Energy efficient control of a stand-alone wind energy conversion system with AC current harmonics compensation

This paper presents a new energy-efficient control strategy for a variable-speed wind energy conversion system (WECS). The considered WECS is designed for dc load supply and battery charging in stand-alone applications. The batteries are charged through a three-phase full-bridge power converter. The WECS contains a vector-controlled self-excited induction generator (SEIG) coupled to a wind turbine (WT) for electric power generation on the ac side. The control algorithm proposed in this paper includes three separate optimizations: two fuzzy-logic-based optimizations, which ensure that maximum energy is extracted from both the WT and the SEIG, respectively, at all operating conditions, and also the optimization of phase current harmonics through adaptive hysteresis control. In addition, a recently developed algorithm for real-time loss calculation of a hysteresis-driven power converter is utilized to quantitatively assess the power converter losses with respect to different hysteresis bandwidth settings. The performance of the proposed control algorithm is experimentally evaluated and compared with two competing algorithms which do not involve current harmonics compensation, whereas one of them also does not involve optimization of the SEIG output power. This enables evaluation of the gain in system performance due to the introduced optimizations. The evaluation and comparison are made over a wide range of wind speeds, both in steady state and under transient conditions, by using a 1.5 kW experimental setup with the DS1103 controller board (dSPACE). •Stand-alone WECS containing an IRFO-controlled SEIG and a battery bank.•Included optimizations of the turbine power, SEIG losses and current harmonics.•Non-model-based optimizations not requiring knowledge of the WECS’s parameters.•Stable and optimal control ensured for wide ranges of wind speed and load.•Superior performance compared to two considered competing algorithms.