Ahmed A. Zaki Diab

In this paper, a simulation model describing the operation of a PV/wind/diesel hybrid microgrid system with battery bank storage has been proposed. Optimal sizing of the proposed system has been presented to minimize the cost of energy (COE) supplied by the system while increasing the reliability and efficiency of the system presented by the loss of power supply probability (LPSP). Novel optimization algorithms of Whale Optimization Algorithm (WOA), Water Cycle Algorithm (WCA), Moth-Flame Optimi

Recently, building an accurate mathematical model with the help of the experimentally measured data of solar cells and Photovoltaic (PV) modules, as a tool for simulation and performance evaluation of the PV systems, has attracted the attention of many researchers. In this work, Coyote Optimization Algorithm (COA) has been applied for extracting the unknown parameters involved in various models for the solar cell and PV modules, namely single diode model, double diode model, and three diode mode

Hybrid renewable energy (HRE) sources have become a popular alternative in isolated and rural locations; because of the increased prices of fossil fuels and their CO2 emissions. This paper investigates the application of recent optimization methods to dedicate the optimal configuration of HRE sources. These HRE sources comprise photovoltaic (PV) panels, wind turbines (WT) with a battery storage system (BSS), and backup diesel generators (DGs). The cost function for the optimization problem has b

Among all renewable energy sources, solar cells are considered the most popular solution for a clean source of energy and have a wide range of applications from few watts to Megawatt industrial and domestic loads. Building a precise mathematical model based on nonlinear equations for solar cells as well as photovoltaic (PV) modules is an essential issue for reasonable performance assessment, control and optimal operation of PV energy systems. In the current study, a novel optimization algorithm,

Proton Exchange Membrane Fuel Cells (PEMFC) is considered a propitious solution for an environmentally friendly energy source. A precise model of PEMFC for accurate identification of its polarization curve and an in-depth understanding of all its operating characteristics attracted the interest of many researchers. In this paper, recent meta-heuristic optimization methods have been successfully applied to evaluate the unknown parameters of PEMFC models, particularly Marine Predators Algorithm (M

In this paper, the impact of integrating photovoltaic plants (PVPs) with high penetration levels into the national utility grid of Egypt is demonstrated. Load flow analysis is used to examine the grid capacity in the case of integrating the desired PVPs and computer simulations are also used to assess the upgrading of the transmission network to increase its capacity. Furthermore, the impact of increasing the output power generated from PVPs, during normal conditions, on the static voltage stabi

The accurate arithmetical models of solar photovoltaic (PV) modules plays a vital role in the performance, operation, and control of the PV systems as a part of renewable generation. Therefore, the proposed paper develops a novel robust Honey Badger Algorithm (HBA) and African Vulture Optimization algorithm (AVOA) that have been utilized for deducing the unknown parameters of various solar PV units accurately and efficiently. The HBA and AVOA techniques are developed to identify the approximate

Nowadays, forecasting methods have gained significant attention, particularly with the design and development of energy systems. In fact, accurate load and price forecasting is crucial for effective planning, controlling, and operation of power systems, especially with renewable energy sources (RES). This paper implemented an improved Markov Chain Artificial Neural network (ANN-MC) for load forecasting. The proposed design involved a two-step implementation process, considering various statistic

In this paper, a robust speed control scheme for high dynamic performance sensorless induction motor drives based on the H_infinity (H∞) theory has been presented and analyzed. The proposed controller is robust against system parameter variations and achieves good dynamic performance. In addition, it rejects disturbances well and can minimize system noise. The H∞ controller design has a standard form that emphasizes the selection of the weighting functions that achieve the robustness and perform