Hadi TARIMORADI

Microgrids consist of four control layers, among witch the secondary layer plays a crucial role. The secondary layer's function is to maintain voltage and frequency at their nominal values and prevent deviations, while also ensuring proper active and reactive power sharing. This layer can be implemented in three ways: centralized, distributed, and decentralized. Both centralized and distributed control strategies require a communication infrastructure to exchange information among units, making the microgrid susceptible to cyber-attacks. Conversely, the decentralized strategy does not involve inter-unit communication, thereby eliminating the risk of cyber-attacks and enhancing the microgrid's security. This study employs robust control based on the H∞ method for frequency regulation and active power sharing. In this approach, appropriate weighting functions are selected with the aim of minimizing the system's transfer function, considering uncertainties, weighting functions, and the controller. The design of this controller relies solely on the dynamics of the low-pass filter and droop control. Moreover, this controller does not require system state estimation, time-dependent protocols, or event detectors. By using this method, frequency restoration in the presence of network parameter changes after disturbances has been effectively achieved, and the frequency has returned to its nominal value, while active power has been accurately shared.

Power transformers are one of the important, vital, and expensive equipment in electrical energy transmission and distribution networks, and it can be said that there is a direct relationship between the correct operation of this equipment and the reliability of the network. Therefore, their health is necessary to maintain the stability and increase the reliability of the network. In general, transformers may be under stress and exposed to different types of errors with different levels of intensity during the operation phase. Among all the factors that put transformers at risk are mechanical errors and stresses caused by short circuits, which are more common. The currents caused by short circuits cause deformation of the coils in the radial and axial direction by introducing compressive and tensile forces. For this reason, monitoring their condition is very important. In general, power transformer status monitoring systems can be classified into two main categories: online and offline. In the offline mode, the transformer must be removed from the circuit to monitor the status, which will disrupt the power supply, but in online monitoring, the transformer is in service, and at the same time as the operation, the status of the transformer is monitored, and there is no need to disconnect the transformer. Currently, various diagnostic methods are used to detect defects in power transformers. Among all these methods, frequency response analysis (FRA) technique is used more because of its low cost, convenience, simplicity, and effectiveness. The principles of the frequency response analysis technique are based on the fact that the transformation function of each transformer is part of its unique characteristics, so that any change in the geometry and physical shape of its windings causes a change in the transformation function, through which errors can occur in Transformer realized. Considering the problems and challenges that exist in offline monitoring methods, the basis of this research is based on online monitoring. There are various methods for monitoring the condition and determining the conversion function of transformers online, each of which has problems and challenges during implementation. In this thesis, an attempt is made to produce a transient with a wide frequency band through the practical design of a controllable switching circuit so that the frequency response of the transformer can be obtained online to detect the mechanical defects of the coil. The switching circuit can be a capacitor, which will be concluded about the circuit, its values, and the switching voltage level after simulation and checking the results. The next step is extracting the frequency response from the obtained transient voltages and currents. In this thesis, the impedance conversion function of the transformer has been obtained by two simulation and practical methods. EMTP and Matlab software are used in the simulation method. The practical method has been done in several stages. EMTP and Matlab software are used in the simulation method. The practical method has been done in several stages. After designing the switching circuit and implementing it in the laboratory, first the input voltage power signal is removed by a designed hardware filter, and then the steps of noise removal and signal preparation to extract the frequency spectrum are performed with software methods. Two current prop methods and high-power brick resistors have been used to record the current signal. Finally, by using the fast Fourier transformation of two input voltage and current signals, the frequency response of the input impedance of the transformer has been obtained in no-load mode.

The deployment of energy storage systems (ESS) is an important way to maximize the energy efficiency of the distribution network, and the overall performance of the network can be increased by determining the best place for installation, their capacity or size, and their optimal performance. An optimized ESS in terms of size and installation location can help the grid to meet the maximum energy demand, increase the benefits of integrating renewable and distributed energy sources, improve the benefits of combining renewable energy sources and energy distribution. help in power quality management and reduce distribution network expansion costs. In this thesis, an overview of the placement, size and optimal efficiency of ESS is presented. This collection considers a wide range of scenarios, targeted performance goals, application strategies, types of ESS, advantages and limitations of proposed systems and approaches. While batteries are widely used as ESS in various applications, a detailed comparative analysis of ESS specifications shows that gear energy storage (FES) also warrants attention in some distribution network scenarios. Is. This research provides recommendations for relevant requirements or procedures, appropriate selection of ESS, intelligent charging and discharging of ESS, measurement of ESS, placement and operation, and power quality issues. In addition, this study identifies future research opportunities related to the challenges of optimal ESS placement planning, development and implementation issues, optimization techniques, social impacts, and energy security.

Abstract: The development of large-scale renewable energy sources has led to significant penetration of these variable generation sources in the world's power systems. One of the main obstacles to the expansion of the penetration of renewable resources, especially photovoltaic systems, in distribution system is the problem of increasing network harmonics due to the presence of electronic power converters. Harmonics can have inappropriate effects on the load and network and even damage other parts of the network. In this thesis, in addition to controlling the PV system to receive maximum power from the sun, a new control strategy for controlling the grid connected inverter to improve the power quality at the PCC point for a three-phase, four-wire distribution system is presented. Four methods of PI controller, fuzzy controller, neural network controller and controller with PSO algorithm have been simulated, investigated and compared. All the above control methods have significantly improved the current and voltage harmonics of the system. However, according to the comparisons made for the four implemented control methods, it was observed that in terms of performance and stability, fuzzy control and neural network had better results than PI control and PSO algorithm. On the other hand, the PSO algorithm adjusts the THD value and better power quality for the network current output. In terms of response performance and imbalance compensation, fuzzy and neural algorithms have provided more acceptable results. In general, by comparing the two methods of fuzzy logic and neural network, it can be said that fuzzy logic is somewhat better than neural network in terms of performance and somewhat in terms of THD, and for this reason, the proposed controller of this thesis is considered. The effects of control systems on imbalance current compensation have also been investigated and the correctness of its performance in this field has also been investigated.

Microgrid has various challenges and limitations, one of the most important of which is the question of power quality. Various methods have been proposed to improve power quality. Among these methods, the use of storage devices has received more attention in recent years. In the past, storage devices only functioned as energy buffers, but with the advancement of technology and power electronics, nowadays storage devices are used more in the issues of stability, power quality, and reliability. Among the storage structures, batteries have received more attention. In this research, the new structure of battery-battery hybrid storage is used. These batteries are controlled separately. In the control system of the first battery, the voltage and frequency are controlled under different disturbance conditions, including changes in the mechanical power of the generator. ANN-PSO algorithm has been used to optimize the controller coefficients. This algorithm works online and determines the coefficients. The second battery control system includes two control paths and a power quality disturbance detection algorithm. Control paths with layered structure have been used separately to solve imbalance and harmonic disorders. In fact, each path is used to solve a problem. The generalized Hilbert transform algorithm has been used to select the control path. This algorithm is used for power quality disturbances and control path selection.

The distribution network consists of the main feeder, laerals, sub-laterals and finally loads. The distribution network in the power system is responsible for transmitting electric power to consumers; In other words, distribution networks are the meeting place of subscribers with the electricity industry. If a power outage occurs at a point in the distribution network, it will cause an interruption in the supply of electric power to some subscribers. The occurrence of these interruptions is considered a problem of the entire power system from the point of view of consumers. Almost the interruptions created in power devices are due to failures in distribution networks. Therefore, it is essential to locate the fault in the distribution network, because it will help to fix the fault in the shortest possible time and return the system to its normal operation. Impedance methods are often used to fault location in power distribution networks. The main drawback of impedance-based methods is multi-point estimation. As a result, these methods indicate the location of the fault accurately but not definitively. This problem is known as the multiple estimation problem, which causes more cost and time to recover the line. By adding the error indicator, these points are reduced and even disappeared in some basses. In this thesis, a fault location strategy based on the impedance method and with the help of the optimal number of voltage gauges and fault indicators is presented. The studied network is the real network. Fault location has been done for several scenarios and their differences have been investigated. Finally, by using multi-objective genetic algorithm, the number and arrangement of gauges and indicators have been optimized.

The global electricity industry is facing many challenges that require immediate attention towards growth, expansion and energy management Most of the electricity supply companies are facing shortfall of availability of electrical energy. Therefore to make up for the shortfall of the electrical energy availability, reducing losses and hence saving energy becomes the first and foremost important step as a part of demand side management. Application of smart grid technologies is one of the key tools in solving the problems faced by electricity industry. In this direction determination of optimal location of the distribution transformer is an important issue to be addressed. The electricity supply companies do not seem to use any proved method to find the optimal location of the distribution transformer. Moreover in many cases distribution transformers can not be placed in the optimal position due to socio-political and economical considerations which will result in higher losses. Numerical studies in this thesis have been done on a real distribution system. The said network is a part of the Sanandaj distribution network called Hossein Abad feeder, whose main feeder is 20 kV and its sub feeders are 20 kV or 400 volts. In total, this feeder has 6306 busbars and, accordingly, 6306 lines because it is a radial network and has a tree graph. All load distribution calculations and the proposed algorithm program have been carried out in order to be implemented in the study distribution network using MATLAB software.

Transformers have been one of most expensive and all-purpose equipment in electrical power network. Current fault diagnosis methods aren’t capable to detect the types of faults. Therefore, in addition to common protective methods, using transformers monitoring systems is necessary to prevent, diagnose and inhibit the rapid and extensive growth of defects. Timely diagnosis and notification in primary stages caused the stability of electrical network and prevention of serious damage to transformer and other network-connected equipment. Although protective equipment could diagnose different internal faults, they aren’t able to diagnose partial faults and mechanical deformations like Displacement, and minimal Winding deformation. Latter deformation caused voltage gradient change, as a result, early insulation aging and partial discharge. In this thesis, to improve study precision, it was used finite-element method – based software to model transformer and coil mechanical defects. At first, C, L and R matrices to extract healthy mode of transformer, then they were retrieved by imposing three faults: Axial Displacement, Radial Deformation, and Disc space variation with different intensities and locations, Obtained values were compared to healthy mode To examine the extent and manner of changes in the elements of the above matrices. At following, various algorithms were used to classify faults in regard to type, intensity and location by means of C, L and R matrices arrays. The accuracy of the classification is compared by the same algorithm for each of the parameters and the sensitivity of the parameters to the fault is investigated. Of different transformer fault diagnosis methods, frequency response analysis is more reliable to diagnose Winding mechanical because of its higher sensitivity to small changes in Winding geometry. Here, frequency response was considered by means of EMTP software, with transformer modelling through matrices extracted from finite element method for defected and healthy modes, and investigated type of fault, its location and intensity on different frequency response range. Finally, most applied statistical indicators, computed from frequency response in healthy and defected modes, were used for classification of faults.

In most industrial processes, the use of electric machines is common, and among the types of electric machines, three-phase induction motors have received more attention due to their special structural features and economic efficiency. Also, the wide use of these engines and the importance of stops in the processes have made the timely and accurate error detection of these engines an important issue. On the other hand, with the passage of time, the condition monitoring systems have been upgraded to detect the fault of three-phase induction motors, and currently, any type of fault occurring in these motors can be identified and evaluated with different methods with different degrees of accuracy. In this thesis, firstly, the construction, principles of operation of three-phase induction motors and their common errors are presented, then different methods of error detection are introduced and the advantages and disadvantages of each are stated. In the following, the behavior of the induction motor at high frequencies is investigated, and in the following, the behavior of the induction motors at high frequencies is investigated, and equivalent circuits are used to better understand the performance of the motor at high frequencies. It has the power to diagnose faults in transformers, in this thesis it is used to diagnose faults in three-phase induction motors. Because the principles of the frequency response analysis method are based on the comparison of the results with the reference response, in this thesis, a large number of common errors such as stator winding errors, bearing errors, poor installation and rotor rod breakage errors have been tried to be applied to the motor in a practical way. Induction was applied and numerical data were collected and recorded with WK6500B analyzer and the resulting data were simulated and analyzed using MATLAB software. The result of the frequency response of the faulty state has been compared with the reference curve (frequency response in the healthy state), CC, SIGMA, NRMSD and CSD statistical indices have been used to check the changes and analyze the results of the frequency response. In order to increase the validity of the results of the tests and further investigation, the diagnosis of the above-mentioned common errors has been carried out online with the exp3000 online test device and the results have been presented.