A comparative study of the reliability of the power electronics in grid connected small wind turbine systems

This work presents a reliability analysis of the power conditioning system (PCS) for both the permanent magnet generator (PMG) and wound rotor induction generator (WRIG)-based small wind turbine generation systems. The PCS for grid connection of the PMG-based system requires a rectifier, boost converter and a grid-tie inverter, while the WRIG-based system employs a rectifier, a chopper and an external resistor in the rotor side with the stator directly connected to the grid. Reliability of the PCS is analyzed for the worst case scenario of maximum conversion losses at a predetermined wind speed. The analysis reveals that the mean time between failures (MTBF) of the PCS of a WRIG-based small wind turbine is much higher than the MTBF of the PCS of a PMG-based small wind turbine. The investigation is extended to identify the least reliable component within the PCS for both systems. It is shown that the inverter has the dominant effect on the system reliability for the PMG-based system, while the rectifier is the least reliable for the WRIG-based system. This research indicates that the WRIG-based small wind turbine with a simple PCS is a much better option for small wind energy conversion system

Modeling and control of a small wind turbine

This paper starts with a detailed survey of control methods commonly employed by commercially available small wind turbines. This detailed survey indicates that the most commonly used control method of small wind turbines is horizontal furling method. Such furling mechanism and resulting dynamics are described in the paper. Furling is used to control the aerodynamic power extraction from the wind. A dynamic model of a small wind turbine with furling dynamics is presented in this paper. Such small wind turbines are based on permanent magnet generators and their speed can be regulated using the load control. The extraction of maximum power output from such wind turbines is investigated using tip speed ratio control and hill-climbing control methods. The system is simulated in Matlab/Simulink to determine a suitable control strategy. Two dynamic controllers are designed and simulated. In the first method, a controller uses the wind speed and rotor speed information and controls the load in order to operate the wind turbine at the optimum tip speed ratio. The generator output is observed in varying wind condition as the furl angle increases and decreases. In the second method, a controller compares the output power of the turbine with the previous power and based on the comparison it controls the load. Using a hill-climbing algorithm the controller tries to extract the maximum power from the wind, while the generator output is observed as the furl angle increase or decreases. Finally, the output of these two controllers is compared and investigated to determine which controller leads to the best results

Performance and reliability comparison of grid connected small wind turbine systems

Small wind energy conversion systems are electromechanical devices that generate electricity from wind power for use in commercial as well as residential applications. System level comparison pertaining to such conversion systems is an important and challenging problem and in-depth analysis is essential for high penetration of wind power. A set of unique problems associated with this technology requires that the maximum power point tracking control be achieved through a simple, efficient, and most importantly, highly reliable manner. This research identifies these challenges and subsequently presents a comparison in terms of the performance and reliability of a furling control grid connected Permanent Magnet Generator (PMG) and Wound Rotor Induction Generator (WRIG)-based small wind turbine system. The power conditioning system for grid connection of the PMG-based system requires a rectifier, boost converter and a grid-tie inverter, while the WRIG-based system employs a rectifier, a switch and an external resistance in the rotor side with the stator directly connected to the grid. The proposed research develops the system level mathematical model for the power conditioning system losses that fluctuates with the wind speed. It is found by the simulation that compared to the PMG-based system, the WRIG-based system can provide low power losses at low wind speeds, thus resolving the typical obstacle of variable speed operation. The comparison is further enhanced by investigating the annual energy capture, annual energy loss and efficiency for the wind speed information of eight test sites in Newfoundland and Labrador, Canada: Battle Harbour (BH); Cartwright (CW); Little Bay Island (LB); Mary's Harbour (MH); Nain (NA), Ramea (RA); St. Brendan's (SB); and St. John's (SJ). It is demonstrated that the WRIG-based system yields lower energy loss which results in a system of higher efficiency for a wind speed of 2 m/s (cut-in) to 17 m/s (cut-out). Furthermore, experimental test benches are developed for both systems based on a wind turbine emulator that incorporates furling control and associated dynamics, as well as power conditioning systems required for variable speed operation. The maximum power extraction to the grid for both systems is ensured by tracking the optimum tip speed ratio. The experimental energy production is calculated for the regions considered during simulation. It is found that the WRIG-based system provides 2% more efficiency than the PMG-based system and corresponds well with the simulated conclusion. -- Additionally, the reliability of the power conditioning system for the systems is analyzed at a predetermined wind speed. The analysis reveals that the Mean Time Between Failures (MTBF) of the power conditioning system of the WRIG-based system is much longer than the MTBF of the power conditioning system of the PMG-based system. The investigation is extended to identify the least reliable component within the power conditioning system for both systems. It is shown that the inverter has the dominant effect on the system reliability for the PMG-based system, while the rectifier is the least reliable component for the WRIG-based system. This research finally concludes that the WRIG-based small wind turbine system with a simple power conditioning system is a much better option for a small wind energy conversion system

An isolated small wind turbine emulator

Furling control method is the most commonly used control method by small wind turbine industry to control the aerodynamic power extraction from the wind. In this thesis, a small wind turbine with furling mechanism and its resulting dynamics are modeled on Matlab/Simulink platform. The model is simulated to regulate the speed of the wind turbine via a load control method. Tip-speed ratio and hill climbing control methods for the maximum power extraction are investigated. The wind speed data and Rayleigh distribution of St. John's, Newfoundland, is used to determine the annual energy capture. Satisfactory simulation performance leads to the implementation of an isolated small wind turbine emulator based on a separately excited DC motor to emulate and evaluate the performance of a small wind turbine using different control strategies. The test rig consists of a 3HP separately excited DC motor coupled to a synchronous generator. Wind turbine rotor and furling dynamics are incorporated in the emulator with the use of a PC based wind turbine model. A dump load is connected to the generator through a buck-boost converter controlled by a microcontroller. Emulation of the wind turbine is confirmed by running the DC motor to track the theoretical rotational speed of the wind turbine rotor. A dynamic maximum power controller is implemented and tested. The controller uses the wind speed and rotor speed information to control the duty cycle of the buck-boost converter in order to operate the wind turbine at the optimum tip-speed ratio. Test results indicate that the proposed system accurately emulates the behavior of a small wind turbine system

Energy capture by a small wind-energy conversion system

Furling is the most common method used by the small wind-turbine industry to control the aerodynamic power extraction from the wind. A small wind-turbine with furling mechanism and its resulting dynamics are modelled using Matlab/Simulinkplatform in this paper. The model simulates regulating the speed of the wind-turbine via a load-control method. Tip-speed ratio and hill-climbing control methods for maximum-power extraction from a small wind-turbine are investigated. Two dynamic controllers are designed and their behaviours simulated. In the first method, the controller uses the wind-speed and rotor speed information to control the load in order to operate the wind-turbine at its optimal tip-speed ratio. In the second method, the controller compares the output power of the turbine with the previous power, and controls the load based on the power difference. In order to determine a suitable control strategy for the small wind-energy conversion system, several tests are performed. Wind-speed versus power-curve and annual energy capture of the system for each control method are determined for wind conditions in St. John's, Newfoundland. The annual energy-capture is determined using the bin's power-curve method. Wind-speed data and Rayleigh distribution of St. John's, Newfoundland are used to determine the annual energy-capture. The results of the simulations indicate that the energy capture of a wind-turbine depends not only on the control strategy but on the wind-speed and Rayleigh distribution. The results of the investigation lead to the conclusion that the hill-climbing method of control results in a greater annual energy-output.Wind-turbines Furling control Tip-speed ratio control Hill-climbing control Rayleigh distribution Energy capture

Bayesian estimation and prediction based on Rayleigh sample quantiles

Bayes estimators and predictors, HPD estimators and credibility intervals, Bayes tolerance limits, Reliability and failure rate functions,