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Divyanshi Tanwar
Sanjay Kumar Bansal
Keywords:
Distributed Generation, Genetic Algorithm, Distribution Network Optimization, Techno-Economic Analysis, Power Loss Minimization.
Abstract:
The increasing penetration of distributed generation (DG) sources such as solar photovoltaic, wind, and hybrid renewable systems has transformed conventional electric power distribution networks into more active and complex systems. Optimal placement and sizing of DG units have therefore become critical to achieving technical efficiency and economic viability while maintaining system reliability. This paper presents a comprehensive review of optimal DG placement in distribution networks using genetic algorithm (GA)-based techno-economic approaches. The review begins with an overview of electric power distribution systems, including primary, secondary, and DC distribution configurations, highlighting their operational characteristics and challenges. A detailed literature survey is then presented, covering conventional mathematical optimization techniques, heuristic algorithms, and hybrid optimization methods applied to DG placement problems. Furthermore, the paper discusses optimization and bio-inspired computational intelligence techniques, emphasizing different computational and evolutionary approaches used to handle the nonlinear, multi-objective nature of DG planning. Special attention is given to the application of genetic algorithms, outlining their formulation, encoding strategies, fitness functions, and advantages in minimizing power losses, improving voltage profiles, and reducing overall system costs. Finally, potential future research directions are identified, including the integration of smart grid technologies, uncertainty modeling of renewable sources, and real-time optimization frameworks. The review aims to provide researchers and power system planners with a structured understanding of GA-based DG placement methodologies suitable for modern distribution networks.
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International Journal of Recent Research and Review
ISSN: 2277-8322
Vol. XIX, Issue 1
March 2026
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PUBLISHED
March 2026
ISSUE
Vol. XIX, Issue 1
SECTION
Articles
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