市场环境下梯级电站厂间﹣厂内负荷分配模型
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摘要
市场环境下梯级负荷分配包括厂间负荷分配和厂内机组两个层次,厂间负荷分配目标为梯级效益最大化,厂内负荷分配目标为在安全前提下满足耗水量最小化。本文建立两个层次分配模型:厂间采用发电收益最大目标,使用逐步优化算法解决;厂内机组负荷分配采用耗水量最小目标,使用双动态规划解决,先采用动态规划解决逐时段内安全约束下最优分配,在此基础上时段间采用动态规划解决机组启停优化。两层次间以时段综合出力系数为协调变量的策略进行协调优化,将厂间负荷分配作为第一阶段,将厂内负荷分配作为第二阶段,两阶段迭代求解,得到最优分配结果。实例表明算法高效、快速完成了厂间﹣厂内负荷分配的统一调度,提高市场环境下梯级电站的竞争能力。
In the market environment, cascade load is allocated at both the inter-plant level and the inplant level of different generating units. Its targets are to maximize cascade benefit at the inter-plant level and minimize water consumption under security constraints at the in-plant level. This paper develops and integrates two hierarchical allocation models for the two levels. The inter-plant allocation is aimed at maximum power output profit, which is solved using a progressive optimal algorithm. The model of load allocation over the in-plant units is solved by a two-step dynamic programming to achieve the objective of minimum water consumption. It uses dynamic programming to solve the optimal allocation under security constraints in successive periods, and then in the second step to optimize the procedure to start up and shut down the units. Calculations at the two levels are coordinated and optimized through a comprehensive output coefficient as the coordination variable, and solved iteratively at the first and second stages, respectively, producing optimal results of the inter-plant and in-plant allocations. A case study shows that the algorithm is efficient and fast in achieving a unified dispatching between the load allocations, thus improving the competitiveness of cascade hydropower stations in the market.
In the market environment, cascade load is allocated at both the inter-plant level and the inplant level of different generating units. Its targets are to maximize cascade benefit at the inter-plant level and minimize water consumption under security constraints at the in-plant level. This paper develops and integrates two hierarchical allocation models for the two levels. The inter-plant allocation is aimed at maximum power output profit, which is solved using a progressive optimal algorithm. The model of load allocation over the in-plant units is solved by a two-step dynamic programming to achieve the objective of minimum water consumption. It uses dynamic programming to solve the optimal allocation under security constraints in successive periods, and then in the second step to optimize the procedure to start up and shut down the units. Calculations at the two levels are coordinated and optimized through a comprehensive output coefficient as the coordination variable, and solved iteratively at the first and second stages, respectively, producing optimal results of the inter-plant and in-plant allocations. A case study shows that the algorithm is efficient and fast in achieving a unified dispatching between the load allocations, thus improving the competitiveness of cascade hydropower stations in the market.
引文
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[9]陈森林,梁斌,卢慧.水电站负荷优化分配的分解聚合原理及应用[J].水利学报,2017,48(10):1185-1194.CHEN Senlin,LIANG Bin,LU Hui.Derivation of the aggregation-decomposition principle for optimal load distribution of hydropower station[J].Journal of Hydraulic Engineering,2017,48(10):1185-1194.(in Chinese)
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[14]赵雪花,黄强,吴建华.蚁群算法在水电站厂内经济运行中的应用[J].水力发电学报,2009,28(2):139-142.ZHAO Xuehua,HUANG Qiang,WU Jianhua.Application of ant colony algorithm for economic operation of hydropower station[J].Journal of Hydroelectric Engineering,2009,28(2):139-142.(in Chinese)
[15]程春田,唐子田,李刚,等.动态规划和粒子群算法在水电站厂内经济运行中的应用比较研究[J].水力发电学报,2008,27(6):27-31.CHENG Chuntian,TANG Zitian,LI Gang,et al.Comparison study between dynamic programming and particle swarm algorithm for the optimal operation of hydropower plant[J].Journal of Hydroelectric Engineering,2008,27(6):27-31.(in Chinese)
[16]李崇浩,纪昌明,李文武.微粒群算法在水电站厂内经济运行中的应用研究[J].水利水电技术,2006,37(1):88-91.LI Chonghao,JI Changming,LI Wenwu.Study on application of particle swarm optimization to in-plant economic operation of hydropower station[J].Water Resources and Hydropower Engineering,2006,37(1):88-91.(in Chinese)
[17]陶春华,马光文,涂扬举,等.实码退火遗传算法在厂内经济运行中的应用[J].四川大学学报(工程科学版),2005,37(6):41-44.TAO Chunhua,MA Guangwen,TU Yangju,et al.Economical operation of hydropower station based on real-coded annealing genetic algorithm[J].Journal of Sichuan University(Engineering Science Edition),2005,37(6):41-44.(in Chinese)
[18]徐刚.梯级电站厂间负荷分配算法研究[J].水力发电学报,2012,31(3):49-52.XU Gang.Study on load allocation algorithm for cascade hydropower stations[J].Journal of Hydroelectric Engineering,2012,31(3):49-52.(in Chinese)
[19]韩桂芳,陈启华,张仁贡.动态规划法在水电站厂内经济运行中的应用[J].水电能源科学,2005,23(1):48-51.HAN Guifang,CHEN Qihua,ZHANG Rengong.Application of dynamic programming in innerplant economical operation of hydropower station[J].Water Resources and Power,2005,23(1):48-51.(in Chinese)
[20]王德意,南海鹏,刘栋,等.快速动态规划法在运行机组间有功负荷分配中的应用[J].水利水电技术,2001,32(6):28-30.WANG Deyi,NAN Haipeng,LIU Dong,et al.Application of fast dynamic programming method in active load distribution between running units[J].Water Resources and Hydropower Engineering,2001,32(6):28-30.(in Chinese)
[21]周冉,杨侃,郝永怀,等.考虑空蚀振动区的水电站厂内经济运行方法[J].中国农村水利水电,2011(6):153-155.ZHOU Ran,YANG Kan,HAO Yonghuai,et al.Research on the economic operation method for hydropower stations taking account of cavitation and vibration areas[J].China Rural Water and Hydropower,2011(6):153-155.(in Chinese)
[22]王黎,马光文.基于遗传算法的水电站厂内经济运行新算法[J].中国电机工程学报,1998,18(1):64-66.WANG Li,MA Guangwen.Genetic algorithm in hydro station economic dispatch[J].Proceedings of the CSEE,1998,18(1):64-66.(in Chinese)
[23]孙昌佑,马震岳.基于遗传算法的水电站厂内运行研究[J].水电能源科学,2004,22(1):48-50.SUN Changyou,MA Zhenyue.Advanced genetic algorithm based innerplant economical operation of hydropower station[J].Water Resources and Power,2004,22(1):48-50.(in Chinese)
[24]纪昌明,谢唯,朱新良,等.基于病毒进化粒子群算法的梯级电站厂间负荷优化分配[J].水力发电学报,2013,31(2):38-43.JI Changming,XIE Wei,ZHU Xinliang,et al.Optimized load allocation of cascaded hydropower stations based on virus particle swarm optimization algorithm[J].Journal of Hydroelectric Engineering,2013,31(2):38-43.(in Chinese)
[25]SUMIT B,DEBLINA M,CHANDAN K C.Teaching learning based optimization for economic load dispatch problem considering value point loading effect[J].International Journal of Electrical Power&Energy Systems,2015,73(1):456-464.
[26]NASER G,EBRAHIM B.Exchange market algorithm for economic load dispatch[J].International Journal of Electrical Power&Energy Systems,2016,75(1):19-27.
[27]MOUMITA P,PROVAS K R,TANDRA P.Grey wolf optimization applied to economic load dispatch problems[J].International Journal of Electrical Power&Energy Systems,2016,83(1):325-334.
[2]KIRCHMAYER L K,STAGG G W.Analysis of total and incremental losses in transmission systems[J].Transactions of the American Institute of Electrical Engineers,1952,71(III):513-520.
[3]BELLMAN R.Dynamic programming[M].Princeton:Princeton University Press,1957.
[4]FUKAO T.An application of dynamic programming to economic operation problem of a power system[J].Electric Technical Journal of Japan,1959,5(2):64-68.
[5]BERNHOLTZ B,GRAHAM L J.Hydrothermal economic scheduling[J].IEEE Transactions on Power Apparatus and System,1960,79(2):921-932.
[6]权先璋.动态规划原理在水电站厂内经济运行中的运用[J].水电能源科学,1983,1(1):95-104.QUAN Xianzhang.Application of the dynamic programming principle to economic operation in a hydroelectric plant[J].Water Resources and Power,1983,1(1):95-104.(in Chinese)
[7]王定一,伍永刚.水电站自动发电控制的实施[J].华中理工大学学报,1993,6(21):52-56.WANG Dingyi,WU Yonggang.Implementation of automatic generation control for hydropower plants[J].Journal of Huazhong University of Science and Technology,1993,6(21):52-56.(in Chinese)
[8]郭富强,郭生练,刘攀,等.隔河岩水电站实时运行负荷分配控制研究[J].水力发电,2007,33(7):82-86.GUO Fuqiang,GUO Shenglian,LIU Pan,et al.Real-time load distribution control for the operation of Geheyan Hydropower Station[J].Water Power,2007,33(7):82-86.(in Chinese)
[9]陈森林,梁斌,卢慧.水电站负荷优化分配的分解聚合原理及应用[J].水利学报,2017,48(10):1185-1194.CHEN Senlin,LIANG Bin,LU Hui.Derivation of the aggregation-decomposition principle for optimal load distribution of hydropower station[J].Journal of Hydraulic Engineering,2017,48(10):1185-1194.(in Chinese)
[10]NAJAFI S,POURJAMAL Y.A new heuristic algorithm for unit commitment problem[J].Energy Procedia,2012,14(1):2005-2011.
[11]JAYABARATHI R,JISMA M,SUYAMPULINGAM A.Unit commitment using embedded systems[J].Procedia Technology,2015,21(1):96-102.
[12]ERLON C F,MURILO R S.Hydro unit commitment and loading problem for day-ahead operation planning problem[J].International Journal of Electrical Power&Energy Systems,2013,44(1):7-16.
[13]张智晟,龚文杰,段晓燕,等.类电磁机制算法在水电站厂内经济运行中的应用研究[J].电工电能新技术,2011,30(4):17-20.ZHANG Zhisheng,GONG Wenjie,DUAN Xiaoyan,et al.Application of electromagnetism-like mechanism algorithm for economic operation of hydropower station[J].Advanced Technology of Electrical Engineering and Energy,2011,30(4):17-20.(in Chinese)
[14]赵雪花,黄强,吴建华.蚁群算法在水电站厂内经济运行中的应用[J].水力发电学报,2009,28(2):139-142.ZHAO Xuehua,HUANG Qiang,WU Jianhua.Application of ant colony algorithm for economic operation of hydropower station[J].Journal of Hydroelectric Engineering,2009,28(2):139-142.(in Chinese)
[15]程春田,唐子田,李刚,等.动态规划和粒子群算法在水电站厂内经济运行中的应用比较研究[J].水力发电学报,2008,27(6):27-31.CHENG Chuntian,TANG Zitian,LI Gang,et al.Comparison study between dynamic programming and particle swarm algorithm for the optimal operation of hydropower plant[J].Journal of Hydroelectric Engineering,2008,27(6):27-31.(in Chinese)
[16]李崇浩,纪昌明,李文武.微粒群算法在水电站厂内经济运行中的应用研究[J].水利水电技术,2006,37(1):88-91.LI Chonghao,JI Changming,LI Wenwu.Study on application of particle swarm optimization to in-plant economic operation of hydropower station[J].Water Resources and Hydropower Engineering,2006,37(1):88-91.(in Chinese)
[17]陶春华,马光文,涂扬举,等.实码退火遗传算法在厂内经济运行中的应用[J].四川大学学报(工程科学版),2005,37(6):41-44.TAO Chunhua,MA Guangwen,TU Yangju,et al.Economical operation of hydropower station based on real-coded annealing genetic algorithm[J].Journal of Sichuan University(Engineering Science Edition),2005,37(6):41-44.(in Chinese)
[18]徐刚.梯级电站厂间负荷分配算法研究[J].水力发电学报,2012,31(3):49-52.XU Gang.Study on load allocation algorithm for cascade hydropower stations[J].Journal of Hydroelectric Engineering,2012,31(3):49-52.(in Chinese)
[19]韩桂芳,陈启华,张仁贡.动态规划法在水电站厂内经济运行中的应用[J].水电能源科学,2005,23(1):48-51.HAN Guifang,CHEN Qihua,ZHANG Rengong.Application of dynamic programming in innerplant economical operation of hydropower station[J].Water Resources and Power,2005,23(1):48-51.(in Chinese)
[20]王德意,南海鹏,刘栋,等.快速动态规划法在运行机组间有功负荷分配中的应用[J].水利水电技术,2001,32(6):28-30.WANG Deyi,NAN Haipeng,LIU Dong,et al.Application of fast dynamic programming method in active load distribution between running units[J].Water Resources and Hydropower Engineering,2001,32(6):28-30.(in Chinese)
[21]周冉,杨侃,郝永怀,等.考虑空蚀振动区的水电站厂内经济运行方法[J].中国农村水利水电,2011(6):153-155.ZHOU Ran,YANG Kan,HAO Yonghuai,et al.Research on the economic operation method for hydropower stations taking account of cavitation and vibration areas[J].China Rural Water and Hydropower,2011(6):153-155.(in Chinese)
[22]王黎,马光文.基于遗传算法的水电站厂内经济运行新算法[J].中国电机工程学报,1998,18(1):64-66.WANG Li,MA Guangwen.Genetic algorithm in hydro station economic dispatch[J].Proceedings of the CSEE,1998,18(1):64-66.(in Chinese)
[23]孙昌佑,马震岳.基于遗传算法的水电站厂内运行研究[J].水电能源科学,2004,22(1):48-50.SUN Changyou,MA Zhenyue.Advanced genetic algorithm based innerplant economical operation of hydropower station[J].Water Resources and Power,2004,22(1):48-50.(in Chinese)
[24]纪昌明,谢唯,朱新良,等.基于病毒进化粒子群算法的梯级电站厂间负荷优化分配[J].水力发电学报,2013,31(2):38-43.JI Changming,XIE Wei,ZHU Xinliang,et al.Optimized load allocation of cascaded hydropower stations based on virus particle swarm optimization algorithm[J].Journal of Hydroelectric Engineering,2013,31(2):38-43.(in Chinese)
[25]SUMIT B,DEBLINA M,CHANDAN K C.Teaching learning based optimization for economic load dispatch problem considering value point loading effect[J].International Journal of Electrical Power&Energy Systems,2015,73(1):456-464.
[26]NASER G,EBRAHIM B.Exchange market algorithm for economic load dispatch[J].International Journal of Electrical Power&Energy Systems,2016,75(1):19-27.
[27]MOUMITA P,PROVAS K R,TANDRA P.Grey wolf optimization applied to economic load dispatch problems[J].International Journal of Electrical Power&Energy Systems,2016,83(1):325-334.