Multi-mode control strategy for a stand-alone wind energy conversion system with battery energy storage. (July 2022) - Watil, Aziz; El Magri, Abdelmounime; Lajouad, Rachid; Raihani, Abdelhadi; Giri, Fouad
Abstract: This work addresses the problem of controlling a stand-alone wind energy conversion system with battery energy storage. The study target consists of a series association of a permanent magnet synchronous aero-generator, an uncontrolled rectifier, a Zeta converter, a Li-ion battery, and a DC load. It is well-known that the intermittent nature of wind power, as well as the frequent variations in load demand, decreases battery lifetime and reduces its charging performance. To overcome these drawbacks, a battery charge controller is required to instantaneously balance the wind turbine power flow delivered to the DC load and the battery, so that the wind turbine power is properly utilized and the battery is suitably charged. Precisely, depending on the available wind power, the battery state of charge (SOC), and DC load demand, three charging modes are adapted, namely, maximum power point tracking (MPPT) charging mode, constant current (CC) charging mode, and constant voltage (CV) charging mode. Afterward, to ensure the safety of the battery a new battery energy management algorithm is designed to operate the system in one of the three aforementioned modes, taking into account the weather conditions and load demand variations. Interestingly, no wind speed or battery soc. sensors are required for the implementation of the control system. Therefore, a nonlinear adaptive is also developed to provide the online estimation of the battery SOC required for the management algorithm. The performances of the studied system are tested through a semi-experimental platform involving a Processor-in-the-Loop (PIL) under the embedded board eZdsp TMS320F28335. The obtained simulation results prove that the proposed controller meets its objectives with high performances. Highlights: A multi-mode nonlinear control strategy for a stand-alone system is proposed. Three operating battery charging modes are considered. No wind speed and battery SOC sensors are required for the implementation of control system. A nonlinear observer is employed for the online estimation of the battery state of charge. A new battery management algorithm is designed to ensure an adequate charging mode. Semi-experimental tests under the embedded board eZdsp TMS320F28335 are performed to validate the performances of the control strategy.