Simultaneous Coordinated Design of IPFC Damping Controller and PSS Using Reinforcement Learning For Low-Frequency Oscillation Enhancement

Stability margins of power system is decreasing continuously and unstable or less damped low frequency oscillations appear in modern power systems. Inter-connected power systems are nonlinear in inherent and power transfering between system areas (due to increase in demand) increased this nonlinearity characteristic. The main objective of this thesis is to enhance the stability of power system by coordinated design of IPFC and PSS using a robust and adaptive control method called Reinforcement Learning (RL). In this thesis, standard test systems are simulated in power system laboratory. In summary, for implementing this thesis following steps done: 1- Study about power system low frequency damping controller design, selecting the best type of PSS for use in this thesis, and selecting appropriate test systems. 2- Study about multi-agent systems and their applications in power system control. 3- Simulation of Single Machine Infinite Bus (SMIB) power system in power system laboratory and coordinated designing of PSS and IPFC using reinforcement learning. 4- Simulation of multi-machine power system in power system laboratory and coordinated designing of PSS and IPFC using reinforcement learning. 5- Evaluation of performance of the proposed reinforcement learning based controller in standard test systems and compare the results with valid references. Keywords:1- IPFC. 2. Reinforcement learning. 3. Low-frequency oscillations. 4- Multi-agent systems. 5- Power system stabilizer.