Sustainable energy planning for cost minimization of autonomous hybrid microgrid using combined multi-objective optimization algorithm

Article


Haidar, Ahmed M.A., Fakhar, Adila and Helwig, Andreas. 2020. "Sustainable energy planning for cost minimization of autonomous hybrid microgrid using combined multi-objective optimization algorithm." Sustainable Cities and Society. 62. https://doi.org/10.1016/j.scs.2020.102391
Article Title

Sustainable energy planning for cost minimization of autonomous hybrid microgrid using combined multi-objective optimization algorithm

ERA Journal ID201543
Article CategoryArticle
AuthorsHaidar, Ahmed M.A. (Author), Fakhar, Adila (Author) and Helwig, Andreas (Author)
Journal TitleSustainable Cities and Society
Journal Citation62
Article Number102391
Number of Pages20
Year2020
Place of PublicationNetherlands
ISSN2210-6707
2210-6715
Digital Object Identifier (DOI)https://doi.org/10.1016/j.scs.2020.102391
Web Address (URL)https://www.sciencedirect.com/science/article/abs/pii/S2210670720306120
Abstract

With the development of scattered energy resources in the rural areas of Sarawak (Malaysia), various operational problems due to the unplanned installation of autonomous microgrids become gradually remarkable. To address this concern, the paper proposes an optimal strategy to evaluate the performance of different hybrid microgrid configurations for the Long San Village in Sarawak. A mathematical model is presented for sizing the component of the system to meet the maximum load demand under changing weather conditions and at the lowest possible cost. The developed approach simulates different microgrid models using deterministic and stochastic optimization methods to find the exact dynamic energy price of the selected optimal configuration in the context of system uncertainties. Furthermore, the operational feasibility of the system in terms of reliability and voltage security is studied in addition to economic feasibility with a comparative analysis of the environmental impact. The results show that the optimal configuration with the lowest cost of energy and net present cost can be achieved if the installed solar PV is less than 61 kW with 85 kWh of energy storage and 11 kW of hydro generation, where such system has 55,725 (kg/year) Carbon Dioxide and 330 (kg/year) Nitrogen Oxides. The findings also indicate that the dynamic energy pricing increases to 0.71 $/kWh when the power generation from renewable resources drops to zero. Further, the dynamic analysis shows that in order to reduce the voltage drop during disturbances, it is crucial to carefully install the sources in the buses connected to high energy demand.

KeywordsCost minimization; Hybrid energy systems; Multi-objective optimization; Operational analysis; Regression analysis; Rural areas electrification
ANZSRC Field of Research 2020400899. Electrical engineering not elsewhere classified
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Institution of OriginUniversity of Southern Queensland
Byline AffiliationsUniversity of Malaysia, Sarawak, Malaysia
School of Engineering
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