Voltage profile improvement and losses minimization for Hayin Rigasa radial network Kaduna using distributed generation

I. A. Araga, A. Airoboman, Simon A. Auta
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Abstract

This research work has presented the application of distributed generation (DG) units in a simultaneous placement approach on IEEE 33 radial test systems for validation of the technique with further implementation on 56-Bus Hayin Rigasa feeder. The genetic algorithm (GA) is employed in obtaining the optimal sizes and load loss sensitivity index for locations of the DGs for entire active and reactive power loss reduction. The voltage profile index is computed for each bus of the networks to ascertain the weakest voltage bus of the network before and after DG and circuit breaker allocation. The simultaneous placement approach of the DGs is tested with the IEEE 33-bus test networks and Hayin Rigasa feeder network and the results obtained are confirmed by comparing with the results gotten from separate DGs allocation on the networks. For IEEE 33-bus system, the simultaneous allocation of DGs and of optimal sizes 750 kW, 800 kW and at locations of buses 2 and 6 respectively, lead to a 66.49 % and 68.64 % drop in active and reactive power loss and 3.02 % improvement in voltage profile. For the 56-bus Hayin Rigasa network in Kaduna distribution network, the simultaneous placement of DGs of sizes 1,470 kW and 1490 kW at locations of bus 16 and 23 respectively, lead to a 79.54 % and 73.98 % drop in active and reactive power loss and 15.94 % improvement in voltage profile. From results comparison, it is evident that the allocation of DGs using the combination GA and load loss sensitivity index, gives an improved performance in relations to power loss reduction and voltage profile improvements of networks when compared to without DGs.
利用分布式发电改善卡杜纳海因Rigasa径向电网的电压分布并使损耗最小化
本研究工作介绍了分布式发电(DG)单元在IEEE 33径向测试系统上的同时放置方法的应用,以验证该技术,并进一步在56总线Hayin Rigasa馈线上实现。采用遗传算法求出dg位置的最优尺寸和负荷损耗灵敏度指标,从而达到降低有功和无功损耗的目的。通过计算各母线的电压分布指数,确定DG前后电网的最弱电压母线和断路器配置。在IEEE 33总线测试网和海印Rigasa馈线网络上对dg的同时布放方法进行了测试,并与单独dg布放的结果进行了比较。对于IEEE 33母线系统,分别在母线2和母线6的位置同时配置750 kW和800 kW的最优尺寸dg,可使有功和无功损耗分别下降66.49%和68.64%,电压分布改善3.02%。对于卡杜纳配电网56母线Hayin Rigasa网络,分别在16母线和23母线位置同时放置1470 kW和1490 kW的dg,可使有功和无功功率损失分别下降79.54%和73.98%,电压分布改善15.94%。从结果比较中可以明显看出,与不使用dg相比,使用遗传算法和负载损耗灵敏度指数相结合的dg分配在降低功率损耗和改善网络电压分布方面具有更好的性能。
本文章由计算机程序翻译,如有差异,请以英文原文为准。
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