Technical-economic management of smart home energy system in the presence of stochastic and seasonal behavior of PV and EV

Document Type : Original Article


1 Energy Management Research Centre, University of Mohaghegh Ardabili, Ardabil, Iran.

2 Faculty of Electrical and Computer Engineering, University of Tabriz, Tabriz, Iran.



Smart home energy management is a useful tool to optimally manage the energy devices of a dwelling. A building with renewable units, controllable appliances, and the electric vehicle has the ability to implement home energy management. This study presents a novel multi-objective method for the smart home energy management system during the different seasons. The smart home has controllable and uncontrollable appliances while the rooftop photovoltaic panel can supply part of the demand during the day. The considered private electric vehicle has the vehicle-to-home technology for better participation in the home energy management program. The solar irradiance, state of charge, and availability of the electric vehicle in the parking are the uncertain parameters that are calculated using the combination of Latin hypercube sampling and K-means algorithms. The defined multi-objective technical-economic function is optimized using the dragonfly algorithm and then the best solution is selected using the fuzzy mechanism. The considered multi-objective algorithm is compared with other optimization methods for showing its efficiency. The numerical results, which are the output of implementing the method in a sample smart home, show the proper performance of the proposed method rather than other algorithms by about 10-40 %. Although the proposed method considerably improves the indices of the smart home, the highest efficiency of the smart home is achieved after applying the proposed energy management method on a spring day because of more availability of domestic energy units.


Main Subjects

Volume 6, Issue 4 - Serial Number 4
December 2022
Pages 270-281
  • Receive Date: 02 July 2022
  • Revise Date: 30 July 2022
  • Accept Date: 14 August 2022
  • First Publish Date: 30 August 2022