Over the past few years, people have been using more energy because of globalization and as many countries have moved from farm-based to industrial and knowledge-based economies. As a result of this change, there are greater demands for energy and emissions have gone up. Because of these issues, fuzzy logic, neural networks, and genetic algorithms are used more often to help with energy planning and policies, which promotes both economic growth and conservation of nature. This study looks in detail at how fuzzy logic plays a role in solar, wind, bioenergy, microgrids, and hybrids. Results discovered that fuzzy logic is most often used during site scouting, for renewable energy installations, finding the highest energy point, and optimizing several important factors. According to the review, fuzzy models are dependable and useful for finding effective, accurate outcomes in many renewable energy fields.