Nearly zero-energy buildings are increasingly evolving from conventional energy consumers into systems with both demand and on-site supply functions. However, the operational changes associated with shifts in supply-demand dominance remain insufficiently understood. This study investigated a nearly zero-energy office building. Under unified boundary conditions, comparative models of reference and designed buildings were established to reconstruct hourly building energy demand and on-site renewable energy supply profiles. The transition of supply-demand relationships was evaluated from four aspects: structural characteristics, supply-demand status, temporal coupling, and techno-economic performance. Results show that the annual energy demand was reduced by 40.8%, while the supply-demand ratio increased from 0 to 1.44, indicating a shift from external dependence to annual net surplus. Meanwhile, the end-use load structure was reshaped, with heating and air-conditioning loads significantly decreasing and internally driven loads relatively increasing, transforming the system from a single-dominant structure to a multi-load interactive structure. Further analysis reveals that although annual energy surplus was achieved, only 54.9% of the on-site supply was effectively utilized due to temporal mismatch between supply profiles and demand patterns, with a mismatch index of 0.352. In addition, under the present annual-scale engineering boundary, the unit energy investment intensity of demand-side pathways was lower than that of supply-side pathways by a factor of 1.82. These findings indicate that optimization priorities for buildings with high renewable penetration should move beyond demand reduction toward coordinated improvement of structural balance, temporal matching, and pathway configuration. This study provides a new perspective for the design and operation of nearly zero-energy and zero-carbon building energy systems.

Under carbon peaking and neutrality goals, building integrated with photovoltaics and energy storage system clusters (BIPECs) enable efficient on-site renewable energy use and can act as dispatch units for the public grid. However, BIPECs face significant uncertainties and are still under development. This study proposes a decentralized cooperative power dispatch model coupling a multi-agent proximal policy optimization (MAPPO) algorithm and offline digital twin (ODT) technology to optimize the photovoltaic (PV) power consumption of clusters despite limited data availability. An integrated BIPEC energy system model is established, and by leveraging the multi-agent system model of the BIPEC, the decentralized dispatch problem is converted into a fully cooperative multi-agent reinforcement learning (MARL) problem. A simulation-assisted ODT framework constructs a digital environment for MAPPO to augment data, conduct MAPPO training, and optimize the reward function, thereby obtaining power dispatch strategies. The results show that the proposed optimization model can obtain dispatch strategies that reflect a high degree of collaboration, reducing the cumulative power supply from the public grid by 0.55–2.56% per month compared to the non-cooperative self-generating and self-using strategy. This study presents the application of MARL in BIPECs by introducing a decentralized collaborative power dispatch methodology for building clusters, enhancing building energy efficiency and facilitating flexible collaborative power dispatch.

Accurate photovoltaic (PV) forecasting is crucial for grid stability, yet data-driven models are often hindered by the "cold-start" problem of data scarcity at new installations. Current generative models that directly synthesize power data act as "black-box" solutions, lacking physical interpretability and generalizability. To address this, we propose StochRad-UAGAN, a novel gray-box GAN framework. Instead of generating power data, it synthesizes physically-consistent solar radiation scenarios by modeling the key stochastic driver: the cloud-induced daily attenuation coefficient (mu DNI(t)). Our U-Net Attention GAN (UAGAN) proves superior to baseline models in capturing complex time-series features. In a BIPV forecasting case study, using our framework to augment a limited dataset reduced the prediction RMSE of various models by 10.1 %-49.7 %, with an optimal generated-to-real data ratio of 2:1 to 4:1. This validates StochRad-UAGAN as an effective, generalizable solution to the data scarcity problem in solar applications, bridging deep learning with physical principles.

Nearly zero energy buildings (NZEBs) require optimisation of parameters like air tightness and heat recovery to minimise heating, ventilation and air conditioning (HVAC) energy use. This four climate zones in China: – severe cold (SCZ), cold (CZ), hot summer and cold winter (HSCWZ), and hot summer and warm winter (HSWWZ). Building energy simulations analysed the impact of air tightness and exhaust heat recovery efficiency on the energy use in NZEB archetypes with the identified operation patterns in each zone. Results show SCZ and CZ benefit from improved air tightness up to the Code limit ( N 50 = 0.6), giving 36% and 8% energy savings, respectively, with heat recovery compared with using only infiltration for ventilation. For HSWWZ, reducing airtightness to provide adequate fresh air eliminates the need for heat recovery, yielding the lowest energy consumption. When improving the airtightness, sensible heat recovery suits SCZ/CZ, for HSWWZ, total heat recovery is technically more effective for energy savings; however, due to minimal energy consumption differences, meeting ventilation requirements through infiltration is more economical. Thus, regional optimisation of air tightness, ventilation strategy, and heat recovery selection can facilitate the design of high-performance NZEBs. The established coupled operation patterns also better represent NZEB performance versus standardised assumptions. Implications include revised design code requirements for air tightness according to climate zone, transitioning standards to realistic operating conditions and selection criteria for heat recovery equipment. The optimisation methodology and results guide the NZEB energy efficiency in China’s various regions.

The uncontrolled integration of numerous electric vehicles (EVs) brings great uncertainty to grid regulation. Real-time monitoring of widely dispersed EV charging load meter data requires a large number of efficient data acquisition equipment and transmission channels, which brings high investment and operating costs. To address this challenge, this paper proposes a data-driven method for real-time estimation of aggregated EV charging load. A maximum relevance minimum redundancy selection method based on pearson correlation coefficient (mRMR-P) is proposed to select a representative subset of EV charging station (EVCS) meter data and eliminate redundancy. Subsequently, a deep learning model constructed in this paper extracts the load features and temporal relationships from the selected representative meter data to achieve aggregated estimation of EV charging load. Additionally, to address the issue of model degradation due to changes in EV users' charging behavior over time, an adaptive window concept drift detection (CDD) method based on the model's input-output mapping relationship is proposed. Finally, the proposed method is validated using real data from residential and public EVCS in Hangzhou, China. Experimental results demonstrate the effectiveness and superiority of the proposed method.

Due to the increase in global energy consumption and carbon dioxide emissions, new energy are eagerly expected to be widely put into application. The installation of photovoltaic systems will increase the fluctuation and uncertainty of load, which will have a certain impact on the planning of customer-side energy storage systems (ESSs). The current tariff policy and the scenarios of energy storage devices have made strict requirements on the ability to control load. In this paper, an energy storage revenue assessment method based on portfolio theory is proposed. The uncertainty of load is analysed by non-parametric kernel density estimation (KDE). Then a factor is used to measure the risk of reducing the load, which is coped with the ESS. The capacity and operation strategies of ESS is optimally allocated by linear programming (LP). Then a method based on portfolio theory is used to quantify the combined impact of risk and revenue, which provides a certain reference for the determination of the capacity of the behind-the-meter (BTM) ESS and the operation strategy.

Urban morphology significantly influences building energy consumption, solar energy potential, and outdoor thermal microclimate. This study seeks to optimize the urban morphology of high-rise residential clusters, using a framework that emphasizes energy use, outdoor thermal microclimate and incremental investment cost at a preliminary stage of design. The proposed framework is based on performance oriented parametric simulation and implements multi-objective optimization using the Grasshopper platform to assess residential cluster morphology. The study analyzed the five morphological parameters (floor area ratio (FAR), building density (BD), average floor (AF), average orientation (AO), and average aspect ratio (AAR)) to achieve the minimize of the Net Energy Intensity (NEI), Universal Thermal Climate Index (UTCI), and Incremental Investment Cost (IIC) of residential clusters. This approach aims to enhance energy efficiency and improve summer microclimate while reducing investment costs. Additionally, analyzed the correlation between morphological parameters and three key performance metrics: Energy Use Intensity (EUI) (encompassing heating, cooling, and lighting requirements), Photovoltaic Energy Generation (PVEG), and UTCI. The findings reveal that the optimal morphology of residential clusters varies significantly depending on the desired objective. When prioritizing PVEG, a morphology characterized by low height, high density, and a small aspect ratio is recommended. It is noteworthy that in this morphology, the cluster also demonstrates optimal UTCI during the summer. Conversely, if EUI is the primary objective, a configuration with higher height and aspect ratio, along with lower density, is suggested. On the other hand, balancing the requirements of these three objectives may require a moderately-spaced layout with low height, large aspect ratio, and compact front-to-back building spacing. Under these morphologies, particular attention should be given to the layout in the north–south directions. Furthermore, southward orientation is advisable. Additionally, based on analysis of Pareto solutions, a FAR of approximately 2.6 to 2.7 is recommended.

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.

To improve the recovery of waste heat and avoid the problem of abandoning wind and solar energy, a multi-energy complementary distributed energy system (MECDES) is proposed, integrating waste heat and surplus electricity for hydrogen storage. The system comprises a combined cooling, heating, and power (CCHP) system with a gas engine (GE), solar and wind power generation, and miniaturized natural gas hydrogen production equipment (MNGHPE). In this novel system, the GE’s waste heat is recycled as water vapor for hydrogen production in the waste heat boiler, while surplus electricity from renewable sources powers the MNGHPE. A mathematical model was developed to simulate hydrogen production in three building types: offices, hotels, and hospitals. Simulation results demonstrate the system’s ability to store waste heat and surplus electricity as hydrogen, thereby providing economic benefit, energy savings, and carbon reduction. Compared with traditional energy supply methods, the integrated system achieves maximum energy savings and carbon emission reduction in office buildings, with an annual primary energy reduction rate of 49.42–85.10% and an annual carbon emission reduction rate of 34.88–47.00%. The hydrogen production’s profit rate is approximately 70%. If the produced hydrogen is supplied to building through a hydrogen fuel cell, the primary energy reduction rate is further decreased by 2.86–3.04%, and the carbon emission reduction rate is further decreased by 12.67–14.26%. This research solves the problem of waste heat and surplus energy in MECDESs by the method of hydrogen storage and system integration. The economic benefits, energy savings, and carbon reduction effects of different building types and different energy allocation scenarios were compared, as well as the profitability of hydrogen production and the factors affecting it. This has a positive technical guidance role for the practical application of MECDESs.

In the context of the dual carbon goal,research on energy conservation and emission reduction in cities and buildings has been widely carried out.As an important carrier of built environment information,three-dimensional urban models are indispensable preliminary preparations in architectural design,physical environment simulation and analysis of buildings,and urban climate research.However,for domestic cities,there is currently a lack of exploration of the complete process of 3D urban modeling based on the Rhino platform.This paper compares the advantages and disadvantages of existing methods,and constructs a set of processes that are complete and real-time in data sources,simple and convenient in operation,fast in generation,clear in generation model layers,and can fully connect with later analysis.A demonstration is conducted using West Lake District of Hangzhou City as an example,Provide certain convenience and inspiration for relevant research conducted on this platform.

The diffuse radiance and luminance can be anisotropic over the skydome, which is important to the daylight and thermal environments of buildings and the urban areas. This paper proposes a model that can estimate the luminance and radiance distributions over the skydome by the basic global and diffuse irradiance, and the solar altitude measurements/data that are readily accessible for many places over the world. The radiance and luminance are normalized by the horizontal irradiance and illuminance instead of the uncommon zenith radiance and luminance. The approach is developed and tested by the mid-to long-term (a few months to two years) field measurements of several locations with various climates/latitudes, showing a good accuracy when compared to the reference models.

自然通风是一种健康及高效的绿色建筑技术手段.文章基于绿色建筑理念,利用PHOENICS软件,对某典型建筑大厅门斗的自然通风情况进行了定量分析,通过改变门斗长宽比,对比厅内自然通风效果情况.结果表明:杭州地区过渡季节,建筑大厅不同长宽比的门斗会对厅内自然通风效果产生影响,且当门斗采用长宽比为4:1时室内通风情况最佳;当采用长宽比为2:1时,则不利于室内自然通风,从而为今后建筑入口设计提供一些理论参考.

Due to the influence of surrounding buildings on the radiation transfer process, the irradiance of individual buildings in building stocks is more uneven and different than that of individual buildings in open spaces. In view of the defect of the existing building surface irradiance calculation model in the sky radiation energy balance calculation, the complex surface reflection radiative transfer in diffuse irradiance, and complex processes, this paper combined the calculation of the complex surface narrow sky view, multiple reflections, and radiation characteristics of nonuniformity, and finally established the model for irradiance on the facade of a building stock (IFBS model) in a sheltered environment. The simulation results show that the IFBS model is superior to the traditional model in the calculation of sky diffuse irradiance and reflection irradiance of building stocks and is more suitable for the numerical calculation of the radiation transfer process of complex buildings.

The paper calculates and analyzes the current situation of carbon emission from building sector in one province in China. The research shows that carbon emissions from building sector in this province mainly come from public buildings and residential buildings, accounting for 43.56% and 46.84% of the total carbon emissions, respectively. GDP growth and improvement of people's lives have a significant role in promoting carbon emissions in the building sector. According to the existing development model, it is difficult for the building sector of this province to achieve peak carbon emissions in 2030. Therefore, it is necessary to carry out carbon reduction measures in the construction sector based on the actual conditions of this province.

u Although there have been numerous studies on the evaluation of models that estimate sky diffuse radiation on inclined surfaces, it is still difficult for investigators to select from available sky diffuse radiation models for urban microclimate and building performance simulation. This is due to the fact that results from different studies are not consistent, or even contradictive, which indicates the fact that the evaluation criterion itself has a great effect on the performance of the model. To explore the effect of different evaluation criteria on the performance rating of the models, four evaluation methods are applied in this paper: diffuse irradiance on facades with respect to sky condition, diffuse irradiance on facades with respect to orientation, diffuse irradiance distribution among sky dome with respect to sky condition and diffuse irradiance on buildings in obstructed environment. Based on a statistical test on available data, Igawa model is considered to be the most accurate and appropriate model for urban and building energy simulation. Besides, an evaluation criterion appropriate for screening sky diffuse models for urban and building energy simulation is proposed. Furthermore, potential errors that may occur in the measurement and the corresponding quality control is presented.

血管支架介入手术能有效扩张狭窄的冠状动脉.医生根据经验对病人血管的二维影像进行分析,并选取支架进行置入.结合勿能—行为—结构模型开展血管支架置入模型研究.提出了利用虚拟现实语言建立支架三维模型,模拟支架置入过程.通过虚拟现实交互技术结合FBS产品设计方法,对虚拟支架选型和置入过程不断调整,直到达到最优过程.该原型系统能帮助病人建立个性化置入模型,针对病人血管的特异性准确进行支架选型,还能辅助医生开展虚拟现实环境下的支架置入手术训练.

高层高密建筑群是现代城市发展的典型特征之一,其内部形成的独特微环境(尤其是行人高度)直接影响居民的生活质量,因此评价行人高度的风舒适性以及分析风环境形成原因是建筑群风环境的重要研究内容.对同济大学彰武路校区宿舍群行人高度的风环境进行了实测和基于标准K-ε湍流模型的数值模拟,并依据风舒适理论对建筑群风环境进行了分析.研究表明,当建筑群总体朝向与来流方向一致时能实现高质量的建筑群风环境,但街谷文丘里效应使建筑群局部环境的风舒适性难以保证.

Based on the measured radiation data of a radiation station in Shanghai,constructs shortwave radiation calculation models for building groups using the anisotropic diffuse radiation model (NADR model) and isotropic diffuse radiation model,respectively.Simulates radiation values of different buildings using Matlab.The results show that diffuse radiation simulation values under the isotropic diffuse radiation model are relatively small in all orientations for individual building.For those in building groups,diffuse radiation simulation values in all orientations are also relatively small.The difference of simulation values between two models is slightly increased as the ratio of buildings' height and length increases.Suggests that the NADR model can be applied to simulate radiation values of a point on a wall or an entire wall.

The Isotropic Diffuse Radiation Model and Anisotropic Diffuse Radiation Model have been widely applied to building thermal simulation, however, their different performance in simulation have not been fully studied, especially the simulation of building groups. Based on radiation data collected by a radiation station in Shanghai(121.208°E, 31.290°N), an Anisotropic Diffuse Radiation Model(NADR model) and Isotropic Diffuse Radiation Model(IDR model) were used to simulate irradiance values for individual building and building groups, respectively. The analysis results show that diffuse radiation simulation value under the Isotropic Diffuse Radiation Model is relatively small in all orientations for individual building and building groups, except the north. Moreover, the potential impact of applying Isotropic Diffuse Radiation Model on results for thermal simulation and practical application is briefly illustrated. Keywords: diffuse radiation, anisotropic, radiation model

With the urban development, complex urban structure and variable sky radiance distribution lead to unpredictable solar energy, especially diffuse radiance, on building facades. Accurate irradiance estimation based on diffuse sky radiance models is required for high performance building design and use. A comparison is presented of seven anisotropic distribution models for sky diffuse radiance: Bugler model, Klucher model, Skartveit model, Perez model, Muneer model, Yao model and Igawa model. Their performance was judged against measurement data from the aspect of orientations and sky conditions. On the whole, it suggests that Iwaga model, which is based on continuous distribution functions and all-weather conditions, should be implemented to estimate diffuse irradiance on building facades in Beijing.