Full metadata record
| DC Field | Value | Language |
|---|---|---|
| dc.contributor | Department of Building Environment and Energy Engineering | en_US |
| dc.contributor.advisor | Wang, Shengwei (BEEE) | en_US |
| dc.creator | Han, Binglong | - |
| dc.identifier.uri | https://theses.lib.polyu.edu.hk/handle/200/13667 | - |
| dc.language | English | en_US |
| dc.publisher | Hong Kong Polytechnic University | en_US |
| dc.rights | All rights reserved | en_US |
| dc.title | Modelling, assessment and scheduling for using building energy flexibility as spinning reserve in power systems | en_US |
| dcterms.abstract | The growing adoption of renewable energy and the increasingly frequent extreme weather events pose great challenges to the supply-demand balance and the reliability of power systems. Spinning reserve is an essential means to manage power imbalance due to renewable forecast uncertainties and generator failures. Traditionally, spinning reserve is provided by standby generators operating at part load. However, more spinning reserve capacity is needed while fewer standby generators are available due to increased renewable penetration. Buildings, particularly their air-conditioning systems, have great potential to provide spinning reserve due to their large electricity use and energy flexibility. However, there are several problems and challenges when using this alternative spinning reserve resource. First, effective methods are needed to model and quantify the energy flexibility capacity of buildings for providing spinning reserve. Second, the impacts of using building energy flexibility for spinning reserve on power systems and buildings need to be assessed. Third, the power system reserve scheduling should be optimized to utilize building energy flexibility in a reliable and economic manner. | en_US |
| dcterms.abstract | This PhD study, therefore, aims to comprehensively and systematically investigate the modelling, assessment and scheduling of building energy flexibility for providing spinning reserve in power systems. | en_US |
| dcterms.abstract | Analytical solutions are developed for energy flexibility modelling of building air-conditioning systems. Five straightforward equations are derived from a commonly used second-order building thermodynamic model, which quantify the load reduction and subsequent load rebound of buildings at both individual and aggregated levels. The solutions avoid time-consuming iterative and finite difference computations of the existing numerical method, facilitating the integration of flexibility quantification in power system scheduling and dispatch. The high accuracy and computational efficiency of analytical solutions are verified through numerical simulations. | en_US |
| dcterms.abstract | The impacts of using building energy flexibility for spinning reserve are assessed and compared with that for load shifting, considering the operation of both power systems and buildings. An integrated grid-buildings model is developed to capture the dynamic interaction between buildings and the power supply side. The model is applied to the Hong Kong power system in 2035. The results show that spinning reserve provision not only offers higher operating cost savings for the power system but also has much less interference to building operation compared to load shifting. Therefore, spinning reserve is proposed as a priority use of building energy flexibility in smart grids. | en_US |
| dcterms.abstract | Buildings may fail to achieve their committed spinning reserve provision in actual operation due to various uncertainties. A probabilistic model is proposed for real-time quantification of building energy flexibility, considering uncertainties in model inputs, model bias, and building response failures. An analytical equation is used to quantify the flexibility of each building, which effectively captures the distinct characteristics of diverse buildings. Test results show that the proposed model accurately quantifies the aggregated energy flexibility of 150 buildings in 6.7 seconds, up to 537 times faster than existing probabilistic models. | en_US |
| dcterms.abstract | A risk-averse reserve scheduling framework is proposed for power systems that engage building energy flexibility, considering the trade-off between cost savings and the risk of using building energy flexibility as spinning reserve. The framework leverages the outputs of the probabilistic model of building energy flexibility to provide risk-based decision-making. A new risk indicator, namely expected reserve shortage, is proposed for more accurate risk assessment. Test results show that adopting building energy flexibility as spinning reserve can reduce both the operation costs and risks of the power system, compared to using conventional generators solely. | en_US |
| dcterms.abstract | An optimal reserve scheduling strategy is proposed for power systems that engage building energy flexibility, considering the load rebound effect after demand response. The strategy accounts for the uncertainties in both renewable forecasts and generator failures, enabling more effective utilization of building flexibility potential. A two-stage robust optimization problem is formulated for reserve scheduling considering load rebound. Test results show that the proposed strategy reduces the power system operation cost by 7.54%, compared to the strategy without considering load rebound. | en_US |
| dcterms.extent | xvi, 122 pages : color illustrations | en_US |
| dcterms.isPartOf | PolyU Electronic Theses | en_US |
| dcterms.issued | 2025 | en_US |
| dcterms.educationalLevel | Ph.D. | en_US |
| dcterms.educationalLevel | All Doctorate | en_US |
| dcterms.accessRights | open access | en_US |
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