OPTIMIZING THE EXPANSION SCHEDULE OF SYSTEM CAPACITY FOR GROUNDWATER SUPPLY IN AN UNCONFINED AQUIFER

摘要

Groundwater resources play a diverse but vital role in regional water supplies, and generally depend on a network of pumping wells to distribute water to the community. The design of the network determines its capacity, the goal of which at the time of construction is to satisfy the water demand of a community into the foreseeable future. Since water demand increases over time, the system may be over designed initially, but eventually needs to be expanded if water demands exceed the maximum capacity of the system. Therefore, this research proposes a novel optimal capacity-expansion model capable of determining an optimal schedule to expand the system capacity according to increasing water demand. The proposed model assumes a 2-D groundwater flow for a confined and unconfined aquifer while combining the Genetic Algorithm (GA) and Differential Dynamic Programming (DDP) to solve the optimization problem. The main structure of the hybrid algorithm is GA, in which each chromosome represents a possible network design and its expansion schedule. The fixed cost of each chromosome can be computed easily. The DDP then solves the optimal pumping and injecting scheme while evaluating the optimal operating costs associated with each chromosome. Simulation results indicate that this capacity-expansion model saves more of the present value of the total cost for the same annul interest rate and water requirement than the conventional design that determined the system capacity at the beginning. Furthermore, the benefits of using this capacity-expansion model increases with a rising interest rate. Results further demonstrate that the proposed model is highly promising for use in facilitating a cost-efficient well system design for regional groundwater supplies.