|
|
|
 |
Search published articles |
 |
|
Showing 2 results for Samanfar
Mohammad Reza Ghodsi, Dr. Alireza Tavakoli, Dr. Amin Samanfar,
Volume 12, Issue 3 (12-2023)
Abstract
To deal with the challenge of the level of penetration of renewable energy sources against uncertainties and in order to develop the secondary load frequency control loop, with the aim of reducing the impact of disturbances and adjusting the resistant gain coefficient to uncertainties, using a virtual inertial controller based on the resistant control of the Mu-synthesis method. For the lack of inertia in the islanded microgrid clusters, alternating current has been done. The stability and performance of this method is proved based on the structured singular value. The experimental results of the hardware in the loop by the TMS320F2812 digital signal processor and the simulation in the MATLAB/SIMULINK software environment confirm the performance of the proposed controller for the development of traditional load frequency control in comparison with the enhanced virtual inertial control and inertialess mode, under various disturbances, that the application of the controller The virtual inertia based on Mu-synthesis improves the stability of islanded microgrid clusters and damping of power fluctuations, and also reduces frequency deviations to a significant extent.
Seyed Hossein Hassanzadeh Fard, Dr Amin Samanfar, Dr Mehdi Nikzad, Dr Mohsen Rashidi,
Volume 13, Issue 3 (11-2024)
Abstract
Today's distribution networks have made significant progress in terms of dimensions and components and are one of the important pillars of the economy of each country. Governments often look for ways to minimize network damage in critical and fault situations, limiting the scope of faults to maintain maximum service continuity. After a failure occurs, during the restoration period, the operator or network administrator`s right decision, can reduce the dimensions of the failure and prevent further damage. As future networks move towards self-healing, decision-making functions must be empowered so that by maintaining the technical constraints of the network, they can create sustainable emergencies with timely interventions. To do this, the customer damage function factor can be used, which is presented as a number for each type of customer with the unit of $/kWh. So, the feeders can be valued, but due to the probable nature of the cost in outages, this factor is not complete alone. This article uses the customer damage probability function, which is calculated separately for each feeder and can be applied to the entire network. The cost prediction method for the sample feeder with different kinds of load has been simulated, using the Monte Carlo method as well as the UGF method in MATLAB software. The results show despite having the same input and achieving the same results for both methods, the response speed in the UGF method is much higher.
|
|
