摘要
水火电力系统最优潮流问题(HTOPF)是一个大规模多时段的动态非线性最优化问题,其计算量远远大于经典的最优潮流问题(OPF)。随着电力系统规模的日益扩大,求解模型的不断精确与完善,运行周期中的计算时间间隔越来越短,时段数越来越多,相应的计算量急剧增加。特别是当模型中考虑了梯级水电厂之后,由于实际的运行特性,各个水电厂之间、各个时段之间因水量关系相互耦合,必须将整个运行周期进行统一考虑,计算量将十分庞大,采用传统的单机集中式计算,计算时间无法满足要求。因此,研究高效的水火电力系统最优潮流的分布式算法已是势在必行。
本文在现代内点算法中,依据分块法,将大规模的简约修正方程解耦,从而得到了一种各个时段分布计算的HTOPF问题的分布式计算方法。并采用性价比高的PC机群(PC-cluster)和数值计算能力强大的Matlab分布式计算环境(MDCE)搭建了分布式计算平台,成功地求解了大规模系统的HTOPF问题。通过对5个测试系统分别在5个不同的运行周期中运行的仿真计算结果分析中可以得出,本文的算法继承了内点法良好的收敛性,模型真实的反映了实际电力系统中各种发电厂的出力情况,以及梯级水电厂运行情况,节省了大量计算时间,获得了较高的加速比和效率。该方法能满足水火电力系统最优潮流问题的实际应用,具有广泛的应用前景。
Hydro-thermal optimal power flow (HTOPF) is one of large scale dynamic nonlinear optimize problem, the amount of computation is far greater than the classical optimal power flow (OPF).With the system scale is enlarge and model is demand more accurate continuously, the problem is hard to be solved by traditional centralize computing, the calculation periods of operating cycle is shorter and shorter, corresponding dramatic increase in the amount of computation, Especially when considered in the model of cascade hydropower plants, the actual operation characteristics, the entire operation must be considered a unified cycle, will be very large amount of computation, the problem is hard to be solved by traditional centralize computing. The research on high-powered parallel HTOPF algorithm and its distributed implementation become a question for discussion.
This paper used accurate decompose method in Primal-Dual Interior Point Method (PDIPM) under perturbed Karush-Kuhn-Tucker (KKT) conditions, decoupled The large-scale reduced correction equation, then get a distributed computing methods for HTOPF by decoupled with periods. According to the distributed algorithm, the paper proposes distributed computing program based on a PC-cluster with Matlab distributed computing engine (MDCE). PC-cluster has a high performance and price ratio. And MDCE is powerful in numerical computing. By simulation in Matlab distributing environment with PC-cluster, large-scale HTOPF problem is solved successfully. Through the five test system in five different operating cycle to run the simulation results, the results verify that the proposed distributed algorithm possesses a good convergence property in a distributed environment, the real model reflects the actual power system in various The power plant output, and the cascade hydropower plant operation, many CPU times is saved, and hence, the method is quite promising for large-scale applications. Some problems are handled effectively, such as communication flux, load balance, and the good accelerate rate and efficiency is obtained.
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