Self-Tuning PI Control of SSSC Based on Neural Networks

Power system with SSSC is a large-scale nonlinear, indeterminist, multivariable system, and the traditional PI controller has a limited application in some cases because of its non-adaptive parameters. In this paper, a new control strategy of SSSC based on self-adaptive PI algorithm with neural network is proposed for power flow control of power systems. In the proposed controller, an identification network is modeled to analyze the dynamic power systems, and PI self-tuning parameters network is employed to obtain the optimal control parameters using training algorithm presented in this paper. With perfect dynamic characteristics of controller, the active and reactive power of power systems is flexibly controlled using PI regulating parameters with neural networks. A studying example is carried out to estimate good robustness and adaptability of the proposed controller in the MATLAB dynamic simulation platform. The results verified the adaptability and feasibility of the proposed control strategy in power flow control of power systems.