Optimal design of the renewable energy map of Greece using weighted goal-programming and data envelopment analysis

Eleni Zografidou, Konstantinos Petridis, Garyfallos Arabatzis, Prasanta Dey*

*Corresponding author for this work

Research output: Contribution to journalArticlepeer-review


Renewable energy forms have been widely used in the past decades highlighting a "green" shift in energy production. An actual reason behind this turn to renewable energy production is EU directives which set the Union's targets for energy production from renewable sources, greenhouse gas emissions and increase in energy efficiency. All member countries are obligated to apply harmonized legislation and practices and restructure their energy production networks in order to meet EU targets. Towards the fulfillment of 20-20-20 EU targets, in Greece a specific strategy which promotes the construction of large scale Renewable Energy Source plants is promoted. In this paper, we present an optimal design of the Greek renewable energy production network applying a 0-1 Weighted Goal Programming model, considering social, environmental and economic criteria. In the absence of a panel of experts Data Envelopment Analysis (DEA) approach is used in order to filter the best out of the possible network structures, seeking for the maximum technical efficiency. Super-Efficiency DEA model is also used in order to reduce the solutions and find the best out of all the possible. The results showed that in order to achieve maximum efficiency, the social and environmental criteria must be weighted more than the economic ones.

Original languageEnglish
Pages (from-to)313-326
Number of pages14
JournalComputers and Operations Research
Early online date28 Mar 2015
Publication statusPublished - Feb 2016

Bibliographical note

© 2014, Elsevier. Licensed under the Creative Commons Attribution-NonCommercial-NoDerivatives 4.0 International http://creativecommons.org/licenses/by-nc-nd/4.0/


  • data envelopment analysis
  • energy production
  • goal programming
  • renewable energy


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