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Journal articles on the topic 'Power Outage'

Author: Grafiati

Published: 4 June 2021

Last updated: 25 July 2025

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1

Ohiri Paschal Chinedu, Mfonobong Eleazar Benson, Ogomaka Chrysogonus Chukwumere, Anyalewechi Chika Juliana, and Oleka Chidubem Messhack. "Analysis of power outages and their economic impact: A comparative study of Nigerian distribution companies." World Journal of Advanced Engineering Technology and Sciences 15, no. 3 (2025): 759–65. https://doi.org/10.30574/wjaets.2025.15.3.0900.

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Reliable electricity supply is crucial for economic development, yet Nigeria continues to grapple with frequent power outages. This study analyzes power outage data from Nigerian electricity distribution companies (DisCos) to quantify the frequency, duration, and economic impact of outages across different regions. Utilizing outage records and customer complaint data from six DisCos over a 36-month period (2020-2022), we employ statistical analysis and economic modeling to assess the relationship between outage patterns and economic indicators. Results reveal significant disparities in outage

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Mgaya, Stephan, and Hellen Maziku. "Machine Learning Approach for Classifying Power Outage in Secondary Electric Distribution Network." Tanzania Journal of Engineering and Technology 41, no. 1 (2022): 1–9. http://dx.doi.org/10.52339/tjet.vi.767.

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Power outage is the problem that hinders social and economic development especially for developing countries like Tanzania. Frequent power outages damage electric equipment, and negatively affect the industrial production process. Power outages cannot be completely eradicated due to uncontrolled cause like natural calamities but technical challenges can be managed and hence reducing power outages. The existing manual methods used to locate power outage like customer calls is inefficient and time consuming. On the other hand, modern method like the Advanced Metering Infrastructure (AMI) still f

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Alpay, Berk A., David Wanik, Peter Watson, Diego Cerrai, Guannan Liang, and Emmanouil Anagnostou. "Dynamic Modeling of Power Outages Caused by Thunderstorms." Forecasting 2, no. 2 (2020): 151–62. http://dx.doi.org/10.3390/forecast2020008.

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Thunderstorms are complex weather phenomena that cause substantial power outages in a short period. This makes thunderstorm outage prediction challenging using eventwise outage prediction models (OPMs), which summarize the storm dynamics over the entire course of the storm into a limited number of parameters. We developed a new, temporally sensitive outage prediction framework designed for models to learn the hourly dynamics of thunderstorm-caused outages directly from weather forecasts. Validation of several models built on this hour-by-hour prediction framework and comparison with a baseline

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McBrien, Heather, Daniel Mork, Marianthi-Anna Kioumourtzoglou, and Joan A. Casey. "Assessing bias in measuring power outage exposure with simulations." Environmental Epidemiology 9, no. 4 (2025): e403. https://doi.org/10.1097/ee9.0000000000000403.

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Background: New national power outage exposure data have become available since 2020, which can support epidemiologic studies of power outage and health outcomes, but exposure assessment challenges remain. Two sources of bias could affect results: available datasets are missing large percentages of observations, and the health-relevant duration of power outages remains unknown. Here, we aimed to determine if existing datasets can produce usable effect estimates in epidemiologic studies despite missing data, and quantify bias introduced by incorrect assumptions about the health-relevant duratio

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Arora, Prateek, and Luis Ceferino. "Probabilistic and machine learning methods for uncertainty quantification in power outage prediction due to extreme events." Natural Hazards and Earth System Sciences 23, no. 5 (2023): 1665–83. http://dx.doi.org/10.5194/nhess-23-1665-2023.

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Abstract. Strong hurricane winds damage power grids and cause cascading power failures. Statistical and machine learning models have been proposed to predict the extent of power disruptions due to hurricanes. Existing outage models use inputs including power system information, environmental parameters, and demographic parameters. This paper reviews the existing power outage models, highlighting their strengths and limitations. Existing models were developed and validated with data from a few utility companies and regions, limiting the extent of their applicability across geographies and hurri

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Gedel, Ibrahim A., and Wahab A. Iddrisu. "Modeling the Causes of Power-Related Network Outages Using Discrete-Time Markov Chains." Wireless Communications and Mobile Computing 2023 (December 20, 2023): 1–11. http://dx.doi.org/10.1155/2023/8717626.

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In this paper, we model the causes of power-related network outages in Ghana using discrete-time Markov chains. We used data consisting of 2,756 small-scale carrier telecommunications outages occurring in Ghana, with accompanying root causes over a period of 5 years and 8 months, from August 2015 to April 2021. The results indicate that the majority (n = 1,404) of the network outages were caused by the generators while the least number (18) of outages were caused by a communication equipment. However, longer network outages were caused by fuel issues with an average outage time of 1,027.82 min

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Moridi, Saeed Shahi, Seyed Hamed Moosavirad, Mitra Mirhosseini, Hossein Nikpour, and Armin Mokhtari. "Prioritizing power outages causes in different scenarios of the global business network matrix." Decision Making: Applications in Management and Engineering 6, no. 1 (2023): 321–40. http://dx.doi.org/10.31181/dmame0301072022m.

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Power outage is one of the significant problems for electricity distribution companies. Power outages cause customer dissatisfaction and reduce distribution companies' profits and revenues. Therefore, the electricity distribution companies are trying to moderate the leading causes of the outage. However, the dynamics of environmental conditions create uncertainties that require prioritizing the solutions of outages causes in different situations. Therefore, this study presents a scenario-based approach to prioritize power outage causes. Four case studies have been conducted in four cities of K

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Richards, Claire A., Solmaz Amiri, Von P. Walden, Julie Postma, Mohammad Heidari Kapourchali, and Alain F. Zuur. "Association of social vulnerability factors with power outage burden in Washington state: 2018–2021." PLOS ONE 19, no. 9 (2024): e0307742. http://dx.doi.org/10.1371/journal.pone.0307742.

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Major power outages have risen over the last two decades, largely due to more extreme weather conditions. However, there is a lack of knowledge on the distribution of power outages and its relationship to social vulnerability and co-occurring hazards. We examined the associations between localized outages and social vulnerability factors (demographic characteristics), controlling for environmental factors (weather), in Washington State between 2018–2021. We additionally analyzed the validity of PowerOutage.us data compared to federal datasets. The population included 27 counties served by 14 e

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9

Fan, Fulai, Xuesong Tang, Jianming Wang, et al. "Comprehensive assessment and early warning of the risk of repeated power outages in distribution networks based on multi-source information fusion." Journal of Physics: Conference Series 2087, no. 1 (2021): 012087. http://dx.doi.org/10.1088/1742-6596/2087/1/012087.

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Abstract In order to reduce the occurrence of power outages with repeated occurrences in the distribution network, this paper first defines the quantitative index of the concept of repeated occurrences. The FP-Growth data mining algorithm based on the optimal frequent itemset is proposed to obtain the correlation between the power outage factors. Combined with the fuzzy analytic hierarchy process, the main reasons for repeated power outages are obtained. The analytic hierarchy process combining subjective and objective weights is used to comprehensively evaluate the risk of repeated power outa

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Godwin, PhD, Sandria L., Richard J. Coppings, PhD, Katherine M. Kosa, MS, Sheryl C. Cates, BS, and Leslie Speller-Henderson, MS. "Keeping food safe during an extended power outage: A consumer’s perspective." Journal of Emergency Management 8, no. 6 (2010): 44. http://dx.doi.org/10.5055/jem.2010.0038.

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Most Americans live at risk of experiencing a natural disaster. Such disasters are often accompanied by power outages, sometimes for extended periods. Six formal focus groups were conducted, two in North Carolina and four in Tennessee, to assess consumers’ food safety knowledge and practices during extended power outages. Forty-seven adults of various ethnicities, ages, and genders participated in the focus groups held in libraries, extension offices, or other community centers. Participants’ knowledge of safety precautions that should be taken during and after a power outage and the actions t

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Jimoh, Boyi, Juliet N. Adegboye, and Babatunde A. Adegboye. "Analysis of the Effect of Environmental Factors on Outage Rates of Overhead Distribution Feeders: A Case Study of Zaria Distribution Network." Advanced Materials Research 824 (September 2013): 120–28. http://dx.doi.org/10.4028/www.scientific.net/amr.824.120.

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The paper is aimed at analysing the environmental factors on the outage rates of the overhead distribution feeders. This was facilitated using daily outage data on the six 33kV feeders of the Zaria distribution system collected from the Zaria Transmission substation of the Power Holding Company of Nigeria (PHCN) for twelve months. Outage models were developed from where power losses due to the feeder outages were obtained. Frequent and delayed forced outages occur during the rainy season, the peak being in August and during harmattan, especially in October. There were relatively high outage ra

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Yan, Weikang, Bing He, and Tianxiang Xie. "Study on High-precision Grid Outage Region Based on Distribution Network Topology Analysis." Journal of Physics: Conference Series 2215, no. 1 (2022): 012007. http://dx.doi.org/10.1088/1742-6596/2215/1/012007.

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Abstract Based on the recursion method and the Java language, this paper develops a program for analyzing the distribution network topology diagram and explores various scenarios of power outages. The power line topology analysis can pinpoint the power outage range, providing a solid foundation for power outage information release and distribution network reliability calculation.

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Hussein Farh, Hassan M., Abdullrahman A. Al-Shamma’a, Affaq Qamar, Fahman Saeed, and Abdullah M. Al-Shaalan. "Optimal Sizing and Placement of Distributed Generation under N-1 Contingency Using Hybrid Crow Search–Particle Swarm Algorithm." Sustainability 16, no. 6 (2024): 2380. http://dx.doi.org/10.3390/su16062380.

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Line outage contingencies in power distribution systems pose critical challenges, leading to disruptions, reduced reliability, and potential cascading failures. These problems include increased vulnerability, limited resilience, and the need for efficient mitigation strategies to enhance the overall system reliability and quality. This study aims to investigate, analyze, and evaluate the renewable distributed generator (RDG) allocation and sizing under N-1 line outage conditions in terms of the reliability and quality for the IEEE 30-bus benchmark power system as a case study. Under all possib

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Aljurbua, Rafaa, Jumanah Alshehri, Shelly Gupta, Abdulrahman Alharbi, and Zoran Obradovic. "Leveraging multi-modal data for early prediction of severity in forced transmission outages with hierarchical spatiotemporal multiplex networks." PLOS One 20, no. 6 (2025): e0326752. https://doi.org/10.1371/journal.pone.0326752.

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Extended power transmission outages caused by weather events can significantly impact the economy, infrastructure, and residents’ quality of life in affected regions. One of the challenges is providing early, accurate warnings for these disruptions. To address this challenge, we introduce HMN-RTS, a hierarchical multiplex network designed to predict the duration of a forced transmission outage by leveraging a multi-modal approach. We investigate outage duration prediction over two years at the county level, focusing on the states of the Pacific Northwest region, including Idaho, California, Mo

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Sultan, Vivian, and Brian Hilton. "A Spatial Analytics Framework to Investigate Electric Power-Failure Events and Their Causes." ISPRS International Journal of Geo-Information 9, no. 1 (2020): 54. http://dx.doi.org/10.3390/ijgi9010054.

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The U.S. electric-power infrastructure urgently needs renovation. Recent major power outages in California, New York, Texas, and Florida have highlighted U.S. electric-power unreliability. The media have discussed the U.S. aging power infrastructure and the Public Utilities Commission has demanded a comprehensive review of the causes of recent power outages. This paper explores geographic information systems (GIS) and a spatially enhanced predictive power-outage model to address: How may spatial analytics enhance our understanding of power outages? To answer this research question, we develope

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Zhang, Zhihao, Yulin Qian, Diandian Zhou, and Kexin Zhang. "Approach for Provincial distribution automation system in Outage analysis." Journal of Physics: Conference Series 2108, no. 1 (2021): 012019. http://dx.doi.org/10.1088/1742-6596/2108/1/012019.

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Abstract People’s lives are becoming more and more inseparable from electricity, and the requirements for the quality of power supply are getting higher and higher. Because of most of the faults in the power system originate from the distribution network, the need to standardize the management of power outages and improve the efficiency of research and judgment has become more and more significant. However, in China, the differences in the development of automation construction in various places and the outage information of different departments require that power outage business applications

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Owolabi, Olukunle O., and Deborah A. Sunter. "Bayesian Optimization and Hierarchical Forecasting of Non-Weather-Related Electric Power Outages." Energies 15, no. 6 (2022): 1958. http://dx.doi.org/10.3390/en15061958.

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Power outage prediction is important for planning electric power system response, restoration, and maintenance efforts. It is important for utility managers to understand the impact of outages on the local distribution infrastructure in order to develop appropriate maintenance and resilience measures. Power outage prediction models in literature are often limited in scope, typically tailored to model extreme weather related outage events. While these models are sufficient in predicting widespread outages from adverse weather events, they may fail to capture more frequent, non-weather related o

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Rizvi, Mohammed. "Leveraging Deep Learning Algorithms for Predicting Power Outages and Detecting Faults: A Review." Advances in Research 24, no. 5 (2023): 80–88. http://dx.doi.org/10.9734/air/2023/v24i5961.

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Power outage prediction and fault detection play crucial roles in ensuring the reliability and stability of electrical power systems. Traditional methods for predicting power outages and detecting faults rely on rule-based approaches and statistical analysis, which often fall short of accurately capturing the complex patterns and dynamics of power systems. Deep learning algorithms, with their ability to learn automatically representations from large amounts of data, have emerged as promising solutions for addressing these challenges. In this literature review, we present an overview of deep le

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Das, Sanjoy, Padmavathy Kankanala, and Anil Pahwa. "Outage Estimation in Electric Power Distribution Systems Using a Neural Network Ensemble." Energies 14, no. 16 (2021): 4797. http://dx.doi.org/10.3390/en14164797.

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Outages in an overhead power distribution system are caused by multiple environmental factors, such as weather, trees, and animal activity. Since they form a major portion of the outages, the ability to accurately estimate these outages is a significant step towards enhancing the reliability of power distribution systems. Earlier research with statistical models, neural networks, and committee machines to estimate weather-related and animal-related outages has reported some success. In this paper, a deep neural network ensemble model for outage estimation is proposed. The entire input space is

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Thiel, Diane. "Power Outage." Hudson Review 56, no. 2 (2003): 299. http://dx.doi.org/10.2307/3853241.

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Jolley, Rachael. "Power outage." Index on Censorship 44, no. 1 (2015): 3–5. http://dx.doi.org/10.1177/0306422015572973.

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Boggess, Ace. "Power Outage." Appalachian Heritage 44, no. 1 (2016): 112. http://dx.doi.org/10.1353/aph.2016.0020.

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Zhang, Wangjian, Scott C. Sheridan, Guthrie S. Birkhead, et al. "Power Outage." Chest 158, no. 6 (2020): 2346–57. http://dx.doi.org/10.1016/j.chest.2020.05.555.

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Fan, Xiao Long, and Jin Quan Zhao. "Fast Algorithms of Line Outage Distribution Factors with Cascading Failures." Advanced Materials Research 1070-1072 (December 2014): 843–48. http://dx.doi.org/10.4028/www.scientific.net/amr.1070-1072.843.

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The prominent role of cascading outages in recent blackouts has created a need in security applications for evaluating line outage distribution factors (LODFs) under the multiple-line outages. Two fast algorithms of LODFs with multiple-line outages are proposed in this paper. In the first method, the double-line outage LODFs are expressed in terms of single-line outage LODFs, and it can be extended to N-k (k≥2) contingencies without any complex matrix operation through the recursive theory. In the second method, a computationally efficient expression of LODFs based on power transfer distributi

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Wanik, D. W., E. N. Anagnostou, M. Astitha, et al. "A Case Study on Power Outage Impacts from Future Hurricane Sandy Scenarios." Journal of Applied Meteorology and Climatology 57, no. 1 (2018): 51–79. http://dx.doi.org/10.1175/jamc-d-16-0408.1.

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AbstractHurricane Sandy (2012, referred to as Current Sandy) was among the most devastating storms to impact Connecticut’s overhead electric distribution network, resulting in over 15 000 outage locations that affected more than 500 000 customers. In this paper, the severity of tree-caused outages in Connecticut is estimated under future-climate Hurricane Sandy simulations, each exhibiting strengthened winds and heavier rain accumulation over the study area from large-scale thermodynamic changes in the atmosphere and track changes in the year ~2100 (referred to as Future Sandy). Three machine-

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Koroglu, Mustafa, Bridget R. Irwin, and Karen A. Grépin. "Effect of power outages on the use of maternal health services: evidence from Maharashtra, India." BMJ Global Health 4, no. 3 (2019): e001372. http://dx.doi.org/10.1136/bmjgh-2018-001372.

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IntroductionElectricity outages are common in low/middle-income countries and have been shown to adversely affect the operation of health facilities; however, little is known about the effect of outages on the utilisation of health services.MethodsUsing data from the 2015–2016 India Demographic Health Survey, combined with information on electricity outages as reported by the state electricity provider, we explore the associations between outage duration and frequency and delivery in an institution, skilled birth attendance, and caesarean section delivery in Maharashtra State, India. We employ

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Islam, Kazi Sifatul, Samiul Hasan, Tamal Chowdhury, Hemal Chowdhury, and Sadiq M. Sait. "Outage Survivability Investigation of a PV/Battery/CHP System in a Hospital Building in Texas." Sustainability 14, no. 22 (2022): 14965. http://dx.doi.org/10.3390/su142214965.

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Climate change and the associated global warming raise the possibility of weather-related natural disasters. Power outages due to natural catastrophes cause substantial financial loss. Moreover, an uninterrupted power supply is essential in disaster-prone areas to continue rescue and other humanitarian activities. Therefore, energy systems must be resilient to withstand power outages due to natural events. Resilience and enhancement techniques, and schemes of integrated electricity and microgrids’ heat demand during power outages, were mainly overlooked in the earlier analysis. Therefore, this

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Papic, Milorad, Svetlana Ekisheva, and Eduardo Cotilla-Sanchez. "A Risk-Based Approach to Assess the Operational Resilience of Transmission Grids." Applied Sciences 10, no. 14 (2020): 4761. http://dx.doi.org/10.3390/app10144761.

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Modern risk analysis studies of the power system increasingly rely on big datasets, either synthesized, simulated, or real utility data. Particularly in the transmission system, outage events have a strong influence on the reliability, resilience, and security of the overall energy delivery infrastructure. In this paper we analyze historical outage data for transmission system components and discuss the implications of nearby overlapping outages with respect to resilience of the power system. We carry out a risk-based assessment using North American Electric Reliability Corporation (NERC) Tran

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Vasudha, D., Dr N. C. Kotaiah, and Dr K. Radha Rani. "Development of Static Model for a Current Based UPFC." International Journal of Electrical and Electronics Research 11, no. 4 (2023): 1183–87. http://dx.doi.org/10.37391/ijeer-110440.

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The power system loads are dispersed across the network and generators are concentrated in a few key locations. In between generation and loads, there exist transmission systems. FACTS devices have applications to regulate voltage magnitude and angle, and impedance of the system. In FACTS devices, UPFC is one of its kind. Generally, line outages are occurred due to the faults on the transmission lines. One of the sensitive measures to understand the line outages is Line Outage Distribution Factor (LODF). In this paper, a suitable location is identified for UPFC to place where the line outage d

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Ghasemkhani, Bita, Recep Alp Kut, Reyat Yilmaz, et al. "Machine Learning Model Development to Predict Power Outage Duration (POD): A Case Study for Electric Utilities." Sensors 24, no. 13 (2024): 4313. http://dx.doi.org/10.3390/s24134313.

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In the face of increasing climate variability and the complexities of modern power grids, managing power outages in electric utilities has emerged as a critical challenge. This paper introduces a novel predictive model employing machine learning algorithms, including decision tree (DT), random forest (RF), k-nearest neighbors (KNN), and extreme gradient boosting (XGBoost). Leveraging historical sensors-based and non-sensors-based outage data from a Turkish electric utility company, the model demonstrates adaptability to diverse grid structures, considers meteorological and non-meteorological o

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He, Jindong, Shanshan Lei, and Lijin Wu. "Multi-source data fusion for power outage warning based on transformer model." Journal of Physics: Conference Series 2816, no. 1 (2024): 012030. http://dx.doi.org/10.1088/1742-6596/2816/1/012030.

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Abstract In this study, we propose a method that uses the Transformer model to enhance power outage alerts by integrating data from multiple sources. By integrating data from various sources, including operational data from the local distribution network and meteorological data, we have constructed a comprehensive multi-source data framework for power outage warnings. The Transformer model, known for its ability to capture complex dependencies and patterns, has been employed to extract features and make accurate predictions. Results on actual power system data have shown that our approach sign

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Rice, Julian R., Karthik Balaguru, Andrea Staid, Wenwei Xu, and David Judi. "Projected increases in tropical cyclone-induced U.S. electric power outage risk." Environmental Research Letters 20, no. 3 (2025): 034030. https://doi.org/10.1088/1748-9326/adad85.

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Abstract While power outages caused by tropical cyclones (TCs) already pose a great threat to coastal communities, how—and why—these risks will change in a warming climate is poorly understood. To address this need, we develop a robust machine learning model to capture TC-induced power outage risk. When applied to 900 000 synthetic TCs downscaled from simulated historical and future climate conditions under a strong warming scenario, we find outage risk in the United States and Puerto Rico is expected to increase broadly by the end of the century, with some states seeing increases of 60% and h

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Abhay, Nath Dubey, Deepika Chauhan Dr., and Asif Iqbal Md. "A Case Study on Blackout." International Journal of Trend in Scientific Research and Development 2, no. 3 (2018): 1390–95. https://doi.org/10.31142/ijtsrd11287.

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Indian grid system is a synchronized system and presently operating as National Grid. India has five provincial grids altogether as per geological region which covers the distinct states electrical power framework to be specific these are Northern Grid, Eastern Grid, Western Grid, Southern Grid and North Eastern Grid. Southern Grid isnt synchronized with whatever is left of the areas and consequently keeps running on a marginally different frequency and associated with Western Grid and Eastern Grid through HVDC links. A power outage is the total or partial loss of energy to a territory and is

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Anaman, Dinah Koranteng, and Bawuah Bernard. "Power Outages in Ghana: Did They Have an Effect on the Financial Performance of Listed Firms?" International Journal of Management Excellence 10, no. 3 (2018): 1434–39. http://dx.doi.org/10.17722/ijme.v10i3.982.

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The paper seeks to find out whether the recent power outages in Ghana had a negative effect on listed firms.. Out of 35 listed firms in Ghana, 25 were purposively chosen as the sample size for the study. The research design was explanatory and employed quantitative methods that enabled comparison of six years trend analysis of firms’ performance – ‘before’ and ‘during’ power outage periods. Key performance indicators measured were Revenue, Profitability and Growth Rate. Findings were that power outages did not have effect on revenue generation of listed firms and that contrary, they recorded h

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Matsubara, Masashi, Masahiro Mae, and Ryuji Matsuhashi. "Investigation of Residential Value of Lost Load and the Importance of Electric Loads During Outages in Japan." Energies 18, no. 8 (2025): 2060. https://doi.org/10.3390/en18082060.

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Reducing damage caused by power outages is important against the background of severe natural disasters. Estimating the value of lost load (VoLL) is key to making an optimal investment plan for power systems. This paper aims to estimate the recent residential VoLL in Japan by using a survey. The contingent valuation method quantifies the residential willingness to pay (WTP) and its distribution in a 2 h outage during summer. When combining actual demand data, the VoLL is estimated at 501.1 JPY/kWh for a predictable outage and 559.9 JPY/kWh for a sudden one. In addition, the random utility mode

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Northrop, Alexander J., Nina M. Flores, Vivian Do, Perry E. Sheffield, and Joan A. Casey. "Power outages and pediatric unintentional injury hospitalizations in New York State." Environmental Epidemiology 8, no. 1 (2023): e287. http://dx.doi.org/10.1097/ee9.0000000000000287.

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Background: In the past decade, electrical power disruptions (outages) have increased in the United States, especially those attributable to weather events. These outages have a range of health impacts but are largely unstudied in children. Here, we investigated the association between outages and unintentional injury hospitalizations, a leading cause of childhood morbidity. Methods: The study setting was New York State (NYS) from 2017 to 2020. Outage exposure was defined as ≥10%, ≥20%, and ≥50% of customers from a power operating locality without power, ascertained from NYS Department of Publ

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Jin, Jun, Wen Xia Liu, and Zong Qi Liu. "A Weather Dependent Failure Rate Model for Overhead Lines." Applied Mechanics and Materials 291-294 (February 2013): 2387–92. http://dx.doi.org/10.4028/www.scientific.net/amm.291-294.2387.

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In power system planning and operation, accurate assessment of overhead lines outage rate is essential for making timely decisions. The overhead lines are often influenced by many random events, such as accidents and weather conditions, resulting in power outages. Especially, the reliability of the overhead lines is subjected to weather conditions to a great extent[9]. At present, research about weather conditions dependent reliability is abundant, but many of them are based on synthetical weather, little of them base on specific weather conditions such as typhoon and thunder .This paper propo

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Kim, Tae-Woo, Yenjae Chang, Dae-Wook Kim, and Man-Keun Kim. "Preventive Maintenance and Forced Outages in Power Plants in Korea." Energies 13, no. 14 (2020): 3571. http://dx.doi.org/10.3390/en13143571.

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Maintaining high facility reliability in power plants is essential to secure long-term electricity supply. This paper applies the survival analysis to the actual unit level power generation data in Korea to estimate the relationship between facility reliability and the preventive maintenance. Duration of generators between forced outages is used to measure plant reliability. the empirical analysis shows that preventive maintenance cost, planned outage for maintenance, use rate, and reserve margin lead to the longer duration of generators and, in turn, the lower forced outage rates. We uncover

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Onyedikachi, S. Nnamdi, A. Anazia Emmanuel., and O. Rebecca Obroh. "Predicting Post Outage Transmission Line Flows using Linear Distribution Factors." International Journal of Engineering and Management Research 8, no. 5 (2018): 100–106. https://doi.org/10.31033/ijemr.8.5.11.

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In order to design and implement preventive and remedial actions, a continuous performance of fast security analysis is imperative amid outages of system components. Following the contingency of a system component, State estimation and Load flow techniques are the two popular techniques used to determine system state variables leading to estimation of flows, losses and violations in nodal voltages and transmission line flows. But the dynamic state and complexity of the system requires faster means of estimations which can be achieved by linear distribution factors. The use of Distribution fact

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Fu, Jun, Xin Xu, Zhijie Sun, Li Wang, Dongmei Gong, and Lingyu Zhang. "Model Construction of Early Warning for Frequently Outage Complaint Based on Data Mining." MATEC Web of Conferences 173 (2018): 01002. http://dx.doi.org/10.1051/matecconf/201817301002.

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At present, frequent outages have become the major source of power customer complaints and, seriously affect improvement of customer service satisfaction. The current control of frequent outages, complaints has been in a passive state of compensation, which can only get half the result with twice the, effort and has caused adverse perception of customers. In response to this problem, this article takes the, initiative to prevent as a starting point, through studying rules of complaints business for the frequent power outage, constructs the early warning model of the frequent outages complaints

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Modarres, Mohammad. "Power outage planning." European Journal of Operational Research 49, no. 2 (1990): 254–65. http://dx.doi.org/10.1016/0377-2217(90)90343-a.

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Abir, Mahshid, Sophia Jan, Lindsay Jubelt, Raina M. Merchant, and Nicole Lurie. "The Impact of a Large-Scale Power Outage on Hemodialysis Center Operations." Prehospital and Disaster Medicine 28, no. 6 (2013): 543–46. http://dx.doi.org/10.1017/s1049023x13008844.

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AbstractIntroductionOn June 29, 2012, mid-Atlantic storms resulted in a large-scale power outage affecting up to three million people across multiple (US) states. Hemodialysis centers are dependent on electricity to provide dialysis care to end-stage renal disease patients. The objective of this study was to determine how the power outage impacted operations in a sample of hemodialysis centers in the impacted regions.MethodsThe sample consisted of all hemodialysis centers located in the District of Columbia and a total of five counties with the largest power losses in West Virginia, Virginia,

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Zaidan, Majeed Rashid, Ghanim Thiab Hasan, Mohit Bajaj, and Saber Izadpanah Toos. "Improving voltage collapse point under transmission line outage by optimal placement and sizing of SVC using genetic algorithm." International Journal of Applied Power Engineering (IJAPE) 13, no. 1 (2024): 213. http://dx.doi.org/10.11591/ijape.v13.i1.pp213-222.

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In many power systems, voltage instability can increase the risk of voltage collapse and, as a result, turn the power system toward a blackout. Therefore, increasing the voltage collapse point is required. A transmission line outage is an emergency condition in power systems that can lead to voltage instability and voltage collapse. Thus, it is expected to employ shunt-connected flexible AC transmission systems (FACTS) such as the static var compensator (SVC) to increase the voltage collapse point when lines outage. This paper presents the genetic algorithm (GA) application to optimal placemen

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Zaidan, Majeed Rashid, Ghanim Thiab Hasan, Mohit Bajaj, and Saber Izadpanah Toos. "Improving voltage collapse point under transmission line outage by optimal placement and sizing of SVC using genetic algorithm." International Journal of Applied Power Engineering (IJAPE) 13, no. 1 (2024): 213–22. https://doi.org/10.11591/ijape.v13.i1.pp213-222.

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In many power systems, voltage instability can increase the risk of voltage collapse and, as a result, turn the power system toward a blackout. Therefore, increasing the voltage collapse point is required. A transmission line outage is an emergency condition in power systems that can lead to voltage instability and voltage collapse. Thus, it is expected to employ shunt-connected flexible AC transmission systems (FACTS) such as the static var compensator (SVC) to increase the voltage collapse point when lines outage. This paper presents the genetic algorithm (GA) application to optimal placemen

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Jirovec, Ronald L., and John A. Erich. "Gray Power or Power Outage?" Journal of Women & Aging 7, no. 1-2 (1995): 85–99. http://dx.doi.org/10.1300/j074v07n01_07.

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Ali, Rafal, Ikramullah Khosa, Ammar Armghan, et al. "Financial Hazard Prediction Due to Power Outages Associated with Severe Weather-Related Natural Disaster Categories." Energies 15, no. 24 (2022): 9292. http://dx.doi.org/10.3390/en15249292.

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Severe weather conditions not only damage electric power infrastructure, and energy systems, but also affect millions of users, including residential, commercial or industrial consumers. Moreover, power outages due to weather-related natural disasters have been causing financial losses worth billions of US dollars. In this paper, we analyze the impact of power outages on the revenue of electric power suppliers, particularly due to the top five weather-related natural disasters. For this purpose, reliable and publicly available power outage events data are considered. The data provide the time

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Zhu, Laiyin, and Steven M. Quiring. "Hybrid Machine Learning Model for Hurricane Power Outage Estimation from Satellite Night Light Data." Remote Sensing 17, no. 14 (2025): 2347. https://doi.org/10.3390/rs17142347.

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Hurricanes can cause massive power outages and pose significant disruptions to society. Accurately monitoring hurricane power outages will improve predictive models and guide disaster emergency management. However, many challenges exist in obtaining high-quality data on hurricane power outages. We systematically evaluated machine learning (ML) approaches to reconstruct historical hurricane power outages based on high-resolution (1 km) satellite night light observations from the Defense Meteorological Satellite Program (DMSP) and other ancillary information. We found that the two-step hybrid mo

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Bradu, B., and G. Ferlin. "LHC cryogenics and helium management in case of a major power outage." IOP Conference Series: Materials Science and Engineering 1327, no. 1 (2025): 012118. https://doi.org/10.1088/1757-899x/1327/1/012118.

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Abstract The Large Hadron Collider (LHC) houses a very large inventory of helium (to-talizing 150 tons, including the strategic operational reserve) which must be properly managed and secured in the event of a major power outage. This paper presents dynamic simulations of the LHC cryogenic system following such an event and analyzes the different possible scenarios with their consequences. The simulations are first compared with experimental data obtained during relatively short power outages to validate the model. Then, the simulations are used to predict the behavior of the LHC cryogenic sys

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Flores, Nina M., Alexander J. Northrop, Vivian Do, et al. "Powerless in the storm: Severe weather-driven power outages in New York State, 2017–2020." PLOS Climate 3, no. 5 (2024): e0000364. http://dx.doi.org/10.1371/journal.pclm.0000364.

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The vulnerability of the power grid to severe weather events is a critical issue as climate change is expected to increase extreme events, which can damage components of the power grid and/or lessen electrical power supply, resulting in power outages. However, largely due to an absence of granular spatiotemporal outage data, we lack a robust understanding of how severe weather-driven outages, their community impacts, and their durations distribute across space and socioeconomic vulnerability. Here, we pair hourly power outage data in electrical power operating localities (n = 1865) throughout

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Amit, S. Closepet*1 &. K. Uma Rao2. "PARTIAL OUTAGE ALONG WITH GAME THEORY ALGORITHM FOR ENERGY COST OPTIMIZATION IN DEVELOPING COUNTRIES." INTERNATIONAL JOURNAL OF ENGINEERING SCIENCES & RESEARCH TECHNOLOGY 7, no. 2 (2018): 93–101. https://doi.org/10.5281/zenodo.1165662.

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This paper describes the significant cost saving opportunities for consumers in developing coun- tries by the use of a simple non-co-operative game theoretic mathematical model for demand- side-management techniques along with partial outage to mitigate the massive use of diesel back-up during grid outages and also other cost optimization schemes. Application of real time load scheduling optimization is investigated during power outages, for residential consumer in India. This method involves a beautiful formulation of a non–co-operation behavior between the diesel generator & the re

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