In this paper, the influence of adding changeable renewable energy, namely, solar-photovoltaic energy from the Kamuthi Solar Power Project, on the stability of the electrical system on the power grid in southern India is investigated. This paper proposes a unified optimization framework that combines predictive control of solar irradiation-based thermal heating systems with reactive power compensation planning in unbalanced distribution networks. Unlike existing Particle Swarm Optimization (PSO) applications focused solely on Automatic Generation Control (AGC), the proposed method optimizes demand-side thermal load scheduling and reactive support in real-time. Solar irradiation is predicted using past weather data to plan its use for heating and storing the energy i.e., capacitors or STATCOMs (Static Synchronous Compensators). PSO also finds the optimal values and sizes of devices that help to manage the reactive power compensation to keep the voltage stable in unbalanced three-phase systems. The proposed PSO algorithm is combined with the AGC system to optimize the distribution of solar energy. According to the findings, combining AGC with PSO stabilizes the frequency at the thermal power plant, and it will reduce the overall active losses by 13.90%. Moreover, intelligent power factor management at the injection buses ensures optimal power quality and maximizes the utilization of the photovoltaic park, reducing the grid’s reliance on gas turbines by 4.84%.
Sinu et al. (Thu,) studied this question.