Multi-criteria Analysis for the Selection of the Best Energy Efficient Option in Urban Water Systems

Carriço, Nelson; Gonçalves, Fábio Veríssimo; Covas, Dídia; Almeida, M. C.; Alegre, Helena

doi:10.1016/j.proeng.2014.02.033

Cited by 15 publications

(15 citation statements)

References 11 publications

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“…An integrated fuzzy [45] and comparative analysis of hybrid decision-making with balanced scorecard-based [46] approaches were used for investment analysis of renewable energy alternatives. Carrico et al [47] investigated the optimal energy-efficient options in water systems using Ant Colony and ELECTRE-III to solve the multi-criteria GDM problems. Bhowmik et al [48] used TOPSIS to find the optimal green energy source.…”

Section: Literature Reviewmentioning

confidence: 99%

Assessment of Energy Systems Using Extended Fuzzy AHP, Fuzzy VIKOR, and TOPSIS Approaches to Manage Non-Cooperative Opinions

et al. 2020

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Energy systems planning commonly involves the study of supply and demand of power, forecasting the trends of parameters established on economics and technical criteria of models. Numerous measures are needed for the fulfillment of energy system assessment and the investment plans. The higher energy prices which call for diversification of energy systems and managing the resolution of conflicts are the results of high energy demand for growing economies. Due to some challenging problems of fossil fuels, energy production and distribution from alternative sources are getting more attention. This study aimed to reveal the most proper energy systems in Saudi Arabia for investment. Hence, integrated fuzzy AHP (Analytic Hierarchy Process), fuzzy VIKOR (Vlse Kriterijumska Optimizacija Kompromisno Resenje) and TOPSIS (Technique for Order Preferences by Similarity to Idle Solution) methodologies were employed to determine the most eligible energy systems for investment. Eight alternative energy systems were assessed against nine criteria—power generation capacity, efficiency, storability, safety, air pollution, being depletable, net present value, enhanced local economic development, and government support. Data were collected using the Delphi method, a team of three decision-makers (DMs) was established in a heterogeneous manner with the addition of nine domain experts to carry out the analysis. The fuzzy AHP approach was used for clarifying the weight of criteria and fuzzy VIKOR and TOPSIS were utilized for ordering the alternative energy systems according to their investment priority. On the other hand, sensitivity analysis was carried out to determine the priority of investment for energy systems and comparison of them using the weight of group utility and fuzzy DEA (Data Envelopment Analysis) approaches. The results and findings suggested that solar photovoltaic (PV) is the paramount renewable energy system for investment, according to both fuzzy VIKOR and fuzzy TOPSIS approaches. In this context our findings were compared with other works comprehensively.

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Section: Literature Reviewmentioning

confidence: 99%

Assessment of Energy Systems Using Extended Fuzzy AHP, Fuzzy VIKOR, and TOPSIS Approaches to Manage Non-Cooperative Opinions

et al. 2020

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“…Several of the reviewed studies triangulated various methods to compare outcomes either between two common methods, e.g., between ELECTRE III and WSM Frijns et al, 2015) or ANP , AHP, and WSM , or to assess the results of less common or self-designed methods with more common ones (e.g., between TOPSIS and VIKOR , WSM and QCBS , AHP and a variant of WSM , AHP and SIMUS, comparing more specifically differences in subjectivity accounting , or WSM with MEW and COPRAS ). Carriço et al (2014), Frijns et al (2015) observed nearly similar results and pointed out that in general, MCDA literature does not discuss which method is most suited for which case nor why results would differ using different methods with same input data. They underline the fact that selecting appropriate methods for different problem types is still an open research question.…”

Section: Methods Combinationsmentioning

confidence: 93%

Multicriteria Decisions in Urban Energy System Planning: A Review

et al. 2017

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Urban energy system planning (UESP) is a topic of growing concern for cities in deregulated energy markets, which plan to decrease energy demand, reduce their dependency on fossil fuels, and increase the share of renewable energy sources. UESP being a highly multisectoral and multi-actor task, multicriteria decision analysis (MCDA) methods are frequently used in the decision processes. These methods may provide support in organizing and identifying solutions to problems with conflicting objectives. However, knowing which method to use is generally not straightforward, as the appropriateness of a method or combination of methods depends on the decision problem's context. Therefore, this article reviewed scientific papers to characterize and analyze MCDA problems and methods in the context of UESP. The review systematically explores issues such as the scope of the problems, the alternatives and criteria considered, the expected decision outcomes, the decision analysis methods and the rationales for selecting and combining them, and the role of values in driving the decision problems. The final outcome is a synthesis of the data and insights obtained, which may help potential users identify appropriate decision analysis methods based on given problem characteristics.

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“…They have been used extensively in various fields that include: resource allocation planning (Ogryczak, 2007); the medical field (Azar, 2000;Hancerliogullari et al, 2017); and most prevalently, the sustainable and renewable energy field (Kolios et al, 2016;Mateo, 2012). When applied to the energy field, the most common MCDA methods include: the weighted sum and weighted product method (WSM/WPM) (Carrico et al, 2014;Kolios et al, 2016;Mateo, 2012); technique for the order of preference by similarity to the ideal solution (TOP-SIS) (Kolios et al, 2016;Mateo, 2012); analytical hierarchy process (AHP) (Kolios et al, 2016;Mateo, 2012;Saaty, 2008); élimination et choix traduisant la realité (ELECTRE) (Carrico et al, 2014;Kolios et al, 2016;Mateo, 2012); and the preference ranking organisation method for enrichment evaluation (PROMETHEE) (Kolios et al, 2016;Mateo, 2012).…”

Section: Decision Support Methodsmentioning

confidence: 99%

A systematic decision support system to objectively evaluate retrospective energy efficiency modelling options

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Booysen

Mathews

et al. 2019

J. energy South. Afr.

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Tax incentives are one of the methods used by the South African government to incentivise energy efficiency. One of these incentives is Section 12L of the Income Tax Act (1962), which allows a significant tax deduction as a result of quantifiable energy efficiency (EE) savings. The associated EE savings are calculated by means of baseline models and must be in accordance with the national standard for measurement and verification, i.e. SANS 50010, which is based on international practice. The present study developed a methodology that assists EE projects with incentive applications to objectively evaluate potential modelling options and ultimately select a final model. This methodology is based on the weighted sum method. It is verified by applying it to three actual case studies and is further validated by comparing the results obtained from the case studies to independent results of formal and successful incentive applications. The methodology allows for a transparent selection of a modelling option that is compliant with the relevant tax incentive regulatory requirements and untainted by personal bias.

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Multi-criteria Analysis for the Selection of the Best Energy Efficient Option in Urban Water Systems

Cited by 15 publications

References 11 publications

Assessment of Energy Systems Using Extended Fuzzy AHP, Fuzzy VIKOR, and TOPSIS Approaches to Manage Non-Cooperative Opinions

Assessment of Energy Systems Using Extended Fuzzy AHP, Fuzzy VIKOR, and TOPSIS Approaches to Manage Non-Cooperative Opinions

Multicriteria Decisions in Urban Energy System Planning: A Review

A systematic decision support system to objectively evaluate retrospective energy efficiency modelling options

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