Power Supply Interruption Research Articles

Assessment of electric energy transport reliability (as exemplified by JSC "Rosseti Siberia Tyvaenergo" power networks)

Analysis of electric energy transport by power distribution networks of JSC Tyvaenergo over the period of 2017 – 2022 has been carried out. The structure of the company is considered, the characteristics of the main elements of the studied electric networks are given, the balance of the transmission of electric energy in and out of the company's networks is estimated. Based on the information published in open sources on the rate of accidents in the company's electrical networks, an estimate has been made of the number of emergency situations that occurred during the period under study. The duration of interruptions of power supply to consumers, as well as the amount of undersupply of electric energy caused by those interruptions, has been estimated. The influence of the seasonal component on the number of emergencies during the period under study is considered. Based on the data for the last quarter of 2022, analysis of the main causes of damage to elements of electrical networks has been carried out. The classification of failures is made, their main characteristics for this period are considered. The percentage ratio of the number of failures for the most characteristic reasons to the total number of outages during the period under study has been established. A technical tool is proposed to improve the reliability in conditions of unbalanced power consumption. General scientific methods, numerical methods of analysis, methods of the theory of electrical circuits were used in the research. To visualize the results of the analysis, the technologies of the MATLAB graphics editor were used. The results obtained may be of interest to the heads of power grid companies, as well as researchers and engineers engaged in research in the field of reliability of power supply.

Drone-Robot to Clean Power Line Insulators.

The inspection and maintenance of transmission systems are necessary for their proper functioning. In this way, among the line's critical points are the insulator chains, which are responsible for providing insulation between conductors and structures. The accumulation of pollutants on the insulator surface can cause failures in the power system, leading to power supply interruptions. Currently, the cleaning of insulator chains is performed manually by operators who climb towers and use cloths, high-pressure washers, or even helicopters. The use of robots and drones is also under study, presenting challenges to be overcome. This paper presents the development of a drone-robot for cleaning insulator chains. The drone-robot was designed to identify insulators by camera and perform cleaning through a robotic module. This module is attached to the drone and carries a battery-powered portable washer, a reservoir for demineralized water, a depth camera, and an electronic control system. This paper includes a literature review on the state of the art related to strategies used for cleaning insulator chains. Based on this review, the justification for the construction of the proposed system is presented. The methodology used in the development of the drone-robot is then described. The system was validated in a controlled environment and in field experimental tests, with the ensuing discussions and conclusions formulated, along with suggestions for future work.

Issues of electric energy transport reliability (on example of JSC Krasnoyarskenergosbyt)

Analysis has been performed of the transmission of electric energy through the power distribution networks of PJSC Krasnoyarskenergosbyt over the period of 2016 – 2022. The structure of the company is considered, the characteristics of the main elements of the studied power networks are given, the degree of wear of the main electrical equipment is estimated. Based on the information from public media on the level of accidents in the company's power networks, an estimate has been made of the number of emergencies that occurred during the study period, the share of self-healing failures in the total amount of damage has been determined. The duration of interruptions of power supply to consumers, as well as the amount of undersupply of electric energy caused by these interruptions, has been estimated. The influence of the seasonal component on the number of emergencies during the study period is considered. Based on the data for the first half of 2022, the analysis of the main causes of damage to the elements of electrical networks has been performed. The classification of failures is made, with their main characteristics over the period under study considered. The possibility of using various methods of forecasting the reliability level of the power networks under consideration is evaluated. The results of the analysis of the use of statistical and cybernetic methods of preventive assessment of undersupply of electrical energy are presented. Based on the comparison of the results obtained, it is concluded that statistical methods are the most effective. The research uses general scientific methods, numerical methods of analysis, methods of the theory of electrical circuits, theories of mathematical statistics, data interpolation and forecasting. To visualize the results of the analysis, the technologies of the MATLAB graphics editor were used. The results obtained may be of interest to the heads of power grid companies, as well as researchers and engineers engaged in research in the field of reliability of power supply.

Modeling of Electrical Systems for Uninterrupted Operation of Drives in Case of Short-Term Distortions in the Supply Networks

The article considers the problem of increasing the stability of an electrical system with running synchronous and asynchronous electric motors, which are electrically connected through an intra-factory network and for which the operating modes affect the stability of the entire load. A method is proposed for studying electrical systems with an electric motor load to assess the effect of short-term power supply interruptions (voltage dips) in supply networks on the dynamic stability of synchronous and asynchronous drives. The influence of considering operating synchronous and asynchronous electric motors on transient processes and levels of residual voltages of sections was studied. It was found that to ensure the stability of the drives, to avoid shutdowns in case of various types of short circuits, it is desirable to use an automatic reserve input with a response time of less than 12 ms. A device for the instantaneous activation of a reserve is proposed, providing a response time of 9 ms and a total switching time to a reserve input within 17 ÷ 65 ms. The results of experiments and calculations according to the author’s developed programs are presented, confirming the possibility of the uninterrupted operation of technical electric systems consumers. The requirements for such automation devices are determined.

A normalized Haar wavelet transformation based firefly optimization algorithm for power transmission line fault detection problems

ABSTRACT Through transmission lines (TLs), an electric power transmission system has been able to transmit power from generating stations to consumers. During transmission, various kinds of malfunctions take place and they are termed as a fault. Although fault is undesirable, it is unavoidable event hampering the smooth functioning of the power system. In power transmission systems, and a large number of voltage and current signal, distortions take place due to faults. Faults occur in power TL causing power supply interruption. Several fault detection techniques have been presented by researchers to detect a fault in TL. However, the time required to locate the fault remained higher and the power loss rate (PLR) was not reduced. To overcome these issues and identify faults in electrical power TL, Haar wavelet feature extraction-based firefly optimized fault detection (HWFE-FFOFD) method has been introduced. The power TL signal sample has been taken as an input. Zero-mean normalization is the pre-processing approach that converts the transmission signal sample into a specified range. To extort features (i.e. voltages and current values) with higher accuracy, the normalized signal has been given to Haar Wavelet Transform. Then, the extracted features at different time instants have been given to the firefly optimized fault detection (FFOFD) algorithm. In the FFOFD algorithm, extracted features have been considered as firefly populations. The FFOFD algorithm functions with the flashing behavior of a firefly. At last, the firefly position has been updated and ranked according to light intensity to detect a fault in electrical power TL. In this manner, the fault detection time (FDT) gets reduced using HWFE-FFOFD method. HWFE-FFOFD method is evaluated in FEA, FDT, and PLR. From the experimental results obtained, it can be confirmed that the HWFE-FFOFD method has been able to enhance accuracy by 14% and minimize time by 26% and PLR by 62% when compared to conventional methods.

Voltage Optimization Control and Risk Assessment Technology for High-proportion Distributed Photovoltaic Access to Distribution Network

The high proportion of distributed photovoltaic connected to the distribution network will lead to an increase in terminal voltage and network loss, which will not only generate many adverse effects on the safe and reliable operation of the distribution network but also easily lead to power supply disconnection and power supply interruption accidents caused by voltage out of limit. At present, the voltage control of the distribution network does not fully consider the regulation characteristics of the photovoltaic inverter itself and ignores the impact of different control methods on the distribution network security risk management and control. Therefore, this paper establishes a voltage closed-loop control model for high-proportion distributed photovoltaic access to the distribution network and proposes a real-time active voltage optimization control strategy with the goal of minimizing the deviation of the actual operation state of the distribution network from the scheduling plan. Finally, a typical industrial park is taken as a case for calculation and analysis. The results show that using real-time data to formulate a real-time voltage optimization control strategy can not only ensure the economic operation of each voltage regulating unit in the distribution network but also reduce operational risks. The control method proposed in this paper provides a new idea for improving the voltage control level of distributed photovoltaic access distribution network and fully guarantees the operation reliability of the entire distribution network.

Discount as an Example of a Guarantee Instrument in the Field of the Consumer’s Right to Energy of an Adequate Quality

The European Union obliged the member states to introduce monitoring and control tools in order to improve the quality of provided transmission services and to guarantee the contracted amount of energy to end users. However, the EU has left the member states the freedom to create and implement compensation tools, enabling customers to claim their rights arising from non-compliance by transmission companies with the provisions of distribution agreements. The introduction of quantitative energy monitoring and an appropriate compensation mechanism is of great importance not only for end users but also for distribution companies. For end users, this would be a tool to enforce their rights against transmission companies, while transmission companies would gain a tool to control and manage both legal and financial risks. The aim of this study is to analyze discount as an example of a guarantee instrument in the field of the consumer’s right to energy of an adequate quality based on the Polish example supported by a systematic legal review. In the EU, discount is not regulated directly at the EU level; hence, it is impossible to base it on acquis and analyze it through the prism of EU regulation. In Poland, the possibility for recipients to apply for a discount for poor-quality electricity was introduced into the first version of the Energy Law in 1998, long before the adoption of Directive 2019/944 by the EU. The fundamental issues that were addressed and discussed in this paper were as follows: (1) Is the discount compensatory in nature? (2) Should it be included in the compensation due to the consumer? (3) Is it possible to reduce it when the power supply interruption results from circumstances beyond the control of the energy company (e.g., unforeseen weather conditions)?

English

The development of renewable energies is essential to meet the energy demand which is growing year after year. Africa has a strong solar potential which is, however, little exploited. The development of solar photovoltaic (PV) energy will be more favored with the democratization of performance monitoring and characterization tools for PV systems. Monitoring systems are very important because they allow the monitoring of the operation and control of PV installations in order to reduce maintenance costs and avoid undesirable power supply interruptions. There are several monitoring systems, more or less efficient, proposed on the market but they are often too expensive and not adapted to all existing systems. This paper presents a low-cost electronic board for monitoring and characterizing photovoltaic systems. The designed board is based on the ATMega328 microcontroller of the open-source development platform Arduino. It is composed of four blocks that allow the acquisition of electrical and environmental parameters. The board has been tested in monitoring mode with the follow-up of a small PV solar installation. The results of these experiments are consistent with what is found in the literature. Its use in characterization mode has allowed to obtain, in real time, the current-voltage and power-voltage characteristics. Compared to the results of the IV-500W tracer, the characterization results are consistent with an RMSE of 0.81 in voltage and 0.15 in current on all points measured. The design work is completed with the PCB design on Altium designer which resulted in the Gerber file. Key words: Microcontroller, photovoltaic (PV) monitoring, PV characterization, PCB.

Effectiveness n Online Professional i Education: Influences of Technology, Lms, Personal Factors and Teaching Aids

Abstract: Student learning through online tools during the pandemic covid-19 situation has been studied and reported in this paper. Students pursuing engineering under graduation and business management post graduation were given a Google form to respond to questions related to type and kind of online platform used, difficulties in teaching-learning, expectations of students etc. Suggestions were invited for better learning online. This paper presents the results of the feedback of students on technical and non-technical issues during online learning. The online environment is sub-divided into four broad categories viz., technological, personal, teaching aids and learning management system. Influence of these parameters on effectiveness of online teaching and feedback from students are discussed. Students had difficulties in internet network, bandwidth, clarity of audio-visual, interruptions in power supply, wifi-networks, poor infrastructure and affordability. 57 percent of respondents are dependent on mobile phone instruments for online class work. Majority of students felt that online certification courses can reduce burden to some extent. The results can be used for designing better online tools for effective online learning for students. Key words: Online learning platform, teachinglearning, difficulties in learning,

Изменение режима работы системы электроснабжения сети 6 кВ при переходе от изолированной нейтрали к резистивно-заземленной

The existing system of the electric network 6 kV used in the greenhouse facilities “Ovoshchi Krasnodarskogo kraya” with the insulated neutral does not ensure its reliable operation. Short single-phase short circuits in the network lead to ferroresonance, multiple short circuits and failure of power line sections and electrical equipment of the network up to the complete halting of greenhouse production. To eliminate ferroresonance processes and overvoltages in the electrical network and increase the reliability of the electrical supply system of the greenhouse facilities “Ovoshchi Krasnodarskogo kraya”, the authors have analyzed the effi ciency of an electrical supply system of 6kV network at its transition from the isolated neutral to the resistive-earthed neutral. They have determined the values of the capacitive currents of the electric network sections of the greenhouse facilities to show the excess of their allowable values. Based on the results obtained, they have stated the need for the modernization of the neutral grounding system of the electric network of the greenhouse facilities by transition to the neutral grounding through the low resistors used in commercially available transformer neutral grounding cabinets with the resistors 100 ohm for the 6 kV networks. The change in operating mode of the high-voltage network of the greenhouse enterprise from the isolated neutral to the resistive-grounded neutral ensured its reliable operation without interruptions of power supply and disconnection of its consumers. The network modernization has increased the current at the point of a single-phase short circuit to ground and provided the possibility of an immediate shut down of the damaged lines, thereby avoiding repeated short circuits in power lines and damage of electric equipment caused by ferroresonance. It has also reduced the probability of intermittent short-circuits, overvoltage in the network and electric shock to personnel and bystanders.1

INCREASING THE CAPACITY OF ELECTRICAL TRANSMISSION LINES IN THE POST-EMERGENCY MODE

Automatic switching on of the reserve (AVR) points are used to increase the reliability of power supply to consumers, which are advisable to install in distribution power networks and consumer networks for the power supply of production processes, the technology of which does not allow even short-term interruptions in power supply. The purpose of the research: substantiating the location of the AVR point for mutual redundancy of power transmission lines; determination of the effect of longitudinal capacitive compensation on the transmission capacity in the post-emergency mode; determining the impact of reactive power compensation on the economy of the post-emergency power transmission mode. The article considers a method of increasing the capacity of power transmission in the post-emergency mode, as a result of which an adjacent (reserved) line is connected to one of the working power transmission lines with a voltage of 10 kV using the point of automatic switching on of the reserve (AVR). However, the effectiveness of such redundancy in most cases turns out to be low due to the limited capacity of trunk sections of mutual-reserved lines with smaller cross-sections of wires at the end sections of both mutually-reserved lines, which were built as radials. As a result of such redundancy, there are increased losses of active power and voltage, and, as a result, unacceptable deviation of the voltage in remote nodes of the load of the redundant power transmission line. In order to improve the parameters of the operation mode of power transmission, it is proposed to use devices of longitudinal capacitive compensation and reactive power compensation in the scheme of the AVR point.

Design and Development of a Short-Term Photovoltaic Power Output Forecasting Method Based on Random Forest, Deep Neural Network and LSTM Using Readily Available Weather Features

Renewable energy sources (RES) are an essential part of building a more sustainable future, with higher diversity of clean energy, reduced emissions and less dependence on finite fossil fuels such as coal, oil and natural gas. The advancements in the renewable energy sources domain bring higher hardware efficiency and lower costs, which improves the likelihood of wider RES adoption. However, integrating renewables such as photovoltaic (PV) systems in the current grid is still a major challenge. The main reason is the volatile, intermittent nature of RES, which increases the complexity of the grid management and maintenance. Having access to accurate PV power output forecasting could reduce the number of power supply disruptions, improve the planning of the available and reserve capacities and decrease the management and operational costs. In this context, this paper explores and evaluates three Artificial Intelligence (AI) methods - random forest (RF), deep neural network (DNN) and long short-term memory network (LSTM), which are applied for the task of short-term PV output power forecasting. Following a statistical forecasting approach, the selected models are trained on weather and PV output data collected in Berlin, Germany. The assembled data set contains predominantly broadly accessible weather features, which makes the proposed approach more cost efficient and easily applicable even for geographic locations without access to specialized hardware or hard-to-obtain input features. The performance achieved by two of the selected algorithms indicates that the RF and the DNN models are able to generate accurate solar power forecasts and are also able to handle sudden changes and shifts in the PV power output.

ENHANCE EFFICIENCY OF SOLAR ENERGY CONVERSION SYSTEM USING ANFIS WITH ISOLATED MODE

This paper shows performance investigation on enhance efficiency of standalone solar energy conversion system using ANFIS based MPPT controller. Now a days many researches are going in the field of renewable energy technologies to bridge the gap between supply and demand. Due to the Intermittent nature of renewable sources, operating standalone operation of them is highly unreliable causes interruption in power supply to the load. A solar photovoltaic system with MPPT based on Adaptive-Network-Based Fuzzy Inference System (ANFIS) is used for stable operation and to meet the supply with the load demand. The application of ANFIS based MPPT technique requires detailed study and analysis of the Solar Photovoltaic (SPV) system. Adaptive-Network-Based Fuzzy Inference System based MPPT technique is used along with Solar PV system as they can provide fast and accurate response to various environmental conditions. The Levenberg-Marquardt algorithm is used to train the neural network for MPPT in the photovoltaic system. This developed control strategy is able to control the devices and various power interface circuitry used therein. The main aim of this paper is to ensure a maximum power output coordinating appropriate control strategy with sources & compare the performance analysis of the ANFIS based MPPT with conventional incremental conductance based MPPT for the SPV system. The simulation studies have been carried out to find out the SPV system performance with different input conditions such as typical solar radiation and temperature. The Simulation test results show variable power generation and verifies that the performance of the integrated system with this control strategy is effective for the real-time installation. The simulation results shows that the performance of this developed control strategy for receiving maximum power output from the standalone SPV system is farfetched. Simulation test results show variable power generation and verify the performance of the integrated system with control strategy is overall effective for real-time installation. The developed system is essential in an isolated region where an existing grid is unable to supply secure power generation and system is beneficial with smartly feed ultimate power generation sources.

Predictive risks assessment of power supply interruption to oil production consumers, taking into account changes in significant factors

THE GOAL. To develop a decision-making procedure for the commissioning of equipment in the power supply system of oil production facilities in accordance with the minimum risk criterion. To substantiate the effectiveness of its practical application in the tasks of equipment repair management with the "technical condition" strategy based on a risk-oriented approach.METHODS. When solving the tasks, the following methods were used: the flowchart method for calculating the structural reliability indicators of the distribution electrical network with changes in its operational composition and technical condition of elements (equipment), the method for predicting the risks of power supply disruption in the circuit of each technological consumer, taking into account the possibility of reserving and imposing emergency recovery of the main element on the planned repair of the backup, scenario approach for determining scenarios for changing the risk of power supply failures when the operating state of the electrical network circuit changes.RESULTS. As a result of solving the problems, the values of the structural reliability indicators of the studied distribution electrical network are calculated under the most likely scenarios of changes in its operational composition and technical condition of equipment, the features of the integrated assessment of the technical condition of objects of voltage class 6 kV in their operating conditions are considered. The functions of forecasting the probabilities of power supply failures of oil production facilities are obtained depending on the integral assessment of their technical condition, which, along with the severity of the consequences of failures, make it possible to predict risks.CONCLUSION. A computational procedure has been developed that includes mathematical models and an algorithm for prioritizing equipment with a strategy "according to technical condition" when putting it into repair based on a forecast of the risks of power supply disruption to consumers. On a concrete example, the verification of calculation models and algorithm was carried out, the effectiveness of the developed computational procedure and its applicability in solving practical problems of managing repairs of electrical equipment of oil production facilities based on a risk-oriented approach was shown.

Seismic Isolation and Reinforcement of Main Transformer in Substation

Due to the inadequate seismic capacity of the equipment in the substation, once the earthquake happens, the equipment takes the lead to collapse extremely. The interruption of power supply in the earthquake zone has caused great difficulties in the subsequent rescue efforts. Learning from the experience of seismic isolation in the construction industry and the features of the power equipment, this paper puts forward the seismic isolation and reinforcement method for the main transformer equipment in the built-up substation. Through the isolation design and analysis for the main transformer equipment in a particular project, the result shows that the isolation coefficient is about 0.4. In other words, the seismic energy transmitted to the main transformer equipment will be reduced by about 60% after adopting the seismic isolation and reinforcement methods, and the overall seismic capacity of the equipment will be significantly improved. After determining the isolation design scheme, the construction process of the overall isolation strengthening transformation is put forward. Combined with the specific engineering project, the isolation-strengthening transformation of the overall project is completed according to the corresponding construction process, the power is delivered successfully and the operation is carried out safely.

Recovery of missing field measured wind pressures on a supertall building based on correlation analysis and machine learning

In long-term field measurements and structural health monitoring (SHM), data loss sometimes occurs due to interruption of power supply, sensor failure, and disruption of data transmission, which inevitably affects subsequent data analysis and structural condition assessment. To address this issue, this paper proposes a novel data recovery method based on correlation analysis and machine learning (ML) for recovery of missing wind pressures on cladding of high-rise buildings in field measurements and SHM. The method first utilizes correlation analysis to select appropriate inputs of the ML model, and subsequently to recover the missing wind pressures using the ML model with the selected appropriate inputs. In this study, four ML models (i.e., data recovery models), including deep neural network (DNN), particle swarm optimization-DNN (PSO-DNN), extreme learning machine (ELM), and support vector regression (SVR), are developed based on the proposed data recovery method. The time series of wind pressures with non-Gaussian features, which were collected by a multi-point synchronous monitoring system on a 600-m-high skyscraper during Super Typhoon Mangkhut, are employed to validate the performance of the developed data recovery models. The results show that all the four ML models perform satisfactorily in the recovery of the missing time series of wind pressures, among which the PSO-DNN model performs best and has good recovery accuracy for data loss that occurs in different areas of building cladding. This demonstrates that the proposed data recovery method based on correlation analysis and machine learning is a reliable and effective tool to recover the missing time series of wind pressures on high-rise buildings under severe wind conditions. Notably, this is the first attempt based on field measurements to recover the missing time series of wind pressures with non-Gaussian characteristics on a skyscraper during an extreme typhoon event, which aims to provide a useful means for the recovery of missing monitoring data in field measurements and SHM.

Smart Grid Stability Prediction with Machine Learning

Smart grids refer to a grid system for electricity transmission, which allows the efficient use of electricity without affecting the environment. The stability estimation of this type of network is very important since the whole process is time-dependent. This paper aimed to identify the optimal machine learning technique to predict the stability of these networks. A free database of 60,000 observations with information from consumers and producers on 12 predictive characteristics (Reaction times, Power balances, and Price-Gamma elasticity coefficients) and an independent variable (Stable / Unstable) was used. This paper concludes that the Random Forests technique obtained the best performance, this information can help smart grid managers to make more accurate predictions so that they can implement strategies in time and avoid collapse or disruption of power supply.

Overhead Transmission Line Anti-External Force Damage System

In recent years, human production activities often lead to short-circuit grounding and other faults in overhead transmission lines, resulting in power supply interruption and economic losses, and traditional manual inspection methods are difficult to quickly find the cause and give early warning. In order to reduce the occurrence of such faults and ensure the reliability of power supply, the research on the anti-external force anti-damage system for overhead transmission lines is carried out in this paper. In this paper, the architecture of the anti-external force damage system for overhead transmission lines is designed, and an anti-external force damage algorithm for overhead transmission lines based on the improved R-FCN network model is proposed. have higher accuracy. The anti-external force damage system for overhead transmission lines designed and developed in this paper can realize real-time monitoring of the on-site environment of overhead transmission lines, and can quickly warn of various intrusions that may cause external damage, so as to avoid possible losses.

Maintenance Management Practices in Electricity Industry in Arab World: Case Study in Jordan

Nowadays, power plants, generators, substations, and equipment are becoming technologically more sophisticated and difficult to control besides that any interruption in power supply will cause losses to the industry and economy. Therefore, the importance of maintenance with enhancing availability, performance efficiency, on-time deliveries, safety necessities, and overall plant productivity become more necessary.
 In this context, the electricity industry in Arab countries is increasingly realizing the importance of the maintenance role. The main objective of this paper is to assess the maintenance management (MM) practices, operational performance, and issues faced by maintenance functions in Jordanian power companies as a representative case study for all Arab countries.
 A comprehensive survey methodology was developed, implemented, and presented to collect data in this study.
 To achieve this goal, a questionnaire was developed to analyze the requirements, and service difficulties, namely, maintenance planning, automation implementation, maintenance barriers, productivity measurements, staff training needs, and assessment. We then distributed the questionnaire to a selected sample of Jordanian electricity companies which has been filled out mainly through text surveys and personal interviews.
 The main obtained results of this study, related to maintenance practices and procedures that promote equipment availability, are summarized as increased use of predictive, intensive maintenance, computerized maintenance management systems (CMMS), and maintenance troubleshooting techniques. Additionally, more understanding of the company's development strategy and maintenance automation.
 Thus, a more comprehensive maintenance program has to be implemented, so that the enhancement of performance in the equipment availability can be attained.

Analysis of functioning of electric networks of the Irkutsk Electric Grid Company

The article presents the analysis of the Irkutsk Electric Grid Company activities over the years 2014–2021. The detailed characteristics of the company's balance activities in electric power transmission and its losses are presented, and the failure rate of the company's 0.38 to 500 kV electric networks is considered in detail. The number of failures of electric network elements for each year of the period under consideration, as well as the duration of power supply interruptions are determined. The ratio of self-recovering failures that are self-eliminated after actuation of automatic reclosing (AR) in the total volume of emergency situations has been found. The most characteristic periods of occurrence of the largest number of failures in the electric networks under consideration have been determined. The causes of failures have been considered in detail, and their analysis resulted in establishing that the key causes are the aging and wear and tear of electric network elements. The data are given on the percentage ratio of electric networks of several rated voltage classes, the service life of which exceeded the established normal values. The analysis is performed of the company’s financial expenses on development of electric networks and conformity of the planned measures to the fulfilled investments. It is established that the level of the company’s actual investments significantly exceeds the targets.The company's policy in reducing electric energy losses through the implementation of organizational and technical measures is analyzed.