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This paper investigates the application of model free control (MFC) strategy to optimally control the oscillation of single body heaving waves energy converter (WEC). The aim of the proposed controller is to maximize the electrical energy output of the device. The MFC is an off-line fixed structure control approach that combines between simplicity and insensitivity to system uncertainties and/or operational conditions. The proposed controller is based on a classical linear compensator, which is designed and tuned using only the well-known dynamics of the WEC. Therefore, any extra unknown or partially known dynamics are taken care of using the ultra-local model (ULM). Simulation results show that the MFC performance is superior to that of the base linear compensator, in terms of reference tracking capability and robustness towards uncertainties. Also other well-established control strategies are used to further validate the proposed controller.

Electricity in Lebanon is facing many problems leading to serious implications on the economic, social, and industrial levels of this country. The big deficit in electricity generation and not meeting the demand is by far the most important problem that needs an immediate. This paper suggests a new idea to reinforce the capacity of existing thermal power plants in Lebanon with the use of photovoltaic (PV) panels. Two thermal power plants will be investigated as case studies; Zouk and Jiyeh power plants. The added PV elements will produce additional energy at a lower cost compared to traditional PV systems. The low cost of the additional PV system in the thermal power plant is obtained through the use of low cost lands and avoiding the use of batteries for energy storage.

The Lebanese electricity system system's deteriorating situation (mainly characterized by the daily long rationing hours), has led to the wide use of diesel generators by Lebanese citizens to compensate for the outage hours. Unfortunately, this has led to lower energy efficiency, higher cost of power production, and notably higher greenhouse gas emissions. In this paper, a renewable-based micro-grid system is proposed, which provides the needed backup power at a lower cost and carbon footprint. In order to increase the flexibility of the system and decrease the payback time, the concept of sharing between houses is applied. Moreover, the extra generated power is injected into the national grid through the net-metering protocol. This feasibility study is applied to 3 types of houses in Lebanon (small, medium, and large). This system could pave the way towards the wide-scale implementation of micro grids and smart grids in Lebanon. In general, it has 3 times less payback period and 5–23 tons of annual CO2 reduction per house.

A tool, “MY PV TOOL”, has been developed in this work to study the behavior of series and shunt resistances in PV modules. Experimental as well as theoretical equations have been used to determine the series and shunt resistances for a given commercial PV module.

It is well-known that the bottleneck of Photovoltaic (PV) systems is the use of storage batteries and the area needed to install the system. The main idea in this work is to design a large PV system with almost zero cost of land needed for the installation, and without the need of batteries. The proposed PV system makes use of special areas of the Lebanese lands; the middle of high-ways which are usually left unoccupied without being exploited by any other business. This way, the traditional high cost of PV systems residing in the land and storage is eliminated. The fact that we do not need batteries in the proposed PV system results from the ability to connect the output power directly to the public utility grid. The design consists of 20,476 PV panels that cover the middle of the high-way extending from Tyre to Saida, with a distance of 27,300 meters and 2 meters wide. The resulting PV system has a capacity of 6.2 MW, and the total initial cost is ∼8.845 M$, however, after 25 years (which is the proposed lifetime of the PV system) the project would generate a total of ∼54.7 M$. Moreover, the PV system would provide net reduction of CO2 and GHG emissions of ∼7,388 tCO2/year.

We propose in this paper a programmable band-pass filter based on an array of fully differential transconductance circuits that controls the filter parameters. The signal path does not contain any switch, and fine-tuning of the filter parameters is implemented using programmable capacitors. A digital building block is implemented in the proposed band-pass filter to tune its central frequency as well as its bandwidth. The filter circuit is based on a biquad topology, which is designed and implemented with CMOS 0.18 μm technology. Experimental results show a programming ability of the center frequency between 5.9 and 58 MHz, and the quality factor can be tuned from 0.36 to 10. These features are obtained for a total power consumption of less than 10.5 mW from a single 1.8 V power supply.

This study suggests a simple and robust control strategy for improving captured power in heaving wave energy converters (WEC). The controller aims at optimizing the captured power using a hierarchical control strategy (HCS), which consists of a higher and lower control levels. The top level control is responsible of producing the reference velocity that is used by the lower level controller to regulate the actual velocity of the WEC buoy. The reference is generated by solving an offline optimization problem for maximizing the absorbed energy subject to the buoy motion constraints. As an attempt to avoid computational complexity in real-time operation, a simple look-up table is produced for various sea-states conditions. In order to track this reference, sliding mode controller (SMC) is deployed. The design parameters of the SMC is tuned offline using a well-known model of WEC. Any perturbations, nonlinearities, and disturbances not covered by the used model will be handled by the robustness property of the SMC. Moreover, the used SMC does not add any further complexity to the overall control strategy. The proposed method is validated in both regular and irregular sea-states, as well as in both nominal and perturbed scenarios. Other control strategies were also used to further assess the performance of the proposed control strategy. Based on the simulation results, the proposed hierarchical controller outperformed the other controllers in both nominal and perturbed scenarios.

We propose in this paper a tunable second order band-pass filter based on two CMOS current feedback operational amplifiers (CFOAs). The CFOA includes a novel offset compensation technique. A digital building block is implemented in the proposed band-pass filter to tune its central frequency. An important feature of the adopted tuning procedure is the ability to tune the filter without affecting other characteristics such as gain, phase and quality factor. The band-pass filter topology is validated with a configuration where the central frequency is tuned from 60 MHz to 95 MHz with frequency steps of 5 MHz. Measurements of the offset-compensated CFOA are promising, and simulation results of the CFOA-based band-pass filter using the 0.18 ? m CMOS process confirm our theoretical analysis.

International audience; This article presents an intelligent fuzzy logic controller (FLC) for controlling single-body heaving wave energy converter (WEC) or what is widely known as “Point Absorber”. The controller aims at maximizing the energy captured from the sea waves. The power take-off (PTO) limitations are addressed implicitly in the fuzzy inference system (FIS) framework. In order to enhance the WEC power capturing bandwidth and make it less susceptible to wave environment irregularities and the system parametric uncertainties, the controller is built to have a self-configurable capability. This also eliminates the need to repeatedly run in-situ tuning procedure of the fuzzy controller or switch between several controllers based on the operating conditions. The fuzzy membership functions (MFs) are optimally tuned using particle swarm optimization (PSO) algorithm. To alleviate the computational burden associated with performing on-line optimization, the fuzzy controller is tuned at a rate significantly lower than the system sampling time. The suggested PSO-FLC has shown promising results compared with the fixed structure fuzzy logic controller (FS-FLC) and other passive control strategies. Several computer simulations were carried out to evaluate the controller effectiveness by applying different sea-states and analyzing the resultant WEC dynamics.

This paper investigates the application of function based model predictive control (MPC) approach to control the movement of single-body heaving wave energy converter (WEC). The proposed controller is designed based on the principle of maximum power transfer, at which maximum power absorption is attained. In addition, the suggested MPC controller respects the physical and thermal limitations of the WEC. Also, the generalized architecture of the proposed controller allows for longer prediction horizons and permits to effectively tune the controller based on the surrounding wave environment. Simulations have been carried out to assess the performance of the proposed controller using realistic sea states. Results show that the proposed MPC controller has achieved satisfactory performance allowing the WEC to optimize energy absorption while respecting the system limitations.

This paper describes a CMOS building block dedicated to high performance mixed analog-digital circuits and systems. The circuit consists of six MOS transistors realizing a new wideband and tunable transconductance. The theory of operation of this device is presented and the effects of transistor nonidealities on the global performances are investigated. Use of the proposed circuit to realize tunable functions (Gm-C filter and current opamp) is illustrated. HSPICE simulations show a wide tuning range of the transconductance value from 40 μS to 950 μS (500 μS) for ±2.5 V (±1.5 V) supply voltages. The transconductance value remains constant up to frequencies beyond 500 MHz. The bandpass filter built with few transconductance blocks and capacitances was simulated with ±2.5 V supply voltage, the center frequency is tunable in the range of 30 MHz to 110 MHz. However, the opamp, which is designed with a transresistance-transconductance architecture, was simulated with ±1.5 V supply voltage. The gain of the opamp can be tuned between 70 dB and 96 dB and high gain-bandwidth product of 145 MHz has been achieved at power consumption of less than 0.5 mW. Experimental results on a fabricated transconductor chip are provided.

This work describes a new CMOS current-feedback operational amplifier (CFOA) with an on-chip continuous-time current-mode input offset voltage compensation circuit. The proposed compensation method is based on a combination of two techniques: the error integration and the current feedback. In addition, this method is irrespective of process and temperature parameters because of its fully symmetrical architecture. HSPICE simulations of the designed CMOS CFOA layout show that the input offset voltage could be reduced to lass than 1 mV, and a gain of around 112 dB and a power consumption of less than 3 mW are achievable.

Many articles on the status of renewable energy in Lebanon have been published recently and this paper comes as a modest contribution to what has been said till now emphasizing the importance of keeping the renewable energy strategy adopted by the current and previous Lebanese governments. This paper sheds light on the current status of renewable energy in Lebanon, problems opposing its implementation, and suggestions to improve this unavoidable choice.

This paper proposes two control strategies for controlling the heaving wave energy converter (WEC): sliding mode control (SMC) and fuzzy logic control (FLC). The two methods are implemented to maximize the absorbed energy of the heaving WEC. This can be achieved by designing the control laws so that the buoy's velocity follows its reference. The two control strategies are tested using actual polychromatic ocean wave. The control strategies consider the physical limitation of the control force and the buoy's elevation. Finally, the performances of the two control methods are tested and compared in the nominal and perturbation scenarios.

This paper presents an artificial neural network (ANN) model for predication global solar radiation (GSR) for main cities in the UAE namely, Abu Dhabi, Al-Ain and Dubai. Multi-Layer Perceptron (MLP) and Radial Basis Function (RBF) techniques with comprehensive training algorithms, architectures, and different combinations of inputs are used to develop these models. The measured data include the maximum temperature (°C), mean wind speed (knot), sunshine hours, mean relative humidity (%) and mean daily global solar radiation on a horizontal surface (kWh/m2). This data was provided by the National Center of Meteorology and Seismology (NCMS) of Abu Dhabi. The results show the generalization capability of ANN approach and its ability to generate accurate prediction of GSR in UAE.

This paper aims at presenting the experience of the renewable energy group at the United Arab Emirates University (UAEU) in the organization of the “Engineering Students Renewable Energy Competition (ESREC)” for undergraduate engineering and technical college students in the United Arab Emirates (UAE). The benefits of such competition to students are that it allows them to use and apply the technical knowledge gained during their engineering formation in the design of a renewable energy (RE) system. The paper presents the evolution of the ESREC competition over four cycles, its judging process and the results.

This paper considers sliding mode controller (SMC) for heaving wave energy converter (WEC). The proposed SMC is implemented to maximize the absorbed energy of the heaving WEC. The problem of chattering control force is solved via the approximation method using the saturation function. The proposed method is tested using polychromatic sea state to simulate the real sea environment. A large difference in energy absorption is resulted using the proposed method compare to a freely motion of heaving WEC. The proposed method maintains the excursion of the buoy within the acceptable limit. The proposed method can maintain the maximum energy absorption despite the presence of uncertainty in its model parameter.

This paper proposes a new reactive control technique for controlling single body heaving wave energy converter (WEC). A function-based continuous model predictive controller (MPC) is implemented to maximize the absorbed energy while respecting the physical limitations of the device. Laguerre orthonormal functions are deployed to approximate the input variable trajectory, which reduces the computational burden associated with MPC. The developed control strategy is evaluated using both monochromatic and polychromatic sea states. The function-based mode predictive controller showed decent reference signal tracking capabilities, optimizing the control effort to achieve maximum power transfer, while respecting the actuators mechanical and electrical limitations. Also the controller provides means to alleviate the problem of excessive real/reactive power flows.

Shading and overheating of photovoltaic cells can result in a significant energy reduction of PV systems. Tilting and natural ventilation allows the buildup of fine sand to be blown off from the PV array's surface. However, dust particles tend to gradually accumulate on the PV surface making the cleaning task more difficult. The accumulated dust reduces the overall PV panel efficiency due to the combined effect of shading and heating. In this research work an original method to reduce effect of windblown sand and dust and increased PV temperature on photovoltaic arrays is described. The proposed method consists of removing air blown dust from photovoltaics using forced air flow of cooled return air from existing air conditioning systems.

This paper presents a new control strategy based on fuzzy logic for maximizing the absorbed energy of heaving wave energy converters (WEC). The fuzzy logic controller is responsible of minimizing the discrepancy between the optimal reference buoy velocity and the actual buoy velocity, hence maximizing the captured power for irregular sea environment. The proposed controller performed well compared to a conventional fixed reactive control strategy.

This paper proposes a new suboptimal reactive control technique for controlling single body heaving wave energy converter (WEC). A self-tunable fuzzy logic controller is implemented to maximize the absorbed energy while respecting the physical limitations of the device. Particle swarm optimization (PSO) algorithm is utilized to carry out an on-line optimization process of the fuzzy membership functions (MFs) embedded in the fuzzy controller. The proposed PSO-FLC out-performed the conventional fuzzy logic controller (C-FLC) in terms of improving reference signal tracking accuracy, widening the device wave absorption bandwidth, and preserving a degree of robustness to model uncertainties.

The prediction of the global solar radiation is of great importance for several engineering applications. Just to name few, solar radiation estimates are fundamental during the design phase of several technologies such as: flat plates and concentrating collectors, solar energy storage devices, solar heaters, and photovoltaic systems. The geographical location of the United Arab Emirates (UAE) (between 26° and 32° North Latitude and between 51° and 56° 25 East Latitude) favors the development and utilization of solar energy. A graphical user interface (GUI) was designed to assist solar energy planners, engineers, architectural scientists, and researchers to predict global solar radiation in different regions of the UAE. The predicted models are developed using Artificial Neural Network techniques.

Information about the availability of solar radiation on horizontal surface is essential for the optimum design and study of solar energy systems. For a country like UAE, the efficient application of solar energy seems inevitable because of abundant sunshine available throughout the year. The traditional way of knowing the amount of global solar radiation (GSR) in a particular region is to install pyranometers at as many locations as possible in this region thus requiring daily maintenance and data recording, and consequently increasing cost of GSR data collection. Therefore, it is rather more economical to develop methods to estimate the GSR using climatological parameters (Akhlaque et al., 2009; Kassem et al., 2009; Falayi et al., 2008; El-Sebaii & Trabea, 2005). Many researchers estimated global solar radiation by using artificial neural networks. (Mohandes et al, 1998) applied ANN techniques to predict GSR using weather data from 41 stations in Saudi Arabia. Data from 31 stations was used in training the NN and the remaining data was used for testing. Input variables to the NN included 4 parameters: latitude, longitude, altitude and sunshine duration. Their sample data was not large enough to allow a credible comparison between the ANN models used and empirical regression models. (Lam et al., 2008) have used Artificial Neural networks ANNs to develop predication models for daily global solar radiation using measured sunshine duration for 40 cities covering 9 major thermal climatic zones and sub-zones in China. (Alam et al., 2009) used ANNs to estimate monthly mean hourly and daily diffuse solar radiation based on weather data from 10 Indian stations which have different climatic conditions. (Alawi & Hinai, 1998) applied ANNs to predict solar radiation in areas not covered by direct measurement instrumentation. The input data that was used for building the network were the location, month, mean pressure, mean temperature, mean vapor pressure, mean relative humidity, mean wind speed and mean duration of sunshine. (Tasadduq et al., 2002) have used neural networks for the prediction of hourly mean values of ambient temperature 24 hours in advance. Full year hourly values of ambient temperature are used to train a neural network model for a coastal location — Jeddah, Saudi Arabia. (Elminir et al., 2005) applied ANN modeling techniques to predict solar radiation data in different spectrum bands from data of meteorology for Helwan (Egypt) meteorology monitoring station. (Rehman & Mohandes, 2008) developed ANN-based estimation GSR for Abha city in Saudi Arabia; by

Planning a photovoltaic (PV) system is complex. Many different factors must be taken into account such as site information, module type and inclination of the modules, level of irradiation, choice of the most suitable inverter, etc. To ease the planning process, computer based tools must be utilized. In this paper, a MATLAB-based modeling tool to design, predict and analyze grid - tied PV systems is presented. This software has a user friendly interface which requires a minimum of data in order to present your optimum system and examine its performance in a clear graphical form. The user can explore different combinations and scenarios to meet the proposed design requirements. Simplicity, accuracy and ability to adapt the designed tool to any updates in both site information and system components would probably make it an excellent tool for educational and research purposes.

Technologies of solar energy offer a clean, renewable and domestic energy source, and are essential components of a sustainable energy future. Conventionally, PV modules used to be located over the roof, but presently and with the advances in photovoltaic technologies a new emerging field of application science the building integrated photovoltaic (BIPV) is taking place worldwide. In this newly emerging field PV cells are incorporated with horizontal and vertical elements of the building envelop such as windows and solar louvers. In this paper a computer modeling tool is developed to predict PV system power generation in typical housing of the United Arab Emirates (UAE). This MATLAB-based tool uses daily weather data for the location in UAE under investigation. A large database that includes various PV modules and inverters was built. Using this tool, 20 degree PV module tilt angle proved to produce the maximum power across the whole year in Al-Ain city - UAE. The results obtained were validated in comparison to other data collected from different cities. Moreover, this tool is flexible and can be easily adapted to changes in PV technologies and weather data.

A 10 MHz, low-power, high-accuracy fully- differential always-valid sample-and-hold (AVSH) circuit is described. The circuit is based on the high dc gain Miller compensation operational amplifier. Its low- power make it suitable for biomedical application such that implantable smart medical devices (SMDs). The proposed circuit has been designed with CMOS 0.13 mum technology. The simulation shows that at 1.2 V supply voltage and 10 MHz of sampling frequency, the harmonic distortion is less than -52 dB for an input swing of 800 mV @ 2 MHz. The power dissipation is 1.26 mW.

A new programmable bandpass filter approach is presented. It is based on an array of fully differential transconductance circuits to control the filter parameters. The signal path does not contain any switch and fine-tuning of the filter parameters is implemented using programmable capacitors. The filter circuit is based on a biquadratic topology and designed with CMOS 0.18 /spl mu/m technology. SpectreS simulation results show a power consumption less than 5.2 mW with a /spl plusmn/ 0.9 V power supply. In addition, a wide frequency range (10-126 MHz) is achieved. The quality factor can also be tuned from 0.1 to 10.6.

The low-input offset voltage is considered as an important aspect of the performance of an amplifier especially when signals are in the range of few hundreds micro volts. The aim of this paper is to describe a new CMOS current-feedback operational amplifier with an on-chip current-mode input offset voltage compensation. This voltage is due to the mismatch between transistors threshold voltages. In order to reduce the offset voltage, we vary the bias currents of the input buffer as a function of the detected error. Simulation results of the compensated CFOA, using 0.18 /spl mu/m CMOS process parameters, show a: 50% reduction of the input offset voltage, 71 dB open loop gain, 160 MHz bandwidth, and power consumption less than 1.5 mW from 1.8 V supply voltage.

On-grid photovoltaic systems are renowned and established systems in countries where solar and wind energy is used for residential buildings. The main objective of this project is to design a comprehensive MATLAB-based tool that performs a technical and economical analysis of on-grid photovoltaic systems. This tool will be used to design on-grid building-integrated photovoltaic (BIPV) systems for the United Arab Emirates (UAE) real-estate market. A large PV equipments database including PV modules and grid-connected inverters from various PV vendors' worldwide and weather information for Al-Ain in UAE are used in this tool. This database will offer good diversity for a PV designer to design a system that meets power requirements. Using this tool, an on-grid PV system is proposed for a real villa design in Al-Ain city.