This paper presents a methodology to size Standalone Hybrid Renewable Energy System (SHRES) which combines solar PV, wind turbine (WT) and battery energy storage (BES) for application in rural areas. These sources are integrated via an AC bus to support the load demand. SHRES is simulated under varying load demand, solar radiation, temperature and wind speed obtained from the Malaysian Meteorological Department. A Multi-objective Optimization using Non-dominate Sorting Genetic Algorithm (NSGA-II) was utilized to determine the best sizing of PV / wind turbine / battery, and minimize Cost of Energy (COE) and Loss of Power Supply Probability (LPSP). The results show that the NSGAII optimization of the model is able to determine the best techno-economic sizing for the suggested location. For the case study, the optimum COE was 0.1099 (USD/kWh) and LPSP was 0.0865. The proposed tool can be used to size the SHRES for rural electrification and enhance energy access within remote locations.
|Journal||IOP Conference Series: Earth and Environmental Science|
|Publication status||Published - 02 Jul 2019|
|Event||International Conference on Sustainable Energy and Green Technology 2018, SEGT 2018 - Kuala Lumpur, Malaysia|
Duration: 11 Dec 2018 → 14 Dec 2018
All Science Journal Classification (ASJC) codes
- Environmental Science(all)
- Earth and Planetary Sciences(all)