Optimal Clean Energy Resource Allocation in Balanced and Unbalanced Operation of Sustainable Electrical Energy Distribution Networks

被引:0
|
作者
Kumar, Abhinav [1 ]
Kumar, Sanjay [1 ]
Sinha, Umesh Kumar [1 ]
Bohre, Aashish Kumar [2 ]
Saha, Akshay Kumar [3 ]
机构
[1] Natl Inst Technol Jamshedpur, Dept Elect, Jamshedpur 831014, India
[2] Natl Inst Technol, Dept Elect Egg, Durgapur 713209, India
[3] Univ KwaZulu Natal, Discipline Elect Elect & Comp Engn, ZA-4041 Durban, South Africa
关键词
distributed clean energy resources; active power loss index; reactive power loss index; voltage index; balanced and unbalanced distribution systems; soft computing techniques; LOAD FLOW SOLUTION; LEARNING-BASED OPTIMIZATION; DISTRIBUTION-SYSTEMS; VOLTAGE REGULATION; OPTIMAL PLACEMENT; GENERATION; DG; RECONFIGURATION; ALGORITHM; COUNTRIES;
D O I
10.3390/en17184572
中图分类号
TE [石油、天然气工业]; TK [能源与动力工程];
学科分类号
0807 ; 0820 ;
摘要
Electric power is crucial for economic growth and the overall development of any country. The efficient planning of distribution system is necessary because all the consumers mainly rely on the distribution network to access the power. This paper focuses on addressing distribution system challenges and meeting consumers' fundamental needs, such as achieving an improved voltage profile and minimizing costs within an environmentally sustainable framework. This work addressed the gap in the existing research by analysing the performance of both balanced and unbalanced systems within the same framework, specifically using the IEEE 33-bus and IEEE 118-bus test systems. Unlike prior studies that focused solely on either balanced or unbalanced systems, this work redistributed balanced loads into three-phase unequal unbalanced loads to create a more challenging unbalanced distribution network. The primary objective is to compare the effects of balanced and unbalanced loads on system the performances and to identify strategies for mitigating unbalanced load issues in each phase. Six optimization methods (PSO, TLBO, JAYA, SCA, RAO, and HBO) were employed to minimize losses, voltage variations, and other multi-objective function factors. Additionally, the study compared the cost of energy loss (CEL), emission factors, costs associated with distributed clean energy resources (DCER), and active and reactive power losses. Phase angle distortions due to unbalanced loads were also analysed. The results showed that among the optimization techniques tested (PSO, TLBO, JAYA, SCA, RAO, and HBO), the HBO method proved to be the most effective for the optimal allocation of distributed clean energy resources, yielding the lowest PFMO values and favourable outcomes across the technical, economic, and environmental parameters.
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页数:52
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