Power System Reliability Analysis Research Articles

Precise Modeling and Analysis of Aviation Power System Reliability via the Aviation Power System Reliability Probability Network Model

This study addresses the challenges of accurately analyzing the reliability of aviation power systems (APS) using traditional models by introducing the Aviation Power System Reliability Probability Network Model (APS-RPNM). The model directly transforms the system architecture into an equivalent probability network, aiming to develop a precise reliability model that captures system functions and fault logic. By classifying APS components into five distinct structural patterns and mapping them to corresponding nodes in the APS-RPNM, the model is successfully constructed. Specifically, None-Input-to-Multiple-Output components are transformed into two-state nodes, while Multiple-Input-to-None-Output, Single-Input-to-Multiple-Output, and Multiple-Input-to-Single-Output components are mapped to three-state nodes. For Multiple-Input-to-Multiple-Output components, a novel approach employing multiple two-state sub-nodes is adopted to capture their complex functional logic. A case study comparing the performance of the APS-RPNM with the traditional minimal path set method in reliability analysis was conducted. The results demonstrate that the APS-RPNM not only simplifies the model construction process and eliminates errors stemming from subjective engineering judgments but also enables the efficient computation of power supply reliability for all load points in a single inference by integrating all of the components. This significantly improves computational efficiency and system dependency analysis capabilities, highlighting the APS-RPNM’s tremendous potential in optimizing the reliability design of APS.

Composite reliability analysis of electric power systems considering climatic and spatial conditions using self-organizing map

This article presents an innovative approach by integrating different models that represent the failure rates of components related to weather events, considering the geographic location and its variation over time, to a customized Monte Carlo simulation model to ensure the draw synchronized with the load and generation curves, and then quantify the impact of these events through the power flow. The study focuses on using a neural network is trained to classify/filter system states in order to reduce the need for electrical studies and speed up the reliability assessment process. The approach is demonstrated with reference to the IEEE-RTS network test case. The results obtained indicate that the inclusion of renewable sources and climatic conditions have a significant impact on reliability indicators, as failure rates subject to these meteorological conditions tend to increase, providing a greater risk of simultaneous shutdowns, and contributing to the worsening of the system severity index. Therefore, the proposed model allows for a faster and more realistic reliability assessment, directing the planning of expansions and reinforcements and allowing risk monitoring during system operation.

Reliability Analysis of Power System Considering Flexibility Resources

Flexible resources are a critical resource in ensuring the security and steady running of a large percentage of electricity systems that use new sources of energy. The power system’s flexible resources participate in power regulation, improving the power system capability to absorb new energy and also the electricity system’s reliability. This paper calculates the dependability index of electricity system using the basic calculation method of the equivalent energy function. By flexibly handling the new power generation curve’s adjustable capacity and flexible resources, new energy generation and flexible resources count toward equivalent energy calculation, and the dependability index of the electricity system is calculated. The efficacy of this approach is illustrated by an example.

Accounting for component condition and preventive retirement in power system reliability analyses

AbstractDeteriorated power system components have a higher probability of failure than new components. Still, the reliability of supply analyses traditionally models all components of the same type with the same probability of failure, and thus neglects the effect of deteriorated components. This paper presents a methodology to integrate a condition‐dependent component probability of failure model into a power system reliability analysis. The component state is described by a semi‐Markov process, and the paper shows how this, under reasonable assumptions, can be approximated by a Markov process. The Markov assumption simplifies the analysis and allows the model to include preventive retirement and be calibrated to statistical data. A case study using statistical data for Norwegian power transformers shows that, in the Norwegian power system, the proportion of failures that are due to the poor condition is small, partly due to the common strategy of preventive retirement. However, if the condition of the transformers were worse, the impact of poor conditions can be considerable. The methodology further enables the identification of the transformers that contribute most to the risk to the reliability of supply. The paper thus highlights the importance of accounting for the component condition in strategic decisions such as long‐term renewal planning

Reliability Analysis and Economic Prospect of Wind Energy Sources Incorporated Microgrid System for Smart Buildings Environment

This work deals with assessing the reliability of wind energy sources incorporated into a microgrid system to increase grid stability. As the share of power generated from wind energy continues to increase due to environmental concerns and to reduce carbon footprints, the case study proposed is designing an effective wind energy system for a smart building environment to reduce the burden on the grid. Incorporating wind energy systems into grid-connected buildings increases the reliability of the microgrid system for smart building environments. Applying smart techniques with integrated automation in the built environment can play a key role in decreasing peak demand for load development in smart cities. This can also enhance the overall efficiency of power grids, reduce waste, and enable the effective use of energy resources. Furthermore, researchers are finding new ways to collect energy from renewable sources and power-built environments due to dwindling fossil fuel resources and increased environmental awareness. The analysis of wind-connected power systems has been initiated to satisfy the increasing demand for reliable supply systems by consumers. This has prompted the use of wind energy systems with controlled techniques to enhance the reliability of power systems and reduce carbon footprints generated by fossil fuel-based power systems. Therefore, the main purpose of this work is to understand the economic prospects of wind energy sources for smart building environments, reliability analysis of wind energy sources-based power systems, reduce carbon footprints, and balance power demand through wind energy systems. The Progressive Wind Model Taylor-Sequence Proliferation (PWMTSP) and Innovative Six Parameters Based Progressive Beta Creative Model (ISPBPBCM) approaches are proposed to understand the reliability of wind energy-based power systems in smart building environments. The work also provides an economic analysis of the proposed low-cost wind power system with different capacities for residential consumers in selected geographic location. Eight cases are considered for the proposed effective wind energy system for smart building environments ranging from 2 MW to 32 MW. Hence, the economic analysis of the proposed systems is discussed for residential users. All eight cases are eco-friendly and reduce carbon emissions as these generated units from wind energy sources need not be purchased from fossil fuel-based plants, which increases the reliability of the proposed system. The expected energy not supplied (EENS) in the planned work increases as wind power capacity increases. Loss of load expectation (LOLE), loss of load probability (LOLP), and failure rate all decrease with the installation of more wind power systems. Moreover, it can be seen that mean time to repair (MTTR) improves when wind energy capacity rises incrementally from 2 MW to 32 MW. The proposed method is anticipated to be adaptable to various types of wind energy systems where dependability is a crucial component of system design and scalable to large wind integrated power systems.

Повышение киберустойчивости SCADA и WAMS при кибератаках на информационно-коммуникационную подсистему ЭЭС

Research objective: development of measures to ensure cyber resilience of SCADA and WAMS under realized threats, the consequence of which is a decrease in the quality of information required in the control of the electric power system (EPS). Research methods: probabilistic methods, methods of power system reliability analysis, Markov methods. Research result. A comparative analysis of possible states of information collection, transmission, and processing systems (SCADA, WAMS) during cyberattacks on the information and communication system was carried out. SCADA and WAMS cyber resilience models were developed. On the basis of the models proposed, measures to ensure cyber resilience of information collection, transmission, and processing system were put forward. Keywords: cyber-physical power system; resilience; information collection, processing, and transmission system; false data injection attack; DoS-attack; state estimation.

Adequacy Evaluation of an Islanded Microgrid

The reliability of power converters has been extensively examined in terms of component- and converter level. However, in case of multiple generation units, the evaluation of the performance of power systems requires system-level modeling. This paper aims to merge the prior art of reliability modeling of power converters with the adequacy evaluation of power systems through an extensive design and evaluation analysis of a microgrid based case study. The methodology proposed in the paper integrates the device-level analysis into the domain of the conventional power system reliability analysis while outlining the steps needed to deal with non-exponential distributed failures of power electronic-based generation units. A replacement policy of the power electronic-based units is adopted by means of evaluating the system risk of not supplying system loads, and, finally, an approach on how to ensure a desired replacement frequency is outlined.

Reliability evaluation of generating systems considering aging processes

Equipment aging has been a major concern among electric utilities’ planners, since quality of service can be put at risk. This paper proposes a new method that allows the effects of the aging of generators to be properly included into the reliability analysis of power systems. First, a new model for the failure rate capable of representing the stages of normal operation and wear-out, replacing the adoption of constant failure rates, is described. The effects of repairable and non-repairable (i.e., catastrophic) failures on the reliability assessment of generation systems are also discussed. The proposed method is built from the previous models using a sequential Monte Carlo simulation and variance reduction techniques. To validate the proposed method, the IEEE Reliability Test System is used with modifications in which different ages are defined for existing generating units that are progressively aging over the years. Several tests are described together with strategies for adopting preventive refurbishments and the corresponding results are duly discussed.

Full Scale Experiment for Vibration Analysis of Ice-Coated Bundled-Conductor Transmission Lines

Full scale experiment has received increasing attention in recent years for the reliability analysis of power supplies and power systems. In this paper, the vibration behaviours of conductors with and without D-section ice coatings are addressed by virtue of a field test platform consisting of the prototype of a transmission tower-line system. Utilizing fibre Bragg grating sensors, the vibration of conductors under artificial displacement and natural wind excitations are monitored, and their dynamic characteristics are assessed by the spectral analysis and the identification technique of Hilbert-Huang transform. It is revealed that the vibrations of ice-free and ice-coated multi-bundled conductors vary wildly despite under similar artificial displacements and natural wind excitations. The vibration of ice-coated conductors is mainly dominated by their low-order modes, especially in the frequency range of 0.24–2.0 Hz; while the vibration of ice-free conductors gains more benefits from their high-order modes. Compared to the ice-free conductors, the conductors with eccentric ice coating are prone to suffer from galloping under specified wind attack angle; although their vibrations are still controlled by the low-order modes, yet the frequency values of the dominant modes have changed from one wind attack angle case to another. This kind of frequency modulation phenomenon indicates that nonlinear vibration characteristics of ice-coated conductors might change under different wind conditions, which brings great challenges to the research of wind-induced vibration characteristics of ice-coated conductors.

Incorporating Power Electronic Converters Reliability Into Modern Power System Reliability Analysis

This article aims to incorporate the reliability model of power electronic converters into power system reliability analysis. The converter reliability has widely been explored in device- and converter-levels according to physics of failure analysis. However, optimal decision-making for design, planning, operation, and maintenance of power electronic converters require system-level reliability modeling of power electronic-based power systems. Therefore, this article proposes a procedure to evaluate the reliability of power electronic-based power systems from the device-level up to the system-level. Furthermore, the impact of converter failure rates including random chance and wear-out failures on power system performance in different applications such as wind turbine and electronic transmission lines is illustrated. Moreover, because of a high calculation burden raised by the physics of failure analysis for large-scale power electronic systems, this article explores the required accuracy for reliability modeling of converters in different applications. Numerical case studies are provided employing modified versions of the Roy Billinton Test System (RBTS). The analysis shows that the converter failures may affect the overall system performance depending on its application. Therefore, an accurate converter reliability model is, in some cases, required for reliability assessment and management in modern power systems.

Оценка показателей киберустойчивости систем сбора и обработки информации в ЭЭС на основе полумарковских моделей

Purpose of the study: The study aims to design an algorithm for determining the cyber resilience indices of information collection, transmission, and processing systems (SCADA, WAMS) to control electric power systems. This algorithm makes it possible to factor in possible states and measures to restore such systems when cyber resilience is lost. Research methods include the probability theory, methods of power system reliability analysis, and Markov methods. Result of the research: The analysis of the reliability of WAMS, which is necessary for assessing the cyber resilience of the EPS, has been carried out. A cyber resilience model is proposed, on the basis of which an algorithm for determining the cyber resilience index of SCADA, WAMS systems with a low quality of measurement information used in EPS control has been developed. To take into account possible states of SCADA, WAMS systems and measures for their restoration (detection, mitigation and response) in case of violation of cyber resilience, the algorithm uses the tools of probability theory and Markov methods. The effectiveness of the application of the developed algorithm is confirmed by the example of calculating the WAMS cyber resilience index with a low quality of PMU data. The results obtained can be useful in making decisions on the formation of control actions on the EPS to ensure its cybersecurity in the context of cyber-attacks on information collection, transmission, and processing systems.

Faults and reliability analysis of negative resistance converter traction power system

To analyse the reliability of negative resistance converter traction power system (NRC-TPS), this paper discusses the short-circuit and open-circuit faults of its components. NRC-TPS is adopted to mitigate rail potential and stray current for the urban rail transit. The simulation results show that NRC-TPS can still mitigate rail potential and stray current at most faults. NRC-TPS is reliable for the urban rail transit to solve rail potential and stray current issues.

Reliability Analysis of Power Systems Integrated With High-Penetration of Power Converters

With the growing penetration of power electronic converters in power systems, the issue of reliability becomes more critical than ever before. This paper proposes a hierarchical reliability framework to evaluate the electric power system reliability from the power electronic converter level to the overall system level. On the converter level, the reliability model of a power electronic converter is developed based on the power electronic devices it is composed of, for which various hourly based input profiles and converter topologies are considered. On the system level, reliability metrics such as expected energy not served (EENS) and loss of load expectation (LOLE) are estimated through a non-sequential Monte Carlo simulation. Machine learning regression models, such as support vector regression (SVR), and random forests (RF) are implemented to bridge the nonlinear reliability relationship between two levels. The proposed framework is demonstrated through the modified IEEE Reliability Test System (RTS) 24-bus network. Numerical results show power converter reliability should be considered as an important factor when evaluating overall system reliability performance.

Component-Level Reliability Evaluation Model for Cyber Power Devices

Reliability evaluation of power components in the presence of automation devices and cyber links is critical for the improved performance of a smart grid. This work presents a model representing a cyber power component for reliability studies, incorporating interdependency and common-cause failure while reducing computational complexity. Power-component failure, automation-component failure, communication failure, communication delay, and cyberattack are incorporated to develop a comprehensive component-level reliability-evaluation model. A multistate model is proposed with 36 states for a cyber-enabled power component by integrating cyber links as a part of the smart component. Based on the power system reliability analysis, this model is reduced to a 12-state model. Finally, a two-state model is presented for its practical adaptation to specific applications. Due to the nature of the smart component, the following basic applications are considered in this work: (i) health monitoring, (ii) real-time monitoring, and (iii) actuation. A sensitivity analysis is carried out to evaluate the impact of cyber failure and cyberattacks on the reliability of the smart component. Model-reduction techniques, reliability-evaluation procedures, and example case study are provided in order to validate the proposed method.

Power system reliability analysis

Electric power development is the key factor of economic development, but also an important guarantee of industrial modernization. At present, with the improvement of people’s quality of life, electricity has become an indispensable part of ensuring people’s lives. Therefore, the stable and reliable development of power system has an important impact on economic development, industrial modernization and people’s lives. With the continuous maturity of the reliability theory, the power system and its combination have evolved into an important application subject called the reliability evaluation of the power system, which has penetrated into the whole industrial chain of the power system, which is a reliable guarantee for the industrial chain to gain economic and social benefits. Based on the analysis of the operation reliability of power system, this paper puts forward the main measures to improve the operation reliability of power system in order to meet the operation requirements.

Bayesian Estimates of Transmission Line Outage Rates That Consider Line Dependencies

Transmission line outage rates are fundamental to power system reliability analysis. Line outages are infrequent, occurring only about once a year, so outage data are limited. We propose a Bayesian hierarchical model that leverages line dependencies to better estimate outage rates of individual transmission lines from limited outage data. The Bayesian estimates have a lower standard deviation than estimating the outage rates simply by dividing the number of outages by the number of years of data, especially when the number of outages is small. The Bayesian model produces more accurate individual line outage rates, as well as estimates of the uncertainty of these rates. Better estimates of line outage rates can improve system risk assessment, outage prediction, and maintenance scheduling.

Eigenvector dimension-reduction method for reliability analysis of power systems under the time-dependent load uncertainty

ABSTRACT Power systems have become central pillars of modern society. Various uncertainties in power systems, however, make reliability analysis difficult. To date, the worst-case scenario was usually employed to tackle uncertainties in the system, which could make the overall system design prohibitively expensive especially when more and more uncertainty sources would be considered in modern power grids. This paper proposes reliability analysis of power systems under the time-dependent load uncertainty using an effective uncertainty quantification (UQ) method, i.e., the eigenvector dimension reduction (EDR) method. As such, reliability can be explicitly calculated in the probability manner for meeting the performance constraints without significantly overdesigning the system. Compared to the Monte Carlo simulation (MCS), the EDR method is much more efficient with satisfactory accuracy. Two case studies, including a 12-bus and a modified IEEE 118-bus power system, are used to demonstrate the feasibility of the proposed work.

Impact of Down Spinning Reserve on Operation Reliability of Power Systems

The development of renewable energy and the increasing peak-valley difference of load demand lead to an increasing requirement of spinning reserve (SR). However, the traditional operation reliability analysis of power system mainly focuses on the up SR and neglects the down SR. Therefore, the operation reliability of power system considering the impacts of down SR is investigated in this paper. Firstly, the constraints of down SR are incorporated into the day-ahead unit commitment (UC) model to obtain the generation scheduling and reserve allocation of power systems. Based on the dispatch results of UC model, the re-dispatched energy and load interruption can be determined using optimal power flow (OPF) model in the real-time operation in various contingency states. Operation reliability indices are calculated based on the load curtailment to represent the reliability performances of power systems. The proposed approaches are validated using the modified IEEE reliability test system. Case studies demonstrate that down SR can improve the operation reliability of power systems.

A comprehensive framework for vulnerability analysis of extraordinary events in power systems

Electric power systems are critical infrastructures subject to the possibility of extraordinary events with high societal consequences. Although such possibilities are often associated with very low probabilities of being realized, it is nevertheless crucial to be able to identify and understand the vulnerabilities of power systems related to extraordinary events. The objective of the work presented in this article is to establish a methodological basis for vulnerability analysis that is complementary to conventional risk and reliability analysis of power systems. It presents a comprehensive framework of definitions, indicators and methods that can be used to classify, analyse and monitor vulnerabilities in power transmission and distribution systems. Its main components include (1) a conceptual framework of definitions that forms the basis for understanding and classifying vulnerabilities, (2) an assessment methodology for identifying vulnerabilities related to extraordinary events and barriers to mitigate them, and (3) vulnerability indicators for quantifying and monitoring power system vulnerabilities. The applicability of the vulnerability analysis framework is demonstrated through several studies of real power systems. Moreover, the concept of power system vulnerability elaborated in this article is also related to the concept of power system resilience.

Reliability and exploitation analysis of ITS power systems including RES

The problem of reliability and exploitation analysis of power systems used in intelligent transport systems (ITS) is extremely important from the point of view of ensuring the traffic safety. The use of advanced electronic devices in ITS systems requires their power supply from properly designed power systems. To ensure the continuity of operation of electronic devices, the basic and backup power supply are most often used. They should have specific values of reliability and performance indicators. Therefore, a reliability and exploitation model of the power system has been developed, taking into account renewable energy sources (RES), such as used in intelligent transport systems. This allowed to obtain dependencies enqabling to determine the probability of staying of the power system used in the intelligent transport system in the specified reliability and exploitation states.