Distributed Generation Allocation on Radial Distribution Networks Under Uncertainties of Load and Generation Using Genetic Algorithm

This paper presents a distribution generation (DG) allocation strategy for radial distribution networks under uncertainties of load and generation using adaptive genetic algorithm (GA). The uncertainties of load and generation are modeled using fuzzy-based approach. The optimal locations for DG integration and the optimal amount of generation for these locations are determined by minimizing the network power loss and maximum node voltage deviation. Since GA is a metaheuristic algorithm, the results of multiple runs are taken and the statistical variations for locations and generations for DG units are shown. The locations and sizes for DG units obtained with fuzzy-based approach are found to be different than those obtained with deterministic approach. The results obtained with fuzzy-based approach are found to be comparatively efficient in working with future load growth. The proposed approach is demonstrated on the IEEE 33-node test network and a 52-node Indian practical distribution network.