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.
This paper proposes a microelectric power grid that includes wind and fuel cell power generation units, as well as a water electrolyzer for producing hydrogen gas. The grid is loaded by an induction motor (IM) as a dynamic load and constant impedance load. An optimal control algorithm using the Mine Blast Algorithm (MBA) is designed to improve the performance of the proposed renewable energy system. Normally, wind power is adapted to feed the loads at normal circumstances. Nevertheless, the fuel cell compensates extra load power demand. An optimal controller is applied to regulate the load voltage and frequency of the main power inverter. Also, optimal vector control is applied to the IM speed control. The response of the microgrid with the proposed optimal control is obtained under step variation in wind speed, load impedance, IM rotor speed, and motor mechanical load torque. The simulation results indicate that the proposed renewable generation system supplies the system loads perfectly and keeps up the desired load demand. Furthermore, the IM speed performance is acceptable under turbulent wind speed.Processes 2019, 7, 85 2 of 21 renewable energy resources for electrical power production showed that wind energy is the first choice [8].Renewable energy systems may be classified into grid-connected systems and standalone systems. The present capacities of the grid-connected renewable energy systems vary from several kilowatts of residential PV systems to large-scale wind farms. The grid-connected systems do not need any storage as the generated energy is injected directly to the grid. These systems are suitable for urban regions where the grid is available. However, standalone systems are suitable for rural areas, where grid extension is not feasible. In standalone renewable energy systems, the load is an individual house and not connected to a grid. The capacities of these systems are usually small. In some applications, several houses are connected to form a small power grid called microgrids (MGs) [9,10]. Microgrid technology has become popular in islands as it provides a cost-effective alternative where power grid extension is expensive and fuel transportation is difficult and costly [11,12].The major obstacle for utilizing one technology of renewable energy sources is the intermittent nature of that source. That intermittent behavior of the renewable energy sources comes from the strong dependency on the environmental conditions, which are changing continuously. A suggestion to solve the intermittency problem of the renewable energy systems is the use of energy storage element. Energy storage units are classified as capacity-oriented storage systems and access-oriented storage systems. The capacity-oriented storage systems include pumped hydroelectric storage, compressed air energy storage, and hydrogen storage systems. It has a slow response and is considered long-term energy storage. Batteries, superconducting magnetic energy storage, supercapacitors, and flywheels are considered access-oriented storage s...
In this paper, an adaptive virtual inertia-damping system based on model predictive control (MPC) is proposed to enhance the frequency dynamic performance of islanded microgrids (MGs) considering a high penetration level of renewable energy sources (RESs). Where a large amount of RESs is recently replacing traditional generating units, causing an undesirable effect on the MG frequency stability and the system inertia, and thus weakening the MG. Therefore, the proposed control system handles this challenge to enhance the robust performance and stability of the MG with high RESs penetration during contingencies. The proposed online MPC strategy estimates the gains of the virtual inertia control (VIC) system (i.e., inertia and damping coefficients) in high RESs MG. The performance of the proposed adaptive VIC system is compared with the conventional VIC system (i.e., constant values of inertia and damping coefficients) using MATLAB/Simulink under numerous disturbances and system uncertainties. Also, the effectiveness of the proposed adaptive VIC system based on the online MPC strategy (which considers both inertia and damping coefficients) is verified by comparing its performance with the adaptive VIC system based on fuzzy logic control, which is designed to estimate only the inertial gain. The results highlight that the frequency stability is upgraded, and the adaptive virtual inertia system based on MPC successfully supports low-inertia islanded MGs with RESs and load fluctuations.INDEX TERMS Adaptive virtual inertia system, model predictive control (MPC), microgrid (MG), frequency stability, high penetration of renewable energy sources (RESs).
This paper investigates how to increase the efficiency of a photovoltaic/energy storage generation unit supplying dynamic loads by regulating and managing both the photovoltaic generator and the storage battery charge-discharge modes. The proposed photovoltaic/energy storage unit is proposed to supply an induction motor driven industrial pump with controlled speed and/or a DC motor driven water pump. An optimal proportional-integral-derivative control based on an Artificial Bee Colony Optimization algorithm is used to regulate the photovoltaic generator in case of normal operation or in case of maximum power point tracking (MPPT) and to also control the battery storage charge discharge modes. A vector control based on the proposed optimal control is used to regulate the induction motor rotor speed at its low reference values needed by the industrial pump. First, a total model of the entire system is obtained. The controller performance with the proposed system is studied with both a DC motor and/or induction motor loads. Simulation results show that the proposed photovoltaic/storage generator is able to supply the suggested dynamic loads under different conditions and with good performance. Also, it is noticed that operating the photovoltaic base on maximum power point tracking condition will give about 43% extra generation power than the normal operation case.
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