|
|
|
 |
Search published articles |
 |
|
Showing 3 results for Fuzzy Controller
Negin Mehrpooya, Dr. Ali Karami Mollayi,
Volume 6, Issue 1 (9-2017)
Abstract
The loss of balanced voltages involves a voltage drop due to symmetric three-phase errors, or the initiation of high-power three-phase loads or symmetric three-phase switches. While these events in an unbalanced way lead to asymmetric voltage drops. Voltage drops can cause asymmetric load on the power grid, the occurrence of volatility, and even network power outage. One of the most common ways of dealing with voltage drop is the use of power electronics devices in sensitive feeders of distribution networks. In this research, dynamic voltage restorer is used. In order to avoid this voltage drop, optimal PID, fuzzy and fuzzy controllers are the controllers that this article intends to implement and compare their results.
Parisa Kolah Kaj, Dr. Ebrahim Aghajari, Dr. Seyed Mohsen Seyed Mousavi,
Volume 11, Issue 3 (12-2022)
Abstract
Nowadays, the use of renewable energy has become very important. Considering the changes in radiation intensity and the continuous switching of the inverter, the control algorithm of the inverter plays an important role. In the DC part, adjusting the voltage of the DC link is very important, and stabilizing the voltage at this point will have a significant impact on the performance of the entire system. In the existing methods in order to regulate the voltage, a proportional integral controller (PI) is used and the coefficients of this controller are usually fixed and its performance decreases when the working conditions change, so using structures with an approach Fuzzy is noticeable. The use of the fuzzy PI controller improves the performance of the controller, increases the speed of realizing the maximum power tracking algorithm, reduce the fluctuations of the DC link voltage and the output power of the photovoltaic system inverter. In this article, a new structure based on the fuzzy PI controller is presented in order to improve the performance of the inverter control algorithm, so that the DC link voltage becomes equal to the reference value for 2 seconds faster than the normal PI method and the grid voltage range for 1/5 seconds faster. And the active power of the grid will reach a steady state 2 seconds faster and the fluctuation of these variables will be significantly reduced.
Ehsan Zarasvandi Hosseini, Dr. Ebrahim Aghajari, Dr. Seyed Mohamad Sadegh Ghiasi,
Volume 12, Issue 2 (9-2023)
Abstract
Today, global attention has been drawn to energy production through renewable sources, especially solar energy. Partial shading conditions have created challenging issues for maximum power point tracking, including trapping at local maximum power points, slow tracking time, and fluctuations in power output during tracking time. Therefore, in order to overcome the problems related to shading conditions and deal with local peaks, researchers have presented various hybrid techniques based on fuzzy controllers and meta-heuristic algorithms. Among all meta-heuristic algorithms, particle swarm optimization and gray wolf algorithm are the most common optimization methods due to their easy implementation, simplicity and low computational load. But the drawbacks of these algorithms are the low convergence speed and the difficulty in adjusting their parameters, and they may be caught under the rapid changes of solar radiation and shading conditions in local peaks. To deal with these problems, a new hybrid structure based on type two fuzzy controller and squirrel search algorithm has been used in this research. The type two fuzzy controller is used instead of the normal fuzzy controller and it is optimized and adjusted by the squirrel search algorithm which is used instead of the gray wolf algorithm. In this structure, by applying four radiation patterns, the effectiveness of the proposed controller has been investigated. The simulation results in MATLAB software show that the efficiency of the proposed method is about 99% on average, And using the proposed method, compared to not using it, reduces the settling time by about 36%, increases the maximum power tracking speed, and reduction of power fluctuations is possible.
|
|
