Distributed optimal wind farm control for fatigue load minimization: A consensus approach

Abstract

In this paper, we introduce a distributed approach to optimal control of wind farms (WFs). Our control approach enables wind generators (WGs) to dynamically dispatch and regulate their power outputs to optimal equilibria that result in minimum total fatigue loading and aggregate power output that matches a given reference. The underlying control algorithm requires WGs to only update and exchange minimal local nonsensitive information via an arbitrary peer-to-peer communication network and is characterized by: (a) computationally efficiency, as the computational effort is uniformly distributed among all WGs, (b) resilience with respect to communication network topology variations and, (c) privacy preservation, as WGs only exchange nonsensitive information. We establish convergence of the underlying distributed algorithm under mild conditions in the communication network connectivity and control gains. Finally, we corroborate the effectiveness of the proposed distributed control approach via numerical simulations and show how WGs, by adopting the proposed controllers, can regulate their total power output on demand while ensuring that the harmful fatigue loads that they experience are kept at minimal levels.