Multi-Objective Control Strategies and Prognostic-Based Lifetime Extension of Utility-Scale Wind Turbines

Windenergie wird zunehmend als erneuerbare Energiequellen attraktiv, da Wind nachhaltig genutzt werden kann. In vielen Ländern gibt es umfangreiche Anstrengungen, die Produktion von elektrischer Energie aus Wind zu steigern. Im Vergleich zu anderen erneuerbaren Energiequellen wie Sonne, Gezeiten, Wasserkraft o.ä. ist die Energiegewinnung aus Wind technologisch ausgereifter. Daher ist die Energiegewinnung aus Wind stärker gewachsen ist als andere Technologien. Windkraft verursacht weniger nachteilige Auswirkungen auf die Umwelt als konventionelle Energiequellen. Aufgrund der vergleichsweise hohen Investitions-, Betriebs- und Wartungskosten sind trotz einer weltweit starken Verbreitung von Windenergieanlagen die Produktionskosten von Windenergie im Vergleich mit anderen alternativen Energiequellen hoch. Um die wachsende Nachfrage nachWindkraft zu befriedigen, werdenWindkraftanlagen in Größe und Leistung zunehmend skaliert. Bei zunehmender Größe dominieren die strukturellen Lasten der Turbine. Dies führt vermehrt zu Materialermüdung und Ausfällen. Ein weiterer Schwerpunkt in der Entwicklung von Windtechologie ist die Forderung nach Senkung der Produktionskosten, um einen Wettbewerbsvorteil gegenüber anderen alternativen Energiequellen zu schaffen. Im Bereich der Steuerung können niedrigere Produktionskosten durch den Betrieb der Windturbine am/oder in der Nähe der optimalen Energieeffizienz im Teillastbetrieb erreicht werden. Dies erhöht die Zuverlässigkeit durch Verringerung des Verschleißes und die erzeugte Nennleistung auf ihrem Nennwert im hohen Windregime. Häufig ist es schwierig, einen Steueralgorithmus zu realisieren, der sowohl Effizienz als auch Zuverlässigkeit gewährleistet, da diese beiden Ziele widersprechen. In dieser Arbeit werden Mehrzielsteuerungsstrategien sowohl für den Teillastbereich als auch für hohe Windgeschwindigkeits bereiche vorgestellt. Im Bereich geringer Windgeschwindigkeiten ist eine Steuerungsstrategie so zu konzipieren, dass die Stromerzeugung sowie die strukturelle Belastung im Sinne einer Balance zwischen maximalen Stromproduktion und verlängerter Lebensdauer der Windturbine optimal ist. Für den Bereich hoher Windgeschwindigkeiten wird ein multivariates Steuerungsverfahren vorgeschlagen, um das Verhältnis von Leistung/Geschwindigkeit und struktureller Lastreduzierung zu optimieren. Es wird ein Regler zur Einzelblattverstellung entworfen, um sowohl die unausgewogene Strukturlasten als auch durch die Variation des Windgeschwindigkeit verursachte Rotorscheibe, vertikale Windscherung und Gierversatz fehler zu reduzieren. Um die Zuverlässigkeit derWindturbine zu gewährleisten, ist ein Online-Schadensbewertungsmodell in den Hauptwindturbinenregelkreis integriert, so dass die Windturbine entsprechend ihres aktuellen Verschleißzustandes betrieben wird. In Abhängigkeit von der akkumulierten Schadenshöhe werden Regler zur Einzelblattverstellung mit unterschiedlichen Lastreduktionen und Kompromissen bei der Stromerzeugung eingesetzt, um zwischen den beiden Zielen verlängerte Lebensdauer und Leistungsregelung einen geeigneten Kompromiss zu erzielten. Aufgrund der Herausforderungen die mit Offshore-Windpark Standorten verbunden sind, ist diese Art von prognose-basierter Regelung im Windturbinenbetrieb vor allem im Offshore-Einsatz vorteilhaft. Insbesondere im Kontext output-basierter Vertragsformen z.B. power purchase agreement (PPA) kann dieser Ansatz zur Optimierung der Wartungsplanung genutzt werden. Die Ergebnisse zeigen, dass die vorgeschlagenen Strategien die Auflast auf Windturbinen reduzieren kann ohne sich auf andere Ziele wie die Leistungsoptimierung und Leistung/Drehzahlregelung auszuwirken. Es konnte außerdem gezeigt werden, dass eine prognostisch basierte Steuerung effektiv die Lebensdauer von Windenergieanalagen verlängern kann, ohne das Ziel der Leistungsregelung einzuschränken.Wind energy is one of the rapidly growing renewable sources of energy due to the fact that wind is abundantly available and unlikely to be exhausted like fossil fuel. Additionally, there are deliberate effort to sensitize many countries to develop polices that support production of electrical power from wind. Maturity of wind energy technology has made power production from wind grow significantly compared to other renewable energy sources such as solar, tidal, hydro among others. Like many other renewable energy sources, production of power from wind has less adverse effects on the environment. Despite the growth of global cumulative installed wind capacity, its cost of production is still higher compared to other alternative energy sources due to high initial investment cost and high operation and maintenance (O&M) costs. To meet the growing demand of wind power, wind turbines are being scaled up both in size and power rating. However, as the size increases, the structural loads of the turbine become more dominant, causing increased fatigue stress on the turbine components and consequent loss of functionality before the end of lifetime. Another area of focus in wind power production is lowering its production cost; hence, making it more competitive compared to other alternative power sources. From the control point of view, low production cost of wind energy can be achieved by operating wind turbine at/or near the optimum power efficiency during partial load regime, regulating generated power to its rated value in the high wind regime as well as mitigating structural loads so as to guarantee extended lifetime. Often, it is difficult to realize a control algorithm that can effectively guarantee both efficiency and reliability because these two aspects involve conflicting objective. Therefore, it is important to optimize the trade-off between these competing control objectives. In this thesis, multi-objective control strategies for both the partial load region and high wind speed region are presented. During low wind speed, a control strategy that optimizes power production as well as mitigating structural load is designed to balance between power production maximization and extended lifetime of wind turbine. On the other hand, a multivariate control method to balance between power/speed regulation and structural load reduction is proposed for high wind speed region. More specifically, an individual blade pitch controller is designed to eliminate the unbalanced deterministic structural loads across rotor disc caused by variation in wind speed, vertical wind shear, and yaw misalignment error. To guarantee reliability in wind turbine, an online damage evaluation model is also integrated into the main wind turbine control loop such that wind turbine is operated accordance to its structural health status in order to tolerate fault or to extend its service lifetime by a given period of time. Depending on the accumulated damage level, individual pitch controllers with different degrees of load reduction and power production compromise are employed to balance between extended lifetime and power regulation objective. This kind of prognostic-based control is useful in wind turbine operation, especially in offshore application due to challenges associated with offshore wind farm sites. Additionally, in wind farms that are managed through output-based contracts such as power purchase agreement (PPA), this approach can be utilized to optimize maintenance scheduling to avoid unscheduled downtime. The results demonstrated that the proposed multi-objective control strategies can reduce structural load on wind turbine without adversely affecting other objectives of power optimization and power/speed regulation. It has also be shown that a prognostic-based control can be effectively used to extend the lifetime of wind turbine without sacrificing the objective of power regulation

Robust Active Disturbance Rejection Control Approach to Maximize Energy Capture in Variable-Speed Wind Turbines

This paper proposes an alternative robust observer-based linear control technique to maximize energy capture in a 4.8 MW horizontal-axis variable-speed wind turbine. The proposed strategy uses a generalized proportional integral (GPI) observer to reconstruct the aerodynamic torque in order to obtain a generator speed optimal trajectory. Then, a robust GPI observer-based controller supported by an active disturbance rejection (ADR) approach allows asymptotic tracking of the generator speed optimal trajectory. The proposed methodology controls the power coefficient, via the generator angular speed, towards an optimum point at which power coefficient is maximum. Several simulations (including an actuator fault) are performed on a 4.8 MW wind turbine benchmark model in order to validate the proposed control strategy and to compare it to a classical controller. Simulation and validation results show that the proposed control strategy is effective in terms of power capture and robustness

Load mitigation of a class of 5-MW wind turbine with RBF neural network based fractional-order PID controller

Copyright © 2019 ISA. All rights reserved.Peer reviewedPostprin

Control of Next Generation Aircraft and Wind Turbines

The first part of this talk will describe some of the exciting new next generation aircraft that NASA is proposing for the future. These aircraft are being designed to reduce aircraft fuel consumption and environmental impact. Reducing the aircraft weight is one approach that will be used to achieve these goals. A new control framework will be presented that enables lighter, more flexible aircraft to maintain aircraft handling qualities, while preventing the aircraft from exceeding structural load limits. The second part of the talk will give an overview of utility-scale wind turbines and their control. Results of collaboration with Dr. Balas will be presented, including new theory to adaptively control the turbine in the presence of structural modes, with the focus on the application of this theory to a high-fidelity simulation of a wind turbine

Power regulation and load mitigation of floating wind turbines via reinforcement learning

Floating offshore wind turbines (FOWTs) are often subjected to heavy structural loads due to challenging operating conditions, which can negatively impact power generation and lead to structural fatigue. This paper proposes a novel reinforcement learning (RL)-based control scheme to address this issue. It combines individual pitch control (IPC) and collective pitch control (CPC) to balance two key objectives: load reduction and power regulation. Specifically, a novel incremental model-based dual heuristic programming (IDHP) strategy is developed as the IPC solution to reduce structural loads. It integrates the online-learned FOWT dynamics into the dual heuristic programming process, making the entire control scheme data-driven and free from dependence on analytical models. Furthermore, the proposed method differs from existing IDHP methods in that only partial system dynamics need to be learned, resulting in a simplified design structure and improved training efficiency. Tests using a high-fidelity FOWT simulator demonstrate the effectiveness of the proposed method

A MIMO periodic ARX identification algorithm for the Floquet stability analysis of wind turbines

The paper presents a new stability analysis approach applicable to wind turbines. At first, a reduced order periodic model is identified from response time histories, and then stability is assessed using Floquet theory. The innovation of the proposed approach is in the ability of the algorithm to simultaneously consider multiple response time histories, for example in the form of measurements recorded both on the rotor and in the stand still system. As each different measurement carries a different informational content on the system, the simultaneous use of all available signals improves the quality and robustness of the analysis

Experimental Issues in Testing a Semiactive Technique to Control Earthquake Induced Vibration

This work focuses on the issues to deal with when approaching experimental testing of structures equipped with semiactive control (SA) systems. It starts from practical experience authors gained in a recent wide campaign on a large scale steel frame structure provided with a control system based on magnetorheological dampers. The latter are special devices able to achieve a wide range of physical behaviours using low-power electrical currents. Experimental activities involving the use of controllable devices require special attention in solving specific aspects that characterize each of the three phases of the SA control loop: acquisition, processing, and command. Most of them are uncommon to any other type of structural testing. This paper emphasizes the importance of the experimental assessment of SA systems and shows how many problematic issues likely to happen in real applications are also present when testing these systems experimentally. This paper highlights several problematic aspects and illustrates how they can be addressed in order to achieve a more realistic evaluation of the effectiveness of SA control solutions. Undesired and unavoidable effects like delays and control malfunction are also remarked. A discussion on the way to reduce their incidence is also offered