Stochastic Optimal Reservoir Operation Management, Applying Group Conflict Resolution Model

Alireza Mojarabi-Kermani, Ehsan Shirangi (), Amin Bordbar, Amir Abbas Kaman Bedast and Alireza Masjedi
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Alireza Mojarabi-Kermani: Islamic Azad University
Ehsan Shirangi: Islamic Azad University
Amin Bordbar: Islamic Azad University
Amir Abbas Kaman Bedast: Islamic Azad University
Alireza Masjedi: Islamic Azad University

Water Resources Management: An International Journal, Published for the European Water Resources Association (EWRA), 2019, vol. 33, issue 8, No 15, 2847-2865

Abstract: Abstract In the present study, qualitative simulation model of reservoir and genetic algorithm optimization model were combined based on fuzzy logic to determine the trade off curve with stochastic quantitative and qualitative objectives. According to contradictory utilities of decision makers with respect to the obtained optimum trade off curve, a model of group conflict resolution was developed in order to determine the best point on the trade off curve from the perspective of decision makers. Using the outcome of conflict resolution model which was indicative of acceptable water quality for all decision makers, the optimization model was re-run, and time series of monthly water opeartion was determined for the agreed quality of beneficiaries. Finally, with the aim of formulating timely policies of operation of the reservoir, the use of probabilistic support vector machines that have the ability to create output possibilities was suggested. The proposed model was used for the operation of 15-Khordad Dam Reservoir, Iran. The results demonstrate the efficiency and accuracy of the fuzzy optimization model as well as the importance of using group conflict resolution model to provide the utility of decision makers in the operation of the reservoir.

Keywords: Reservoir operation; Group conflict resolution model; Support vector machines (SVMs); Water quality; Fuzzy optimization model (search for similar items in EconPapers)
Date: 2019
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DOI: 10.1007/s11269-019-02271-2

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