Charge/Discharge Scheduling of Electric Vehicles and Battery Energy Storage in Smart Building: a Mix Binary Linear Programming model

IF 1.7 Q3 COMPUTER SCIENCE, ARTIFICIAL INTELLIGENCE ADCAIJ-Advances in Distributed Computing and Artificial Intelligence Journal Pub Date : 2022-06-06 DOI:10.14201/adcaij.27904
Zahra Foroozandeha, S. Ramos, J. Soares, Vale Zita, António Gomes
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引用次数: 1

Abstract

Nowadays, the buildings have an important role on high demand of electricity energy. Therefore, the energy management of the buildings may have significant influence on reducing the electricity consumption. Moreover, Electric Vehicles (EVs) have been considering as a power storage devices in Smart Buildings (SBs) aiming to reduce the cost and consuming energy. Here, an energy management framework is proposed in which by considering the flexibility of the contracted power of each apartment, an optimal charging-discharging scheduled for EVs and Battery Energy Storage System (BESS) is defined over long time period to minimize the electricity cost of the building. The proposed model is design by a Mixed Binary Linear rogramming formulation (MBLP) that the charging and discharging of EVs as well as BESS in each period is treated as binary decision variables. In order to validate the model, a case study involving three scenarios are considered. The obtained results indicate a 15% reduction in total electricity consumption cost and consumption energy by the grid over a one year. Finally, the impact of capacity and charge/discharge rate of BESS on the power cost is analyzed and the optimal size of the BESS for assumed SB in the case study is also reported.
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智能建筑中电动汽车充放电调度与电池储能:一个混合二元线性规划模型
如今,建筑对电能的高需求有着重要的作用。因此,建筑的能源管理可能对降低电力消耗产生重大影响。此外,电动汽车(ev)已被考虑作为智能建筑(SBs)的电力存储设备,旨在降低成本和消耗能源。在这里,我们提出了一个能源管理框架,考虑到每个公寓的合同电力的灵活性,为电动汽车和电池储能系统(BESS)定义了一个长期的最佳充放电计划,以最大限度地降低建筑的电力成本。该模型采用混合二元线性规划(MBLP)方法,将电动汽车的充放电和电池储能系统(BESS)在每个时间段作为二元决策变量进行设计。为了验证该模型,考虑了一个涉及三种场景的案例研究。结果表明,在一年的时间里,电网的总电力消耗成本和能源消耗降低了15%。最后,分析了BESS容量和充放电速率对电力成本的影响,并给出了案例研究中假设SB情况下BESS的最佳尺寸。
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来源期刊
CiteScore
1.40
自引率
0.00%
发文量
22
审稿时长
4 weeks
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