Multi-microgrid optimization and energy management under boost voltage converter with Markov prediction chain and dynamic decision algorithm
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 energie...
| Main Authors: | , , , , , |
|---|---|
| Format: | Article |
| Language: | English English |
| Published: |
Elsevier Ltd
2022
|
| Subjects: | |
| Online Access: | http://umpir.ump.edu.my/id/eprint/40437/ http://umpir.ump.edu.my/id/eprint/40437/1/Multi-microgrid%20optimization%20and%20energy%20management.pdf http://umpir.ump.edu.my/id/eprint/40437/2/Multi-microgrid%20optimization%20and%20energy%20management%20under%20boost%20voltage%20converter%20with%20Markov%20prediction%20chain%20and%20dynamic%20decision%20algorithm_ABS.pdf |
| _version_ | 1848826049142456320 |
|---|---|
| author | Esmaeili Shayan, Mostafa Najafi, Gholamhassan Ghobadian, Barat Gorjian, Shiva Rizalman, Mamat Mohd Fairusham, Ghazali |
| author_facet | Esmaeili Shayan, Mostafa Najafi, Gholamhassan Ghobadian, Barat Gorjian, Shiva Rizalman, Mamat Mohd Fairusham, Ghazali |
| author_sort | Esmaeili Shayan, Mostafa |
| building | UMP Institutional Repository |
| collection | Online Access |
| description | 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. |
| first_indexed | 2025-11-15T03:38:38Z |
| format | Article |
| id | ump-40437 |
| institution | Universiti Malaysia Pahang |
| institution_category | Local University |
| language | English English |
| last_indexed | 2025-11-15T03:38:38Z |
| publishDate | 2022 |
| publisher | Elsevier Ltd |
| recordtype | eprints |
| repository_type | Digital Repository |
| spelling | ump-404372024-04-16T04:26:36Z http://umpir.ump.edu.my/id/eprint/40437/ Multi-microgrid optimization and energy management under boost voltage converter with Markov prediction chain and dynamic decision algorithm Esmaeili Shayan, Mostafa Najafi, Gholamhassan Ghobadian, Barat Gorjian, Shiva Rizalman, Mamat Mohd Fairusham, Ghazali T Technology (General) TA Engineering (General). Civil engineering (General) TJ Mechanical engineering and machinery TL Motor vehicles. Aeronautics. Astronautics 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. Elsevier Ltd 2022-12 Article PeerReviewed pdf en http://umpir.ump.edu.my/id/eprint/40437/1/Multi-microgrid%20optimization%20and%20energy%20management.pdf pdf en http://umpir.ump.edu.my/id/eprint/40437/2/Multi-microgrid%20optimization%20and%20energy%20management%20under%20boost%20voltage%20converter%20with%20Markov%20prediction%20chain%20and%20dynamic%20decision%20algorithm_ABS.pdf 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) https://doi.org/10.1016/j.renene.2022.11.006 https://doi.org/10.1016/j.renene.2022.11.006 |
| spellingShingle | T Technology (General) TA Engineering (General). Civil engineering (General) TJ Mechanical engineering and machinery TL Motor vehicles. Aeronautics. Astronautics Esmaeili Shayan, Mostafa Najafi, Gholamhassan Ghobadian, Barat Gorjian, Shiva Rizalman, Mamat Mohd Fairusham, Ghazali Multi-microgrid optimization and energy management under boost voltage converter with Markov prediction chain and dynamic decision algorithm |
| title | Multi-microgrid optimization and energy management under boost voltage converter with Markov prediction chain and dynamic decision algorithm |
| title_full | Multi-microgrid optimization and energy management under boost voltage converter with Markov prediction chain and dynamic decision algorithm |
| title_fullStr | Multi-microgrid optimization and energy management under boost voltage converter with Markov prediction chain and dynamic decision algorithm |
| title_full_unstemmed | Multi-microgrid optimization and energy management under boost voltage converter with Markov prediction chain and dynamic decision algorithm |
| title_short | Multi-microgrid optimization and energy management under boost voltage converter with Markov prediction chain and dynamic decision algorithm |
| title_sort | multi-microgrid optimization and energy management under boost voltage converter with markov prediction chain and dynamic decision algorithm |
| topic | T Technology (General) TA Engineering (General). Civil engineering (General) TJ Mechanical engineering and machinery TL Motor vehicles. Aeronautics. Astronautics |
| url | http://umpir.ump.edu.my/id/eprint/40437/ http://umpir.ump.edu.my/id/eprint/40437/ http://umpir.ump.edu.my/id/eprint/40437/ http://umpir.ump.edu.my/id/eprint/40437/1/Multi-microgrid%20optimization%20and%20energy%20management.pdf http://umpir.ump.edu.my/id/eprint/40437/2/Multi-microgrid%20optimization%20and%20energy%20management%20under%20boost%20voltage%20converter%20with%20Markov%20prediction%20chain%20and%20dynamic%20decision%20algorithm_ABS.pdf |