FarmConners market showcase results: wind farm flow control considering electricity prices

The EU and UK have made ambitious commitments under the net-zero plans to decarbonise their economies by 2050. 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 power maximisation to profit maximisation which includes income from providing power system services and the reduction of maintenance costs. 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. 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 even for low electricity prices. However, a strong correlation between income and power gain is also observed for the analysed high-electricity-price scenarios, underlining the need for additional modelling capabilities to carry out a more comprehensive value optimisation including lower prices and system requirements driven cases.FarmConners market showcase results: wind farm flow control considering electricity pricespublishedVersio

Sensitivity analysis and Bayesian calibration of a dynamic wind farm control model: FLORIDyn

FLORIDyn is a parametric control-oriented dynamic model suitable to predict the dynamic wake interactions between wind turbines in a wind farm. In order to improve the accuracy of FLORIDyn, this study proposes to calibrate the tuning parameters present in the model by employing a probabilistic setting using the UQ4WIND framework. The strategy relies on constructing a surrogate model (based on polynomial chaos expansion), which is then used to perform both global sensitivity analysis and Bayesian calibration. For our analysis, a nine wind turbine configuration in a yawed setting constitutes the test case. The results of sensitivity analysis offer valuable insight into the time-dependent influence of the model parameters onto the model output. The model parameter tied to the turbine efficiency appear to be the most sensitive parameter affecting the model output. The calibrated FLORIDyn model using the Bayesian approach yield predictions much closer to the measurement data, which is equipped with an uncertainty estimate.Team Jan-Willem van Wingerde

Towards integrated wind farm control: Interfacing farm flow and power plant controls

Concepts for control of wind farms (WFs) can be clustered into two distinct concepts, namely, wind power plant control (WPPC) and wind farm flow control (WFFC). WPPC is concerned with the connection to the power system, compliance with grid codes, and provision of power system services. This comprises the traditional way of operating a WF without consideration of aerodynamic turbine interaction. However, flow phenomena like wake effects can have a large impact on the overall performance of the WF. WFFC considers such aerodynamic phenomena in the WF operation. It can be viewed as a new feature that shall be integrated with the existing control functions. The interaction of these different control concepts is discussed in this article, leading to an identification of the challenges whose solutions will contribute to a successful integration of electrical system and aerodynamic aspects of WF control

Expert Elicitation on Wind Farm Control

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 researc

Towards integrated wind farm control: Interfacing farm flow and power plant controls

Concepts for control of wind farms (WFs) can be clustered into two distinct concepts, namely, wind power plant control (WPPC) and wind farm flow control (WFFC). WPPC is concerned with the connection to the power system, compliance with grid codes, and provision of power system services. This comprises the traditional way of operating a WF without consideration of aerodynamic turbine interaction. However, flow phenomena like wake effects can have a large impact on the overall performance of the WF. WFFC considers such aerodynamic phenomena in the WF operation. It can be viewed as a new feature that shall be integrated with the existing control functions. The interaction of these different control concepts is discussed in this article, leading to an identification of the challenges whose solutions will contribute to a successful integration of electrical system and aerodynamic aspects of WF control.Towards integrated wind farm control: Interfacing farm flow and power plant controlspublishedVersio

Launch of the FarmConners Wind Farm Control benchmark for code comparison

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.Team Jan-Willem van Wingerde