Decomposition based multiobjective evolutionary algorithm for PV/Wind/Diesel Hybrid Microgrid System design considering load uncertainty
This paper aims to optimally design a PV/Wind/Diesel Hybrid Microgrid System (HMS) for a small number of houses considering load uncertainty for the city of Yanbu, Saudi Arabia. Designing such a hybrid system with all the renewable and non-renewable sources, storage devices, converters, and loads is...
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| Published in: | Energy reports Vol. 7; pp. 52 - 69 |
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| Main Authors: | , , , , , |
| Format: | Journal Article |
| Language: | English |
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Elsevier Ltd
01.11.2021
Elsevier |
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| ISSN: | 2352-4847, 2352-4847 |
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| Abstract | This paper aims to optimally design a PV/Wind/Diesel Hybrid Microgrid System (HMS) for a small number of houses considering load uncertainty for the city of Yanbu, Saudi Arabia. Designing such a hybrid system with all the renewable and non-renewable sources, storage devices, converters, and loads is a complicated task. A multiobjective approach has been adopted to optimize the microgrid design. Two methodologies are available for solving such multiobjective problems. In the first approach, the problem is transformed into a single objective one (using aggregation, for instance), whereas, the second technique treats objectives simultaneously and independently as adopted in this paper. The proposed approach offers the Pareto front; a set of solutions in one run opening the door of choosing the most suitable solution from the available options based on the experience, expertise and requirement of the designer. This paper presents a novel approach of using Decomposition Based Multiobjective Evolutionary Algorithm (MOEA/D) to optimally design the PV/Wind/Diesel HMS considering load uncertainty. Loss of Power Supply Probability (LPSP) and Cost of Electricity (COE) are considered as the objective functions of the optimization problem. Furthermore, two separate load cases of 5 and 10 houses are tested to verify the robustness of the approach. The obtained results are beneficial in assisting researchers and practitioners in selecting the optimal configuration of the microgrid. |
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| AbstractList | This paper aims to optimally design a PV/Wind/Diesel Hybrid Microgrid System (HMS) for a small number of houses considering load uncertainty for the city of Yanbu, Saudi Arabia. Designing such a hybrid system with all the renewable and non-renewable sources, storage devices, converters, and loads is a complicated task. A multiobjective approach has been adopted to optimize the microgrid design. Two methodologies are available for solving such multiobjective problems. In the first approach, the problem is transformed into a single objective one (using aggregation, for instance), whereas, the second technique treats objectives simultaneously and independently as adopted in this paper. The proposed approach offers the Pareto front; a set of solutions in one run opening the door of choosing the most suitable solution from the available options based on the experience, expertise and requirement of the designer. This paper presents a novel approach of using Decomposition Based Multiobjective Evolutionary Algorithm (MOEA/D) to optimally design the PV/Wind/Diesel HMS considering load uncertainty. Loss of Power Supply Probability (LPSP) and Cost of Electricity (COE) are considered as the objective functions of the optimization problem. Furthermore, two separate load cases of 5 and 10 houses are tested to verify the robustness of the approach. The obtained results are beneficial in assisting researchers and practitioners in selecting the optimal configuration of the microgrid. |
| Author | Shaaban, Yusuf Abubakar Latreche, Yaqoub Javaid, Muhammad Sharjeel Shahriar, Mohammad Shoaib Bouchekara, Houssem Rafik El-Hana Ramli, Makbul Anwari Muhammad |
| Author_xml | – sequence: 1 givenname: Houssem Rafik El-Hana orcidid: 0000-0001-7702-990X surname: Bouchekara fullname: Bouchekara, Houssem Rafik El-Hana email: bouchekara.houssem@gmail.com organization: Department of Electrical Engineering, University of Hafr Al Batin, Hafr Al Batin 31991, Saudi Arabia – sequence: 2 givenname: Muhammad Sharjeel orcidid: 0000-0002-5315-0702 surname: Javaid fullname: Javaid, Muhammad Sharjeel organization: Department of Electrical Engineering, University of Hafr Al Batin, Hafr Al Batin 31991, Saudi Arabia – sequence: 3 givenname: Yusuf Abubakar orcidid: 0000-0001-5130-263X surname: Shaaban fullname: Shaaban, Yusuf Abubakar organization: Department of Electrical Engineering, University of Hafr Al Batin, Hafr Al Batin 31991, Saudi Arabia – sequence: 4 givenname: Mohammad Shoaib orcidid: 0000-0003-2202-0371 surname: Shahriar fullname: Shahriar, Mohammad Shoaib organization: Department of Electrical Engineering, University of Hafr Al Batin, Hafr Al Batin 31991, Saudi Arabia – sequence: 5 givenname: Makbul Anwari Muhammad orcidid: 0000-0002-5281-0377 surname: Ramli fullname: Ramli, Makbul Anwari Muhammad organization: Department of Electrical and Computer Engineering, King Abdulaziz University, Jeddah 21589, Saudi Arabia – sequence: 6 givenname: Yaqoub surname: Latreche fullname: Latreche, Yaqoub organization: Modelling of Energy Renewable Devices and Nano-Metric (MoDERNa) Laboratory, University of Freres Mentouri Constantine, 25000 Constantine, Algeria |
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| Keywords | Decomposition based multi-objective evolutionary algorithm Wind energy Load uncertainty PV Hybrid system |
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| Snippet | This paper aims to optimally design a PV/Wind/Diesel Hybrid Microgrid System (HMS) for a small number of houses considering load uncertainty for the city of... |
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| SubjectTerms | Decomposition based multi-objective evolutionary algorithm Hybrid system Load uncertainty Wind energy |
| Title | Decomposition based multiobjective evolutionary algorithm for PV/Wind/Diesel Hybrid Microgrid System design considering load uncertainty |
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