|
Nitesh Kumar Baroliya
Jitendra Kumar Sharma
Keywords:
Distributed Generation (DG), Multi-Objective Frameworks, Pareto-Optimal Solution, Opposition-Based Chaotic Differential Evolution (OCDE), Krill Herd Algorithm (KHA), Power Loss Sensitivity Factor and Simulated Annealing (LSFSA)
Abstract:
In radial distribution grids, correctly locating appropriately sized Distributed Generation (DG) units can greatly enhance system performance. The most significant techno-economic advantages come from decreasing yearly economic losses, which involve deployment, operation, and maintenance costs as well as voltage fluctuations and power loss at the buses. The current issue is being evaluated with different multi-objective frameworks, and the Pareto-optimal solution is also discussed as the optimal compromise solution. When addressing a multi-objective optimization problem, specific equality and inequality constraints are also considered. This paper concentrates on a unique multi-objective approach called whale optimization.
Utilizing genetic algorithms to solve problems with multiple objectives. In order to evaluate its efficiency, the proposed method is applied to IEEE-33 radial bus distribution systems for testing. This paper also contains a comparison with other recent multi-objective algorithms like opposition-based chaotic Differential evolution (OCDE), Krill herd algorithm (KHA), and Power Loss Sensitivity Factor and Simulated Annealing (LSFSA). The proposed method may enhance power loss, annual economic loss mitigation, and voltage profile improvement, as found in research.
|
|
International Journal of Recent Research and Review
ISSN: 2277-8322
Vol. XVII, Issue 4
December 2024
|
PDF View
PUBLISHED
December 2024
ISSUE
Vol. XVII, Issue 4
SECTION
Articles
|
