A distributed peer‐to‐peer energy trading model in integrated electric–thermal system
Abstract To promote the energy accommodation of both electrical and heating power while considering the source–load uncertainties, a peer‐to‐peer (P2P) energy trading model among prosumers in the integrated electric–thermal system is proposed here, considering the energy trading agent (ETA) with sel...
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| Main Authors: | , , , , |
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| Format: | Article |
| Language: | English |
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Wiley
2024-11-01
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| Series: | IET Renewable Power Generation |
| Subjects: | |
| Online Access: | https://doi.org/10.1049/rpg2.12918 |
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| _version_ | 1846164203379884032 |
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| author | Ting Huang Yi Sun Jianhong Hao Chong Sun Chuang Liu |
| author_facet | Ting Huang Yi Sun Jianhong Hao Chong Sun Chuang Liu |
| author_sort | Ting Huang |
| collection | DOAJ |
| description | Abstract To promote the energy accommodation of both electrical and heating power while considering the source–load uncertainties, a peer‐to‐peer (P2P) energy trading model among prosumers in the integrated electric–thermal system is proposed here, considering the energy trading agent (ETA) with self‐build energy system. The solar heat‐pump hybrid thermal water system (SPTS) and the transferring loss of heating power is considered and modelled based on the principle of steady‐state thermal transfer. Since the variations of load and PV cannot be described by any single common distribution, the chance‐constraints programming based on the Gaussian mixture model (GMM) is proposed to handle the uncertainty of the net load. As the proposed power trading problem is a non‐convex problem with binary variables, an improved alternating direction method of multiplier (ADMM) based on the predictor‐corrector and two‐stage cycle iterations is proposed to enhance the convergence performance of standard ADMM. Finally, an example simulation verifies the effectiveness; this results show that the proposed model can decrease the total cost by 26.7% and enhance local energy balance by 61.8% compared to other cases. |
| format | Article |
| id | doaj-art-c4e58fdd39e7438cac49b9f4d2903905 |
| institution | Kabale University |
| issn | 1752-1416 1752-1424 |
| language | English |
| publishDate | 2024-11-01 |
| publisher | Wiley |
| record_format | Article |
| series | IET Renewable Power Generation |
| spelling | doaj-art-c4e58fdd39e7438cac49b9f4d29039052024-11-18T14:18:26ZengWileyIET Renewable Power Generation1752-14161752-14242024-11-0118153188320310.1049/rpg2.12918A distributed peer‐to‐peer energy trading model in integrated electric–thermal systemTing Huang0Yi Sun1Jianhong Hao2Chong Sun3Chuang Liu4Department of Electrical and Electronic Engineering North China Electric Power University Beijing ChinaDepartment of Electrical and Electronic Engineering North China Electric Power University Beijing ChinaDepartment of Electrical and Electronic Engineering North China Electric Power University Beijing ChinaMarketing Service Centre State Grid Hebei Electric Power Co., Ltd. Shijiazhuang ChinaMarketing Service Centre State Grid Hebei Electric Power Co., Ltd. Shijiazhuang ChinaAbstract To promote the energy accommodation of both electrical and heating power while considering the source–load uncertainties, a peer‐to‐peer (P2P) energy trading model among prosumers in the integrated electric–thermal system is proposed here, considering the energy trading agent (ETA) with self‐build energy system. The solar heat‐pump hybrid thermal water system (SPTS) and the transferring loss of heating power is considered and modelled based on the principle of steady‐state thermal transfer. Since the variations of load and PV cannot be described by any single common distribution, the chance‐constraints programming based on the Gaussian mixture model (GMM) is proposed to handle the uncertainty of the net load. As the proposed power trading problem is a non‐convex problem with binary variables, an improved alternating direction method of multiplier (ADMM) based on the predictor‐corrector and two‐stage cycle iterations is proposed to enhance the convergence performance of standard ADMM. Finally, an example simulation verifies the effectiveness; this results show that the proposed model can decrease the total cost by 26.7% and enhance local energy balance by 61.8% compared to other cases.https://doi.org/10.1049/rpg2.12918demand side managementdistributed controlenergy management systemsGaussian distributionpower markets |
| spellingShingle | Ting Huang Yi Sun Jianhong Hao Chong Sun Chuang Liu A distributed peer‐to‐peer energy trading model in integrated electric–thermal system IET Renewable Power Generation demand side management distributed control energy management systems Gaussian distribution power markets |
| title | A distributed peer‐to‐peer energy trading model in integrated electric–thermal system |
| title_full | A distributed peer‐to‐peer energy trading model in integrated electric–thermal system |
| title_fullStr | A distributed peer‐to‐peer energy trading model in integrated electric–thermal system |
| title_full_unstemmed | A distributed peer‐to‐peer energy trading model in integrated electric–thermal system |
| title_short | A distributed peer‐to‐peer energy trading model in integrated electric–thermal system |
| title_sort | distributed peer to peer energy trading model in integrated electric thermal system |
| topic | demand side management distributed control energy management systems Gaussian distribution power markets |
| url | https://doi.org/10.1049/rpg2.12918 |
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