Hamed H. H. Aly

State of the art for tidal currents electric energy resources

Renewable energy is an effective and clean source of supplying electrical loads especially in remote and rural areas. In this paper we discuss tidal in-stream energy as it relies on the same technologies developed from offshore wind turbines for generating electricity at offshore sites. In particular, we survey the tidal in-stream technologies, challenging issues, various types of generators, their dynamic modeling, grid integration performance, and finally the new research issues.

An overview of offshore wind electric energy resources

In this paper we review offshore wind energy for generating electricity at off-shore sites. In particular, we survey the impacts of offshore wind integration into the grid, various types of generators and their dynamic modeling, fault ride-through techniques used to improve generator and grid integration performance, the aggregated wind turbines modeling and finally highlight some stability and control issues.

A Proposed ANN and FLSM Hybrid Model for Tidal Current Magnitude and Direction Forecasting

The paper proposes a hybrid model of an artificial neural network (ANN) and Fourier series model based on the least squares method (FLSM) for monthly forecasting of tidal current magnitude and direction. The proposed hybrid model is highly accurate and outperforms either of the ANN or the FLSM applied alone. This study was done using data collected from the Bay of Fundy, NS, Canada, in 2008.

An overview of inverter topologies for photovoltaic electrical energy

This paper presents a general overview of photovoltaic power generation technology, the development of associated technologies and components, PV infrastructure, and, why there is now significant attention to PV systems. The paper explores current research and proposed topologies and their similarities and differences are discussed as well as the advantages and limitations of each design topology. A review of current research aims atidentifying where the industry is headed in terms of technological advances in the manufacture of inverter. This paper also shows that PV inverter technology is improving by leaps and bounds and that those improvements are largely based on better design principles and the reduction of needless components such that costs are decreased and efficiencies are increased.

Small signal stability analysis of tidal current turbine using ddpmsg with and without controller

Renewable energy is an effective and clean source of supplying electrical loads especially in remote and rural areas. This paper deals with the small signal stability analysis of the tidal current turbine with direct drive permanent magnet synchronous generator (DDPMSG) and its integration into the grid. DDPMSG is used with and without PI controller and tested in both cases for small signal stability analysis. The Eigenvalues of the overall system show the importance of the PI controller for securing the system stability.

PV harmonic distribution analysis for various conditions

Solar sources require using power converters introducing harmonics in the output waveforms. Data used is the solar radiation and temperature in Halifax, Nova Scotia, Canada. In this work we studied the effect of changing the blanking angle of the square-wave inverter with 60Hz switching. The harmonics are evaluated for various temperatures and solar radiation for the optimum firing angle. Also probability density function is obtained for this case. The effect of the weather parameters on each harmonic component and on the fundamental are evaluated. Showing the variability in the amplitude of each harmonic component will allow for the determinations of where to put emphasis on the sizing of filtering system. Different loads and their effect on the THD and signal smoothing due to the variable weather conditions are also studied.

Small signal stability analysis comparison of tidal current energy using DFIG and DDPMSG

The increasing penetration of a renewable energy in the power system grid makes it one of the most important topics for generating electricity for the near future. Tidal currents energy is one of the most technologies growing rapidly for generating electric energy. This paper deals with the small signal stability analysis of the tidal current turbine using two different types of generators, doubly fed induction generator (DFIG) and direct drive permanent magnet synchronous generator (DDPMSG) for a single machine infinite bus system. DFIG and DDPMSG are tested for small signal stability analysis. The eigenvalues of the overall system show the advantages of using the DDPMSG over the DFIG.

Stability and control of tidal current energy with DFIG using PI controllers

Renewable energy is an effective and clean source of supplying electrical loads especially in remote and rural areas. This paper deals with the small signal stability analysis of the tidal current turbine with doubly fed induction generator (DFIG) and its integration into the grid for a single machine infinite bus system. DFIG is used with and without PI controllers and tested in both cases for small signal stability analysis. The Eigenvalues of the overall system show the importance of the PI controllers for securing the system stability.

Tidal currents forecasting using a hybrid of ANN and least squares model

Forecasting is the first step for dealing with the future generation of the tidal current power. A neural network is one of the most commonly used models for forecasting. It is generally constructed from input, output and hidden layers. The least squares method is used to determine the approximate solution of over-determined system in which the number of equations is greater than the number of unknowns. In this study tidal currents models based on combining an artificial neural network (ANN) and the least squares method (LSM) were developed and evaluated for forecasting currents over a future month. The results of the least squares model are compared with those of the artificial neural networks. A hybrid model of ANN and least squares is proposed and this model gives good results compared to either the ANN or LSM alone. This study was done using data collected from the Bay of Fundy in 2008.