Integrating risk analysis and multi-criteria decision support under uncertainty in electricity distribution system asset management

Catrinu, Maria Daniela; Nordgård, Dag Eirik

doi:10.1016/j.ress.2010.12.028

Cited by 62 publications

(22 citation statements)

References 9 publications

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“…The analysis of other aspects of risk, such as the risk to personal safety, the risk of environmental damage or the risk of a negative public response are usually "decoupled" from quantitative risk analysis. So for Catrinu and Nordgård (2011), it is necessary to improve the current practice of asset management, by making the best use of knowledge and data available from experts and adopting new methods of risk analysis and decision support, and moreover, the best ways to document decisions.…”

Section: Power Electricity Systemsmentioning

confidence: 99%

Multidimensional Risk Analysis

Almeida

Cavalcante

Alencar

et al. 2015

International Series in Operations Research &Amp; Management Science

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Accidents involve critical consequences that require an appropriate and efficient form of risk management. A multidimensional risk analysis allows a broader view. MCDM/A approaches enable more consistent decision-making, taking into account the DM's rationality (compensatory or non-compensatory), DM's behavior regarding risk (prone, neutral or averse) and the uncertainties inherent in the risk context. This chapter presents numerical applications illustrating the use of multicriteria models in two different contexts: a natural gas pipeline and an underground electricity distribution system. Two different MCDM/A approaches are considered: MAUT (Multiattribute Utility Theory) and the ELECTRE TRI outranking method. In the numerical applications, MCDM/A approach steps for building decision models are presented: identifying hazard scenarios, estimating the set of payoffs, eliciting the MAU function (Multi-attribute Utility function), computing the probability function of consequences and estimating multidimensional risk. Loss functions are introduced in the models to calculate the probability distribution functions over the multiple criteria such as impact on humans, and environmental and financial losses. Therefore, Decision Theory concepts are applied to estimate risk in industrial plants and modes of transportation. Finally, other decision problems related to multidimensional risk analysis, using MCDM/A, are considered in different contexts, such as: power electricity systems, natural hazards, risk analysis on counter-terrorism, nuclear power plant. Justifying the Use of the Multidimensional RiskThe perceived level of risk is directly linked to the perceived intensity of consequences to people and society as well as to issues related to the level of probability. These consequences are multidimensional and are associated to the objectives, represented by criteria and can be approached with an MCDM/A or a multiobjective method (see Chap. 2). Many studies show that using a single dimension of risk may not be realistic (Morgan et al.

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Section: Power Electricity Systemsmentioning

confidence: 99%

Multidimensional Risk Analysis

Almeida

Cavalcante

Alencar

et al. 2015

International Series in Operations Research &Amp; Management Science

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“…Therefore, researchers tempt to find appropriate methods for optimal placement of DG to improve system characteristics such as reliability increasing and power losses reduction [11,15]. Most of the studies on DGs sizing and siting have focused on finding the optimized placement based on minimizing the system power losses [19]. Other system parameters such as voltage profile, total harmonic distortion (THD) and reliability have been studied, too [20,21].…”

Section: Introductionmentioning

confidence: 99%

Optimized Placement of Connecting the Distributed Generationswork Stand Alone to Improve the Distribution Systems Reliability

Hashemi‐Dezaki¹,

Agheli²,

Vahidi³

et al. 2013

Journal of Electrical Engineering

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The use of distributed generations (DGs) in distribution systems has been common in recent years. Some DGs work stand alone and it is possible to improve the system reliability by connecting these DGs to system. The joint point of DGs is an important parameter in the system designing. In this paper, a novel methodology is proposed to find the optimum solution in order to make a proper decision about DGs connection. In the proposed method, a novel objective function is introduced which includes the cost of connector lines between DGs and network and the cost of energy not supplied (CENS) savings. Furthermore, an analytical approach is used to calculate the CENS decrement. To solve the introduced nonlinear optimization programming, the genetic algorithm (GA) is used. The proposed method is applied to a realistic 183-bus system of Tehran Regional Electrical Company (TREC). The results illustrate the effectiveness of the method to improve the system reliability by connecting the DGs work stand alone in proper placements.K e y w o r d s: stand alone distributed generations, distribution systems, genetic algorithm (GA), system reliability, energy not-supplied (ENS)

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“…Kriege and Vlok, 2015), data management (e.g. Braaksma et al, 2011), risk management (Catrinu and Nordgård, 2011), information communication technologies (e.g. Al-Turki, 2011), the environment (Niekamp et al, 2015) and customer relationships (Jooste and Vlok, 2015).…”

Section: Alcm Is a Multidisciplinary Practicementioning

confidence: 99%

“…Therefore, the authors propose to use MCDA as a solution to Identified Problem #2. In addition, MCDA offers a structured and transparent decision-making process (Catrinu and Nordgård, 2011). This allows the decision makers to discuss preferred alternatives resulting from the analysis.…”

Section: Initial Solutionsmentioning

confidence: 99%

Manoeuvring physical assets into the future

Ruitenburg¹

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Integrating risk analysis and multi-criteria decision support under uncertainty in electricity distribution system asset management

Cited by 62 publications

References 9 publications

Multidimensional Risk Analysis

Multidimensional Risk Analysis

Optimized Placement of Connecting the Distributed Generationswork Stand Alone to Improve the Distribution Systems Reliability

Manoeuvring physical assets into the future

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