Determination of optimal site and capacity of DG systems in distribution network based on genetic algorithm

Abdulwahab Alhamali, M. Farrag, G. Bevan, D. Hepburn
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引用次数: 16

Abstract

Concerns over global climate changes coupled with growing demand for energy are leading to increased penetration of distributed generation from intermittent sources into low voltage networks. In such cases distribution network (DN) operation will be affected. Consequently, there have been serious concerns over reliability and satisfactory operation of these power systems which contain distributed generation (DG) equipment. Distributed power generated from renewable sources is variable particularly in the case of wind generation or solar energy. The variability affects the stability of the system between supply and consumers. In DN, the losses and voltage drop across the network are significant matters and the DG location has a critical impact on the network operation. So, there is a clear need to optimise the DG size and location in the DN; for example, optimising the number of DG's and co-ordinating their operation can improve voltage drop and network losses. In this paper, an optimisation technique based on the genetic algorithm (GA) in conjunction with the power flow (PF) method is used to improve the DN performance and to identify the best location and size of the DG's. The main goal of the optimisation function is to reduce both the network losses and regulate the voltage level under different loading conditions.
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基于遗传算法的配电网DG系统最优位置和容量确定
对全球气候变化的担忧,加上对能源需求的不断增长,导致间歇性分布式发电越来越多地渗透到低压电网中。在这种情况下,将影响配电网络(DN)的运行。因此,这些包含分布式发电(DG)设备的电力系统的可靠性和令人满意的运行受到了严重关注。可再生能源产生的分布式电力是可变的,特别是在风力发电或太阳能的情况下。这种可变性影响供给者和消费者之间系统的稳定性。在分布式电网中,整个网络的损耗和压降是一个重要的问题,DG的位置对网络的运行有着至关重要的影响。因此,显然需要优化DG在DN中的大小和位置;例如,优化DG的数量并协调它们的运行可以改善电压降和网络损耗。本文提出了一种基于遗传算法(GA)的优化技术,结合功率流(PF)方法来提高分布式电网的性能,并确定分布式电网的最佳位置和大小。优化函数的主要目标是在不同负载条件下降低电网损耗和调节电压水平。
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