As wind power penetration increases, the wind farms are required by newly released grid codes to provide frequency regulation service. The most critical challenge is how to formulate the dynamic model of wind farm for dynamic control, since it is essentially is nonlinear and there are huge amount of parameters to be maintained frequently. This paper proposes a data-driven model predictive control (data-driven MPC) method to make wind farms participate primary frequency regulation. In this method,a specialized dynamic mode decomposition (SDMD) algorithm is developed, which can linearly approximate the dynamics of wind farm from measurements based on Koopman operator theory.Compared with the existing extended dynamic mode decomposition (EDMD) method,this tailored SDMD has two advantages: 1) fully capturing the nonlinear transients of wind turbine dynamics with good accuracy under a wide range of working conditions; 2) much less computational burden with model dimensionality reduction. Based on the recursively updated linear dynamic model, a model predictive control solution is implemented. The simulation results show this model-free solution can dynamically optimize wind turbine generators' active power to track the frequency response requirement from system operator and minimize the rotor speed distortion.
This paper proposes a novel coordinating mechanism between synchronous generators (SGs) and wind turbines (WTs) based on doubly-fed induction generators (DFIGs) for enhanced primary frequency regulation. WTs are urged to participate on frequency regulation, specially if wind power penetration keeps increasing. WTs control support is possible, but it is transient due to the WTs lack of energy storage. This drawback can result in either a further delayed response from the governors of SGs or further frequency decay when WTs support is over. The proposed coordination attempt to tackle this issue.…
This paper studies the frequency response using PV. Multiple control strategies are considered and simulated in the high PV ERCOT model, including inertia control, synthetic governor control, and AGC control. The impact of different parameters in PV inertia control and their correlation and impact on frequency response are analyzed. The simulation results show that PV farm has potential to provide multiple types of grid service to support system frequency. This paper also proposed a distributed fast frequency control approach that can better leverage the PV headroom reserve to improve the syst…
With increased wind power penetration in modern power systems, wind plants are required to provide frequency support similar to conventional plants. However, for the existing frequency regulation scheme of wind turbines, the control gains in the auxiliary frequency controller are difficult to set because of the compromise of the frequency regulation performance and the stable operation of wind turbines, especially when the wind speed remains variable. This paper proposes a novel frequency regulation scheme (FRS) for de-loaded wind turbines. Instead of an auxiliary frequency controller, frequen…
This paper proposes a new strategy for optimal grid frequency regulation (FR) in an interconnected power system where regional ac grids and an offshore wind farm are linked via a multi-terminal high voltage direct-current (MTDC) network. In the proposed strategy, decentralized H-infinity controllers are developed to coordinate the operations of ac synchronous generators and hybrid MTDC converters, thus achieving optimal power sharing of interconnected ac grids and minimizing frequency deviations in each grid. To develop the controllers, robust optimization problems are formulated and solved us…
This paper presents an optimal control strategy for operating a solar hybrid system consisting of solar photovoltaic (PV) and a high-power, low-storage battery energy storage system (BESS). A state-space model of the hybrid PV plant is first derived, based on which an adaptive model predictive controller is designed. The controller's objective is to control the PV and BESS to follow power setpoints sent to the the hybrid system while maintaining desired power reserves and meeting system operational constraints. Furthermore, an extended Kalman filter (EKF) is implemented for estimating the batt…
Contingency Analysis of a Grid of Connected EVs for Primary Frequency Control of an Industrial Microgrid Using Efficient Control Scheme
Manipal Institute of Technology, Manipal Academy of Higher Education（曼尼帕尔理工学院，曼尼帕尔高等教育学院）；BEARS；Universidad Castilla-La Mancha（卡斯蒂利亚-拉曼查大学）；CUNEF Universidad（CUNEF大学）
This work presents a suite of two optimisation models for the short-term scheduling and redispatch of a virtual power plant (VPP) composed of a wind farm and a Li-ion battery, that participates in the day-ahead energy and secondary regulation reserve markets of the Iberian electricity market. First, a two-stage stochastic mixed-integer linear programming model is used to obtain the VPP's generation and reserve schedule and the opportunity cost of the energy stored in the battery. The model has an hourly resolution and a look-ahead period beyond the markets' scheduling horizon and considers the…
Wind turbines are prone to structural degradation, particularly in offshore locations. Based on the structural health condition of the tower, power de-rating strategies can be used to reduce structural loads at the cost of power losses.This paper introduces a novel closed-loop switching control architecture to constrain the thrust in individual turbines. By taking inspiration from developments in the field of reference governors, an existing demanded power tracking controller is extended by a thrust tracking controller. The latter is activated only when a user-defined constraint on fore-aft th…
Optimal Intelligent Control for Wind Turbulence Rejection in WECS Using ANNs and Genetic Fuzzy Approach
Faculty of Electrical and Computer Engineering, Tarbiat Modares University（塔比巴特莫达雷斯大学电气与计算机工程学院）；Department of computer science, Tehran University（德黑兰大学计算机科学系）
