Alhussein Albarbar

Modeling and control for smart grid integration of solar/wind energy conversion system

Performance optimization, system reliability and operational efficiency are key characteristics of smart grid systems. In this paper a novel model of smart grid-connected PV/WT hybrid system is developed. It comprises photovoltaic array, wind turbine, asynchronous (induction) generator, controller and converters. The model is implemented using MATLAB/SIMULINK software package. Perturb and observe (P&O) algorithm is used for maximizing the generated power based on maximum power point tracker (MPPT) implementation. The dynamic behavior of the proposed model is examined under different operating conditions. Solar irradiance, temperature and wind speed data is gathered from a grid connected, 28.8kW solar power system located in central Manchester. Real-time measured parameters are used as inputs for the developed system. The proposed model and its control strategy offer a proper tool for smart grid performance optimization.

Comparison between Wigner–Ville distribution- and empirical mode decomposition vibration-based techniques for helical gearbox monitoring

This article presents a comparison between empirical mode decomposition (EMD) and smoothed pseudo-Wigner–Ville distribution (SPWVD) methods based on vibration signature and energy calculation procedure for monitoring gearbox systems. The simulation and experimental work were carried out using two-stage helical gears for a healthy pair of gears and a pair suffering from a tooth breakage with severity fault 1 (25 per cent tooth removal), fault 2 (50 per cent tooth removal), fault 3 (75 per cent tooth removal), and fault 4 (100 per cent tooth removal) under loads (0, 20, 40, 60, and 80 per cent of the total load) and speeds (10, 30, 50, 70, and 90 per cent of full speed). This article illustrates that the calculation of energy using EMD techniques offers a more effective way to detect early faults than that computations using the SPWVD method, and that the computation of energy using the EMD technique is faster than the calculations done using the SPWVD method.

Maintenance Today and Future Trends

This chapter describes the state of the art in maintenance and its future trends. The key areas that have influenced maintenance in the last 40 years are management of people and assets, and technological capability. These areas are important because they aim to take the best advantage of expensive resources, whether that advantage be profit, or to provide the best possible service with limited resources. The chapter first sets out the current range of maintenance in industrial practice. It is recognised that many businesses do not undertake the full extent of the work reported here, but it is our purpose to survey the state of the art. The chapter then continues to survey the influences of nascent technologies and ideas, before making some predictions about the future. Indeed, some of the most advanced condition-based maintenance effectively aims to predict the future. However, here we do not offer a crystal ball calibrated to international standards; we will constrain ourselves to an informed, independent opinion.

Solar power plant performance evaluation: simulation and experimental validation

In this work the performance of solar power plant is evaluated based on a developed model comprise photovoltaic array, battery storage, controller and converters. The model is implemented using MATLAB/SIMULINK software package. Perturb and observe (PO using hourly average irradiance and cell temperature. It was found that system degradation could be clearly monitored by determining the residual (the difference) between the output power predicted by the model and the actual measured power parameters. It was found that the residual exceeded the healthy threshold, 1.7kW, due to heavy snow in Manchester last winter. More important, the developed performance evaluation technique could be adopted to detect any other reasons that may degrade the performance of the P V panels such as shading and dirt. Repeatability and reliability of the developed system performance were validated during this period. Good agreement was achieved between the theoretical simulation and the real time measurement taken the online grid connected solar power plant.

A More Reliable Method for Monitoring the Condition of Three-Phase Induction Motors Based on Their Vibrations

This paper is concerned with accurate, early, and reliable fault diagnosis using an enhanced vibration measurement technique based on short-time Fourier transform. The novelty of this work lies in detecting very low-phase imbalance-related faults. The energy contained within specified frequency bands centred on the rotor frequency and power supply frequency, and their sideband zones were calculated. The technique was firstly demonstrated by simulated signals and then verified by experimental measurements taken from two different-sized test rigs. The first one comprised a 1.1 kW variable speed three-phase induction motor with varying output load (no load, 25%, 50%, 75%, and 100% load). Two types of common faults were introduced: imbalance in one phase as the electrical fault and misalignment of load as the mechanical fault. The second test rig had a 3 kW three-phase induction motor again with varying load, and here the two seeded faults were: phase imbalance and one broken rotor bar. The measured energy levels in the test conditions were found to be affected by type of fault and fault severity. It is concluded that the proposed method offers a potentially reliable and computationally inexpensive condition monitoring tool which can be implemented with real-time monitoring systems.

An automated tool for solar power systems

In this paper a novel model of smart grid-connected solar power system is developed. The model is implemented using MatLab/SIMULINK software package. Artificial neural network (ANN) algorithm is used for maximizing the generated power based on maximum power point tracker (MPPT) implementation. The dynamic behavior of the proposed model is examined under different operating conditions. Solar irradiance, and temperature data are gathered from a grid connected, 28.8 kW solar power system located in central Manchester. The developed system and its control strategy exhibit excellent performance with tracking efficiency exceed 94.5%. The proposed model and its control strategy offer a proper tool for smart grid performance optimization.

Petroleum Pumps’ Current and Vibration Signatures Analysis Using Wavelet Coherence Technique

Vibration analysis is widely used for rotating machinery diagnostics; however measuring vibration of operational oil well pumps is not possible. The pump’s driver’s current signatures may provide condition-related information without the need for an access to the pump itself. This paper investigates the degree of relationship between the pump’s driver’s current signatures and its induced vibration. This relationship between the driver’s current signatures (DCS) and its vibration signatures (DVS) is studied by calculating magnitude-squared coherence and phase coherence parameters at a certain frequency band using continuous wavelet transform (CWT). The CWT coherence-based technique allows better analysis of temporal evolution of the frequency content of dynamic signals and areas in the time-frequency plane where the two signals exhibit common power or consistent phase behaviour indicating a relationship between the signals. This novel approach is validated by experimental data acquired from 3 kW petroleum pump’s driver. Both vibration and current signatures were acquired under different speed and load conditions. The outcomes of this research suggest the use of DCS analysis as reliable and inexpensive condition monitoring tool, which could be implemented for oil pumps, real-time monitoring associated with condition-based maintenance (CBM) program.

Guide to Modeling and Simulation

In this chapter, a step-by-step guide for simulation and models used in this book is explained. Finite element models using COMSOL and MATLAB/Simulink codes’ writing procedures are outlined in easy to follow points. Those include thermal model of a single switch power module, thermomechanical model of a dual power modules and a single-switch discrete switching devices. Modeling of wind and solar renewable energy systems, using MATLAB/Simulink, with thermal characterisation of the associated power electronic devices are also explained.

Real-time system for monitoring the electro-thermal behaviour of power electronic devices used in boost converters

Abstract Reliability of power electronic devices (PEDs) is a key issue to secure power supplies in modern word, especially, those generated from renewable energy sources. Thermal stress due to switching frequency and environmental conditions are commonest cause of currently unsatisfactory PEDs reliability scores. In this paper, the electro thermal performance of PEDs and related parameters are critically investigated using three types of differently manufactured insulated gate bipolar transistors (IGBTs). Namely, punch through (PT), non-punch through (NPT) and field stop (FS) silicon trench gate technologies. First, currents and voltages of the examined IGBTs were measured under different operating temperatures, switching frequencies and electrical loading conditions. Second, power losses of the examined devices were calculated, in real time, based on their measured currents and voltages using realistic mathematical model embedded in a dSPACE system. Subsequently, the power losses for each device were used as an input to a finite element model to graphically predict heat distributions for each of the monitored devices. Compared to expensive measurements taken by high-resolution thermal imaging cameras, the accuracy of the developed system achieved 97%. The obtained results demonstrate the developed model would serve as an inexpensive and powerful tool for monitoring PEDs thermal conditions.

Novel Approach to Rotating Machinery Diagnostics Based on Principal Component and Residual Matrix Analysis

Rotating machinery such as induction motors and gears driven by shafts are widely used in industry. A variety of techniques have been employed over the past several decades for fault detection and identification in such machinery. However, there is no universally accepted set of practices with comprehensive diagnostic capabilities. This paper presents a new and sensitive approach, to detect faults in rotating machines; based on principal component techniques and residual matrix analysis (PCRMA) of the vibration measured signals. The residual matrix for machinery vibration is extracted using the PCA method, crest factors of this residual matrix is determined and then machinery condition is assessed based on comparing the crest factor amplitude with the base line (healthy) level. PCRMA method has been applied to vibration data sets collected from several kinds of rotating machinery: a wind turbine, a gearbox, and an induction motor. This approach successfully differentiated the signals from healthy system and systems containing gear tooth breakage, cracks in a turbine blade, and phase imbalance in induction motor currents. The achieved results show that the developed method is found very promising and Crest Factors levels were found very sensitive for machinery condition.