Identifying differential scheduling plans for microgrid operations under diverse uncertainties
To satisfy the differential operation requirements of microgrids under the nominal and uncertain scenarios, a novel three-stage close-looped robust optimization (TSCL-RO) method is proposed to obtain more practical scheduling plans. In the first stage, the fixed startup and shutdown plans are identi...
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sg-ntu-dr.10356-1691092023-06-30T05:00:07Z Identifying differential scheduling plans for microgrid operations under diverse uncertainties Qiu, Haifeng Gooi, Hoay Beng School of Electrical and Electronic Engineering Engineering::Electrical and electronic engineering Decomposition Algorithm Microgrid Scheduling To satisfy the differential operation requirements of microgrids under the nominal and uncertain scenarios, a novel three-stage close-looped robust optimization (TSCL-RO) method is proposed to obtain more practical scheduling plans. In the first stage, the fixed startup and shutdown plans are identified considering both the cutting planes from the nominal and uncertain scenarios. According to the startup/shutdown schemes, the decision-making of the basic flexible plans under the nominal scenario is performed to minimize the operation cost in the second stage considering the second-order cone relaxed distflow model. To confront the disturbances from the power and N-k uncertainties, the basic flexible variables are revised to capture the worst-case scenario via a max-min bi-level optimization in the third stage, and the derived results are returned as feasibility cuts to preserve the robustness of the fixed plans. To solve this intractable TSCL-RO model proficiently, a tailored bi-layer chaining decomposition algorithm is further devised to handle the resulting multi-level mixed-integer second-order cone programming (MISOCP) via alternate iterations. Finally, numerical simulations verify the applicability and superiority of the investigated TSCL-RO model and the decomposition algorithm. National Research Foundation (NRF) This work was supported in part by the National Research Foundation, Singapore, EMA and ESG under Award NRF2019NRFCG002-002 and in part by the Department of the Navy, Office of Naval Research Global under Award N62909-19-1-2037. Paper no. TSTE-00356-2022. 2023-06-30T04:55:21Z 2023-06-30T04:55:21Z 2023 Journal Article Qiu, H. & Gooi, H. B. (2023). Identifying differential scheduling plans for microgrid operations under diverse uncertainties. IEEE Transactions On Sustainable Energy, 14(1), 309-324. https://dx.doi.org/10.1109/TSTE.2022.3211865 1949-3029 https://hdl.handle.net/10356/169109 10.1109/TSTE.2022.3211865 2-s2.0-85146327246 1 14 309 324 en NRF2019NRFCG002-002 N62909-19-1-2037 IEEE Transactions on Sustainable Energy © 2022 IEEE. All rights reserved. |
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Engineering::Electrical and electronic engineering Decomposition Algorithm Microgrid Scheduling Qiu, Haifeng Gooi, Hoay Beng Identifying differential scheduling plans for microgrid operations under diverse uncertainties |
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To satisfy the differential operation requirements of microgrids under the nominal and uncertain scenarios, a novel three-stage close-looped robust optimization (TSCL-RO) method is proposed to obtain more practical scheduling plans. In the first stage, the fixed startup and shutdown plans are identified considering both the cutting planes from the nominal and uncertain scenarios. According to the startup/shutdown schemes, the decision-making of the basic flexible plans under the nominal scenario is performed to minimize the operation cost in the second stage considering the second-order cone relaxed distflow model. To confront the disturbances from the power and N-k uncertainties, the basic flexible variables are revised to capture the worst-case scenario via a max-min bi-level optimization in the third stage, and the derived results are returned as feasibility cuts to preserve the robustness of the fixed plans. To solve this intractable TSCL-RO model proficiently, a tailored bi-layer chaining decomposition algorithm is further devised to handle the resulting multi-level mixed-integer second-order cone programming (MISOCP) via alternate iterations. Finally, numerical simulations verify the applicability and superiority of the investigated TSCL-RO model and the decomposition algorithm. |
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School of Electrical and Electronic Engineering |
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School of Electrical and Electronic Engineering Qiu, Haifeng Gooi, Hoay Beng |
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Article |
author |
Qiu, Haifeng Gooi, Hoay Beng |
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Qiu, Haifeng |
title |
Identifying differential scheduling plans for microgrid operations under diverse uncertainties |
title_short |
Identifying differential scheduling plans for microgrid operations under diverse uncertainties |
title_full |
Identifying differential scheduling plans for microgrid operations under diverse uncertainties |
title_fullStr |
Identifying differential scheduling plans for microgrid operations under diverse uncertainties |
title_full_unstemmed |
Identifying differential scheduling plans for microgrid operations under diverse uncertainties |
title_sort |
identifying differential scheduling plans for microgrid operations under diverse uncertainties |
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2023 |
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https://hdl.handle.net/10356/169109 |
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1772825208966610944 |