Distributed renewable generations such as photovoltaic units are electricity generators for installing close to the loads on the distribution system. In this paper, the dispatch function of a non-centralized Virtual Power Plant (VPP) with having a photovoltaic unit in each bus is considered to optimize. This dispatch function is assigned based on the predicted load shape of the next day. A new day-ahead hybrid optimization algorithm is presented to optimize the dispatch function. The proposed algorithm implements a new hybrid combination of Particle Swarm Optimization (PSO) and Genetic Optimization (GA) algorithms simultaneously to benefit both algorithms’ advantages. The objective function is the optimization of the voltage deviation of the VPP. The suggested algorithm is executed on a 13-bus-radial IEEE standard VPP system using MATLAB software coupled with open-source software called Open-DSS. The results show the importance of the proposed algorithm to optimize the voltage deviation of the VPP. The superiority of the proposed algorithm is related to the accuracy and calculation velocity in comparison with the other tested evolutionary algorithms. The Distribution System Operator could map and move towards its full benefits of the increasing integration of DGs with a strategic placement that could keen prosumers on integrating these actions.
Chaotic slime mould optimization algorithm for optimal load-shedding in distribution system
