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

Situated within the framework of urban regeneration, this dataset systematically quantifies the rooftop photovoltaic (PV) retrofit potential and economic feasibility of 343 legacy residential neighborhoods (Xincun) built in Shanghai between 1949 and 1990, encompassing a total of 10,688 buildings. 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). This dataset provides high-fidelity quantitative support for urban planners, policymakers, and energy investors, serving as a data cornerstone for the low-carbon transformation of existing building stocks in high-density urban environments.