Prioritizing Energy Blockchain Use Cases Using Type-2 Neutrosophic Number-Based EDAS

Abstract

The modern power systems are evolving in parallel to the development of other technological trends such as decarbonization and digitalization. While the penetration of renewable energy resources is increasing within the national and regional energy mix, emerging digitalization technologies, such as artificial intelligence and blockchain technology are shaping modern power systems. Especially blockchain technology has a very high potential to disrupt the current and future energy sector landscape by enabling various use cases in this domain. This paper aims to prioritize different energy use cases where blockchain technology can actively be utilized to create additional value. This study proposes a Type-2 Neutrosophic Number (T2NN) based Evaluation based on Distance from Average Solution (EDAS) to evaluate and rank a set of existing use cases of an energy blockchain system. Testing and validation of the model is done through a comparison against one alternative T2NN based Multi-Criteria Decision Making (MCDM) model and an existing approach from literature. In addition, a sensitivity analysis is performed, revealing that changing criteria weightings do not affect the ranking order of the use cases of the energy blockchain system. Prioritizing the use cases can assist the companies, standardization bodies, and related government authorities to make better decisions for their operations, such as ranking the investment decisions.

A multi-criteria based analytic framework for exploring the impact of Covid-19 on firm performance in emerging market

“…Therefore, the efficacy of LOPCOW in the presence of subjective bias has not been tested. The model (LOPCOW-EDAS) may be extended and tested by using fuzzy and rough set based models as demonstrated in various recently published work (for instance, [143] , [144] , [145] , [146] , [147] ). Secondly, while aggregating the year wise rankings the BC model does not consider priority of any single year.…”

Additive manufacturing process selection for automotive industry using Pythagorean fuzzy CRITIC EDAS

“…Compared to many other decision-making techniques, EDAS is simpler, follows a clear logic that is easy for practitioners to understand, and the mathematical process is relatively basic. Integration of EDAS and Pythagorean fuzzy sets (PF-EDAS) is a recently developed approach that has swiftly attracted attention, having been applied in different fields, including car selection [55], sustainable circular supplier selection in the manufacturing sector [56], evaluating investment projects for highways [57] selecting an optimal drug to treat the Coronavirus ailment [58], supplier selection for coal thermal power plant [59], ship navigation environment safety assessment [60], selection of waste management techniques [61], loan evaluation for banking customers [62], analysis of metaverse integration of freight fluidity assessment solutions [63], evaluation of alternatives for mobility sharing [64] and ranking of use cases for energy blockchain [65].…”

Entropy and discrimination measures based q-rung orthopair fuzzy MULTIMOORA framework for selecting solid waste disposal method

“…With the expansion of socio-economic settings, the real-life MCDM problems are becoming progressively complicated. Accordingly, numerous MCDM methods have successfully been discussed and implemented in realistic applications (Cali et al, 2022 ; Pamucar et al, 2022a , b ; Deveci et al, 2022b , c ; Wu et al, 2022 ). The “multi-objective optimization method by ratio analysis (MOORA) (Brauers and Zavadskas, 2006 )” is a one of the effective and prominent MCDM techniques, which consists of “ratio system (RS)” and “reference point (RP)” model.…”