A generalized fuzzy chance-constrained energy systems planning model for Guangzhou, China
In this study, a generalized fuzzy chance constrained programming method is developed for the energy system planning in Guangzhou under multiple uncertainties. Through integrating the generalized fuzzy programming and chance-constrained programming into an inexact optimization framework, this method...
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| Vydané v: | Energy (Oxford) Ročník 165; s. 191 - 204 |
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| Hlavní autori: | , , , , |
| Médium: | Journal Article |
| Jazyk: | English |
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Oxford
Elsevier Ltd
15.12.2018
Elsevier BV |
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| ISSN: | 0360-5442, 1873-6785 |
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| Abstract | In this study, a generalized fuzzy chance constrained programming method is developed for the energy system planning in Guangzhou under multiple uncertainties. Through integrating the generalized fuzzy programming and chance-constrained programming into an inexact optimization framework, this method can handle uncertainties expressed as probability distributions, fuzzy sets and fuzzy random variables. Solutions of energy supply, power generation, capacity expansion, air pollutant emissions, forest planning, and system cost under different levels of α-cut are obtained considering the constraint violation risk. The results show that the consumption of coal will decline gradually, while natural gas will become the main source of energy supply in the future; the power structure of the city changes from coal to clean energy (e.g., solar, wind, hydro and other renewable energy), and the city's energy supply security is enhanced by stimulating the utilization of renewable energy and reducing the utilization of imported energy. Moreover, a rational use of ecological land is of great significance. Forests can absorb carbon dioxide and will play a positive role in reducing greenhouse effects. When the preferred α value is predetermined by the decision makers, the energy selections can also be obtained directly from the resulting fuzzy membership function. The solutions obtained in the study will help managers to optimize the existing city energy structure, make decisions according to different preferences between system cost and the violation of the constraint, and thus reflect the corresponding energy supply security level.
•A generalized fuzzy chance constrained approach for uncertainty analysis.•Uncertainties expressed as fuzzy set and random variable are effectively tackled.•Forest carbon sequestration is introduced for greenhouse gas mitigation.•Sustainable strategies are obtained under difference risk levels.•Tradeoffs between economy and environment can provide decision-making insights. |
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| AbstractList | In this study, a generalized fuzzy chance constrained programming method is developed for the energy system planning in Guangzhou under multiple uncertainties. Through integrating the generalized fuzzy programming and chance-constrained programming into an inexact optimization framework, this method can handle uncertainties expressed as probability distributions, fuzzy sets and fuzzy random variables. Solutions of energy supply, power generation, capacity expansion, air pollutant emissions, forest planning, and system cost under different levels of α-cut are obtained considering the constraint violation risk. The results show that the consumption of coal will decline gradually, while natural gas will become the main source of energy supply in the future; the power structure of the city changes from coal to clean energy (e.g., solar, wind, hydro and other renewable energy), and the city's energy supply security is enhanced by stimulating the utilization of renewable energy and reducing the utilization of imported energy. Moreover, a rational use of ecological land is of great significance. Forests can absorb carbon dioxide and will play a positive role in reducing greenhouse effects. When the preferred α value is predetermined by the decision makers, the energy selections can also be obtained directly from the resulting fuzzy membership function. The solutions obtained in the study will help managers to optimize the existing city energy structure, make decisions according to different preferences between system cost and the violation of the constraint, and thus reflect the corresponding energy supply security level.
•A generalized fuzzy chance constrained approach for uncertainty analysis.•Uncertainties expressed as fuzzy set and random variable are effectively tackled.•Forest carbon sequestration is introduced for greenhouse gas mitigation.•Sustainable strategies are obtained under difference risk levels.•Tradeoffs between economy and environment can provide decision-making insights. In this study, a generalized fuzzy chance constrained programming method is developed for the energy system planning in Guangzhou under multiple uncertainties. Through integrating the generalized fuzzy programming and chance-constrained programming into an inexact optimization framework, this method can handle uncertainties expressed as probability distributions, fuzzy sets and fuzzy random variables. Solutions of energy supply, power generation, capacity expansion, air pollutant emissions, forest planning, and system cost under different levels of α-cut are obtained considering the constraint violation risk. The results show that the consumption of coal will decline gradually, while natural gas will become the main source of energy supply in the future; the power structure of the city changes from coal to clean energy (e.g., solar, wind, hydro and other renewable energy), and the city's energy supply security is enhanced by stimulating the utilization of renewable energy and reducing the utilization of imported energy. Moreover, a rational use of ecological land is of great significance. Forests can absorb carbon dioxide and will play a positive role in reducing greenhouse effects. When the preferred α value is predetermined by the decision makers, the energy selections can also be obtained directly from the resulting fuzzy membership function. The solutions obtained in the study will help managers to optimize the existing city energy structure, make decisions according to different preferences between system cost and the violation of the constraint, and thus reflect the corresponding energy supply security level. |
| Author | Huang, Guohe Chen, Jiapei Cai, Mengting Fan, Yurui Li, Yunhuan |
| Author_xml | – sequence: 1 givenname: Mengting surname: Cai fullname: Cai, Mengting organization: Institute for Energy, Environment and Sustainability Research, UR-NCEPU, North China Electric Power University, Beijing 102206, China – sequence: 2 givenname: Guohe surname: Huang fullname: Huang, Guohe email: huangg@uregina.ca organization: Institute for Energy, Environment and Sustainability Research, UR-NCEPU, North China Electric Power University, Beijing 102206, China – sequence: 3 givenname: Jiapei surname: Chen fullname: Chen, Jiapei organization: Institute for Energy, Environment and Sustainable Communities, UR-BNU, 3737 Wascana Parkway, Regina, Saskatchewan S4S0A2, Canada – sequence: 4 givenname: Yunhuan surname: Li fullname: Li, Yunhuan organization: Institute for Energy, Environment and Sustainability Research, UR-NCEPU, North China Electric Power University, Beijing 102206, China – sequence: 5 givenname: Yurui surname: Fan fullname: Fan, Yurui organization: Institute for Energy, Environment and Sustainable Communities, UR-BNU, 3737 Wascana Parkway, Regina, Saskatchewan S4S0A2, Canada |
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| SubjectTerms | air pollutants Air pollution Carbon dioxide Chance-constrained programming China Clean energy coal Constraints decision making emissions Emissions control energy Energy model Energy modeling Energy security Energy sources forest management Forests Fuzzy logic Fuzzy sets Fuzzy systems Generalized fuzzy linear programming GHG mitigation Greenhouse effect Greenhouse gases Linear programming Natural gas planning power generation probability distribution Programming Random variables Renewable energy risk Security Solar energy Systems planning Uncertainty Urban planning water power wind power |
| Title | A generalized fuzzy chance-constrained energy systems planning model for Guangzhou, China |
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