Reduction of Low Frequency Oscillations Using an Enhanced Power System Stabilizer via Linear Parameter Varying Approach

• Published in: Journal of renewable energy and environment Vol. 9; no. 2; pp. 59 - 74
• Main Authors: Vahid Nazari, Mohammad Hossein Mousavi, Hassan Moradi CheshmehBeigi
• Format: Journal Article
• Language: English
• Published: Materials and Energy Research Center (MERC) 01.04.2022
• Subjects: linear matrix inequality (lmi); linear parameter varying (lpv); power system stabilizer; single machine infinite bus power system
• ISSN: 2423-5547; 2423-7469
• DOI: 10.30501/jree.2021.306909.1265

Over the past decades, power engineers have begun to connect power grids to other networks such as microgrids associated with renewable units using long transmission lines to provide higher reliability and greater efficiency in production and distribution besides saving resources. However, many dynamic problems such as low frequency oscillations were observed as a result of these connections. Low frequency oscillation is a normal phenomenon in most power systems that causes perturbations and, thus, the grid stability and damping process are of paramount importance. In this paper, to attenuate these oscillations, a novel method for designing Power System Stabilizer (PSS) is presented via Linear Parameter-Varying (LPV) approach for a Single Machine Infinite Bus system (SMIB). Because the system under study is subject to frequent load and production changes, designing the stabilizer based on the nominal model may not yield the desired performance. To guarantee the flexibility of the stabilizer with respect to the aforementioned issues, the power system polytopic representation is used. In order to apply the new method, the nonlinear equations of the system at each operating point, located in a polytope, are parametrically linearized by scheduling variables. Scheduling variables can be measured online in any operating point. By using this model and following the H∞ synthesis, feedback theories, and Linear Matrix Inequalities (LMIs), LPV controllers at all operating points are obtained. Finally, the simulation results verify the effectiveness of the proposed controller over classic and robust controllers with regard to uncertainties and changes in system conditions.