基于粒子群优化的太阳能经济调度

W. A. Augusteen, S. Geetha, R. Rengaraj
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引用次数: 17

摘要

本文提出了一种利用粒子群优化技术解决太阳能系统经济调度问题的创新方法。在PSO技术中,太阳辐射是按小时计算的,而我们考虑的是一天的辐射。太阳辐射取决于标准环境条件,光伏发电机组输出的总功率为常数。在这个系统中,电池没有连接,因此电池的总充放电被设置为零。粒子运动由惯性运动、认知运动和社会运动三种活动指导。该方法由斜坡限制等发电机的非线性唯一性、具有最大和最小运行限制的功率平衡约束以及可感知电力系统运行的禁止运行区域等组成。为实现这一目标,粒子群算法是解决电力系统优化问题的一种有效方法,可用于解决电力系统中大多数困难的优化问题。该方法由10个发电机组组成,并考虑了光伏太阳能电池板的太阳辐射。数值结果表明,与以往的算法相比,该方法具有较高的解质量和合理的计算时间(速度)。
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Economic dispatch incorporation solar energy using particle swarm optimization
In this proposed paper presents an innovative method to solve the economic dispatch problem with the solar energy system using particle swarm optimization technique (PSO). The solar radiations are considered on an hourly basis while we are considering for a day in PSO technique. The solar radiation depends on the standard environmental conditions and the total power output from the PV generator is taken as constant. In this system the battery is not connected and hence the total charge and discharge from the battery is set as zero. The particle movement in the PSO technique is directed by three activities, they are inertial, cognitive, and societal. The proposed method consists of the nonlinear uniqueness of a generator for instance like ramp limit, power balance constraints with their maximum and minimum operating limits and prohibited operating zones for the perceptible power system operation. For this proposed objective the PSO algorithm is an effective method to solve the ED problem and it is the implemented to solve most of the difficult optimization problems in the power system. In this proposed method consists of ten generating units and the solar radiation from the PV solar panel have been considered. The numerical result shows that the proposed method has a higher quality solution with reasonable computational time (speed) when compared with other past algorithm.
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