فهرست مطالب رحمت اعظمی

In this paper, the fuzzy neural controller has been used to control the speed of the surface permanent magnet synchronous motor, despite its uncertainty in parameters and torque load. This method first uses a variety of local controllers (such as PIDs, LQRs, etc.) for different engine operating points and for different uncertainties and torque for precise engine control. Then the adaptive fuzzy controller learns that all of the local controllers are included and therefore, despite the indeterminacy in the parameters and torque of the motor, the reference speed with fast response and the least stable mode error are followed. Fuzzy neural network training algorithm is a mixed method, which is a combination of two methods of least squares and descending gradients with error propagation method. The least squares method is used to adjust the linear parameters of the output layer and the descending gradient algorithm uses an error propagation method for adjusting and updating the nonlinear parameters of the fuzzy layer. In the end, simulation of this controller is compared with H∞, Fuzzy and PID controller. Simulation results show the effectiveness of the proposed method in the paper.

One of the main components of distribution systems is transformer, and their failure will cause irreparable damage in power systems and distribution companies. These failures are to increase the losses of the transformers due to the increase of harmonics, especially the current harmonics. These losses increase the temperature of transformers and reduced the lifetime of distribution transformers. In this paper evaluated losses and lifetime in the presence of harmonic loads in Ilam distribution transformers. Technical and practical assessments of the presence of harmonic loads and their effect on the lifetime of transformers have been investigated. According to the obtained results the useful lifetime of some transformers from 30 years to 17 years are decreased.

In this paper a joint energy and reserve market with transmission switching considering dynamic constraints has been proposed to minimize the cost of supplying load, reliability expenses and avoidance of transient instability in line switching.Transmission switching is used during contingencies and steady state to determine optimal required energy and reserve values. To investigate the efficiency of the proposed strategy IEEE 14 bus test is studied. According to the obtained results, this strategy decreases energy and reserve marginal prices, as well as reliability cost.

There is a great resolution calling for smart grids in recent years. Introduction of new technologies, that make the network flexible and controllable, is a main part of smart grid concept and a key factor to its success. Transmission network as a part of system network has drawn less attention. Transmission switching as a transmission service can release us from load shedding and remove the constraints’ violations.
In addition to removing the congestion and decreasing the system cost, transmission switching may damage generating units due to transient states in instance of reconfiguration. Therefore, in optimal transmission switching, the system security, practical limitations and possible damages should be considered.
Considering dynamic constraints in proposed model avoid the occurrence of transient instability when opening the line in transmission switching action.
A network reduction method based on modified Jacobean AC Newton-Raphson technique power flow considering switchable line in technique is used for speeding up the calculation, efficiency and simplicity.
An approach for selecting the best lines in switching operation in the network is proposed. Based upon this approach, the lines with the highest effect on cost reduction are considered as the candidate switchable line.
To investigate the efficiency of the proposed strategy IEEE 57 bus test system is studied.