Energy costs are the key factors regarding the selection of appropriate renewable energy (RWG) alternatives. All costs of a power plant, such as investment, operation, maintenance, and repair are considered in the scope of levelized costs. Therefore, for the effective determination of the selling price of the energy, levelized cost has a guiding role. Because the levelized costs of RWG alternatives develop the sustainable production and energy consumption for the long term, the leading indicators of these costs should be analyzed significantly. Accordingly, in this study, it is aimed to investigate the levelized cost of RWG alternatives by using bipolar q-rung orthopair fuzzy (q-ROF) hybrid decision-making approach. The novelty of this study is to recommend an integrated decision-making model based on bipolar and q-ROFSs with golden cut. At the first stage, bipolar q-ROF multi stepwise weight assessment ratio analysis (M-SWARA) is employed for weighting the selected criteria of levelized costs of RWG alternatives. At the following stage, bipolar q-ROF technique for order preference by similarity to ideal solution (TOPSIS) is considered to rank the alternatives in terms of the levelized cost performance. On the other side, vise kriterijumska optimizacija i kompromisno resenje (VIKOR) model is also considered to rank the alternatives. In addition to this issue, the sensitivity analysis is also performed with four cases comparatively. Hence, consistency, reliability and coherency of the proposed model can be measured. It is identified that capacity loss has the greatest importance regarding the levelized cost of RWG projects. Solar is found as the best clean energy type with respect to the levelized cost management performance. In this context, it would be appropriate for investors to design projects close to the center. This will contribute to increasing the efficiency and productivity of these projects. 

Bipolar q-ROF Hybrid Decision Making Model With Golden Cut for Analyzing the Levelized Cost of Renewable Energy Alternatives

Energy costs are the key factors regarding the selection of appropriate renewable energy (RWG) alternatives. All costs of a power plant, such as investment, operation, maintenance, and repair are considered in the scope of levelized costs. Therefore, for the effective determination of the selling price of the energy, levelized cost has a guiding role. Because the levelized costs of RWG alternatives develop the sustainable production and energy consumption for the long term, the leading indicators of these costs should be analyzed significantly. Accordingly, in this study, it is aimed to investigate the levelized cost of RWG alternatives by using bipolar q-rung orthopair fuzzy (q-ROF) hybrid decision-making approach. The novelty of this study is to recommend an integrated decision-making model based on bipolar and q-ROFSs with golden cut. At the first stage, bipolar q-ROF multi stepwise weight assessment ratio analysis (M-SWARA) is employed for weighting the selected criteria of levelized costs of RWG alternatives. At the following stage, bipolar q-ROF technique for order preference by similarity to ideal solution (TOPSIS) is considered to rank the alternatives in terms of the levelized cost performance. On the other side, vise kriterijumska optimizacija i kompromisno resenje (VIKOR) model is also considered to rank the alternatives. In addition to this issue, the sensitivity analysis is also performed with four cases comparatively. Hence, consistency, reliability and coherency of the proposed model can be measured. It is identified that capacity loss has the greatest importance regarding the levelized cost of RWG projects. Solar is found as the best clean energy type with respect to the levelized cost management performance. In this context, it would be appropriate for investors to design projects close to the center. This will contribute to increasing the efficiency and productivity of these projects.

https://ieeexplore.ieee.org/ielx7/6287639/6514899/09759290.pdf

A study on the marine ecological security assessment of Guangdong-Hong Kong-Macao Great Bay Area.

A digital smart product service system and a case study of the mining industry: MSPSS

The Internet-based platform in the construction industry is a carrier for integrated construction information, which positively contributes to the development of smart construction sites (SCS). However, the lack of relevant research results in the ambiguous definition of the construction industry Internet platform. Meanwhile, the current development path of these platforms is also confusing. For this reason, this research first concludes on the main features of Internet-based platforms in the construction industry and puts forward a clear definition. Secondly, a large quantity of literature is overviewed to identify branches of Internet-based platforms as comprehensively as possible. Then, 26 platforms are sorted and classified according to different construction phases. Based on the analytic hierarchy process, an AHP–TOPSIS model, a decision-making method frequently used in the engineering industry, is established with dimensions of technology, demand, policy, and standards. Eventually, the priority of the development of the Internet platform of each segment is sorted, thereby forming the three-stage development path of the construction industry Internet platform, namely Foundation Construction Stage (Platform 1.0), Function Developing Stage (Platform 2.0), Platform Integration Stage (Platform 3.0), and analyzing the characteristics of each development stage. This research opened a clear path for developing Internet-based platforms and providing a basis for formulating development policies for these platforms in the construction industry. With the limitation of an incomprehensive summary of evaluation criteria and platform branches, a better-designed evaluation with more experts in various positions should be conducted in future further research.

/pdf/development-path-of-construction-industry-internet-platform-2xa3419j.pdf

Development Path of Construction Industry Internet Platform: An AHP–TOPSIS Integrated Approach

• Large data matrix solution in Fuzzy AHP. • Novel approach of data mapping in Fuzzy AHP. • Discussions on consistency ratio for large size matrix. • Time investment of experts is reduced. Fuzzy AHP is one of the widely used methods in Multi Criteria Decision Making, even in recent times. In Fuzzy AHP, the experts compare the pairwise criteria either jointly or individually. If the number of criteria to be compared is large, there can be ambiguity in the comparisons leading to inconsistency. Some researchers have tried to overcome this issue by considering criteria at global and local levels to reduce the number of criteria to be compared pairwise in each matrix. This simplifies individual matrix as the pairwise comparisons to be made are less in number. But, the numbers of matrices to be solved are increased in such cases. Also, there is a distinct drawback of creating global and local criteria. Secondly, for solving large data problems, it is a tedious affair to find experts sharing their time. In this paper, the authors have introduced an innovative approach to overcome limitations in the existing methodology, by providing an easier way of handling the data with an advantage of keeping all the criteria at the same level, validating the data and minimizing the time required by experts by simplifying the input data requirement for large data problems. New areas of research are cited for solving large matrix problems where pair wise comparisons are desired. 

Milind Jaiwant Sakhardande

Papers

On Solving Large Data Matrix Problems in Fuzzy AHP