Urban rooftop solar deployment can reduce building-sector emissions, but planning decisions must balance rooftop availability, hourly demand matching, technology configuration, investment cost, and grid export constraints. This study develops a hierarchical multi-objective planning framework for city-scale rooftop solar deployment. Building-level rooftop solar potential, hourly electricity demand from an urban building energy model, rooftop photovoltaic systems, solar water heating systems, battery storage options, operating modes, techno-economic performance, and grid export capacity limits were integrated into an integer linear programming-based portfolio optimization model. The framework compares net-present-value (NPV)-led, life-cycle-energy-saving (LCES)-led, and cost-led planning priorities through controlled tolerance relaxation of the primary objective. The case study included 7,674 buildings, with 2.32 km² of available rooftop area, 1.40 km² of practically installable photovoltaic area, and 308.59 MW of maximum photovoltaic capacity. Results showed that grid export capacity strongly reshaped deployment outcomes, but the benefits saturated beyond a threshold. Under the NPV-led scenario, increasing grid export capacity raised NPV by 44.12% and LCES by 51.53% before saturation at 270 MW. Under the LCES-led scenario, storage-intensive portfolios under tight grid constraints were progressively replaced by export-enabled configurations as grid capacity increased. Under the cost-led scenario, grid expansion mainly reduced initial investment by 0.25 billion CNY and improved NPV by 0.21 billion CNY, with limited additional energy-saving gains. Marginal analysis showed that modest tolerance relaxation captured most co-benefits, whereas larger relaxations produced diminishing returns. The framework provides interpretable planning evidence for city-scale rooftop solar deployment under competing priorities and grid constraints.

To address the limitations of current urban building energy modeling (UBEM), which often neglects moisture effects, we developed a comprehensive roadmap for modeling urban heat and moisture flows. This effort included developing an urban-scale whole-building heat and moisture transfer (HAMT) model that considers wind-driven rain, integrated with a microclimate model known as Urban Weather Generator (UWG). The proposed model was validated through analytical and comparative cases of whole-building hygrothermal performance analyses from the Annex 41 Project. The integrated whole-building and microclimate HAMT models were applied to a real urban building to assess the impact of moisture on annual energy predictions in a hot-humid region of Shanghai. The results show that incorporating moisture effects into the UBEM increases the annual cooling energy demand by 22.11% (5.92% owing to latent heat loads) and the annual heating loads by 6.06%, resulting in a 19.73% increase in the total annual energy loads. Additionally, the outer wall surface temperature decreases during and after rainfall events, with maximum decreases of 3.23 ℃ in winter and 8.80 ℃ in summer. Therefore, integrating moisture effects into UBEM is crucial, particularly in humid regions.

While previous research has explored factors influencing point-in-time thermal comfort, the mechanisms behind long-term thermal comfort remain elusive. This study utilized cognitive psychology theory to identify factors influencing long-term thermal comfort through statistical analyses of surveys across China and physical measurements in three Shanghai offices. Six of the 17 investigated factors exhibited strong linear relationships with long-term thermal comfort. The findings confirmed the existence of the Primacy Effect, Perceptual Bias, Recency Bias, and Peak-End Rule in long-term thermal evaluation, highlighting the impact of initial perceptions, past adverse experiences, and current comfort levels on one’s long-term thermal comfort. The study also indicated that these cognitive biases are primarily psychological and independent of the physical environment. Factors such as age, gender, climate, and controllability, which affect short-term thermal comfort, did not significantly impact long-term comfort. This research is one of the earliest attempts to understand long-term thermal comfort, underscoring its complexity and providing valuable insights for building managers and researchers aiming to enhance thermal comfort in office settings.