This paper presents a hybrid energy resources (HER) system consisting of solar PV, storage, and utility grid. It is a challenge in real time to extract maximum power point (MPP) from the PV solar under variations of the irradiance strength.  This work addresses challenges in identifying global MPP, dynamic algorithm behavior, tracking speed, adaptability to changing conditions, and accuracy. Shallow Neural Networks using the deep learning NARMA-L2 controller have been proposed. It is modeled to predict the reference voltage under different irradiance. The dynamic PV solar and nonlinearity have been trained to track the maximum power drawn from the PV solar systems in real time.

Moreover, the proposed controller i

In this study, the kinematic analysis including the forward and inverse kinematic developed for a 5 degree of freedom robotic arm. The forward kinematic is elaborated using Denavit-Hartenberg (DH) convention. Inverse Kinematic is established using Deep Neural Network (DNN) model with five hidden layer each contain 50 neurons fully connected using ReLu activation. A data of inputs and outputs are created and trained. The inputs are the end-effector position and orientation. The outputs are the joint angles of the manipulator. The data is generated by the forward kinematics, where a set of joint angles that limited by their corresponding ranges are inserted to the forward kinematic equations to result the end-effector positions and or

Maximizing the net present value (NPV) of oil field development is heavily dependent on optimizing well placement. The traditional approach entails the use of expert intuition to design well configurations and locations, followed by economic analysis and reservoir simulation to determine the most effective plan. However, this approach often proves inadequate due to the complexity and nonlinearity of reservoirs. In recent years, computational techniques have been developed to optimize well placement by defining decision variables (such as well coordinates), objective functions (such as NPV or cumulative oil production), and constraints. This paper presents a study on the use of genetic algorithms for well placement optimization, a ty

<p>Photovoltaic (PV) systems are becoming increasingly popular; however, arc faults on the direct current (DC) side are becoming more widespread as a result of the effects of aging as well as the trend toward higher DC voltage levels, posing severe risk to human safety and system stability. The parallel arc faults present higher level of current as compared with the series arc faults, making it more difficult to spot the series arc. In this paper and for the aim of condition monitoring, the features of a DC series arc fault are analyzed by analysing the arc features, performing model’s simulation in PSCAD, and carrying out experimental studies. Various arc models are simulated and investigated; for low current arcs, the heur

The poor hole cleaning efficiency could causes many problems such as high torque, drag, poor hydraulics and pipe stuck. These inherent problems result in an avoidable high operation cost which this study tried to address.  In this study, the effect of cutting density on hole cleaning efficiency in deviated and horizontal wells was investigated. Experiments were conducted using 40 feet (12 m) long of flow loop made from iron and PVC. However, the test section was made from PVC with (5.1m) long and (4” ID) for outer pipe and (2” OD) inner pipe. The cutting transport ratio (CTR) was determined from weight measurements for each test. Cutting Transport Ratio has been investigated for effects of the following parameters; flow rate, cu

This paper is focused on studying the effect of cutting parameters (spindle speed, feed and depth of cut) on the response (temperature and tool life) during turning process. The inserts used in this study are carbide inserts coated with TiAlN (Titanum, Aluminium and Nitride) for machining a shaft of stainless steel 316L. Finite difference method was used to find the temperature distribution. The experimental results were done using infrared camera while the simulation process was performed using Matlab software package. The results showed that the  maximum difference between the experimental and simulation results was equal to 19.3 , so, a good agreement between the experimental and simulation results  was achieved. Tool life w

A multivariate multisite hydrological data forecasting model was derived and checked using a case study. The philosophy is to use simultaneously the cross-variable correlations, cross-site correlations and the time lag correlations. The case study is of two variables, three sites, the variables are the monthly rainfall and evaporation; the sites are Sulaimania, Dokan, and Darbandikhan.. The model form is similar to the first order auto regressive model, but in matrices form. A matrix for the different relative correlations mentioned above and another for their relative residuals were derived and used as the model parameters. A mathematical filter was used for both matrices to obtain the elements. The application of this model indicates i