Related papers: Closed-loop model-predictive wind farm flow contro…
This paper proposes a data-driven algorithm for model order reduction (MOR) of large-scale wind farms and studies the effects that the obtained reduced-order model (ROM) has when this is integrated into the power grid. With respect to…
Wind power forecasting (WPF), as a significant research topic within renewable energy, plays a crucial role in enhancing the security, stability, and economic operation of power grids. However, due to the high stochasticity of…
This paper proposes a novel wind power smoothing control paradigm in context of performance-based regulation service. Conventional methods aim at adjusting wind power output using hard-coded filtering algorithms that can result in visually…
A new framework is developed for control of constrained nonlinear systems with structured parametric uncertainties. Forward invariance of a safe set is achieved through online parameter adaptation and data-driven model estimation. The new…
Hydropower is an important source of renewable energy that provides clean energy. Pump-turbine type hydraulic turbine is widely used to mitigate the intermittent energy demand and store a large-scale energy. Pump-turbine operates in reverse…
We present an estimator-based control design procedure for flow control, using reduced-order models of the governing equations, linearized about a possibly unstable steady state. The reduced models are obtained using an approximate balanced…
This study explores the effectiveness of predictive maintenance models and the optimization of intelligent Operation and Maintenance (O&M) systems in improving wind power generation efficiency. Through qualitative research, structured…
This paper introduces a new methodology for designing and optimizing the performance of hydraulic Cross-Flow turbines for a wide range of operating conditions. The methodology is based on a one-step approach for the system-level design…
This paper implements a recently developed social hierarchy-based distributed economic model predictive control (DEMPC) algorithm in floating offshore wind farms for the purpose of power maximization. The controller achieves this objective…
Power loss mechanisms in large wind farms are complex due to the multiscale nature of wind farm aerodynamics. Recent studies based on the two-scale momentum theory have brought new insights into this field; however, most of them have been…
Controlling nonlinear dynamical systems remains a central challenge in a wide range of applications, particularly when accurate first-principle models are unavailable. Data-driven approaches offer a promising alternative by designing…
A learning method is proposed for Koopman operator-based models with the goal of improving closed-loop control behavior. A neural network-based approach is used to discover a space of observables in which nonlinear dynamics is linearly…
Modern wind turbines gather a wealth of data with Supervisory Control And Data Acquisition (SCADA) systems. We study the short-term mutual dependencies of a variety of observables by evaluating Pearson correlation matrices on a moving time…
This paper addresses the problem of predicting a wind farm's power generation when no or few statistical data is available. The study is based on a time-series wind speed model and on a simple dynamic model of a DFIG wind turbine including…
Wind farm layout optimization (WFLO) seeks to alleviate the wake loss and maximize wind farm power output efficiency, and is a crucial process in the design of wind energy projects.Since the optimization algorithms typically require…
Low-fidelity analytical models of turbine wakes have traditionally been used for wind farm planning, performance evaluation, and demonstrating the utility of advanced control algorithms in increasing the annual energy production. In…
The trend towards larger wind turbines and remote locations of wind farms fuels the demand for automated condition monitoring strategies that can reduce the operating cost and avoid unplanned downtime. Normal behaviour modelling has been…
The growing focus on reducing energy consumption, particularly in electric vehicles with limited autonomy, has prompted innovative solutions. In this context, we propose a real-time flap-based control system aimed at improving aerodynamic…
This paper addresses the distributed optimal frequency control of power systems considering a network-preserving model with nonlinear power flows and excitation voltage dynamics. Salient features of the proposed distributed control strategy…
In this paper, disturbance reconstruction and robust trajectory tracking control of biped robots with hybrid dynamics in the port-Hamiltonian form is investigated. A new type of Hamiltonian function is introduced, which ensures the…