Selection of the Multiple-Criteria Decision-Making Method for Evaluation of Sustainable Energy Development: A Case Study of Poland

Abstract

One of the basic objectives of the European Union’s energy policy is to obtain and use energy in a sustainable way. Multiple-criteria decision making (MCDM) methods, in particular linear ordering based on the synthetic variable procedure, are used for comparative analyses of the level of energy sustainability. Despite many studies, the problem of choosing the optimal ordering method is still not fully resolved. This paper presents an original procedure that facilitates the selection of an effective method of the linear ordering of multi-feature objects for the evaluation of sustainable energy development of regions. What is understood as the effective ordering of regions is not only the effective ranking of objects but also their effective clustering. In order to obtain the best results of linear ordering, the authors put forward a multi-stage optimization of the selection of the method of ordering and normalization of diagnostic variables. Analysis of variance was used for the assessment of the object ranking quality, while for the assessment of the object clustering quality, an innovative approach was presented based on the analysis of the empirical distribution of the frequency of occurrence of the distance between objects. The linear ordering method, selected on the basis of the procedure proposed in the paper, was used to assess the energy sustainability of Polish regions. The calculations and analyses were carried out using the set of indicators developed by the authors. They characterize the sustainable energy development of regions in the social, economic, and environmental dimensions.

Management of Energy Sources and the Development Potential in the Energy Production Sector—A Comparison of EU Countries

“…With the DEA method, it is possible to determine not only fully effective objects but also those that are not fully effective. This method is widely used in research in the field of energy management [27,34]. This method, however, goes beyond the purpose of the research adopted in the paper but is an indicator of future research by the authors.…”

“…However, these authors do not study the impact of changes in the structure of these energy sources on the development potential of the energy sector itself, which is the subject of this article. Moreover, it can be noted that thematically compatible, available research on the energy production sector is mainly based on statistical methods of data analysis, as for example simple additive weighting (SAW) [27], technique for order of preference by similarity to ideal solution (TOPSIS) [28], data envelopment analysis (DEA) [29,30], the fully-modified least square (FMOLS) method [23] etc. Nevertheless, most of the studies in this field refer to a specific economy of a given country, and do not cover such a large group of countries as in the European Union.…”

A Multicriteria Decision-Making Model for the Selection of Suitable Renewable Energy Sources

“…The model was applied to a case study in Vietnam and the result showed that the optimal location for a hydroelectric plant is Nghe An Province. Trojanowska and Nęcka [24] performed a comparative research of four different MCDM methods-simple additive weighting (SAW), synthetic measure of development (SMD), weighted aggregated sum product assessment (WASPAS), and TOPSIS-in solving the sustainable energy development evaluation problem. As a result, the SMD method was the preferred method for the problem.…”

Green Growth in the OECD Countries: A Multivariate Analytical Approach

“…Ten variables belong to stimulants, i.e., the indicators x 1 -x 10 , and five indicators belong to destimulants, i.e., x 11 -x 15 . The indicators where the maximalization is positive are stimulants and the variables where the minimalization is positively rated are destimulants [69][70][71].…”