Multi-Objective Energy Management System in Smart Homes with Inverter-Based Air Conditioner Considering Costs, Peak-Average Ratio, and Battery Discharging Cycles of ESS and EV

Moslem Dehghani, Seyyed Mohammad Bornapour (), Felipe Ruiz () and Jose Rodriguez
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Moslem Dehghani: Centro de Transición Energética (CTE), Facultad de Ingeniería, Universidad San Sebastián, Bellavista 7, Santiago 8420524, Chile
Seyyed Mohammad Bornapour: Electrical Engineering Department, Faculty of Engineering, Yasouj University, Yasouj 7493475918, Iran
Felipe Ruiz: Centro de Transición Energética (CTE), Facultad de Ingeniería, Universidad San Sebastián, Bellavista 7, Santiago 8420524, Chile
Jose Rodriguez: Centro de Transición Energética (CTE), Facultad de Ingeniería, Universidad San Sebastián, Bellavista 7, Santiago 8420524, Chile

Energies, 2025, vol. 18, issue 19, 1-21

Abstract: The smart home contributions in energy management systems can help the microgrid operator overcome technical problems and ensure economically viable operation by flattening the load profile. The purpose of this paper is to propose a smart home energy management system (SHEMS) that enables smart homes to monitor, store, and manage energy efficiently. SHEMS relies heavily on energy storage systems (ESSs) and electric vehicles (EVs), which enable smart homes to be more flexible and enhance the reliability and efficiency of renewable energy sources. It is vital to study the optimal operation of batteries in SHEMS; hence, a multi-objective optimization approach for SHEMS and demand response programs is proposed to simultaneously reduce the daily bills, the peak-to-average ratio, and the number of battery discharging cycles of ESSs and EVs. An inverter-based air conditioner, photovoltaic system, ESS, and EV, shiftable and non-shiftable equipment are considered in the suggested smart home. In addition, the amount of energy purchased and sold throughout the day is taken into account in the suggested mathematical formulation based on the real-time market pricing. The suggested multi-objective problem is solved by an improved gray wolf optimizer, and various weather conditions, including rainy, sunny, and cloudy days, are also analyzed. Additionally, simulations indicate that the proposed method achieves optimal results, with three objectives shown on the Pareto front of the optimal solutions.

Keywords: smart home; enhanced energy management system; inverter-based air conditioner; optimal operation; sunny, cloudy, and rainy days (search for similar items in EconPapers)
JEL-codes: Q Q0 Q4 Q40 Q41 Q42 Q43 Q47 Q48 Q49 (search for similar items in EconPapers)
Date: 2025
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