Evaluation of the energy system through data envelopment analysis: Assessment tool for Paris Agreement

Abstract Various energy related studies use the data envelopment analysis (DEA) approach to measure the efficiency of decision making units (DMUs). However, heterogenous DMUs and either inappropriate input or output-oriented DEA model lead to unreasonable results. K-Mean clustering method was applied to select homogenous countries from energy data perspective. The input oriented DEA model was performed for power stations (PS) under renewables. The PS under non-renewables and refineiries as well as demand side were analyzed via the output-oriented model. The energy related quality of life (QoL) was the output of the demand efficiency analysis. The overall energy efficiency was calculated by multiplying the efficiency of both sides of energy. The results of the paper specified that the highest potential energy saving (PES) source in the supply side belongs to the non-renewables in power stations, followed by refineries, and finally deployment of renewables. Demand side analysis identified that the highest PES belongs to countries with high population, and high-income economy. In conclusion, the results of overall energy efficiency relying on QoL, suggested an allowance for non-renewables deployment in countries with low economic and low population. The allowance was proposed to support energy poverty, health improvement, and promotion of education.

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