Analysis Of Outages Research Articles

Research on the Root Cause Analysis and Governance Measures of Frequent Power Outages in Electric Power Enterprises

Abstract Accompanied by the rapid development of the economy and the great strides of reform, the whole society puts forward higher and higher requirements for the safety and stability of the power grid, and the frequent power outage events will bring great losses to the power enterprises. In this paper, we employ the linear encoding function in the MAGNN method to linearly process the risk factors associated with frequent power outages in electric power enterprises. We then assign weights to these linearly processed risk factor vectors using a graph attention mechanism. Finally, we apply the correction matrix of outage risk factors to identify the risk of power outages in electric power enterprises and design an intelligent power outage control system. The study discovered that 10 kV system failure is the primary cause of frequent outages in Power Enterprise-A. The number of failures occurred 129 times due to 10kV feeder system failures in rural distribution networks. The study also reveals that the implementation of an intelligent outage control system resulted in a 73.60% year-over-year decrease in the reliability loss of fault outages in power enterprise A, thereby effectively addressing the issue of frequent outages and reducing the economic losses incurred by power enterprises. This paper provides an effective method for resolving frequent power outages in electric power enterprises and provides a guiding direction for improving power supply reliability in electric power enterprises.

Analysis of animal-related electric outages using species distribution models and community science data

Animal-related outages (AROs) are a prevalent form of outages in electrical distribution systems. Animal-infrastructure interactions vary across species and regions, underlining the need to study the animal-outage relationship in more species and diverse systems. Animal activity has been an indicator of reliability in the electrical grid system by describing temporal patterns in AROs. However, these ARO models have been limited by a lack of available species activity data, instead approximating activity based on seasonal patterns and weather dependency in ARO records and characteristics of broad taxonomic groups, e.g. squirrels. We highlight available resources to fill the ecological data gap limiting joint analyses between ecology and energy sectors. Species distribution modeling (SDM), a common technique to model the distribution of a species across geographic space and time, paired with community science data, provided us with species-specific estimates of activity to analyze alongside spatio-temporal patterns of ARO severity. We use SDM estimates of activity for multiple outage-prone bird species to examine whether diverse animal activity patterns were important predictors of ARO severity by capturing existing variation within animal-outage relationships. Low dimensional representation and single patterns of bird activity were important predictors of ARO severity in Massachusetts. However, both patterns of summer migrants and overwintering species showed some degree of importance, indicating that multiple biological patterns could be considered in future models of grid reliability. Making the best available resources from quantitative ecology known to outside disciplines can allow for more interdisciplinary data analyses between ecological and non-ecological systems. This can result in further opportunities to examine and validate the relationships between animal activity and grid reliability in diverse systems.

Lights-Out After Hurricane Michael: A Spatially Informed Bayesian Network Analysis of Power Outages

Lights-Out After Hurricane Michael: A Spatially Informed Bayesian Network Analysis of Power Outages

Statistical and Spatial Analysis of Hurricane-induced Roadway Closures and Power Outages

Hurricanes lead to substantial infrastructure system damages, such as roadway closures and power outages, in the US annually, especially in states like Florida. As such, this paper aimed to assess the impacts of Hurricane Hermine (2016) and Hurricane Michael (2018) on the City of Tallahassee, the capital of Florida, via exploratory spatial and statistical analyses on power outages and roadway closures. First, a geographical information systems (GIS)-based spatial analysis was conducted to explore the power outages and roadway closure patterns in the city including kernel density estimation (KDE) and density ratio difference (DRD) methods. In order to provide a more detailed assessment on which population segments were more affected, a second step included a statistical analysis to identify the relationships between demographic- and socioeconomic-related variables and the magnitude of power outages and roadway closures caused by these hurricanes. The results indicate that the high-risk locations for roadway closures showed different patterns, whereas power outages seemed to have similar spatial patterns for the hurricanes. The findings of this study can provide useful insights and information for city officials to identify the most vulnerable regions which are under the risk of disruption. This can lead to better infrastructure plans and policies.

Outage Analysis and System Disturbances on 330 kV and 132 kV Transmission System in Nigeria

The Persistent power outage in the country due to faults has become alarming to the government and the body responsible for electricity generation in the country. It also creates a major problem for electricity consumers in Nigeria, there must be an improvement in the reliability of the transmission system in Nigeria. This research work is predominantly concerned with the analysis of outages on 330kV and 132kV transmission system, and system disturbances on generation and transmission system for five (5) years. The result shows that the forced outages are the most occurred outages on the 330 kV line, while on 132 kV line, emergency outages have the highest number of outages in 2014 but decreases rapidly over the years, similarly, twenty-seven (27) major system disturbances occurred in 2016 with 31% against ten (10) with 11% disturbances in 2015, while 2014 and 2018 with the same number of system disturbances of thirteen (13) with 15%, it is apparent that more disturbances occur on the transmission system, and there should be a proper protection scheme to maintain stable grid network. Consequently, Mini-grid and off-grid solutions will prominently address the issue of power supply shortage and instability in Nigeria. Keywords: outage, transmission, generation, disturbances, grid.

Outage Analysis and System Disturbances on 330 kV and 132 kV Transmission System in Nigeria

The Persistent power outage in the country due to faults has become alarming to the government and the body responsible for electricity generation in the country. It also creates a major problem for electricity consumers in Nigeria, there must be an improvement in the reliability of the transmission system in Nigeria. This research work is predominantly concerned with the analysis of outages on 330kV and 132kV transmission system, and system disturbances on generation and transmission system for five (5) years. The result shows that the forced outages are the most occurred outages on the 330 kV line, while on 132 kV line, emergency outages have the highest number of outages in 2014 but decreases rapidly over the years, similarly, twenty-seven (27) major system disturbances occurred in 2016 with 31% against ten (10) with 11% disturbances in 2015, while 2014 and 2018 with the same number of system disturbances of thirteen (13) with 15%, it is apparent that more disturbances occur on the transmission system, and there should be a proper protection scheme to maintain stable grid network. Consequently, Mini-grid and off-grid solutions will prominently address the issue of power supply shortage and instability in Nigeria. Keywords: outage, transmission, generation, disturbances, grid.

Outage Analysis and System Disturbances on 330 kV and 132 kV Transmission System in Nigeria

The Persistent power outage in the country due to faults has become alarming to the government and the body responsible for electricity generation in the country. It also creates a major problem for electricity consumers in Nigeria, there must be an improvement in the reliability of the transmission system in Nigeria. This research work is predominantly concerned with the analysis of outages on 330kV and 132kV transmission system, and system disturbances on generation and transmission system for five (5) years. The result shows that the forced outages are the most occurred outages on the 330 kV line, while on 132 kV line, emergency outages have the highest number of outages in 2014 but decreases rapidly over the years, similarly, twenty-seven (27) major system disturbances occurred in 2016 with 31% against ten (10) with 11% disturbances in 2015, while 2014 and 2018 with the same number of system disturbances of thirteen (13) with 15%, it is apparent that more disturbances occur on the transmission system, and there should be a proper protection scheme to maintain stable grid network. Consequently, Mini-grid and off-grid solutions will prominently address the issue of power supply shortage and instability in Nigeria.

An Online Search Method for Representative Risky Fault Chains Based on Reinforcement Learning and Knowledge Transfer

In the analysis of cascading outages and blackouts in power systems, risky cascading fault chains should be accurately identified in order to do further block or alleviate blackouts. However, the huge computational burden makes online analysis difficult. In this paper, an online search method for representative risky fault chains based on reinforcement learning and knowledge transfer is proposed. This method aims at promoting efficiency by exploiting similarities of adjacent power flow snapshots in operations. After the “representative risky fault chain” is defined, a framework of tree search based on Markov Decision Process and Q-learning is constructed. The knowledge in past runs is accumulated offline and then applied online, with a mechanism of knowledge transition and extension. The proposed learning based approach is verified on an illustrative 39-bus system with different loading levels, and simulations are carried out on a real-world 1000-bus power grid in China to show the effectiveness and efficiency of the proposed approach.

The CRI-model: A domain-independent taxonomy for non-conformance between observed and specified behaviour

Anomaly detection is the process of identifying nonconforming behaviour. Many approaches from machine learning to statistical methods exist to detect behaviour that deviate from its norm. These non-conformances of specifications can stem from failures in the system or undocumented changes of the system during its evolution. However, no generic solutions exist for classifying and identifying these non-conformances. In this paper, we present the CRI-Model (Cause, Reaction, Impact), which is a taxonomy based on a study of anomaly types in the literature, an analysis of system outages in major cloud companies and evolution scenarios which describe and implement changes in Cyber-Physical Production Systems. The goal of the taxonomy is to be usable for different objectives like discover gaps in the detection process, determine components most often affected by a particular anomaly type or describe system evolution. While the dimensions of the taxonomy are fixed, the categories can be adapted to different domains. We show and validate the applicability of the taxonomy to distributed cloud systems using a large data set of anomaly reports and cyber-physical production systems by categorizing common changes of an evolution benchmarking plant.

An Analysis of Power Transformer Outages and Reliability Monitoring

Power transformers play an important and significant role in the power system to connecting the subsystems and delivering the electricity to consumers. Power transformers are one of the most expensive elements in the power system, so focus on their status of parameters is the primary task. The reliability assessment and efficiency of the transformers have a major impact on the security. The power transformers constantly subjected to failures in its components, and their effect is interruptions of consumer’s supply and reliability. So, methodology related to reliability assessment of power transformers includes; monitoring of operation status, type of failures, forced outages and interruption time. The study includes; type of failures, reliability and condition assessment based on statistical data monitoring during the years in the Power Transmission System of Kosovo.

Vulnerability Analysis of Multiple Critical Fault Outages and Adaptive Under Voltage Load Shedding Scenarios in Marmara Region Electrical Power Grid

The utilization of electrical power system has been rising frequently from past to now and there is a need of dependable electrical transmission and distribution networks so as to ensure continuous and balanced energy. Besides, conventional energy governance systems have been forced to change as a result of rises in the usage of renewable energy resources and the efficiency of demand-side on the market. In this regard, electrical power systems should be planned and operated, appropriately and the balance of production and consumption demand should be provided within the nominal voltage limits. In this study, firstly, the current status of Marmara region interconnected power grid in Turkey is evaluated. Afterwards, the multiple cascading failure outages scenarios are modeled by “DIgSILENT Power Factory V14” software. The critical transmission line scenarios are implemented on the high voltage power grid model improved. These scenarios are based on the period of maximum and minimum production and consumption demand and the effects of demand response in this period. As a result of grid vulnerability analyses performed, several findings has been obtained about the impacts of different line scenarios on the high voltage transmission system, the optimization of power grid voltage profile and the role of production and consumption demand response on voltage regulation.

Dual Theory of Transmission Line Outages

A new graph dual formalism is presented for the analysis of line outages in electricity networks. The dual formalism is based on a consideration of the flows around closed cycles in the network. After some exposition of the theory is presented, a new formula for the computation of Line Outage Distribution Factors (LODFs) is derived, which is not only computationally faster than existing methods, but also generalizes easily for multiple line outages and arbitrary changes to line series reactance. In addition, the dual formalism provides new physical insight for how the effects of line outages propagate through the network. For example, in a planar network a single line outage can be shown to induce monotonically decreasing flow changes, which are mathematically equivalent to an electrostatic dipole field.

Analysis of Country-Wide Internet Outages Caused by Censorship

In the first months of 2011, Internet communications were disrupted in several North African countries in response to civilian protests and threats of civil war. In this paper, we analyze episodes of these disruptions in two countries: Egypt and Libya. Our analysis relies on multiple sources of large-scale data already available to academic researchers: BGP interdomain routing control plane data, unsolicited data plane traffic to unassigned address space, active macroscopic traceroute measurements, RIR delegation files, and MaxMind's geolocation database. We used the latter two data sets to determine which IP address ranges were allocated to entities within each country, and then mapped these IP addresses of interest to BGP-announced address ranges (prefixes) and origin autonomous systems (ASs) using publicly available BGP data repositories in the US and Europe. We then analyzed observable activity related to these sets of prefixes and ASs throughout the censorship episodes. Using both control plane and data plane data sets in combination allowed us to narrow down which forms of Internet access disruption were implemented in a given region over time. Among other insights, we detected what we believe were Libya's attempts to test firewall-based blocking before they executed more aggressive BGP-based disconnection. Our methodology could be used, and automated, to detect outages or similar macroscopically disruptive events in other geographic or topological regions.

Bayesian Methods for Analysis of Electric Grid Outages

Electric transmission network reliability assessment is considered in this paper. The lack of coherent probabilistic treatment of network reliability is discussed and advantages of Bayesian modelling are used in order to take into account uncertainties due to differences of network parts (i.e. transmission lines located in varying environmental conditions) and resulting failure mechanisms. By analysing real North American electric transmission grid outage event data we show the superiority of Bayesian hierarchical models for network reliability evaluation. General results of network outage hierarchical analysis were directly transferred to evaluate reliability of specific network configuration of several lines.

Risk analysis of critical infrastructures emphasizing electricity supply and interdependencies

Failures in critical infrastructures can cause major damage to society. Wide-area interruptions (blackouts) in the electricity supply system have severe impacts on societal critical functions and other critical infrastructures, but there is no agreed-upon framework on how to analyze and predict the reliability of electricity supply. Thus, there is a need for an approach to cross-sector risk analyses, which facilitates risk analysis of outages in the electricity supply system and enables investigation of cascading failures and consequences in other infrastructures. This paper presents such an approach, which includes contingency analysis (power flow) and reliability analysis of power systems, as well as use of a cascade diagram for investigating interdependencies. A case study was carried out together with the Emergency Preparedness Group in the city of Oslo, Norway and the network company Hafslund Nett. The case study results highlight the need for cross-sector analyses by showing that the total estimated societal costs are substantially higher when cascading effects and consequences to other infrastructures are taken into account compared to only considering the costs of electricity interruptions as seen by the network company. The approach is a promising starting point for cross-sector risk analysis of electricity supply interruptions and consequences for dependent infrastructures.

Lights Out

Little is known about how power outages affect health. We investigated mortality effects of the largest US blackout to date, 14-15 August 2003 in New York, NY. We estimated mortality risk in New York, NY, using a generalized linear model with data from 1987-2005. We incorporated possible confounders, including weather and long-term and seasonal mortality trends. During the blackout, mortality increased for accidental deaths (122% [95% confidence interval = 28%-287%]) and nonaccidental (ie, disease-related) deaths (25% [12%-41%]), resulting in approximately 90 excess deaths. Increased mortality was not from deaths being advanced by a few days; rather, mortality risk remained slightly elevated through August 2003. To our knowledge, this is the first analysis of power outages and nonaccidental mortality. Understanding the impact of power outages on human health is relevant, given that increased energy demand and climate change are likely to put added strain on power grids.

Bayesian Network Model With Monte Carlo Simulations for Analysis of Animal-Related Outages in Overhead Distribution Systems

This paper extends previous research on using a Bayesian network model to investigate impacts of time (month) and weather (number of fair weather days in a week) on animal-related outages in distribution systems. Outage history (outages in the previous week) is included as an additional input to the model, and inputs and outputs are classified systematically to reduce errors in estimates of outputs. Conditional probability table obtained from the historical data are used to estimate weekly animal-related outages which is followed by a Monte Carlo simulation to find estimates of mean and confidence limits for monthly animal-related outages. Comparison of results obtained for four cities of different sizes in Kansas with those obtained using a hybrid wavelet/neural network model shows consistency between the two models. The methodology presented in this paper is simple to implement and useful for the utilities for year-end analysis of the outage data to identify specific reliability-related concerns.

Research on Vulnerability Assessment System of Complicated Power System

The factors which lead to large-area power outages are more than ever, when the complexity of the expansion power system is increasing. Therefore, it is important to assess the vulnerability of the complicated power system. This paper first proposes an objective, practical and adaptive vulnerability assessment system of complicated power system by use of Analytic Hierarchy Process, which based on multi-factors analysis of large-area outages. This system can find out the vulnerability point of the power system，and take advantages of the government, who can over-all plan, correspond and organize the social resource to reduce the vulnerability of power system and prevent large-area power outages, and the power enterprises who can maintaining the stability of power system by technology. Finally, the paper gives an assessment example of provincial power system.

Analysis of Animal-Related Outages in Overhead Distribution Systems With Wavelet Decomposition and Immune Systems-Based Neural Networks

Outages in overhead distribution systems caused by different factors significantly impact their reliability. Since animals cause large number of outages in overhead distribution systems, analysis of these outages has a practical value as it allows utilities to keep track of historical trends. This paper presents a methodology for yearend analysis of animal-caused outages in the past year. Models to estimate weekly animal-caused outages in overhead distribution systems using combination of wavelet transform techniques and neural networks are presented. Discrete wavelet transform is applied to decompose the time series of weekly animal-caused outages into two components and separate neural networks are constructed for each decomposed coefficient series. The outputs of neural networks are combined according to wavelet reconstruction techniques to get estimated results for the weekly animal-caused outages. Artificial immune system (AIS) is used to overcome the overtraining problem associated with neural networks. Results obtained for four districts in Kansas of different sizes are compared with observed outages to evaluate performance of three different models for estimating these outages.

Hybrid Model for Cascading Outage in a Power System: A Numerical Study

Analysis of cascading outages in power systems is important for understanding why large blackouts emerge and how to prevent them. Cascading outages are complex dynamics of power systems, and one cause of them is the interaction between swing dynamics of synchronous machines and protection operation of relays and circuit breakers. This paper uses hybrid dynamical systems as a mathematical model for cascading outages caused by the interaction. Hybrid dynamical systems can combine families of flows describing swing dynamics with switching rules that are based on protection operation. This paper refers to data on a cascading outage in the September 2003 blackout in Italy and shows a hybrid dynamical system by which propagation of outages reproduced is consistent with the data. This result suggests that hybrid dynamical systems can provide an effective model for the analysis of cascading outages in power systems.