This article studied the load frequency control (LFC) of a multi-source microgrid with the presence of renewable energy sources. To maintain a sustainable power supply, the frequency of the system must be kept constant. A Proportional–Integral–Derivative (PID) controller is presented as a secondary controller to control the frequency of the microgrid in island mode, and the integral of squared time multiplied by error squared (ISTES) is used as a performance index. The use of the Craziness-Based Particle Swarm Optimization (CRPSO), which is an improved version of Particle Swarm Optimization (PSO), improves the convergence speed in optimizing the nonlinear problem of load and frequency controller design. The test microgrid is composed of the load and distributed generation units such as diesel generators, photovoltaics and wind turbines. The proposed controller provided the desired response to adjusting the microgrid frequency, achieving the final response after a short time and making it more stable and less oscillatory compared with the conventional system.

Because of the lack of transmission and distribution grid of electricity in remote and inaccessible areas due to the high cost of construction of the transmission line along with the unsuitable geographical conditions and taking into account the factors affecting sustainable energy production, renewable energy seems like a sensible solution. Therefore, in this paper, considering the solar and wind potential of Turkalan village located in East Azerbaijan Province, the combined solar-wind-diesel generator system with battery bank and independent of the grid was evaluated. Sensitivity analysis and optimal measurement of the studied system were performed by HOMER software. Sensitivity analysis was performed on the parameters of solar radiation, light reflection from the environment, and wind speed. The goal was to supply 22 kWh/d of energy with a maximum load demand of 2.5 kW. The four hybrid systems proposed by the software considering the total net present cost (NPC) were solar-generator-battery, solar-wind-generator-battery, solar-battery, and solar-wind-battery, respectively. The studies were conducted to determine which of the systems is more suitable for the area.

Given the importance of renewable energy sources in distribution systems, this article addresses the problem of locating and determining the capacity of these sources, namely, wind turbines and solar panels. To solve this optimization problem, a new algorithm based on the behavior of salp is used. The objective functions include reducing losses, improving voltage profiles, and reducing the costs of renewable energy sources. In this method, the allocation of renewable resources is considered for different load models in distribution systems and different load levels using smart meters. Due to the fact that these objective functions are multi-objective, the fuzzy decision-making method is used to select the optimal solution from the set of Pareto solutions. The considered objective functions lead to loss reduction, voltage profile improvement, and RES cost reduction (A allocating RES resources optimally without resource limitations; B: allocating RES resources optimally with resource limitations). In addition, daily wind, solar radiation, and temperature data are taken into account. The proposed method is applied to the IEEE standard 33-bus system. The simulation results show the better performance of the multi-objective salp swarm algorithm (MSSA) at improving voltage profiles and reducing losses in distribution systems. Lastly, the optimal results of the MSSA algorithm are compared with the PSO and GA algorithms.

A desire to produce power in microgrids has grown as the demand for electricity has expanded and the cost of installing modern transmission lines over long distances has become infeasible. As such, microgrids pose DC/AC harmonic distortion losses to the voltage supply that eventually fluctuate the output voltage. The key takeaways that this study presents are: (a) a configuration for microgrids integrated to the national grid using back-to-back converters in a renewable power system is achieved; (b) different scenarios of various schemes of sustainability of the power management in microgrids are analyzed; and (c) the reliable and stable network output power distribution is achieved. In this, the proposed control configuration provides space for construction and stability of the power system with sustainability of the power management. The results show that this current configuration works and stabilizes the network in the shortest time possible, and that the DC connection voltage is regulated and maintains reliable network output despite declining slope controllers, DC power and voltage, and power electronic back-to-back converters. Overall, the simulation results show that the proposed system shows acceptable performance under different scenarios. The accuracy of the results is validated with mathematical formulation simulation using MATLAB software. This system can be utilized in distant regions where there is no power grid or in areas where, despite having a power infrastructure, renewable energies are used to supply the output load for the majority of the day and night.

Microgrids are a part of the power system that consists of one or more units of distributed generation and are expected to remain in operation after being disconnected from the system. Since they rely on overlying networks, frequency control is very important for network-independent operation. Some of the most common problems in independently operating microgrids are frequency sustainability and its fluctuations. The main purpose of this study is to control the frequency of a microgrid in island mode in different scenarios. The objective function is defined based on time and changes in the system frequency. Thus, the variable parameters of the PID controller are transformed into an optimization problem and are solved through the hybrid PSO-GSA algorithm. The study considers four scenarios: (a) a microgrid dynamic model and optimal PID controller coefficients; (b) variable velocity disturbance applied to the studied system in order to observe power changes and the microgrid frequency; (c) stepped load changes applied to the studied system; and (d) the proposed methods on the standard test function. Simulations under different operating conditions are performed, indicating improvements in the stability of microgrid frequency fluctuations by means of the proposed control method.