This paper proposes a new energy management model for residential buildings to handle the uncertainties of demand and on-site PV generation. For this purpose, the building energy management system (BEMS) organizes a transactive energy (TE) market among plug-in electric vehicles (PEVs) to determine their charge/discharge scheduling. According to the proposed TE framework, the PEV owners get reimbursed by the BEMS for the flexibility they offer. In this regard, the PEV owners submit their response curves for reimbursement upon arrival. Then, the BEMS solves an optimization problem to maximize its own profit and determine the real-time TE market-clearing price. Afterward, based on the clearing price, the real-time scheduling of PEV batteries and the reimbursements to the PEV owners for their responses are determined. Additionally, the original mixed-integer non-linear optimization problem is reformulated as a mixed-integer linear programming one using a set of linearization techniques. Finally, the proposed model is applied to a residential building with 50 PEV charging piles, and the simulation results show that the proposed model decreases the actual charging payment of PEV owners by 17.6% and 52.3%, and the total cost of BEMS by 5.1% and 10.8% compared to demand response concept-based and uncontrolled charging models, respectively.

中文翻译：

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住宅建筑中支持 V2G 的电动汽车的交互式能源管理：MILP 方法


本文提出了一种新的住宅建筑能源管理模型，以处理需求和现场光伏发电的不确定性。为此，建筑能源管理系统 (BEMS) 在插电式电动汽车 (PEV) 之间组织了一个交互能源 (TE) 市场，以确定其充电/放电计划。根据拟议的 TE 框架，PEV 所有者因其提供的灵活性而获得 BEMS 的补偿。在这方面，PEV 车主在抵达时提交响应曲线以进行报销。然后，BEMS解决优化问题以最大化自身利润并确定实时TE市场出清价格。随后，根据清算价格，确定PEV电池的实时调度以及对PEV车主响应的补偿。此外，使用一组线性化技术将原始混合整数非线性优化问题重新表述为混合整数线性规划问题。最后，将所提出的模型应用于拥有50个PEV充电桩的住宅楼，仿真结果表明，所提出的模型使PEV车主的实际充电费用分别降低了17.6%和52.3%，BEMS总成本降低了5.1%与基于需求响应概念的收费模型和不受控制的收费模型相比，分别节省了 10.8% 和 10.8%。