Optimization Study of Hybrid Renewable Energy System in Autonomous Site


Saib S., Gherbi A., BAYINDIR R.

ARTIFICIAL INTELLIGENCE IN RENEWABLE ENERGETIC SYSTEMS: SMART SUSTAINABLE ENERGY SYSTEMS, cilt.35, ss.431-438, 2018 (SCI İndekslerine Giren Dergi) identifier

  • Yayın Türü: Makale / Tam Makale
  • Cilt numarası: 35
  • Basım Tarihi: 2018
  • Doi Numarası: 10.1007/978-3-319-73192-6_45
  • Dergi Adı: ARTIFICIAL INTELLIGENCE IN RENEWABLE ENERGETIC SYSTEMS: SMART SUSTAINABLE ENERGY SYSTEMS
  • Sayfa Sayıları: ss.431-438

Özet

This study aims to investigate the optimal sizing and the reliability of the (PV/wind/battery) hybrid energy system to supply a stand-alone site during their 20 years of lifetime. In this case, an Equivalent Loss Factor (ELF) as reliability index is used and applied in this work. A metaheuristic method such as particle swarm optimization (PSO) is used to solve the optimization problem and compared with other new and improved PSO Algorithms as Fast Convergence and Time Varying Acceleration. A comparative analysis is performed between this study and previous works for a standalone system with a hybrid energy system considering the economic cost using PSO method. Simulation results using Matlab software prove the reliability of the hybrid PV/wind/battery system during its lifetime and the improved PSO method by FC-TVAC algorithm has shown its performance in the optimisation study.