The widespread availability and affordability of photovoltaic (PV) systems are driving the future of demand-side generation towards end-user-based PV plants. Building-integrated PV systems offer an additional source of electrical energy, but their power output depends on external factors like solar insolation, weather conditions, geographical location, and earth’s rotation, causing non-constant energy generation, even in ideal weather conditions. In grid-connected systems, this variability leads to fluctuations in grid demand. Both BIVP and rooftop PV systems are photovoltaic-based, but their installation differences result in distinct energy generation characteristics. To address this, we propose an innovative approach to optimally integrate BIPV and rooftop PV systems by leveraging their contradictory energy generation nature. By employing mathematical and evolutionary algorithms to design an optimal system and develop a multi-objective optimization model, we address practical design issues. The outcome of these single and multi-objective systems helps minimize fluctuations in grid dependency throughout the year. The proposed system is validated on the IEEE-33 bus radial distribution network using the B&R X20CP1586 PLC, confirming its effectiveness in ensuring a stable and reliable grid performance while mitigating energy fluctuation impacts.