Application of Bayesian Networks in Modeling of Underground Gas Storage Energy Security

Energy security is a multidimensional and multifaceted concept, therefore defining it complex problem. It requires the consideration of wide set factors from fields economics, geology, ecology geopolitics, all which have an influence on energy or lack thereof. The article focuses natural gas, very specific fuel in European context. most “politicized” source energy, as consequence its growing importance transition transformation process. In order to identify dependencies between variables gas market analyze their impact (in particular underground storage), authors chose built Bayesian network. network effective flexible tool that allows analysis relationships build them model values based evidence. presents two stages work with first one, was historical data. shows well probability value ranges individual variables. A huge advantage presented can be used various scenarios market. Moreover, ability make statistical inferences for nodes represents valuable additional feature. Several examples such are second stage analysis, examining consumption variability level inventory storage facilities, having LNG terminal share electricity production capacity given country. use tools networks us better discover interrelationships influencing market, them, estimate distinct described metrics. simple example metric, i.e., minimum at end winter season, modeling using relatively network, this article.