Multi-objective optimal power flow of thermal-wind-solar power system using an adaptive geometry estimation based multi-objective differential evolution

作     者：Huy, Truong Hoang Bao Doan, Hien Thanh Vo, Dieu Ngoc Lee, Kyu-haeng Kim, Daehee 

作者机构：Soonchunhyang Univ Dept Future Convergence Technol Asan 31538 Chuncheongnam D South Korea Sogang Univ Dept Elect Engn Seoul South Korea Ho Chi Minh City Univ Technol HCMUT Dept Power Syst 268 Ly Thuong Kiet StDist 10 Ho Chi Minh City Vietnam Vietnam Natl Univ Ho Chi Minh City Ho Chi Minh City Vietnam Dankook Univ Dept Mobile Syst Engn Yongin 16890 Gyeonggi Do South Korea 

出 版 物：《APPLIED SOFT COMPUTING》 (应用软计算)

年 卷 期：2023年第149卷第PartA期

核心收录：

学科分类：08[工学] 0812[工学-计算机科学与技术（可授工学、理学学位）] 

基　　金：National Research Foundation of Korea (NRF) - Korea government (MSIT) [2021R1A4A2001810, NRF-2021R1F1A1049778, RS-2023-00277255] Institute for Information & communications Technology Planning & Evaluation (IITP) - Korea government (MSIT) [2022-0-01197] Convergence security core talent training business (SoonChunHyang University) Soonchunhyang Research Fund 

主　　题：Adaptive geometry estimation Differential evolution Multi-objective optimal power flow Solar power Wind power 

摘      要：Sustainable energy is a key component of sustainable development. The current grid can be supplied by fossil fuel generators and renewable energy sources (RESs)-based generators, such as solar photovoltaic (PV) and wind power generators. In an electrical network, power generation from several sources must be optimally coordi-nated to ensure efficient and economical operation. However, the intermittent and uncertain nature of RESs complicate the operation of power systems. In this study, an adaptive geometry estimation-based multi-objective differential evolution (AGE-MODE) method is proposed for multi-objective optimal power flow in a hybrid power system of thermal, wind, and solar energy sources (MOOPF-TWS). In the proposed approach, wind and solar PV power outputs are predicted based on Weibull and lognormal probability distribution functions, respectively. Therefore, the generation costs for solar and wind power can be divided into direct costs, penalty costs for underestimation, and reserve costs for overestimation. Furthermore, the emissions, voltage deviation, and real power loss are considered in particular cases. AGE-MODE is applied to modified IEEE 30-bus and 57-bus systems, where different case studies are simulated with combinations of two-, three-, and four-objective optimizations in MOOPF-TWS problems. Comparisons between AGE-MODE and other recently developed multi-objective methods demonstrate its effectiveness in resolving MOOPF-TWS problems, particularly for cases with more than two objectives.