Simultaneous network reconfiguration and DG allocation in radial distribution networks using arithmetic optimization algorithm

被引:5
|
作者
Dey, Indrajit [1 ,3 ]
Roy, Provas Kumar [2 ]
机构
[1] Camellia Inst Technol & Management, Dept Elect Engn, Bainchi, India
[2] Kalyani Govt Engn Coll, Dept Elect Engn, Kalyani, India
[3] Camellia Inst Technol & Management, Bainchi 712134, W Bengal, India
关键词
arithmetic optimization algorithm (AOA); decremented power loss; optimum disposition and capacity of DG; reconfiguration of distribution system; voltage deviation; voltage stability index; POWER LOSS MINIMIZATION; DISTRIBUTION FEEDER RECONFIGURATION; PARTICLE SWARM OPTIMIZATION; DISTRIBUTION-SYSTEM; LOSS REDUCTION; CUCKOO SEARCH; STABILITY; PLACEMENT;
D O I
10.1002/jnm.3105
中图分类号
TM [电工技术]; TN [电子技术、通信技术];
学科分类号
0808 ; 0809 ;
摘要
This article introduces a newly suggested meta-heuristic arithmetic optimization algorithm (AOA) to reorganize the distribution network with the simultaneous distribution of distributed generators (DGs). The algorithm is designed to be flexible with a new approach that employs the scattering behavior of arithmetic operators in mathematics to discover the solution space more proficiently throughout the path of iterations. The usefulness of the AOA is demonstrated on 33-bus, and 69-bus radial distribution networks (RDNs) with network reconfiguration (NR) in the presence of DGs. The main objective of NR and effective DG arrangement in RDNs is to truncate the true power loss, reduce the voltage fluctuation, and voltage stability index enlargement. In order to increase the efficacy of the RDN, a multi-objective function is created in view of active power loss, voltage deviation, and voltage stability index of the system with appropriate strategy without destroying the system restrictions. To illustrate the effectiveness of the RDN, four separate cases of NR and DG employment have been carried out. Four cases namely, base case (case-1), reconfiguration (case-2), simultaneous reconfiguration and DG installation with a unity power factor (case-3), and simultaneous reconfiguration and DG installation with 0.95 lagging power factor (case-4) are explored. The projected technique gives better results than other renowned methods, namely, fireworks algorithm (FWA), harmony search algorithm (HSA), refined genetic algorithm (RGA), and improved sine-cosine algorithm (ISCA) strategy in view of 33, 69-bus RDN at three dissimilar load conditions and its supremacy is confirmed.
引用
收藏
页数:41
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