Abstract
The optimal performance of the smart home energy management system (SHEMS) in coordinating and integrating the equipment in the house plays a significant role in increasing the efficiency and economic benefits of the smart home. This paper proposes a two-level optimization algorithm for the energy management of residential appliances within a smart home, including interruptible, uninterruptible, thermostatically controlled, and non-schedulable loads, as well as the charging/discharging strategies of electric vehicles (EVs) and energy storage systems (ESSs) in the presence of distributed energy resources (DERs). In the first level of optimization, to minimize the cost of electricity, the operating time of smart home components is determined by SHEMS, and active power is exchanged between equipment. At this level, the impact of demand response (DR) constraints on the cost and load factor (LF) of the smart home have also been investigated. In the second level, considering the optimal cost obtained in the first level, in addition to the active power, the reactive power required by loads is also provided by using the additional capacity of EV and ESS inverters and improves the power factor (PF) of the house at the connection point to the grid. Day-ahead electricity costs are calculated depending on different pricing signals (TOU, RTP) with the power exchange capacity (buying/ selling) with the grid. The effectiveness of the proposed strategy is examined on a typical smart home over a 24-h. By reviewing the numerical results obtained for the cost and the LF in different scenarios, and observing the increase of the PF of home from 0.65 to 0.94 and also examining the performance of the equipment during the planning time, the efficiency of the model is proved.
Original language | English (US) |
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Article number | 102972 |
Journal | Sustainable Cities and Society |
Volume | 71 |
DOIs | |
State | Published - Aug 2021 |
All Science Journal Classification (ASJC) codes
- Civil and Structural Engineering
- Geography, Planning and Development
- Renewable Energy, Sustainability and the Environment
- Transportation
Keywords
- Demand response
- Electric vehicles
- Load factor
- Optimization
- Power factor
- Smart home energy management system
- Thermostatically controlled loads