Optimal Techno-Economic Design of Standalone Hybrid Renewable Energy System Using Genetic Algorithm

International Conference on Sustainable Energy and Green Technology 2018

能源学;生态环境科学

Hlal, Izdin Mohamad^1 ; Ramachandaramurthy, Vigna K.^1 ; Hafiz Nagi, Farrukh^1 ; Bin Tuan Abdullah, Tuan Ab Rashid^2

Institute of Power Engineering, Department of Electrical Power Engineering, College of Engineering, Universiti Tenaga Nasional, Jalan IKRAM-UNITEN, Kajang

43000, Malaysia^1

Institute of Energy Policy and Research (IEPRe), Universiti Tenaga Nasional, Jalan IKRAM-UNITEN, 43000, Malaysia^2

关键词: Battery energy storages (BES);    Cost of energies;    Hybrid renewable energy systems;    Loss of power supply probability;    Remote location;    Rural electrification;    Sorting genetic algorithm;    Techno-economics;   

Others  :  https://iopscience.iop.org/article/10.1088/1755-1315/268/1/012012/pdf
DOI  :  10.1088/1755-1315/268/1/012012

学科分类：环境科学（综合）

来源: IOP

【 摘 要 】

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.