Performance evaluation of complex electricity generation systems: A dynamic network-based data envelopment analysis approach

Reza Alizadeh*, Ramin Gharizadeh Beiragh, Leili Soltanisehat, Elham Soltanzadeh, Peter D. Lund

*Corresponding author for this work

Research output: Contribution to journalArticleScientificpeer-review

7 Citations (Scopus)

Abstract

To evaluate the performance of complex electricity generation systems, a new dynamic network-based data envelopment analysis (DNDEA) approach is presented. Past data envelopment analysis (DEA) studies on energy system efficiency have often ignored the dynamics of each process of the system individually. Here a network-based DEA method is built, which considers the interrelationships of the operations to determine the efficacy of the system. For assessing the performance over successive periods, with time-based dependencies between the successive periods, a dynamic DEA (DDEA) model is proposed. In DDEA, a linear combination of the efficiencies in successive periods is used as the complement of the system. The network-based and dynamic features of the created model enable measuring the performance of each sub-system process and the entire system in multi-period planning horizons simultaneously. These features make the DEA model identify changes in system efficiencies so much better than the current approaches. The created model is comprehensively implemented in the Iranian electricity sector using real data. Based on the findings, the efficiencies of power generation and transmission sectors are decreasing while the distribution performance is increasing. The proposed model could be applied to electricity generation systems in other countries as well.

Original languageEnglish
Article number104894
Number of pages15
JournalEnergy Economics
Volume91
DOIs
Publication statusPublished - Sep 2020
MoE publication typeA1 Journal article-refereed

Keywords

  • Data envelopment analysis
  • Dynamic
  • Efficiency assessment
  • Electricity generation systems
  • Energy
  • Network

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