Advanced load frequency control in smart grids using optimization techniques for enhanced stability and performance

Abstract

The pursuit of sustainability in power systems involves optimizing the operation and control strategies to achieve improved stability, reliability, and performance while minimizing environmental impacts. The power system stability plays a vital role in ensuring reliable and sustainable electricity supply. This chapter develops an advanced growth optimizer (GO) algorithm by integrating proportional-integral-derivative (PID) controllers for enhancing the load frequency control (LFC) in a multi-area thermal power plant. Also, the proposed integrated approach of the GO-PID controller is specifically tailored to address the nonlinearities present in each thermal power plant within the system. This individual design ensures that the stability and performance of the existing LFC controller are preserved even in the presence of governor deadband and generation rate constraint (GRC) nonlinearities. By accounting for these nonlinearities, the proposed GO-PID controller offers a robust and reliable solution, effectively regulating key control parameters in terms of the frequency in each area, and tie-line power flow. In comparison to the well-known particle swarm optimization (PSO) and other reported results, the proposed GO-PID controller derives effective enhanced power system stability and performance under different cases of varying load disturbances. Moreover, the proposed GO-PID controller maintains stability in a multi-area thermal power plant with efficient adaptation to several uncertainties, thereby improving system resilience and sustainability. The simulation findings declare the capability of the proposed GO-PID controller to face system uncertainties in different areas simultaneously. In comparison to the PSO algorithm, the proposed GO-PID controller shows an improvement of 11.67%. Also, it attains highly stable dynamic responses of the frequencies and the power transferred compared to PSO and previously reported outcomes.