ECSTO Framework for PHS-PV Systems in Karst Regions

This dataset contains the supplementary materials accompanying the research article titled "Ecologically-Constrained Spatio-Temporal Optimization and Ecological Threshold Identification for Pumped Storage-Photovoltaic Hybrid Systems in Karst Regions" submitted to Applied Energy. The data package includes four appendices that support the methodology, geological parameters, supplementary results, and sensitivity analyses presented in the main article: Appendix A. Mathematical derivation of the optimization modelProvides the complete mathematical formulation of the bi-level coordinated optimization model (ECSTO), including duality transformation for robust optimization, Big-M linearization for stochastic programming, and the detailed Column-and-Constraint Generation (C&CG) algorithm. Appendix B. Karst geological parameters and leakage coefficientsContains raw geological data from three deep boreholes (ZK01-ZK03) in the study area of Bijie, Guizhou, including fracture statistics, hydraulic conductivity measurements, and the calculation of leakage coefficients (k_leak) for different karst development zones based on dual-media seepage theory. Appendix C. Supplementary figures and tablesPresents additional visual and tabular data supporting the main findings, including PHS efficiency degradation curves, annual dispatch heatmaps comparing optimization strategies, monthly operational statistics, and raw biodiversity survey data from 12 cave sampling sites with Shannon-Wiener diversity indices. Appendix D. Sensitivity analysis of ecological constraint weightingExtends the trade-off analysis by examining the sensitivity of system configuration to the ecological weighting coefficient, defining the Marginal Cost of Ecological Protection (MCEP), and testing the robustness of optimization results to uncertainty in the ecological threshold (θ₀). These materials enable full reproducibility of the ECSTO framework and provide essential data for researchers working on renewable energy optimization in geologically complex and ecologically fragile karst regions. The data can be freely used under the Creative Commons Attribution 4.0 International (CC BY 4.0) license.