Renewable energy sources planning with uncertainties by using chance constrained planning in distribution network

Nowadays, more and more renewable energy sources (RESs) have been integrated into distribution networks, how to address the random variables such as wind speed, irradiance and load demands in the RES planning procedure is a significant challenge. To deal with uncertainties, scenario technology is adopted. A chance constrained RESs planning model is developed using scenarios yielding from Monte Carlo sampling (MCS). Then a novel solving strategy, combining loss sensitivity factor (LSF) approach and particle swarm optimization (PSO) algorithm is developed. Test results has demonstrated the effectivity and precision of the proposed method.