Multi-configurational sizing and analysis in a nanogrid using nested integer linear programming
Optimization algorithms are tools used in the planning and operations of renewable energy-based distributed power systems. Mixed integer linear programming as a classical optimization method is considered in the literature for sizing nanogrid systems due to simplicity and speed. However, the method...
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Elsevier Ltd
2021
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author | Dahiru, Ahmed Tijjani Tan, Chee Wei Salisu, Sani Lau, Kwan Yiew |
author_facet | Dahiru, Ahmed Tijjani Tan, Chee Wei Salisu, Sani Lau, Kwan Yiew |
author_sort | Dahiru, Ahmed Tijjani |
collection | ePrints |
description | Optimization algorithms are tools used in the planning and operations of renewable energy-based distributed power systems. Mixed integer linear programming as a classical optimization method is considered in the literature for sizing nanogrid systems due to simplicity and speed. However, the method has limited capabilities in implementing multi-configurational analysis and requires large formulations. In this paper, nested integer linear programming is proposed to decompose the large formulations and simplify the multi-configurational sizing of residential nanogrid in a semiarid zone. The proposed method is aimed at optimal sizing for energy cost reduction and increased supply availability. The method is implemented in multi-stage hybridization of relaxation and integer methods of linear programming to achieve optimal sizes of the nanogrid components using photovoltaics, wind turbines, and battery. The method realizes $72,343 net present cost and 0.3755 $/kWh levelized cost of energy indicating 33% and 11% reductions compared to mixed integer linear programming and particle swarm optimization. System availability of 99.97% is envisaged to achieve 6677–7782 kWh per capita electricity consumption in residential buildings against the existing 150 kWh. Three configurations analyzed indicated the robustness of the proposed method and the multi-configurational designs clarify options against factors such as space, logistics, or policies. |
first_indexed | 2024-03-05T21:02:59Z |
format | Article |
id | utm.eprints-94450 |
institution | Universiti Teknologi Malaysia - ePrints |
last_indexed | 2024-03-05T21:02:59Z |
publishDate | 2021 |
publisher | Elsevier Ltd |
record_format | dspace |
spelling | utm.eprints-944502022-03-31T15:41:34Z http://eprints.utm.my/94450/ Multi-configurational sizing and analysis in a nanogrid using nested integer linear programming Dahiru, Ahmed Tijjani Tan, Chee Wei Salisu, Sani Lau, Kwan Yiew TK Electrical engineering. Electronics Nuclear engineering Optimization algorithms are tools used in the planning and operations of renewable energy-based distributed power systems. Mixed integer linear programming as a classical optimization method is considered in the literature for sizing nanogrid systems due to simplicity and speed. However, the method has limited capabilities in implementing multi-configurational analysis and requires large formulations. In this paper, nested integer linear programming is proposed to decompose the large formulations and simplify the multi-configurational sizing of residential nanogrid in a semiarid zone. The proposed method is aimed at optimal sizing for energy cost reduction and increased supply availability. The method is implemented in multi-stage hybridization of relaxation and integer methods of linear programming to achieve optimal sizes of the nanogrid components using photovoltaics, wind turbines, and battery. The method realizes $72,343 net present cost and 0.3755 $/kWh levelized cost of energy indicating 33% and 11% reductions compared to mixed integer linear programming and particle swarm optimization. System availability of 99.97% is envisaged to achieve 6677–7782 kWh per capita electricity consumption in residential buildings against the existing 150 kWh. Three configurations analyzed indicated the robustness of the proposed method and the multi-configurational designs clarify options against factors such as space, logistics, or policies. Elsevier Ltd 2021-11-10 Article PeerReviewed Dahiru, Ahmed Tijjani and Tan, Chee Wei and Salisu, Sani and Lau, Kwan Yiew (2021) Multi-configurational sizing and analysis in a nanogrid using nested integer linear programming. Journal of Cleaner Production, 323 . ISSN 0959-6526 http://dx.doi.org/10.1016/j.jclepro.2021.129159 DOI:10.1016/j.jclepro.2021.129159 |
spellingShingle | TK Electrical engineering. Electronics Nuclear engineering Dahiru, Ahmed Tijjani Tan, Chee Wei Salisu, Sani Lau, Kwan Yiew Multi-configurational sizing and analysis in a nanogrid using nested integer linear programming |
title | Multi-configurational sizing and analysis in a nanogrid using nested integer linear programming |
title_full | Multi-configurational sizing and analysis in a nanogrid using nested integer linear programming |
title_fullStr | Multi-configurational sizing and analysis in a nanogrid using nested integer linear programming |
title_full_unstemmed | Multi-configurational sizing and analysis in a nanogrid using nested integer linear programming |
title_short | Multi-configurational sizing and analysis in a nanogrid using nested integer linear programming |
title_sort | multi configurational sizing and analysis in a nanogrid using nested integer linear programming |
topic | TK Electrical engineering. Electronics Nuclear engineering |
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