Selection Methodology of Energy Consumption Model Based on Data Envelopment Analysis

Authors

  • Vladimir Nakhodov Associate Professor, National Technical University of Ukraine “Kyiv Polytechnic Institute”
  • Algirdas Baskys Professor, Vilnius Gediminas Technical University, Center for Physical Science and Technology
  • Nils-Olav Skeie Associate Professor, Telemark University College,
  • Carlos F. Pfeiffer Professor, Telemark University College,
  • Ivanko Dmytro Ph.D. student, Vilnius Gediminas Technical University, National Technical University of Ukraine “Kyiv Polytechnic Institute”

DOI:

https://doi.org/10.1515/ecce-2016-0006

Keywords:

Energy consumption, Energy efficiency, Data models, Production management

Abstract

The energy efficiency monitoring methods in industry are based on statistical modeling of energy consumption. In the present paper, the widely used method of energy efficiency monitoring “Monitoring and Targeting systems” has been considered, highlighting one of the most important issues — selection of the proper mathematical model of energy consumption. The paper gives a list of different models that can be applied in the corresponding systems. The numbers of criteria that estimate certain characteristics of the mathematical model are represented. The traditional criteria of model adequacy and the “additional” criteria, which allow estimating the model characteristics more precisely, are proposed for choosing the mathematical model of energy consumption in “Monitoring and Targeting systems”. In order to provide the comparison of different models by several criteria simultaneously, an approach based on Data Envelopment Analysis is proposed. Such approach allows providing a more accurate and reliable energy efficiency monitoring.

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Published

2016-12-01

How to Cite

Nakhodov, V., Baskys, A., Skeie, N.-O., Pfeiffer, C. F., & Dmytro, I. (2016). Selection Methodology of Energy Consumption Model Based on Data Envelopment Analysis. Electrical, Control and Communication Engineering, 11(1), 5-12. https://doi.org/10.1515/ecce-2016-0006