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This paper present test and analyses of piezoelectric transducers tile with drop test technique. This piezoelectric tile was tested together with bending mechanism. The bending mechanism was designed using SolidWork software and manufactured by employing 3D printer technology to conduct the evaluation. The piezoelectric transducers connected in a parallel configuration and inserted in piezoelectric tile together with bending mechanism. The drop test employed to test this piezoelectric tile with various loads and speeds. This test conducted based on free fall concept. A wooden box used as a guide to drop an object onto the piezoelectric tile. The various weight load released at a fixed height with different speeds. The output power generated based on the weight and speed of the object were recorded with average force applied on piezoelectric transducer. The highest output power generated was 634.54 µW when 6 kg load released at 2 drop/s with 1.89 N average force applied on each piezoelectric transducer. The lowest output power generated was 6.28 µW when 1 kg load released at 0.5 drop/s with 0.22 N average force applied. The results showed good output power of the piezoelectric transducer was generated for energy harvesting application.

This paper presents a step-by-step procedure for the simulation of photovoltaic modules with numerical values, using MALTAB/Simulink software. The proposed model is developed based on the mathematical model of PV module, which based on PV solar cell employing one-diode equivalent circuit. The output current and power characteristics curves highly depend on some climatic factors such as radiation and temperature, are obtained by simulation of the selected module. The collected data are used in developing Artificial Neural Network (ANN) model. Multilayer Perceptron (MLP) and Radial Basis Function (RBF) are the techniques used to forecast the outputs of the PV. Various types of activation function will be applied such as Linear, Logistic Sigmoid, Hyperbolic Tangent Sigmoid and Gaussian. The simulation results show that the Logistic Sigmoid is the best technique which produce minimal root mean square error for the system.

The Neutral to Earth Voltage (NTEV) rise are categorised one of power quality (PQ) problems in the commercial building. Usually, the NTEV rise occur due to the neutral conductor problems. Theoretically, the neutral problems give an adverse effect to the network system where the phase voltage and harmonic distortion become more imbalance, heating on the conductor cable, and the electrical appliances prone to damaged. This paper presents a novel technique to identify the source location of NTEV rise in the commercial building due to the loose and open neutral conductor. The proposed technique able to identify the problems that occur either on the upstream or downstream location which respected to the measurement points. In addition, the characteristics of neutral problem due to the loose termination and open conductor are also explored based on the 13-nodes distribution system. The results show the source of NTEV rise can be correctly identified. Keywords: Power quality (PQ), Neutral to Earth Voltage (NTEV), Loose termination, Open conductor

Expansive soils are found in typical areas in the world especially in arid and semi-arid regions. The problems associated with this type of soil drive geotechnical engineers to invent new technologies as remediation’s such as physical and chemical treatments. Innovative foundation techniques were also suggested for remedying the swell-shrink problems of the expansive soil. The granular pile anchor (GPA) is relatively a more favorable technique indebted to its cost-effective, easy and fast to assemble and most importantly was found to be more efficient in remedying the expansive soil. Despite the extensive studies on the expansive soil remedies, yet the granular pile anchor system requires more comprehensive and in-depth investigations. This study is aimed at developing a model with granular piles of various length and diameter extended to the stable zone to investigate the heave and uplift pressure in the expansive soil. For this purpose, experimental and numerical analysis were conducted in a small and in a full scale model respectively. A significant improvement was attained in heave reduction and an increment of uplift capacity. The findings also show that heave decreased significantly when the length and diameter of the GPA increases while the uplift capacity increased. However, it was noted that the extension of length to the stable zone resulted in insignificant changes. Therefore, it can be concluded that the maximum length of 6 m is the ideal length for GPA with different diameters according to foundations design requirement for this particular type of soil.

Solar power is mainly harnessed from photovoltaic (PV) panels which are arranged in multiple arrays in a solar farm or solar system. Though, power generation from PV solar system is characterised by uncertain efficiency, many countries with high insolation prefer solar as an alternative way of generating clean energy. However, the efficiency of energy generated from PV panels is affected by the accumulation of dust and debris, even on one panel in an array. This condition leads to the need for regular cleaning of the surface of PV panels. Current labour-based cleaning methods for photovoltaic arrays are costly in time, water and energy usage as well as lacking in automation capabilities. To overcome this problem, a fully automatic solar panel cleaning system with/without water is proposed. Hence, in this paper, the design of a robot for automated cleaning of the surface of PV panel is presented. The design utilizes an Arduino controller system to control the robot movement during the cleaning process. In addition, it is equipped with two rough sponge and a water pump system that can be used to clean dust or debris found on PV panel surfaces. The efficiency of the PV panels before and after the cleaning process is also observed. The result shows that the developed solar panel cleaning robot is able to clean the panel effectively and increase back the output current as well as the maximum power of the panel by 50%, after the dust on the PV panel is cleaned.

One of the major challenges forbattery energy stowage system is to design a supervisory controller whichcan yield high energy concentration, reducedself-discharge rate and prolong the battery lifetime. A regulatory PV-Battery Management System (BMS) based State of Charge (SOC) estimation is presented in this paper that optimally addresses the issues. The proposed control algorithm estimates SOC by Backpropagation Neural Network (BPNN) scheme and utilizesthe Maximum Power PointTracking(MPPT)schemeof the solar panels to take decision for charging, discharging or islanding mode of the Lead-Acid battery bank. A case study(SOC estimation) is demonstrated as well to depictthe efficiency(Error 0.082%) of the proposed modelusing real time data. The numerical simulation structured through real-time information concedes that the projected control mechanismis robust and accomplishes several objectives of integratedPV-BMS for instance avoiding overcharging and deep discharging manner under different solar radiations

Expansive soil is found in many parts of the world where its major drawback is its expansion and shrinking property upon moisture absorption and drying during alternation of rainy-dry seasons. Due to its swelling-shrinkage repeated process, fatigue and distress cause crack to structures. Granular pile anchor (GPA) system is a pioneering technique that is utilised in reinforcing these expansive soils. Granular pile anchor (GPA) system is a pioneering technique that is utilised in reinforcing expansive soils. The GPA provides tensile resistance which arrest the exerted upward forces and hence reducing heave. Previous investigations have only focused on load-displacement relationships by utilizing the pull-out technique. In this technique, an external force pulls the GPA and the corresponding displacements are recorded. The results provide indication of the GPA resistance to the applied force. However, in real conditions the heave and expansion forces were developed as a result of the pressure caused by the water absorption which pushes the entire soil bed in the upward direction along with the GPA. Therefore, this paper is aimed to explore this concept by carrying experimental and numerical investigations on a small scale model for a single pile with a diameter of 4 cm, with lengths of 20 and 40 cm. Ultimately, the reinforced soil exhibits reduction in upward force and heave compared to the unreinforced soil. Also, verifications for the testing shows that the relationship between the upward force and heave exhibits almost linear relationship for both experimental and numerical investigations. Therefore, shallow foundations incorporated with a GPA system proves to effectively lessen the heave that occurs in expansive soils which in turn can solve problems for constructions.

Granular pile anchor foundations (GPAF) are considered a significant promising foundation system to alleviate the serious effects of changes in the volume of expansive soils that occur throughout shrinkage and expansion. In this paper, 3D finite element analyses are presented by applying PLAXIS software, which is carried out on a typical double-story building built over a GPAF system in expansive soil. An investigation on GPAF system is presented in terms of its resistance ability to the forces caused by the soil movement as a result of variant moisture and the effect of the resistance on the superstructure induced by the straining actions. The results indicate the significance of the GPAF system in restricting the soil movement with high efficiency, which results in a noticeable improvement in the building structural responses in terms of uplift forces, heave and induced deformations.

This paper describes the design of an artificial neural network (ANN) control with power sharing control abilities of a new proposed double-input boost power converter (DIBC). The goal of this research is to model and design a high effectiveness and great performance double-input power converter for renewable energy applications. First, an artificial neural network controller design which is flexible versus a variable input voltage resource and variable load (to achieve the line regulation test and load regulation test) is proposed. Lastly, the suggested concept has been validated through experimentally on the laboratory prototype by using DSP TMS320F28335 real-time digital control. The experimental outcomes emphasize the authenticity of the suggested topology, which can be promising a novel topology that includes double-input power converter appropriate for renewable energy application systems.

The renewable energy technology has become very popular due to major constraint in the existing electrical system such as high electricity demand, increased in fuel prices and concern of environmental pollution. The aims of this project are to develop a complete Proton Exchange Membrane Fuel Cell (PEMFC) model with hydrogen reformer by using MATLAB/Simulink with three different controllers and comparison between the three controllers will be discussed. This project presents the development of methods to solve the problem of PEMFC output voltage by using different controllers which are Proportional Integral (PI), Proportional Integral Derivatives (PID) and Proportional Integral Fuzzy (PI-Fuzzy) controllers. The Ziegler Nicholas tuning method is used to tune PI and PID gains in a Simulink model. It helps the system to achieve a balance between performance and robustness for both controllers. The Mamdani type was used to develop the fuzzy controller in Simulink model. The transient performances that will be discussed are rise time, settling time, maximum overshoot, and percentage of overshoot. The results show that the proposed PI-Fuzzy is better than the conventionally used PI and PID controllers.

A renewable energy source that works alone can’t achieve customers’ requirements for a stable power supply. Therefore, the paper proposes a multi-input converter for hybrid renewable energy system. This converter is designed for two input sources, PV and wind generator in order to design high efficiency and high performance converters for renewable energy applications. The proposed multi-input converter is composed by interleaved technique with two step-up converters and the two inputs are accommodated with some extra semiconductors, inductances and diodes. The modes of operation based on the status of the four switches, where S1 and S2 operate as main switches in order to deliver energy from both voltage sources. A constant output power to the load is provided by switching S3 switch, which guarantied the appropriate output voltage by reduce the ripple and improve the reliability. Simulations of multi-input converter has been performed using MATLAB/SIMULINK. The simulation results confirm the validity of the proposed method, which can be seen as a promising new topology that ensure multi-input converter suitable for renewable energy applications.