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Facing the challage of energy conservation and emission reduction in the building sector, most energy saving strategies of central heating only focus on the performance improvement of building envelope, ignoring the impact of energy use behavior. This paper proposed a building energy conservation strategy based on energy use behavior analysis, which provides a perspective for in-depth exploration of building energy conservation. After investigating a typical university in the northern China, the energy use behaviors were characterized and two different DeST energy consumption models before or after considering energy use behavior were established. By comparing the results calculated by these two models, the impact of energy use behavior analysis on building energy consumption was quantitatively analyzed. The results show that the heating energy consumption and carbon emission can be reduced by 23.28% and 23% respectively through the proposed strategy based on energy use behavior. Therefore, the analysis of energy use behavior can provide a theoretical basis for heating operators to make decisions on energy supply regulation. With central cooling and heating further popularizing in the future, the research methodology of this paper has more extensive reference value for energy conservation and emission reduction strategies in the building sector. [ABSTRACT FROM AUTHOR]

Abstract Numerous occupant behavior models, typically stochastic ones, have been built to quantify the effect of occupants on building energy simulation, which however are supposed to go through a rigorous validation, or evaluation process to claim that they are qualified to be used in the application. Current contributions relevant with occupant behavior modeling in literature have been resorting to statistical metrics rather than those orienting on their application, causing the disputation in interpreting the accuracy of the occupant behavior models when they are actually used in simulation. Furthermore, the stochasticity of occupant behavior models necessitates statistical evaluation of the model accuracy, instead of the comparison between actual data and a single-run simulated data. This paper proposes a methodological framework for model evaluation from an application-oriented perspective, with lighting behavior as a case study. The metrics for evaluating lighting behavior models are identified according to different application scenarios, while the comparison between the measurement and simulation is done by introducing the statistical hypothesis testing. Analogous analyses on other behaviors can be conducted in the future, which altogether would foster more rigor and application significance in occupant behavior model evaluation. [ABSTRACT FROM AUTHOR]

• The resilience of a building designed to be nearly zero energy is evaluated in Mediterranean climate. • Weather file defined with monitored data are used for a short-term analysis. • Projections of climate changes are considered in the construction of weather files. • The net primary energy will decrease (–23%) and the in-situ renewable adoption will increase (85%). • Overheating will occur in the intermediate months with the need to turned on the cooling system. The paper is focused on the evaluation of how the climate changes can influence the performance of buildings designed to be nearly zero energy (nZEB) and on the evaluation of the resilience in term of energy balance. A real case study is used; it is named BNZEB, a single-storey dwelling built in Benevento (South Italy, Mediterranean climate). With five-years monitored meteorological data, both a short-term and medium-term analysis is developed; the first one consists in the evaluation of the energy behavior compared to the first operating year. Then, the energy performance is evaluated considering the medium-term climate projections generated using the CCWorldWeatherGen tool. This analysis, with reference to the case study, suggests to designers and researchers that, in a typical Mediterranean climate, the reduction of the heating demand could compensate the increment in the cooling request. In the worst climatic scenario, the net primary energy could change from 25.4 kWh/m2 year (first year of life, 2017) to 19.5 kWh/m2 year (projection to 2050) with a rate of self-consumption of 85% (80% for 2017). However, a critical point is the operating period of the cooling system. Indeed, an indoor overheating problem could occur during the spring with operative temperature higher than 30 °C; this indicates that in future, the occupants will require higher number of operating hours with most frequent switch off. This could change the results of the energy balance, reducing, for instance, the imbalance between production and consumption that currently occurs in the intermediate periods. [ABSTRACT FROM AUTHOR]