Utilities Research Articles

Framework of Smart Multi-purpose Utility Tunnel Information Modeling for Lifecycle Management

Multi-purpose Utility Tunnels (MUTs), as an alternative to buried and above-ground utilities, can accommodate multiple utilities, such as gas, water, and sewer pipes, and electrical and telecommunication cables. Despite MUTs' advantages, their high initial construction cost and the need for coordination among utility companies hindered their wide usage. Building Information Modeling (BIM) can solve some of these problems by facilitating the design, construction, operation, and coordination of utility companies. However, BIM is mainly developed for buildings and extended to some civil structures. There is a lack of a comprehensive framework covering MUT components and information requirements for other use cases, and its integration with Geographic Information Systems (GIS) and other technologies. This paper proposes an integrated framework for Smart MUT Information Modeling (SMUTIM) by (1) gathering the information requirements for all the phases of lifecycle management, (2) analyzing the use cases of SMUTIM, and (3) extending the Industry Foundation Classes (IFC) to SMUTIM. A case study demonstrates the benefits of the proposed framework.

Powering Change: A Methodology for Prioritizing Locations When Burying Power Lines to Minimize Wildfire Damage in Communities

Purpose: Overhead power lines can spark and cause extremely devastating wildfires. This has happened with power lines from utility companies such as Pacific Gas and Electric Company (PG&E), Southern California Edison (SCE), and San Diego Gas and Electric (SDG&E). One method of preventing widespread wildfires is to bury power lines underground. When planning to bury lines, utility companies must evaluate where power lines should be buried to minimize collateral damage from wildfires while enhancing infrastructure strength. This research paper advances a novel methodology for identifying and prioritizing the ideal locations for underground power lines. Methodology: Using California as a case study, I examine low, medium, and high wildfire risk locations in PG&E’s, SCE’s, and SDG&E’s jurisdictions. I determine which locations should be prioritized regarding the construction of underground lines by looking at the following factors in geographic information system (GIS) mapping: overhead power lines, critical infrastructure, past wildfire activity, population density, disadvantaged communities, and thermal hotspots. Findings: The results reveal the importance of considering variables like population and infrastructure density when mitigating wildfire risk with underground power lines, expanding the evaluation beyond typical factors like dry vegetation. Unique Contribution to Theory, Practice and Policy: My methodology can be used by utility companies in order to conserve resources and time due to the structured approach. Doing so will also expedite the process of burying power lines which minimizes the impact of wildfires caused by overhead lines.

Goods and Services Tax (GST) and Its Impact on North East India: A Study of Revenue Generation and Public Utilities

Goods and Services Tax (GST) and Its Impact on North East India: A Study of Revenue Generation and Public Utilities

Utilization of Electronic Information Resources as Correlates of Publication Output by Researchers in Agricultural Research Institutes in Oyo State, Nigeria

The study examined the utilization of electronic information resources (EIRs) as correlates of publications among research scientists in National Agricultural Research Institutes (NARIs) headquarter in Ibadan, Oyo State, Nigeria. Correlational research method was used to determine the relationship between utilization of EIRs and publications output among research scientists. Simple random sampling technique was used to select 217 respondents from a sample frame of 282 researchers based on Morgan’s table for sample size in four (Institute of Agricultural Research and Training, National Institute of Horticultural Research, Forestry Research Institute of Nigeria and Cocoa Research Institute of Nigeria) NARIs. Data were obtained on types of EIRs utilized, extent of use, effect of EIRs utilization on publication and the total of researchers’ publications using a structured questionnaire. The results obtained were analyzed using descriptive statistics (frequency counts, percentages, mean and standard deviation) and Pearson Product Moment Correlation coefficient (PPMC). Results revealed that major types of EIRs utilized by the researchers for their publications were Access to Global Online Research in Agriculture ( 3.46), Online Access to Research in the Environment ( 3.41) and The Essential Electronic Agricultural Library ( 3.32). The result further revealed that researchers have a high extent of use of EIRs with 100% utilization. The researchers stated that utilization of EIRs enhances efficient and effective publications ( 3.58) improve the quality of their publications ( 3.52) and enhance their decision making in publishing ( 3.48). Results further revealed that 74.9% and 85.3% of the researchers published more in local journals and proceedings respectively compared to 25.1% and 14.7% that published in international journals and proceedings respectively. PPMC revealed a significant (p<0.05) relationship between utilization of EIR (r = 0.127) and researchers publications. In conclusion, utilization of EIRs enhances the publication output of researchers in agricultural research institutes. Therefore, the study recommended that stakeholders and policy makers in agricultural research institutes should invest in facilities that will facilitate utilization of EIRs for publications activities among research scientists.

Decomposing disparities in the utilization of basic public health services between locals and internal migrants in China: the role of social determinants

BackgroundInternal migrants in China have long been at a disadvantage in terms of access to publicly financed services, as well as the utilization of public health services. The aim of the study was to examine inequities in the use of basic public health services between internal migrants and the local population and estimate the factors that contributed to inequity in use.MethodsThe data for this study was derived from the 2017 wave of the China Migrants Dynamic Survey. Basic public health services utilization was measured by the establishment of health records, health education and chronic disease management. We performed multivariable logistic regressions to examine inequities in the utilization of basic public health services between locals and internal migrants, and Oaxaca-Blinder decomposition was used to explore possible explanations for such inequities between the two groups.ResultsA total of 27,998 cases were included in the analysis. We found that the utilization rates for establishment of health records, health education and chronic disease management among internal migrants were 71.3%, 49.2% and 65.7% lower than their local counterparts, respectively. The decomposition results indicated that the inequities in the establishment of health records between locals and internal migrants were mainly explained by whether people had heard of the National Basic Public Health Services Program (NBPHSP) (17.67%) and by health insurance (5.99%). The contributors to the inequities in health education between locals and internal migrants were community involvement (14.71%) and whether people had heard of the NBPHSP (13.89%). The main factors contributing to the difference in utilization of chronic disease management between the two groups were whether people had heard of the NBPHSP (14.49%) and community involvement (8.43%).ConclusionsTo reduce inequities in the utilization of basic public health services between locals and internal migrants, measures need to be taken to improve knowledge about the basic public health services and to help migrants integrate into the local community.

The Impact of EU Taxonomy for Sustainable Activities on European Utilities' Performance

ABSTRACTThis study investigates the relationship between European utility companies' compliance with the EU Taxonomy for Sustainable Activities and their overall performance. The EU Taxonomy is a new regulation proposed by the European Commission to promote sustainable finance by 2050. The literature shows that nonfinancial disclosures have a favorable impact on financial performance. However, no research has been conducted to assess the implementation of the EU Taxonomy and its effect on firm performance. Using a sample of European utilities from 2012 to 2022, a difference‐in‐differences (DiD) model was applied to analyze the causal relationship between compliance and performance. Based on institutional and signaling theories, the results show that companies reporting alignment with the Taxonomy exhibit higher market value, profitability, and efficiency than those that do not. This study contributes to firms' transparency and enriches academic discussions by offering insights for policymakers and by improving industry practices.

Regional Government Obligations in Fulfilling the Right to Clean Water

This study examines the regional government’s obligations in fulfilling the right to clean water to achieve public utility benefits, focusing on the Regional Water Utility Company (PDAM) in Bone Regency. The research adopts an empirical juridical method, combining field studies on the implementation of existing laws with data gathered through observation, interviews, and documentation. The results indicate that the fulfillment of the right to clean water by PDAM Bone Regency is not optimal. Challenges persist in three key aspects: quality, quantity, and continuity of water supply. The water quality often fails to meet standards, with issues such as turbidity reported by consumers. The quantity of water distributed remains insufficient to meet the needs of all citizens, particularly during extended dry seasons, and the continuity of water flow is inconsistent, disrupting daily activities. These issues hinder the realization of public welfare and equitable access to clean water, as mandated by Indonesia’s legal framework and human rights principles. This study highlights the need for improved management, infrastructure upgrades, and policy interventions to ensure the right to clean water is upheld for all citizens of Bone Regency.

Commodifying Public Utilities: EU's New Governance Prescriptions for Rail and Water

ABSTRACTIn the mid‐2000s, the Single Market Program and European Monetary Union lost momentum, as public services advocates increasingly succeeded in tempering attempts to liberalize public utilities through legislative amendments and Court of Justice rulings. After the 2008 crisis, however, the EU's shift to a new economic governance (NEG) regime provided EU executives with a new tool to advance their objectives. Unlike EU directives, country‐specific NEG prescriptions require neither the approval of the European Parliament nor their transposition into law, making it more difficult for social forces to contest them. Our analysis of NEG prescriptions for public utilities in two sectors (rail and water) and four countries (Germany, Ireland, Italy, Romania) across 10 years (2009–2019) shows that the shift to NEG provided EU executives with new extra‐parliamentarian and extra‐juridical tools that allowed them to revive their stalled commodification agenda; at the price of accentuating the EU's democratic and justice deficits.

Hybrid Numerical Weather Prediction: Downscaling GraphCast AI Forecasts for Downslope Windstorms

Abstract Preemptively managing electrical circuits during periods of elevated wildfire risk, such as downslope windstorms in complex terrain, necessitates accurate, high-resolution forecasts days in advance. Currently available high-resolution operational guidance is limited with respect to the forecasting period and/or spatial detail it can provide. As a consequence, many public utilities support their own NWP systems, primarily WRF-based, with initial conditions and boundary forcings supplied by operational global models such as the GFS. This study demonstrates pairing Google’s artificial intelligence (AI)-based GraphCast (GC) model, which operates on a 0.25° grid and produces global forecasts every 6 h, with a “last mile” WRF (WRF-LM) downscaling framework to refine GC’s spatial and temporal resolution for utility forecasting needs. We illustrate the potential of this system through a case study involving the December 2021 Marshall Fire windstorm in the Boulder, Colorado, area. Our results suggest that GC-initialized WRF forecasts are competitive with those guided by NCEP and ECMWF operational products, offering a promising hybrid approach for utility weather forecasting. Significance Statement Downslope windstorms are difficult to forecast with small errors potentially affecting the timing, magnitude, and location of concerning winds. Due to the elevated wildfire danger caused by these windstorms, accurate forecasts with lead times greater than 48 h are often needed to allow utilities time to prepare for the de-energization of transmission lines to reduce ignition risk. This paper examines methods of downscaling coarse synoptic-scale forecasts using the downslope windstorm associated with the 2021 Marshall Fire as our case study. A novel aspect of this work is the incorporation of machine learning weather prediction models and downscaling their forecasts using a high-resolution numerical model.

연구시설 공동활용 서비스가 이용만족과 지속사용의도에 미치는 영향

This study aims to investigate user satisfaction and intention for continuous use from the perspective of users who share research facilities and equipment, focusing on users of the ZEUS (Research Equipment Utilization Service) portal. The research examines national policies on shared research facilities and equipment, and applies the Information Systems Success Model to assess system quality, service quality, and social benefit quality of ZEUS. It also explores user satisfaction based on the service product quality and service environment quality after reserving and using shared equipment. The results indicate that both service quality and social benefit quality significantly affect perceived usefulness and ease of use, while system quality only influences ease of use. Ease of use positively impacts perceived usefulness, which in turn positively affects user satisfaction, but ease of use does not directly influence satisfaction. Both service product quality and service environment quality significantly affect satisfaction, and satisfaction influences the intention for continuous use. The study's limitations include the inability to analyze service quality in greater detail due to regulated procedures for equipment registration. Future research should use expanded models like the Technology Acceptance Model (TAM) or E-SERVQUAL, and consider regional distribution in sample selection for broader analysis.

Assessing Public Awareness and Practices in Medicine Disposal: A Cross- Sectional Study on the Utilisation of the 'Return Your Medicines' Program in Terengganu, Malaysia

Improper disposal of unused and expired medicines poses a significant risk to public health and the environment. While medication return programs have been established in various countries to mitigate this issue, data on their utilisation remain limited. The study aims to identify the disposal practices of unused and expired medicines; evaluate the public's awareness and utilisation of the "Return Your Medicines" (RYM) program; and investigate factors related to disposal practices, awareness, and RYM usage. A quantitative, cross-sectional survey was conducted in Terengganu, Malaysia, involving 290 adults recruited through convenience sampling. Data were analysed using SPSS, employing both descriptive and inferential analyses, including the chi-square test. The findings show that nearly 90% of participants improperly dispose of unused and expired medicines by discarding them in household trash and giving them to friends and relatives. Out of 290 participants, only 33.4% were aware of the RYM program, and only 23.7% had used it. There is a notable prevalence of improper medicine disposal practices, as well as a limited level of public awareness about the RYM program. These findings highlight the crucial role of healthcare practitioners, especially pharmacists, in continuously educating the public on safe disposal practices. Furthermore, the development and implementation of innovative strategies are imperative to increase public engagement with the RYM program and promote safer disposal methods.

Hybrid Communication Architecture Based on Hierarchical Computing for Low Voltage Power Network Automation in Developing Countries

Utility companies in developing countries, such as Tanzania, have made significant advancements in automating the generation, transmission, and primary distribution segments of their electrical grids. However, automation in the Low Voltage Power Network (LVPN) remains minimal and largely unmonitored, leading to manual fault management that results in losses and inconveniences for both utilities and customers. Effective Smart Grid (SG) infrastructure relies on seamless communication between end-devices and controlling systems to ensure timely execution of critical applications. Key SG applications for LVPN automation include Advanced Metering Infrastructure (AMI), Distributed Energy Resource (DER) coordination, and Distribution Automation (DA), each with specific latency requirements that must be met. Current architectures outlined in the literature present challenges for utility companies attempting to implement these applications while satisfying latency criteria for automation. This paper introduces a hybrid communication architecture based on a three-level hierarchical computing model specifically designed for LVPN automation. Laboratory results indicate that this architecture achieves an average delay of 7.059ms, significantly below the maximum allowable latency of 20ms for AMI, DER, and DA which demonstrates the architecture's capability for effective LVPN automation.

Management of the Service Improvement System in Public Utilities in Bosnia and Herzegovina

The business of public utilities in the present has become unimaginable without the represented aspect of relations with the public. The main goal of this paper is to show how successful public relations contribute to better management of the service improvement system in public utility companies in Bosnia and Herzegovina. In addition, the aim is to analyze the importance of managing the policy of improving the efficiency of water supply, and wastewater treatment and the importance of communication strategy. The paper investigates the mechanisms that influence the communication strategy on determining the communication goals that public companies in Bosnia and Herzegovina have to achieve to communicate with the public. The work explores key communication messages, target groups, and communication channels. The paper indicated that the key skills and strategies for improving communication, building strong public relations and effective advocacy in a public water and utility company is knowing the psychographic and behavioral characteristics of the target group to adapt messages. Also, it was shown that strategic communication in the field of water supply and wastewater treatment greatly helps in understanding the broader picture of the performance of public water and utility companies. It was emphasized how important it is to create a communication strategy and action plans, especially when it comes to key points, goals, messages, and roles in the company. Also, it was pointed out that it is very important to understand the concepts, tools, techniques, and materials for public relations (statements, press releases, invitations, media briefs, interviews) as well as the basic requirements for a successful appearance in public.

Revisiting the Role of Renewable Energy, Government Spending, Exports, and Imports, in Economic Growth: A Panel Data Analysis of Selected Asian Countries

Investing in renewable energy sources reduces a country’s reliance on fossil fuel imports, enhancing energy security. By diversifying the energy mix, nations can mitigate the risks associated with price volatility and geopolitical tensions related to fossil fuel dependency. This stability in the energy supply promotes economic growth by ensuring a steady and affordable source of power for industries and businesses. Therefore, the present study examines the impact of renewable energy, government spending, exports, and imports on economic growth in selected Asian countries (namely, Bangladesh, Bhutan, India, Nepal, Pakistan, and Sri Lanka) from 2000 to 2021. This study uses the Fixed Effects method of estimation based on the Hausman specification test. The findings reveal that renewable energy consumption, government spending, exports, and import have a positive effect on economic growth. Moreover, it is found that among these variables, renewable energy consumption and exports have maximum impact on economic growth in selected countries. Governments can allocate funds for the development, renewable energy project, and maintenance of infrastructure, such as transportation networks, roads, bridges, ports, and public utilities. It not only creates immediate job opportunities but also enhances productivity and growth.

The Family Doctor in the "COVID-19 Era".

The SARS-CoV-2 virus infection, the most severe pandemic in recent human history, found healthcare systems around the world more or less unprepared. Adjusting to this challenge involved changes in the daily routines of healthcare systems, as well as the patients, once again highlighting the importance of primary care (family physician or general practitioner). In the context of the COVID-19 pandemic, the family doctor in Romania played a crucial role in patient management, rapidly adapting to the changes and challenges imposed by the state of emergency. Their involvement quickly evolved from in-person consultations to online assessments, as they took on responsibilities such as monitoring patients in isolation or quarantine and issuing necessary medical leaves. Moreover, family doctors were directly involved in the COVID-19 vaccination process, facing challenges related to access to scheduling platforms and limited resources of protective equipment. Although they were on the front line of the healthcare response, recognition through incentives or compensations came late and incompletely, and their efforts in combating the pandemic were often overlooked. Designating family doctors' offices as public utility medical units (regardless of their organisational form) and supporting their activities through increased equipment and medical devices provided by local or central authorities are the keys to fighting for human lives in critical situations. Implementing clear and universal rules regarding the competencies (skills) and duties of family doctors, both in normal life situations and in exceptional circumstances, is of utmost importance. Little is known about the dedicated work and dedication of family physicians to their patients. Few studies have been carried out on the activity of the family doctor and their professional difficulties during the pandemic period. Some studies, on a small number of subjects, tried to evaluate the psychological adaptation of the family doctor to the new epidemiological situation. The aim of this narrative review is to highlight the difficulties to which family doctors had to adapt, comparing the data from the Romanian medical system with those discovered in the medical literature regarding family doctors from all over the world.

IISE PG&E Energy Analytics Challenge 2024: Forecasting Day-Ahead Electricity Prices

Electricity price forecasting is one of the cornerstones of modern-day power system operation. Over the last two decades, the field has seen many methodological advancements. On one end, traditional statistical methods remain widely prevalent in today’s energy industry, as they have proven consistently to “stand the test of time.” On the other end, emerging predictive techniques (e.g., machine and deep learning) have demonstrated immense potential. Yet, due to limited benchmarking studies, the magnitude of improvement realized by such emerging methods relative to their statistical counterparts is not entirely clear. In response, two technical divisions of the Institute of Industrial & Systems Engineers (IISE) partnered with the Pacific Gas and Electric Company (PG&E)—one of the largest utility companies in the United States—in order to organize an electricity price forecasting challenge in 2024. Using three years of pricing signals and exogenous information from California’s electricity market, the competition challenged teams of researchers and practitioners to design their own models and submit forecasts for day-ahead electricity prices, which were independently evaluated against a test set that has been reserved from all teams. This paper introduces the challenge, as well as an overview of the methods used by the top-performing contestants. A distilled summary of the key insights and lessons learned by the challenge organizers is then presented, together with their relevance to the topic of electricity price forecasting. This is then followed by recommendations for future similarly focused competitions. To accelerate the research and development on this important topic, all data used in the challenge have been made publicly available by the challenge organizers.

Revenue loss reduction in the electrical distribution networks using distributed generators: A case of Tanzania electrical distribution network

Most power losses in power systems occur within distribution networks, resulting in poor service quality, higher electricity costs for consumers, and revenue loss for utility companies. This study suggests strategies for minimizing these revenue losses by integrating distributed generators (DGs) into the distribution networks. The process involves identifying optimal locations and determining the best power output for each DG based on fluctuating power system variables, making it a complex NP-hard optimization problem. Therefore, this study proposes the use of metaheuristic algorithms to solve the DG power dispatch problem and reduce revenue losses in the electrical distribution networks. The proposed technique has been tested in the Tanzanian electrical distribution network using an hourly load profile and tariff D1, T1 and T2 users. Four metaheuristic algorithms were used, namely Golden jackal optimization (GJO), Grey wolf optimizer (GWO), Walrus optimizer (WO) and Marine Predators Algorithm (MPA). The algorithms were evaluated based on convergence profiles and computational times, with GWO performing the best. The study analyzed the impact of the number of DGs on revenue loss reduction, finding that the revenue losses decrease with the increase in the number of DGs. The analysis of the impact of the tariffs category on revenue loss reduction shows that integrating DGs reduced revenue loss by over 56% in all cases. These results demonstrate that DG integration can effectively decrease revenue losses in distribution networks.

Enhancing line loadability in urban rail systems: evaluating the impact of distributed generation on voltage stability, power losses and generation costs

Alternative source of electrical energy for urban railway electrification system is Direct Current (DC). Traction Power Substations (TPS) were essentially connected to the electrical grid network managed by the electrical utility company for operating and powering purposes. Power unbalance frequently occurs in the high voltage railway network due to the load of the traction system. The aim of this project is to find the impact of distribution generation (DG) for line loadability in urban rail systems. The output that needs to be considered are the voltage profile, power losses and generation cost. The simulation was considered to prove the positive impact of distributed generation for line loadability in urban rail system. Electrical energy was crucial for Direct Current (DC) railway electrification systems, as it provided the traction power necessary for train operations via Traction Power Substations (TPS) that connected to the electrical grid network. However, power imbalances frequently arose due to the varying loads imposed by traction systems, resulting in inefficiencies, suboptimal voltage profiles, increased power losses and higher operational costs. With the expansion of urban rail networks and the growing need for efficient power management, it became vital to explore solutions that could enhance loadability and system performance. This project examined the impact of integrating Distributed Generation (DG) on the line loadability of urban rail systems, concentrating on improvements in voltage profiles, reductions in power losses and the evaluation of generation costs. The methodology involved developing a detailed simulation model of the urban rail system, incorporating DG scenarios, analyzing their effects on voltage stability, power losses and costs. The simulation results were anticipated to demonstrate that DG could improve voltage stability, reduce power losses, lower generation costs and increase line loadability. The implications of these findings encompassed enhanced operational efficiency, potential economic benefits despite high initial investments, increased sustainability through renewable energy and valuable guidance for future infrastructure development and investment decisions.

Residential Load Forecasting Based on Long Short-Term Memory, Considering Temporal Local Attention

Accurate residential load forecasting is crucial for the stable operation of the energy internet, which plays a significant role in advancing sustainable development. As the construction of the energy internet progresses, the proportion of residential electricity consumption in end-use energy consumption is increasing, the peak load on the grid is growing year on year, and seasonal and regional peak power supply tensions, mainly for household electricity consumption, grow into common problems across countries. Residential load forecasting can assist utility companies in determining effective electricity pricing structures and demand response operations, thereby improving renewable energy utilization efficiency and reducing the share of thermal power generation. However, due to the randomness and uncertainty of user load data, forecasting residential load remains challenging. According to prior research, the accuracy of residential load forecasting using machine learning and deep learning methods still has room for improvement. This paper proposes an improved load-forecasting model based on a time-localized attention (TLA) mechanism integrated with LSTM, named TLA-LSTM. The model is composed of a full-text regression network, a date-attention network, and a time-point attention network. The full-text regression network consists of a traditional LSTM, while the date-attention and time-point attention networks are based on a local attention model constructed with CNN and LSTM. Experimental results on real-world datasets show that compared to standard LSTM models, the proposed method improves R2 by 14.2%, reduces MSE by 15.2%, and decreases RMSE by 8.5%. These enhancements demonstrate the robustness and efficiency of the TLA-LSTM model in load forecasting tasks, effectively addressing the limitations of traditional LSTM models in focusing on specific dates and time-points in user load data.

Art in public utility buildings – an example of a collection in an international juridical institution

The article tries to highlight the phenomenon of integrating art collections into public buildings, focusing on the example of an international juridical institution exhibiting art from different countries. The motivation for collecting art in such spaces is often to improve the aesthetics of the building, to promote diverse perspectives and reflections through art. The creation of this unique collection in the late 1960s was a pioneering initiative undertaken 50 years ago by the European Court of Justice based in Luxembourg and has since been adopted by other international European institutions. The exhibition of art in public buildings can be considered from the perspective of social capital or the dimension of the sociology of art. The motives are not always obvious and the social influences remain unspecified, there is also an aspect of the historical context of the selection of artists and their works and diplomacy through art.