Data-Driven Wide-Area Model-Free Adaptive Damping Control With Communication Delays for Wind Farm

Abstract

The strong nonlinearity, time-varying structure, and complex operating conditions in interconnected power systems with the wind farm deteriorate the control performance of wide-area damping control (WADC) designed by conventional model-based methods. In this paper, an improved model-free adaptive control (MFAC), which employs the pseudo-partial derivative (PPD) to linearize the nonlinear power system dynamically, considering WADC requirements and system disturbances is proposed to damp out the inter-area oscillation for wind farm. In addition, to compensate for communication delays in a wide-area measurement system (WAMS), an adaptive delay compensator (ADC) is employed to reimbursed both constant and variable delays. The proposed controller depends only on online I/O data, which avoids the complicated system modeling process and can adapt to variations of system operating conditions and delay scenarios. Moreover, compared to existing MFAC damping approaches, the proposed approach provides additional advantages for wind farm on managing initial values and the stability region of PPD. The communication delays are compensated, which is not considered in other MFAC-based methods. Finally, case studies with various uncertainties and disturbances are conducted to validate the proposed control strategy.