Renewable energy sources planning with uncertainties by using chance constrained planning in distribution network
Konferenz: EMIE 2022 - The 2nd International Conference on Electronic Materials and Information Engineering
15.04.2022 - 17.04.2022 in Hangzhou, China
Tagungsband: EMIE 2022
Seiten: 6Sprache: EnglischTyp: PDF
Autoren:
Wang, Jing; Li, Hongwei; Pan, Zhiyuan; Liu, Jing (Grid Operation Training Department, State Grid of China Technology College, Jinan, Shandong, China)
Xiong, Ziwei; Huang, Yifan; Wang, Wei (College of Intelligent Equipment, Shandong University of Science and Technology, Tai’an, Shandong, China)
Inhalt:
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.