基于ELQG算法的水库群优化调度研究
|
摘要
针对目前复杂水库群优化调度算法存在早熟收敛和运行时间长等问题,本文深入研究基于ELQG算法的水库群优化调度的原理、方法与步骤,利用ELQG算法求解新安江-富春江水库优化调度模型,并将不同典型年优化下调度结果与DP算法进行对比。结果表明:ELQG算法中梯级水库联合年发电量减少0.1亿~0.3亿k W·h,平均水位降低1.0~1.3 m,但计算速度平均提高20倍。ELQG算法具有较强的实用性和可操作性,为多目标、高维水库群的优化调度提供了一种新的途径。
In view of the problems such as premature convergence and long running time of complex reservoir optimal scheduling algorithm,this paper studied the principle,method and procedure optimal operation of reservoir group based on extended linear quadratic gaussian algorithms( ELQG). It applied ELQG to solve the optimal operation model of Xin'an River reservoir and Fuchun River one and compared the dispatcher result under the optimum of different typical years with that of DP algorithm. The result showed that annual generating capacity of cascade reservoir joint calculated by ELQG algorithm reduced10 to 30 million k W oh and the average water level decreased by 1. 0 to 1. 3m. The calculation velocity increase by nearly 20 times. ELQG algorithm has strong practicability and maneuverability,and can provide a new way for the optimal operation of multi-target and high-dimensional reservoir group.
In view of the problems such as premature convergence and long running time of complex reservoir optimal scheduling algorithm,this paper studied the principle,method and procedure optimal operation of reservoir group based on extended linear quadratic gaussian algorithms( ELQG). It applied ELQG to solve the optimal operation model of Xin'an River reservoir and Fuchun River one and compared the dispatcher result under the optimum of different typical years with that of DP algorithm. The result showed that annual generating capacity of cascade reservoir joint calculated by ELQG algorithm reduced10 to 30 million k W oh and the average water level decreased by 1. 0 to 1. 3m. The calculation velocity increase by nearly 20 times. ELQG algorithm has strong practicability and maneuverability,and can provide a new way for the optimal operation of multi-target and high-dimensional reservoir group.
引文
[1]朱记伟,张洪波,辛琛,等.水库调度PSO优化模型及求解方法[J].系统工程,2010,28(1):105-112.
[2]Little J D C.The use of storage water in a hydroelectric system[J].Journal of the operations research society of America,1955,3(2):187-197.
[3]刘双全,张海龙.水电优化调度算法研究综述[J].云南电力技术,2011,39(4):5-9.
[4]郭生练,陈炯宏,刘攀,等.水库群联合优化调度研究进展与展望[J].水科学进展,2010,21(4):496-503.
[5]张忠波,吴学春,张双虎,等.并行动态规划和改进遗传算法在水库调度中的应用[J].水力发电学报,2014,33(4):21-27.
[6]王丽萍,孙平,蒋志强,等.基于正态云变异蛙跳算法的梯级水电站短期优化调度[J].水力发电学报,2014,33(6):61-67+104.
[7]郑慧涛,梅亚东,胡挺,等.改进差分进化算法在梯级水库优化调度中的应用[J].武汉大学学报(工学版),2013,46(1):57-61.
[8]方国华,黄显峰.多目标决策理论,方法及其应用[M].北京:科学出版社,2011.
[9]Guaracy F H.D,da Silva D L F,Ferreira L H C.On the properties of augmented open-loop stable plants using LQG/LTR control[J].IEEE Transactions on Automatic Control,2015,60(8):2172-2176.
[10]Florescu A,Bratcu A I,Munteanu I,et al.LQG Optimal control applied to on board energy management system of all electric vehicles[J].IEEE Transactions on Control Systems Technology,2015,23(4):1427-1439.
[11]Alizadeh Iman,Sajjadi-Kia Solmaz,Villac Benjamin.Low-thrust adaptive guidance scheme accounting for engine performance degradation[J].Advances in the Astronautical Sciences,2012,142(2):1991-2002.
[12]Hata H,Sekine J.Explicit solution to a certain nonELQG risk-sensitive stochastic control problem[J].Applied Mathematics and Optimization,2010,62(3):341-380.
[13]王杰文.约束多目标优化问题中约束处理方法综述[J].现代计算机,2012(36):12-14+19.
[2]Little J D C.The use of storage water in a hydroelectric system[J].Journal of the operations research society of America,1955,3(2):187-197.
[3]刘双全,张海龙.水电优化调度算法研究综述[J].云南电力技术,2011,39(4):5-9.
[4]郭生练,陈炯宏,刘攀,等.水库群联合优化调度研究进展与展望[J].水科学进展,2010,21(4):496-503.
[5]张忠波,吴学春,张双虎,等.并行动态规划和改进遗传算法在水库调度中的应用[J].水力发电学报,2014,33(4):21-27.
[6]王丽萍,孙平,蒋志强,等.基于正态云变异蛙跳算法的梯级水电站短期优化调度[J].水力发电学报,2014,33(6):61-67+104.
[7]郑慧涛,梅亚东,胡挺,等.改进差分进化算法在梯级水库优化调度中的应用[J].武汉大学学报(工学版),2013,46(1):57-61.
[8]方国华,黄显峰.多目标决策理论,方法及其应用[M].北京:科学出版社,2011.
[9]Guaracy F H.D,da Silva D L F,Ferreira L H C.On the properties of augmented open-loop stable plants using LQG/LTR control[J].IEEE Transactions on Automatic Control,2015,60(8):2172-2176.
[10]Florescu A,Bratcu A I,Munteanu I,et al.LQG Optimal control applied to on board energy management system of all electric vehicles[J].IEEE Transactions on Control Systems Technology,2015,23(4):1427-1439.
[11]Alizadeh Iman,Sajjadi-Kia Solmaz,Villac Benjamin.Low-thrust adaptive guidance scheme accounting for engine performance degradation[J].Advances in the Astronautical Sciences,2012,142(2):1991-2002.
[12]Hata H,Sekine J.Explicit solution to a certain nonELQG risk-sensitive stochastic control problem[J].Applied Mathematics and Optimization,2010,62(3):341-380.
[13]王杰文.约束多目标优化问题中约束处理方法综述[J].现代计算机,2012(36):12-14+19.