Robust dispatch for electrical–thermal combined smart building considering impacts of uncertainties on thermal side
The close connection between electrical energy and thermal energy is an important attribute of current smart buildings. Most previous works aim to emphasize the important role of the power side, thus neglecting the accuracy of the thermal side model. At the same time, from the perspective of the bui...
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| Main Authors: | , , , |
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| Format: | Article |
| Language: | English |
| Published: |
Elsevier
2025-10-01
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| Series: | International Journal of Electrical Power & Energy Systems |
| Subjects: | |
| Online Access: | http://www.sciencedirect.com/science/article/pii/S0142061525005587 |
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| Summary: | The close connection between electrical energy and thermal energy is an important attribute of current smart buildings. Most previous works aim to emphasize the important role of the power side, thus neglecting the accuracy of the thermal side model. At the same time, from the perspective of the building layer, uncertainties such as random solar radiation will affect not only the electrical side but also the thermal side. This paper presents a robust day-ahead dispatch for the smart building which is integrated with coupled electrical system and thermal system. First, we propose a comprehensive thermodynamic model to evaluate impacts of uncertain factors on the thermal system of the smart building in this paper. Subsequently, a robust co-optimization framework is formulated to cope with the uncertainties in a unified manner. To deal with the nonlinearity brought by the electrical–thermal coupled relationship, we propose a piecewise linearization method to convert the nonlinear robust co-optimization dispatch to a linear min–max–min problem, which can be solved by a traditional decomposition algorithm. Case studies demonstrate that the impact of solar radiation uncertainty on the thermal side accounts for 16.2% of that on the power side, indicating its significance. Compared with traditional thermodynamic models, the refined model can better reflect the actual working conditions of the building thermal storage system. The robust scheduling model proposed in this paper that considers the uncertainty on both sides jointly improves the conservatism of traditional scheduling schemes while achieving better economic benefits. |
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| ISSN: | 0142-0615 |