Nowadays, there is a great development in electric vehicle production and utilization. It has no pollution, high efficiency, low noise, and low maintenance. However, the charging stations, required to charge the electric vehicle batteries, impose high energy demand on the utility grid. One way to overcome the stress on the grid is the utilization of renewable energy sources such as photovoltaic energy. The utilization of standalone charging stations represents good support to the utility grid. Nevertheless, the electrical design of these systems has different techniques and is sometimes complex. This paper introduces a new simple analysis and design of a standalone charging station powered by photovoltaic energy. Simple closed-form design equations are derived, for all the system components. Case-study design calculations are presented for the proposed charging station. Then, the system is modeled and simulated using Matlab/Simulink platform. Furthermore, an experimental setup is built to verify the system physically. The experimental and simulation results of the proposed system are matched with the design calculations. The results show that the charging process of the electric vehicle battery is precisely steady for all the PV insolation disturbances. In addition, the charging/discharging of the energy storage battery responds perfectly to store and compensate for PV energy variations.

In improving PV system performance, the parameters associated with electrical photovoltaic equivalent models play a pivotal role. However, due to the increased mathematical complexities and non-linear traits of PV cells, the precise prediction of these parameters is a challenging task. To estimate the parameters associated with PV models, a reliable, robust, and accurate optimization technique is needed. This paper introduces a new algorithm, Rat Swarm Optimizer (RSO), for obtaining the optimum PV cell and module parameters. The proposed method maintains an adequate balance between the exploration and exploitation phases to overcome premature particle issues. The results obtained using RSO are compared with those of other algorithms, i.e., Particle Swarm Optimization (PSO), Ant Lion Optimizer (ALO), Salp Swarm Algorithm (SSA), Harris Hawks Optimization (HHO), and Grasshopper Optimization (GOA), in this work. The modified one-diode model (MODM) and modified two-diode model (MTDM) are used to analyze the parameters of the mono-crystalline PV cell using the suggested RSO. The obtained findings imply that the parameters estimated by the suggested RSO are more accurate than those calculated by the other algorithms taken into consideration in the paper. The statistical results are compared, and it is clear that RSO is a very accurate, fast, and dependable approach for the parameter estimation of PV cells.

Recently, micro-grids (MGs) have had a great impact on power system issues due to their clear environmental and economic advantages. This paper proposes an equilibrium optimizer (EO) technique for solving the energy management problem of MGs incorporating energy storage devices concerning the emissions from renewable energy sources (RES) of MGs. Because of the imprecision and uncertainties related to the RESs, market prices, and forecast load demand, the optimization problem is described in a probabilistic manner using a 2m + 1 point estimation approach. Then, the EO approach is utilized for solving the probabilistic energy management (EM) problem. The EM problem is described according to the market policy on the basis of minimizing the total operating cost and emission from RESs through optimal settings of the power generated from distributed generators (DGs) and grids connected under the condition of satisfying the operational constraints of the system. The proposed EO is evaluated based on a grid-connected MG that includes energy storage devices. Moreover, to prove the effectiveness of the EO, it is compared with other recently meta-heuristic techniques. The simulation results show acceptable robustness of the EO for solving the EM problem as compared to other techniques.

With the increasing development of EVs, the energy demand from the conventional utility grid increases in proportion. On the other hand, photovoltaic (PV) energy sources can overcome several problems when charging EVs from the utility grid especially in remote areas. This paper presents an effective photovoltaic stand-alone charging station for EV applications. The proposed charging station incorporates PV array, a lithium-ion battery representing the EV battery, and a lead-acid battery representing the energy storage system (ESS). A bidirectional DC-DC converter is employed for charging/discharging the ESS and a unidirectional DC-DC converter is utilized for charging the EV battery. The proposed controllers achieve maximum power extraction from the PV and regulate the DC-link voltage. It also controls the voltage and current levels of both the ESS and the EV during the charging/discharging process. The study has been applied to two cases with different power levels. Analysis, simulation, and implementation of the proposed system are presented. A 120 W laboratory prototype is carried out to verify the system performance, experimentally. Design guides for higher power levels are proposed to help in choosing the proper parameters of the converters. Both the simulation and experimental results are matched and verify the high performance of the proposed system.

This study proposes a classical control algorithm for solving the transcendental set of equations for the unequal DC sources of five-level multilevel inverters (MLIs). Such sources can be generated from renewable energy sources. Two DC sources with different values are used to produce an output voltage with five levels. Then, a set of two transcendental equations is formulated with two targeted functions to control the fundamental component and cancel the stipulated single harmonic order. The proposed solution uses a simple classical proportional control with two loops to generate two switching angles. The first switching angle is assigned with an initial value, whereas the second one is calculated from the inner loop. The outer loop is used to cancel the specified harmonic by sending the error signal to the proposed proportional control that tunes the switching angles. The proposed algorithm is easy, fast, and accurate, and has a wide-range solution in terms of modulation index ($\mathrm{MI}$ ) and input DC source ratio ($\mathrm{x}=\frac{{\mathrm{V}}_1}{{\mathrm{V}}_2}\le 1$). The proposed algorithm is tested for a wide range of $\mathrm{MI}$ and $\mathrm{x}$ to verify its feasibility. Moreover, several simulation and laboratory tests are presented to further validate the applicability of the proposed approach.

Grid-connected photovoltaic (PV) systems based on transformer-less inverters have been widely used. Various topologies of transformer-less inverters are presented. The requirements of minimizing leakage current through transformer-less inverters and maximizing the power generated from PV arrays are of great importance. This paper presents a complete system that can effectively minimize the leakage current to safe values. In addition, operation at maximum PV array power point is realized. The system is based on modified H6 transformer-less inverter to minimize the leakage current. Perturbation and Observation P&O maximum power point tracker in addition to a dc-dc boost converter are utilized to achieve the second target. Analysis of each part and system controllers in the proposed system are presented in detail. Losses and system efficiency are introduced. Effects of sun irradiance variations are included. Simulation results prove the effectiveness of the proposed system.