An enhanced particle swarm optimization algorithm for improving the renewable energy penetration and small signal stability in power system

In power systems, increasing the renewable energy penetration with small signal stability is one of the demanding and critical tasks in recent days. This research work aims to develop a multistage optimization technique, namely particle swarm optimization (PSO), for improving both the energy penetration and small signal stability. Here, the wind and solar power sources are considered, and its penetration is maximized by satisfying the grid requirements such as the bus voltage, line flows, and real and reactive power generation within the limit. This work includes two stages: in the first stage, PSO algorithm is implemented for maximizing the renewable energy penetration to the test systems. Then, in the second stage, the small signal stability of the systems is improved with maximum renewable energy penetration in which the best locations for connecting the wind farm are identified by using the calculation of wind farm placement index and solar generation is fixed by considering voltage and bus load absorption capability. During simulation, the proposed method is tested and validated by using IEEE 14-bus standard system, and the 220 kV Kerala (India) grid practical system with the solar and wind power. Moreover, various measures such as power generation, load and bus voltage are evaluated for two different case studies. In this evaluation, it is proved that the renewable energy sources are safely integrated with the power system with increased energy penetration and improved small signal stability.