Global electricity generation from renewable sources using fuzzy sets and spatial analysis: revolution in solar and wind energy in BRICS countries

The adverse and increasing consequences of global climate change facing the modern world point to the need to reduce carbon emissions and transition to cleaner and more eco-friendly sources of energy for electricity generation. This paper explores global renewable electricity production using novel analytical model and methodological approach based on fuzzy sets and spatial analysis from 1990 to 2022. The innovative aspects of the proposed approach are: artificial intelligence and fuzzy logical approach, higher accuracy and low source energy demand. The findings obtained and innovative aspects of the proposed approach. Paper uses data from open sources mainly as reported by Global Carbon Project (Annual carbon dioxide (CO₂) emissions worldwide from 1940 to 2023 in Statista, 2023). Originality of paper is in proof of the development of solar and wind energy, their advantages and disadvantages, as well as their impact on the environment. The novelty of this paper comes from the diversification of energy generation solutions that can meet highly variable needs in a more efficient and carbon-free manner. The findings of the research can contribute to a better understanding of the dynamics of the electricity generation using renewable sources and help to identify ways to improve the sustainability and efficiency of the energy supply system in the future. Analysis of various studies also shows the next future directions of research (1) Integration of the multiple renewable energy sources. (2) Control systems using fuzzy logic. (3) Optimization of energy storage systems. (4) Systems aimed at supporting decision making. Such systems can help policymakers and practitioners make energy planning decisions, as well as decisions about the deployment of renewable energy technologies.