Study On The Optimal Allocation Of Grid-Connected Photovoltaic Generation Based On Improved Genetic Algorithm
INTERNATIONAL CONFERENCE ON ELECTRICAL, CONTROL AND AUTOMATION (ICECA 2014)(2014)
Abstract
Photovoltaic generation will become the mainstream of new distributed generation systems in future, this paper studies the optimal allocation of grid-connected photovoltaic generation. It establishes the photovoltaic power position and capacity of multi-objective optimization model with minimum network loss, minimum node voltage offset and minimum cost. It improves parallel selection method based genetic algorithm, highlighting optimize key objectives function, and obtaining the optimal solution based on the use of the improved algorithm; Finally, adopting IEEE33 distribution network test system testes the models and algorithms, simulation results show the correctness of the model and the superiority of the improved algorithm.
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