Challenges and opportunities for carbon neutrality in China’s building sector—Modelling and data

A novel approach of day-ahead cooling load prediction and optimal control for ice-based thermal energy storage (TES) system in commercial buildings

The identification of some radar reflectivity signatures plays a vital role in severe thunderstorm nowcasting. A weak echo region is one of the signatures that could indicate updraft, which is a fundamental condition for hail production. However, this signature is underutilized in automatic forecasting systems due to the lack of a reliable detection method and the uncertain relationships between different weak echo regions and hail-producing thunderstorms. In this paper, three algorithms related to weak echo regions are proposed. The first is a quasi-real-time weak echo region morphology identification algorithm using the radar echo bottom height image. The second is an automatic vertical cross-section-making algorithm. It provides a convenient tool for automatically determining the location of a vertical cross-section that exhibits a visible weak echo region to help forecasters assess the vertical structures of thunderstorms with less time consumption. The last is a weak echo region quantification algorithm mainly used for hail nowcasting. It could generate a parameter describing the scale of a weak echo region to distinguish hail and no-hail thunderstorms. Evaluation with real data of the Tianjin radar indicates that the critical success index of the weak echo region identification algorithm is 0.61. Statistics on these data also show that when the weak echo region parameters generated by the quantification algorithm are in a particular range, more than 85% of the convective cells produced hail.

https://www.mdpi.com/2073-4433/10/6/325/pdf

Radar-Based Automatic Identification and Quantification of Weak Echo Regions for Hail Nowcasting

Commercial prototype building models were developed by the United States Department of Energy (DOE) to analyze the energy savings of the ASHRAE 90.1 standard. However, in the DOE models, occupant behavior inputs were deterministic and the stochasticity of occupant behavior was not fully characterized. This study evaluated the impacts of stochastic occupant behavior on building energy consumption and energy savings analysis from upgrading the ASHRAE 90.1-2016 to 2019 in sixteen climate zones in the United States (U.S.). Three occupant behavior styles (austerity, normal, and wasteful) were defined to represent the different levels of energy consciousness. The DOE medium office prototype models were used as the baseline (normal behavior style). The occupant behavior functional mock-up unit (obFMU) was used to model the stochastic occupant behavior models (austerity and wasteful). The EnergyPlus medium office prototype models were modified to co-simulate with the obFMU models. The results of 16 climate zones were aggregated by the relative construction volume of each climate zone. The results showed that the weighted national annual source energy use intensity (EUI) of the austerity, normal, and wasteful behavior styles were 203.81 kWh/m2, 287.15 kWh/m2, and 388.33 kWh/m2 for ASHRAE 90.1-2016, and 192.43 kWh/m2, 273.48 kWh/m2, and 371.28 kWh/m2 for ASHRAE 90.1-2019, respectively. Compared to the normal behavior style, the austerity behavior style consumed 29% less source energy, while the wasteful behavior style consumed 36% more source energy. From upgrading the ASHRAE 90.1-2016 to 2019, the energy saving percentages based on the austerity, normal, and wasteful behavior styles were 5.59%, 4.78%, and 4.42%, respectively. The stochastic occupant behavior significantly impacted the building energy consumption, and their impacts on the energy savings analysis of upgrading ASHRAE 90.1 were also not negligible.

/pdf/impacts-of-occupant-behavior-on-building-energy-consumption-34u7o4j5.pdf

Impacts of Occupant Behavior on Building Energy Consumption and Energy Savings Analysis of Upgrading ASHRAE 90.1 Energy Efficiency Standards

Impacts of uncertainty in building envelope thermal transmittance on heating/cooling demand in the urban context

Buildings contribute to almost 30% of total energy consumption worldwide. Developing building energy modeling programs is of great significance for lifecycle building performance assessment and optimization. Advances in novel building technologies, the requirements of high-performance computation, and the demands for multi-objective models have brought new challenges for building energy modeling software and platforms. To meet the increasing simulation demands, DeST 3.0, a new-generation building performance simulation platform, was developed and released. The structure of DeST 3.0 incorporates four simulation engines, including building analysis and simulation (BAS) engine, HVAC system engine, combined plant simulation (CPS) engine, and energy system (ES) engine, connected by air loop and water loop balancing iterations. DeST 3.0 offers numerous new simulation features, such as advanced simulation modules for building envelopes, occupant behavior and energy systems, cross-platform and compatible simulation kernel, FMI/FMU-based co-simulation functionalities, and high-performance parallel simulation architecture. DeST 3.0 has been thoroughly evaluated and validated using code verification, inter-program comparison, and case-study calibration. DeST 3.0 has been applied in various aspects throughout the building lifecycle, supporting building design, operation, retrofit analysis, code appliance, technology adaptability evaluation as well as research and education. The new generation building simulation platform DeST 3.0 provides an efficient tool and comprehensive simulation platform for lifecycle building performance analysis and optimization. 

https://link.springer.com/content/pdf/10.1007/s12273-022-0909-9.pdf

DeST 3.0: A new-generation building performance simulation platform

This paper analyzes the radar echo characteristics of the hail clouds in a strong convection which happens on the daybreak of May 1st, 2011 in Chengdu area. It concludes the comparison and analysis of the top height of the radar echoes, the CAPPI(constant altitude plan position indicating) materials of reflectivity in different altitudes and the RHI(range-height indicating) materials of reflectivity in any direction of the radar station that happen in different time. All the work above is for the early identification and warning of the hail clouds in the hail suppression operation to decrease the effect of the hail disaster. The results show that we can identify the hail clouds 15 minutes in advance. Superimposing the geographic information of the 37mm antiaircraft guns operation points over the radar echoes is useful to hail suppression operation.

Xin Zhou

Papers

DeST 3.0: A new-generation building performance simulation platform

An analysis of a hail cloud process and it's hail suppression operation