Major changes in the technologies of power generation and distribution systems have been introduced in recent years due to concern over rapid climate change. Therefore, disturbances in the large-scale generation, transmission, and distribution of energy are expected to occur in the near future. This is due to the difficulty in controlling the transmission and distribution of energy produced from renewable energy sources (RESs), caused by the instability of these sources and the intermittent nature of their energy. As a result, maintaining the dynamic stability of wind power flow and control of the network frequency is becoming more challenging due to the high penetration impacts of RESs. In this paper, a control algorithm using the power-sharing method is proposed for a wind-based energy storage system to maintain the dynamic stability of wind power flow and control of frequency in the power network. To maintain the network stability, a storage system (battery) was installed to store the excess wind power without throwing it into the Secondary/Dump Load (SL) and minimize losses in power generated by the wind turbine. The results show, the transient time of wind power flow and the fluctuation rate of frequency are reduced significantly using a Fuzzy Logic (FL) controller compared to the Proportional Integral Derivative (PID) controller.

Distributed generation (DG) has environmental as well as economic benefits and develops new concepts to make the power network more effective and minimize pollution in the environment. Being the fluctuation behavior of renewable energy sources (RESs), generation, balance, and demand is not an easy task to control because it is not desirable to have a constant power generation from RESs due to natural prospects. As a result, the dynamic stability of power flow and control of frequency is becoming more challenging due to the high penetration impacts of RESs. In this article, we have proposed a control algorithm with two scenarios for a high-penetration/hybrid diesel wind-based energy storage system to maintain the dynamic stability of power flow and control the frequency in the overall power system. The results show, using an integral-derivative (I-D) controller, the transient time of wind power flow and the fluctuation rate of frequency are reduced significantly compared to the prior research of publication. To regulate the network frequency, a storage system (battery) was used to store the excess energy without throwing it to the secondary/dump load (DL) and minimize the wastage of power produced by the wind turbine. The battery was supplied the excess wind power when there is a high load demand.

In this paper a new global maximum power point tracking (GMPPT) approach is proposed for a photovoltaic (PV) module using a genetic algorithm (GA) system under partial shading conditions. The partial shading condition is one of the adverse phenomena that the PV system experiences, it is difficult to track true peaks because of existence of multiple peaks in a PV array (partially shaded based). The conventional GMPPT algorithms met in the literature, the initial value of reference is approximated arbitrarily for various conditions of irradiation and temperature and they can’t distinguish between the local and global peaks if partial shading occurs, what reduces the performances of the tracking of the point of optimal operation of PV systems. So, to improve these performances, we proposed a nonlinear based GMPPT method to estimate the initial optimal operating point. To compare with conventional GAs methods, the global peak (GP) tracking process is accomplished after follow the far fewer power perturbation steps. This approach made a possible to largely improve the GP tracking in the PV system, improve the accuracy of the GMPPT algorithms, and accelerate the convergence speed. This GMPPT method is checked for different shading profiles through the simulation and verification.

Power generation from Renewable Energy Sources (RESs) is unpredictable due to climate or weather changes. Therefore, more control strategies are required to maintain the proper power supply in the entire microgrid. This paper presents a simulation scheme utilizing a solar system instanced by Photovoltaic (PV) panels coupled to the grid, loads, and an energy storage device. At first, modeling the PV panels cell and their operation were analyzed. The synthesis of the adaptive notch filter was designed to compensate for the input currents. The power converter’s/inverter’s efficiency and control facility allowed us to link the energy storage system with an electrical grid. Several simulations were accomplished consistently with nonlinear control techniques for the simple inverter, multi-variable filter, notch filter, and without a filter. Finally, the performances of the nonlinear controller with various filters were carried out to regulate the DC bus of the proposed grid. The advantage of these controllers is compensating the reactive power and harmonic currents to obtain a disturbance-free power network. The overall installations and simulations were established using the Matlab/Simulink software.

Distributed Generation (DG) becomes a very impressive and renowned power generation system in the presence of the power engineering industry. It has economical as well as environmental benefits in respect of conventional power generation systems and develops new ideas to build up the system more effectively and reduce pollution in the environment. Due to the fluctuating behavior of Renewable Energy Sources (RES), balancing, demand and generation are not an easy task to control the power system. It is impossible to have a continuous power production from the RES because of natural situations. That's why control of frequency in a power generation system makes it more challenging due to the increasing penetration of RES. In this paper, a control technique has been developed with two cases for a hybrid diesel / high-penetration wind-based energy storage system to control the frequency in the overall power system. The results show that without throwing the large amount of power in a secondary/dump load to maintain the desired level of frequency, a storage system (battery) can be charged when power from renewable energy sources is higher than load demand and discharged when power from renewable energy sources is less than total load demand. To investigate the fluctuation behavior of overall system a PID Controller has been used.

This paper implements and compares the existing power supply converters for an energy storage system to determine the best suited for the smart grid application. A survey of different DC-DC converters is carried out to analyze the battery's overall performance. The main objective is to identify this application's most appropriate energy storage device. The advantages of this technology have high efficiency and reliability, which can connect various energy sources and reduce conduction losses in the power converters. Through the converter control, reference currents are imposed to charge the battery. The battery nominal voltage needs to change to see which type of converter is the most suitable and robust. Simulation results show that the operating ranges of boost-buck, buck-boost, and buck-boost converters with negative output voltage enhance the efficiency of battery and renewable energy sources and compared the DC converters to know the functional voltage for the energy storage system. The power converter's efficiency and control facility will allow us to link the energy storage system with the power grid. The overall installation is established using MATLAB/Simulink software.