Dataset of Rooftop Photovoltaic Retrofit Potential and Economic Assessment for Existing Residential Communities in Shanghai (1949-1990)

By integrating geospatial informatics with multi-scenario PV simulations, the dataset aims to resolve the dual challenges of "spatial constraints and economic contention" faced by high-density, aging residential blocks.

The data architecture consists of four dimensions: (1) macro-scale zoning and chronological statistics of Shanghai’s residential neighborhoods (1949–1990); (2) building-level micro-geometric parameters, including footprint area, aspect ratios, primary/secondary orientations, and neighborhood identifiers; (3) a discretized Photovoltaic Performance Mapping Lookup Table (PV-PMLT) derived from localized meteorological data; and (4) aggregated community-level economic indicators—including Net Present Value (NPV), Internal Rate of Return (IRR), Levelized Cost of Electricity (LCOE), and Dynamic Payback Period—evaluated across various reconfiguration scenarios (e.g., pitched-roof benchmarks, optimal-tilt arrays, and asymmetric reconstruction) and business models (e.g., grid-connected vs. PV-plus-storage).