Narayana M.,Northumbria University |
Putrus G.A.,Northumbria University |
Jovanovic M.,Northumbria University |
Leung P.S.,Northumbria University |
McDonald S.,New and Renewable Energy Center
Renewable Energy | Year: 2012
The output power of a wind energy conversion system (WECS) is maximized if the wind rotor is driven at an optimal rotational speed for a particular wind speed. To achieve this, a Maximum Power Point Tracking (MPPT) controller is usually used. A successful implementation of the MPPT controller requires knowledge of the turbine dynamics and instantaneous measurements of the wind speed and rotor speed. To obtain the optimal operating point, rotor-generator characteristics should be known and these are different from one system to another. Therefore, there is a need for an efficient universal MPPT controller for WECS to operate without predetermined characteristics. MPPT control of WECSs becomes difficult due to fluctuation of wind speed and wind rotor inertia. This issue is analyzed in the paper, and an Adaptive Filter together with a Fuzzy Logic based MPPT controller suitable for small-scale WECSs is proposed. The proposed controller can be implemented without predetermined WECS characteristics. © 2012 Elsevier Ltd.
Yang W.,New and Renewable Energy Center |
Tavner P.J.,Durham University |
Crabtree C.J.,Durham University |
Wilkinson M.,Garrad Hassan
IEEE Transactions on Industrial Electronics | Year: 2010
Cost-effective wind turbine (WT) condition monitoring assumes more importance as turbine sizes increase and they are placed in more remote locations, for example, offshore. Conventional condition monitoring techniques, such as vibration, lubrication oil, and generator current signal analysis, require the deployment of a variety of sensors and computationally intensive analysis techniques. This paper describes aWTcondition monitoring technique that uses the generator output power and rotational speed to derive a fault detection signal. The detection algorithm uses a continuous-wavelet-transform- based adaptive filter to track the energy in the prescribed time-varying fault-related frequency bands in the power signal. The central frequency of the filter is controlled by the generator speed, and the filter bandwidth is adapted to the speed fluctuation. Using this technique, fault features can be extracted, with low calculation times, from director indirect-drive fixed- or variable-speed WTs. The proposed technique has been validated experimentally on a WT drive train test rig. A synchronous or induction generator was successively installed on the test rig, and both mechanical and electrical faultlike perturbations were successfully detected when applied to the test rig. Copyright © 2010 IEEE.
Bailey H.,University of Edinburgh |
Crozier R.C.,University of Edinburgh |
McDonald A.,University of Edinburgh |
Mueller M.A.,University of Edinburgh |
And 2 more authors.
IECON Proceedings (Industrial Electronics Conference) | Year: 2010
A coupled electromechanical and hydrodynamic simulation of a novel generator connected to a heaving buoy for wave energy conversion has been developed. The simulation is based primarily in MATLAB using its built-in Ordinary Differential Equation (ODE) solvers. These solvers have acted on the data derived from an electromagnetic finite element analysis and from the WAMIT wave interaction simulation software, to simulate the full system in the time domain. © 2010 IEEE.
Bentley E.C.,Northumbria University |
Putrus G.A.,Northumbria University |
McDonald S.,New and Renewable Energy Center |
Minns P.,Northumbria University
IET Generation, Transmission and Distribution | Year: 2010
Power quality (PQ) is becoming increasingly important owing to the increasing use of power electronic devices, coupled with the increasing penetration of loads, which are sensitive to voltage disturbances. As a result of the problems caused by the confluence of these two trends, there is an increasing need for PQ to be monitored in order to diagnose its nature and locate the source of the disturbance, allowing remedial measures to be taken. While automated systems for diagnosis of PQ events have been developed, identifying the location of the source of a disturbance is a problem, which has not been fully addressed to date; in particular the question of locating a non-stationary disturbance. In this study, a novel approach to identify the location of the source of a PQ disturbance is described, using a form of artificial neural network known as a self-organising map. The proposed technique is verified via simulation of the IEEE 14-bus model in PSCAD and an experimental system based on the IEEE 6-bus model. This approach provides a mean of locating the source of PQ events, including transient disturbances. © 2010 The Institution of Engineering and Technology.