The need of clean and renewable energy, as well as the power shortage in Gaza strip with few wind energy studies conducted in Palestine, provide the importance of this paper. Probability density function is commonly used to represent wind speed frequency distributions for the evaluation of wind energy potential in a specific area. This study shows the analysis of the climatology of the wind profile over the State of Palestine; the selections of the suitable probability density function decrease the wind power estimation error percentage. A selection of probability density function is used to model average daily wind speed data recorded at for 10 years in Gaza strip. Weibull probability distribution function has been estimated for Gaza based on average wind speed for 10 years. This assessment is done by analyzing wind data using Weibull probability function to find out the characteristics of wind energy conversion. The wind speed data measured from January 1996 to December 2005 in Gaza is used as a sample of actual data to this study. The main aim is to use the Weibull representative wind data for Gaza strip to show how statistical model for Gaza Strip over ten years. Weibull parameters determine by author depend on the pervious study using seven numerical methods, Weibull shape factor parameter is 1.7848, scale factor parameter is 4.3642 ms-1, average wind speed for Gaza strip based on 10 years actual data is 2.95 ms-1 per a day so the behavior of wind velocity based on probability density function show that we can produce energy in Gaza strip.

The use of Model Predictive Control (MPC) is investigated for a three phase to three phase direct matrix converter with input and output LC filter for power supply applications. It allows generation of sinusoidal output voltages and input currents with low harmonic distortion. The work describes in details the design of the proposed finite states model predictive control in conjunction with a full load observer. The proposed matrix converter power supply produces unity input power factor and a perfect tracking of the sinusoidal output voltage, accurately following the imposed reference in the presence of a linear load. A simulation study is presented to validate the proposed control scheme.

Smart street light is an intelligent control of street lights to optimize the problem of power consumption of the street , late in night. Currently, usual street lights are automatically turn on when it becomes dark and turn off when it becomes bright. This is huge waste of energy in the entire world as it is an essential community service, but current implementation is not efficient. Conventional street lights are being replaced by Light Emitting Diode (LED) street lighting system, which reduces the power consumption. The focus of this project is to design a system of street lights controller to provide a reduction in power consumption. The prototype is design by using Light Dependent Resistor (LDR), Infrared sensor (IR), battery and LED. All this component was controlled by Arduino UNO

The generation, distributionand transmission of electricity in Palestine have recently emerged as major issues. This study comprehensively assesses the production of wind energy and the estimation of wind energy potential in Palestine’s south coastal plain. The goal is to evaluate Palestine’s wind energy production by studying wind data and calculating energy and power. This study analyses two actual time series datasets. Findings are elaborated to determine the wind energy conversion per 1 m2. The wind speed data from January 1996 to December 2006 in Gaza and from January 2012 to December 2015 in Ashqelon are selected as the data sample. This study is crucial given the need for clean and renewable energy, the power shortage in the Gaza Strip and the limited number of wind energy studies conducted in the south coastal plain of Palestine, especially Gaza Strip. This study estimates the wind energy potential of the Gaza Strip to determine the wind potential. The annual mean wind speed and power are 4.11 ms-1 and 903.4 Wm-2, respectively. Moreover, the study clarifies the electrical energy generation in the Gaza Strip using small-scale turbines and offers a feasible alternative to existing schemes.

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The inductive power transfer (IPT) has contributed to the fast growth of the electric vehicle (EV) market. The technology to recharge the EV battery has attracted the attention of many researchers and car manufacturers in developing green transportation. In IPT charging system, the coil design is indispensable in enhancing the EV battery charging process performance. This paper starts by describing the two charging techniques; static charging and dynamic charging before further presents the IPT system descriptions. Afterwards, this paper describes a brief review of coil designs which discusses the critical factors that affect the power transmission efficiency (PTE) including their basic designs, design concepts and features merits. The discussions on the basic coil designs for IPT are of the circular spiral coil (CSC), square coil (SC), rectangular coil (RC), and double-D coil (DDC). Furthermore, the significant advantages and limitations of each research on different geometries are analyzed and discussed in this paper. Finally, this paper evaluates some essential aspects that influence the coil geometry designs in practical.

In Wireless Sensor Networks which are deployed in remote and isolated tropical areas; such as forest; jungle; and open dirt road environments; wireless communications usually suffer heavily because of the environmental effects on vegetation; terrain; low antenna height; and distance. Therefore; to solve this problem; the Wireless Sensor Network communication links must be designed for their best performance using the suitable electromagnetic wave behavior model in a given environment. This study introduces and analyzes the behavior of the LoRa pathloss propagation model for signals that propagate at near ground or that have low transmitter and receiver antenna heights from the ground (less than 30 cm antenna height). Using RMSE and MAE statistical analysis tools; we validate the developed model results. The developed Fuzzy ANFIS model achieves the lowest RMSE score of 0.88 at 433 MHz and the lowest MAE score of 1.61 at 433 MHz for both open dirt road environments. The Optimized FITU-R Near Ground model achieved the lowest RMSE score of 4.08 at 868 MHz for the forest environment and lowest MAE score of 14.84 at 868 MHz for the open dirt road environment. The Okumura-Hata model achieved the lowest RMSE score of 6.32 at 868 MHz and the lowest MAE score of 26.12 at 868 MHz for both forest environments. Finally; the ITU-R Maximum Attenuation Free Space model achieved the lowest RMSE score of 9.58 at 868 MHz for the forest environment and the lowest MAE score of 38.48 at 868 MHz for the jungle environment. These values indicate that the proposed Fuzzy ANFIS pathloss model has the best performance in near ground propagation for all environments compared to other benchmark models

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