Decision-making in sustainable energy transition in Southeastern Europe: probabilistic network-based model

Polona Šprajc,Simonida Vukadinović,Nena Hribar,Goran Šimić

doi:10.1186/s13705-021-00315-3

Abstract

BackgroundSustainable energy transition of a country is complex and long-term process, which requires decision-making in all stages and at all levels, including a large number of different factors, with different causality. The main objective of this paper is the development of a probabilistic model for decision-making in sustainable energy transition in developing countries of SE Europe. The model will be developed according to the specificities of the countries for which it is intended—SE Europe. These are countries where energy transition is slower and more difficult due to many factors: high degree of uncertainty, low transparency, corruption, investment problems, insufficiently reliable data, lower level of economic development, high level of corruption and untrained human resources. All these factors are making decision-making more challenging and demanding.MethodsResearch was done by using content analysis, artificial intelligence methods, software development method and testing. The model was developed by using MSBNx—Microsoft Research’s Bayesian Network Authoring and Evaluation Tool.ResultsDue to the large number of insufficiently clear, but interdependent factors, the model is developed on the principle of probabilistic (Bayesian) networks of factors of interest. The paper presents the first model for supporting decision-making in the field of energy sustainability for the region of Southeastern Europe, which is based on the application of Bayesian Networks.ConclusionTesting of the developed model showed certain characteristics, discussed in paper. The application of developed model will make it possible to predict the short-term and long-term consequences that may occur during energy transition by varying these factors. Recommendations are given for further development of the model, based on Bayesian networks.

Highlights

Sustainable energy transition of a country is complex and long-term process, which requires decisionmaking in all stages and at all levels, including a large number of different factors, with different causality
The model presented in the paper was developed using MSBNx—Microsoft Research’s Bayesian Network Authoring and Evaluation Tool, in order to enable a successful transition to a sustainable energy sector
The model was tested on a sample of 12 countries of SE Europe, for the period from 2009 to 2019

Summary

Introduction

Sustainable energy transition of a country is complex and long-term process, which requires decisionmaking in all stages and at all levels, including a large number of different factors, with different causality. These are countries where energy transition is slower and more difficult due to many factors: high degree of uncertainty, low transparency, corruption, investment problems, insufficiently reliable data, lower level of economic development, high level of corruption and untrained human resources. All these factors are making decision-making more challenging and demanding. There is a causal dependence between these factors, sometimes positive, sometimes negative, from year to year, from one country to another It implies high level of uncertainty and determines the way of transition model development [9]. There are numerous uncertainties that make the decision-making in the field of sustainable energy transition in SE Europe significantly more difficult, and they can be conditionally divided into three basic groups

Objectives

Methods

Results

Discussion

Conclusion