Next Generation Heffron-Phillips Model for Damping Power System Oscillations based on a Novel Meta-Heuristic Snake Optimization Algorithm
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Abstract
Low-Frequency Oscillations (LFO) created due to various disturbances affect the integrity, security, efficiency, and safety of the power system. The traditional Heffron-Phillips (HP) Model of a power system has 6-K-Constants and the state vector is composed of only four state variables. In the present work, a higher-order Synchronous Machine Model 1.1 is used to develop the next-generation HP Model called an Advanced Heffron-Phillips Model (AHPM). There are now 5 state variables and 10 K-Constants including the dynamics of d and q-axis internal voltages. A novel meta-heuristic snake optimization algorithm (SOA) with the key features of exploration and exploitation is used for optimizing the parameters of PSS, TCSC, and Coordinated PSS and TCSC, and the results are compared. The coordinated model based on AHPM produced excellent stability results. The system oscillations died out fastest, with a settling time of less than 2 seconds, and a damping ratio as high as 99.30% is achieved with the coordinated model. Together with the graphical responses, the dominant eigenvalues are mentioned to highlight this notable shift in performance. The system’s power transfer capacity is also improved along with stability. The integration of renewables into the grid creates new stability issues and challenges. This AHPM based on SOA is capable of meeting these challenges. The power grid with AHPM is more efficient, robust, secure, and safe against unpredictable operating conditions with renewables.
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