A multiple criteria decision making method to weight the sustainability criteria of renewable energy technologies under uncertainty

Sitorus, Fernando

doi:10.1016/j.rser.2020.109891

Cited by 59 publications

(24 citation statements)

References 65 publications

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“…Moreover, integrating MEREC with the other objective and subjective weighting methods like Entropy, IDOCRIW (Integrated Determination of Objective CRIteria Weights), WE-BIRA (Weight Balancing Indicator Ranks Accordance), ACW (Adaptive Criteria Weights), SWARA and considering other methods of expert evaluation can be the focus in future research [68][69][70][71][72]. Another area for future research could be to apply the proposed method to real-world problems, such as designing geographic information systems, economic indicators assessment, evaluations in tourism management, and pollution management [2,[73][74][75].…”

Section: Discussionmentioning

confidence: 99%

Determination of Objective Weights Using a New Method Based on the Removal Effects of Criteria (MEREC)

et al. 2021

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The weights of criteria in multi-criteria decision-making (MCDM) problems are essential elements that can significantly affect the results. Accordingly, researchers developed and presented several methods to determine criteria weights. Weighting methods could be objective, subjective, and integrated. This study introduces a new method, called MEREC (MEthod based on the Removal Effects of Criteria), to determine criteria’ objective weights. This method uses a novel idea for weighting criteria. After systematically introducing the method, we present some computational analyses to confirm the efficiency of the MEREC. Firstly, an illustrative example demonstrates the procedure of the MEREC for calculation of the weights of criteria. Secondly, a comparative analysis is presented through an example for validation of the introduced method’s results. Additionally, we perform a simulation-based analysis to verify the reliability of MEREC and the stability of its results. The data of the MCDM problems generated for making this analysis follow a prevalent symmetric distribution (normal distribution). We compare the results of the MEREC with some other objective weighting methods in this analysis, and the analysis of means (ANOM) for variances shows the stability of its results. The conducted analyses demonstrate that the MEREC is efficient to determine objective weights of criteria.

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Section: Discussionmentioning

confidence: 99%

Determination of Objective Weights Using a New Method Based on the Removal Effects of Criteria (MEREC)

et al. 2021

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“…There exist studies using multi-criteria methods [14,15,[20][21][22][23][24][25][26], but the application of the SMART (Simple Multi-Attribute Rating Technique) method to investment decisions in the power sector remains little studied. In the literature, a lot of attention has been paid to the problem of the selection of energy generation technologies, especially in relation to renewable energy sources [14,[27][28][29][30], as well as general planning for the sustainable development of the sector [31][32][33][34]. Despite many studies in this area, the issue of selection itself and the support to the decision concerning the selection of conventional sources and widely understood clean coal technologies is not fully resolved.…”

Section: Introductionmentioning

confidence: 99%

Multi-Attribute Rating Method for Selecting a Clean Coal Energy Generation Technology

Lipka

Szwed

2021

Energies

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The process of technology management contains various stages, such as the identification, selection, acquisition, implementation, and maintenance of technologies. In the case of power generation companies, a key aspect of the selection stage is the choice of generation technologies for newly commissioned units. The investment decision depends on many factors, primarily economic, environmental, social, technological, and legal, and represents a complex multi-criteria problem. Currently, the decision is further complicated by the often unpredictable tightening of environmental standards, forcing the closure of conventional sources, on which many countries have so far based their energy security. The paper analyzes the problem of choosing one of the so-called clean coal technologies to be implemented in conditions of transformation of the power sector. In this paper, five selected clean coal technologies are characterized, and the SMART method is adopted to technology selection. The following technologies were considered: supercritical coal-fired power plant (with and without CCS), IGCC power plant (with and without CCS), and IGCC power plant with CCS and integrated hydrogen production. Nine practical criteria (in three main groups: environmental, technological, economic) for comparing technologies are defined, computational experiments performed, and conclusions from the research presented. The work was based on the literature study of multi-criteria decision support and an analysis of power sector needs based on the example of the Polish power sector. The conducted research, apart from the technology recommendation, led to the conclusion that the chosen method may be applied to decision-making in the field of power generation technology management. The study also indicated the potential direction of the development of a power generation structure in a situation where a component of ensuring energy security is the use of available coal fuels.

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“…The environmental criteria traditionally employed is concerned with sustainability of energy infrastructures and aimed at evaluating their environmental impact. These include the amounts of GHG emissions and air pollution associated with the infrastructure, the amount of land used by the infrastructure equipment, and the noise levels from energy systems operation [3][4][5][6][7][8][9][10]. Economic criteria used in practice are used to evaluate costs and benefits associated with the energy infrastructure life cycle.…”

Section: Introductionmentioning

confidence: 99%

“…Furthermore, revenues include income from selling energy, and other co-benefits associated with the infrastructure. These indicators are often used to evaluate the infrastructure economic aspect using different criteria, including the net present value (NPV), life cycle costs (LCC), and levelized cost of energy (LCOE) [3][4][5][6][7][8][9][10][11]. Technical criteria used in previous projects aim at evaluating the equipment used by the infrastructure.…”

Section: Introductionmentioning

confidence: 99%

A Systematic Methodology for Design of Sustainable Urban Neighborhood Energy Infrastructure

2021

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The growing share of global energy consumption by cities (currently over 65%) raises the requirements for a systematic holistic approach for designing urban energy infrastructure in order to ensure its sustainability. A literature review of state-of-the-art modeling of urban energy infrastructure design emphasized the incomprehensive sustainability of the performed evaluations, as they accounted for several aspects of sustainability but missed others. Omitting important aspects can have significant implications which can put the sustainability of the energy infrastructure at risk. In this study, we attempted to develop a comprehensive model for designing sustainable energy infrastructure for urban districts, which accounts for the four aspects of sustainability: social, technical, environmental, and economic. The model is based on a four-step methodology: district characterization, a technological survey for distributed generation and energy storage, selecting suitable technologies according to social and technical criteria, and simulations of different energy infrastructure configurations to find the most suitable configurations basing on economic and environmental criteria. The research includes a case study in which the model was implemented for the Technion campus in Haifa. The developed model proved to be a comprehensive, efficient, and versatile tool for designing urban energy infrastructure.

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A multiple criteria decision making method to weight the sustainability criteria of renewable energy technologies under uncertainty

Cited by 59 publications

References 65 publications

Determination of Objective Weights Using a New Method Based on the Removal Effects of Criteria (MEREC)

Determination of Objective Weights Using a New Method Based on the Removal Effects of Criteria (MEREC)

Multi-Attribute Rating Method for Selecting a Clean Coal Energy Generation Technology

A Systematic Methodology for Design of Sustainable Urban Neighborhood Energy Infrastructure

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