Abstract
Finding optimal policies for real-life reservoir systems operation (RSO) is a challenging task as the available analytical methods cannot handle the arbitrary functions of the problem. Most of the methods employed are numerical or iterative type and are computer dependent. Since the computer resources in terms of memory and CPU time are limited efficient algorithms are necessary to deal with the RSO problems. In this paper we present a Genetic Algorithms (GA) optimized rule curve (RC) model for monthly operation of a multipurpose reservoir which maximizes hydropower produced while meeting the irrigation demands with a given reliability. Instead of the usual single target storage for each period the proposed model considers three sets of target storages, namely dry, normal, and wet storages, based on the beginning of the period storage level. The reservoir considered is Bhadra Multipurpose Reservoir, in the state of Karnataka, India, which supplies water to irrigation fields through two canals while generating hydropower with turbines installed at each of the canal heads and at the river bed. Optimization ability and robustness of GA-RC approach are ascertained through simulation with a different inflow sequence for which global optimum is computed using Dynamic Programming. Further, a 15 year real-time simulation of the reservoir using historical inflows and demands showed significant improvement in the benefit, i.e. power produced, without compromising on the irrigation demands throughout the operation period.
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Acknowledgements
A significant portion of this work is based on the PhD dissertation work carried out by the author at the Department of Civil Engineering, Indian Institute of Science, Bangalore, India under the guidance of Prof. Rama Prasad. The dissertation was funded by the Indian Institute of Science under the student stipend program.
Funding
A significant portion of this work is from the PhD dissertation by the author at the Department of Civil Engineering, Indian Institute of Science, Bangalore, India under the guidance of Prof. Rama Prasad. The dissertation work was funded by the Indian Institute of Science under the student stipend program.
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The author, Katakam V SeethaRam contributed to the study conception, design, material preparation, data collection, C program coding, results analysis, and manuscript drafting.
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The novelty of the paper is a rule curve model with three levels of target storages which satisfy the primary irrigation demands with a specified reliability before optimizing the hydropower produced.
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ANNEXURE
ANNEXURE
Where Hg is gross head (elevation of water level above river bed) in meters and is given as:
And S is reservoir storage in M.cu.m
a (Energy expressions)
Power produced, P by a flow Q with a net head, H is given as
Where w is unit weight of water (=9810 N); Q is flow through turbines in cu.m/s; H is net head (= actual reservoir water level - tailwater level) in m.
Energy produced, E, with a constant flow of Q cu.m/s in a standard month, having 30.4375 days which is the average number of days for a month in a four year period, is
If Q is expressed in M.cu.m/month (million cubic meters per month),
Using plant efficiency as 0.85 and losses due to friction in penstocks and valves as 2%,
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SeethaRam, K.V. Three Level Rule Curve for Optimum Operation of a Multipurpose Reservoir using Genetic Algorithms. Water Resour Manage 35, 353–368 (2021). https://doi.org/10.1007/s11269-020-02738-7
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DOI: https://doi.org/10.1007/s11269-020-02738-7