Abstract:

This article addresses the problem of efficiency assessment of electricity generation technologies using a multicriteria approach. The proposed evaluation framework is based on Data Envelopment Analysis (DEA), a non-parametric method for measuring the relative efficiency of decision-making units. DEA models have gained increasing attention in the energy sector due to their flexibility in handling multiple inputs and outputs without requiring predefined weights or functional relationships. Recent developments in DEA modeling, tailored to the needs of the energy industry, allow for the inclusion of both energy-related and non-energy inputs, as well as desired and undesired outputs, such as greenhouse gas emissions or waste. The models discussed in this article enable the calculation of a unified efficiency score that integrates technological, economic, and environmental aspects of performance. In addition to identifying efficient technologies, DEA also provides guidance for improving inefficient units by benchmarking them against comparable, more efficient alternatives. The information derived from such analyses supports strategic decision-making and helps guide investments towards more effective and sustainable technological solutions. The article provides a review of selected DEA models and discusses their applicability in the context of electricity generation efficiency assessment.