Assessment of demand-side management strategies in PV-integrated residential systems

This paper investigates the impact of three distinct Demand-Side Management (DSM) strategies, Peak Shaving, Load Shifting, and Valley Filling, on the operational performance of a residential PV and battery-integrated system under a time-of-use (TOU) electricity pricing scheme. A simulation framework based on MATLAB is developed using one year of hourly data for a typical European prosumer with a 6,000 kWh load, 6 kWp PV, 6kWh battery and realistic tariff conditions. While DSM strategies have been widely studied, comparative assessments at the residential scale focusing on both cost and grid stability in PV-battery systems remain limited. The strategies are subsequently assessed using three key performance indicators (KPIs), namely self-consumption, grid dependency, and annual electricity cost. In the findings, compared to a baseline scenario (31.73% self-consumption and 85.39% grid dependency), all DSM strategies demonstrated notable improvements. Peak Shaving and Load Shifting increased self-consumption to over 35% and reduced grid dependency to nearly 70%, yielding annual savings up to €151. Valley Filling, while achieving lower local energy utilization (33%), significantly enhanced grid stability by reducing load fluctuations. These findings highlight the trade-offs between maximizing economic efficiency and supporting grid stability. Future research will expand on hybrid integration of these strategies within Energy Communities to enhance both prosumer autonomy and distribution network resilience.