Probabilistic technique for sizing FACTS devices for steady-state voltage profile enhancement

A novel and simple stochastic-based approach to determine the optimal sizing of multiple flexible AC transmission systems (FACTS) devices in a power system for steady-state voltage profile enhancement is presented. In this context, investigations have been conducted on a published test system taking into consideration the uncertainty of the system load and generator scheduling. Two FACTS schemes are considered, namely a thyristor controlled series capacitor (TCSC) and two static synchronous compensators (STATCOMs) and a unified power flow controller (UPFC) and a STATCOM. The TCSC and UPFC are employed in the system to adjust the natural power sharing of two different parallel transmission lines and therefore enable the maximum transmission capacity to be utilised. Risk indices to estimate the likelihood that the voltage magnitude at a certain bus falls below a desired value is also presented.     

Decision tree-based fault zone identification and fault classification in flexible AC transmissions-based transmission line

Transmission line distance relaying for flexible AC transmission lines (FACTS) including thyristor controlled series compensator (TCSC), STATCOM, SVC and unified power flow controller (UPFC) has been a very challenging task. A new approach for fault zone identification and fault classification for TCSC and UPFC line using decision tree (DT) is presented. One cycle post fault current and voltage samples from the fault inception are used as input vectors against target output dasia1psila for fault after TCSC/UPFC and dasia0psila for fault before TCSC/UPFC for fault zone identification. Similarly, the DT-based classification algorithm takes one cycle data from fault inception of three phase currents along with zero-sequence current and voltage, and constructs the optimal DT for classifying all ten types of shunt faults in the transmission line fault process. The algorithm is tested on simulated fault data with wide variations in operating parameters of the power system network including noisy environment. The results indicate that the proposed method can reliably identify the fault zone and classify faults in the FACTs-based transmission line in large power network.     

Reliability assessment of embedded digital system using multi-state function

This work describes a combinatorial model for estimating the reliability of the embedded digital system by means of multi-state function. This model includes a coverage model for fault-handling techniques implemented in digital systems. The fault-handling techniques make it difficult for many types of components in digital system to be treated as binary state, good or bad. The multi-state function provides a complete analysis of multi-state systems as which the digital systems can be regarded. Through adaptation of software operational profile flow to multi-state function, the HW/SW interaction is also considered for estimation of the reliability of digital system. Using this model, we evaluate the reliability of one board controller in a digital system, Interposing Logic System (ILS), which is installed in YGN nuclear power units 3 and 4. Since the proposed model is a generalized combinatorial model, the simplification of this model becomes the conventional model that treats the system as binary state. This modeling method is particularly attractive for embedded systems in which small sized application software is implemented since it will require very laborious work for this method to be applied to systems with large software.     

Differential equation-based fault locator for unified power flow controller-based transmission line using synchronised phasor measurements

The fault location algorithm based on a differential equation-based approach for a transmission line employing a unified power flow controller (UPFC) using synchronised phasor measurements is presented. First, a detailed model of the UPFC and its control is proposed and then, it is integrated into the transmission system for accurately simulating fault transients. The method includes the identification of fault section for a transmission line with a UPFC using a wavelet-fuzzy discriminator. Features are extracted using a wavelet transform and the normalised features are fed to the fuzzy logic systems for the identification of fault section. After the identification of the fault section, the control shifts to the differential equation-based fault locator that estimates the fault location in terms of the line inductance up to the fault point from the relaying end. Shunt faults are simulated with wide variations in operating conditions and a pre-fault parameter setting. The instantaneous fault current and voltage samples at the sending and receiving ends are fed to the designed algorithm sample by sample, which results in the fault location in terms of the line inductance. The proposed method is tested for different fault situations with wide variations in operating conditions in the presence of a UPFC.     

Economical design of reliable systems—some practical situations

Designing reliability into a system is one of the most important objectives of a system disigner. A system normally consists of several components, and the possibility that each component is available in the market in different categories with various specifications, reliability values and costs requires serious consideration while designing a system. Therefore, the difficulty which the system designer always comes across is how to choose an appropriate combination of components so that the achieved system reliability is maximum for the given cost. The present paper aims at investigating an efficient approach which generates directly those combinations of components which guarantee the maximum system reliability at a specified cost. Also, if the system designer wants to increase his resources, the proposed method provides a way of selecting a configuration with higher reliability if it exists. Based on the developed algorithm an interactive package has been prepared, which also permits the user to exercise options such as minimum acceptable reliability value, maximum affordable cost, duty ratios for components which work for a period less than the mission time, and criticality values for components which are not fully critical. A complete example illustrating all these features is also discussed.     

Operational reliability assessment of power systems considering condition-dependent failure rate

Failure rate of a system component is usually assumed to be constant in conventional reliability evaluation of power systems. It has been realised from the real-time operation that a component will experience more failures during heavy loading condition than those during light loading condition, which means that the failure rate of a component in real-time operation is not constant and varies with loading condition. In order to evaluate system operational reliability related to load condition, the factors affected condition-dependent failure rate (CDFR) are investigated and a basic CDFR model is proposed in this study. In predictive operational reliability study, equipment loading condition for a given load period is determined using AC power flow based on the corresponding load level with considering load uncertainty. A four-state model has been proposed to represent a system component. The equations for determining the probability of each state for the four-state model have been derived. A technique based on these equations and models has been developed to evaluate operational and annual reliability indices of components, load points and system. The IEEE-RTS has been analysed to illustrate the proposed models and technique.     

Maintenance schedule optimisation for a railway power supply system

High reliability is the crucial requirement in railway operation and a power supply system is one of the key components of electrified railways. The cost-effectiveness of the maintenance works is also the concern of the railway operators while the time window on trackside maintenance is often limited. Maintenance scheduling is thus essential to uphold reliability and to reduce operation cost. It is however difficult to formulate the optimal schedule to meet both reliability and maintenance cost for a railway power supply system as a whole because of its functional complexity and demanding operation conditions. Maintenance scheduling models to achieve reliability and maintenance cost are proposed in this study. Optimisation algorithms are then developed to attain the solutions of the model. The applicability of the models and efficiency of the solution algorithms are demonstrated in an example. The proposed methods are vitally important for the railway engineers and operators to assure the service quality in the increasing demands of the modern electrified railways.     

Reliability evaluations of railway power supplies by fault-tree analysis

High reliability of railway power systems is one of the essential criteria to ensure quality and cost-effectiveness of railway services. Evaluation of reliability at system level is essential for not only scheduling maintenance activities, but also identifying reliability-critical components. Various methods to compute reliability on individual components or regularly structured systems have been developed and proven to be effective. However, they are not adequate for evaluating complicated systems with numerous interconnected components, such as railway power systems, and locating the reliability critical components. Fault tree analysis (FTA) integrates the reliability of individual components into the overall system reliability through quantitative evaluation and identifies the critical components by minimum cut sets and sensitivity analysis. The paper presents the reliability evaluation of railway power systems by FTA and investigates the impact of maintenance activities on overall reliability. The applicability of the proposed methods is illustrated by case studies in AC railways     

Selective maintenance optimisation for series-parallel systems alternating missions and scheduled breaks with stochastic durations

This paper deals with the selective maintenance problem for a multi-component system performing consecutive missions separated by scheduled breaks. To increase the probability of successfully completing its next mission, the system components are maintained during the break. A list of potential imperfect maintenance actions on each component, ranging from minimal repair to replacement is available. The general hybrid hazard rate approach is used to model the reliability improvement of the system components. Durations of the maintenance actions, the mission and the breaks are stochastic with known probability distributions. The resulting optimisation problem is modelled as a non-linear stochastic programme. Its objective is to determine a cost-optimal subset of maintenance actions to be performed on the components given the limited stochastic duration of the break and the minimum system reliability level required to complete the next mission. The fundamental concepts and relevant parameters of this decision-making problem are developed and discussed. Numerical experiments are provided to demonstrate the added value of solving this selective maintenance problem as a stochastic optimisation programme.     

Representation of line optimisation control in unified power-flow controller model for power-flow analysis

Drawing on constrained optimisation based on Newton's method, a systematic and general method for determining optimal reference inputs to unified power-flow controllers (UPFCs) in steady-state operation is developed. The method is directly applicable to UPFCs operation with a high-level line optimisation control. Through the selection of weighting coefficients used in the objective function which is formed from the weighted difference between the specified reference inputs and their optimal values, the method represents the priority assigned for any UPFC control function in constraint or limit resolution. Another key advance reported is that of combining the sparse Newton's method with the continuation technique for solving the nonlinear constrained optimisation. The composite algorithm extends substantially the region of convergence achieved with the conventional Newton's method. The method uses a general and flexible UPFC model based on nodal voltages developed. Any UPFC control functions together with operating limits can be included in the model. The steady-state formulation developed together with its software implementation is tested with a practical long-distance transmission interconnection where a UPFC is required.     

Application of the fault tree analysis for assessment of power system reliability

A new method for power system reliability analysis using the fault tree analysis approach is developed. The method is based on fault trees generated for each load point of the power system. The fault trees are related to disruption of energy delivery from generators to the specific load points. Quantitative evaluation of the fault trees, which represents a standpoint for assessment of reliability of power delivery, enables identification of the most important elements in the power system. The algorithm of the computer code, which facilitates the application of the method, has been applied to the IEEE test system. The power system reliability was assessed and the main contributors to power system reliability have been identified, both qualitatively and quantitatively.     

Strategy and tool development for nuclear power plant design synthesis with measurement of reliability and simplicity

In this work, the conceptual design supporting tools for nuclear power plants have been developed. These tools are made for system synthesis, complexity measure and reliability analysis.This design synthesis program combined with the reliability analysis program accomplishes the system synthesis. This design strategy can reduce mistakes, effort and time. This design tool, based on Prolog language, is applied to the auxiliary feedwater system. A logic based fault tree analysis program (LOFT) is also developed using Prolog language. As LOFT performs symbolic computation during the fault tree analysis, linking with knowledge-base systems is very easy and the partial usage of the program is possible. The importance measure of components obtained from the system reliability analysis and the complexity measure of the system give very important information to the system designer.     

跨声速风洞测力模型主动减振系统的试验研究

跨声速风洞测力试验模型通常采取尾部支撑方式，构成的模型系统刚度较低。试验过程中，受气流脉动力的作用，模型在进入大攻角试验状态时，极易产生剧烈的低频振动，严重影响风洞测力试验的正常进行。针对跨声速风洞测力试验模型系统及其动力学特性，采用主动控制技术来实现风洞模型的振动抑制。建立了一套计算机实时主动减振系统；利用白行研制的、具有激振与减振双重功能的作动器来实施控制，作动器直接装载于模型的内结构空腔，不改变或破坏试验模型的外形结构；基于学习控制策略，提出了相应的控制律设计方法，并给出了一种简单、实用的控制算法；以内含实际支撑装置的风洞测力试验模型系统为对象，通过大量的地面试验评估了整个减振系统的性能。试验结果验证了该主动减振系统的可行性与有效性。     

A Software Tool for Reliability Estimation

Over the years, several tools have been developed to estimate the reliability of hardware and software components. Typically, such tools are either for hardware or software. This paper presents the Software Tool for Reliability Estimation (STORE), which can be used for systems containing hardware and/or software components. For software components, exponential, Weibull, gamma, power, geometric, and inverse-linear models were implemented. Goodness of fit statistics are provided for each model. The user can select the most appropriate model for a given system configuration and failure data. The STORE program can analyze series, parallel, and complex systems. Tieset and cutset algorithm is utilized to determine the reliability of a complex system. The paper presents several examples to demonstrate the software tool.     

Transmission cost allocation based on use of reliability margin under contingency conditions

A reliability-based method for allocating the cost of transmission networks is presented. The cost of a transmission line is divided into two components. The first component corresponds to a part of the line capacity, which is used under normal conditions. The second component corresponds to a portion of the line capacity, which is only used under contingency conditions. The latter is the part that market agents use to calculate the reliability benefit charges of the line. In the proposed method, a probabilistic index is defined based on single-contingency analysis, which measures the reliability margin of each line for each transaction. Furthermore, the cost components associated with capacity use and reliability benefit charges are determined based on the actual reliability margin of lines. This method can be used to provide an equitable means for allocating the cost of transmission network among users of a bilateral market model. The proposed method is illustrated in a small power system as well as the 24-bus IEEE-RTS, and its conceptual and computational feasibility are demonstrated.     

Optimal design of multi-state weighted k-out-of-n systems based on component design

This paper presents a study on design optimization of multi-state weighted k-out-of-n systems. The studied system reliability model is more general than the traditional k-out-of-n system model. The system and its components are capable of assuming a whole range of performance levels, varying from perfect functioning to complete failure. A utility value corresponding to each state is used to indicate the corresponding performance level. A widely studied reliability optimization problem is the “component selection problem”, which involves selection of components with known reliability and cost characteristics. Less adequately addressed has been the problem of determining system cost and utility based on the relationships between component reliability, cost and utility. This paper addresses this topic. All the optimization problems dealt with in this paper can be categorized as either minimizing the expected total system cost subject to system reliability requirements, or maximizing system reliability subject to total system cost limitation. The resulting optimization problems are too complicated to be solved by traditional optimization approaches; therefore, genetic algorithm (GA) is used to solve them. Our results show that GA is a powerful tool for solving these kinds of problems.     

A model-driven multivariable controller for vapor compression refrigeration systems

A model-driven controller for vapor compression refrigeration systems is presented herein. Mathematical sub-models were developed for each of the system components: heat exchangers (condenser and evaporator), variable-speed compressor and variable-orifice electric expansion device. The overall system simulation model was used to design a MIMO controller based on the linear-quadratic Gaussian method using a state observer of the Kalman filter type. A purpose-built testing apparatus comprised of a variable-speed compressor and a pulse-width modulated expansion valve was used to collect data for the system identification and model validation exercises. It was found that the model reproduces the experimental trends of the working pressures in conditions far from the operation point (±30%) with a maximum deviation of ±5%. Additional experiments were also performed to verify the ability of the controller of tracking reference changes and rejecting thermal load disturbances as high as 15%.     

Reliability Analysis for Multistate Systems with Multistate Components

An important problem in reliability theory is to determine the reliability of a complex system given the reliabilities of its components. In real life, the system and its components can be found in a range of states varying from perfect functioning through various levels of performance degradation to complete failure. This paper presents some models and their applications, in terms of reliability analyses, to situations where the system can have a whole range of states and all its components can also have a wide range of multiple states. Properties of the system structure function and computation and approximation of system state probabilities and system reliability measures are given.     

Analysis of correlated multivariate degradation data in accelerated reliability growth

Modern engineering systems have become increasingly complex and at the same time are expected to be developed faster. To shorten the product development time, organizations commonly conduct accelerated testing on a small number of units to help identify failure modes and assess reliability. Many times design changes are made to mitigate or reduce the likelihood of such failure modes. Since failure-time data are often scarce in reliability growth programs, existing statistical approaches used for predicting the reliability of a system about to enter the field are faced with significant challenges. In this work, a statistical model is proposed to utilize degradation data for system reliability prediction in an accelerated reliability growth program. The model allows the components in the system to have multiple failure modes, each associated with a monotone stochastic degradation process. To take into account unit-to-unit variation, the random effects of degradation parameters are explicitly modeled. Moreover, a mean-degradation-stress relationship is introduced to quantify the effects of different accelerating variables on the degradation processes, and a copula function is utilized to model the dependency among different degradation processes. Both a maximum likelihood (ML) procedure and a Bayesian alternative are developed for parameter estimation in a two-stage process. A numerical study illustrates the use of the proposed model and identifies the cases where the Bayesian method is preferred and where it is better to use the ML alternative.