A.M. Leite da Silva

Probabilistic evaluation of the effect of maintenance on reliability. An application [to power systems]

The purpose of maintenance is to extend equipment lifetime, or at least the mean time to the next failure. While too little maintenance may have very costly consequences, maintenance, too, incurs expenditures and it may not be economical to perform it too frequently. Therefore, the two costs must be balanced. In the past, attempts to approximate this balance have often been based on trial and error. In this paper, a probabilistic model is proposed for the purpose, and a computer program based on this model is described. The model provides a quantitative connection between reliability and maintenance, a link missing in the heuristic approaches. The component ageing process is modelled, and the mean and distribution of the remaining life to failure are predicted for any stage of ageing. The method is applied to a practical example.

Pseudo-chronological simulation for composite reliability analysis with time varying loads

This paper presents a new methodology to evaluate loss of load indices, with particular emphasis on LOLC (loss of load cost) assessment, for composite generation and transmission systems considering time varying loads for different areas or buses. The proposed approach, named pseudo-chronological simulation, retains the computational efficiency of nonsequential Monte Carlo simulation and the ability to model chronological load curves in sequential simulation. It considers the actual blocks of unsupplied energy per consumer class, per bus, and the respective duration, to accurately characterize the interruption process. Case studies on the IEEE-MRTS (Modified Reliability Test System) and the BSS (Brazilian South-Southeastern System) are presented and discussed.

Probabilistic Load Flow Considering Dependence Between Input Nodal Powers

This paper presents a new method for obtaining a probabilistic load flow solution when dependence between the input nodal powers is considered. Such dependence is modeled in order to account for the criteria used to balance the system active power and also the correlation between loads due-mainly to environmental and social factors. The proposed technique is applied to a typical power system and the results discussed.

Evaluation of reliability worth in composite systems based on pseudo-sequential Monte Carlo simulation

This work describes a new methodology for calculating total system interruption costs in composite generation and transmission systems. The proposed approach, called pseudo-sequential simulation, is based on the nonsequential Monte Carlo sampling of system states and on the chronological simulation of only the sub-sequences associated with failed states. Case studies with the IEEE Modified Reliability Test System (MRTS) and a 415-bus system derived from the Brazilian Southeastern region are presented and discussed. >

A conditional probability approach to the calculation of frequency and duration indices in composite reliability evaluation

The authors describe a new methodology for frequency and duration (F&D) assessment in composite generation and transmission reliability evaluation. The proposed approach uses the concept of conditional probability to characterize the contribution of each component to the frequency indices, and allows the calculation of F&D indices at both system and bus level. The algorithm is easy to implement, and requires the same computational effort as the estimation of the system loss of load probability (LOLP) and the system expected power not supplied (EPNS) indices. Case studies with utility-derived systems are presented and discussed. >

Discrete Convolution in Power System Reliability

This paper describes a general method for convolving discrete distributions using Fast Fourier Transforms. It can be used in evaluating reliability of any system involving discrete or discretised convolution. It has been used in power system studies to deduce capacity-outage probability tables and to solve probabilistic load flows. These studies have shown it to be much less time-consuming and more efficient than the conventional direct methods. The method is used in the paper to evaluate the loss of load probability of a generating system in order to demonstrate the methods application and inherent merits.

An Efficient Dynamic State Estimation Algorithm including Bad Data Processing

This paper presents a comparison between the performance of dynamic and tracking estimators, in power systems operating under quasi-static conditions, concerning their characteristics of forecasting and filtering. From this comparison a new dynamic estimator which incorporates the main advantages of the previous estimators is proposed. Also, a new scheme of detection and identification of bad data properly built for dynamic algorithms is presented. Numerical results showing the performance of the new algorithm under different operational conditions are discussed.

Composite Reliability Assessment Based on Monte Carlo Simulation and Artificial Neural Networks

This paper presents a new methodology for reliability evaluation of composite generation and transmission systems, based on nonsequential Monte Carlo simulation (MCS) and artificial neural network (ANN) concepts. ANN techniques are used to classify the operating states during the Monte Carlo sampling. A polynomial network, named group method data handling (GMDH), is used, and the states analyzed during the beginning of the simulation process are adequately selected as input data for training and test sets. Based on this procedure, a great number of success states are classified by a simple polynomial function, given by the ANN model, providing significant reductions in the computational cost. Moreover, all types of composite reliability indices (i.e., loss of load probability, frequency, duration, and energy/power not supplied) can be assessed not only for the overall system but also for areas and buses. The proposed methodology is applied to the IEEE Reliability Test System (IEEE-RTS), to the IEEE-RTS 96, and to a configuration of the Brazilian South-Southeastern System.

Static and dynamic aspects in bulk power system reliability evaluations

This work extends the concepts and evaluation techniques for composite generation and transmission reliability assessment, in order to provide performance measures considering both static (adequacy) and dynamic (security) consequences of the disturbances, which may occur in electric power systems. The assessment of dynamic aspects requires the modeling of protection systems, control actions and restoration processes. The cascading effects associated with dynamic problems are usually nonMarkovian in nature, and they are better modeled through a Monte Carlo chronological or sequential simulation. For the transient stability analysis, a method combining time simulation and transient energy function is used. The IEEE-RTS (Reliability Test System) is first extended to be analyzed bearing in mind both aspects, static and dynamic, and then used to test the proposed methodology. The usual reliability indices, e.g. LOLP, are separately calculated for measuring adequacy and security. They are also decomposed to capture the contributions of various types of failures considered; phase faults, etc.

Bibliography on composite system reliability

A comprehensive bibliography on the subject of composite system reliability and closely related topics is presented. It is believed to fill a gap which exists in the literature, since approximately 2/3 of the items registered here have not appeared in previously published bibliographies on power system reliability. An author index for the listed references is included. >