Optimal Planning of Renewable-Based Distributed Resources for Power Distribution System Using Artificial Intelligent Based Genetic Algorithm
Keywords:
Artificial Intelligence, Optimization Algorithm, Genetic Algorithm, Distributed GenerationAbstract
Renewable-based distributed generation has become an attractive alternative to meet the growing electric demand of the future. It has many advantages, including pollution fee generation and other technical parameters. Such DGs are typically deployed at the load end and highly influence network performance. However, improper DG planning and deployment may result in poor voltage regulation and higher line losses. The generation of such DGs is not constant but depends on environmental conditions. This paper presents an optimal strategy for deploying such renewable-based DGs, which provide variable generation on a real-time basis based on different environmental parameters. An artificial intelligence genetic algorithm has been used to get a realistic solution for deploying such DGs across the distribution network. The IEEE-33 bus network has been used for the analysis, and the NR-based load flow program has been used to compute the network performance parameters. The present strategy helps the distribution network operator to decide which type of Dgs are more suitable at a specific geographical location to reduce the payback period for a particular investment. It gives these DGs an appropriate location and size to ensure consistent generation, good power quality, and higher distribution efficiency. A multi-objective fitness function has been formulated to solve the constraint optimization problem. The present strategy has been proposed for optimal planning of a distribution grid operated with renewable-based micro DGs.
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