A multiyear DG-incorporated framework for expansion planning of distribution networks using binary chaotic shark smell optimization algorithm

Energy ◽  
2016 ◽  
Vol 102 ◽  
pp. 199-215 ◽  
Author(s):  
Masoud Ahmadigorji ◽  
Nima Amjady
Keyword(s):  
Optimization Algorithm ◽  
Distribution Networks ◽  
Expansion Planning

scholarly journals A Two-layer Multistage Expansion Planning Method for Adaptability Enhancement of Distribution Networks

2021 ◽  
Vol 645 ◽  
pp. 012080
Author(s):  
Liang Feng ◽  
Yichao Dong ◽  
Shouxiang Wang ◽  
Qingzhi Jian ◽  
Long Zhao ◽  
...  
Keyword(s):  
Distribution Networks ◽  
Planning Method ◽  
Expansion Planning

scholarly journals Optimal placement of distributed generation using colliding bodies optimization

2018 ◽  
Vol 7 (3.3) ◽  
pp. 168
Author(s):  
Gera Kalidas Babu ◽  
P V. Ramana rao
Keyword(s):  
Distributed Generation ◽  
Optimization Algorithm ◽  
Distribution Networks ◽  
Optimal Placement ◽  
Solar Photovoltaic ◽  
Load Power ◽  
Colliding Bodies Optimization ◽  
Power Loss Reduction ◽  
Radial Distribution Networks ◽  
Distribution Generation

The present paper foremost objective is to resolve best practicable location of solar photovoltaic distribution generation (DG) of several cases using different distribution load power factors and to analyze power loss reduction. This objective achieved by a recent developed method, the so called colliding bodies’ optimization algorithm, to perceive optimum location. Performances of colliding bodies’ optimization algorithm have been evaluated and compared with other search algorithms. The execution to test viability and efficiency, the proposed collid-ing bodies’ optimization is simulated on standard IEEE 38 bus radial distribution networks. The acquired outcome from colliding bodies Optimization algorithm exhibits the possible location of distributed generation through different pre assumed load power factors compared to the other stochastic search bat and genetic algorithm.  

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