Energy management in smart home including PV panel, battery, electric heater with integration of plug-in electric vehicle

The objective of this study is to optimal scheduling of resources and loads in a smart home (SH) including photovoltaic (PV) panel, battery, plug-in electric vehicle (PEV) and electric heater (EH) along with electrical and thermal loads. Advantages of SH with the proposed structure is that all electrical and thermal loads can be met by electric energy and as a result, it decreases additional investment in natural gas infrastructure, balances electricity and natural gas consumption during seasons, reduces air pollution in home environment, and diminishes SH bills. To this end, an energy management system (EMS) is designed using shuffled frog leaping (SFLA) algorithm for load and resource scheduling such that SH daily energy consumption cost is minimum. Performance of the SH in different scenarios are studied, a feasibility study for the SH is conducted and the results are discussed. Simulation results show that SFLA algorithm has higher capability compared to other algorithms in solving optimal energy management problem in the SH, and it has been shown that PEV which will penetrate significantly in future, has a considerable effect on SH costs and should be considered in residential planning studies.