Optimal Control of BESS for Improved Grid Integration of the Hybrid DFIG/PV System Using Dual-Layer Adaptive Control

Abstract

In view of the stochastic nature of wind and solar energy, maintaining quality power in grid-connected hybrid energy system is critical for efficient energy utilization, especially in the presence of non-linear loads. This paper deals with the control and performance assessment of grid-integrated hybrid energy system that comprises of doubly fed induction generator (DFIG) and photovoltaic (PV) system including battery energy storage (BES) as a stand-by supply to meet utility and load demand. In order to maintain power balance and address various power quality issues encountered with hybrid renewable integration along the source and the grid/load end, a dual-layer variable-step size adaptive control is implemented for the grid-interfaced converter of the proposed system. The variable step-size based dual-layer least mean square (LMS) adaptive control functions by extracting weights of various control signals (stator and load current) where the step-size parameter adjusts according to the conditions that limit the maladjustment error and increase the rate of convergence. The DC-link voltage control realized by bidirectional BES control reduces the steady-state error and fluctuations in the voltage. An artificial bee colony (ABC) optimization is adopted for optimal gain tuning of the DC-link voltage controller as a result of which the battery performance and grid-side converter performance is enhanced with the increased power exchange to the grid. The system model is developed in MATLAB/Simulink and controller performance is evaluated for diverse operating conditions including steady-state, unbalanced non-linear load conditions, wind-speed and solar irradiation variation and specified grid power modes.