Estimation of renewable energy sources under uncertainty using fuzzy AHP method

Renewable energy sources are natural energy forms that are replenished on a human timescale and are seen as more sustainable and eco-friendlier compared to fossil fuels. These resources are crucial for lowering carbon emissions and addressing climate change, ensuring a cleaner and more sustainable energy future. Choosing renewable energy sources in an uncertain environment presents a complex decision-making challenge, as it involves assessing multiple factors under conditions of uncertainty, such as fluctuating energy prices, shifting government policies, varying resource availability (e.g., solar, wind, hydro), and technological advancements. Fuzzy multi-criteria decision-making approaches offer a structured way to evaluate different options based on several criteria while addressing these uncertainties. The region in question experiences a combination of sunny, windy, and rainy days throughout the year, but the availability of solar, wind, and hydro resources is subject to significant uncertainty. Solar energy varies by season and location, and weather patterns are hard to predict. While government incentives exist, they may change overtime. Wind resources can be inconsistent, with the region’s average annual wind speed supporting wind power, but occasional periods of low wind intensity. Hydropower, though valuable, is affected by uncertain factors such as water availability, climate change, and regulatory or environmental considerations. In this article, the fuzzy AHP method with fuzzy Z-numbers is employed to assess renewable energy sources such as solar, wind, hydro based on criteria like economic factors, environmental impact, and technical feasibility.