IGDT-based economic dispatch considering the uncertainty of wind and demand response
Integration of wind generation and demand response (DR) poses challenges for the power system operation due to their uncertain characteristics. In this study, an economic dispatching method considering the uncertainties of wind and DR is proposed. The method based on the information gap decision the...
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| Published in: | IET renewable power generation Vol. 13; no. 6; pp. 856 - 866 |
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| Main Authors: | , , , |
| Format: | Journal Article |
| Language: | English |
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The Institution of Engineering and Technology
29.04.2019
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| ISSN: | 1752-1416, 1752-1424, 1752-1424 |
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| Abstract | Integration of wind generation and demand response (DR) poses challenges for the power system operation due to their uncertain characteristics. In this study, an economic dispatching method considering the uncertainties of wind and DR is proposed. The method based on the information gap decision theory (IGDT) can be used to evaluate risks associated with uncertainties from risk averse (RA) and risk-seeking (RS) perspectives. The RA IGDT-based model can provide maximum tolerable robustness region for the required cost target. The RS IGDT-based model can help achieve the lowest operation costs with desired uncertainties. The proposed model is bi-level. The upper level subproblem aims to maximise (minimise) the allowable uncertainty level to satisfy the pre-determined cost target, while the lower level subproblem is to maximise (minimise) possible cost considering the uncertainties. The bi-level model is then transformed into a single level mixed integer linear programming problem that can be solved through commercial solves. Finally, the authors evaluate the performance of the IGDT-based approach by simulations on the modified 6-bus and IEEE 118-bus systems. The results show that the proposed approach can provide suggestions for system operators to make appropriate scheduling plan based on the expected cost targets and risk preferences. |
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| AbstractList | Integration of wind generation and demand response (DR) poses challenges for the power system operation due to their uncertain characteristics. In this study, an economic dispatching method considering the uncertainties of wind and DR is proposed. The method based on the information gap decision theory (IGDT) can be used to evaluate risks associated with uncertainties from risk averse (RA) and risk-seeking (RS) perspectives. The RA IGDT-based model can provide maximum tolerable robustness region for the required cost target. The RS IGDT-based model can help achieve the lowest operation costs with desired uncertainties. The proposed model is bi-level. The upper level subproblem aims to maximise (minimise) the allowable uncertainty level to satisfy the pre-determined cost target, while the lower level subproblem is to maximise (minimise) possible cost considering the uncertainties. The bi-level model is then transformed into a single level mixed integer linear programming problem that can be solved through commercial solves. Finally, the authors evaluate the performance of the IGDT-based approach by simulations on the modified 6-bus and IEEE 118-bus systems. The results show that the proposed approach can provide suggestions for system operators to make appropriate scheduling plan based on the expected cost targets and risk preferences. |
| Author | Wang, Ying Yang, Shengchun Dai, Xuemei Zhang, Kaifeng |
| Author_xml | – sequence: 1 givenname: Xuemei surname: Dai fullname: Dai, Xuemei organization: 1Key Laboratory of Measurement and Control of CSE, Ministry of Education, School of Automation, Southeast University, Nanjing, People's Republic of China – sequence: 2 givenname: Ying surname: Wang fullname: Wang, Ying organization: 1Key Laboratory of Measurement and Control of CSE, Ministry of Education, School of Automation, Southeast University, Nanjing, People's Republic of China – sequence: 3 givenname: Shengchun surname: Yang fullname: Yang, Shengchun organization: 2China Electric Power Research Institute, Nanjing, People's Republic of China – sequence: 4 givenname: Kaifeng surname: Zhang fullname: Zhang, Kaifeng email: kaifengzhang@seu.edu.cn organization: 1Key Laboratory of Measurement and Control of CSE, Ministry of Education, School of Automation, Southeast University, Nanjing, People's Republic of China |
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| Keywords | decision theory integer programming single level mixed integer linear programming problem power system operation wind generation IGDT-based economic dispatch linear programming lower level subproblem power generation scheduling DR risk preferences RA IGDT-based model required cost target power generation economics pre-determined cost target optimisation scheduling possible cost power markets uncertain characteristics bi-level model IGDT-based approach system operators 6-bus lowest operation costs expected cost targets allowable uncertainty level risk averse desired uncertainties upper level subproblem power generation dispatch information gap decision theory risks maximum tolerable robustness region economic dispatching method (RS) perspectives RS IGDT-based model demand response |
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| SubjectTerms | (RS) perspectives 6‐bus allowable uncertainty level bi‐level model decision theory demand response desired uncertainties economic dispatching method expected cost targets IGDT‐based approach IGDT‐based economic dispatch information gap decision theory integer programming linear programming lower level subproblem lowest operation costs maximum tolerable robustness region optimisation possible cost power generation dispatch power generation economics power generation scheduling power markets power system operation pre‐determined cost target RA IGDT‐based model required cost target risk averse risk preferences risks RS IGDT‐based model scheduling single level mixed integer linear programming problem Special Issue: Demand Side Management and Market Design for Renewable Energy Support and Integration system operators uncertain characteristics upper level subproblem wind generation |
| Title | IGDT-based economic dispatch considering the uncertainty of wind and demand response |
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