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Matti Lehtonen - One of the best experts on this subject based on the ideXlab platform.

  • comparison of different models for estimating the residential sector Customer interruption costs
    Electric Power Systems Research, 2015
    Co-Authors: Sinan Kufeoglu, Matti Lehtonen
    Abstract:

    Abstract Estimation of economic impacts of power interruptions in residential Customers segment is a challenging and tedious task. The literature presents different methods to come up with sound calculations for these Customer interruption costs. This paper makes use of a detailed Customer Survey study that was conducted in Finland and presents a comparison of five different models: WTA, WTP, direct worth approach, price elasticity approach and a new macroeconomic model. When doing the analysis a total of 1009 Customers are divided into three sub-categories regarding the distinct characteristics of power consumptions: households, vacation houses and farm house Customers.

  • interruption costs of service sector electricity Customers a hybrid approach
    International Journal of Electrical Power & Energy Systems, 2015
    Co-Authors: Sinan Kufeoglu, Matti Lehtonen
    Abstract:

    Abstract A power outage brings in economic losses for both the Customers and the utilities. Studying these unwanted events and making solid predictions about the outcomes of the interruptions has been an attractive area of interest for the researchers for the last couple of decades. By making use of a Customer Survey study conducted in Finland, this paper benefits from both the reported cost data collected from Customers and from the analytical data that are available and then presents a new hybrid approach to estimate the Customer interruption costs of service sector Customer segment. Making use of Value Added information of the Customers is a common practice for the cost normalization purposes. This paper verifies the approach by comparing the findings of the Customer Survey and the econometric model suggested here. This study is a unique source in terms of providing a reliable, easy to apply, and a straightforward model for calculating the economic impacts of power outages.

  • Customer interruption costs estimations for service sectors via Customer Survey method a case study
    International Review of Electrical Engineering-iree, 2013
    Co-Authors: Sinan Kufeoglu, Matti Lehtonen
    Abstract:

    The estimations of the economic impacts of the unwanted power interruptions have been a popular area of interest among the electric power society for the last three decades. In this paper the authors put forward estimations of Customer interruption costs for service sectors by the aid of a Customer Survey conducted in Finland. The Customer Survey method has been criticised and a necessity of a more sophisticated future work have been emphasised

Artemis Kloess - One of the best experts on this subject based on the ideXlab platform.

  • bayesian reliability analysis with evolving insufficient and subjective data sets
    Journal of Mechanical Design, 2009
    Co-Authors: Pingfeng Wang, Byeng D Youn, Artemis Kloess
    Abstract:

    A primary concern in product design is ensuring high system reliability amidst various uncertainties throughout a product life-cycle. To achieve high reliability, uncertainty data for complex product systems must be adequately collected, analyzed, and managed throughout the product life-cycle. However, despite years of research, system reliability assessment is still difficult, mainly due to the challenges of evolving, insufficient, and subjective data sets. Therefore, the objective of this research is to establish a new paradigm of reliability prediction that enables the use of evolving, insufficient, and subjective data sets (from expert knowledge, Customer Survey, system inspection & testing, and field data) over the entire product life-cycle. This research will integrate probability encoding methods to a Bayesian updating mechanism. It is referred to as Bayesian Information Toolkit (BIT). Likewise, Bayesian Reliability Toolkit (BRT) will be created by incorporating reliability analysis to the Bayesian updating mechanism. In this research, both BIT and BRT will be integrated to predict reliability even with evolving, insufficient, and subjective data sets. It is shown that the proposed Bayesian reliability analysis can predict the reliability of door closing performance in a vehicle body-door subsystem where the relevant data sets availability are limited, subjective, and evolving.

  • bayesian reliability analysis with evolving insufficient and subjective data sets
    Design Automation Conference, 2008
    Co-Authors: Pingfeng Wang, Byeng D Youn, Artemis Kloess
    Abstract:

    A primary concern in product design is ensuring high system reliability amidst various uncertainties throughout a product life-cycle. To achieve high reliability, uncertainty data for complex product systems must be adequately collected, analyzed, and managed throughout the product life-cycle. However, despite years of research, system reliability assessment is still difficult, mainly due to the challenges of evolving, insufficient, and subjective data sets. Therefore, the objective of this research is to establish a new paradigm of reliability prediction that enables the use of evolving, insufficient, and subjective data sets (from expert knowledge, Customer Survey, system inspection & testing, and field data) over the entire product life-cycle. This research will integrate probability encoding methods to a Bayesian updating mechanism. It is referred to as Bayesian Information Toolkit (BIT). Likewise, Bayesian Reliability Toolkit (BRT) will be created by incorporating reliability analysis to the Bayesian updating mechanism. In this research, both BIT and BRT will be integrated to predict reliability even with evolving, insufficient, and subjective data sets. It is shown that the proposed Bayesian reliability analysis can predict the reliability of door closing performance in a vehicle body-door subsystem where the relevant data sets availability are limited, subjective, and evolving.Copyright © 2008 by ASME and General Motors Corporation

J Aweya - One of the best experts on this subject based on the ideXlab platform.

  • a canadian Customer Survey to assess power system reliability worth
    IEEE Transactions on Power Systems, 1994
    Co-Authors: G Tollefson, R Billinton, G Wacker, E Chan, J Aweya
    Abstract:

    A common approach used in quantifying the worth or benefit of electric service reliability is to estimate the Customer costs (monetary losses) associated with power interruptions. Customer Surveys are often used to determine interruption costs. The IEEE Power Systems Research Group has conducted Surveys of Canadian electric utility Customers in the residential, commercial and industrial sectors. These Surveys were sponsored by the Natural Sciences and Engineering Research Council and seven participating utilities. This paper presents the overall results of these Surveys with emphasis on the cost results. >

Sinan Kufeoglu - One of the best experts on this subject based on the ideXlab platform.

  • comparison of different models for estimating the residential sector Customer interruption costs
    Electric Power Systems Research, 2015
    Co-Authors: Sinan Kufeoglu, Matti Lehtonen
    Abstract:

    Abstract Estimation of economic impacts of power interruptions in residential Customers segment is a challenging and tedious task. The literature presents different methods to come up with sound calculations for these Customer interruption costs. This paper makes use of a detailed Customer Survey study that was conducted in Finland and presents a comparison of five different models: WTA, WTP, direct worth approach, price elasticity approach and a new macroeconomic model. When doing the analysis a total of 1009 Customers are divided into three sub-categories regarding the distinct characteristics of power consumptions: households, vacation houses and farm house Customers.

  • interruption costs of service sector electricity Customers a hybrid approach
    International Journal of Electrical Power & Energy Systems, 2015
    Co-Authors: Sinan Kufeoglu, Matti Lehtonen
    Abstract:

    Abstract A power outage brings in economic losses for both the Customers and the utilities. Studying these unwanted events and making solid predictions about the outcomes of the interruptions has been an attractive area of interest for the researchers for the last couple of decades. By making use of a Customer Survey study conducted in Finland, this paper benefits from both the reported cost data collected from Customers and from the analytical data that are available and then presents a new hybrid approach to estimate the Customer interruption costs of service sector Customer segment. Making use of Value Added information of the Customers is a common practice for the cost normalization purposes. This paper verifies the approach by comparing the findings of the Customer Survey and the econometric model suggested here. This study is a unique source in terms of providing a reliable, easy to apply, and a straightforward model for calculating the economic impacts of power outages.

  • Customer interruption costs estimations for service sectors via Customer Survey method a case study
    International Review of Electrical Engineering-iree, 2013
    Co-Authors: Sinan Kufeoglu, Matti Lehtonen
    Abstract:

    The estimations of the economic impacts of the unwanted power interruptions have been a popular area of interest among the electric power society for the last three decades. In this paper the authors put forward estimations of Customer interruption costs for service sectors by the aid of a Customer Survey conducted in Finland. The Customer Survey method has been criticised and a necessity of a more sophisticated future work have been emphasised

Pingfeng Wang - One of the best experts on this subject based on the ideXlab platform.

  • bayesian reliability analysis with evolving insufficient and subjective data sets
    Journal of Mechanical Design, 2009
    Co-Authors: Pingfeng Wang, Byeng D Youn, Artemis Kloess
    Abstract:

    A primary concern in product design is ensuring high system reliability amidst various uncertainties throughout a product life-cycle. To achieve high reliability, uncertainty data for complex product systems must be adequately collected, analyzed, and managed throughout the product life-cycle. However, despite years of research, system reliability assessment is still difficult, mainly due to the challenges of evolving, insufficient, and subjective data sets. Therefore, the objective of this research is to establish a new paradigm of reliability prediction that enables the use of evolving, insufficient, and subjective data sets (from expert knowledge, Customer Survey, system inspection & testing, and field data) over the entire product life-cycle. This research will integrate probability encoding methods to a Bayesian updating mechanism. It is referred to as Bayesian Information Toolkit (BIT). Likewise, Bayesian Reliability Toolkit (BRT) will be created by incorporating reliability analysis to the Bayesian updating mechanism. In this research, both BIT and BRT will be integrated to predict reliability even with evolving, insufficient, and subjective data sets. It is shown that the proposed Bayesian reliability analysis can predict the reliability of door closing performance in a vehicle body-door subsystem where the relevant data sets availability are limited, subjective, and evolving.

  • bayesian reliability analysis with evolving insufficient and subjective data sets
    Design Automation Conference, 2008
    Co-Authors: Pingfeng Wang, Byeng D Youn, Artemis Kloess
    Abstract:

    A primary concern in product design is ensuring high system reliability amidst various uncertainties throughout a product life-cycle. To achieve high reliability, uncertainty data for complex product systems must be adequately collected, analyzed, and managed throughout the product life-cycle. However, despite years of research, system reliability assessment is still difficult, mainly due to the challenges of evolving, insufficient, and subjective data sets. Therefore, the objective of this research is to establish a new paradigm of reliability prediction that enables the use of evolving, insufficient, and subjective data sets (from expert knowledge, Customer Survey, system inspection & testing, and field data) over the entire product life-cycle. This research will integrate probability encoding methods to a Bayesian updating mechanism. It is referred to as Bayesian Information Toolkit (BIT). Likewise, Bayesian Reliability Toolkit (BRT) will be created by incorporating reliability analysis to the Bayesian updating mechanism. In this research, both BIT and BRT will be integrated to predict reliability even with evolving, insufficient, and subjective data sets. It is shown that the proposed Bayesian reliability analysis can predict the reliability of door closing performance in a vehicle body-door subsystem where the relevant data sets availability are limited, subjective, and evolving.Copyright © 2008 by ASME and General Motors Corporation

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