Measuring Efficiency of Generating Electric Processes

Abstract

Electric energy sources are the foundation for supporting for the industrialization and modernization; however, the processes of electricity generation increase CO 2 emissions. This study integrates the Holt-Winters model in number cruncher statistical system (NCSS) to estimate the forecasting data and the undesirable model in data envelopment analysis (DEA) to calculate the efficiency of electricity production in 14 countries all over the world from past to future. The Holt-Winters model is utilized to estimate the future; then, the actual and forecasting data are applied into the undesirable model to compute the performance. From the principle of an undesirable model, the study determines the input and output factors as follows nonrenewable and renewable fuels (inputs), electricity generation (desirable output), and CO 2 emissions (undesirable output). The empirical results exhibit efficient/inefficient terms over the period from 2011-2021 while converting these fuels into electricity energy and CO 2 emissions. The efficiency reveals the environmental effect level from the electricity generation. The analysis scores recommend a direction for improving the inefficient terms via the principle of inputs and undesirable outputs excess and desirable outputs shortfalls in an undesirable model.

Efficiency assessment of electricity generation from renewable and non‐renewable energy sources using Data Envelopment Analysis

“…Wang et al 20 calculated the efficiency of electricity production from renewable and non‐renewable fuels between countries, this study included output variables that can be desirable or undesirable, such as electricity generation or CO 2 produced, respectively. Wang et al 21 also emphasized the importance of improving electrical efficiency to restore the balance of ecosystems, considering undesirable output variables, such as those related to the production of CO 2 , CH 4 and N 2 O that are attributed to electricity generation.…”

Special Issue on “Energy, Economy and Environment for Industrial Production Processes”

“…Their results reveal that different water-distribution proportion scenarios and uncertainties can lead to changed water allocations, sewage discharges, chemical oxygen demand (COD) emissions and system benefits, and the variation of scenarios (i.e., from S2 to S3) can result in a change of 9% over the planning horizon for water allocation in the industrial sector. Wang et al [29] integrate the Holt-Winters model into a number cruncher statistical system (NCSS) to estimate the forecasting data and the undesirable model in data envelopment analysis (DEA), in order to calculate the efficiency of electricity production in 14 countries from the past to the future. Li et al [30] propose a two-step many-objective optimal power flow (MaOPF) solution method based on a knee point-driven evolutionary algorithm, and through examining the two-step method via the IEEE 118-bus system and the real-world Hebei provincial power system they verify that the approach is suitable for addressing the MaOPF problem of power systems.…”

Efficiency of the electricity sector in Mexico 2008-2015

“…Wang et al (2019) made a model using DEA to calculate the efficiency of electricity production in 14 countries all over the world. The study determines the input and output factors as follows nonrenewable and renewable fuels (inputs), electricity generation (desirable output) and CO 2 emissions (undesirable output).…”