2024/03/25 by Mir Sayed Shah Danish, Soichiro Ueda, Masahiro Furukakoi +5 · 1 voice
Energy · Engineering · Environmental Science · #Energy and Environment Impacts #Hybrid Renewable Energy Systems #Integrated Energy Systems Optimization
paper · doi:10.1002/tee.24065
openalex publication_date 2024/03/25 · openalex created_date 2025/10/10 · openalex updated_date 2026/07/22
Integrating renewable energy sources (RES) into power systems presents significant challenges due to their diverse nature and operational characteristics. This study addresses these challenges through an innovative strategy that simulates solar and wind farms, storage systems, fuel cell generators of hydrogen energy (via electrolysis), and hydrogen storage, all governed by an intelligent controller. Alongside a mathematical model defining the system's dynamics, a multi‐objective optimization model is employed, exploring the system's operational, financial, and environmental impacts. While the mathematical model has limitations, the advanced model captures the system's dynamic behavior with exceptional precision. This intelligent simulation simplifies the complex interrelationships between various resources in the system, highlighting the viability of RES integration for enhanced benefits. Multi‐objective optimization of a real case study of Iowa 240‐Bus power system in the Midwest United States has resulted in an annual savings of 126 147.8, along with a significant CO 2 reduction of 951 035.6 kg compared with the basecase. The total annual energy costs, including capital costs and electricity sales, are reported to be 157 430.4, and the total annual CO 2 emissions are −4453.8 kg. Financial indicators highlight an annual cost reduction of 10.3% and an annual emission reduction of 100.5%. The simple and detailed project break‐even years are 18 and 1, respectively, with the project savings to cost minimization scenario ratio at 1.04. The optimization process efficiently handled a complex problem involving 5921 iterations, 299 247 variables, 11 854 discrete variables, and 342 167 equations, completing the entire operation in 12.7 s. © 2024 Institute of Electrical Engineers of Japan and Wiley Periodicals LLC.