Development and Application of Storage-Zone Decision Method for Long-Term Reservoir Operation Using the Dynamically Dimensioned Search Algorithm

A zone-based operation uses a simple method to make operational decisions based on rules established for storage zones. However, the division of a reservoir into appropriate storage zones involves complicated procedures. Using test functions to compare the three heuristic methods of a genetic algorithm, the shuffled complex evolution method developed by the University of Arizona, and the dynamically dimensioned search (DDS) method, we found that DDS might be useful for determining good global solutions to a problem with many decision variables. Hence, we applied the DDS method to determine three series of water levels for zoned reservoir storage division. The developed reservoir-operating method was applied to Andong Dam in the Republic of Korea. We derived zone boundaries using a generated dam inflow series and performed zone-based operations for validation using historical data under the assumption of known inflow data. The results showed improvements in the water supply reliability and vulnerability compared with historical data. The zone-based operating method derived from the present research could prove valuable because of its simplicity and practicality.