Метод идентификации одиночных утечек тока в фазах распределительной сети, контролируемой автоматизированной системой учета

The paper dwells upon a 0.4-kV four-wire three-phase distribution grid (DG), where energy consumption is monitored by an automated metering system. Phase wires are assumed to have equal unknown non-neutral resistance in each inter-customer section of the DG; the metering system measures the operating voltage, current, and phase angles between the customers as well as at the DG entry point. The paper dwells upon finding the values of, and locating the leakage currents resulting from unauthorized power outtake. It analyzes an earlier proposed method that relies on phase (linear) wire voltage increments to simulate disturbed and desired state of the DG; analysis reveals the disadvantages of this method. The paper further presents a novel solution based on calculating the grid parameters (resistances) and currents in real time. The paper also proposes an algorithm for calculating the grid parameters, which samples data from two different modes of DG operation. Mathematical expressions are shown herein that implement this method and have been tested by computational experiments. The results could be of use in the design of non-process electricity loss metering systems for distribution grids.В работе рассматривается четырехпроводная трехфазная распределительная электрическая сеть (РЭС) напряжением 0,4 кВ, в которой выполняется контроль энергопотребления автоматизированной системой учета. Предполагается, что в РЭС на каждом межабонентском участке сопротивления фазных проводов равны и отличаются от нейтрального, причем их значения неизвестны, а системой учета выполняются измерения действующих напряжений, тока и угла сдвига фаз между ними у всех абонентов и в начале РЭС. Решается задача идентификации значений и места отвода токов утечки вследствие воздействия на РЭС несанкционированных отборов электроэнергии. Проведен анализ предложенного ранее метода, использующего приращения напряжений фазного (линейного) провода для моделированного возмущенного и желаемого состояния РЭС. Показаны его недостатки и представлен новый метод решения указанной задачи, основанный на оперативном расчете и анализе параметров (комплексных сопротивлений) распределительной сети и их токов. При этом предложен алгоритм для расчета параметров сети, для которого необходимы данные двух разных режимов работы РЭС. Получены математические выражения, реализующие предлагаемый метод, проверенные вычислительными экспериментами. Полученные результаты могут быть полезны при разработке систем учета и мониторинга нетехнических потерь электроэнергии в распределительных сетях

CPS Attacks Mitigation Approaches on Power Electronic Systems with Security Challenges for Smart Grid Applications: A Review

This paper presents an inclusive review of the cyber-physical (CP) attacks, vulnerabilities, mitigation approaches on the power electronics and the security challenges for the smart grid applications. With the rapid evolution of the physical systems in the power electronics applications for interfacing renewable energy sources that incorporate with cyber frameworks, the cyber threats have a critical impact on the smart grid performance. Due to the existence of electronic devices in the smart grid applications, which are interconnected through communication networks, these networks may be subjected to severe cyber-attacks by hackers. If this occurs, the digital controllers can be physically isolated from the control loop. Therefore, the cyber-physical systems (CPSs) in the power electronic systems employed in the smart grid need special treatment and security. In this paper, an overview of the power electronics systems security on the networked smart grid from the CP perception, as well as then emphases on prominent CP attack patterns with substantial influence on the power electronics components operation along with analogous defense solutions. Furthermore, appraisal of the CPS threats attacks mitigation approaches, and encounters along the smart grid applications are discussed. Finally, the paper concludes with upcoming trends and challenges in CP security in the smart grid applications

Energy Data Analytics for Smart Meter Data

The principal advantage of smart electricity meters is their ability to transfer digitized electricity consumption data to remote processing systems. The data collected by these devices make the realization of many novel use cases possible, providing benefits to electricity providers and customers alike. This book includes 14 research articles that explore and exploit the information content of smart meter data, and provides insights into the realization of new digital solutions and services that support the transition towards a sustainable energy system. This volume has been edited by Andreas Reinhardt, head of the Energy Informatics research group at Technische Universität Clausthal, Germany, and Lucas Pereira, research fellow at Técnico Lisboa, Portugal

Intelligent machine learning with evolutionary algorithm based short term load forecasting in power systems

Electricity demand forecasting remains a challenging issue for power system scheduling at varying stages of energy sectors. Short Term load forecasting (STLF) plays a vital part in regulated power systems and electricity markets, which is commonly employed to predict the outcomes power failures. This paper presents an intelligent machine learning with evolutionary algorithm based STLF model, called (IMLEA-STLF) for power systems which involves different stages of operations such as data decomposition, data preprocessing, feature selection, prediction, and parameter tuning. Wavelet transform (WT) is used for the decomposition of the time series and Oppositional Artificial Fish Swarm Optimization algorithm (OAFSA) based feature selection technique to elect an optimal set of features. In order to improvise the convergence rate of AFSA, oppositional based learning (OBL) concept is integrated into it. Then, the water wave optimization (WWO) with Elman neural networks (ENN) model is employed for the predictive process. Finally, inverse WT is applied and obtained the hourly load forecasting data. To validate the effective predictive outcome of the IMLEA-STLF model, an extensive set of simulations take place on benchmark dataset. The resultant values ensured the promising results of the IMLEA-STLF model over the other compared methods

K-Means and Alternative Clustering Methods in Modern Power Systems

As power systems evolve by integrating renewable energy sources, distributed generation, and electric vehicles, the complexity of managing these systems increases. With the increase in data accessibility and advancements in computational capabilities, clustering algorithms, including K-means, are becoming essential tools for researchers in analyzing, optimizing, and modernizing power systems. This paper presents a comprehensive review of over 440 articles published through 2022, emphasizing the application of K-means clustering, a widely recognized and frequently used algorithm, along with its alternative clustering methods within modern power systems. The main contributions of this study include a bibliometric analysis to understand the historical development and wide-ranging applications of K-means clustering in power systems. This research also thoroughly examines K-means, its various variants, potential limitations, and advantages. Furthermore, the study explores alternative clustering algorithms that can complete or substitute K-means. Some prominent examples include K-medoids, Time-series K-means, BIRCH, Bayesian clustering, HDBSCAN, CLIQUE, SPECTRAL, SOMs, TICC, and swarm-based methods, broadening the understanding and applications of clustering methodologies in modern power systems. The paper highlights the wide-ranging applications of these techniques, from load forecasting and fault detection to power quality analysis and system security assessment. Throughout the examination, it has been observed that the number of publications employing clustering algorithms within modern power systems is following an exponential upward trend. This emphasizes the necessity for professionals to understand various clustering methods, including their benefits and potential challenges, to incorporate the most suitable ones into their studies

Introduction to Development Engineering

This open access textbook introduces the emerging field of Development Engineering and its constituent theories, methods, and applications. It is both a teaching text for students and a resource for researchers and practitioners engaged in the design and scaling of technologies for low-resource communities. The scope is broad, ranging from the development of mobile applications for low-literacy users to hardware and software solutions for providing electricity and water in remote settings. It is also highly interdisciplinary, drawing on methods and theory from the social sciences as well as engineering and the natural sciences. The opening section reviews the history of “technology-for-development” research, and presents a framework that formalizes this body of work and begins its transformation into an academic discipline. It identifies common challenges in development and explains the book’s iterative approach of “innovation, implementation, evaluation, adaptation.” Each of the next six thematic sections focuses on a different sector: energy and environment; market performance; education and labor; water, sanitation and health; digital governance; and connectivity. These thematic sections contain case studies from landmark research that directly integrates engineering innovation with technically rigorous methods from the social sciences. Each case study describes the design, evaluation, and/or scaling of a technology in the field and follows a single form, with common elements and discussion questions, to create continuity and pedagogical consistency. Together, they highlight successful solutions to development challenges, while also analyzing the rarely discussed failures. The book concludes by reiterating the core principles of development engineering illustrated in the case studies, highlighting common challenges that engineers and scientists will face in designing technology interventions that sustainably accelerate economic development. Development Engineering provides, for the first time, a coherent intellectual framework for attacking the challenges of poverty and global climate change through the design of better technologies. It offers the rigorous discipline needed to channel the energy of a new generation of scientists and engineers toward advancing social justice and improved living conditions in low-resource communities around the world