RESERVOIR OPERATION OPTIMIZATION USING ANT COLONY OPTIMIZATION A CASE STUDY OF MAHANADI RESERVOIR PROJECT COMPLEX CHHATTISGARH - INDIA
The significance of water resource management is undeniable, and optimizing reservoir operations for hydropower generation, irrigation, and flood mitigation is a profound task. To accomplish this, a variety of optimization approaches and procedures were employed. Ant colony optimization (ACO) techniques are employed in this study for reservoir operation, where a collection of cooperative agents called ants can achieve near-optimal reservoir operation. To use ACO algorithms, a finite horizon with an inflow time series is a primary assumption. The Mahanadi Reservoir Project comprises a multireservoir system, which makes the optimum operation complex and uncertain for such a reservoir. Furthermore, the ACO technique was employed to optimize the operation of the Mahanadi Reservoir Project Complex. Traditional water resource optimization models have failed due to the increasing number of decision variables and time constraints. The ACO model outperforms the existing operational policy, and the average percentage change in reliability, resilience, and sustainability suggests an increase of up to 12.79%, 3.98%, and 15.48%, respectively, while the vulnerability is reduced by up to 10.28%. Therefore, the ACO algorithm is a novel and promising method for finding optimal reservoirs. It is worth investigating for future applications in the field of water resource systems.
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