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Inter-Criteria Dependencies-Based Decision Support in the Sustainable wind Energy Management

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  • Paweł Ziemba

    (Faculty of Economics and Management, University of Szczecin, Mickiewicza 64, 71-101 Szczecin, Poland)

Abstract

Decision problems related to the wind energy require considering many, often interrelated and dependent on each other, criteria. To solve such problems, decision systems based on Multi-Criteria Decision Analysis (MCDA) methods are usually used. Unfortunately, most methods assume independence between the criteria, therefore, their application in decision problems related to the wind energy is debatable. This paper presents the use of the Analytic Network Process (ANP) method to solve a decision problem consisting in selecting the location and design of a wind farm. The use of the ANP method allows capturing the complexity of the decision problem by taking into consideration dependencies between criteria. As part of the verification of the solution, the results of the ANP method were compared with those of the Analytic Hierarchy Process (AHP) method, which uses only hierarchical dependencies between criteria. The conducted verification showed that the inter-criteria dependencies may have a significant influence on the obtained solution. On the basis of the conducted sensitivity analysis and the research into robustness of the rankings to the rank reversal phenomenon, it has been found out that the ranking obtained with the use of the ANP is characterized by a higher quality than by means of the AHP.

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  • Paweł Ziemba, 2019. "Inter-Criteria Dependencies-Based Decision Support in the Sustainable wind Energy Management," Energies, MDPI, vol. 12(4), pages 1-29, February.
    • Handle: RePEc:gam:jeners:v:12:y:2019:i:4:p:749-:d:208639
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    15. Qigan Shao & Sung-Shun Weng & James J.H. Liou & Huai-Wei Lo & Hongbo Jiang, 2019. "Developing A Sustainable Urban-Environmental Quality Evaluation System in China Based on A Hybrid Model," IJERPH, MDPI, vol. 16(8), pages 1-25, April.
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    17. Zhen Li & Yun Li & Yanbin Li, 2019. "Performance Evaluation of Energy Transition Based on the Technique for Order Preference by a Similar to Ideal Solution and Support Vector Machine Optimized by an Improved Artificial Bee Colony Algorit," Energies, MDPI, vol. 12(16), pages 1-21, August.
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