Hydropower is one of the most reliable and inexpensive forms of renewable energy that has maximum potential to replace conventional energy resources. However, due to the variations in climatic parameters along with the increased rate of urbanization, the reliability of hydropower plant in satisfying the increased demand requires additional measures which upsurges the operational expenditure. As a consequence, smart mitigation techniques are required to be adopted which can identify the trade-off between optimization of power production considering economic constraints, climatic variability and increased demand. This paper aims at proposing an intelligent mitigation measure to control the trade-off with the help of some group of indicators which have the maximum impact on production reliability of a power plant. This significance-based parameter modification entails recognition of the indicators and their significance in controlling reliability of a hydropower plant with the help of objective decision making methods and validating the selection by laboratory-based physical models as well as real-life case studies. A number of multi-criteria decision making methods which were popular in the identification of best decision out of many options were utilized in the detection of the significant indicators and their importance where the ensembled output from multiple multi-criteria decision making methods was used to detect the priority indicators and their priority. The results were validated by the physical replication of a hydropower plant which seconded the output from the decision making techniques. According to the results, the efficiency of the prime mover and the generators was found to be most substantial in regulating the reliability of the plant production. The physical model and real-life scenario both supported the selection.
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Multi-criteria decision making
- Fuzzy AHP:
Fuzzy analytic hierarchy process
- Fuzzy WSM:
Fuzzy weighted sum model
- Fuzzy ANP:
Fuzzy analytic network process
Technique for order preference by similarity to ideal solution
Data envelopment analysis
Climate change impacts
Reliability of plant performance
Electrical or generator efficiency
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Majumder, P., Majumder, M., Saha, A.K. et al. Selection of features for analysis of reliability of performance in hydropower plants: a multi-criteria decision making approach. Environ Dev Sustain 22, 3239–3265 (2020). https://doi.org/10.1007/s10668-019-00343-2
- Reliability analysis
- Ensemble multi-criteria decision making
- Feature selection
- Renewable energy
- Physical model of power plant