Optimal planning of microgrid systems under uncertainty
An effective approach to serve unelectrified areas and potentially decrease carbon emissions is by installing microgrid systems powered by renewable sources. This paper develops an optimization model that aims to minimize the total costs involved in deploying an off-grid microgrid in a rural area. T...
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| Format: | text |
| Language: | English |
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Animo Repository
2021
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| Subjects: | |
| Online Access: | https://animorepository.dlsu.edu.ph/etdm_induseng/2 https://animorepository.dlsu.edu.ph/cgi/viewcontent.cgi?article=1004&context=etdm_induseng |
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| Institution: | De La Salle University |
| Language: | English |
| Summary: | An effective approach to serve unelectrified areas and potentially decrease carbon emissions is by installing microgrid systems powered by renewable sources. This paper develops an optimization model that aims to minimize the total costs involved in deploying an off-grid microgrid in a rural area. The optimization model is written in a multi-period mixed-integer linear programming method. In addition to the minimization of total costs, the objective of the model includes the reduction of carbon emission by converting it to penalty costs. The resulting model maximizes first the renewable sources based on solar irradiation and wind speed per month before purchasing a diesel generator. However, diesel generators acquired the majority of the budget distribution in the base model due to their high capital and variable costs. To validate the deterministic model, it is subjected to different scenarios which revealed the factors affecting the decisions of the decision model – solar irradiation, wind speed, capital cost, and demand. Since the microgrid system is powered by renewable sources – Photovoltaic Panels and Wind Turbines, this study considered uncertainty in solar irradiation and wind speed. In doing this, Target-Oriented Robust Optimization (TORO) was utilized to enhance the base model so it can operate within a budget set by the decision-maker and provide solutions on different risk levels due to parameter uncertainty. Contrary to the deterministic model, the results of the TORO model are inclined in installing clean energy and almost zero diesel generators. |
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