Analyzing the Interaction of Renewable Energy Penetration with the Wealth of Nations Using Bayesian Nets

Recently, countries are trying to improve their economies while increasing the number of positive steps they are taking against climate change and minimizing greenhouse carbon emission. However, this effort is futile unless these countries turn their attention to renewable energy sources. The shift from conventional energy to renewable energy will contribute to economic growth, employment opportunities, and human welfare while meeting climate goals in the long-term. In this study, using the data provided mainly by The World Bank (WB) and The International Renewable Energy Agency (IRENA), the authors aim to construct a Bayesian Network to analyze the interaction of renewable energy penetration with the wealth of nations. In this context, initially, the factors related to Renewable Energy will be determined, and then a Bayesian Network is going to be developed. Using multiple what-if analyses, the resulting model will act as a diagnostic tool for policymakers in their attempts to understand and manage the renewable energy system. The what-if analyses conducted from the resulting model show that if renewable energy consumption increases and fossil fuel energy consumption decreases, CO2 intensity as well as health expenditures will be expected to decrease. Similarly several other scenarios are constructed and reflected in the study.