A Rigorous Two-Scale Predictive Optimization Framework for RE100 Grid Integration: Upcycling Urban Stormwater Detention Basins into Low-Head Variable-Speed Pumped Hydropower Plants with Hybrid Storage

The global mandate for RE100 compliance has accelerated the deployment of distributed photovoltaic (PV) generation, posing significant challenges to grid inertia and voltage stability in land-scarce urban networks. To address these challenges, this study proposes an infrastructure upcycling paradigm that transforms subterranean urban stormwater detention basins into decentralized, low-head variable-speed pumped hydro energy storage (VS-PHES) systems coupled with flywheel (FESS) and lithium-ion battery (BESS) hybrid energy storage systems (HESS). The facility is governed by a two-stage hierarchical energy management system (EMS): Stage 1 utilizes mixed-integer linear programming (MILP) for day-ahead macroeconomic scheduling with battery degradation penalties, while Stage 2 executes a dual-rate non-linear model predictive control (NMPC) framework (100 ms supervisory/10 ms local loop) for sub-second micro-transient voltage and frequency regulation. Incorporating a 1D-CNN predictive feature extraction model refined with Symlet-4 wavelet pre-filtering, the system achieves 97.85% transient state classification accuracy. A fail-safe, flood control-priority state-switching logic ensures municipal flood safety during severe precipitation events. Validated on a modified IEEE 33-bus radial grid and a practical 22.9 kV 134-bus Korean urban distribution network under a localized 5 MW PV dropout contingency (within a 20 MW total installed capacity), the coordinated 3.5 MW hybrid facility mitigates transient voltage sags from 0.931 p.u. to 0.952 p.u. and arrests frequency nadirs at 59.35 Hz. A 20-year life-cycle cost (LCC) analysis demonstrates that FESS shielding saves up to USD 1.91 million in BESS replacement overheads, supported by a dynamic nodal tariff mechanism for private RE100 investment.