Group Based on Bird Swarm Algorithm
DOI: 10.12677/JWRR.2023.121006, PDF,   
作者: 唐红兵, 李崇浩, 黄 巍：中国南方电网电力调度控制中心，广东 广州；王 欢, 程春田：连理工大学水电与水信息研究所，辽宁 大连
关键词: 梯级水电站；长期调度；全局搜索；鸟群算法；优化调度；Cascade Hydropower Station； Long-Term Scheduling； Global Search； Bird Swarm Algorithm； Optimal Operation
摘要: 针对大规模梯级水电站群调度复杂、优化困难、求解耗时长等问题，研究提出了一种基于鸟群算法(bird swarm algorithm, BSA)的梯级库群长期优化调度求解方法。该方法利用BSA平衡全局搜索和局部搜索的特点，充分发挥其收敛速度快，求解效率高的优势，易于获得满足复杂约束的最优结果。在西南某流域梯级水电站不同典型年调度问题上的应用结果，验证了该方法在梯级库群长期调度问题方面的求解精确性和高效性，是一种实用性较强的有效算法。
Abstract: In order to solve the problems of complex operation difficulty in optimization and time-consuming solution of large-scale cascade hydropower station group, a method for long-term optimal operation of cascade reservoir group based on bird swarm algorithm (BSA) was put forward. This method utilizes BSA’s characteristics of balancing global search and local search, and makes full use of its advantages of fast convergence, high efficiency of solution and easy to obtain optimal results satisfying complex constraints. The application results on different typical annual dispatching problems of cascade hydropower stations in a watershed in southwest China prove that the method is an effective and practical algorithm for solving long-term dispatching problems of cascade reservoirs.
文章引用：唐红兵, 李崇浩, 黄巍, 王欢, 程春田. 基于鸟群算法的梯级水库群长期优化调度研究[J]. 水资源研究, 2023, 12(1): 47-57. https://doi.org/10.12677/JWRR.2023.121006

参考文献

[1] 崔东文, 金波. 改进鸟群算法及其在梯级水库优化调度中的应用[J]. 三峡大学学报(自然科学版), 2016, 38(6): 7-14. CUI Dongwen, JIN Bo. Improved bird swarm Algorithm and its application in optimal operation of cascade reservoirs. Journal of China Three Gorges University (Natural Sciences), 2016, 38(6): 7-14. (in Chinese)
[2] 冯仲恺, 程春田, 牛文静. 均匀动态规划方法及其在水电系统优化调度中的应用[J]. 水利学报, 2015, 46(12): 1487-1496. FENG Zhongkai, CHENG Chuntian and NIU Wenjing. Uniform dynamic programming method and its application in optimal operation of hydropower system. Journal of Hydraulic Engineering, 2015, 46(12): 1487-1496. (in Chinese)
[3] 王建群, 贾洋洋, 肖庆元. 狼群算法在水电站水库优化调度中的应用[J]. 水利水电科技进展, 2015, 35(3):1-4. WANG Jianqun, JIA Yangyang and XIAO Qingyuna. Application of wolf swarm algorithm in optimal operation of hydropower station reservoir. Advances in Science and Technology of Water Resources, 2015, 35(3): 1-4. (in Chinese)
[4] 纪昌明, 李继伟, 张新明, 等. 基于免疫蛙跳算法的梯级水库群优化调度[J]. 系统工程理论实践, 2013, 33(8): 2125-2132. JI Changming, LI Jiwei, ZHANG Xinming, et al. Optimal operation of cascade reservoirs based on immune frog leaping algorithm. Systems Engineering-Theory & Practice, 2013, 33(8): 2125-2132. (in Chinese)
[5] 徐刚, 马光文, 梁武湖, 等. 蚁群算法在水库优化调度中的应用[J]. 水科学进展, 2005, 16(3): 397-400. XU Gang, MA Guangwen, LIANG Wuhu, et al. Application of ant colony algorithm in reservoir optimal operation. Advances in Water Science, 2005, 16(3): 397-400. (in Chinese)
[6] 王文川, 雷冠军, 邱林, 等. 群居蜘蛛优化算法在水电站优化调度中的应用及其效能分析[J]. 水力发电学报, 2015, 34(10): 80-87. WANG Wenchuan, LEI Guangjun, QIU Lin, et al. Application of social spider optimization algorithm in optimal operation of hydropower station and its efficiency analysis. Journal of Hydroelectric Engineering, 2015, 34(10): 80-87. (in Chinese)
[7] 向波, 纪昌明, 罗庆松. 免疫粒子群算法及其在水库优化调度中的应用[J]. 河海大学学报(自然科学版), 2008(2): 198-202. XIANG Bo, JI Changming and LUO Qingsong. Immune particle swarm optimization algorithm and its application in reservoir optimal operation. Journal of Hohai University (Natural Sciences), 2008(2): 198-202. (in Chinese)
[8] 钟平安, 张卫国, 张玉兰, 赵云发. 水电站发电优化调度的综合改进差分进化算法[J]. 水利学报, 2014, 45(10): 1147- 1155. ZHONG Pingan, ZHANG Weiguo, ZHANG Yulan and ZHAO Yunfa. Comprehensive improved differential evolution algorithm for optimal generation scheduling of hydropower stations. Journal of Hydraulic Engineering, 2014, 45(10): 1147-1155. (in Chinese)
[9] 明波, 黄强, 王义民, 等. 基于改进布谷鸟算法的梯级水库优化调度研究[J]. 水利学报, 2015, 46(3): 341-349. MING Bo, HUANG Qiang, WANG Yimin, et al. Research on optimal operation of cascade reservoirs based on improved cuckoo algorithm. Journal of Hydraulic Engineering, 2015, 46(3): 341-349. (in Chinese)
[10] 明波, 黄强, 王义民. 基于改进布谷鸟算法的梯级水库长期优化调度研究[J]. 水利水电快报, 2015, 36(4): 9-13. MING Bo, HUANG Qiang and WANG Yimin. Study on long-term optimal operation of cascade reservoirs based on improved cuckoo algorithm. Express Water Resources & Hydropower Information, 2015, 36(4): 9-13. (in Chinese)
[11] 董亚迪. 梯级水电站群中长期优化调度的多Agent进化算法研究[D]: [硕士学位论文]. 大连: 大连理工大学, 2019. DONG Yadi, Research on Multi Agent Evolutionary Algorithm for medium and long term optimal operation of cascade hydropower stations. Master’s Thesis, Dalian: Dalian University of Technology, 2019. (in Chinese)
[12] 王森, 程春田, 武新宇, 等. 自适应混沌整体退火遗传算法在水电站群优化调度中的应用[J]. 水力发电学报, 2014, 33(5): 63-71. WANG Sen, CHENG Chuntian, WU Xinyu, et al. Application of adaptive chaotic global annealing genetic algorithm in optimal operation of hydropower stations. Journal of Hydroelectric Engineering, 2014, 33(5): 63-71. (in Chinese)
[13] 李文武, 刘江鹏, 蒋志强, 等. 基于HSARSA(λ)算法的水库长期随机优化调度研究[J]. 水电能源科学, 2020, 38(12): 53-57. LI Wenwu, LIU Jiangpeng, JIANG Zhiqiang, et al. Based on HSARSA(λ) study on long-term stochastic optimal operation of reservoirs based on algorithm. Water Resources and Power, 2020, 38(12): 53-57. (in Chinese)
[14] MENG, X.-B., GAO, X. Z., LU, L. H., et al. A new bio-inspired optimisation algorithm: Bird swarm algorithm. Journal of Experimental & Theoretical Artificial Intelligence, 2015, 28(4): 1-15.
[15] 张伊, 张明华, 卢振鹏. 一种改进的梯级水电站多目标长期优化调度模型[J]. 通信电源技术, 2017, 34(4): 148-150. ZHANG Yi, ZHANG Minghua and LU Zhenpeng. An improved multi-objective long-term optimal operation model for cascaded hydropower stations. Telecom Power Technology, 2017, 34(4): 148-150. (in Chinese)
[16] 张宇航, 唐超, 姚李孝. 基于改进粒子群算法的梯级水电站长期优化调度研究[J]. 陕西电力, 2016, 44(6): 59-63. ZHANG Yuhang, TANG Chao and YAO Lixiao. Research on long-term optimal operation of cascade hydropower stations based on improved particle swarm optimization algorithm. Shaanxi Electric Power, 2016, 44(6): 59-63. (in Chinese)
[17] 余玉娇. 基于粒子群算法的水库调度函数的研究[D]: [硕士学位论文]. 武汉: 华中科技大学, 2014. YU Yujiao. Research on reservoir operation function based on particle swarm optimization algorithm. Master’s Thesis, Wuhan: Huazhong University of Science and Technology, 2014. (in Chinese)
[18] 汪明清, 牛文静, 廖胜利. 基于遗传-蚁群算法的库群长期优化调度[J]. 水电能源科学, 2013, 33(11): 49-52, 194. WANG Mingqing, NIU Wenjing and LIAO Shengli. Long-term optimal scheduling of reservoir group based on genetic ant colony algorithm. Water Resources and Power, 2013, 33(11): 49-52, 194. (in Chinese)
[19] 赵晓凤, 翁朝晖, 陈华. 基于改进肾脏算法的梯级水库长期发电优化调度研究[J]. 中国农村水利水电, 2021(3): 179-185. ZHAO Xiaofeng, WEN Chaohui and CHEN Hua. Research on long-term optimal operation of cascade reservoirs based on improved kidney algorithm. China Rural Water and Hydropower, 2021(3): 179-185. (in Chinese)