Classification of Renewable Energy Trends by Utilizing the Novel Entropy Measures under the Environment of q-rung Orthopair Fuzzy Soft Sets

Abstract

Energy generated from naturally replenishing sources such as the sun and wind is said to be renewable energy (RE). The production of electricity, water heating, and cooling can all be done with renewable energy. Some recent trends in renewable energy are (1) advanced photovoltaics, (2) distributed energy storage systems, (3) hydropower, and (4) Bioenergy. The utilization of fuzzy set theory is very important for the classification of renewable energy trends. q-rung orthopair fuzzy soft set (q-ROFSS) is a parameterization tool and a more efficient apparatus to resolve unclear and vague data in general. As entropy is a quantified measure of disorder or randomness in a system, it can handle the uncertainty of data in fuzzy set theory for a disordered system. So, in this article, based on q-ROFSS, we have initiated some novel entropy measures in the environment of q-ROFSS to relate more complex data and to give more room to decision-makers for handling many decision-making problems. So, the entropy of q-ROFSS is the measure of ambiguity related to q-ROFSS. To show the authenticity of the established work further, we have established an algorithm for the introduced work along with a descriptive example to substantiate the reliability of the initiated work. We have also initiated a comparative study of the introduced notion with some existing theories to demonstrate the usefulness and consistency of the given idea.