Optimal control of wind farms for fatigue load minimization

Abstract

In this paper, we introduce a distributed control methodology that enables wind generators (WGs) to dynamically dispatch and regulate their power outputs to optimal equilibria in real-time. These equilibria are constructed such that the total mechanical fatigue loads experienced by WGs are minimized and a total assigned power demand is collectively met. We begin by posing the fatigue-load minimization constrained optimal control problem (FLMCOC) as a restricted agreement problem and then propose a fully distributed control methodology for recovering its solution that leverages a particular consensus+innovations algorithm. The distributed algorithm can be realized via any arbitrary peer-to-peer communication network and under any case, it can guarantee dynamic regulation of WGs' power outputs to their optimal values. Collectively, this paper offers a distributed control methodology for attaining a solution to the FLMCOC problem for large-scale wind farms that is computationally efficient, scalable, resilient to single-point communication or agent failures and privacy preserving. The proposed control methodology is validated through numerical simulations on the modified IEEE 24-bus power network.