Stochastic Optimal Operation for Integrated Energy System Considering Multiple Uncertainties
Given uncertainties of distributed generation (DG) output and multi-energy loads including electricity, heating, and cooling in integrated energy systems (IES), an IES stochastic optimal operation strategy considering multiple uncertainties of source-side and load-side is proposed in the paper. Firs...
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| Vydané v: | 2022 IEEE 3rd China International Youth Conference on Electrical Engineering (CIYCEE) s. 1 - 5 |
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03.11.2022
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| Abstract | Given uncertainties of distributed generation (DG) output and multi-energy loads including electricity, heating, and cooling in integrated energy systems (IES), an IES stochastic optimal operation strategy considering multiple uncertainties of source-side and load-side is proposed in the paper. Firstly, through analyzing the influences of multiple uncertainties, the stochastic optimization model of IES is established. Then, with the sample average approximation (SAA), the stochastic optimization model is converted into a deterministic mixed-integer linear programming model and solved by the CPLEX solver. Finally, the feasibility of the proposed strategy is verified through an example, and sensitivity analysis of different fluctuation degrees and uncertainty factors is further carried out. Compared with the traditional deterministic model, the proposed stochastic optimization model is more in line with reality. |
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| AbstractList | Given uncertainties of distributed generation (DG) output and multi-energy loads including electricity, heating, and cooling in integrated energy systems (IES), an IES stochastic optimal operation strategy considering multiple uncertainties of source-side and load-side is proposed in the paper. Firstly, through analyzing the influences of multiple uncertainties, the stochastic optimization model of IES is established. Then, with the sample average approximation (SAA), the stochastic optimization model is converted into a deterministic mixed-integer linear programming model and solved by the CPLEX solver. Finally, the feasibility of the proposed strategy is verified through an example, and sensitivity analysis of different fluctuation degrees and uncertainty factors is further carried out. Compared with the traditional deterministic model, the proposed stochastic optimization model is more in line with reality. |
| Author | Pu, Yue Gao, Yukun Liu, Haoming Li, Chengao |
| Author_xml | – sequence: 1 givenname: Chengao surname: Li fullname: Li, Chengao email: 1245666122@qq.com organization: College of Energy and Electrical Engineering, Hohai University,Nanjing,China,210000 – sequence: 2 givenname: Yue surname: Pu fullname: Pu, Yue email: puyue@hhu.edu.cn organization: College of Energy and Electrical Engineering, Hohai University,Nanjing,China,210000 – sequence: 3 givenname: Yukun surname: Gao fullname: Gao, Yukun organization: College of Energy and Electrical Engineering, Hohai University,Nanjing,China,210000 – sequence: 4 givenname: Haoming surname: Liu fullname: Liu, Haoming organization: College of Energy and Electrical Engineering, Hohai University,Nanjing,China,210000 |
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| Snippet | Given uncertainties of distributed generation (DG) output and multi-energy loads including electricity, heating, and cooling in integrated energy systems... |
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| SubjectTerms | Analytical models Electrical engineering Fluctuations integrated energy system Mixed integer linear programming multiple uncertainties sample average approximation Sensitivity analysis stochastic optimization Stochastic processes Uncertainty |
| Title | Stochastic Optimal Operation for Integrated Energy System Considering Multiple Uncertainties |
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