مجله کیفیت و بهره وری صنعت برق ایران
سال یازدهم شماره 1 (پیاپی 26، بهار 1401)

Power transformers are one of the most vital and expensive devices in the electricity transmission and distribution network. Therefore, monitoring and evaluating their operational condition is a vital issue for managers in the electricity industry to prevent failure in the power distribution network, maintain their highly reliable performance, manage their assets, and increase the productivity of the network. The results of many research works have indicated that the useful life of a transformer is directly related to the life of its paper insulation system. The measurement of furan compounds released into the insulation oil due to the degradation of cellulose in insulation paper is a common method for assessing the operational condition of the transformers. High-performance liquid chromatography (HPLC) has been introduced as one of the relatively well-established methods for measuring furan compounds according to ASTM-D-5837. Regarding the need for high profession and expertise for operating and using HPLC system as well as the high price of this system, it is inevitable to develop fast, simple, cheap, and user-friendly systems and techniques with high precision without any need for high operator profession. The use of ultraviolet-visible (UV-Vis) spectroscopy has been proposed as a new, effective, and economically preferable alternative method for measuring the concentration of cellulose degradation compounds in insulation oil. However, the excessive turbidity of the oil in older transformers caused by the cellulose degradation products exerts a relatively high ambiguity on the results of this technique and may make its results somehow unreliable. In this paper, a new method is proposed to improve the optical spectrum results and solve the turbidity problem of the used oil samples. This method is composed of the dilution of oil samples with adequate solvents to overcome their high turbidity in combination with the fuzzy logic to evaluate the UV-Vis results. The proposed method was implemented on oil samples taken from 23 transformers. A fuzzy logic algorithm is used to estimate the furan compound contents from the optical spectrum of the oil. The comparison between the results of the method developed in this work and the results of HPLC analysis reveals a relative error as low as 11%, proving that the developed method can be a safe, fast, and cost-effective solution for electricity distribution network operators to assess and monitor the status of network transformers.

The countrys electricity industry, which is responsible for supplying, producing, transmitting and distributing electricity in the country, needs to pay attention to creative approaches. This can be seen in the review of jobs related to this industry, as about fifty percent of jobs in this industry require creativity skills, and not paying attention to strategies and targeted measures to promote organizational creativity can challenge the industry in the near future. Face basic. In this study, by considering the main and secondary questions regarding the selection of appropriate organizational creativity strategy in the electricity industry, by collecting the opinions of electricity industry experts, the factors and conditions affecting organizational creativity were determined and using content analysis technique. Interpretive The results of the interviews with the experts were analyzed. Using the three-step approach of data-driven theory, the phenomenon of non-creativity was studied in an inductive manner at each level, and the relationships between the phenomenon, causal conditions, mediating conditions, strategy and strategy and the consequences of each strategy were obtained. At the individual level, non-creative phenomena were categorized into 5 categories and 58 codes. At the team or unit level this phenomenon was categorized into 5 categories and 36 codes, at the organization level it was categorized into 5 categories and 42 codes and at industry level this phenomenon was categorized into 5 categories and 40 codes. This model can be used in other areas of government.

There is an increasing demand for low-cost single-phase DC–AC inverters in many applications such as PV systems. PV system may be used without the transformer to improve efficiency and make the whole system lighter, smaller, and easier to install. Using transformerless topology, the system efficiency may be increased by about 2%, and the related cost may be decreased by about 25%. There are large leakage currents in transformerless topologies, especially in photovoltaic systems, where safety issues and electromagnetic interference problems often occur. To overcome such disadvantages, common-ground topologies can be used, which minimize the leakage current of the transformerless inverter ones. The transformerless semi-quasi-Z-source inverter (SqZS) with a common-ground structure offers many advantages over conventional single-phase inverters. Leakage current elimination, high power density, lower components, and low-cost features make it an attractive option as a micro-inverter in photovoltaic applications. The basic topology of SqZSI is especially suitable for a PV module in the low-voltage application as a low-cost micro-inverter with high-voltage SiC switching devices. However, the unity voltage gain is one of the disadvantages of the SqZS inverter, which is referred to as a drawback; In other words, the conventional structure of SqZS is not able to step up the voltage and the maximum amplitude of AC voltage that can be extracted is equal to the input DC voltage; Therefore, in this paper, a modified structure of single-phase inverter (MSqZS) is proposed to achieve voltage boost capability. The voltage boost is achieved in a single-stage conversion just by adding an additional series DC blocking capacitor to the basic inverter. It also maintains the common-ground feature. Nonlinear sinusoidal modulation (NLSPWM) is modified to allow the SqZS basic structure to achieve high voltage gain. However, the proposed inverter is modified in topology and modulation; its complexity is not increased in comparison to the basic SqZSI. The proposed inverter has the least number of components than the similar step-up common-ground topologies. In this paper, the closed-loop control is proposed to improve the performance of the MSqZS under variable input voltage as well as output load and compensation for the undesired and non-ideal effect of the parasitic elements. In addition, the proposed inverter is also capable to generate reactive power. Also, the design considerations for series capacitor is analysed for proper capacitor selection. The simulation and experimental results under various closed-loop and open-loop scenarios comply with the IEEE Std 1547 and verify the appropriate performance of the proposed inverter.

Dissolved gases in transformer oil indicate the occurrence of a fault in the transformer. Many standards use the ratio of dissolved gases in transformer oil to detect faults in transformers. These traditional methods cannot, however, be used in cases in which the transformer needs to be immediately removed from service in case of a serious error such as electric arcs to prevent the error from spreading. For this purpose, this paper uses signal processing methods that analyze the signal online. The paper assumes that CO and CO2 dissolved gases in transformer oil are measured online by a sensor and then some signal processing methods are applied to the measurement data. These methods include Fast Fourier Transform, Discrete Wavelet Transform, Hilbert Transform, Gabor Transform, the combination of discrete wavelet and Hilbert transform, the combination of discrete wavelet and Gabor transform, and spectrogram. These methods are continuously applied to these two gases that are soluble in transformer oil to determine their variations in the transformer oil at a certain time or a certain frequency. The gases are also modified and then the performance of each of the processing methods mentioned in these changes is investigated. Fault detection reference is the CIGER 761-2019 standard. The purpose of this paper is to find out the samples of gases change in a frequency interval or timeframe together irrespective of the faults in the transformer and changes in the volume of dissolved gases in transformer oil, analyze the signal processing methods, and detect the type of fault using CIGRE 761-2019 standard. The fast Fourier transform method analyzes signal power by frequency. The discrete wavelet transform method extracts high-frequency components of gases and detects faults based on the largest components. The Hilbert transform method converts the signal into two real and imaginary parts. Then, it uses the imaginary part that represents the signal phase to detect faults. The Gabor transform method extracts instantaneous frequencies in the time-frequency plane and uses this method to detect faults. In the methods that combine discrete wavelet transform and Hilbert or Gabor transform, high-frequency components are extracted by discrete wavelet transform, and then Hilbert or Gabor transform methods are applied. The spectrogram method also indicates the size of the short-time Fourier transform, which is used to analyze the signal. These signal processing methods are compared in several features, and the discrete wavelet transform method is introduced as the best method for fault detection.

Low impedance differential relays are widely used in the protection systems of power transformers. While being highly reliable, differential relays can misidentify the inrush currents generated during the switching of power transformers as faults and issue a tripping command when one is not needed. Therefore, these protection systems need a mechanism to differentiate between inrush currents and faults in order to prevent unnecessary activation. Accordingly, this paper presents a new method based on a group method of data handling (GMDH) neural network for differentiating faults from inrush currents. The proposed method can quickly detect a wide variety of faults that may occur simultaneously with inrush currents and is perfectly noise-resistant. The proposed method is compared with the conventional methods used in the industry, namely second harmonic and zero-crossing methods. The results demonstrate the ability of the proposed method to outperform conventional methods under a wide variety of operating conditions.

Power systems are complex systems that are not easy to understand and analyze. Also, many faults and incidents occur in these systems, many of which are mended without human interference. Meanwhile, electricity companies are responsible for the security of power systems and operators because if any part of the power system acts as an unwanted island, it may be unsafe for grid personnel and may result in serious damages to grid equipment. Therefore, it is important and necessary to identify the parts of the grid, which have become islands, and apply load shedding to abolish these islands. This paper proposes a new approach for load shedding in the islanded microgrid in the presence of distributed generations. Features of the proposed method include high flexibility, speed, and accuracy. The proposed method is simulated by powerful DIgSILENT software, and the simulation results support the capability of the proposed method.

This paper presents a method for detecting the location of partial discharge in medium voltage covered conductor (CC) lines. The use of CCs is increasing day by day due to higher reliability, less susceptibility to climate change, and fewer short circuit faults than overhead lines.  CCs are commonly used in forests.  The lack of rapid failure detection of protection relays when the tree falls on the CC is one of its most important disadvantages. Scratching of CC insulation due to a tree falling on it usually leads to partial discharge (PD), which can lead to short circuit faults in the long run. Because the CC may be installed in an impassable path, it is difficult to detect a tree falling on the CC or the growing foliage colliding with the CC, and if not done promptly, it can lead to a short circuit fault. In this paper, for the first time, while obtaining a three-phase CC model, the falling of a tree on CC is simulated by applying a PD pulse source at the desired location. The proposed method is that first the PD signal is applied at the location of the electrical posts and the waveform obtained at the end of the line is stored and then their FFT is calculated as reference signals. To find the location of an unknown location PD, the signal obtained at the end of the line is saved after eliminating its main component of frequency and noise. Afterward, its FFT is calculated. Then, using the method of maximum correlation of signals, the nearest electric pole to the location of PD is determined. The proposed method was applied in different cases in a sample system, and satisfactory results were obtained.

One of the most important pieces of equipment in power systems is the power transformer. The main task of transformers is to change the voltage level in the system to deliver the generated energy to the final consumers. Power transformers are the main components of power systems because, without them, power transmission from the power plants to the consumers is not practically possible. Therefore, the importance of power transformers makes their protection a crucial issue. Differential relay is the relay most commonly used to protect power transformers throughout the world. Despite their many advantages, these types of relays may operate incorrectly during the magnetizing inrush current of the transformer and cause the healthy transformer to be separated from the power network. Thus, using some appropriate techniques to cope with this problem is necessary for power transformer protection. In a power network, the sampling rate can significantly impact the performance of the protection system. In this case, as the sampling rate increases, the computational complexity also rises. On the other hand, if the sampling rate decreases, it can reduce the accuracy of the protection system. Therefore, this paper presents a new method based on adaptive sampling and Hilbert transform to discriminate between inrush current and internal faults in a power transformer. The proposed method is also capable of detecting sympathetic inrush current. Besides, this method precisely detects various fault types and has an accurate performance when the current transformer is saturated, or the signal is noisy. The proposed method has been tested on a 230/63 kV transformer. The simulation results demonstrate that the proposed method has an appropriate performance during normal and sympathetic inrush currents. In addition, the proposed technique can distinguish between all fault types and

Optimal reactive power dispatch (ORPD), is one of the most challenging problems of power system operation. This problem deals with both system security and the economy. The problem’s objective functions are usually decreasing the voltage profile deviation of the system, improving the voltage stability margin, and decreasing system loss. ORPD is modeled as an optimization problem with nonlinear functions and constraint and mixed continuous/discrete decision variables. The decision variables are the reactive power of the generators and compensators and the tap number of the transformers. To consider the security of the system, the effect of unscheduled events must be modeled and investigated in the ORPD problem. This type of ORPD is called security constraint ORPD (SC-ORPD). However, the uncertain nature of power systems makes it inevitable to consider them in planning issues. These uncertainties are the source of risk in power grids and must be addressed in planning issues, including ORPD. Risk is the possibility of something bad happening. In other words, risk involves uncertainty about the effects of an activity. Therefore, risk functions include a combination of the probability of an event and its impact. Considering deterministic objective functions (not risk-based ones) in ORPD problems may decrease system economy because most of the events are rare in power system operation. In addition, due to low event probability, the calculated risk may not reflect the true risk that operators and networks are facing. These uncertainties are classified into two categories: technical and economic. Technical uncertainties, which affect the system security, include network topology and operation (like demand and generation) whereas economic uncertainties include micro and macro economies. This paper presents, security-constrained optimal reactive power dispatch by considering the technical uncertainties of power systems. Maximizing the voltage stability margin based on the new voltage instability risk index and minimizing losses are the technical and economic objective functions, respectively. The proposed index is more compatible with practical criteria than existing indicators because it excludes the effect of the low events outage probability of power system components on the risk index. The SPEA-II optimization algorithm is then used to find non-dominant solutions, and finally, the fuzzy decision-maker is used to select the dominant solution. The proposed method is applied to standard 30 IEEE-bus system. The results show, that the proposed algorithm is superior to existing methods and increases the voltage stability margin for postulated contingencies and at the same time reduces operating costs.

One of the most common types of wind turbines (WTs) is the Doubly-Fed Induction Generator (DFIG) with a back-to-back converter. The power converter with an Insulated Gate Bipolar Transistor (IGBT) switch is essential equipment for power regulation and grid connection in WTs. The converter IGBT open-circuit causes a drawback in output current and as a result, the production performance of the turbine is reduced. Condition Monitoring (CM), Fault Diagnostic (FD), and Fault-Tolerant Control (FTC) of a WT increase the reliability and availability of the turbine and are typical methods to reduce energy production costs and WT downtime. The IGBT switch’s open-circuit failure rate is significant compared to the overall fault rate in WTs. This paper discusses IGBT open-circuit FTC in back-to-back DFIG converters. In the proposed structure, the converter switch fault is first diagnosed using a fast and numerical method. In the first part, a method based on normalized phase currents, the absolute of the phase currents, and an adaptive threshold is used. The FTC system can be divided into two classes of redundancy and non-redundancy or into active and inactive classes. In this article, the proposed method is active and non-redundancy. In the second step, the FTC process is activated to compensate for the system degradation. In this method, the faulty leg is removed with the gate opening of both IGBTs in one leg by the controller, and one of the legs is positioned as a common leg between the two grid side and rotor side converters. The conventional method in this structure is to use Pulse Width Modulation (PWM) with a zero sequence signal. The novelty of the paper is the use of the proposed SVM vector control. The proposed structure is inexpensive. Furthermore, the fault diagnostic structure operates without additional sensors and the FTC structure operates with minimal hardware. To evaluate the proposed structure, a 2.5 MW turbine software simulator based on real data is used. The simulations show that the proposed method is effective and robust in FD and FTC and that the proposed method is successful in detecting multiple defects of the grid-side and rotor-side converters, as well as the defects of one leg. The proposed method can compensate for the open switch fault to construct three-phase output currents by comparing the numerical parameters. The ability of the proposed method is specified.