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Article
Publication date: 1 December 1999

K.L. Lo, W.P. Luan, M. Given, J.F. Macqueen, A.O. Ekwue and A.M. Chebbo

Voltage ranking attempts to rank busbar voltage deviations from their normally accepted security margins based on a set of performance indices (PI), without performing a full load…

364

Abstract

Voltage ranking attempts to rank busbar voltage deviations from their normally accepted security margins based on a set of performance indices (PI), without performing a full load flow. Existing methods suffer from either masking effects or long computation time. In this paper, an artificial neural network method is proposed for voltage ranking. Counterpropagation network (CPN) has been employed to overcome the problems listed above. A variety of input features are used with the aim of lowering the dimension of the proposed ANN to make it applicable for large power systems. The method is tested on two example systems, a five‐bus system and a 71‐bus system with very encouraging results.

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COMPEL - The international journal for computation and mathematics in electrical and electronic engineering, vol. 18 no. 4
Type: Research Article
ISSN: 0332-1649

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Article
Publication date: 1 June 2002

K.L. Lo, W.P. Luan, M. Given, M. Bradley and H.B. Wan

Automatic contingency selection aims to quickly predict the impact of a set of next contingencies on an electric power system without actually performing a full ac load flow…

291

Abstract

Automatic contingency selection aims to quickly predict the impact of a set of next contingencies on an electric power system without actually performing a full ac load flow. Artificial neural network methods have been employed to overcome the masking effects or slow execution associated with existing methods. However, the large number of input features for the ANN limits its applications to large power systems. In this paper, a novel feature selection method, named the Weak Nodes method, based on a heuristic approach is proposed for an ANN‐based automatic contingency selection for electric power system, especially for the voltage ranking problem. Pre‐contingency state variables of weak nodes in the power system are adopted as input features for the ANN. The method is tested on the 77 busbar NGC derived network by Counter‐propagation Method and it is proved that it reduces the input features for ANN dramatically without losing ranking accuracy.

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COMPEL - The international journal for computation and mathematics in electrical and electronic engineering, vol. 21 no. 2
Type: Research Article
ISSN: 0332-1649

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Article
Publication date: 9 March 2015

Binghai Zhou, Jiadi Yu, Jianyi Shao and Damien Trentesaux

The purpose of this paper is to develop a bottleneck-based opportunistic maintenance (OM) model for the series production systems with the integration of the imperfect effect into…

777

Abstract

Purpose

The purpose of this paper is to develop a bottleneck-based opportunistic maintenance (OM) model for the series production systems with the integration of the imperfect effect into maintenance activities.

Design/methodology/approach

On the analysis of availability and maintenance cost, preventive maintenance (PM) models subjected to imperfect maintenance for different equipment types are built. And then, a cost-saving function of OM is established to find out an optimal OM strategy, depending on whether the front-bottleneck machines adopt OM strategy or not. A numerical example is given to show how the proposed bottleneck-based OM model proceeded.

Findings

The simulation results indicate that the proposed model is better than the methods to maintain the machines separately and the policy to maintain all machines when bottleneck machine reaches its reliability threshold. Furthermore, the relationship between OM strategy and corresponding parameters is identified through sensitivity analysis.

Practical implications

In practical situations, the bottleneck machine always determines the throughput of the whole series production system. Whenever a PM activity is carried out on the bottleneck machine, there will be an opportunity to maintenance other machines. Under such circumstances, findings of this paper can be utilized for the determination of optimal OM policy with the objective of minimizing total maintenance cost of the system.

Originality/value

This paper presents a bottleneck-based OM optimization model with the integration of the imperfect effect as a new method to schedule maintenance activities for a series production system with buffers. Furthermore, to the best of the knowledge, this paper presents the first attempt to considering the bottleneck constraint on system capacity and diverse types of machines as a means to minimize the maintenance cost and ensure the system throughput.

Details

Journal of Quality in Maintenance Engineering, vol. 21 no. 1
Type: Research Article
ISSN: 1355-2511

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Article
Publication date: 8 March 2022

Ibrahim Mashal

Smart grid is an integration between traditional electricity grid and communication systems and networks. Providing reliable services and functions is a critical challenge for the…

381

Abstract

Purpose

Smart grid is an integration between traditional electricity grid and communication systems and networks. Providing reliable services and functions is a critical challenge for the success and diffusion of smart grids that needs to be addressed. The purpose of this study is to determine the critical criteria that affect smart grid reliability from the perspective of users and investigate the role big data plays in smart grid reliability.

Design/methodology/approach

This study presents a model to investigate and identify criteria that influence smart grid reliability from the perspective of users. The model consists of 12 sub-criteria covering big data management, communication system and system characteristics aspects. Multi-criteria decision-making approach is applied to analyze data and prioritize the criteria using the fuzzy analytic hierarchy process based on the triangular fuzzy numbers. Data was collected from 16 experts in the fields of smart grid and Internet of things.

Findings

The results show that the “Big Data Management” criterion has a significant impact on smart grid reliability followed by the “System Characteristics” criterion. The “Data Analytics” and the “Data Visualization” were ranked as the most influential sub-criteria on smart grid reliability. Moreover, sensitivity analysis has been applied to investigate the stability and robustness of results. The findings of this paper provide useful implications for academicians, engineers, policymakers and many other smart grid stakeholders.

Originality/value

The users are not expected to actively participate in smart grid and its services without understanding their perceptions on smart grid reliability. Very few works have studied smart grid reliability from the perspective of users. This study attempts to fill this considerable gap in literature by proposing a fuzzy model to prioritize smart grid reliability criteria.

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Article
Publication date: 28 August 2020

Ali Karevan, Kong Fah Tee and Mohammadreza Vasili

This study presents a reliability-based and sustainability-informed maintenance optimization model for telecommunications equipment. It considers several risk attributes…

316

Abstract

Purpose

This study presents a reliability-based and sustainability-informed maintenance optimization model for telecommunications equipment. It considers several risk attributes associated with sustainability dimensions (i.e. social, economic and environmental aspects).

Design/methodology/approach

Many companies have developed long-term strategies to promote higher resource utilization, which has led to a paradigm shift in the role of maintenance. In parallel, reliability has been recognized as a fundamental factor in characterizing the optimal blend of maintenance strategies for a given system. It is essential for accurate failure prediction, which contributes toward more efficient use of all resources.

Findings

The corresponding subattributes are identified based on expert opinions and then incorporated into the proposed model. Subsequently, using the multiobjective particle swarm optimization (MOPSO), the proposed sustainability risks together with the maintenance costs are optimized, and the proper blend of maintenance strategies is identified.

Originality/value

Effective management of all human and natural resources, which are particularly emphasized by the concept of sustainability, has attracted much attention in recent years. However, contributions that effectively apply this concept in maintenance problems are very few and very few studies have attempted to quantify sustainability.

Details

International Journal of Quality & Reliability Management, vol. 38 no. 4
Type: Research Article
ISSN: 0265-671X

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Article
Publication date: 23 September 2019

Agam Gugaliya and V.N.A. Naikan

When induction motors are considered, there is no specific cost model for net savings per year due to condition-based maintenance (CBM) covering various parameters such as…

250

Abstract

Purpose

When induction motors are considered, there is no specific cost model for net savings per year due to condition-based maintenance (CBM) covering various parameters such as downtime, energy, quality, etc. The purpose of this paper is to develop a cost model for the financial viability of the implementation of CBM for induction motors.

Design/methodology/approach

A literature review has been carried out to identify the existing failure modes of motor, available condition monitoring techniques, the usefulness of CBM and different maintenance models available. Then, a cost model considering all parameters has been proposed.

Findings

A cost model has been proposed for the maintenance of induction motors. Method for the economic evaluation of the model has also been suggested in the paper. The application of the model has been illustrated through a case study of a steel plant, which suggests that investment in the condition monitoring of induction motors increases the net profit of the organization.

Research limitations/implications

The proposed model is specifically designed for induction motors. All the motors under consideration are assumed to be of the same specifications, and fault in any motor is supposed to have the same effect on quality, cost, criticality, etc., of the operation and end product.

Practical implications

This paper will help the maintenance manager in decision making when maintenance action has to be carried out for a given motor under CBM for the better utilization of the equipment and resources. This paper also shows how to compute ROI on CBM investment.

Originality/value

The paper provides a cost model for the economic evaluation of implementing CBM for induction motors which will be useful to researchers and maintenance managers in effective decision making and maintenance planning. The methodology and the cost models are the original contribution of the authors.

Details

Journal of Quality in Maintenance Engineering, vol. 26 no. 2
Type: Research Article
ISSN: 1355-2511

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Article
Publication date: 3 July 2007

Javad Barabady and Uday Kumar

To define availability importance measures in order to calculate the criticality of each component or subsystem from the availability point of view and also to demonstrate the…

1313

Abstract

Purpose

To define availability importance measures in order to calculate the criticality of each component or subsystem from the availability point of view and also to demonstrate the application of such importance measures for achieving optimal resource allocation to arrive at the best possible availability.

Design/methodology/approach

In this study the availability importance measures of a component are defined as a partial derivative of the system availability with respect to the component availability, failure rate, and repair rate. Analyses of these measures for a crushing plant are performed and the results are presented. Furthermore, a methodology aimed at improving the availability of a system using the concept of importance measures is identified and demonstrated by use of a numerical example.

Findings

The availability importance measure of a component/subsystem is an index which shows how far an individual component contributes to the overall system availability. The research study indicates that the availability importance measures could be applied in developing a strategy for availability improvement. The subsystem/component with the largest value of importance measure has the greatest effect on the system availability.

Research limitations/implications

The result of availability improvement strategy is demonstrated using only a hypothetical example.

Practical implications

Using availability importance measures will help managers and engineers to identify weaknesses and indicate modifications which will improve the system availability.

Originality/value

This paper presents the concept of availability importance measure for a component/subsystem. It also introduces some availability importance measures based on failure rate, mean time between failures (MTBF), and repair rate/mean time to repair (MTTR) of a component /subsystem. The concept of importance measures is used to prioritise the components or subsystems for the availability improvement process.

Details

International Journal of Quality & Reliability Management, vol. 24 no. 6
Type: Research Article
ISSN: 0265-671X

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Article
Publication date: 14 March 2016

Shervin Shahvi, Enrico Orsi, Roberto Canziani, Enrico Larcan and Gianfranco Becciu

The purpose of this paper is to study the transformation of some macropollutants including hydrocarbons, surfactants and metals in Milan west sewer basin. The study is part of a

309

Abstract

Purpose

The purpose of this paper is to study the transformation of some macropollutants including hydrocarbons, surfactants and metals in Milan west sewer basin. The study is part of a wider research (named SWARMNET and proposed by Politecnico di Milano and Metropolitana Milanese S.p.A and has been classified as fundable by the Ministry of Education, University and Research of Italy), aiming at installing a monitoring system for measurement of accidental discharge of pollutants from industrial activities and real-time protection of the wastewater treatment plant (WWTP) by avoiding dangerous discharges entering the sewers. Good effluent and waste sludge quality allow safe agricultural reuse of both streams. Other objectives include food safety, lower treatment costs and reduction of pollution of soil, surface and groundwater.

Design/methodology/approach

The west basin of Milan sewer network, discharging to San Rocco WWTP was considered. Among 700 industries, 16 have been selected for their specific characteristics and/or high industrial pollution load. A quality model was coupled with a hydraulic model to evaluate the effect of pollutants transport in the network.

Findings

Heavy metals, surfactants and hydrocarbons have different behavior from biodegradable domestic sewage and can be modeled as conservative matter conveyed by advection only. Results show that the concentration values of these macropollutants at the inlet of the WWTP are below the Italian standard values with the exception of Cadmium and Mercury. These heavy metals should be considered in the planned sampling campaign.

Originality/value

This study will estimate environmental benefits and both methodology and monitoring techniques can be extended to other cities in Italy and Europe.

Details

Management of Environmental Quality: An International Journal, vol. 27 no. 2
Type: Research Article
ISSN: 1477-7835

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Article
Publication date: 8 October 2018

Anil Rana and Emosi V.M. Koroitamana

The purpose of this paper is to provide a framework for measuring the imprecise and subjective “effectiveness” of a major maintenance activity. Such a measure will not only bring…

407

Abstract

Purpose

The purpose of this paper is to provide a framework for measuring the imprecise and subjective “effectiveness” of a major maintenance activity. Such a measure will not only bring objectivity in gauging the effectiveness of maintenance task carried out by the workforce without any intervention from an expert but also help in measuring the slow degradation of the performance of the concerned major equipment/system.

Design/methodology/approach

The paper follows a three-step approach. First, identify a set of parameters considered important for estimating the maintenance activity effectiveness. Second, generate a set of data using expert opinions on a fuzzy performance measure of maintenance activity effectiveness (output). Also, find an aggregated estimate of the effectiveness by analysing the consensus among experts. This requires using a part of the “fuzzy multiple attribute decision making” process. Finally, train a neuro-fuzzy inference system based on input parameters and generated output data.

Findings

The paper analysed major maintenance activity carried out on diesel engines of a power plant company. Expert opinions were used in selection of key parameters and generation of output (effectiveness measure). The result of a trained adaptive neuro-fuzzy inference system (ANFIS) matched acceptably well with that aggregated through the expert opinions.

Research limitations/implications

In view of unavailability of data, the method relies on training a neuro-fuzzy system on data generated through expert opinion. The data as such are vague and imprecise leading to lack of consensus between experts. This can lead to some amount of error in the output generated through ANFIS.

Originality/value

The originality of the paper lies in presentation of a method to estimate the effectiveness of a maintenance activity.

Details

Journal of Quality in Maintenance Engineering, vol. 24 no. 4
Type: Research Article
ISSN: 1355-2511

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Article
Publication date: 8 May 2009

Matjaž Dolinar, Miloš Pantoš and Drago Dolinar

The purpose of this paper is to present an improved approach to reactive power planning in electric power systems (EPS). It is based on minimization of a transmission network's…

702

Abstract

Purpose

The purpose of this paper is to present an improved approach to reactive power planning in electric power systems (EPS). It is based on minimization of a transmission network's active power losses. Several operating conditions have to be fulfilled to ensure stable operation of an EPS with minimal power losses. Some new limitations such as voltage instability detection and generator capability curve limit have been added to the existing method in order to improve the reliability of reactive power planning. The proposed method was tested on a model of the Slovenian power system. The results show the achievement of significant reduction in active power losses, while maintaining adequate EPS security.

Design/methodology/approach

Optimal voltage profile has to be found in order to determine minimal possible active power losses of EPS. The objective function, used to find the optimal voltage profile, has integer and floating point variables and is non‐differentiable with several local minima. Additionally, to ensure secure operation of EPS, several equality and inequality boundaries and limitations have to be applied. Differential evolution (DE) was used to solve the optimization problem.

Findings

Corresponding reactive power planning can significantly reduce active power losses in EPS. However, such planning can affect the security of EPS, therefore, several additional constrains have to be considered. The presented constrains considerably improve the operational security of EPS.

Research limitations/implications

DE was used to solve the minimization problem. Although this method has proven to be fast and reliable, it is theoretically possible that the obtained solution is not global minimum.

Originality/value

Novel approach to voltage security constrained reactive power planning with additional nonlinear constrains, such as generator capability curves and voltage instability detection.

Details

COMPEL - The international journal for computation and mathematics in electrical and electronic engineering, vol. 28 no. 3
Type: Research Article
ISSN: 0332-1649

Keywords

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