A Fuzzy Analytic Hierarchy Process Based COPRAS Approach for the Evaluation of the Renewable Energy Sources

Renewable energy sources are those that naturally replenish over time and provide an endless supply of energy without the risk of resource exhaustion. Examples include solar power, wind energy, hydropower, geothermal energy, and biomass. These energy sources are crucial due to their sustainable nature, enabling continuous energy production while minimizing environmental harm and preserving natural resources. Unlike conventional fossil fuels, which are limited and heavily pollute the environment, renewable energy significantly reduces carbon emissions, improves air quality, and helps address climate change challenges. Embracing renewable energy is vital for building a sustainable future. This study evaluates renewable energy sources using a hybrid fuzzy multi-criteria decision-making approach. The proposed method integrates two techniques: the fuzzy analytic hierarchy process and the fuzzy-based COPRAS method. The fuzzy analytic hierarchy process is first applied to determine the relative importance of criteria and create a fuzzy decision matrix. Then, the COPRAS method processes this matrix, incorporating the calculated weights, to systematically assess and rank renewable energy options.