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Climate change and its negative effects are driving the global shift from fossil fuels to renewable energy sources. To tackle the dependency on traditional energy sources in harsh winter regions and improve heating quality during periods of thermal demand fluctuations, this paper proposes a new distributed heating peak shaving system (DHPS). The system combines municipal heat and clean energy within the secondary network while reducing the return water temperature in the primary network. It comprises solar collectors, electric thermal storage tanks (ETST), and absorption heat pump (AHP) units, integrated into conventional heat exchange stations. The system operates in two modes to manage peak and off-peak loads respectively, with TRNSYS simulation used to evaluate performance across a range of peak-shaving gradients. A multidimensional comprehensive assessment is conducted between the DHPS under optimal peak shaving coefficient (θ) conditions and conventional peak clipping boiler (PCB). Results indicate that DHPS achieves a high primary energy ratio (PER) of 1.251 at θ = 0.5, reducing combustion emissions by nearly 40%. The static payback period (PBP) of the system is 3.5 years. When the electricity price drops to 0.275 CNY, its operational costs are comparable to PCB. DHPS caters to the energy characteristics of cold regions where electricity supply exceeds demand. It enables flexible peak shaving while ensuring the complete utilization of clean energy and effectively utilizing waste heat from power plants. [ABSTRACT FROM AUTHOR]

Building operations account for a large amount of energy use and CO2 emissions, and the morphology of buildings in residential clusters strongly impacts energy efficiency performance. However, little research has focused on the morphology and energy electricity usage of high-rise residential clusters in hot summer and cold winter (HSCW) regions. We investigated 96 residential clusters in Hangzhou, China, and established a corresponding morphology database. Additionally, we obtained annual electricity consumption for 16 of these residential clusters. With this database, we performed optimization of morphological parameters upon energy use intensity (EUI) using a genetic algorithm (GA). Specifically, the cooling, heating, and lighting EUIs of high-rise residential clusters were studied. After implementing the optimized morphological parameters, there was a reduction of up to 7.73% in EUI. According to regression analysis, the average aspect ratio was the most significant factor influencing EUI (r = −0.907), followed by floor area ratio (r = −0.755), average orientation (r = 0.502), and average number of floors (r = −0.453). These results indicate that a higher intensity of land development with a greater floor area ratio, average aspect ratio, and average number of floors can reduce total energy consumption. Additionally, we found that an average building orientation of southwest 15° (with respect to south) is optimal. The findings of this study can assist urban planners and designers in developing more sustainable residential clusters, leading to decreased energy costs and CO2 emissions. [ABSTRACT FROM AUTHOR]

Recently, air quality has become a hot topic due to its profound impact on the quality of the human living environment. This paper selects the tourist city of Dalian as the research object. The concentration and spatial distribution of PM10 and NO2 in the main urban area were analyzed during the peak tourist seasons in summer and winter. Simulations were used to explore the spatial and temporal variation patterns of PM10 and NO2, combining building and road density at different scales to reveal the coupling relationship between individual pollutant components and urban parameters. The results show that the PM10 concentration is high in the center and NO2 is concentrated in the northern district of Dalian City. In an area with a radius of 100 m, the dilution ratio of building density and road density to the concentration of the PM10 pollutants is at least 43%. Still, the concentration of NO2 is only coupled with road density. This study reveals the spatial and temporal variation patterns of PM10 and NO2 in Dalian, and finds the coupling relationship between the two pollutants and building density and road density. This study provides a reference for preventing and controlling air pollution in urban planning. [ABSTRACT FROM AUTHOR]