Multi Criteria Decision Model for Risk Assessment of Transmission and Distribution Assets: A Hybrid Approach Using Analytical Hierarchy Process and Weighted Sum Method

Multi Criteria Decision Model for Risk Assessment of Transmission and Distribution Assets: A Hybrid Approach Using Analytical Hierarchy Process and Weighted Sum Method

Bijoy Chattopadhyay (Nevada Energy, Las Vegas, USA) and Angelica Rodriguez (Nevada Energy, Las Vegas, USA)
Copyright: © 2018 |Pages: 19
DOI: 10.4018/IJBAN.2018070103

Abstract

This article describes how in order to prioritize the risks for a large number of assets, various criteria are used for ranking the asset risk. Since the criteria used for developing the risk rank is a mixture of quantitative and qualitative, a method was required to handle both the quantitative and qualitative criteria with varying scales that can be used for the electrical industry's assets. This article proposes a hybrid multi-criteria decision model (MCDM) that combines both weighted sum model (WSM) and analytical hierarchy process (AHP). The hybrid model is then applied to the strategic asset management plan for the electric power industry for ranking the assets risk. In this application, a large number of criteria reflecting asset conditions with their numerical values are available for which WSM method worked quite efficiently. The AHP method was applied to the criteria where qualitative criteria were available. Both methods were then synthesized, and the proposed hybrid method was formulated which resulted in a computationally efficient outcome with robust mathematical framework. The results show that the proposed method exhibited optimal results for the electric industry's asset where qualitative criteria are for AHP method was limited to 3 to 5. In the case of WSM, a larger number of quantitative criteria could be accommodated although for the application only six criteria were utilized.
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Literature Review

Several studies have been conducted during the last decade that utilized MCDM for solving asset management and engineering decision problems. MCDM was applied in assessing decision options by many industries and ranking the decisions and scenarios (Wang, & Triantaphyllou, 2006; Shyjith, Ilangkumaran, & Kumanan, 2008; Dytczak, & Ginda, 2006; Campanella & Ribeiro 2011; Prida, Viveros, Crespo, & Martin, 2014; Santiago, Romo, Marcos, Borja-de la Rosa, 2015; Thakala, Devlin, Marsch, Baltussen, Boyse, Kalo, Longrenn, Mussen., Peacock, Watkins, Ijzerman, 2016). Wang et al. (2006) provided a few criteria to establish effectiveness of multi criteria decision analysis. Others utilized AHP as a MCDM model for ranking the decisions and scenarios by applying both qualitative and quantitative criteria (Prida et al., 2014). A few other researchers applied weighting method in MCDM for financial decision in allocating research funding, and selecting R&D projects (Pirdashti et al., 2009 & Santiago et al., 2015). The MCDM methodology has been extensively used in energy and sustainability industries (Cinelli et al., 2014; Wang et al., 2009; Handfield 2002; Dytczak & Ginda, 2006; Jaderi et al., 2012; Majumder, 2015). In the construction project, AHP methodology was applied to assess the risks of the projects (Mustafa, 1991).

Triantaphyllou et al. (1998) provided a background of weighted sum method (WSM), which recommended a simple decision model for easily obtainable and quantifiable data. Another competing method, weighted product model (WPM) is considered as a modification of the WSM, and used in order to overcome some of the weaknesses of WSM (Prida, et al., 2014) by eliminating units of measurement from the decision model. Thakala et al. (2016) has utilized WSM model by proposing a “swing weighting” concept. This approach takes into account of ranges of performance relevant to a set of alternatives i.e. the “swing” in performance. Hosseinzadeh et al. (2013) used voting approach in ranking the alternatives. Miljkovic et al. (2017) proposed a new weighted sum model where a normalization process was introduced. The approach allows the alternatives ranking is not reversed when a new alternative is added to the mix of several alternatives.

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