An experimental evaluation of software redundancy as a strategy for improving reliability

The strategy of using multiple versions of independently developed software as a means to tolerate residual software design faults is suggested by the success of hardware redundancy for tolerating hardware failures. Although, as generally accepted, the independence of hardware failures resulting from physical wearout can lead to substantial increases in reliability for redundant hardware structures, a similar conclusion is not immediate for software. The degree to which design faults are manifested as independent failures determines the effectiveness of redundancy as a method for improving software reliability. Interest in multi-version software centers on whether it provides an adequate measure of increased reliability to warrant its use in critical applications. The effectiveness of multi-version software is studied by comparing estimates of the failure probabilities of these systems with the failure probabilities of single versions. The estimates are obtained under a model of dependent failures and compared with estimates obtained when failures are assumed to be independent. The experimental results are based on twenty versions of an aerospace application developed and certified by sixty programmers from four universities. Descriptions of the application, development and certification processes, and operational evaluation are given together with an analysis of the twenty versions

Reliability Modeling and Analysis of Cyber Enabled Electric Power Systems

Cyber-induced failures affect power system reliability and thus are important to be considered in composite system reliability evaluation. This dissertation extends the scope of bulk power system reliability modeling and analysis with the consideration of cyber elements. A novel methodology by introducing the concept of Cyber-Physical Interface Matrix (CPIM) is proposed. The failure modes of cyber components and their impact on transmission line tripping behaviors are modeled and numerically analyzed as an example to illustrate the construction and utility of the CPIM. The methodology is then enhanced and implemented on an extended Roy Billinton Test System (RBTS) with its applicability for large systems illustrated. The results clearly show the impact of cyber-induced failures on system-wide reliability indices. The CPIM is the critical idea in the proposed methodology. It decouples the analysis of the cyber part from the physical part and provides the means of performing the overall analysis in a tractable fashion. The overall methodology proposed in this dissertation also provides a scalable option for reliability evaluation of large cyber-physical power systems. The efficiency of the overall methodology can be further improved with the use of non-sequential Monte Carlo techniques. However, the failure and repair processes in cyber-induced events are inherently sequential involving dependent failures, making it difficult to utilize non-sequential sampling methods as simply as when the components are independent. In this dissertation, the difficulties of using sampling when there are dependent failures are thoroughly explored. An approach is proposed to overcome the difficulties by generating a representative state space and its probabilities from which states can be sampled. The proposed approach not only preserves the sequential and dependent features of cyber-induced events but also improves the efficiency, which is very beneficial for reliability evaluation of large power systems in the presence of cyber-induced dependent failures

Probabilistic Reliability Analysis of Electric Power Systems with Smart Grid Technologies and Water Distribution Networks: Modeling, Assessment, and Comparison

With the rapid growth of population, the modern human society is becoming more and more dependent on the proper operation of critical infrastructures - the interconnected electrical power system, the drinking water distribution and supply system, the natural gas transmission and distribution system, and so forth. It has become an important issue to maintain reliable functions of these critical systems. As a result, comprehensive reliability evaluation is highly needed to quantify their reliability in an objective manner. Conventionally, deterministic criteria were used in reliability evaluations. However, it lacked the ability to model and quantify the stochastic nature of system behaviors such as component failures. In light of these facts, this thesis deploys probabilistic methodologies for conducting quantitative reliability modeling and assessment for nation’s critical infrastructures including electrical power networks incorporating smart grid technologies and water distribution networks. Power system operators are faced with the increasingly complicated operating conditions in bulk power systems. Yet due to the huge investment needed to build new power delivery facilities, cost-effective solutions such as new operational strategies are becoming more attractive and viable in recent years. Optimal transmission switching (OTS) and dynamic thermal rating (DTR) are two such technologies which offer a potential solution to improving the power system reliability by more fully utilizing the existing power delivery assets. In this thesis, these two technologies are first discussed, which are then incorporated into the power system reliability evaluation procedure. Case studies are conducted on modified RTS-79 and RTS-96 systems using MATLAB and IBM CPLEX. The obtained simulation results have shown that with the enforcement of either OTS or DTR technology, the overall system reliability can be improved, and system reliability can be further improved if both technologies are enforced. The growing urban population has brought great stress to the aging drinking water distribution systems. It is becoming more challenging to maintain a reliable drinking water distribution system so as to meet the growing water demand. Thus, a comprehensive reliability evaluation of the aging water delivery infrastructure is of critical importance to enable informed decision-making in asset management of the potable water sector. This thesis also proposes a probabilistic reliability evaluation methodology for water distribution systems based on Monte Carlo simulation (MCS) that takes into account both mechanical failures and hydraulic failures. Additionally, a C++ based software tool is developed to implement the proposed method. Case studies based on two representative water distribution systems are performed to demonstrate the effectiveness of the proposed method. A comparison is made between the reliability analysis of electrical power systems and that of water distribution systems. As interconnected capacitated networks, both systems share similarities in certain aspects such as component modeling and adequacy constraints. However, the specific features of the target systems should also be taken into consideration in the reliability modeling and evaluation in order to obtain a more comprehensive and accurate estimation of the actual system reliability

Probabilistic Reliability Analysis of the Water-energy Nexus Using Monte Carlo Simulation

Nowadays, with the development of science and technologies, our modern society is more and more dependent on the reliable performance of the critical infrastructures. Both water systems and power systems are national critical infrastructure supporting our daily life and the development of economic growth. These two types of systems are highly interconnected and complex networks, which consist of various system elements. Similarly, the core function of water and power system is to deliver satisfactory quality water and power to consumers, and at the same time it should satisfy all the demands at all load points. The reliable performance of these critical infrastructure is becoming more and more important. Therefore, it is very urgent to develop a comprehensive reliability evaluation algorithm to quantify the reliability of these critical systems. When it comes to quantitatively assessing reliability of the facility infrastructure, there is a need to develop a comprehensive method to consider a comprehensive set of variables and uncertainties such as the random failures of mechanical components, the amount of water demands, the power supply reliability, maintenance scheduling, and so forth. The rapidly growing urban population is also a great challenge to the aging drinking water distribution networks. The water facilities are aging and in need of expensive repairs. Therefore, this thesis will aid in making informed decisions on infrastructure repair, maintenance, and staffing planning when the available budgets are limited. This thesis proposes a probabilistic reliability evaluation methodology for water distribution systems considering the impact of power supply reliability based on the sequential Monte Carlo simulation (MCS), which can guide cost-effective preventative measures before system failures. A previously developed C++ software tool is used to help perform the simulation. The probabilistic reliability assessment algorithm can be appropriately applied for both the electric power systems and water distribution system is due to the similar stochastic system nature and modeling manner of the system elements. First, the reliability characteristic of each system component in electric power system can be modeled by a two-state model (i.e., up state and down state). Then, the probability of failure for each component can be calculated and a chronological operating sequence can be further determined based on the sequential Monte Carlo Simulation. Likewise, the reliability models for the water distribution system components can be represented using this method. All these similarities result in the similar reliability assessment procedure. The commonly used deterministic criteria in industrial circles lacked the ability to model and quantify the stochastic nature of system behaviors such as the mechanical failure of system elements. Besides the uncertainties come from water distribution system itself, power supply may also affect the performance of the water distribution network and system reliability. Therefore, the two systems are interactive and physically connected. The purpose of this study is to develop a suitable algorithm to evaluate the water sector and power system as an integrated Water-Energy Nexus (WEN) system. This thesis proposes an integrated, probabilistic reliability evaluation method for the WEN model based on the sequential Monte Carlo Simulation. In the proposed evaluation procedure, both mechanical failures and hydraulic analysis are taken into consideration. Case studies are performed base on a representative water-energy nexus system to demonstrate the effectiveness of the proposed algorithm. The simulation results demonstrate that the proposed probabilistic methodology is appropriate to integrated quantitative reliability modeling and assessment of coupled critical infrastructures (i.e., electrical power networks and water distribution networks) by incorporating the emerging smart grid technologies such as electrical microgrids

Integration of renewable energy sources: reliability-constrained power system planning and operations using computational intelligence

Renewable sources of energy such as wind turbine generators and solar panels have attracted much attention because they are environmentally friendly, do not consume fossil fuels, and can enhance a nation’s energy security. As a result, recently more significant amounts of renewable energy are being integrated into conventional power grids. The research reported in this dissertation primarily investigates the reliability-constrained planning and operations of electric power systems including renewable sources of energy by accounting for uncertainty. The major sources of uncertainty in these systems include equipment failures and stochastic variations in time-dependent power sources. Different energy sources have different characteristics in terms of cost, power dispatchability, and environmental impact. For instance, the intermittency of some renewable energy sources may compromise the system reliability when they are integrated into the traditional power grids. Thus, multiple issues should be considered in grid interconnection, including system cost, reliability, and pollutant emissions. Furthermore, due to the high complexity and high nonlinearity of such non-traditional power systems with multiple energy sources, computational intelligence based optimization methods are used to resolve several important and challenging problems in their operations and planning. Meanwhile, probabilistic methods are used for reliability evaluation in these reliability-constrained planning and design. The major problems studied in the dissertation include reliability evaluation of power systems with time-dependent energy sources, multi-objective design of hybrid generation systems, risk and cost tradeoff in economic dispatch with wind power penetration, optimal placement of distributed generators and protective devices in power distribution systems, and reliability-based estimation of wind power capacity credit. These case studies have demonstrated the viability and effectiveness of computational intelligence based methods in dealing with a set of important problems in this research arena

On cost-effective reuse of components in the design of complex reconfigurable systems

Design strategies that benefit from the reuse of system components can reduce costs while maintaining or increasing dependability—we use the term dependability to tie together reliability and availability. D3H2 (aDaptive Dependable Design for systems with Homogeneous and Heterogeneous redundancies) is a methodology that supports the design of complex systems with a focus on reconfiguration and component reuse. D3H2 systematizes the identification of heterogeneous redundancies and optimizes the design of fault detection and reconfiguration mechanisms, by enabling the analysis of design alternatives with respect to dependability and cost. In this paper, we extend D3H2 for application to repairable systems. The method is extended with analysis capabilities allowing dependability assessment of complex reconfigurable systems. Analysed scenarios include time-dependencies between failure events and the corresponding reconfiguration actions. We demonstrate how D3H2 can support decisions about fault detection and reconfiguration that seek to improve dependability while reducing costs via application to a realistic railway case study

Analysis of significant factors on cable failure using the Cox proportional hazard model

This paper proposes the use of the Cox proportional hazard model (Cox PHM), a statistical model, for the analysis of early-failure data associated with power cables. The Cox PHM analyses simultaneously a set of covariates and identifies those which have significant effects on the cable failures. In order to demonstrate the appropriateness of the model, relevant historical failure data related to medium voltage (MV, rated at 10 kV) distribution cables and High Voltage (HV, 110 kV and 220 kV) transmission cables have been collected from a regional electricity company in China. Results prove that the model is more robust than the Weibull distribution, in that failure data does not have to be homogeneous. Results also demonstrate that the method can single out a case of poor manufacturing quality with a particular cable joint provider by using a statistical hypothesis test. The proposed approach can potentially help to resolve any legal dispute that may arise between a manufacturer and a network operator, in addition to providing guidance for improving future practice in cable procurement, design, installations and maintenance

Evaluation of software dependability

It has been said that the term software engineering is an aspiration not a description. We would like to be able to claim that we engineer software, in the same sense that we engineer an aero-engine, but most of us would agree that this is not currently an accurate description of our activities. My suspicion is that it never will be. From the point of view of this essay – i.e. dependability evaluation – a major difference between software and other engineering artefacts is that the former is pure design. Its unreliability is always the result of design faults, which in turn arise as a result of human intellectual failures. The unreliability of hardware systems, on the other hand, has tended until recently to be dominated by random physical failures of components – the consequences of the ‘perversity of nature’. Reliability theories have been developed over the years which have successfully allowed systems to be built to high reliability requirements, and the final system reliability to be evaluated accurately. Even for pure hardware systems, without software, however, the very success of these theories has more recently highlighted the importance of design faults in determining the overall reliability of the final product. The conventional hardware reliability theory does not address this problem at all. In the case of software, there is no physical source of failures, and so none of the reliability theory developed for hardware is relevant. We need new theories that will allow us to achieve required dependability levels, and to evaluate the actual dependability that has been achieved, when the sources of the faults that ultimately result in failure are human intellectual failures

Modelling interdependencies between the electricity and information infrastructures

The aim of this paper is to provide qualitative models characterizing interdependencies related failures of two critical infrastructures: the electricity infrastructure and the associated information infrastructure. The interdependencies of these two infrastructures are increasing due to a growing connection of the power grid networks to the global information infrastructure, as a consequence of market deregulation and opening. These interdependencies increase the risk of failures. We focus on cascading, escalating and common-cause failures, which correspond to the main causes of failures due to interdependencies. We address failures in the electricity infrastructure, in combination with accidental failures in the information infrastructure, then we show briefly how malicious attacks in the information infrastructure can be addressed