Search

This paper describes the results of a wave tank test campaign of a 1/49 scaled SATH 10 MW floating platform. The software-in-the-loop (SiL) hybrid method was used to include the wind turbine thrust and the in-plane rotor moments. Experimental results are compared with a numerical model developed in OpenFAST of the floating wind turbine. The tank test campaign was carried out in the scaled model tested at the deep ocean basin from the Lir National Ocean Test Facility at Cork, Ireland. This floating substructure design was adapted by Saitec to support the 10 MW wind turbine within the ARCWIND project (Adaptation and Implementation of Floating Wind Energy Conversion Technology for the Atlantic Region) with the aim of withstanding the environmental conditions of the European Atlantic Area region. CENER provided the wind turbine controller specially designed for the SATH 10 MW configuration. A description of the experimental setup, force actuator configuration and the numeric aerodynamic parameters is provided in this work. The most relevant experimental results under wind and wave loading are shown in time series and frequency domain. The influence of the submerged geometry variations in the pitch natural frequency is discussed. The paper shows the simulation of a case with rated wind speed, where the tilted geometry for the computation of the hydrostatic and hydrodynamic properties of the submerged substructure is considered. This case provides a better agreement of the pitch natural frequency with the experiments than an equivalent simulation using the undisplaced geometry mesh for the computation of the hydrodynamic and hydrostatic properties.

This work demonstrates the feasibility of an individual pitch control strategy based on nacelle yaw misalignment measurements to mitigate the platform yaw drift in upwind floating offshore wind turbines, which is caused by the vertical moment produced by the rotor. This moment acts on the platform yaw degree of freedom, being of great importance in systems that have low yaw stiffness. Among them, single-point-mooring platforms are one of the most important ones. During recent years, several floating wind turbine concepts with single-point-mooring systems have been proposed, which can theoretically dispense with the yaw mechanism due to their ability to rotate and align with environmental conditions (weather-vaning). However, in this paper it is proven that the vertical moment overcomes the orienting ability, causing the yaw drift. With the intention of reducing the induced yaw response of a single-point-mooring floating wind turbine, an individual pitch control strategy based on nacelle yaw misalignment is applied, which introduces a counteracting moment. The control strategy is validated by numerical simulations using the 5 MW National Renewable Energy Laboratory (NREL) wind turbine mounted on a single-point-mooring version of the DeepCwind OC4 floating platform to demonstrate that it can mitigate the yaw drift and therefore maintain the alignment of the wind turbine rotor with the wind.

Wind farm flow control (WFFC) is a topic of interest at several research institutes and industry and certification agencies worldwide. For reliable performance assessment of the technology, the efficiency and the capability of the models applied to WFFC should be carefully evaluated. To address that, the FarmConners consortium has launched a common benchmark for code comparison under controlled operation to demonstrate its potential benefits, such as increased power production. The benchmark builds on available data sets from previous field campaigns, wind tunnel experiments, and high-fidelity simulations. Within that database, four blind tests are defined and 13 participants in total have submitted results for the analysis of single and multiple wakes under WFFC. Here, we present Part I of the FarmConners benchmark results, focusing on the blind tests with large-scale rotors. The observations and/or the model outcomes are evaluated via direct power comparisons at the upstream and downstream turbine(s), as well as the power gain at the wind farm level under wake steering control strategy. Additionally, wake loss reduction is also analysed to support the power performance comparison, where relevant. The majority of the participating models show good agreement with the observations or the reference high-fidelity simulations, especially for lower degrees of upstream misalignment and narrow wake sector. However, the benchmark clearly highlights the importance of the calibration procedure for control-oriented models. The potential effects of limited controlled operation data in calibration are particularly visible via frequent model mismatch for highly deflected wakes, as well as the power loss at the controlled turbine(s). In addition to the flow modelling, the sensitivity of the predicted WFFC benefits to the turbine representation and the implementation of the controller is also underlined. The FarmConners benchmark is the first of its kind to bring a wide variety of data sets, control settings, and model complexities for the (initial) assessment of farm flow control benefits. It forms an important basis for more detailed benchmarks in the future with extended control objectives to assess the true value of WFFC.

Wind farm flow control (WFFC) is a topic of interest at several research institutes, industry and certification agencies world-wide. For reliable performance assessment of the technology, the efficiency and the capability of the models applied to WFFC should be carefully evaluated. To address that, FarmConners consortium has launched a common benchmark for code comparison under controlled operation to demonstrate its potential benefits such as increased power production. The benchmark builds on available data sets from previous field campaigns, wind tunnel experiments and high-fidelity simulations. Within that database, 4 blind tests are defined and 13 participants in total have submitted results for the analysis of single and multiple wake under WFFC. Some participants took part in several blind tests and some participants have implemented several models. The observations and/or the model outcomes are evaluated via direct power comparisons at the upstream and downstream turbine(s), as well as the power gain at the wind farm level under wake steering control strategy. Additionally, wake loss reduction is also analysed to support the power performance comparison, where relevant. Majority of the participating models show good agreement with the observations or the reference high-fidelity simulations, especially for lower degrees of upstream misalignment and narrow wake sector. However, the benchmark clearly highlights the importance of the calibration procedure for control-oriented models. The potential effects of limited controlled operation data in calibration is particularly visible via frequent model mismatch for highly deflected wakes, as well as the power loss at the controlled turbine(s). In addition to the flow modelling, sensitivity of the predicted WFFC benefits to the turbine representation and the implementation of the controller is also underlined. FarmConners benchmark is the first of its kind to bring a wide variety of data sets, control settings and model complexities for the (initial) assessment of farm flow control benefits. It forms an important basis for more detailed benchmarks in the future with extended control objectives to assess the true value of WFFC.

Wind farm control allows coordinated operation of the wind turbines within a wind power plant. However, its development has traditionally been split into the distinct disciplines of power plant control and farm flow control. As variable renewable energies, in particular wind energy, increase their penetration into the power system, grid code requirements become stricter for wind power plants and electricity markets necessarily evolve. In such a context, cross-fertilisation between the two categories of wind farm control, targeting an integrated approach where applicable, becomes a priority. An initial overview on how to further align wind farm flow control to grid and electricity markets participation is provided, including an analysis of capabilities and prospects. Additionally, greater detail is given about an open-access data set serving as market showcases for value demonstration of price-driven operation of wind power plants by means of wind farm flow control.

Careful validation of the modelling and control actions is of vital importance to build confidence in the value of coordinated wind farm control (WFC). The efficiency of flow models applied to WFC should be evaluated to provide reliable assessment of the performance of WFC. In order to achieve that, FarmConners launches a common benchmark for code comparison to demonstrate the potential benefits of WFC, such as increased power production and mitigation of loads. The benchmark builds on available data sets from previous and ongoing campaigns: synthetic data from high-fidelity simulations, measurements from wind tunnel experiments, and field data from a real wind farm. The participating WFC models are first to be calibrated or trained using normal operation periods. For the blind test, both the axial induction and wake steering control approaches are included in the dataset and to be evaluated through the designed test cases. Three main test cases are specified, addressing the impact of WFC on single full wake, single partial wake, and multiple wake. The WFC model outcomes will be compared during the blind test phase, through power gain and wake loss reduction as well as alleviation of wake-added turbulence intensity and structural loads. The probabilistic validation will be based on the median and quartiles of the observations and WFC model predictions. Every benchmark participant will be involved in the final publication, where the comparison of different tools will be performed using the defined test cases. Instructions on how to participate are also provided on farmconners.readthedocs.io.

Currently, wind farms are operated with the primary control objective to maximise power generation. As the penetration of wind energy rises, this strategy may no longer be feasible, especially if government subsidies are reduced. In such a scenario, wind farm flow control (WFFC) can offer wind farm operators additional flexibility to maximise profits. For example, if electricity prices fall operators could curtail power generation in favour of load reduction strategies. To date, the lack of convincing evidence for the economic case for WFFC has prevented its widespread adoption. This paper addresses this by introducing a set of showcases that researchers within the WFFC community can use to assess the positive impact of their control strategies. These showcases are based on the TotalControl Reference Wind Power Plant with weather simulation data and estimated electricity prices for both 2020 and 2030, provided courtesy of the DTU Balancing Tool Chain. With this data, researchers can evaluate the performance of their control algorithms using an internationally recognised tool.

Wind farm control is an active and growing field of research in which the control actions of individual turbines in a farm are coordinated, accounting for inter-turbine aerodynamic interaction, to improve the overall performance of the wind farm and to reduce costs. The primary objectives of wind farm control include increasing power production, reducing turbine loads, and providing electricity grid support services. Additional objectives include improving reliability or reducing external impacts to the environment and communities. In 2019, a European research project (FarmConners) was started with the main goal of providing an overview of the state-of-the-art in wind farm control, identifying consensus of research findings, data sets, and best practices, providing a summary of the main research challenges, and establishing a roadmap on how to address these challenges. Complementary to the FarmConners project, an IEA Wind Topical Expert Meeting (TEM) and two rounds of surveys among experts were performed. From these events we can clearly identify an interest in more public validation campaigns. Additionally, a deeper understanding of the mechanical loads and the uncertainties concerning the effectiveness of wind farm control are considered two major research gaps.

Derating of individual turbines is one of the options to implement wind farm performance optimization, although there are different ways to proceed with such derating at the turbine control level. The present paper develops an option based on the minimal thrust coefficient in accordance with the Cp and C t contour levels. This strategy is compared for the region below rated wind speed with two other strategies where either the pitch or the tip speed ratio are maintained at their maximum C p values from normal operation. The study concludes that maintaining the pitch at the optimal value from normal operation produces poorer performance from the thrust and the loads perspective. Practical implementation issues have also been detected.

In this paper the initial results of the European project CAMINO in terms of the realistic roadmap to counter cyber crime and cyber terrorism are presented. The roadmap is built in accordance to so called CAMINO THOR approach, where cyber security is perceived comprehensively in 4 dimensions: Technical, Human, Organisational, and Regulatory.

This paper presents the application of a robust non-diagonal multivariable control design method, based on the Quantitative Feedback Theory (QFT), to the control of a complex wastewater treatment plant (WWTP) with biological removal of nitrogen and phosphorus. The control objective is to simultaneously regulate the concentration of ammonia, nitrates and phosphorus in the plant effluent. The manipulated variables are the dissolved oxygen (DO) level in the aerobic reactor, the sludge recycling flow from the settler and the amount of ferric hydroxide added to chemically precipitate the phosphorus. Thus, the system becomes a three-input-three-output control structure with model parameter uncertainty. A robust non-diagonal multivariable QFT method is used to design a fully populated matrix controller. This sequential method reduces the interactions between control loops, increases the robust stability and fulfils the robust performance specifications defined by the user. It also considers non-minimum phase aspects by avoiding the introduction of right-half plane transmission zeros due to the controller elements. Simulations carried out by using the IWA ASM2d model under WEST® software validate the proposed control methodology.

A submerged wave energy converter point absorber, which will be further referred to as TWED (Torres Wave Energy Device) has been analyzed and studied under irregular wave conditions. A non-linear time domain numerical model of the TWED floater movement has been implemented in Simulink®. In a previous paper, the numerical model was exploited to test the sensibility of the TWED performance to changes in some variables under regular waves: linear generator damping constant, floater diameter, depth, bearing frictions and vertical drag coefficients. In this paper, the TWED is optimized for maximum energy production in real wave climate. To obtain the average wave performance of the converter, a 44 year series of data record at a point near the Cantabrian Coast has been used. The objective functions have been the Average Absorbed Power, AAP, and the sea-state generator linear damping constant variable, K. After the optimization, the full time series of AAP was obtained and from it, several statistics analysis for AAP and K were carried out for different time intervals (complete series, yearly series, and monthly series) in order to study the variability of K and AAP. In addition, an evaluation of the TWED behavior in a sea state in the Operation Limit has been studied. The studies showed that the instantaneous absorbed power in a sea state could be as much as 20 times higher than the mean absorbed power, while the performance in irregular waves is lower, around 70 % less than that of regular waves.

With extraordinary high priority science objectives to break the current barriers of our knowledge of the universe, and dealing with significant weight limitations of launch vehicle for cost-effective access to space, several NASA and ESA missions will involve both formation flying technology and satellites with large flexible structures in the next few decades: Terrestrial Planet Finder, Stellar and Planet Imager, Life Finder, Darwin and Lisa missions, etc. This chapter deals with the design of multi-input multi-output (MIMO) robust control strategies to regulate simultaneously the position and attitude of a telescope-type spacecraft with large flexible appendages. Section 2 describes the main control challenges and dynamic characteristics of a MIMO system in general, and a spacecraft in particular; Section 3 presents advanced techniques to design MIMO robust controllers based on the quantitative feedback theory (QFT); and Section 4 shows some illustrative results achieved when applying the MIMO QFT control methodology to one of the telescope-type spacecraft (a 6inputs/6-outputs MIMO system) of a multiple formation flying constellation of a European Space Agency (ESA) cornerstone mission (Fig. 1). Control of spacecraft with large flexible structures and very demanding astronomical performance specifications, as the telescope-type satellite mission, involves significant difficulties due to the combination of a large number of flexible modes with small damping, model uncertainty and coupling among the inputs and outputs. The scientific objectives of such missions require very demanding control specifications, as micrometer accuracy for position and milli-arc-second precision for attitude, high disturbance rejection properties, loop-coupling attenuation and low controller complexity and order. The dynamics of such spacecraft usually present a complex 6-inputs/6-outputs MIMO plant, with 36 transfer functions with high order dynamics (50th order models in our example), large model uncertainty and high loop interactions introduced by the flexible modes of the low-stiffness appendages. This chapter presents advanced tools and techniques to analyse and design MIMO robust control systems to regulate simultaneously the position and attitude of telescope-type spacecraft with large flexible appendages.

This paper applies a recent full-matrix multi- input-multi-output QFT controller design methodology to simultaneously regulate nitrogen and phosphorus concentrations in the effluent of a wastewater treatment plant (WWTP) according to environmental standard policies. The robust controller is based on two terms: a non-diagonal pre- compensator for decoupling and a diagonal controller for robust performance and stability. Simulation results show the benefits of the control strategy for WWTP-type complex processes with large channel-interaction and uncertainty.

This paper deals with the design of robust control strategies to govern the position and attitude of a Darwin-type spacecraft with large flexible appendages. The satellite is one of the flyers of a multiple spacecraft constellation for a future ESA mission. It presents a 6×6 high order multiple-input–multiple-output (MIMO) model with large uncertainty and loop interactions introduced by the flexible modes of the low-stiffness appendages. The scientific objectives of the satellite require very demanding control specifications for position and attitude accuracy, high disturbance rejection, loop-coupling attenuation, and low controller order. The paper demonstrates the feasibility of a sequential nondiagonal MIMO quantitative feedback theory (QFT) strategy controlling the Darwin spacecraft and compares the results with H-infinity and sequential diagonal MIMO QFT designs.

The EU and UK have made ambitious commitments to decarbonise their economies by 2050 under the Net Zero plans. For this, offshore wind will play a major role, significantly contributing to a paradigm shift in the power generation and greater volatility of electricity prices. The operating strategy of wind farms should therefore move from a power maximisation to revenue maximisation design. Wind farm flow control (WFFC) is a key enabler for this shift through mitigation of wake effects in the design and operation phases. The results of the FarmConners market showcases presented here are the first attempt to economically assess WFFC strategies with respect to electricity market prices and revenue. Here, we present a conceptual simulation study starting from individual turbine control, and extend it to layouts with 10 and 32 turbines operated with WFFC based on the results of five participants. Each participant belonged to a different research group with their respective simulation environments, flow models and WFFC strategies. Via a comparative analysis of relative WFFC benefits estimated per participant, the implications of wind farm size, the applied control strategy and the overall model fidelity are discussed in zero-subsidy scenarios. For all the participants, it is seen that the income gain can differ significantly from the power gain depending on the electricity price under the same inflow, and a favourable control strategy for dominant wind directions can pay off. However, a strong correlation between income and power gain is also observed for the analysed high electricity prices scenarios underlining the need for additional modelling capabilities to carry out a more comprehensive revenue/value optimisation including lower prices and system requirements driven cases.

This paper introduces a reformulation to design full-matrix Quantitative Feedback Theory (QFT) controllers for multi-input-multi-output (MIMO) plants with model uncertainty. It considers a double-step procedure: an inverse-based decoupling and a consecutive loop-by-loop quantitative robust control design. The method generalizes several previous non-diagonal MIMO QFT techniques, avoiding some required prior hypotheses of such former methods, and simplifies the design procedure. It deals with two classical control problems: reference tracking and disturbance rejection at plant output. The paper ends applying the new technique to the design of a MIMO controller for a spacecraft flying in a formation that is moving with respect to a central body in a circular orbit.