Quasi-oppositional Forensic-Based Investigation for Optimal DG Selection for Power Loss Minimization

被引:3
|
作者
Malika, Binaya Kumar [1 ,2 ]
Pattanaik, Vivekananda [2 ,3 ]
Sahu, Binod Kumar [2 ]
Rout, Pravat Kumar [4 ]
机构
[1] Einstein Acad Technol & Management, Dept Elect Engg, Bhubaneswar, India
[2] Siksha O Anusandhan Univ, Dept Elect Engn, Bhubaneswar, Odisha, India
[3] Synergy Inst Technol, Dept Elect Engn, Bhubaneswar, India
[4] Siksha O Anusandhan Univ, Dept Elect & Elect Engn, Bhubaneswar, Odisha, India
关键词
Distribution generation (DG); Forensic-based investigation algorithm (FBI); DG location; DG size; Power loss minimization; Oppositional-based learning (OBL); RADIAL-DISTRIBUTION NETWORK; LEARNING BASED OPTIMIZATION; ORGANISMS SEARCH ALGORITHM; DISTRIBUTED GENERATION; OPTIMAL ALLOCATION; DISTRIBUTION-SYSTEM; OPTIMAL PLACEMENT; ENERGY; INTEGRATION; RESOURCES;
D O I
10.1007/s41660-022-00277-9
中图分类号
X [环境科学、安全科学];
学科分类号
08 ; 0830 ;
摘要
With the emergence of smart-grid and micro-grid concept insurgence into the modern power distribution system, the present research has been forced to focus on the impact of distributed generation (DG) on the overall system performance at the planning stage. The optimal bus location and selection of the proper size of DGs in the radial distribution systems (RDS) is a major issue and needs better optimization techniques during decision making. The major intent of the study is to minimize the active power loss and that is accomplished by taking appropriate bus location, size of the DGs, and power factor as the system variables. This paper presents a quasi-oppositional forensic-based investigation (QOFBI) inspired meta-optimization approach for providing optimal results of DG allocation and sizing along with the power factor considering all the system operating constraints. To validate the superior performance of the proposed approach, IEEE 33-bus, IEEE 69-bus, and IEEE 85-bus test systems are considered for simulation. Various performance indices related to power, voltage, and stability are computed under various levels and types of DG penetration, and comparative results with recently proposed approaches are presented and analyzed. The results reveal the robustness, effectiveness, and better performance with the less computational complexity of the proposed approach.
引用
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页码:73 / 106
页数:34
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