Distribution Management Research Articles

Staying positive: producing net power.

The Spherical Tokamak for Energy Production (STEP) prototype powerplant (SPP) will be a first-of-a-kind powerplant-its prime objective is to export electrical power, to the national power transmission system ('grid'), above 100 MWe. As part of a wider issue, addressing the STEP concept design, this article seeks to explore how electrical power will be generated from a spherical tokamak heat source. Accordingly, the following key functions of the SPP power infrastructure are reviewed.Cooling the tokamak: cooling the tokamak while extracting useful thermal energy.Generating power: conversion of thermal energy to electrical energy (power generation).Managing energy: management of the site-wide distribution, storage and energy export.In each of these areas, the design scope, challenges and solution spaces have been discussed. This has shaped the design of the SPP power infrastructure, which in turn has ensured a powerplant design focused on operability and performance. Furthermore, it has been demonstrated that the SPP will achieve its prime objective in generating net power, which is enabled by a unique power infrastructure. Confidence in the ability to generate net power will be refined as the design matures. Finally, this article recommends key opportunities that STEP could use to improve power generation and reduce the parasitic load of the SPP.This article is part of the theme issue 'Delivering Fusion Energy - The Spherical Tokamak for Energy Production (STEP)'.

Investigation of a model predictive control (MPC) strategy for seasonal thermochemical energy storage systems in district heating networks

This research investigates the integration of model predictive control (MPC) with seasonal thermochemical energy storage systems (STES) within district heating networks, focusing on the Nottingham district heating as a case study. The primary aim is to develop an MPC strategy that utilizes machine learning models for accurate heat load forecasting. This strategy optimizes the charging and discharging cycles of thermochemical energy storage systems to mitigate the mismatch between heating energy supply and demand by storing surplus heat during summer and utilizing it during winter. We employed and validated machine learning models, including support vector regression (SVR), regression trees, and long short-term memory (LSTM) networks, using historical heat load and meteorological data. A validated numerical model of the thermochemical energy storage system (TCES) was integrated into the MPC framework, formulated as a mixed-integer linear program to optimize the STES's operations. The performance of the MPC strategy was benchmarked against a rule-based control approach under varying supply capacities to evaluate scalability and robustness. Our findings reveal that each machine learning model achieved comparable performance, with CVRMSE values within the 9–11% range. The LSTM model, in particular, provided accurate multi-step forecasts essential for the MPC framework. Incorporating these models into the MPC strategy allowed for precise heat demand predictions, enhancing the management of energy storage and distribution. Results confirmed that MPC effectively shifts energy seasonally, reduces reliance on auxiliary heating during winter, and minimizes waste heat. The MPC strategy outperformed the rule-based control by storing a significantly higher percentage of waste heat and meeting a greater portion of the additional heat demand that was not covered by the auxiliary heat supply. The system demonstrated effective performance under varying supply capacities, with the MPC strategy efficiently utilizing stored heat to meet demand at 80% supply capacity, achieving a waste heat reduction to 4% and meeting most of the heat demand. However, performance declined at 60% capacity, indicating the need for careful consideration of supply capacities in system design. This study highlights the potential of integrating machine learning models with MPC to enhance the performance and adaptability of district heating systems with STES, minimizing waste heat and efficiently meeting energy demands.

Entropy generation and Cattaneo–Christov heat flux analysis of binary and ternary hybrid Maxwell nanofluid flows with slip and convective conditions

Hybrid nanomaterials significantly enhance thermal systems through improved thermal conductivity, efficient energy storage, and customized thermomechanical properties. Due to their superior thermophysical characteristics, binary/ternary hybrid nanofluids are crucial in fields such as industry, biomedicine, transportation, and pharmaceuticals. This study examines the hydromagnetic flows and heat transfer properties of binary (CuO+Fe3O4/sodium alginate) and ternary (CuO+Fe3O4+MoS2/sodium alginate) hybrid Maxwell nanofluids over a radially stretching rotating disk. The governing flow equations incorporate Cattaneo–Christov heat flux, mixed convection, velocity and thermal slips, nonlinear radiation, viscous dissipation, and Joule heating in a Darcy–Forchheimer porous medium. These axisymmetric partial differential equations are transformed into ordinary differential equations using similarity variables, and the spectral quasilinearization method (SQLM) is applied for numerical solutions. Results reveal the effects of relevant parameters on velocity, temperature, skin friction, and heat transfer rates. Novelty lies in the comparative analysis of flow behaviors and entropy production rates between binary and ternary hybrid Maxwell nanofluids. When the heat source is included, the Nusselt number increases by 12.9% for ternary nanofluids and 16.07% for binary nanofluids as the thermal relaxation number increases from 0.5 to 1.5. Furthermore, the ternary hybrid nanofluid shows greater resistance to Lorentz and porous medium forces and exhibits a higher temperature distribution and better thermal management capabilities compared to the binary hybrid nanofluid.

Cost analysis of IPv6 distributed mobility management protocols in comparison with TFMIPv6.

The past decade has witnessed a significant evolution in the role of the Internet, transitioning from individual connectivity to an integral aspect of various domains. This shift has prompted a move in IP paradigms from hierarchical to distributed architectures characterized by decentralized structures. This transition empowers efficient data routing and management across diverse networks. However, traditional distributed mobility management (DMM) protocols, reliant on tunneling mechanisms, incur overheads, costs, and delays, exacerbating challenges in managing the exponential growth of mobile data traffic. This research proposes Tunnel-Free Mobility for IPv6 (TFMIPv6) as a solution to address the shortcomings of existing DMM protocols. TFMIPv6 eliminates the need for tunneling, simplifying routing processes and reducing latency. A comprehensive cost analysis and performance evaluation are conducted, comparing TFMIPv6 with traditional protocols such as MIPv6, PMIPv6, FMIPv6, and HMIPv6. The study reveals significant improvements with TFMIPv6. Signaling costs are reduced by 50%, packet delivery costs by 23%, and tunneling costs are completely eliminated (100%). Real-world network traffic datasets are used for simulation, providing statistical evidence of TFMIPv6's efficacy in supporting an uninterrupted movement of IPv6 data across networks.

Dynamic load shedding and system restoration using wide area distribution management system

AbstractThe demand for electric power has consistently been on the rise, owing to urbanisation and technological improvements. On the generation side, renewable sources have been favoured over their polluting, exhaustible, non‐renewable counterparts. These changes in the power system have necessitated a system for maintaining the supply‐demand balance, to maintain system stability. A complex power system is also more prone to blackouts and grid failure. Islanding helps in provision of supply to consumers in a microgrid, reducing the possibility of a blackout. Depending on the power demand and generation, loads need to be shed or restored to mitigate power imbalances. A wide area distribution management system (WADMS) is proposed to dynamically shed and restore loads in the islanded mode, with the aid of micro phasor measurement units (µPMUs). A priority and consumer‐based load shedding and restoration (PCLS) algorithm is proposed in the WADMS that preferentially sheds or restores loads based on their assigned load priority indices and number of consumers. The algorithm has been tested on a modified IEEE 13 bus system, incorporated with a solar photovoltaic (PV) system, diesel generators (DGs) and an energy storage system (ESS) in MATLAB Simulink.

Design and Implementation of a Generalized Safety Fault Diagnosis System for China Space Station Scientific Experimental Rack.

As astronauts stay in the China Space Station for a long time during the operation phase, how to ensure the long-term safety of the scientific experimental rack (SER) in the field of space application is a problem that needs to be solved urgently. Each SER in the field of space station applications is a complex system that faces risks from different hazards. At present, there is no generalized monitoring and diagnosis system for the common risks faced by the SER. In this paper, a generalized safety fault diagnosis system is proposed to ensure the long-term safe and stable work of SERs in orbit, considering the actual risks faced by the SER. With the design of a generalized main control board, a measurement and control board, and an SSPC (solid-state power controller) board, the software and hardware cooperate to realize the acquisition of various physical quantities, data processing, power supply and distribution management, and other functions. Combined with relevant fault detection algorithms, the real-time detection and diagnosis of the relevant risks, abnormality warnings, and fault disposal operations are realized, which can effectively ensure the safety of the payloads in the field of space application, astronauts, and the space-station system.

The Role of Logistics and Infrastructure in Promoting International Trade

This study aims to explore the role of logistics and infrastructure in promoting international trade. Through systematic analysis of relevant theories and practical impacts, the research finds that logistics and infrastructure play key roles in reducing transaction costs, enhancing trade speed and reliability, and promoting market connectivity and integration. Specifically, an efficient logistics system can optimize transportation, warehousing, distribution, and inventory management, thereby improving the overall efficiency of international trade. Meanwhile, modern transportation, information and communication, and energy infrastructure provide robust support for international trade, facilitating efficient global supply chain operations and economic growth. However, the logistics and infrastructure sectors also face challenges such as infrastructure aging, cross-border logistics barriers, environmental issues, and sustainability concerns. In the future, smart logistics, green logistics, public-private partnerships, and international cooperation will become important development trends. Based on these findings, this paper proposes that governments should formulate supportive policies and improve infrastructure investment mechanisms, while enterprises should enhance logistics optimization and technological innovation. By conducting an in-depth study of the role of logistics and infrastructure in international trade, this research aims to provide theoretical support and practical guidance for policymakers and enterprises, promoting sustainable development in international trade.

Assessment of the Technical Impacts of Electric Vehicle Penetration in Distribution Networks: A Focus on System Management Strategies Integrating Sustainable Local Energy Communities

Aligned with the objectives of the energy transition, the increased penetration levels of electric vehicles as part of the electrification of economy, especially within the framework of local energy communities and distributed energy resources, are crucial in shaping sustainable and decentralized energy systems. This work aims to assess the impact of escalating electric vehicles’ deployment on sustainable local energy community-based low-voltage distribution networks. Through comparative analyses across various levels of electric vehicle integration, employing different charging strategies and system management approaches, the research highlights the critical role of active system management instruments such as smart grid monitoring and active network management tools, which significantly enhance the proactive management capabilities of distribution system operators. The findings demonstrate that increased electric vehicle penetration rates intensify load violations, which strategic electric vehicle charging management can significantly mitigate, underscoring the necessity of load management strategies in alleviating grid stress in the context assessed. This study highlights the enhanced outcomes derived from active system management strategies which foster collaboration among distribution system operators, demand aggregators, and local energy communities’ managers within a local flexibility market framework. The results of the analysis illustrate that this proactive and cooperative approach boosts system flexibility and effectively averts severe grid events, which otherwise would likely occur. The findings reveal the need for an evolution towards more predictive and proactive system management in electricity distribution, emphasizing the significant benefits of fostering robust partnerships among actors to ensure grid stability amid rising electric vehicle integration.

Where do data sovereignty security risks come from?-Production perspective based on social reproduction

As a new factor of production, data has been rapidly integrated into all aspects of production, distribution, circulation, consumption and social service management, and has had a profound impact on production methods, lifestyles and social governance methods. In essence, data, as a new factor of production, is the result of the contradictory movement of productivity and production relations in the process of economic development in the digital economy era. It is also the reconstruction of productivity and production relations in the digital era. While the digital industry and digital economy have become an important engine leading global economic growth and bringing huge dividends, data as a production factor is also accompanied by rising sovereign security risks. Taking the production of data elements in social reproduction as an entry point, we clarify the possible security risks of data as a new production factor in the production process, analyze the data sovereignty security risks derived from the security risks, and find that data sovereignty security risks breed when data elements participate in social reproduction. In the production process, there are challenges and threats to data sovereignty security such as internal jurisdiction and control rights owned by sovereign countries, as well as external rights to equality and independence. Therefore, it is necessary to accurately grasp the data sovereignty security risks that exist in the production process of social reproduction of data elements, and build new data production relationships to match the development characteristics of new productive forces, so as to prevent and resolve non-traditional security risks caused by sovereignty security.

SELF-HEALING MECHANISM BASED ON FAULT MANAGEMENT FOR SMART-GRID DEVELOPMENT ON 20kV SPINDLE NETWORKS TO IMPROVE DISTRIBUTION SYSTEM RELIABILITY AT PLN UID JAKARTA-INDONESIA

This study aim is to study for the development of smart grid with the implementation of network automation in the spindle system to improve reliability, revenue and customer experience in the priority areas of PLN UID Jakarta. The addition of new substations has an impact on the reconfiguration changes and the addition of new networks in the context of loading feeders and causing the topology of the distribution network to be increasingly complex and impure spindle systems, in addition to the jammed condition of Jakarta also has an impact on the longer time in investigating disturbances, as well as the limited investment budget of PLN has not supported the installation of new keypoints in all distribution substations. This research was carried out by system modeling in the SCADA Distribution Management System for N-1 contingency and a simulation of the Self-Healing Mechanism test based on static and dynamic data parameters in real-time according to the Load Flow and Load Forecast in the SCADA systems. Evaluation of technical and financial feasibility as a smart feeder design that will be implemented in the spindle system, on the other hand, it is expected to be a Distribution Grid Management design that is feasible to be implemented in the 20kV Spindle system as an alternative to Zero Down Time to accelerate the recovery time of distribution disruptions and improve reliability performance in controlling the operation of the distribution system at PLN UID Jakarta.

Operational challenges and strategic solutions for power distribution in Mendol Island

Purpose: This thesis addresses critical issues within the plant's capacity and operational framework, emphasizing the importance of enhancing the generation system's resilience through the N-1 and N-2 capacity criteria. Research Methodology: The research methodology encompasses both qualitative and quantitative data collection methods, including observations, interviews, brainstorming sessions, and document reviews. Results: The study's findings highlight the significant gaps between the plant's targeted and actual performance metrics over a four-year period, revealing persistent underperformance in energy production and substantial fluctuations in fuel consumption. The application of N-1 and N-2 criteria is crucial for ensuring the system's reliability and resilience, particularly as renewable energy sources are integrated into the grid. Limitations: Contribution: The contribution of this research to the field of power distribution management is twofold: it provides a comprehensive analysis of the challenges facing the Teluk Dalam Diesel Power Plant and proposes viable solutions to enhance its operational performance and sustainability.

Competitive Analysis at the Cournot-Nash Equilibrium of an Interconnected Network

The electric power network has long been subject to monopolization, encompassing production, transportation, and distribution sectors. However, recent liberalization efforts have introduced competition into the electricity market. To understand and manage this competition, game theory, a prominent tool in economics, is frequently employed. Specifically, competition within the electricity market has been analyzed through various game-theoretical models, including Bertrand's atomicity, Cournot's homogeneity, and Nash's research competition. These models aim to achieve the Cournot-Nash equilibrium, where each participant in the market makes optimal decisions given the strategies of others. To effectively allocate production and ensure a balance between supply and demand, as well as to maintain the stability of the interconnected network, one has adopted a method that combines Load Flow techniques with game theory principles. This hybrid approach enables a strategic distribution of power production, taking into account the competitive dynamics of the market. By integrating these methodologies, one can address the complexities of competition while ensuring efficient and stable operation of the power grid. This innovative approach not only enhances the management of electricity production and distribution but also fosters a more competitive and resilient power network. Moreover, the application of game theory in this context allows for a deeper understanding of strategic interactions among market participants. It helps in predicting behaviors, formulating strategies, and anticipating market changes, thus providing a robust framework for decision-making. This is particularly crucial in a liberalized market where multiple entities vie for market share and profitability. By employing game-theoretical insights, one can simulate various market scenarios, optimize resource allocation, and enhance overall market efficiency. Furthermore, this approach supports the integration of renewable energy sources by ensuring that their variable nature is accommodated within the grid's operational dynamics. In summary, the intersection of game theory and load flow methods offers a comprehensive solution to the challenges posed by a competitive electricity market, paving the way for a sustainable and efficient energy future.

Mock Wards: Incorporating a Theoretical Framework to Create a Blended Virtual and In-Person Clinical Reasoning Education Platform.

Introduction The coronavirus 2019 pandemic highlighted virtual learning (VL) as a promising tool for medical education, yet its effectiveness in teaching clinical reasoning (CR) remains underexplored. Past studies have suggested VL can effectively prepare students for clinical settings. Informed by the Milestones of Observable Behaviours for CR (MOBCR) and whole-case theoretical frameworks, the Mock Wards (MW) program was created using a novel blended in-person learning (IPL) and VL platform. MW consisted of case-based small-group formats for medical students interested in learning approaches and differentials to commonly encountered presenting symptoms and diagnoses in internal medicine. This study sought to use MW's blended design to qualitatively analyze CR development and compare its utility between VL and IPL. Methods Qualitative analysis was conducted using in-depth semi-structured interviews with first-year pre-clerkship medical students (n = 8) who completed the MW program and participated in the study. The interview guide was informed by the MOBCR framework. Interview transcripts were analyzed using a directed qualitative content analysis approach. Translational coding and HyperRESEARCHTM (Researchware, Inc., Randolph, MA) software-generated mind maps guided the theme development. Results Three overarching themes were constructed: (1) tailoring pedagogical frameworks to learning modalities, (2) learning through interactivity, and (3) balancing accessibility with learner engagement. Participants emphasized that teaching CR skills is modality-specific and not fully interchangeable, with IPL being superior in facilitating social cohesion, non-verbal communication, and feedback. In contrast, VL required structured approaches and relied more on verbal communication and pre-made digital materials. IPL also enhanced interactivity, peer relationships, and spontaneous communication, whereas VL faced challenges such as social awkwardness and technological constraints hindering effective collaboration. VL provided superior accessibility to facilitate distributed learning and management of concurrent academic obligations. Conclusion The MW-blended platform highlights the importance of focusing on modality-tailored pedagogies, emphasizing group interactability, and balancing VL accessibility against decreased engagement within the IPL environment when teaching CR skills. Blended education models may benefit from a scaffolding approach, using IPL as a prerequisite to VL to improve CR development and alignment within a learner's zone of proximal development.

Binucleate Rhizoctonia on potato: Geographic distribution, identification, taxonomy, genomics, host range and disease management

AbstractAnastomosis groups belonging to the genus Rhizoctonia are phytopathogenic fungi that affect many agricultural crops and are well distributed globally. Among these, Rhizoctonia solani is the dominant, aggressive, widely distributed and the most extensively studied species within the Rhizoctonia genus because of its dominance as a plant pathogen. However, limited attention has been given to other Rhizoctonia species as they were believed to have little or no role in causing diseases on potatoes. Recently, accumulating information indicated that binucleate Rhizoctonia (BNR), previously considered to be saprophytic, mycorrhizal and even biocontrol agent, is phytopathogenic on many agricultural crops including potato. Up until now, there has been no comprehensive review on BNR. However, there is an intense need to understand its taxonomy, biology, detection, genomics and management, not only due to the growing increased survival and occurrence in various climatic conditions. The limited diagnostic methods, and genomic knowledge make understanding and managing of BNR species difficult. This review outlines the information available in peer‐reviewed literature regarding the BNR anastomosis groups associated with potato diseases, geographical distribution, detection methods, genomics, nomenclature and taxonomical evolution along with some possible management and control strategies.

System model of risks and trees of alternative solutions for improving the logistics chain at a manufacturing enterprise

The subject of this article is the decision-making processes for improving the elements of the supply chain of a manufacturing enterprise under conditions of uncertainty and risks. The purpose of the research is to reduce the time and cost of in supply and distribution of products of manufacturing enterprises by considering possible risks through making rational management decisions. The article addresses the following tasks: examination of the characteristics of supply chain elements; investigation of the main problems of supply and distribution management and identification of ways to solve them; development of a systemic model of logistic risks for a manufacturing enterprise; and formation of decision trees for alternative decisions in strategic supply chain management at manufacturing enterprises. The methods applied include a systems approach, structural decomposition methods, a risk-oriented approach. The following results were obtained: features and problems of supply chain elements such as supply, production, storage, and distribution were examined and identified; main supply chain management tasks were investigated and solutions identified; problems in warehouse management were pinpointed; internal and external supply risks were identified; a systemic model of logistic risks for a manufacturing enterprise was formed, which main components are logistic problems, partial risks, their consequences, and possible management decisions to mitigate risks; decision trees were built for problems of raw material supply instability and transportation bottlenecks and delays; an alternative decision diagram was constructed for an illustrative example. Conclusions: To overcome the problem of raw material supply instability, it is recommended to develop diversification of supply sources, stock reservation, and the use of alternative transport routes. Building alternative decision trees in strategic management is an effective tool for making rational decisions by manufacturing enterprises in complex conditions of uncertainty and risks. They help to analyze alternatives and their consequences to choose a path to optimize the supply chain.

The Evaluation of Water Loss in The Western North Tarum Irrigation Channel

The Western North Tarum Irrigation channel plays a crucial role in supplying water to irrigated agricultural areas. However, it encounters challenges in ensuring adequate water delivery to all channel segments. This research assesses water loss during the distribution process in the Western North Tarum Irrigation channel, focusing on the evaluation of channel capacity and the impact of suboptimal water management on water loss. The study employs the HEC-RAS model, a hydraulic system analysis tool, to evaluate the channel’s capacity and simulates its behavior under various discharge conditions. The evaluation reveals that two channel segments, B.TUB 13 and B.TUB 25, have exceeded their capacity limits, resulting in overflow. Sedimentation downstream, particularly in these segments, exacerbates the issue by altering the channel slope and impeding water flow. This research identifies poor water distribution management as a significant factor contributing to water loss in the irrigation channel. Inadequate scheduling and the absence of proper water measurement tools result in instances of overwatering or underwatering in some areas. The lack of monitoring and control in the irrigation system hampers the detection of uncontrolled flow in the channels, leading to substantial water loss and inefficient water use. This research underscores the importance of evaluating and maintaining irrigation channel capacity to prevent overflow and water loss. Furthermore, it emphasizes the significance of effective water management to achieve more efficient water distribution and irrigation. Addressing these challenges is crucial for ensuring the long-term sustainability of irrigated agriculture in the Western North Tarum Irrigation area.Keywords: HEC-RAS, Irrigation Channel, Water Distribution, Water Loss, Western North Tarum

Plant pathogenic Paramyrothecium species: distribution, biology, epidemiology and disease management

Plant pathogenic Paramyrothecium species: distribution, biology, epidemiology and disease management

A Brief Systematics Review and Visualization of Smart Cities based on Fog and Big Data Analysis Technology

The fog computing is based on IoT, and same as clouds are on the edge of a network between a device and the cloud, which can provide very close service to the device in real time. cloud computing frameworks also extend support to emerging application paradigms such as IoT, Fog computing, Edge, and Big Data through service and infrastructure. the ubiquitous deployment of sensors in smart cities requires a high-performance computing paradigm to support big data analysis with smart technologies and communications in IoT, providing location-awareness and latency-sensitive computing near the data sources (i.e., at the edge of the network). Cloud Computing paradigms widely used in enterprises to address the emerging challenges of big data analysis because of its scalable and distributed data management scheme. However, data centers in the Cloud faces great challenges on the burden of exploding amount of big data and the additional requirements of location awareness and low latency at the edge of network necessary for smart cites. the widely distributed sensor networks generate massive volume of data, which leads to a “Big Data “analysis challenge. The machine-to-machine(M2M) communication among massive numbers of sensors will dominate future communication network traffic, namely Internet of Things, instead of traditional Internet of Contents (IoC) in human-to-human and human-to-machine communication. In this review system where we took the research article around 33 from the different database and also taken 1987 datasets form the PubMed database from 1959 to 2024 (02 June 2024). In addition, depending on the different requirement which is partially processed the data. Then the gathered data is stored at the ledger unit through the smart cities based on the fog computing and big data technology. The hashing identity-based data encryption is a public key encryption which uses a digital signature to encrypt the data to prevent the information from the third party.

Effects of gaseous hydrogen peroxide on quality, shelf life and distribution management strategy F.E.F.O. (first expired, first out) of guavas cv. Pedro Sato

During the cold chain, fruits are exposed to variations in temperature and relative humidity, which will contribute to reducing the quality and commercial value of these perishable products. Aiming to extend the shelf life, reduce losses and increase profits from the trade of climacteric fruits, this work estimated the commercial value of ‘Pedro Sato’ guavas treated or not with hydrogen peroxide during the cold chain and evaluated the feasibility of replacing the management system of stock F.I.F.O. (first In, first Out) by F.E.F.O. (first expired, first out) The commercial value of guavas was determined by combining the values of weight loss, tonality and firmness, which were estimated by semi-empirical models. The experimental data showed that peroxide positively influenced the quality of guavas, quality assessments demonstrated that weight loss was the attribute that limited the shelf life of guavas and flow simulations, along the cold chain, confirmed that the implementation of a F.E.F.O. management system can increase retailer's profits by up to 13 %.

Evaluasi Ketidakseimbangan Beban Pada Penyulang Unicora

Load imbalance in electrical distribution transformers can lead to significant power losses and decreased efficiency in electrical distribution systems. This study focuses on the load imbalance problem at the Unicora feeder of PT PLN (Persero) ULP Singosari, which hinders optimal operational efficiency. The purpose of this research is to evaluate the extent of load imbalance, its impact on power losses, and the effectiveness of load balancing interventions in mitigating these losses. The methodology includes phase load measurements from February to September 2021, analysis of load imbalance, and power loss simulations using ETAP 12.6.0 software. The study's important findings indicate that the average load imbalance decreased from 34% to 21% after implementing load balancing interventions. Concurrently, power losses in the neutral conductor were reduced from 106.3 kW to 78.0 kW. ETAP simulations revealed a total power loss of 773.5 kW in the Unicora feeder, underscoring the significant impact of load imbalance on system efficiency. The implications of this research are crucial for operational practices at PT PLN (Persero) ULP Singosari. The findings demonstrate that effective load balancing can significantly enhance distribution efficiency, reduce operational costs, and improve the reliability of electricity provision. This study advocates for continuous monitoring and adaptive management of load distribution in electrical networks to maintain optimal performance and sustainability.