The Concept of Risk and Possibilities of Application of Mathematical Methods in Supporting Decision Making for Sustainable Energy Development

Abstract

This study is devoted to presentation of the concept of risk, and the possibility of applying mathematical methods in supporting decision making in the energy sector to promote sustainable energy development. The problem with risk assessment in the energy sector arises mainly due to the difficulty of expressing risk in numerical terms. To avoid risk, it is necessary to set the criteria and objectives of measurement before making decisions in the energy sector. The aim of this study is to try to fill in this gap by means of comparing decisions under risk conditions within models supporting energy decisions. The authors’ focus is on the problem of risk in supporting decision making towards sustainable energy sector development, which is the main target of the European Union (EU) energy policies. Without the ability to determine the probability of occurrence of certain phenomena and their inclusion into the model, it is not possible to determine how well the solutions resulting from the models are accurate, and what is the probability of their implementation under specific conditions linked to renewable energy development.

Renewable Energy in the Electricity Sector and GDP per Capita in the European Union

“…There are many studies dealing with forecasts of energy consumption from renewables based on various quantitative methods and on the data of the EU-28 countries [43][44][45][46][47][48][49][50] Considering the European Commission principal objective to extend the share of renewable energy production in electricity, the aim of this research is to explain the renewable energy in electricity based on GDP per capita, seen as a measure of standard of living and income inside the EU, in the period of 2007-2017. Knowing the advantages of RES related to environmental protection and reduction of GHG emissions, this paper checks whether the increase in renewable energy in electricity has a positive effect on the EU countries' economies.…”

A Conceptual Framework to Classify and Manage Risk, Uncertainty and Ambiguity: An Application to Energy Policy

“…The liberalization of the EU power market resulted in the reform of the Swiss electric sector; the ideological clash between supporters and opponents represented an important obstacle. Both drivers rank at the top half of the acuity scale (11)(12)(13)(14)(15)(16): they include uncertainty and risk. The high impact was confirmed by the successive evolution.…”

“…More precisely, the acuity depends on the impact's level and the related degree of doubt. The high-impact events are all situated at the top half of the scale (9)(10)(11)(12)(13)(14)(15)(16), and the opposite for low-impact events (1)(2)(3)(4)(5)(6)(7)(8). The "high impact-low doubt" events are at the top of the scale (13-16); the "low impact-low doubt" are at the bottom (1)(2)(3)(4).…”

“…For instance, Ioannou et al summarized an array of methods that have been widely employed for sustainable energy planning [10], in particular mean-variance portfolio analysis (MVP), real-options analysis (ROA), stochastic optimization techniques, Monte Carlo simulation (MCS), scenario analysis and multi-criteria decision analysis (MCDA). In more recent articles, Hamarat and Pruyt focus on adaptive policy making under deep uncertainty [11], whereas Rabe et al concentrate on the concept of risk and the possibility of applying mathematical methods to support decision-making aimed at promoting sustainable energy development [12].…”

Model of Optimization of Wind Energy Production in the Light of Legal Changes in Poland

“…Energy consumption in a given region is influenced by many factors, such as population, energy imports, energy exports, employment, industrial production, and technology development. [43,44]. Since the early 1970s, certain energy demand forecasting methods have been used to build the model.…”