Coordination of vehicle-to-home and renewable capacity resources for energy management in resilience and self-healing building

Hasan Mehrjerdi and Reza Hemmati

Renewable Energy, 2020, vol. 146, issue C, 568-579

Abstract: The home energy management is an efficient tool to manage energy in the buildings that organizes different technologies and mathematical techniques to minimize energy cost. Home energy management often utilizes renewable energy resources to supply load demand in the building. Current home energy management systems utilize one or several of the available hardware-software capacity resources to deal with energy consumption in the buildings. However, a comprehensive model including various hardware and software capacity resources may increase the flexibility of the model. In this regard, this paper studies an efficient paradigm for home energy management in the building connected to electric grid. The proposed model forms an energy hub including the hardware resources (i.e., vehicle-to-home, wind turbine, and diesel generator) and software tools (i.e., demand response program). All the capacity resources and grid power are optimally adjusted to minimize the daily operational cost of the building as well as improvement of resiliency and self-healing. Wind energy and load uncertainty are modeled through stochastic programming. The seasonal pattern is considered for loads, prices, and wind energy. Simulation results demonstrate that operating all capacity resources minimizes the daily operational cost. When the wind energy, demand response program, vehicle-to-home, and diesel generator are not utilized, the cost is increased by 900, 230, 84, and 322%, respectively. It is also confirmed that the building not only can operate when one of the components is not connected, but also it is able to supply the demand under off-grid operation.

Keywords: Demand response program; Home energy management; Resiliency; Stochastic mixed integer binary model; Vehicle to home; Wind turbine (search for similar items in EconPapers)
Date: 2020
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Citations: View citations in EconPapers (29)

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Persistent link: https://EconPapers.repec.org/RePEc:eee:renene:v:146:y:2020:i:c:p:568-579

DOI: 10.1016/j.renene.2019.07.004

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