Decision support techniques have a key role in investment and strategic decisions in the energy sector. As complex decision-making problems involve the simultaneous consideration of an extensive set of different factors, it is an essential part of the methodology to define, structure, and integrate the criteria. The main purpose of the study was to develop a system of criteria and weights that are suitable for general application in the energy sector and can best describe the decision-making mechanisms present in society and various social groups. When developing the system of criteria, we moved away from the hierarchical approach related to the three pillars of sustainability; therefore, a wide range of notions were assessed based on a population representative survey data collected in Hungary. We used algebraic methods to explore the internal structure of the set of criteria that had been previously defined by means of social sciences, while the importance weights were specified by applying the method of analytic network process. Furthermore, the ranking of heating and electricity generation alternatives were determined.
The power generation sector is expected to undergo substantial changes in Hungary in the near future due to the decommissioning of several large units reaching the end of their lifetimes in parallel to the projected increase of renewable electricity generating capacity. In addition to the traditionally widely used deterministic adequacy assessment methods, a probabilistic approach has a great importance in case of technologies with different capacity credits. An analytical country-specific adequacy assessment model enabling the probabilistic modelling of wind power plants was developed and applied to generating capacity forecasts for Hungary. Model parameters were estimated using multi-annual production, plant availability and hourly system demand data. Adequacy indicators obtained from the model clearly show increasing reliance on imported electricity in the absence of investments in new generating capacity.
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