Mohsen Soltani

Estimation of Rotor Effective Wind Speed: A Comparison

Modern wind turbine controllers use wind speed information to improve power production and reduce loads on the turbine components. The turbine top wind speed measurement is unfortunately imprecise and not a good representative of the rotor effective wind speed. Consequently, many different model-based algorithms have been proposed that are able to estimate the wind speed using common turbine measurements. In this paper, we present a concise yet comprehensive analysis and comparison of these techniques, reviewing their advantages and drawbacks. We implement these techniques and compare the results on both aero-servo-elastic turbine simulations and real turbine field experiments in different wind scenarios.

Load reduction of wind turbines using receding horizon control

Large scale wind turbines are lightly damped mechanical structures driven by wind that is constantly fluctuating. In this paper, we address the design of a model-based receding horizon control scheme to reduce the structural loads in the transmission system and the tower, as well as provide constant (or at least smooth) power generation. Our controller incorporates two optimization problems: one to predict or estimate mean wind speed, given LIDAR data, and the other to carry out receding horizon control to choose the control inputs. The method is verified against an existing wind turbine control system, and shows reductions in both extreme loads and power fluctuations by 80% and 90% respectively when compared to a conventional controller.

Optimized Placement of Wind Turbines in Large-Scale Offshore Wind Farm Using Particle Swarm Optimization Algorithm

With the increasing size of wind farms, the impact of the wake effect on wind farm energy yields become more and more evident. The arrangement of locations of the wind turbines (WTs) will influence the capital investment and contribute to the wake losses, which incur the reduction of energy production. As a consequence, the optimized placement of the WTs may be done by considering the wake effect as well as the components cost within the wind farm. In this paper, a mathematical model which includes the variation of both wind direction and wake deficit is proposed. The problem is formulated by using levelized production cost (LPC) as the objective function. The optimization procedure is performed by a particle swarm optimization (PSO) algorithm with the purpose of maximizing the energy yields while minimizing the total investment. The simulation results indicate that the proposed method is effective to find the optimized layout, which minimizes the LPC. The optimization procedure is applicable for optimized placement of WTs within wind farms and extendible for different wind conditions and capacity of wind farms.

Sliding Mode Control of PMSG Wind Turbine Based on Enhanced Exponential Reaching Law

This paper proposes a sliding-mode control (SMC)-based scheme for the variable-speed direct-driven wind energy conversion systems (WECS) equipped with a permanent magnet synchronous generator connected to the grid. In this paper, diode rectifier, boost converter, neutral point clamped inverter, and L filter are used as the interface between the wind turbine and grid. This topology has abundant features such as simplicity for low- and medium-power wind turbine applications. It is also less costly than back-to-back two-level converters in medium-power applications. The SMC approach demonstrates great performance in complicated nonlinear systems control such as WECS. The proposed control strategy modifies reaching law (RL) of the sliding mode technique to reduce chattering issue and to improve total harmonic distortion property compared to conventional RL SMC. The effectiveness of the proposed control strategy is explored by simulation study on a 4-kW wind turbine, and then verified by experimental tests for a 2-kW setup.

Reliable Control of Ship-Mounted Satellite Tracking Antenna

Motorized antenna is a key element in overseas satellite telecommunication. The control system directs the on-board antenna toward a chosen satellite while the high sea waves disturb the antenna. Certain faults (communication system malfunction or signal blocking) cause interruption in the communication connection resulting in loss of the tracking functionality, and instability of the antenna. In this brief, a fault tolerant control (FTC) system is proposed for the satellite tracking antenna. The FTC system maintains the tracking functionality by employing proper control strategy. A robust fault diagnosis system is designed to supervise the FTC system. The employed fault diagnosis solution is able to estimate the faults for a class of nonlinear systems acting under external disturbances. Effectiveness of the method is verified through implementation and test on an antenna system.

A Reactive Power Dispatch Strategy With Loss Minimization for a DFIG-Based Wind Farm

An optimal reactive power dispatch strategy is proposed to minimize the total electrical losses of a wind farm (WF), including not only losses in the transmission cables and wind turbine (WT) transformers, but also losses inside wind energy generation systems. The reactive power dispatch inside a WT uses optimal splitting strategy over the stator and the grid side converter (GSC), which aims to minimize the total loss of the wind energy generation system, including the generator, the converters, and the filters. Optimization problems are formulated based on established loss models and WT reactive power limits. A WF is carefully designed and used for case studies. Wake effect is considered when calculating the active power at each WT. The total losses of the WF are calculated by implementing the proposed strategy at different wind speeds and reactive power references. The simulation results show the effectiveness of the proposed strategy.

Model predictive control of wind turbines using uncertain LIDAR measurements

The problem of Model predictive control (MPC) of wind turbines using uncertain LIDAR (LIght Detection And Ranging) measurements is considered. A nonlinear dynamical model of the wind turbine is obtained. We linearize the obtained nonlinear model for different operating points, which are determined by the effective wind speed on the rotor disc. We take the wind speed as a scheduling variable. The wind speed is measurable ahead of the turbine using LIDARs, therefore, the scheduling variable is known for the entire prediction horizon. By taking the advantage of having future values of the scheduling variable, we simplify state prediction for the MPC. Consequently, the control problem of the nonlinear system is simplified into a quadratic programming. We consider uncertainty in the wind propagation time, which is the traveling time of wind from the LIDAR measurement point to the rotor. An algorithm based on wind speed estimation and measurements from the LIDAR is devised to find an estimate of the delay and compensate for it before it is used in the controller. Comparisons between the MPC with error compensation, the MPC without error compensation and an MPC with re-linearization at each sample point based on wind speed estimation are given. It is shown that with appropriate signal processing techniques, LIDAR measurements improve the performance of the wind turbine controller.

Active power dispatch method for a wind farm central controller considering wake effect

With the increasing integration of the wind power into the power system, wind farm are required to be controlled as a single unit and have all the same control tasks as conventional power plants. The wind farm central controller receives control orders from Transmission System Operator (TSO), then dispatch the wind power reference to each wind turbine. One of the most commonly used dispatch methods is to dispatch the wind power reference to each wind turbine proportional to each wind turbines available wind power without the consideration of the wake effect. The wake which depends on the thrust efficient of upstream wind turbines in the wind farm influences the downstream wind speed which determines the available wind power of the downstream wind turbine. Optimize the wind power production of each wind turbine in the wind farm by the optimization of the pitch angle and tip-speed-ratio of each turbine can increase the total available wind power of the wind farm. This paper proposed a new dispatch method which dispatches the wind power reference to each wind turbine proportional to each wind turbines optimal wind power to increase the available wind power of the whole wind farm. Particle Swarm Optimization (PSO) is used to obtain the optimal wind power for each wind turbine. A case study is carried out. The available wind power of the wind farm was compared between the traditional dispatch method and the proposed dispatch method with the consideration of the wake effect.

Preview-based asymmetric load reduction of wind turbines

Fatigue loads on wind turbines caused by an asymmetric wind field become an increasing concern when the scale of wind turbines increases. This paper presents a model based predictive approach to reduce asymmetric loads by using Light Detection And Ranging (LIDAR) measurements. The Model Predictive Controller (MPC) developed is based on a model with individual blade pitching to utilize the LIDAR measurements. The MPC must also maintain a given power reference while satisfying a set of actuator constraints. The designed controller was tested on a 5 MW wind turbine in the FAST simulator and compared to the same controller without LIDAR data. The results showed that the MPC with LIDAR was able to reduce the asymmetric loads compared to the MPC without LIDAR while still maintaining the power reference.

Model based active power control of a wind turbine

In recent decades there has been increasing interest in green energies, of which wind energy is one of the most important. Wind turbines are the most common wind energy conversion systems and are hoped to be able to compete with traditional power plants in near future. This demands better technology to increase competitiveness of the wind power plants. One way to increase competitiveness of wind power plants is to offer grid services (also called ancillary services) that are normally offered by traditional power plants. One of the ancillary services is called reserve power. There are instants in the electricity market that selling the reserve power is more profitable than producing with the full capacity. Therefore wind turbines can be down-regulated and sell the differential capacity as the reserve power. In this paper we suggest a model based approach to control wind turbines for active power reference tracking. We use model predictive control (MPC) as our control method. We compare three different control strategies, namely Max-Ω, Constant-Ω and Constant-λ and discuss their drawbacks and benefits by presenting analysis of the steady state operating points and simulations on a high fidelity wind turbine model.