Multi-Constraint Multi-Objective Collaborative Optimization Control of Geothermal Water Extraction Systems

To overcome the rapid expansion of the drawdown cone, severe inter-well interference, and high operating costs caused by independent geothermal well operation, this study investigated the coordinated optimal scheduling of geothermal water extraction. Fifteen geothermal production wells in the main urban area of Kaifeng City were selected as the study case. The intake intervals of these wells are located at depths of 1020 to 1330 m. Based on the exploitable yield of the geothermal reservoir, user water demand, and well layout, a management model for coordinated scheduling was developed. Design drawdown, water demand, and heating capacity were used as constraints. The objectives were to minimize operating cost, nodal drawdown, and drawdown interference between wells. The results from several optimization algorithms show that the improved Cheetah Optimization Algorithm converged faster and produced more consistent solutions. Compared with the preoptimization scheme, the optimized scheme reduced total operating cost by 31.64%, total drawdown in the study area by 69.5%, and the sum of inter-well drawdown interference by 34.7%. This study provides useful support for selecting efficient optimization algorithms and offers a basis for the scientific development, utilization, and protection of geothermal water resources.