Multi-microgrid optimization and energy management under boost voltage converter with Markov prediction chain and dynamic decision algorithm

Esmaeili Shayan, Mostafa and Najafi, Gholamhassan and Ghobadian, Barat and Gorjian, Shiva and Rizalman, Mamat and Mohd Fairusham, Ghazali (2022) Multi-microgrid optimization and energy management under boost voltage converter with Markov prediction chain and dynamic decision algorithm. Renewable Energy, 201. pp. 179-189. ISSN 0960-1481. (Published)

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Abstract

Knowledge on operational energy consumption and embodied energy, replacing embodied greenhouse gas (GHG) emissions in building materials, and national energy resources have become a necessity. In this study, the importance of investigating the stochastic nature of weather-dependent renewable energies is well documented. The management of the hybrid renewable energy system (HRES) was built and assessed, utilizing a decision-making algorithm and 13 case studies. When the proportion of renewable energy is at 24% and the average daily fossil fuel usage is 1.11 L per year, the HRES generates 1697 kWh per year with a net present value (NPV) of 553,68 USD, with a rate of return (IRR) of 21.4%, and a payback period (PP) of 15.7 years. With a renewable energy share of 54%, fossil fuel consumption dropped to 0.69 L per year, while yearly energy output was comparable to 1652 kWh per year, with an IRR of 19.5% and a PP of 17.6 years. To achieve zero greenhouse gas emissions, HRES Management employs 100% renewable energy sources to generate 1933 kWh per year at a net present value of −372.09 USD. This scenario is economically possible if the renewable energy feed-in tariff exceeds 0.06 USD.

Item Type: Article
Additional Information: Indexed by Scopus
Uncontrolled Keywords: Decision-making algorithm; Fossil fuel; Greenhouse gas (GHG); Hybrid renewable energy system (HRES); Renewable energies
Subjects: T Technology > T Technology (General)
T Technology > TA Engineering (General). Civil engineering (General)
T Technology > TJ Mechanical engineering and machinery
T Technology > TL Motor vehicles. Aeronautics. Astronautics
Faculty/Division: Faculty of Mechanical and Automotive Engineering Technology
Depositing User: Mr Muhamad Firdaus Janih@Jaini
Date Deposited: 16 Apr 2024 04:26
Last Modified: 16 Apr 2024 04:26
URI: http://umpir.ump.edu.my/id/eprint/40437
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