Components Of Distributed System Research Articles

Assessment of Corporate Carbon Footprint and Energy Analysis of Transformer Industry

Transformers are primarily key components in power transmission and distribution systems. In the electrical industry, transformers are becoming increasingly important to increase energy efficiency and reduce environmental impact. In the process from the production to the use of transformers, various strategies and technologies are adopted to reduce the carbon footprint. To achieve decarbonization targets and a future with sustainable energy, ongoing efforts to reduce the carbon footprint of transformers need to continue. Therefore, this study aims to calculate the carbon footprint (CF) of Beta Energy in the Adana Province of Türkiye. A comprehensive inventory is being created to determine and monitor the greenhouse gas emissions of Beta Energy, a transformer manufacturer. This inventory includes direct and indirect greenhouse gas emissions from all of the company’s activities. The findings show that in 2023, the total CF of Beta Energy is equal to 1,799,482.72 tons of CO2-eq and considering the total of 6044 transformers sold in 2023, results in 297 tons of CO2-eq/transformer per product. The results show that the transformer manufacturing industry has a high carbon footprint because it is an energy-intensive process. The areas where the most carbon emissions occur in transformer production are revealed by CF hot spot analysis in this study. To minimize both current and future greenhouse gas emissions during transformer production, the measures to be taken during the R&D, production, transportation, and service stages are revealed. This study aims to establish a foundation for Beta Energy’s efforts to reduce greenhouse gas emissions by managing them effectively.

Assessment of Corporate Carbon Footprint and Energy Analysis of Transformer Industry

Transformers are primarily key components in power transmission and distribution systems. In the electrical industry, transformers are becoming increasingly important to increase energy efficiency and reduce environmental impact. In the process from the production to the use of transformers, various strategies and technologies are adopted to reduce the carbon footprint. To achieve decarbonization targets and a future with sustainable energy, ongoing efforts to reduce the carbon footprint of transformers need to continue. Therefore, this study aims to calculate the carbon footprint (CF) of Beta Energy in the Adana Province of Türkiye. A comprehensive inventory is being created to determine and monitor the greenhouse gas emissions of Beta Energy, a transformer manufacturer. This inventory includes direct and indirect greenhouse gas emissions from all of the company’s activities. The findings show that in 2023, the total CF of Beta Energy is equal to 1,799,482.72 tons of CO2-eq and considering the total of 6044 transformers sold in 2023, results in 297 tons of CO2-eq/transformer per product. The results show that the transformer manufacturing industry has a high carbon footprint because it is an energy-intensive process. The areas where the most carbon emissions occur in transformer production are revealed by CF hot spot analysis in this study. To minimize both current and future greenhouse gas emissions during transformer production, the measures to be taken during the R&D, production, transportation, and service stages are revealed. This study aims to establish a foundation for Beta Energy’s efforts to reduce greenhouse gas emissions by managing them effectively.

Distribution Pattern of ELF Field Exposure Electricity Distribution Substation Portal Pole Type 20 kV Medium Voltage Network

The electricity distribution substation is one of the components of the electricity distribution system. Electrical distribution substations, especially portal pole-type electrical distribution substations, can emit ELF fields. However, people need to be aware of the health risks of ELF fields and continue to carry out various activities near electricity distribution substations. This research aims to create a distribution pattern for ELF Field and determine its safety level based on WHO thresholds. The research was conducted in the Jember Regency, particularly in Sumbersari District. This research uses a portal pole-type electricity distribution substations. The substation criteria studied were a portal pole distribution substation on a 20 kV transmission line with a transformer capacity of 160 kVA. The measurement points are 0 m below the transformer, 0.7 m, 1.4 m, 2.1 m, 2.8 m, 3.5 m, 4.1 m, and 4.9 m from the distribution substation building at a height of 1.5 m from the ground for three days at 21.00 WIB and 30 measurements were taken. The distances of these points to the transformer are 4.256 m, 4.313 m, 4.480 m, 4.745 m, 5.094 m, 5.510 m, 5.979 m and 6.490 m respectively. The type of research used is quantitative research with survey data collection techniques. The research design used was cross sectional study. Cross sectional study is a type of observational research design that collects data at one specific point in time from a sample which represents the population studied. ELF field measurements show a spherical distribution pattern with an average magnetic field intensity between 0.0358 µT and 2.91 µT and an average electric field intensity between 2.35 V/m and 16.42 V/m. The magnitude of the magnetic field and electric field measured gets smaller as the distance from the measurement point increases. According to WHO, these results are below the threshold for the general group. This research concludes that the portal pole-type distribution substation in the medium voltage network produces a safe ELF field with a spherical distribution pattern that is inversely proportional to the distance.

Three-phase model of SCIG-based variable speed wind turbine for unbalanced DSLF analysis

Steady state performances of the electric power distribution system are normally assessed or evaluated based on load flow analysis. To properly carry out the analysis, a valid steady state load flow model of each distribution system component, including the wind power plant (WPP), needs to be developed. The present paper proposes a method for modeling and integrating squirrel cage induction generator (SCIG)-based variable speed WPP into a three-phase unbalanced distribution system load flow (DSLF) analysis. The proposed method is based on a single-phase T-circuit model of fixed speed WPP, which has successfully been applied to balanced electric power systems. In the present work, the single-phase T-circuit model is extended and modified to be used in steady state load flow analysis of three-phase unbalanced distribution systems embedded with SCIG-based variable speed WPP. Results of the case studies confirm the validity of the proposed method.

Traveling-wave-based Fault Location using Time Delays between Modal Components in Electrical Distribution Systems

Background: The distribution feeders usually include many laterals, too many sensors need to be installed to locate the fault positions in electrical distribution systems by using the traditional double-ended traveling-wave-based fault-location methods Objective: Fault location based on the time delays between the moments of the first wavefronts of zero-mode voltages and that of aerial-mode voltages arriving at one end of the distribution feeder. Methods: Large decomposition level in wavelet transformation is adopted in this paper to obtain the zero-mode velocity. Results: Both theoretical research and simulation experiments have proved that the proposed fault location method can greatly improve the accuracy of the fault location in the electrical distribution systems without many sensors. Conclusion: The proposed fault location method can provide one feasible way to locate the faults in the electrical distribution systems.

Design of Instrumentation and Control Components of Power Distribution Systems

Introduction. In recent years, the development of high-voltage power systems has received a boost due to the need for infrastructural support for priority development areas. Universal models and algorithms are required to implement processes in power components and identify their optimal parameters. However, there are no such solutions. Accordingly, there are no ready-made subsystems with control and optimization algorithms adequate to the tasks under consideration. The objective of the presented research is to develop an optimization subsystem for the design of control and measurement components of power distribution systems.Materials and Methods. Methods for constructing automated design systems, optimization, system analysis, mathematical modeling, and adaptive control were used. When selecting methods, we proceeded from the fact that the components of power distribution systems consisted of a finite number of elements. The synthesis of a power system includes tens or hundreds of sequential operations. This was taken into account in the developed models and algorithms.Results. The possibilities of managing and monitoring manufacturing processes (MP) for the production of components of low-voltage power distribution systems were shown in terms of checking the operability and correct functioning of processing equipment. A modular structure was created to allow the integration of CAD output files into the manufacturing processes of energy distribution system components. A functional diagram of a subsystem for control and monitoring of the manufacturing processes of the production of components of power distribution systems was developed. The proposed schematic diagram of production control showed how the data collection subsystem, management system, and operating mechanisms were involved in the control of operations. The multi-level optimization module model created within the framework of this research sequentially optimized the service intensity of the i-th block, the input flow separation coefficients, and the priorities of the original data flows that form the input flow of the i-th block.Discussion and Conclusion. The combined application of modeling, system analysis, and optimization methods maintains control of the accuracy of the generated power components. The algorithm for controlling electrical loads opens up opportunities for creating a mathematical model of a power supply system that combines management, control, and monitoring, which ultimately leads to an improvement in the quality of electric power. The solution can be in demand in the development of power systems of priority development areas.

Advanced Monitoring for Auxiliary Transformer Failures and Alerting System

Auxiliary transformers are critical components in power distribution systems, and their failure can lead to costly downtime and potential damage to electrical infrastructure. This paper proposes the development of a real-time alert system will be designed to monitor auxiliary transformer health and promptly detect anomalies and failures. The development of a transformer health monitoring system involves the utilization of Arduino-based embedded systems to interface with temperature, ultrasonic, and current sensors. The system aims to monitor essential parameters such as temperature, oil level, and current values. In case of abnormalities, it triggers immediate alerts through GSM messaging and implements protective measures by controlling the load using relays and a buzzer for audible alerts. Key Words: Auxiliary Transformer, GSM Technology, Arduino, Temperature Sensor, Ultrasonic Sensor, Current Sensor.

Field teams coordination for earthquake-damaged distribution system energization

The re-energization of electrical distribution systems in a post-disaster scenario is of grave importance as most modern infrastructure systems rely heavily on the presence of electricity. This paper introduces a method to coordinate the field teams for the optimal energization of an electrical distribution system after an earthquake-induced blackout. The proposed method utilizes a Markov Decision Process (MDP) to create an optimal energization strategy, which aims to minimize the expected time to energize each distribution system component. The travel duration of each team and the possible outcomes of the energization attempts are considered in the state transitions. The failure probabilities of the system components are computed using the fragility curves of structures and the Peak Ground Acceleration (PGA) values which are encoded to the MDP model via transition probabilities. Furthermore, the proposed solution offers several methods to determine the non-optimal actions during the construction of the MDP and eliminate them in order to improve the run-time performance without sacrificing the optimality of the solution.

Parametric and Nonparametric Machine Learning Techniques for Increasing Power System Reliability: A Review

Due to aging infrastructure, technical issues, increased demand, and environmental developments, the reliability of power systems is of paramount importance. Utility companies aim to provide uninterrupted and efficient power supply to their customers. To achieve this, they focus on implementing techniques and methods to minimize downtime in power networks and reduce maintenance costs. In addition to traditional statistical methods, modern technologies such as machine learning have become increasingly common for enhancing system reliability and customer satisfaction. The primary objective of this study is to review parametric and nonparametric machine learning techniques and their applications in relation to maintenance-related aspects of power distribution system assets, including (1) distribution lines, (2) transformers, and (3) insulators. Compared to other reviews, this study offers a unique perspective on machine learning algorithms and their predictive capabilities in relation to the critical components of power distribution systems.

An innovative fuzzy logic based controller for solid oxide fuel cells

The solid oxide fuel cell (SOFC) stands out as a vital component in sustainable distributed generation systems, thanks to its reliability and adaptable power generation capabilities. This adaptability allows the SOFC to efficiently balance grid power by adjusting its power output. Nevertheless, maintaining the desired fuel usage rate and achieving rapid load tracking pose considerable hardships in SOFC control. To deal with these difficulties, this study introduces a novel approach, the Cascaded Double Input Interval Type-2 Fuzzy Logic Controller (C-DIT2-FLC), designed for SOFC control. In this innovative model, the Improved Salp Swarm Algorithm (ISSA) is applied to determine the crucial parameters of Proportional Integral-Proportional Derivative (PI-PD) cascade controllers. The C-DIT2-FLC dynamically adjusts the controller gains, which are optimized using ISSA, to enhance the effectiveness of SOFC operations. The research results substantiate the superior efficacy of the C-DIT2-FLC over conventional controllers, thereby providing enhanced control and performance capabilities for SOFC systems.

Topological Design Optimization Approach for Winding Oil Flow Paths in Oil-Natural Air-Natural Transformers Based on a Fluidic-Thermal Coupled Model

Power transformers are a critical component in transmission and distribution systems. To limit the temperature rise to extend the life-cycle while operating with enough reliability and controllability of a transformer, the design of the cooling system has attracted extensive research attention. In this paper, a topology optimization (TO) methodology is presented for designing the coolant flow paths in a prototype oil-natural air-natural (ONAN) power transformer to maximize the winding heat dissipation capacity without any compromise on the flow resistance. First, the thermal and fluid flow characteristics in both the winding and the radiator of the prototype transformer are numerically investigated through a fluidic-thermal coupled field approach. The preliminary cooling effectiveness of the oil circulation system is initialized. Second, a material-density-based TO scheme is employed to realize the optimal design of the oil baffle structures. In the TO optimization, artificial Darcy frictional forces are applied to the solidified cells to block their internal flows in the fluidic calculations, while the thermal conduction coefficients in those cells are enhanced to separate the baffles from the flowing oil in thermal analyses. Finally, the fluidic and thermal coupled fields of the prototype transformer winding region with structurally optimized oil baffles are numerically investigated to validate the TO effectiveness.

Large-Signal Stability Analysis of DC Distribution Systems With Cascading Converter Structure

DC-DC converters are major components of the DC distribution systems. The converters interface with external power inputs, internal DC buses and loadings of subsystems. The interfacing DC-DC converters should be stable locally and globally under mutual interactions through a DC bus within the system. Current research efforts have focused on the analysis of the stability of the DC distribution system subject to small-signal disturbance. However, in practice, the system routinely operates under large-signal disturbances, such as when an additional subsystem is turned on after being connected to the DC bus. In this scenario, the small-signal model may fail to fully describe the dynamics of the system. In this paper, we identify and analyze the bifurcation process when the system undergoes abrupt load changes. According to the nonlinear operation of the interconnected system, a large-signal stability criterion is derived. This criterion is simple, and can be easily extended to multiple connected converter systems. The criterion is also consistent with the result from bifurcation analysis. Finally, the validity of the proposed criterion is verified by the full-circuit simulations and the experimental works.

A weather-based power distribution system reliability assessment

The continuity of power supply is affected by many factors; the weather conditions to which power system components are exposed are considered the most effect. A new methodology to assess the reliability of distribution system considering the impact of different weather conditions is presented in this paper. The proposed method considers possible future changes in the weather patterns that might occur differently from what it was in the past. Modified sets of reliability indices are presented for mathematically predicting reliability performance based on historical reliability data under specific past weather conditions combined with forecasted future weather conditions. The proposed method is applied to the distribution system components of RBTS; the results demonstrate the significance of considering the forecast of weather conditions in reliability assessment.

A heuristic approach to the stochastic capacitated single allocation hub location problem with Bernoulli demands

Hubs are critical components of transportation and distribution systems, and hub networks play a special role in freight and passenger transportation services worldwide. This paper studies a capacitated single allocation hub location problem with Bernoulli demands. Since the origin-destination (OD) demands are stochastic in nature, and the nodes are allocated to hubs before knowing their realized values, the actual total demand allocated to each hub is uncertain. Therefore, demand can exceed the capacity of hubs, rendering a need for outsourcing. The problem is studied under two distinct outsourcing policies, namely the facility and customer outsourcing. Mathematical models are developed for each case as two-stage stochastic programs. Deterministic equivalent formulations are obtained for problems, assuming a homogeneous demand distribution for all OD pairs. A Tabu Search-based algorithm is presented as a solution approach to deal with large problem instances. Extensive computational tests demonstrate the outstanding performance of the developed models and the metaheuristic procedure in terms of solution quality and computational time. The relevance of using stochastic programming approach for the problems is demonstrated via computational results. This study also reports solutions for problems with 200 nodes for the first time.

Global challenges of electric vehicle charging systems and its future prospects: A review

Global primary energy supply mainly comes from fossil fuels that are limited in supply and have negative impacts on the environment. A large number of conventional vehicles, present on the streets, mainly consume fossil fuels and emit greenhouse gases. The popularity of electric vehicles is increasing rapidly due to various social and economic factors as well as significant environmental impacts. Governments across the world are shifting their sentiments towards electric vehicles (EVs) to reduce these negative effects. Due to this support from governments and public awareness, EVs are increasing rapidly and bringing new types of problems to the existing power system. The rapid increase in charging high-power electric vehicles (EVs) poses challenges to the power system, including load profile distortion, voltage deviation, frequency imbalance, harmonic injection, distribution system component capacity overloading, excess power loss, and grid instability. This study quantitatively analyzes the impact of EV charging on the power system. With an increase in EV penetration from 25% to 50%, the peak power demand on the system rises by 166%. However, implementing a smart charging system optimizes system parameters, leading to reduced power loss, decreased voltage deviation, and a remarkable 96% decrease in the grid's peak power demand compared to conventional uncoordinated charging. Smart charging not only solves existing problems but also facilitates the integration of next-generation technologies like autonomous vehicles, connected mobility, and the energy internet. This research highlights the significant benefits of smart charging in addressing the challenges posed by the rapid growth of EVs while promoting sustainability and technological advancement in the power system.

Data Distribution for Heterogeneous Storage Systems

The exponential growth of data in many science and engineering domains poses significant challenges to storage systems. Data distribution is a critical component in large-scale distributed storage systems and plays a vital role in placing petabytes of data and beyond, among tens to hundreds of thousands of storage devices. Meantime, heterogeneous storage systems, such as those having devices with hard disk drives (HDDs) and storage class memories (SCMs), have become increasingly popular for massive data storage due to their distinct and complement characteristics. This paper presents a new data distribution algorithm called SUORA (Scalable and Uniform storage via Optimally-adaptive and Random number Addressing) specifically for heterogeneous devices to maximize the benefits of them. SUORA provides a fully symmetric, highly efficient methodology to distribute data across a hybrid and tiered storage cluster. It divides heterogeneous devices into different buckets and segments, and adopts pseudo-random functions to map data onto them with the balanced consideration of capacity, performance and life-time. By analyzing hotness and access patterns, SUORA gradually moves hot data from HDDs to SCMs to optimize the throughput, and moves cold data reversely for load balance. It combines data replication with migration to significantly reduce movement overhead while making data placement more adaptive to different workloads. Extensive evaluations on simulation and Sheepdog storage system show that, with considering distinct characteristics of various devices thoroughly, SUORA improves the overall performance efficiency of heterogeneous storage systems.

Optimization Technique for Renewable Energy Storage Systems for Power Quality Analysis with Connected Grid

Power quality is the main problem with the power system network. Poor electricity quality may cause disruptions and financial challenges for consumers. Additionally, it could cause electronic gadgets to overheat, be damaged, or operate inadvertently. Transformers and other components of the power distribution system may also overheat and experience core saturation. This study investigates potential problems with the quality of the electricity in a photovoltaic linked power system. This paper suggests a new optimization method for day-ahead trading and control in DC microgrid power management (MG). The goal of the multiobjective optimization dispatch (MOOD) problem is to lower overall operational costs as well as the costs associated with power loss in efficient conservation systems and exhaust emission quantities such as nitrogen oxides, sulphur dioxide, and carbon dioxide. Using the weighted sum approach, the multiobjective optimization problem is reduced to a single optimization problem. The analytical hierarchy process (AHP) method is then used to calculate the weight coefficients while accounting for each objective function’s preferences. Power balancing, high levels of renewable energy penetration, the most effective scheduling of battery charging and discharging, control of load curtailment, and the technical limitations of the system are all taken into account when evaluating the system’s performance in both grid-connected and standalone operation modes. The ant lion optimizer (ALO) technique is taken into account to tackle MOOD, comparing the effectiveness of the proposed method to other well-known heuristic optimization techniques. The simulation’s results demonstrate how effectively the proposed strategy can address the coordinated control and optimization dispatch difficulties. They also found that operating the MG system economically in grid-connected mode can save overall costs by roughly 4.70% compared to doing it in independent mode.

Methodology for the control of electric power distribution system components to ensure the quality of consumed electricity

Electric power system is a complex organizational structure that provides working interaction for its constituent intelligent electronic devices by defining their roles, communication channels, and powers. The control system of a modern electric power system must ensure the coordination of operation of intelligent electronic devices at the technological stages of power generation, transport, distribution, and consumption. The disadvantage of existing process control systems in electric power systems is the use of a hierarchical control structure in relation to the network topology. This fact leads to conflicts of resources and processes at the stages of generation, transport, distribution, and consumption of electricity. Uncoordinated operation of control devices leads to a decrease in the efficiency of power facilities which negatively affects the quality of electricity in the power supply network. To synchronize the work of intelligent electronic devices distributed over the network, it is proposed to provide their joint work through a single information center in a digital environment. At the same time, it is proposed to control the modes of operation of the power supply network using digital twins of its components. Digital twins of electric power system objects control power quality indicators, simulate the modes of interacting devices in a digital environment, and perform control of power supply network components to ensure a rational mode of their operation. To achieve the universality and speed of the control system it is proposed to use the apparatus of fuzzy artificial neural networks, and for better prediction of power quality indicators in the network — ensembles of artificial neural networks. A methodology for controlling the quality of electricity at sections of the electricity distribution network was developed using digital twins that ensure the relationship between the monitored indicators of electricity quality and regulated values of the actuators of intelligent electronic devices.

Kajian Koordinasi Sistem Proteksi Pada Sistem Transmisi 70 kV GI Banaran Kediri Transmission Line Bay Pare

The substation is one of the components in the electric power distribution system which plays a very important role because itis the connection between electricity services to customers. In the electric power distribution system, there are disturbances that often occur,one of which is a short circuit. For that, the way to overcome this is using the Distance Relay protection system, OCR / GFR and DEF. Thepurpose of writing this research is to determine the value of setting relay distance, setting Over Current Rele and Directional Earth Fault relayin order to secure the 70 kV transmission network connected to GI Banaran, which is then simulated using DigSILENT 15.1 software on thePare line by calculating symmetrical and asymmetrical disturbances. including 3-phase disturbance on February 1, 2018. The simulationresults show that the 3-phase disturbance occurs at Zone 1 relay distance of the Banaran Bay Pare substation with a trip time of 0.02 secondswith a fault impedance of 0.083 ohms below the relay impedance value of 0.887 ohms. The coordination between the distance relay on theside of the Banaran Bay Pare substation has worked well because there is no error reading the relay when it will cut off the disturbance.

Analyse and Design of Equitable Water Supply for Rural Water Distribution Network

The most important need of all living things is water. Industrial, household, and irrigating uses all involve the use of water. A water distribution system should be created in the most straightforward method possible to accommodate the growing population. Better living conditions can be provided by an adequate installation. The distribution pipe shouldn't allow the water's quality to decline. A good water distribution system uses less loss to deliver enough pressure at each distribution point. A good water distribution system meets customer demand at the appropriate time. Water distribution network planning and analysis could be a challenging procedure. Groundwater and surface water are just two of the many sources of water used by water supply systems. In most cases, the water is then cleansed.chlorinated for disinfection and occasionally fluoridated. Treated water is either gravity-fed or pumped to a reservoir, which may be on the bottom or elevated like a reservoir. The distribution system is subsequently fed with the water. Pipelines, tanks, basins, pumps, valves, and other hydraulic infrastructure components are included in the water distribution system. Distribution mains, arterial mains, storage basins, and system components such as valves, hydrants, mainline metres, service connections, and backflow preventers are all crucial for producing water for consumers. The pipes that make up the distribution complex are known as distribution main. Their function is to deliver water to customers from water sources or water treatment facilities. A service connection joins the distribution system mains to other plumbing systems or a private building. the ocean. A distribution system is made up of a network of pipes, tanks, and other components that transport drinking water while also serving to protect buildings such as houses, schools, hospitals, workplaces, and other structures from fires.