ARTIFICIAL INTELLIGENCE AND NATURE-INSPIRED OPTIMIZATION ON INTEGRATIVE CAPACITY OF RENEWABLE ENERGY IN THE WESTERN BALKAN

Two artificial intelligence models for the integration of renewable energy sources are developed within this research to contribute European Green Plan realization. The review natural potential, on one hand, and installed capacity, other in Western Balkans twenty-eight countries is done research, as well emissions. analyses show that countries, sometimes even with lower potential renewables, have much more capacities than higher potential. According this, first model based multi-criteria linear regression analysis. This relies correlation between relevant regressors, i.e. input variables same regressors a particular country. Its goal find maximum possible integrative capacity Balkans’s country real socio-economic environment. second evolution genetic algorithms. electric power system. Nature-inspired optimization applied. From framework given large number generations, technical combinations degree integration, best populations, selected. As nature selects from many generations allows survive punishes „weakˮ, our case, „weak” those failing meet conditions limitations A new methodology offered. Theoretical general formulas both models. Developed tested numerical experiment solar Serbia case study. Analyses sensitivity prove applicable all or regions.