A Comprehensive Survey on Electrical Distribution Systems

Smart grid is a power grid consists of extensive monitoring systems which deal with the monitoring of attributes such as current, voltage, power, and energy at distribution transformers, substations transformers, distribution switching devices and smart meters. Smart grid with advanced communication technologies can be used for several purposes such as efficiency and reliability improvement. IEC 61850 is the core standard in the smart grid domain for distribution and substation automation. This paper introduces a vision of modern substation and distribution systems using the IEC 61850. Network operators mainly assume that the modern substation and distribution systems based on the IEC 61850 are reliable for a long-time of operation. However, similar to any other systems, the implemented IEC 61850 might fail because of the operational failures or aging failures. This paper proposes a novel method for reliability evaluation of modern substation and distribution systems. A typical IEC 61850 based distribution and substation system is developed and analyzed using the proposed method. The fault tree analysis (FTA) is used to quantify the reliability of the system. The technique is implemented and demonstrated on the Roy Billinton test system (RBTS). The analysis is further extended on a 400/63 kV substation with a breaker-and-a-half configuration. In addition, the technique proves to be robust under different operations. The results verify the feasibility and applicability of the proposed method.

Historically, electric power distribution systems were considered passive subsystems served by the larger transmission grid. Recently, smart grid initiatives have driven the evolution of distribution systems into active systems with market-aware customers and distributed power generation. Along with more diverse and complex injections, contemporary distribution systems are equipped with additional sensing equipment, two-way communications networks, and advanced metering infrastructure (AMI). These are essential technologies that enable several core functions of a smart grid, including real-time monitoring and online control. This thesis presents several tools for the online analysis and control of modern electric power distribution systems. "Online" refers to a control framework that can react to changing system conditions in order to maintain static security and meet different operating objectives. Specifically, the objective of this research is to integrate temporal information (i.e., forecasts) into distribution system analysis tools while maintaining fundamental engineering requirements by re-examining classical problems through a contemporary lens. Connected by an underlying injection forecast model, three research topics are explored: 1) distribution load capability, 2) analytical time window selection for quasi-static time series (QSTS) analysis, and 3) distribution state estimation with explicit consideration of non-synchronized measurements. The work proposed here is a necessary step towards distribution system optimization in an online setting with uncertain and/or bidirectional power flows.

Abstract: In the oil and gas sector, supervisory control and data acquisition (SCADA) systems have become a revolutionary force that are transforming operations throughout the whole value chain. This in-depth analysis looks at the development, design, and various uses of SCADA systems in the upstream, middle, and downstream domains. It projects that the global SCADA market for oil and gas will grow to $4.52 billion by 2026. Real-time well monitoring, production optimization, and remote operations are made possible by SCADA systems in upstream operations, which greatly increase output and efficiency. The goal of midstream applications is to increase pipeline efficiency and safety by using predictive maintenance, enhanced leak detection, and flow optimization. By streamlining quality assurance, energy management, and process control, SCADA systems can completely transform refinery operations. SCADA deployments are not without difficulties, though, including data management complications, cybersecurity threats, and legacy system interoperability. In addition to addressing these problems, the study looks at new developments that could improve SCADA capabilities, such as edge computing, digital twins, AI and machine learning integration, and 5G technology. According to the research, SCADA is essential for promoting efficiency, safety, and innovation in the oil and gas industry. Businesses that successfully integrate SCADA technologies while overcoming implementation obstacles will be best positioned to prosper in the complicated and fiercely competitive energy market.

This paper deals with the design and implementation of an internet of things (IoT) based supervisory control and data acquisition (SCADA) system for a multi microgrid system. The individual microgrid in this work is suggested to be consisting of solar photovoltaic (PV) array, battery bank, and diesel generator, in addition to national grid. IoT is used to provide a suitable wireless means to transfer the monitoring and control data between the generation subsystems and the microgrid controller. SCADA architecture that make use of IoT infrastructure enables efficient and reliable power sharing and also give a clear image about the system status and subsystem failure and power shortage. This system gets benefit of various sensors, including current, voltage, power, and temperature sensors, that are used to collect data from of the PV array and battery bank, and also gives clear image about power demand in each microgrid. The microcontroller ESP32 is used as remote terminal unit (RTU) controller in SCADA system in order to get data from sensors as well as to communicate with the master terminal unit (MTU). By using Cayenne remote server IoT platform deploy the message queuing telemetry transport (MQTT) protocol to store, monitor, and manage data from a MTU. The designed system is low-cost and effective system to monitor and control microgrids that contain many distributed generators.

Проаналізовано особливості застосування систем SCADA (Supervisory Control And Data Acquisition) та технологій Інтернету речей в умовах переходу промисловості до Індустрії 4.0. Показано, що використання веб SCADA забезпечує більшість вимог до таких систем та є масштабованим рішенням на всіх її рівнях. Розроблено та реалізовано веб-SCADA, компоненти якої працюють на одноплатних комп’ютерах типу Raspberry Pi, визначені вимоги до технічних характеристик компонентів системи.

The convergence of Supervisory Control and Data Acquisition (SCADA) systems with the Internet of Things (IoT) and Machine Learning (ML) is redefining automation, security, and operational efficiency across industries. Traditional SCADA systems, widely used in critical infrastructure such as energy, water management, and industrial processes, are undergoing a transformative shift with the integration of IoT. IoT-enabled sensors and devices provide real-time data streams from diverse operational environments, enabling SCADA systems to achieve enhanced situational awareness and remote monitoring capabilities. Machine Learning further augments SCADA systems by introducing advanced analytics for predictive maintenance and anomaly detection. ML algorithms analyse vast datasets collected through IoT devices to forecast system failures, optimize resource utilization, and ensure uninterrupted operations. This predictive approach minimizes downtime, reduces maintenance costs, and improves overall efficiency. Cloud-driven security frameworks are pivotal in addressing the growing cybersecurity challenges associated with SCADA and IoT integration. These frameworks provide scalable and resilient solutions for protecting data integrity, preventing unauthorized access, and mitigating cyber threats. The deployment of ML-driven cybersecurity solutions enhances the ability to detect and respond to sophisticated attacks targeting SCADA environments. This paper examines the evolution of SCADA systems in the era of IoT, focusing on the transformative role of ML and cloud-driven security. It explores innovative applications, highlights the challenges of integrating these technologies, and provides insights into future advancements for creating robust and secure automated systems.

This paper discusses the new auspicious trends of internet of things (IoT) and its advanced developments in various sectors of today’s IT arena, including for industrial sectors. Each object acts as a communication node (or entity) that is able to communicate with other nodes, and corresponding information could be accessed and controlled, via several of today’s commonly used electronic devices such as laptops and cellular devices, etc., through an IoT-designed platform. Moreover, in industrial automation sectors, the employment of IoT is very advantageous, in terms of remote communication support; low-cost operations and maintenance; and autonomous collaborations among remote networked field devices, etc. The facility of autonomous collaborations provisioned by IoT, in the context of a supervisory control and data acquisition (SCADA) system as part of an industrial control system, somehow exists in a distributed network protocol (DNP3) during automation and controls. Therefore, the current study takes the step to model a new IoT framework for a SCADA system, which will be efficient at facilitating industrial automation through the collaborative DNP3-Modbus acquisitions and automation, called the SCADA-IoT system. An IoT gateway is employed and configured that supports for both SCADA protocols, such as DNP3 and Modbus and is efficient at communicating, from networked field devices, with inter-processing from both. In the overall SCADA-IoT design, the transmission is carried from an enormous amount of sensors and/or field devices, employing proprietary and nonproprietary protocols; further, sent information is analyzed via big data, stored in a cloud center, monitored and controlled over a SCADA-IoT supportive platform. At the same time, information security (IS) is a big associated challenge and one of the main contributions of this study. Thus, this study also analyzed the potential security mechanisms for securing SCADA-IoT and found cryptography to be a noteworthy security solution, based on the proposed system requirements and its communication demands.

The nature of electrical distribution systems is changing from simple markets towards competitive markets. The modern distribution system must simultaneously be reliable, flexible, and cost conscious. One of the main factors that affect the reliability of power systems is outages. With all efforts that have been done, the existence of outages is a reality. Management of electrical outages is a necessity and in outage times we need some appropriate decision makings. In this paper we propose an integrated, quantitative methodology based on vague sets to assist the distribution systems in making these decisions. This methodology allows information on the suppliers and customers to be expressed either qualitatively or quantitatively to use a multi-criteria decision making model and provide new functions to measure the degree of accuracy in the grades of membership of each alternative with respect to a set of criteria represented by vague values.

With an average herd size of 113 mature cows, Cayuga County is home to 280 dairy farms and 31,500 dairy milking cows producing approximately 855 million gallons of milk per year. The Cayuga Dairy industry is a major contributor to the countys economy, employing nearly 1200 people, while generating $140,000,000 of revenue from sale of milk alone. At the same time, the Cayuga County dairy industry also produces 5.7 million gallons of manure daily: (a) Nearly 34% of this manure is produced on smaller farms. (b) Digesters are expensive pieces of equipment and require attention and care. ( c) The on-farm digester systems have fairly long payback (>10 years) even for larger CAFO farms (>1000 milking cows). In 2005, Cayuga County Soil and Water Conservation District (The District), a Public Agency under Cayuga County, decided to undertake a centralized community digester project. The primary goal of the project was to develop an economically sustainable model, under the auspices of The District to address manure management issues facing the smaller dairies, improve the water quality and improve the quality of life for Cayuga County residents. It is believed that the District has accomplished this goal by completing construction of Cayuga County Regional Digester on a parcel of land behind the Cayuga County Natural Resource Center located at 7413 County House Road in the Town of Sennett in Cayuga County, New York. The digester facility consists of the following major components. 1. Transfer Station: This an indoor truck bay, where 35,000 gallons of manure from three local farms, 8,500 gallons of liquid organic food-processor waste, and 1,200 gallons of brown grease are unloaded from tanker trucks and the digested slurry is loaded onto the tanker trucks for delivery back to the participating farms. 2. Anaerobic Digester: The project utilizes a hydraulic mix anaerobic digester, a unique design that has no internal moving parts for mixing. The digester, which operates at mesophilic temperatures, is designed to process the daily feedstock and produce 220,000 SCF2 of biogas per day. The digester also produces 44,000 gallons of digested slurry per day. 3. Biogas Conditioning System: The plant employs a biological biogas conditioning system to remove the H2S and moisture contents of the biogas and prepare it to be used by the plant generation system. 4. Combined Heat and Power System (CHP): This is a 633kW high efficiency biogas-fired GE-Jenbacher model JMS-312 GS-NL reciprocating engine cogeneration system. The heat recovery system incorporated into the package is designed to capture the waste heat from the engine exhaust, the jacket cooling water and the engine oil circuit. 5. Electrical Substation and Power Distribution Systems: An electrical distribution system has been constructed on-site that aggregates the electrical service of the different county buildings on the District campus into a county owned electric distribution system that is interconnected with the CHP and the local electric grid. The electrical system is designed, in accordance with the utility guidelines, to allow grid-parallel operation of CHP and provide for import and export of electric power. 6. Thermal Energy Distribution System: The heat recovery system has been integrated into a high temperature water distribution system that distributes the heat to the thermal circuits for the anaerobic digester facility. Additional piping has also been installed to transfer the remaining thermal energy to other county buildings on the campus. On a daily basis, the plant will co-process 35,000 gallons of manure from local dairy farms, 8,500 gallons of food-processor waste and 1,200 gallons of brown grease to produce 200,000 ft3/d of biogas and 44,000 gallons of pathogen-free nutrient-rich digested slurry for agricultural use by farms and in the local area.The biogas fueled CHP produces 5,157,000 kWh of electricity and 19,506 dekatherms of thermal energy per year. Electrical power generated by the cogeneration system powers all the buildings on the Cayuga County campus and any surplus power is exported to the grid under a power purchase agreement. Heat recovered from the cogeneration system will be used to maintain the temperature of the process equipment and the excess will be transported to the Cayuga County Public Safety Building to offset purchase of fossil fuel to fuel the boilers. The majority of plant operations are unmanned and automated. However, the plant will have a small staff of well-trained personnel to coordinate the feedstock deliveries and shipments, supervise the day-to-day operation, monitor the systems and perform maintenance, maintain a safe and reliable operation and to respond to emergencies.

Artificial intelligence has provided great potential and space for the optimization of electrical engineering and it will bring about great improvement not only in economic aspect but also in safety and actual operation control. Since the advent of artificial intelligence it has been widely applied in all fields of life and achieved notable application effect its emergence has even pointed out the direction for the development of many fields and the field of electrical automation control is no exception. In reality, the application of artificial intelligence technology has greatly promoted the progress of the concrete practice of electrical automation and should be paid full attention to by related enterprises and staff. This paper aims to summarize the emergence and development of artificial intelligence and its components and finally summarize the advantages and functions of artificial intelligence in electrical automation control. Advances in machine learning and artificial intelligence (AI) techniques bring new opportunities to numerous intractable tasks for operation and control in modern electric distribution systems. Revolving around the characteristics of distribution system operation and integration of distributed energy resources this paper also illuminates prospects and challenges typified by the privacy explain ability and interpretability of such AI applications in smart grids. KEYWORDS: - Distribution systems, smart buildings, neural networks, Artificial Intelligence, Electrical Engineering, power systems.

The smart grid is characterized as a power system that integrates real-time measurements, bi-directional communication, a two-way flow of electricity, and evolutionary computation. The power distribution system is a fundamental aspect of the electric power system in order to deliver safe, efficient, reliable, and resilient power to consumers. A distribution management system (DMS) begins with the extension of the Supervisory Control and Data Acquisition (SCADA) system through a transmission network beyond the distribution network. These transmission networks oversee the distribution of energy generated at power plants to consumers via a complex system of transformers, substations, transmission lines, and distribution lines. The major challenges that existing distribution management systems are facing, maintaining constant power loads, user profiles, centralized communication, and the malfunctioning of system equipment and monitoring huge amounts of data of millions of micro-transactions, need to be addressed. Substation feeder protection abruptly shuts down power on the whole feeder in the event of a distribution network malfunction, causing service disruption to numerous end-user clients, including industrial, hospital, commercial, and residential users. Although there are already many traditional systems with the integration of smart things at present, there are few studies of those systems reporting runtime errors during their implementation and real-time use. This paper presents the systematic model of a distribution management system comprised of substations, distribution lines, and smart meters with the integration of Internet-of-Things (IoT), Nondeterministic Finite Automata (NFA), Unified Modeling Language (UML), and formal modeling approaches. Non-deterministic finite automata are used for automating the system procedures. UML is used to represent the actors involved in the distribution management system. Formal methods from the perspective of the Vienna Development Method-Specification Language (VDM-SL) are used for modeling the system. The model will be analyzed using the facilities available in the VDM-SL toolbox.

The purpose of this paper is to mapping and review what has been done on the topic of research on predictive maintenance in SCADA (Supervisory Control and Data Acquisition) based industries. In the research area of predictive maintenance, various methods for predicting damage or time to failure of a machine have been proposed and applied in various industries. This paper systematically categorizes predictive maintenance in SCADA-based industries research based on industry classifications according to ISIC (International Standard Industrial Classification of All Economic Activities). Furthermore, the research scope is explored its connection to the topics of Internet of Things (IoT), Artificial Intelligence (AI), Machine Learning (ML), and Supervisory Control and Data Acquisition (SCADA). It is found that 81.5% of the research was conducted on the electricity, gas, steam, and air conditioning supply industries, 11.1% of research was conducted on the mining and quarrying industry, and 7.4% of the research conducted in the manufacturing industry. It is also found that 85.2% of studies used AI and ML, 18.5% of the studies used IoT, and 18.5% of research used AI/ML and IoT technology together.

* Each Chapter Provides an Introduction, Illustrative Examples, and a Summary Introduction to Distribution Automation Systems Historical Background Distribution System Topology and Structure Distribution Automation (DA) and Control Computational Techniques for Distribution Systems Complex Power Concepts Balanced Voltage to Neutral-Connected System Power Relationship for f Y-?-Connected System Per-Unit System Calculation of Power Losses Voltage Regulation Techniques Voltage-Sag Analysis and Calculation Equipment Modeling Components Modeling Distribution System Line Model Distribution Power Flow Analysis Distribution System Topology for Development of Load Flow Review of Classical Power Flow Methods Distribution Power Flow Methods Distribution System Protection and Control Single Line-to-Ground Fault Double Line-to-Ground Fault on Phase B and C Three-Phase Fault Analysis Line-to-Ground and Line-to-Line Faults Protection Systems Protective Relay Technology System Protection in General System Protection for Different Power System Zone Components Distribution System Reliability and Maintenance Reliability Evaluation Terminology/Definitions Reliability Indices Methods of Reliability Analysis Failure Modes and Effects Analysis (FMEA) Method Event-Tree Analysis Method Fault-Tree Analysis Method Unavailability of Power Calculations from the Cut Set Simulation Techniques for Reliability Analysis Simulation Methods Utilized for Distribution Reliability Analysis Evaluation of Distribution Reliability Analysis Method Reliability Database Design Maintenance and Reliability Maintenance of Distribution Systems Reliability-Centered Maintenance Security and Reliability-Centered Maintenance Implementation Plan for Various Component-Maintenance Techniques Distribution Automation and Control Functions Demand-Side Management Voltage/VAr Control Fault Detection (Distribution Automation Function) Trouble Calls Restoration Functions Reconfiguration of Distribution Systems Power Quality Optimization Techniques Intelligent Systems in Distribution Automation Distribution Automation Function Artificial Intelligence Methods Intelligent Systems in Distribution Automation Voltage/VAr Control Network Reconfiguration via AI Fault Detection, Classification, and Location in Distribution Systems Renewable Energy Options and Technology Distributed Generation Working Definition and Classification of Renewable Energy Renewable Energy Options Other Nonrenewable Energy Sources Fuel Cell Distributed Generation Concepts and Benefits Distribution Management Systems Functions of EMS SCADA (Supervisory Control and Data Acquisition) RTU (Remote Terminal Units) Distribution Management System (DMS) Automatic Meter Reading (AMR Cost-Benefit Analysis (CBA) in Distribution Systems Communication Systems for Distribution Automation Systems Telecommunication in Principle Data Communication in Power System Distribution Network Signal Representation Types of Telecommunication Media Communication Modulation Techniques Communication Networking Frame-Relay Communications Communication Standards Overview OSI Model Distribution Network Protocol (DNP) Utility Communication Architecture (UCA) Power-Line Carrier Communication Security in Telecommunications and Information Technology Epilogue Challenges to Distribution Systems for a Competitive Power Utility Environment Protection Demand Response Communication Advances Microgrid Standards and Institutional Barriers Pricing and Billing Glossary References Index

The SCADA system applications in management of Yuvacik Dam and Reservoir

The traditional industrial factory automation, the so-called SCADA (Supervisory control and data acquisition), based on OPC (OLE for Process Control) technology. In recent years, under the impact of information technology, OPC technology is now actively updated to the new standard OPC UA (Unified Architecture). SCADA and the Internet of things, in essence, are the data capture and display, there are many overlapping features. Based on the JustIoT Internet of Things system, this paper designs the bridge hardware and software to bring the operation data of old factory automation equipment into the JustIoT with OPC client or the TCP Modbus protocol. The main feature of HMI SCADA is real-time map monitoring and control. This research adds that feature to JustIoT. Tools are added to JustIoT to let users create HMI page, add graphics and animation gif, and set up the association between pictures and data points. Then, remote monitoring and control can be performed. The cloud supervisory control system has been successfully applied in the offshore wind power monitoring.