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

Izdin Mohamad Hlal, Vigna Kumaran Ramachandaramurthy, Farrukh Hafiz Nagi, Tuan Ab Rashid Bin Tuan Abdullah

Research output: Contribution to journalConference article

Abstract

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.

Original languageEnglish
Article number012012
JournalIOP Conference Series: Earth and Environmental Science
Volume268
Issue number1
DOIs
Publication statusPublished - 02 Jul 2019
EventInternational Conference on Sustainable Energy and Green Technology 2018, SEGT 2018 - Kuala Lumpur, Malaysia
Duration: 11 Dec 201814 Dec 2018

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genetic algorithm
economics
energy
wind turbine
rural electrification
cost
sorting
solar wind
solar radiation
rural area
wind velocity
methodology
temperature
loss
demand
battery
sizing

All Science Journal Classification (ASJC) codes

  • Environmental Science(all)
  • Earth and Planetary Sciences(all)

Cite this

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title = "Optimal Techno-Economic Design of Standalone Hybrid Renewable Energy System Using Genetic Algorithm",
abstract = "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.",
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Optimal Techno-Economic Design of Standalone Hybrid Renewable Energy System Using Genetic Algorithm. / Hlal, Izdin Mohamad; Ramachandaramurthy, Vigna Kumaran; Hafiz Nagi, Farrukh; Bin Tuan Abdullah, Tuan Ab Rashid.

In: IOP Conference Series: Earth and Environmental Science, Vol. 268, No. 1, 012012, 02.07.2019.

Research output: Contribution to journalConference article

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