A multi-objective fuzzy robust optimization approach for designing sustainable and reliable power systems under uncertainty
A sustainable and reliable power system is extremely important to ensure the prosperity of a country and its society. Traditional power systems are facing serious environmental and social issues while renewable energy systems possess low reliability due to the intermittent nature of energy sources....
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| Vydáno v: | Applied soft computing Ročník 92; s. 106317 |
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| Hlavní autoři: | , |
| Médium: | Journal Article |
| Jazyk: | angličtina |
| Vydáno: |
Elsevier B.V
01.07.2020
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| ISSN: | 1568-4946, 1872-9681 |
| On-line přístup: | Získat plný text |
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| Abstract | A sustainable and reliable power system is extremely important to ensure the prosperity of a country and its society. Traditional power systems are facing serious environmental and social issues while renewable energy systems possess low reliability due to the intermittent nature of energy sources. This paper addresses the sustainable and reliable power system design problem in an uncertain environment by using an approach called multi-objective fuzzy robust programming. The proposed approach, which is an integration of robust programming and two main branches of fuzzy programming (possibilistic and flexible programming), solves the presented multi-objective problem by simultaneously improving both sustainability and reliability, as well as by capturing uncertain factors. The objective is to determine the optimal number, location, capacity, and technology of the generation units as well as the electricity generated and transmitted through the network while minimizing the sustainability and reliability costs of the system. The proposed model considers uncertainties in the demand, the intermittent nature of renewable energy resources, and cost parameters. A case study in Vietnam was conducted to demonstrate the efficacy and efficiency of the proposed model. Results show that the proposed model improves the total cost of the power system, including sustainability and reliability costs, by approximately 4.2% and reduces the computational time by 20% compared to the scenario-based stochastic programming approach. Our findings also show that due to risk disruption, the reliability cost of the power system increases to 56.72% when more electric power is generated.
•Design a power distribution network with uncertain parameters.•A multi-objective robust possibilistic flexible programming method is presented.•The objective is to minimize the economic costs and environmental and social impacts.•We applied the method to Vietnam’s electric power distribution network.•A robust sensitivity analysis technique allows the decision makers to select a proper energy strategy. |
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| AbstractList | A sustainable and reliable power system is extremely important to ensure the prosperity of a country and its society. Traditional power systems are facing serious environmental and social issues while renewable energy systems possess low reliability due to the intermittent nature of energy sources. This paper addresses the sustainable and reliable power system design problem in an uncertain environment by using an approach called multi-objective fuzzy robust programming. The proposed approach, which is an integration of robust programming and two main branches of fuzzy programming (possibilistic and flexible programming), solves the presented multi-objective problem by simultaneously improving both sustainability and reliability, as well as by capturing uncertain factors. The objective is to determine the optimal number, location, capacity, and technology of the generation units as well as the electricity generated and transmitted through the network while minimizing the sustainability and reliability costs of the system. The proposed model considers uncertainties in the demand, the intermittent nature of renewable energy resources, and cost parameters. A case study in Vietnam was conducted to demonstrate the efficacy and efficiency of the proposed model. Results show that the proposed model improves the total cost of the power system, including sustainability and reliability costs, by approximately 4.2% and reduces the computational time by 20% compared to the scenario-based stochastic programming approach. Our findings also show that due to risk disruption, the reliability cost of the power system increases to 56.72% when more electric power is generated.
•Design a power distribution network with uncertain parameters.•A multi-objective robust possibilistic flexible programming method is presented.•The objective is to minimize the economic costs and environmental and social impacts.•We applied the method to Vietnam’s electric power distribution network.•A robust sensitivity analysis technique allows the decision makers to select a proper energy strategy. |
| ArticleNumber | 106317 |
| Author | Thanh, Vo-Van Tsao, Yu-Chung |
| Author_xml | – sequence: 1 givenname: Yu-Chung orcidid: 0000-0001-5058-8728 surname: Tsao fullname: Tsao, Yu-Chung email: yctsao@mail.ntust.edu.tw – sequence: 2 givenname: Vo-Van orcidid: 0000-0001-5027-5684 surname: Thanh fullname: Thanh, Vo-Van |
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| Keywords | Power system Robust optimization Fuzzy multi-objective Renewable energy Reliability Sustainability |
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