Electrical Distribution System Research Articles

Optimal coordination of directional over current relays for distribution systems using hybrid GWO-CSA

Coordination of protective relays is a critical aspect of electrical distribution systems, ensuring effective and reliable protection against faults. In modern power systems, the integration of distributed generation (DG) sources adds complexity to the coordination task. The dynamic nature of DG systems requires adaptive relay settings that can swiftly detect and isolate faults while minimizing potential damage and downtime. The purpose of this research is to improve the coordination of directional over current relays in electrical distribution systems, particularly in DG systems. An optimization technique combining the grey wolf optimization (GWO) and cuckoo search algorithm (CSA) is developed to identify the best relay settings that reduce overall operation time while ensuring excellent fault identification and isolation. To address relay faults caused by DG integration, a suitable primary and backup relay design is chosen, and the influence of time multiplier settings (TMS) on system performance and reliability is investigated. The proposed GWO-CSA technique is evaluated and implemented on IEEE 3, 8 and 15-bus systems using MATLAB. Simulation results show that the GWO-CSA strategy outperforms well compared to previous algorithms, enabling optimal coordination and increased protection in DG systems while drastically lowering relay operating time.

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.

SISTEM KETIDAK SEIMBANGAN BEBAN PADA JARINGAN TEGANGAN RENDAH MENGGUNAKAN ALAT PHB – SR ( PERALATAN HUBUNG BAGI SAMBUNGAN RUMAH) DI PT. PLN PERSERO ULP BINJAI TIMUR

Load imbalance in an electric power distribution system often occurs in the field. This is a single-phase load on Low Voltage Network customers that is not the same due to the large number of additional electrical loads that do not pay attention to system load imbalances. As a result of this imbalance, a current appears in the transformer neutral. The current flowing in the neutral of the transformer causes losses, namely losses due to neutral current in the neutral conductor of the transformer and losses due to neutral current flowing to the ground. By realizing PHB SR (Home Connection Equipment) is able to balance the load on the Low Voltage Network. balance the load on the Low Voltage Network periodically and continuously so as to reduce technical shrinkage (losses), simplify the Connection Field in the technical connection of the Low Voltage Network. Connection in the technical connection of the House Connection (SR) on the pole, improve the aesthetics and neatness of the Network System.

Development of portable deterioration diagnosis device for oil filled transformers based on near‐infrared spectroscopic information

AbstractA transformer plays a key role in electric power distribution system; therefore, when the transformer fails, several electrical components may get affected. As a result, diagnosing the deterioration of transformers is important for the management of electric power distribution system. The furfural content in the insulating oil of a transformer is widely used as an indicator of deterioration because furfural is generated by the decomposition of insulating paper. However, analyzing the furfural content is time consuming because of the requirement of a professional and the complexity of the diagnosis process. In this study, we propose a novel method for analyzing the amount of furfural in the insulating oil based on near‐infrared spectroscopic data obtained using the developed portable spectrometer, which can be used for the on‐site analysis at transformer installation sites. We selected wavenumbers with high correlation coefficients between the furfural content of oil and the spectroscopic data and estimated the furfural content by partial least squares regression. The results suggest that the furfural content can be analyzed in a few minutes using a small amount of oil through a portable diagnostic device.

Analysis of Load Imbalance in Tarakan Distribution Transformer of PT PLN (Persero) Sukarami Customer Service Unit

Load imbalance in an electric power distribution system always occurs and the cause of this imbalance is unbalanced single-phase loads on low voltage network customers. As a result of this load imbalance, a current arises in the neutral of the transformer, which can cause power losses. The aim of the research is to analyse the load imbalance of the Distribution Transformer PC0044, PC0074, PC0088, PC0129, PC1319 on the Tarakan Feeder of PT PLN (Persero) Sukarami Customer Service Unit. The results of the research show that the highest peak load percentage occurs on the PC1319 Distribution Transformer, namely 93.0874%, and based on PLN ED Decree No. 0017.E/DIR/2014, transformer loading. The largest percentage of load imbalance occurs in the PC0044 Distribution Transformer, namely 38.0952%, and based on PLN ED Decree No. 0017.E/DIR/2014, the current imbalance between phases is included in the bad category because the load imbalance is ≥ 25%. The largest percentage of power losses due to neutral current in the transformer neutral conductor occurs in the PC0044 Distribution Transformer, namely 2.6737%, and based on PLN ED Decree No. 0017.E/DIR/2014, the neutral current TR is included in the good category because the power losses due to the neutral current in the transformer neutral conductor are <10%. The largest percentage of power losses due to neutral current flowing to the ground occurs in the PC0044 Distribution Transformer, namely 5.0784%.

A Digital Twin Framework for Simulating Distributed Energy Resources in Distribution Grids

As the adoption of distributed energy resources (DERs) grows, the future of electricity distribution systems is confronted with significant challenges. These challenges arise from the transformation of consumers into prosumers and the resulting increased system complexity, leading to more pressure on the distribution grids. To address this complexity, a Digital Twin framework is designed to simulate DERs within distribution grids effectively. This framework is structured around four key modules: DERs, the electricity distribution grid, the energy management system, and the consumers. It incorporates a communication interface to facilitate interactions among these modules and includes considerations for grid topologies and demand-side configurations. The framework allows for the exploration of various DER adoption rates and capacities. The validation of this framework involves case studies on two Danish distribution grids with scenarios incorporating rooftop photovoltaic (PV) systems, batteries, and electric vehicles, considering different combinations of these technologies. The findings demonstrate the framework’s ability to depict the states of the grid, PV systems, electric vehicles, and battery systems with a 10 min resolution over periods ranging from a day to over a decade.

Enhancing Electrical Distribution System Efficiency: A Software Tool Design for Conductor Cross-Section Optimization With TLBO Algorithm

In radial distribution networks with many separate branches and sections, it is very difficult to calculate the optimum conductor cross-section. This work introduces a new tool for optimizing conductor cross-sectional area in electrical distribution systems by utilizing the Teaching-Learning-Based Optimization (TLBO) algorithm. The tool can optimize the conductor crossection of the multisection, branching distribution systems. The maximum current carrying capacity constraint is taken into consideration when formulating the objective function to choose the ideal conductor size for each network segment. The optimal conductor sizes are determined by both desired percent voltage drop and current carrying capacity of the conductor. By calculating the currents drawn from the line segments in advance, the search space of the optimization algorithm is narrowed. MATLAB and Excel were used to determine the ideal conductor size. The conductor, which is chosen using the suggested method, will preserve appropriate voltage levels in radial distribution systems while optimizing the overall savings in conducting material and energy loss costs. The outcomes show that the optimal selection of conductor problem can be solved by the TLBO algorithm in a practical and effective manner. Results of testing the suggested tool on a radial distribution system are noteworthy.

Voltage Optimization on Low Voltage Distribution Transformer Zones Using Batteries in Uganda

In the context of Uganda's rapidly growing energy demands and the need for sustainable solutions, this study explores the implementation of voltage optimization techniques in Low Voltage (LV) distribution transformer zones. The research focuses on the innovative integration of batteries to optimize voltage levels, thereby enhancing the efficiency and reliability of the electrical distribution system. By analyzing real-time data from various LV transformer zones in Uganda, this study investigates the impact of voltage fluctuations on the overall power distribution network. The research methodology involves the design and deployment of battery energy storage systems (BESS) strategically placed within LV distribution transformer zones. These BESS units are utilized to store excess energy during periods of low demand and release it during peak hours, ensuring consistent voltage levels and minimizing losses in the distribution network. The study evaluates the effectiveness of this approach through extensive simulations and on-site experiments, considering factors such as battery capacity, charging/discharging rates, and load variations. A comprehensive cost-benefit analysis is conducted to evaluate the potential financial savings and environmental impact associated with this sustainable energy solution. The findings of this research indicate significant improvements in voltage regulation, reduced system losses, and enhanced reliability in LV distribution transformer zones. Additionally, the study demonstrates the feasibility of integrating batteries into the existing infrastructure, thereby contributing to the optimization of the energy distribution system in Uganda. The outcomes of this research provide valuable insights for policymakers, utility companies, and researchers, emphasizing the importance of embracing innovative technologies to address the energy challenges faced by developing nations like Uganda.

A Reviewed Turn at of Methods for Determining the Type of Fault in Power Transformers Based on Dissolved Gas Analysis

Since power transformers are the most important pieces of equipment in electricity transmission and distribution systems, special attention must be paid to their maintenance in order to keep them in good condition for a long time. This paper reviews the main steps in the process of diagnosing the health of power transformer insulation, which involves the science of analysing the gases dissolved in power transformer oil for effective identification of faults. An accurate diagnosis of incipient faults is favourable to sustainable development and necessary to maintain a reliable supply of electricity. The methods presented for fault diagnosis in mineral-oil-immersed power transformers are divided into analytical and graphical methods and have been found to be simple, economical and effective. After describing the methods, both their strengths and weaknesses were identified, and over the years, the methods were complemented to provide highly accurate information, validated by field inspections. This paper focuses on practical information and applications to manage maintenance based on accurate and up-to-date data. The contents of this paper will be of particular use to engineers who manufacture, monitor and/or use high-power transformers in the energy sector, as well as to undergraduate, master’s and PhD students interested in such applications.

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.

Determining target levels of power distribution system reliability indices using machine learning

Electrical distribution system (EDS) reliability has always been a critical subject due to the considerable share of distribution systems in power interruptions to end-users. Meeting regulatory service quality standards requires distribution companies to achieve defined reliability levels for performance improvement. Conventionally, specialists determine target reliability based on experience, experimental knowledge, and rules of thumb. However, these methods are error-prone and may result in suboptimal investments, economic inefficiency, and inadequate resource allocation in EDS operation and planning. Accordingly, this paper presents a machine learning-based method to determine the target level for EDS's reliability indices based on its historical performance. The approach involves comprehensive analysis of historical EDS reliability data, followed by a data envelopment analysis (DEA) to assess performance across subdivisions like substations or feeders, identifying the most effective units. Subsequently, machine learning models—Random Forest (RF), Support Vector Machine (SVM), and Radial Basis Function (RBF) network—are trained on optimal subdivisions from the DEA stage. These models accurately estimate target reliability for all subdivisions, contributing to the overall determination of the EDS target reliability level. A three-scenario case study validates the proposed method, suggesting its potential applicability as a valuable tool for regulatory agencies in setting EDS reliability targets. While admitting the potential challenges, notably the method's reliance on the quality and completeness of the historical data collected by distribution companies, the paper emphasizes the importance of collaborative efforts to ensure data accuracy and sufficiency. The proposed method leads to a fair mechanism to determine the target level for a real EDS's reliability indices in comparison with a business-as-usual scenario. Moreover, it provides a reliability performance ranking for the EDS's subdivisions.

Design of Radial Distribution System to Study Load-Flow and Short Circuit Analysis Using ETAP Software

This work's analysis provides information on fault analysis and load flow studies, which help to understand how radial distribution networks operate both in normal and emergency circumstances. The research explores optimization methods, describing capacitor placement, transformer size, and feeder reconfiguration in order to lower losses and increase system efficacy. Moreover, the work looks at reliability-focused maintenance techniques, stressing the need of predictive maintenance and condition monitoring in raising the dependability of radial distribution networks. Modern electrical power networks depend heavily on their radial distribution system, which effectively and dependable distributes electricity to customers. Many radial distribution system-related topics are covered in detail on this website, including analytical methods, optimization processes, and dependability enhancement strategies. Power flow, voltage control, and losses in radial networks are investigated in this paper under a range of operational situations. The last and crucial stage of a power system, the electrical distribution system makes sure that customers have a steady supply of electricity. Regretfully, because it is often neglected and exposed to environmental risks, our distribution network has a number of problems. Our distribution feeder is rigorously analyzed for load flow and short-circuits in order to overcome these challenges and find and fix problems. The main topics of this study are the load flow and short-circuit analysis of a radial distribution feeder, which is mostly constructed with (ETAP). The final and crucial part of a power system, the electrical distribution system ensures that consumers receive an uninterrupted and steady supply of electricity. Our distribution feeder undergoes a rigorous and cautious process to address these issues front on because of the uncontrollable nature and susceptibility of our network to environmental hazards. This paper delves deeply into the issues of short-circuiting and load flow in radial distribution feeders. Both symmetrical and asymmetrical faults are thoroughly investigated by mathematical computations and ETAP simulations; the results of the software simulations are contrasted with those of the mathematical analysis. These discoveries will definitely influence the development and management of our system and point us in the direction of workable and practical solutions.

Sequential Quadratic Programming (SQP) Based Optimal Power Flow Methodologies for Electric Distribution System With High Penetration of DERs

Sequential Quadratic Programming (SQP) Based Optimal Power Flow Methodologies for Electric Distribution System With High Penetration of DERs

Measuring the digitalisation of electricity distribution systems in Europe: Towards the smart grid

This paper proposes a set of digitalisation indicators focused on measuring the different digital capabilities and infrastructure of electricity distribution systems, as opposed to previous indicators which have mainly focused on performance and quality of service aspects.The indicators are classified according to the pillars of digitalisation: sensor and actuator, connectivity, data processing, and digital culture. They are use-case-agnostic and do not require a huge amount of information. In addition to this, three possible new applications of these indicators for distribution system operators and regulatory authorities are identified and discussed.The extensive use of these indicators in Europe could allow the development of fruitful collaborations between distribution system operators, allow the identification of cause–effect relations between grid performance and digital infrastructure, and improve the replicability of innovative smart grid solutions. However, this will only be possible if regulators promote the adoption of the proposed indicators and the dissemination of their results.

Research on intelligent auxiliary regulation technology of large power grid section based on artificial intelligence

In the modern era, large-scale renewable energy systems are integrated with advanced power systems and provide efficient operations. Also, optimized power systems require accurate energy generation and effective control systems to manage and ensure a stable power supply. Nevertheless, uncertainties are the intermittent balance of supply and high electricity demand. In addition, conventional power sources are not applicable for this challenging task and increase electricity costs. Therefore, an efficient Neuro Fuzzy Single phase Unified Power Quality Conditioner with Maximum Power Point Tracking (NF-SP UPQC -MPPT) strategy is developed for enhancing the grid-connected power systems. Here, Neuro-fuzzy logic is used as dynamic reactive power compensation in the grid. Also, this logic can efficiently handle the Energy storage system (ESS). Then SP UPQC was used to enhance power quality in electrical distribution systems. It combines both series and shunt compensators to mitigate various power quality issues such as voltage sags, harmonics, and unbalance. After that MPPT was utilized to extract the maximum power from the grid system. Model Predictive Control (MPC) controller to determine the overall stability and performance of the system. Moreover, the developed model was implemented on the MATLAB platform and performance is analyzed in terms of voltage deviation, grid current, reactive power fluctuations and Total Harmonic Distortion (THD).

Performance Evaluation of Overcurrent Relay and Ground Fault Relay Coordination in Distribution Feeder

Reliable and sustainable electrical distribution systems require effective protection measures against internal and external disturbances, especially short-circuit disturbances, to avoid damage to the equipment. Overcurrent relays (OCR) and ground fault relays (GFR) play an important role in the safety of the distribution network. To improve performance, evaluation of relay coordination is essential. During the short circuit, the nearest relay to the fault point is activated first and the backup relay is activated if the fault current exceeds the adjustment of the main relay. Coordination ensures that timely signaling is sent to interrupt the circuit. Inspection of the OCR relay revealed that it did not comply with the IEC 60255 standard and consequently adjusted the classification time to 0.402 seconds. Similarly, the results of the GFR relay inspection did not meet the standards and required an adjustment of the evaluation time to 0.492 seconds. Resolving these deviations is crucial to maintaining the reliability and compliance of the distribution network with industry standards, ensuring that the protection relays respond quickly and effectively to disturbances, thereby preventing possible damage to equipment

Need Assessment for Coastal Tourism Area in the Face of Tsunami Risk: The Case of Pangandaran

As the fourth world's longest coastline, coastal tourism has become a significant component of Indonesia’s economy. Approximately 57% of this coastline is prone to the deadliest coastal hazard, i.e., tsunami. The progressive development of the tourism industry has created a massive increase in built infrastructure, hotels, roads, electrical and water distribution systems, and an increased number of people, including tourists and tourism workers, in rural coastal tourism areas. Due to the tsunami threat, rural coastal tourism regions' economic and social development faces enormous potential losses in lives and infrastructure and disruption of economic activity, especially for small and medium business enterprises. However, this coastal tourism industry has failed to engage in proper disaster risk reduction strategy and tourism business resilient building in most tourist destination regions in Indonesia. To address these complex problems, this study explores the adaptation of the concept of Business Continuity Plan of a single enterprise to upscale to an area or zone, i.e., the Area Business Continuity Planning, to enhance the holistic disaster-resilient tourism industry in Indonesia, with Pangandaran as the study location. As a newly formed regency, Pangadaran is an emerging super-destination tourism area designated by national and provincial governments. This region experienced a devastating tsunami in 2006, and even today, its coastal communities live under the threat of tsunamis that South Java Megathrust can generate. Based on an in-depth and holistic study, this study finds the Pangandaran coastal tourism resilience level, recognizing critical stakeholders and identifying the collaborative BCP strategies in Pangandaran.

Multilevel Aircraft-Inverter Design Based on Wavelet PWM for More Electric Aircraft

This paper proposes a comprehensive power system designed for the use of a more electric aircraft power distribution system. Instead of traditional Nicad battery solutions as the energy source of the aircraft power system, lithium battery structures, which are a recent and promising solution in the field of aviation power systems, are modeled and analyzed. In this study, a WPWM-based, single-phase, multi-level pure sine wave static aircraft-inverter system is designed and integrated to improve the performance of conventional aircraft power systems. In the designed power system, a boost converter structure is proposed that boosts 28 VDC-to-270 VDC voltage coming from the lithium–ion battery pack and can reach a steady state in 0.032 s. The performance of the modeled WPWM-based aircraft-inverter system, compared to SPWM Bipolar and Unipolar switching techniques commonly used in single-phase inverter designs, reveals a THD reduction of approximately 27% with WPWM, resulting in a THD value below 2% for both load current and load voltage. As a result of the study, a power system that will enable the aircraft avionics, ventilation, and navigation systems to perform better than conventional power systems and comply with aircraft electric-power characteristic standards has been designed and detailed.

Pre-Disaster Optimal Operation Strategy for Hydrogen-Fuel-Based Isolated Power System with Disaster Uncertainties

The increasing occurrence of severe weather phenomena presents substantial difficulties for electricity distribution systems. This study investigates the integration of hydrogen production plants (HPPs) into power distribution networks to bolster resilience against the increasing frequency of extreme weather events. It highlights the innovative use of hydrogen, generated from renewable sources, as an energy storage medium to ensure a stable power supply during disruptions. By employing stochastic optimization, the study aims to effectively manage hydrogen production and utilization, considering uncertainties in disaster scenarios and energy demands. It addresses critical research gaps, such as the lack of focus on pre-disaster preventive scheduling using hydrogen, the under-explored application of stochastic optimization in such contexts, and the predominance of real-time response strategies over pre-emptive measures. This approach significantly advances current understanding by proposing novel strategies that leverage hydrogen production and sophisticated optimization to enhance the resilience of power networks against extreme weather events. In some scenarios, using our method can reduce the cost of pre-disaster prevention by approximately 15.68% while ensuring that the disaster recovery effect remains unchanged.

Evolution and role of virtual power plants: Market strategy with integration of renewable based microgrids

The use of distributed energy resources (DER) programs, which include separate renewable energy (RE) programs, has expanded in residential as well as commercial structures as an outcome of recent technological developments. The virtual power plant (VPP) may improve the security and reliability of an electricity grid's operations through including energy storage, changeable loads, and distributed energy resources (DER), among other characteristics. Consequently, a growing number of scholars tend to focus on VPP and providing recommendations for its improvement. In order to facilitate the incorporation of distributed generation into electricity distribution systems, cutting-edge management ideas for facilities have emerged in the last few years. As a result, it is now more crucial than ever to improve management abilities for the combining of dispersed energy output and consumption using various virtual power plants (VPPs). To increase operational profits, it's crucial to make use of their capacity to play a role in power markets. This work provides a classification scheme for, and an in-depth analysis of, recent studies that provide VPP models featuring interactions with various forms of electricity markets. The objective of this article is to find out which VPP strategy will yield the greatest possible return in each legislative scenario. These consist of the model's design, strategies for resolving complex mathematical problems, involvement in various marketplaces, and the application of the suggested models to real-world case studies. The research has been evaluated, and it has been concluded that contemporary models are more comprehensive and realistic. This article additionally elaborates on and emphasizes the VPP concept from other researchers' findings. Moreover, a number of prevalent VPP projects from throughout the globe are included. The VPP research also addresses some potential challenges and recommendations for prospective growth.