Hierarchical Clonal Selection Algorithm for Multistage Pumping Station Optimization Operation Problem

This paper presents a novel approach to solve multistage pumping station optimization operation (MPSOO) problem. The problem is analyzed by two-tier mathematical model using decomposition-coordination method of large-scale system theory, and solved by hierarchical clonal selection algorithm (HCSA). The time priority based mutation operation is employed for considering the impact of peak and valley time-of-use electricity price on optimization operation, whilst the flow-approaching mutation operation is employed in the whole antibody genes to ensure the daily water requirements can be satisfied. These strategies ensure the effectiveness and diversity of mutation and prevent HCSA from the local optimal solution. The comparative experiments demonstrate consistently that HCSA outperforms the existing approach and practical application shows its advantages and feasibility in solving MPSOO problem. HCSA enhances the convergence performance and search efficiency.