Optimal scheduling method of regenerative electric heating for emergency residential building heating: An affine arithmetic‐based model predictive control approach
Abstract Residential heating faces the challenge of heating interruption when an electric power outage occurs. As a promising heating electrification form, regenerative electric heating (REH) equipped with thermal energy storage (TES) has the flexibility of maintaining the building indoor temperatur...
| Main Authors: | , , , , , , |
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| Format: | Article |
| Language: | English |
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Wiley
2023-03-01
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| Series: | IET Energy Systems Integration |
| Online Access: | https://doi.org/10.1049/esi2.12082 |
| _version_ | 1811154954940841984 |
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| author | Jiarui Zhang Yunfei Mu Zeqing Wu Zhe Liu Yi Gao Hongjie Jia Hairun Li |
| author_facet | Jiarui Zhang Yunfei Mu Zeqing Wu Zhe Liu Yi Gao Hongjie Jia Hairun Li |
| author_sort | Jiarui Zhang |
| collection | DOAJ |
| description | Abstract Residential heating faces the challenge of heating interruption when an electric power outage occurs. As a promising heating electrification form, regenerative electric heating (REH) equipped with thermal energy storage (TES) has the flexibility of maintaining the building indoor temperature within the desired range during power outages and reducing the operation cost during normal operation states. However, the allocation and scheduling of the limited thermal energy in TES for the above two purposes is impacted by many uncertainties, for example, outdoor temperature, irradiation, and duration of power outages. Overestimation of the thermal energy required for power outages in the TES can improve the heating supply reliability, but it will also increase the REH operation cost to some extent, and vice versa. To address this problem, an affine arithmetic‐based model predictive control approach (AA‐MPC) for an optimal REH scheduling method is proposed to balance the heating supply reliability during power outages and operation economy of REH at the same time. An REH‐based residential building energy system model is developed to describe the building thermal load associated with the outdoor temperature and irradiation. Then, the required thermal energy for emergency building heating provided by the hot water tank (HWT) is determined using the minimum thermal demand of residents during a power outage, which is constrained by the minimum comfort temperature threshold. Based on this, an AA‐MPC approach that takes the thermal energy for emergency building heating as a time‐varying constraint of the HWT is developed to determine the optimal REH scheduling that considers emergency residential building heating under the above uncertainties. Numerical studies show that the proposed method can maintain minimum thermal demand for at least 2 h when a power outage occurs under uncertainties. At the same time, it can reduce the impact of uncertainties on the operation cost and reduce economic problems caused by emergency heating to a certain extent. Compared to the interval arithmetic‐based model predictive control approach, the operation cost intervals of the proposed method are reduced by 57.3%, 0.3%, and 32.5% under low, middle, and high prediction error levels respectively. |
| first_indexed | 2024-04-10T04:25:50Z |
| format | Article |
| id | doaj.art-281f0e3757274fb38ea71657c295e6d2 |
| institution | Directory Open Access Journal |
| issn | 2516-8401 |
| language | English |
| last_indexed | 2024-04-10T04:25:50Z |
| publishDate | 2023-03-01 |
| publisher | Wiley |
| record_format | Article |
| series | IET Energy Systems Integration |
| spelling | doaj.art-281f0e3757274fb38ea71657c295e6d22023-03-10T14:13:22ZengWileyIET Energy Systems Integration2516-84012023-03-0151405310.1049/esi2.12082Optimal scheduling method of regenerative electric heating for emergency residential building heating: An affine arithmetic‐based model predictive control approachJiarui Zhang0Yunfei Mu1Zeqing Wu2Zhe Liu3Yi Gao4Hongjie Jia5Hairun Li6Key Laboratory of Smart Grid of Ministry of Education Tianjin University Tianjin ChinaKey Laboratory of Smart Grid of Ministry of Education Tianjin University Tianjin ChinaKey Laboratory of Smart Grid of Ministry of Education Tianjin University Tianjin ChinaGlobal Energy Interconnection Development and Cooperation Organization Beijing ChinaGlobal Energy Interconnection Development and Cooperation Organization Beijing ChinaKey Laboratory of Smart Grid of Ministry of Education Tianjin University Tianjin ChinaKey Laboratory of Smart Grid of Ministry of Education Tianjin University Tianjin ChinaAbstract Residential heating faces the challenge of heating interruption when an electric power outage occurs. As a promising heating electrification form, regenerative electric heating (REH) equipped with thermal energy storage (TES) has the flexibility of maintaining the building indoor temperature within the desired range during power outages and reducing the operation cost during normal operation states. However, the allocation and scheduling of the limited thermal energy in TES for the above two purposes is impacted by many uncertainties, for example, outdoor temperature, irradiation, and duration of power outages. Overestimation of the thermal energy required for power outages in the TES can improve the heating supply reliability, but it will also increase the REH operation cost to some extent, and vice versa. To address this problem, an affine arithmetic‐based model predictive control approach (AA‐MPC) for an optimal REH scheduling method is proposed to balance the heating supply reliability during power outages and operation economy of REH at the same time. An REH‐based residential building energy system model is developed to describe the building thermal load associated with the outdoor temperature and irradiation. Then, the required thermal energy for emergency building heating provided by the hot water tank (HWT) is determined using the minimum thermal demand of residents during a power outage, which is constrained by the minimum comfort temperature threshold. Based on this, an AA‐MPC approach that takes the thermal energy for emergency building heating as a time‐varying constraint of the HWT is developed to determine the optimal REH scheduling that considers emergency residential building heating under the above uncertainties. Numerical studies show that the proposed method can maintain minimum thermal demand for at least 2 h when a power outage occurs under uncertainties. At the same time, it can reduce the impact of uncertainties on the operation cost and reduce economic problems caused by emergency heating to a certain extent. Compared to the interval arithmetic‐based model predictive control approach, the operation cost intervals of the proposed method are reduced by 57.3%, 0.3%, and 32.5% under low, middle, and high prediction error levels respectively.https://doi.org/10.1049/esi2.12082 |
| spellingShingle | Jiarui Zhang Yunfei Mu Zeqing Wu Zhe Liu Yi Gao Hongjie Jia Hairun Li Optimal scheduling method of regenerative electric heating for emergency residential building heating: An affine arithmetic‐based model predictive control approach IET Energy Systems Integration |
| title | Optimal scheduling method of regenerative electric heating for emergency residential building heating: An affine arithmetic‐based model predictive control approach |
| title_full | Optimal scheduling method of regenerative electric heating for emergency residential building heating: An affine arithmetic‐based model predictive control approach |
| title_fullStr | Optimal scheduling method of regenerative electric heating for emergency residential building heating: An affine arithmetic‐based model predictive control approach |
| title_full_unstemmed | Optimal scheduling method of regenerative electric heating for emergency residential building heating: An affine arithmetic‐based model predictive control approach |
| title_short | Optimal scheduling method of regenerative electric heating for emergency residential building heating: An affine arithmetic‐based model predictive control approach |
| title_sort | optimal scheduling method of regenerative electric heating for emergency residential building heating an affine arithmetic based model predictive control approach |
| url | https://doi.org/10.1049/esi2.12082 |
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