Application of M-SWARA and TOPSIS Methods in the Evaluation of Investment Alternatives of Microgeneration Energy Technologies

Abstract

Investments in microgeneration technologies help to boost the usage of clean energy while reducing pollution. However, selecting the appropriate investment remains the most critical phase in developing these technologies. This study aims to design a multi-criteria decision-making method (MCDM) to evaluate investment alternatives for microgeneration energy technologies. The proposed MCDM is based on a Multi Stepwise Weight Assessment Ratio Analysis (M-SWARA), to define the relative importance of the factors. The Technique for Order Preference by Similarity to Ideal Solution (TOPSIS) and q-Rung Orthopair Fuzzy Soft Sets (q-ROFSs) are used to rank investment alternatives. Calculations were also made with Intuitionistic Fuzzy Sets (IFSs) and Pythagorean Fuzzy Sets (PFSs). For analysis, five evaluation criteria were selected based on the literature: frequency of maintenance, ease of installation, environmental adaptation, transmission technologies, and efficiency of cost. Similarly, six alternatives for microgeneration technology investments were selected: ground source heat pumps, micro hydroelectric power, micro combined heat and power, micro bioelectrochemical fuel cell systems, small-scale wind turbines, and photovoltaic systems. The results showed that cost efficiency was the most significant factor in the effectiveness of microgeneration energy investments, and the photovoltaic system was the best alternative to increase microgeneration energy technology investment performance. Furthermore, the results were the same for the analyses made with IFSs and PFSs, demonstrating the reliability of the proposed method. Therefore, investors in microgeneration technologies should prioritize photovoltaic systems. This conclusion is supported by the fact that photovoltaic is a renewable energy source that has witnessed the most technological improvements and cost reductions over the last decade.

Yeşil Hastanelerin Gelişimi İçin Stratejik Unsurların Belirlenmesi: Enerji Bazlı Faktörlere Yönelik DEMATEL Yöntemi ile Bir Analiz

“…Yeşil hastanelerin verdiği avantajları temel olarak beş kategoride toplanabilmektedir. İlk kategori araştırma sonuçlarına göre daha iyi hasta çıktısı ve güvenliği sağlanmasıdır [14,15]. Çünkü yeşil hastaneler gün ışığı alarak hastaların hastanede kalma süresini kısaltmaktadır.…”

Complex Fuzzy Assessment of Green Flight Activity Investments for Sustainable Aviation Industry

“…The model proposed in this study, however, employs a new technique that we termed M-SWARA that involved the introduction of several improvements to the classical model. The new method allows for the identification of causal relationships [39,40]. After obtaining evaluations from a team of experts, a bipolar q-ROFS relation matrix is created as shown in Equation (33).…”

“…Step 13 relates to the generation of the weighted decision matrix using Equation (32), as shown in Table 9. Step 14 focuses on the determination of the concordance and discordance interval matrices, which are generated via Equations ( 34)- (39). Table A7 provides information on these matrices.…”

A new decision making method based on Z-decision-making trial and evaluation laboratory and ordered weighted average and its application in renewable energy source investment

“…To determine the relationships among criteria in the decision-making of RES investment, analytic hierarchy process (AHP) (Ulewicz et al, 2021;Karatop et al, 2021;Sedghiyan et al, 2021), stepwise weight assessment ratio analysis (SWARA) (Dinçer et al, 2022;Keleş et al, 2022;Rani et al (2021), and decision-making trial and evaluation laboratory (DEMATEL) technique Li et al al., 2022;Xie et al, 2021;Zhang and Deng, 2019) are frequently applied. Among these methods, AHP only takes into account the hierarchy structure of the criteria; SWARA only considers the hierarchical priorities of the experts.…”