Model predictive controllers for reduction of mechanical fatigue in wind farms

We consider the problem of dispatching WindFarm (WF) power demand to individual Wind Turbines (WT) with the goal of minimizing mechanical stresses. We assume wind is strong enough to let each WTs to produce the required power and propose different closed-loop Model Predictive Control (MPC) dispatching algorithms. Similarly to existing approaches based on MPC, our methods do not require changes in WT hardware but only software changes in the SCADA system of the WF. However, differently from previous MPC schemes, we augment the model of a WT with an ARMA predictor of the wind turbulence, which reduces uncertainty in wind predictions over the MPC control horizon. This allows us to develop both stochastic and deterministic MPC algorithms. In order to compare different MPC schemes and demonstrate improvements with respect to classic open-loop schedulers, we performed simulations using the SimWindFarm toolbox for MatLab. We demonstrate that MPC controllers allow to achieve reduction of stresses even in the case of large installations such as the 100-WTs Thanet offshore WF

Model predictive control strategy in waked wind farms for optimal fatigue loads

With the rapid growth of wind power penetration, wind farms (WFs) are required to implement frequency regulation that active power control to track a given power reference. Due to the wake interaction of the wind turbines (WTs), there is more than one solution to distributing power reference among the operating WTs, which can be exploited as an optimization problem for the second goal, such as fatigue load alleviation. In this paper, a closed-loop model predictive controller is developed that minimizes the wind farm tracking errors, the dynamical fatigue load, and and the load equalization. The controller is evaluated in a mediumfidelity model. A 64 WTs simulation case study is used to demonstrate the control performance for different penalty factor settings. The results indicated the WF can alleviate dynamical fatigue load and have no significant impact on power tracking. However, the uneven load distribution in the wind turbine system poses challenges for maintenance. By adding a trade-off between the load equalization and dynamical fatigue load, the load differences between WTs are significantly reduced, while the dynamical fatigue load slightly increases when selecting a proper penalty factor.Comment: Accepted by Electric Power Systems Researc

Resilience in Floating Offshore Wind Turbines: A Scoping Review

Background With climate change a looming global threat, offshore wind energy is a vital resource, and floating offshore wind turbines (FOWT) are essential to capture its full potential. Unfortunately, high operations and maintenance expenses pose an obstacle to widespread implementation of FOWT. Reducing maintenance needs by limiting FOWT damage or failure in harsh environments will undoubtedly contribute to lowering costs and to improving on-site personnel safety. Resilience, an important concept in the field of risk management, may be instrumental in achieving these goals. Objective The objective of this thesis was to develop a thorough understanding of how resilience is understood and its applications to FOWT design and operation. The following issues were of greatest interest: the degree to which FOWT literature addresses resilience, the various interpretations and definitions of resilience that are employed in FOWT research, and how those definitions of resilience are applied to FOWT. These issues and objectives led to the question this thesis sought to answer, in order to map the knowledge and potential gaps in FOWT resilience research: How is resilience understood and applied in the context of FOWT design and operation? Methodology In order to answer this research question, a scoping review was conducted, in which two databases – ScienceDirect and GreenFILE – were searched for sources that discussed resilience with respect to FOWT. In accordance with the JBI scoping review methodology, a search and screening strategy, including search terms and inclusion criteria, was determined in advance. The multi-stage screening process ensured that all relevant sources were included, and the entire process is described in such a way as to be transparent and repeatable. Results Thirteen sources, consisting of twelve articles and one report, were found to meet the inclusion criteria, and these were thematically analyzed in order to investigate the definitions/interpretations and applications of resilience to FOWT technology. Several trends were discovered among the included sources, including a dominant engineering perspective and a glaring lack of explicit resilience definitions. Despite this lack of definitions, however, several interpretations of resilience were found to be used among the thirteen sources, and these are discussed in depth. Furthermore, the various applications of resilience to FOWT were mapped in order to identify popular topics, and these findings were compared to trends noted elsewhere in the literature. Conclusions The results of this review provide valuable insight into the main interpretations of resilience that are used in relation to FOWT. They also provide a solid foundation for future work and for improvements in FOWT resilience research. Among these are the need for a clear definition of resilience in FOWT studies and the potential benefits that could come from the development of a risk management approach to enhance the strong engineering perspective within the field of FOWT resilience research

Model predictive controllers for reduction of mechanical fatigue in wind farms

We consider the problem of dispatching WindFarm (WF) power demand to individual Wind Turbines (WT) with the goal of minimizing mechanical stresses. We assume wind is strong enough to let each WTs to produce the required power and propose different closed-loop Model Predictive Control (MPC) dispatching algorithms. Similarly to existing approaches based on MPC, our methods do not require changes in WT hardware but only software changes in the SCADA system of the WF. However, differently from previous MPC schemes, we augment the model of a WT with an ARMA predictor of the wind turbulence, which reduces uncertainty in wind predictions over the MPC control horizon. This allows us to develop both stochastic and deterministic MPC algorithms. In order to compare different MPC schemes and demonstrate improvements with respect to classic open-loop schedulers, we performed simulations using the SimWindFarm toolbox for MatLab. We demonstrate that MPC controllers allow to achieve reduction of stresses even in the case of large installations such as the 100-WTs Thanet offshore WF