Toward optimal energy management of microgrids via robust two-stage optimization
This paper considers energy management in a grid-connected microgrid which has multiple conventional generators (CGs), renewable generators and energy storage systems (ESSs). A robust two-stage optimization approach is presented to schedule the energy generation under uncertainties, aimed at minimiz...
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sg-ntu-dr.10356-1411932020-06-05T01:15:56Z Toward optimal energy management of microgrids via robust two-stage optimization Hu, Wuhua Wang, Ping Gooi, Hoay Beng School of Computer Science and Engineering School of Electrical and Electronic Engineering Engineering::Electrical and electronic engineering Microgrid Uncertainty This paper considers energy management in a grid-connected microgrid which has multiple conventional generators (CGs), renewable generators and energy storage systems (ESSs). A robust two-stage optimization approach is presented to schedule the energy generation under uncertainties, aimed at minimizing the long-term average operating cost subject to realistic operational and service constraints. The first stage of optimization determines hourly unit commitment of the CGs via a day-ahead scheduling, and the second stage performs economic dispatch of the CGs, ESSs, and energy trading via a real-time scheduling. The combined solution meets the need of handling large uncertainties in the load demands and renewable generation, and provides an efficient solution under limited computational resource which approximately optimizes the long-term average operating cost while meeting the quality-of-service requirements. The performance of the proposed strategy is evaluated by simulations based on real load demand and renewable generation data. NRF (Natl Research Foundation, S’pore) EDB (Economic Devt. Board, S’pore) 2020-06-05T01:15:55Z 2020-06-05T01:15:55Z 2016 Journal Article Hu, W., Wang, P., & Gooi, H. B. (2018). Toward optimal energy management of microgrids via robust two-stage optimization. IEEE Transactions on Smart Grid, 9(2), 1161-1174. doi:10.1109/TSG.2016.2580575 1949-3053 https://hdl.handle.net/10356/141193 10.1109/TSG.2016.2580575 2-s2.0-85042294337 2 9 1161 1174 en IEEE Transactions on Smart Grid © 2016 IEEE. All rights reserved. |
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Engineering::Electrical and electronic engineering Microgrid Uncertainty Hu, Wuhua Wang, Ping Gooi, Hoay Beng Toward optimal energy management of microgrids via robust two-stage optimization |
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This paper considers energy management in a grid-connected microgrid which has multiple conventional generators (CGs), renewable generators and energy storage systems (ESSs). A robust two-stage optimization approach is presented to schedule the energy generation under uncertainties, aimed at minimizing the long-term average operating cost subject to realistic operational and service constraints. The first stage of optimization determines hourly unit commitment of the CGs via a day-ahead scheduling, and the second stage performs economic dispatch of the CGs, ESSs, and energy trading via a real-time scheduling. The combined solution meets the need of handling large uncertainties in the load demands and renewable generation, and provides an efficient solution under limited computational resource which approximately optimizes the long-term average operating cost while meeting the quality-of-service requirements. The performance of the proposed strategy is evaluated by simulations based on real load demand and renewable generation data. |
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School of Computer Science and Engineering |
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School of Computer Science and Engineering Hu, Wuhua Wang, Ping Gooi, Hoay Beng |
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Article |
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Hu, Wuhua Wang, Ping Gooi, Hoay Beng |
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Hu, Wuhua |
title |
Toward optimal energy management of microgrids via robust two-stage optimization |
title_short |
Toward optimal energy management of microgrids via robust two-stage optimization |
title_full |
Toward optimal energy management of microgrids via robust two-stage optimization |
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Toward optimal energy management of microgrids via robust two-stage optimization |
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Toward optimal energy management of microgrids via robust two-stage optimization |
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toward optimal energy management of microgrids via robust two-stage optimization |
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2020 |
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https://hdl.handle.net/10356/141193 |
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1681056506378715136 |