Integration of Renewable Energy Sources into Microgrid Considering Operational and Planning Uncertainties

Abstract

In this paper, a new integration approach for renewable energy sources (RESs), especially intermittent resources (i.e., PV and wind), is presented considering RESs planning uncertainties issues, which are size and location of units, and RESs operational uncertainties issues including operation mode of units and the stochastic nature of prime energy sources (solar irradiance and wind speed). The approach composes of three stages: uncertainties sources modelling, uncertainties expansion, and optimizing uncertainties sources. In the first stage, the nodal active and reactive power uncertainties based on size and operational mode of a renewable power unit are modelled using cumulant technique considering stochastically the solar irradiance, wind speed, and load demands. Secondly, relations of the nodal active and reactive power injections with buses voltage are established. Finally, the particle swarm optimization (PSO) algorithm is utilized to identify the optimal size and operational mode, and the best location and type of RESs for minimizing the buses voltage violations considering technical constraints. The proposed algorithm and analysis on standard 33-bus MG system is implemented using MATLAB. The proposed probabilistic approach by means of cumulant technique reduces the complexity and computational burden of RESs planning problem considering RESs planning and operation uncertainties, which is most important for any researcher in the field of RESs planning and making it very advantageous and practical.