Comfort-Aware and Cost-Optimized Demand Management for PV-Integrated Smart Homes

Increasing use of electric vehicles (EVs) and air conditioning loads in residential energy consumption highlight the need for energy management focused on both economic and comfort aspects. When the instability of photovoltaic (PV) generation, user habits, and dynamic pricing mechanisms are considered together, the need for multi-criteria optimization in smart grids becomes apparent. Although various methods have been evaluated in the literature for peak load reduction and load curve balancing, the joint consideration of economic optimization and thermal comfort has been studied to a limited extent. In this study, an optimization algorithm is developed for energy management under dynamic pricing in a regional system consisting of 25 houses. As a result of scenario analyses, while the total household income is € 149.17 in the purely profit-oriented approach, scenarios that also consider thermal comfort show a decrease in economic profit but a significant improvement in comfort levels. In particular, the average comfort level rises to 68.96 % in the dynamic pricing and comfort-oriented scenario. The findings reveal that the proposed method offers a balanced solution by increasing user comfort in addition to economic benefits.