Risk management strategy for a renewable power supply system in commercial buildings considering thermal comfort and stochastic electric vehicle behaviors

• Published in: Energy conversion and management 2021-02, Vol.230, p.113831, Article 113831
• Main Authors: Xu, Xiao, Hu, Weihao, Liu, Wen, Du, Yuefang, Huang, Rui, Huang, Qi, Chen, Zhe
• Format: Article
• Language: English
• Subjects: Buildings; Commercial building; Commercial buildings; Electric vehicle; Electric vehicles; Emissions control; Energy; Energy management; Greenhouse gases; Integer programming; Linear programming; Mixed integer; Operating costs; Optimization; Photovoltaic cells; Photovoltaics; Power supply; Renewable energy; Retired electric vehicle battery; Risk management; Risk management strategy; Shopping malls; Strategy; Sustainable development; Thermal comfort
• ISSN: 0196-8904; 1879-2227
• DOI: 10.1016/j.enconman.2021.113831

•A novel commercial building-oriented power supply system is proposed.•The energy management strategy of the system is proposed in an uncertain environment.•Different models of EVs are developed based on their different stochastic behaviors.•Integration of REVBs into buildings provides their possible echelon utilization. Reduction of greenhouse gas emissions in the building sector has become a global concern in terms of ensuring sustainable development. Thus it is imperative to investigate the utilization of clean electricity in buildings. This study proposes a novel, cost-effective commercial building-oriented power supply system for providing a comfortable environment in a shopping mall. An energy management strategy is also proposed for this system. Two types of electric vehicles (EVs) are considered, and their models are developed separately based on different stochastic behaviors. Furthermore, the integration of retired electric vehicle batteries (REVBs) in commercial buildings is one of the possible methods for achieving echelon utilization. To address the uncertainties in the system, the scenario-based stochastic optimization method is applied, which formulates the energy management problem as a mixed-integer linear programming model. Results show that by integrating only photovoltaic (PV) energy and both PV and REVBs into commercial buildings, reductions of 82.2% and 83.3%, respectively, in the expected operational cost can be achieved. This proves that the application of PV and REVBs is beneficial for commercial buildings. Moreover, the robustness of the employed method is proven through comparison with other methods.