Distribution System Research Articles

Tilt–Roll Heliostats and Non-Flat Heliostat Field Topographies for Compact, Energy-Dense Rooftop-Scale and Urban Central Receiver Solar Thermal Systems for Sustainable Industrial Process Heat

Industrial process heat typically requires large amounts of fossil fuels. Solar energy, while abundant and free, has low energy density, and so large collector areas are needed to meet thermal needs. Land costs in developed areas are often prohibitively high, making rooftop-based concentrating solar power (CSP) attractive. However, limited rooftop space and the low energy density of solar power are usually insufficient to meet a facility’s demands. Maximizing annual CSP energy generation within a bounded rooftop space is necessary to mitigate fossil fuel consumption. This is a different optimization objective than minimizing the Levelized Cost of Energy (LCOE) in typical open-land, utility-scale heliostat layout optimization. Innovative designs are necessary, such as compact, energy-dense central receiver systems with non-flat heliostat field topographies that use spatially efficient Tilt–Roll heliostats or multi-rooftop and multi-height distributed urban systems. A novel ray-tracing simulation tool was developed to evaluate these unique scenarios. For compact systems, optimized annual energy production occurred with maximum heliostat spatial density, and the best non-flat heliostat field topography found is a shallow section of a parabolic cylinder with an East–West focal axis, yielding a 10% optical energy improvement. Tightly packed Tilt–Roll heliostats showed a double improvement in optical energy at the receiver compared to Azimuth–Elevation heliostats.

Restoration Strategy for Urban Power Distribution Systems Considering Coupling with Transportation Networks Under Heavy Rainstorm Disasters

With the increasing frequency of extreme weather events such as heavy rainstorm disasters, the stable operation of power systems is facing significant challenges. This paper proposes a two-stage restoration strategy for the distribution networks (DNs). First, a grid-based modeling approach is developed for urban DNs and transportation networks (TNs), capturing the dynamic evolution of heavy rainstorm disasters and more accurately modeling the impact on TNs and DNs. Then, a two-stage restoration strategy is designed for the DN by coordinating soft open points (SOPs) and mobile energy storage systems (MESSs). In the disaster progression stage, SOPs are utilized to enable the flexible reconfiguration and islanding of the DN, minimizing load loss. In the post-disaster recovery stage, the MESS and repair crew are optimally dispatched, taking into account the state of the TN to expedite power restoration. Finally, the experimental results demonstrate that the proposed method reduces load loss during restoration by 8.09% compared to approaches without precise TN and DN modeling.

Optimal Distributed Energy Resources Placement to Reduce Power Losses and Voltage Deviation in a Distribution System

Optimal Distributed Energy Resources Placement to Reduce Power Losses and Voltage Deviation in a Distribution System

A Review: Methods of Fault Detection, Identification and Location in Conventional and Active AC Power Distribution System

A Review: Methods of Fault Detection, Identification and Location in Conventional and Active AC Power Distribution System

Strategi Pengurus BAPQAH SIKA dalam Membina dan Meningkatkan Kualitas Qari Qariah dan Hafiz Hafizah di Sumatera Utara

This research aims to analyze the coaching strategies carried out by the management of the Qari Qariah and Hafiz Hafizah Development Agency (BAPQAH SIKA) North Sumatra in improving the quality of students. Through qualitative descriptive methods, this research examines a systematic approach which includes motivation, class distribution systems, teaching methods, and communication with stakeholders. Data collection was carried out through interviews, observation and documentation studies. The research results show that BAPQAH SIKA implements a comprehensive strategy by dividing classes based on individual abilities, special teaching methods for each field (qari, hafiz, calligraphy), and building a supporting ecosystem through the involvement of parents and the community. Despite facing various challenges such as limited infrastructure and resources, BAPQAH SIKA succeeded in producing outstanding graduates at various national and regional Musabaqah Tilawatil Qur'an (MTQ) events. This research provides theoretical and practical contributions in developing strategies for developing Al-Qur'an education at the regional level.

Greenhouse gas emissions from dry season rice irrigation in Bangladesh

Pumping groundwater for irrigation in Bangladesh is a major energy-consuming process and mostly depends on diesel fuel, which is related to greenhouse gas (GHG) emissions. But that issue has not yet been addressed in Bangladesh. `In this study, we have estimated GHG emissions for dry season (DS) irrigated rice considering all irrigation devices with their lifting heads, area coverage, and water sources (surface and groundwater) and power sources (diesel and electricity) during 2019–2020. GHG emissions varied with locations, sources of irrigation, fuel and water sources used. Irrigation water driven GHG emission in Bangladesh is about 2.27 million tons (Mt) CO2e DS−1, which is about only 4% of agricultural sector GHG emission. Groundwater pumps contributed the lion shares (2.04 Mt CO2e DS−1), and surface water pumps contributed only 0.23 Mt CO2e DS−1. Based on the GHG emissions, Rajshahi Division is the main hotspot followed by Rangpur and Mymensingh Divisions, because of intensive groundwater used in these areas. Current deep tubewells (DTWs), shallow tubewells (STWs) and low lift pumps (LLPs) area coverage is about 19.2%, 56.8% and 24.0% of the total cultivable areas of the country; but it contributes about 49.1%, 40.6% and 10.3% of emitted GHG, respectively. The results revealed that withdrawal of groundwater is an important source of GHG emission. Therefore, expansion of surface water irrigation facilities with the adoption of different improved distribution systems, water and energy saving technologies like alternate wetting and drying practices, conservation agriculture along with water use-efficient varieties for rice cultivation can be promoted for reducing GHG emission.

Assessing impacts of climate crisis on water distribution systems though service inefficiency indicator

Assessing impacts of climate crisis on water distribution systems though service inefficiency indicator

Topology and Control Strategy of Multi-Port DC Power Electronic Transformer Based on Soft Switching

Multi-port DC power electronic transformer (PET) is a core equipment for achieving transformation of different voltage levels and flexible interconnection of different DC buses in a DC distribution system. It is capable of bidirectional energy flow, flexible regulation of power flow, port fault isolation, and other functions. A new five-port DC transformer topology based on soft switching technology is proposed in this paper. In this topology, different DC voltage levels can be interconnected efficiently, such as 20 kV, 750 V, ±375 V, and 300 to 500 V adjustable. The control of each port is simple and flexible. The output voltage is stable, and they are independent of each other, which can improve the system reliability. The topology of the proposed multi-port DC transformer is introduced in detail. The working principle, control strategy, and parameter design method of the transformer are analyzed. Simulations and experimental results are provided to validate the theoretical analysis.

Nanogrids in Modern Power Systems: A Comprehensive Review

Nanogrids are becoming an essential part of modern home power systems, offering sustainable solutions for residential areas. These medium-to-low voltage, small-scale grids, operating at medium-to-low voltage, enable the integration of distributed energy resources such as wind turbines, solar photovoltaics, and battery energy storage systems. However, ensuring power quality, stability, and effective energy management remains a challenge due to the variability of renewable energy sources and evolving customer demands, including the increasing charging load of electric vehicles. This paper reviews the current research on nanogrid architecture, functionality in low-voltage distribution systems, energy management, and control systems. It also explores power-sharing strategies among nanogrids within a microgrid framework, focusing on their potential for supplying off-grid areas. Additionally, the application of blockchain technology in providing secure and decentralized energy trading transactions is explored. Potential challenges in future developments of nanogrids are also discussed.

Comprehensive Thermodynamic Performance Evaluation of a Novel Dual-Shaft Solid Oxide Fuel Cell Hybrid Propulsion System

With the rapid growth of air travel, reducing carbon emissions in aviation is imperative. Electric aircraft play a key role in achieving sustainable aviation, especially for large civil aircraft, where reducing emissions, improving the fuel efficiency, and enabling flexible power regulation are essential. This study proposes a dual-shaft, separated-exhaust fuel cell hybrid aircraft propulsion system (HAPS), using a solid oxide fuel cell (SOFC) to replace the conventional turbine-driven compressor. The independent speed control of the high- and low-pressure spools is realized via a power distribution system. A thermodynamic model is developed, and performance evaluations, including parametric, exergy, and sensitivity analyses, are conducted. At the design point, the system delivers 36.304 kN thrust, 16.775 g/(kN·s) specific fuel consumption, 15.931 MW SOFC power, and 54.759% SOFC efficiency. The exergy analysis highlights the optimization of components like the heat exchanger and fan to reduce energy losses. The sensitivity analysis reveals that the spool speeds and fuel utilization significantly impact the performance. The findings provide valuable insights into optimizing control strategies and offer a novel, efficient, and low-carbon power solution for aviation, supporting the industry’s transition towards sustainability.

The Weather On-Demand Framework

This paper describes the Weather On-Demand (WOD) forecasting framework which is a software stack used to run operational and on-demand weather forecasts. The WOD framework is a distributed system for the following: (1) running the Weather Research and Forecast (WRF) model for data assimilation and forecasts by triggering either scheduled or on-demand jobs; (2) gathering upstream weather forecasts and observations from a wide variety of sources; (3) reducing output data file sizes for permanent storage; (4) making results available through Application Programming Interfaces (APIs); (5) making data files available to custom post-processors. Much effort is put into starting processing as soon as the required data become available, and in parallel where possible. In addition to being able to create short- to medium-range weather forecasts for any location on the globe, users are granted access to a plethora of both global and regional weather forecasts and observations, as well as seasonal outlooks from the National Oceanic and Atmospheric Administration (NOAA) in the USA through WOD integrated-APIs. All this information can be integrated with third-party software solutions via WOD APIs. The software is maintained in the Git distributed version control system and can be installed on suitable hardware, bringing the full flexibility and power of the WRF modelling system to the user in a matter of hours.

Assessing Air-Pocket Pressure Peaks During Water Filling Operations Using Dimensionless Equations

Air pockets can become trapped at high points in pipelines with irregular profiles, particularly during service interruptions. The resulting issues, primarily caused by peak pressures generated during pipeline filling, are a well-documented topic in the literature. However, it is surprising that this subject has not received comprehensive attention. Using a model developed by the authors, this paper identifies the key parameters that define the phenomenon, presenting equations in a dimensionless format. The main advantage of this study lies in the ability to easily compute pressure surges without the need to solve a complex system of differential and algebraic equations. Numerous cases of filling operations were analysed to obtain dimensionless charts that can be used by water utilities to compute pressure surges during filling operations. Additionally, it provides charts that facilitate the rapid and reasonably accurate estimation of peak pressures. Depending on their transient characteristics, pressure peaks are either slow or fast, with separate charts provided for each type. A practical application involving a water pipeline with an irregular profile demonstrates the model’s effectiveness, showing strong agreement between calculated and chart-predicted (proposed methodology) values. This research provides water utilities with the ability to select the appropriate pipe’s resistance class required for water distribution systems by calculating the pressure peak value that may occur during filling procedures.

Literature Review of Earth Fault Self _Extinguished Control System using Petersen _Coil

This study analyzes and classifies a set of research related to Petersen's file and control techniques in electrical distribution systems. It is a coil with an iron core installed between the transformer neutral and the ground and is used to limit the value of the ground fault current that flows when a ground fault occurs in the lines. The coil is designed with tapping to adjust the coil reactance with the system capacity. These researches aim to improve the performance and stability of electrical networks by developing new techniques for measuring insulation parameters, controlling ground resistance, and using numerical simulation to analyze the behavior of grounding systems. The focus was on fault detection techniques, ground fault protection, and reducing harmful arc currents. The recent developments in the use of smart and flexible technology to improve the response of networks to faults and increase the reliability and safety of electrical systems were also reviewed. The study concluded that advanced technologies and comprehensive analysis of these researches contribute to enhancing the performance and efficiency of electrical networks, reducing risks and improving the sustainability of energy supplies.

Enhancing Healthcare Efficiency at Almasara Hospital: Distributed Data Analysis and Patient Risk Management

This study presents a distributed system using RAY, K-means clustering, and Weka software to analyze clinical data from Almasara Hospital Group in Tripoli, Libya. The goal is to reduce patient risk and healthcare costs by providing daily feedback to hospital staff. The system utilizes a dataset containing information on 560 patients, including details like patient ID, gender, doctor ID, test IDs, medication, and a binary target variable. By implementing K-means clustering in Weka, the system categorizes patients and identifies patterns to reduce risks and costs for healthcare analytics. The study first reviews existing patient care and feedback practices and then details the implementation of the daily feedback system, which involves advanced data analysis for managing patient feedback and medical data continuously. The use of K-means clustering helps segment patient data, pinpointing specific risk factors and areas for improvement. Weka software aids in the in-depth analysis of these segments, leading to actionable insights. Results show significant improvements in patient outcomes, reduced hospital-acquired infections, and medication errors, and enhanced patient satisfaction scores. Moreover, the study notes a substantial decrease in overall healthcare costs due to more efficient resource allocation and lower hospital readmission rates. This integration of daily feedback with advanced data analysis tools like K-means and Weka emerges as an effective strategy for improving patient safety and operational efficiency in healthcare settings, demonstrating the value of data-driven decision-making and providing a scalable model for other hospitals aiming to enhance patient care and cost management.

Optimizing Supply Chain Management with Real-Time Data Integration Platform

Real-time data integration platforms have emerged as transformative solutions in modern supply chain management, revolutionizing how organizations process, analyze, and act on critical business information. These platforms enable seamless connectivity between suppliers, manufacturers, distributors, retailers, and customers, providing end-to-end visibility and enhanced decision-making capabilities. The evolution from traditional batch processing to real-time integration represents a fundamental shift in supply chain operations, addressing challenges such as data latency, system fragmentation, and operational inefficiencies. Through advanced technological components including sophisticated data ingestion layers, powerful processing engines, and efficient distribution systems, organizations can achieve substantial improvements in inventory management, order fulfillment, and customer satisfaction. The integration of artificial intelligence, edge computing, and blockchain technologies further enhances these capabilities, enabling predictive analytics, automated decision-making, and enhanced security measures. The implementation of these platforms, while challenging, offers significant strategic advantages including improved operational efficiency, reduced costs, and strengthened competitive positioning in the global marketplace.

Continuous monitoring of partial discharge activities in power cables and their stimulation due to the temperature rise

AbstractWith the development of the power distribution systems demands, the grid reliability becomes a strategic issue. Continuous monitoring of power transmission networks is a key component in addressing this issue. Partial discharge (PD) characterisation instruments provide a reliable solution and an important indicator of the state of cable insulation. An increase in the PD level usually indicates the development of a fault that affects the integrity of the cable and can lead to various problems related to the quality and quantity of the transmitted energy. In this context, the use of Internet of Things (IoT) systems for power networks monitoring can provide a significant improvement to the localisation and detection of faults. In this paper, the authors show the advantages of continuous monitoring of power grid cables using a new IoT based framework using an advanced signal processing technique, namely the phase diagram. Also, the authors show that variations in temperature can impact the initiation and progression of PD, affecting the reliability and lifespan of electrical insulation systems. Understanding this temperature dependence is crucial for accurate PD detection and effective maintenance of power cables. Our results show that higher temperatures can accelerate the PD activity, while lower temperatures may suppress it.

Research on Fault Section Location in an Active Distribution Network Based on Improved Subtraction-Average-Based Optimizer

The high penetration of distributed generation (DG) in the distribution system poses a challenge to the protection techniques and strategies of active distribution networks, making it difficult to adapt traditional methods to the fault diagnosis of the new power system. A method based on the improved subtractive optimiser algorithm for fault diagnosis is proposed to address this situation. Firstly, a fault localization model applicable to DG grid connection is constructed, which can effectively deal with the impact of the dynamic switching of DGs on the system and make up for the shortcomings of the traditional single-power network model; secondly, to solve the model, the original algorithm is improved using multi-strategy fusion, and the improved subtraction-average-based optimizer (ISABO) is obtained. Through the test of classical functions, its excellent solving performance and decoupling ability are verified; finally, the ISABO algorithm is applied to the 33-node test system to make it operate in various complex fault conditions. The results show that the ISABO algorithm is feasible in solving the fault location problem and can adapt to the connect/disconnect state of the interconnection switch and the dynamic casting and cutting of multiple DGs. Compared with the original SABO algorithm, its positioning accuracy can always be maintained at 100%, and the positioning speed is increased by 46.68%, symmetrically improving positioning speed, positioning accuracy, and fault tolerance.

Analysis of Dynamic Biogas Consumption in Chinese Rural Areas at Village, Township, and County Levels

Understanding the characteristics of biogas demand in rural areas is essential for on-demand biogas production and fossil fuel offsetting. However, the spatiotemporal features of rural household energy consumption are unclear. This paper developed a rural biogas demand forecasting model (RBDM) based on the hourly loads of different energy types in rural China. The model requires only a small amount of publicly available input data. The model was verified using household energy survey data collected from five Chinese provinces and one year’s data from a village-scale biogas plant. The results showed that the predicted and measured biogas consumption and dynamic load were consistent. The relative error of village biogas consumption was 11.45%, and the dynamic load showed seasonal fluctuations. Seasonal correction factors were incorporated to improve the model’s accuracy and practicality. The accuracy of the RBDM was 19.27% higher than that of a static energy prediction model. Future research should verify the model using additional cases to guide the design of accurate biogas production and distribution systems.

Psychological Analysis and Career Decision-Making of College Students Based on Cognitive Algorithms on Distributed Platforms

This research uses cognitive analytics on a distributed computer system to investigate how students’ decision-making behaviors relate to their personality traits. The goal of the research is to improve our knowledge of the variables affecting students’ professional choices and to offer a solid, expandable framework for individualized career counseling. The investigation examines a range of psychological characteristics, such as personality characteristics, cognitive capacities, passions, and socioeconomic status, by utilizing cognitive algorithms. Massive databases may be processed more easily thanks to the distributed system, which also ensures effective computing and analyses in real time. The approach entails gathering information from a heterogeneous student body, then analyzing it and extracting features to find meaningful trends. Neural networks and combination techniques are examples of sophisticated algorithms for machine learning that are used to create models of prediction that help with career suggestions. The results show how well cognitive computers capture the intricate interactions between variables that influence career choices. The flexibility of the distributed platform guarantees the system’s suitability for big colleges and universities, offering students individualized career counseling on a broad scale. This study offers a fresh method for comprehending and assisting students in their professional choices, which makes a significant contribution to the fields of data mining for education and career planning.

Overview of Wide-Frequency Measurement Technology for Electrical Parameters in Distribution Substations

The rapid development of modern transmission and distribution systems requires transformers with wide bandwidth and high accuracy to meet the measurement needs of new characteristics in distribution substations, including wide dynamic ranges in the time-frequency domain and multi-parameter measurements. This paper outlines the measurement principles and structural design of new wide-frequency voltage and current measurement technologies. Based on the current status and measurement demands of distribution substations, an analysis of the economic, safety, and reliability aspects of these technologies is conducted. The results of the analysis indicate that capacitive voltage transformers and current transformers based on Rogowski coils are the current suitable solutions for wide-frequency measurement in distribution substations. Finally, the paper provides a forward-looking perspective on the development prospects of wide-frequency electrical parameter sensing technologies in distribution substations