Journal of Hydroinformatics Vol 10 No 2 pp 163–179 © IWA Publishing 2008 doi:10.2166/hydro.2008.019
Single-reservoir operating rules for a year using multiobjective genetic algorithm
Taesoon Kim, Jun-Haeng Heo, Deg-Hyo Bae and Jin-Hoon Kim*
School of Civil and Environmental Engineering, Yonsei University, Seoul, 120-749, South Korea jhheo@yonsei.ac.kr
Department of Civil and Environmental Engineering, Sejong University, Seoul, 143-747, South Korea
*Current address: Youngsan River Control Center, 78-7 Daesonggil, Naju-City, Jeollanam-Do 520-200, South Korea
ABSTRACT
A monthly operating rule for single-reservoir operation is developed in this study. Synthetic inflow data over 100 years are generated by using a time series model, AR(1), and piecewise-linear operating rules consisting of 4 and 5 linear lines are found using the implicit stochastic optimization method. In order to consider multiobjective functions in reservoir system operation, a multiobjective genetic algorithm (NSGA-II) is adopted to obtain the optimization results. The search space of NSGA-II is carefully refined using frequency analysis of historical data, and the relationship between inflow and constraints is also investigated. It is determined that 4 and 5 segments are the optimal number of segments for the piecewise-linear operating rule, and the effect of random number seeding on NSGA-II is evaluated. Six years of historical inflow data are used for the simulation model and the results show that the developed operating rule would handle various inflow series. As a result, probabilistic reservoir storage forecasts can be provided to a system operator so as to enable the operator to evaluate the current status of a reservoir quantitatively.
Keywords: frequency analysis; multiobjective genetic algorithm; operating rules; probabilistic reservoir storage forecast
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