Two-stage scheduling strategy for integrated energy systems considering renewable energy consumption
With the crisis of energy and environment, the integrated energy systems (IES) have a bright prospect in future energy reform owing to the excellent economic and environmental performance. The IES combines a large amount of renewable energy (RE), which guarantees its economic and environmental benef...
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sg-ntu-dr.10356-1649902023-03-10T15:40:06Z Two-stage scheduling strategy for integrated energy systems considering renewable energy consumption Liu, Xinghua Xie, Shenghan Tian, Jiaqiang Wang, Peng School of Electrical and Electronic Engineering Engineering::Electrical and electronic engineering Integrated Energy Systems Renewable Energy Consumption With the crisis of energy and environment, the integrated energy systems (IES) have a bright prospect in future energy reform owing to the excellent economic and environmental performance. The IES combines a large amount of renewable energy (RE), which guarantees its economic and environmental benefits. Many uncertainties of RE threaten the performance of IES. How to promote RE consumption under strong uncertainties is a crucial problem in the scheduling of IES. In this work, a two-stage scheduling strategy for IES combining day-ahead scheduling and real-time scheduling is proposed to guide the system operation. The stage of day-ahead scheduling can obtain the optimal scheduling scheme one day in advance based on the forecast data of RE, and the stage of real-time scheduling is introduced to cope with the uncertainties of RE. The model of IES is established based on the energy hub (EH), and the entire strategy is implemented on this model. The model integrates various energy conversion equipment to give full play to the advantages of coordination and complementation of IES. The improved particle swarm optimization (IPSO) is proposed as the solution algorithm of the whole strategy, which improves the traditional PSO through random nonlinearity change inertia weight strategy and best solution perturbation operator (BSPO). Compared with the traditional PSO, IPSO has more excellent performance for solving IES scheduling model. Finally, different schemes under different situations are compared. Published version This work was supported in part by the National Natural Science Foundation of China under Grant U2003110, in part by the Key Laboratory Project of Shaanxi Provincial Department of Education under Grant 20JS110. 2023-03-07T01:42:21Z 2023-03-07T01:42:21Z 2022 Journal Article Liu, X., Xie, S., Tian, J. & Wang, P. (2022). Two-stage scheduling strategy for integrated energy systems considering renewable energy consumption. IEEE Access, 10, 83336-83349. https://dx.doi.org/10.1109/ACCESS.2022.3197154 2169-3536 https://hdl.handle.net/10356/164990 10.1109/ACCESS.2022.3197154 2-s2.0-85136146343 10 83336 83349 en IEEE Access © 2022 The Authors. This work is licensed under a Creative Commons Attribution 4.0 License. For more information, see https://creativecommons.org/licenses/by/4.0/. application/pdf |
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Engineering::Electrical and electronic engineering Integrated Energy Systems Renewable Energy Consumption Liu, Xinghua Xie, Shenghan Tian, Jiaqiang Wang, Peng Two-stage scheduling strategy for integrated energy systems considering renewable energy consumption |
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With the crisis of energy and environment, the integrated energy systems (IES) have a bright prospect in future energy reform owing to the excellent economic and environmental performance. The IES combines a large amount of renewable energy (RE), which guarantees its economic and environmental benefits. Many uncertainties of RE threaten the performance of IES. How to promote RE consumption under strong uncertainties is a crucial problem in the scheduling of IES. In this work, a two-stage scheduling strategy for IES combining day-ahead scheduling and real-time scheduling is proposed to guide the system operation. The stage of day-ahead scheduling can obtain the optimal scheduling scheme one day in advance based on the forecast data of RE, and the stage of real-time scheduling is introduced to cope with the uncertainties of RE. The model of IES is established based on the energy hub (EH), and the entire strategy is implemented on this model. The model integrates various energy conversion equipment to give full play to the advantages of coordination and complementation of IES. The improved particle swarm optimization (IPSO) is proposed as the solution algorithm of the whole strategy, which improves the traditional PSO through random nonlinearity change inertia weight strategy and best solution perturbation operator (BSPO). Compared with the traditional PSO, IPSO has more excellent performance for solving IES scheduling model. Finally, different schemes under different situations are compared. |
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School of Electrical and Electronic Engineering |
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School of Electrical and Electronic Engineering Liu, Xinghua Xie, Shenghan Tian, Jiaqiang Wang, Peng |
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Article |
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Liu, Xinghua Xie, Shenghan Tian, Jiaqiang Wang, Peng |
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Liu, Xinghua |
title |
Two-stage scheduling strategy for integrated energy systems considering renewable energy consumption |
title_short |
Two-stage scheduling strategy for integrated energy systems considering renewable energy consumption |
title_full |
Two-stage scheduling strategy for integrated energy systems considering renewable energy consumption |
title_fullStr |
Two-stage scheduling strategy for integrated energy systems considering renewable energy consumption |
title_full_unstemmed |
Two-stage scheduling strategy for integrated energy systems considering renewable energy consumption |
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two-stage scheduling strategy for integrated energy systems considering renewable energy consumption |
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2023 |
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https://hdl.handle.net/10356/164990 |
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1761781792613859328 |