Grid-Connected Photovoltaic System Stability Enhancement Using Ant Lion Optimized Model Reference Adaptive Control Strategy

• Published in: Differential equations and dynamical systems Vol. 31; no. 2; pp. 503 - 525
• Main Authors: Negi, Pankaj, Pal, Yash, Leena, G.
• Format: Journal Article
• Language: English
• Published: New Delhi Springer India 01.04.2023; Springer Nature B.V
• Subjects: Algorithms; Computer Science; Controllers; Damping; Electric potential; Engineering; Mathematical models; Mathematics; Mathematics and Statistics; Model reference adaptive control; Optimization; Original Research; Parameters; Photovoltaic cells; Steady state; Systems stability; Transfer functions; Voltage; ALO algorithm; Grid-connected PV; LCL filter; MRAC strategy; PR controller
• ISSN: 0971-3514; 0974-6870
• DOI: 10.1007/s12591-020-00525-9

An inductive-capacitive-inductive (LCL) type filters are broadly utilized in grid-connected voltage source inverters (VSIs) since they can give substantially improved attenuation of switching harmonics in currents injected into the grid with lower cost, weight and power losses than their L and LC type counterparts. This paper discusses an improved model reference adaptive control (MRAC) strategy for designing the control parameters to voltage source converter and improves stability of photovoltaic (PV) generation in different grid capabilities. An improved damping strategy is commonly referred to as MRAC, which has been developed using the proportional resonant (PR) controller and its gain parameters are optimized by Ant Lion optimization (ALO) algorithm. The error elimination at steady-state and gain at particular frequency were provided by the PR current controller. The main focus is set on the mathematical modelling of grid-connected PV, LCL filter and PR current controller and its parameters specifically, resonant and proportional gains. Further, the phase margin and gain of the controller transfer function are presented by means of bode plot to evaluate the operating condition of the controller for different gain parameters. Moreover, a large number of control strategies are mandatory for optimizing the controller parameters and to stabilize the system with zero steady-state error. The obtained results of improved MRAC strategy is presented and its effectiveness is compared with some existing controllers.