LAUSR

Abstract This paper presents a two-stage numerical simulation framework for pumped-storage energy system (PSES) to precisely describe its hydraulic-mechanical coupling characteristics. At the first stage, a novel nonlinear variable-parameter model based on the well-known method of characteristics (abbreviated as NVP-MOC model) is established. The originality of NVP-MOC model lies in its high degree of freedom to characterize system’s complicated dynamic behaviors realized by the variable parameters selected through parameter sensitivity analysis. At the second stage, an improved sine cosine algorithm (ISCA) is proposed as the meta-heuristic optimizer to identify the optimal values of the variable parameters in NVP-MOC model. The ISCA combines the original SCA with opposition-based learning and chaotic local search techniques for better initialization diversity and global exploration performance. Applying the on-site measured data, comparative studies have been made by comparing the modeling errors of different modeling schemes under typical operation conditions in both pumping and turbine modes. The results demonstrate that the proposed simulation framework can improve the overall modeling precision in characterizing transient behaviors of rotation speed and hydraulic pressures significantly compared with the traditional nonlinear modeling method for the pumped-storage plant.