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• A novel MOF-based paper sheet was developed for passive indoor moisture control. • The MOF paper sheet has excellent moisture buffer capacity and mechanical properties. • A numerical model was developed to find the optimal thickness of the MOF paper sheet. • The energy-saving potential of wallpaper made of MOF paper sheet was investigated. Passive indoor moisture control is a meaningful way to reduce HVAC operation and improve building energy efficiency. Metal-organic frameworks (MOFs) have been considered one of the most promising sorbent materials for passive indoor moisture control. However, the powder form of MOF is challenging to use in the built environment. Typical shaping methods like pellets, beads, and coating can lead to problems like partial pore blocking, insufficient mechanical stability, amorphization, and low material utilization. Here, we report a new sustainable MOF paper sheet comprising 25% cellulosic fibers and 75% MOF MIL-100(Fe) powder. The porous polymer matrix provides good support and fixation for MOF particles, so it's more applicable in the built environment. The crystalline and pore structure characteristics of the MOF in the membrane are well preserved. Hydro characteristic test results show that MIL-100(Fe) paper sheet has high water vapor uptake, S-shape isotherm, mild regeneration condition, and high MBV. Then, a numerical model was developed to calculate the relation between a material's MBV and its thickness. MIL-100(Fe) paper sheet with the most efficient thickness was applied as wallpaper in a building energy simulation model. The simulation result shows that the MIL-100(Fe) paper sheet is promising for passive indoor moisture control. It can remove about 45%-55% of the latent cooling load in most European climate types. [ABSTRACT FROM AUTHOR]

As the built environment is among the main contributing sectors to climate change, it is needed to investigate new paradigms to push decarbonization efforts towards the ambitious objectives defined internationally. It is a shared understanding that shifting the perspective from the single building to the district perspective is required to fully take into consideration the complexity of all interactions undergoing within the built environment, thus the concept of Positive Energy District emerged as a district with annual net zero energy import and net zero CO 2 emission working towards an annual local surplus production of renewable energy. In this framework, this paper explores the investigation of the potential for achieving the level of Positive Energy District in a group of non-residential buildings in Balaguer, Catalonia, Spain. These buildings, occupying 8,825 m2 in the city centre, require significant refurbishment for improved energy performance. The analysis includes building energy modelling and simulation, renovation studies, several alternative balance calculations, and carbon emissions assessment. The paper also considers mobility and embodied energy and their impact on energy/carbon balances. The results show that Positive Energy Districts carbon and primary energy balances are not met with rooftop PV installations when retrofitting an existing district towards the Positive energy target but further significant PV areas (roughly + 50%) are required to meet merely the use stage balances: negative results are traced when mobility and embodied energy are computed. A formulation alternative to the simple mathematical balance to facilitate the diffusion of Positive Energy District as catalyst of urban decarbonisation could be needed, including context factors and alternative systems (e.g., rating systems). [ABSTRACT FROM AUTHOR]

Bayesian calibration of building energy simulation (BES) has gained growing attention for its capability to tackle uncertainties and narrow the gap between simulated and measured results using expert knowledge. However, how output or parameter correlations influence single-output Bayesian calibration (SOBC) and multiple-output Bayesian calibration (MOBC) for BES has not been investigated and compared. Hence, this paper intends to determine the impacts of output or parameter correlations and data informativeness on BC of BES. Aiming to leverage multiple outputs' correlations while comparing with traditional SOBC in calibration performance and computation cost, we also developed the MOBC model. Compared to including weakly correlated outputs or parameters, the results show that strongly correlated outputs or parameters in MOBC reduce the Coefficient of Variation of the Root Mean Squared Error (CVRMSE) by 5.56% and 4.729% respectively and bring notably better Continuous Ranked Probability Score (CRPS) results. Conversely, including strongly correlated parameters in SOBC causes worse model performance. These results reflect that SOBC has parameter identifiability issues that MOBC can solve. The findings contribute to our better understanding of the impacts of (1) output or parameter correlations and (2) different data streams' informativeness on the calibration performance of SOBC and our developed MOBC for BES. • Employed multiple-output Bayesian calibration (MOBC) on building simulation. • Quantified the impacts of parameter and output correlations separately. • More data does not mean better building energy model calibration performance. • The single-output has parameter identifiability issues, which MOBC can ease. • Output/Parameter correlations can be exploited by MOBC for better performance. [ABSTRACT FROM AUTHOR]

In the era of post-Coronavirus Disease 2019, the dedicated outdoor air system (DOAS), which provides 100% outdoor air for the building, is widely acknowledged as it can ensure acceptable indoor air quality by delivering fresh outdoor air to occupied space. The DOAS with a proper design and operation can provide sufficient ventilation and dehumidification while achieving energy efficiency. Nonetheless, there is limited guidance in determining the optimal control sequence of the DOAS for the designers and operators to implement in practice. Accordingly, in practice, a number of issues have been acknowledged in the design and control phases of DOAS, including insufficient ventilation and dehumidification, and increasing supply air dry-bulb temperature in fear of over-cooling, which might cause significant discomfort and energy waste. There have been efforts to develop high-performing DOAS controls for better energy efficiency. However, such controls are often complex, or difficult to interpret, for building designers and operators to consider in practice. In this regard, this paper explores a simulation-based framework for generating a supply air temperature control sequence of the DOAS not only to ensure improved energy-saving potential but also to guarantee the implement-ability of the control logic. The U.S. Department of Energy prototype primary school with dynamic occupancy profiles was modeled with a whole building simulation program, EnergyPlus. The model consists of a DOAS with an exhaust air energy recovery system for ventilation and fan-coil units for space cooling and heating. Then, a Genetic Algorithm was adopted to find the true optimal supply air temperature control sequence in terms of minimizing the energy cost of the heating, ventilation, and air conditioning system operation. Lastly, Decision Tree was adopted to extract rules out of the optimums to derive an implementable sequence of operation for the DOAS supply air temperature. A total of 12 week-simulation including four weeks of heating, cooling, and shoulder seasons, separately, under the weather condition of New York City was conducted for the case study. This case study identified that the optimization-informed rule extraction-based control, when compared to conventional outdoor air temperature-based reset control, could save about 13% of energy cost and 25% of energy consumption throughout the heating, cooling, and shoulder seasons. It is notable that the energy-saving was mainly achieved by reducing the heating energy consumption. Importantly, it nearly corresponds to the true optimal control result, which reduces approximately 14% of energy cost and 27% of energy consumption. From the results, it can be highlighted that the optimization-informed rule extraction can be as energy effective as the optimal control, while significantly reducing the complexity of the control. [ABSTRACT FROM AUTHOR]

This paper evaluates a parametric analysis towards compliance with the nZEB standard, which in Spain is defined by the latest update of the Technical Building Code. This regulation is critically assessed regarding its ability to promote the concept of cost optimization, promote renewable energy sources and minimize primary energy consumption in the residential sector. To this end, a virtual building was defined and multiple designs were evaluated using DesignBuilder software. A set of 170 alternative scenarios was established and parametrically evaluated for five cities representing the five climatic zones of inland Spain (Bilbao, Burgos, Seville, Madrid and Almeria). The results were evaluated focusing on cost-cost effectiveness and primary energy consumption values for the different scenarios, evaluating them in relation to the minimum requirements set by the regulation. The great potential of photovoltaic energy is highlighted, which allows negative values to be obtained for the two Equivalent Uniform Annual Costs due to the cost avoided through self-consumption. This fact makes the optimal designs tend to electrification, specifically through air and ground source heat pumps. It is worth mentioning that the new Code has only established a minimum target for renewable self-consumption in the residential sector, which should be reinforced in future updates. [ABSTRACT FROM AUTHOR]

School buildings have a great potential for carbon emission reduction since their annual emission is about 72 million metric tons. Currently, more than 30 % of school buildings were built before 1960 and are underperforming. To effectively reduce carbon emissions via school building retrofits, it is critical for policymakers to understand the carbon intensity reduction potential of retrofitting school buildings in different regions. Hence, this study develops a method to comprehensively assess the long-term carbon intensity reduction potential of aggregated commercial buildings on a county-by-county basis in the continental U.S. We apply this method to the K-12 school buildings including primary and secondary school buildings. This paper predicts the carbon intensity reduction potential of K-12 school buildings with eight building retrofit measures from 2022 to 2050 in the continental U.S. The results reveal several interesting findings: (1) In the approximately 3,000 counties of the U.S. from 2022 to 2050, the carbon intensity reduction potential of retrofitting K-12 school buildings in each county ranges from 0.41 kg/m2 to 40.00 kg/m2. (2) Even in the same climate zone, the trends of carbon intensity reduction potential from 2022 to 2050 are different depending on their electricity sources. For example, in a hot and humid climate zone, the carbon intensity reduction potential in Florida will decrease from 2044 to 2048. However, in Mississippi, the carbon intensity reduction potential from 2044 to 2046 will increase due to the termination of the nuclear energy usage. (3) Generally, reducing lighting power density leads to more carbon intensity reduction in most states, but it might not be applicable for states with high clean energy penetration, such as Washington. [ABSTRACT FROM AUTHOR]

• Time Use Survey data used profiles of occupancy and energy behaviours. • Patterns were time-dependent and affected by household size. • Behaviour patterns were aggregated to produce hourly energy demand profiles. Occupants' interactions with building components determine the timing and magnitude of energy demand. Therefore a more realistic representation of energy-related occupant behaviours in energy simulations will enhance the accuracy of predicted building energy demand. The aim of this paper was to assess occupancy and behavioural patterns in Australian households based on a detailed time use survey, which collected daily activities from 6,902 persons in 3,626 households. Profiles of occupancy state and energy-related activities were analysed for different seasons, day of the week, and household compositions. The activity sequences were further aggregated to reproduce the total time use for the activities and occupancy states. The results showed that occupancy and the timing of energy related activities were time dependent and were also affected by season, day of week, and household composition. The outcomes can be used as input to simulation tools where realistic occupant behaviour should be taken into account. [ABSTRACT FROM AUTHOR]

Outdoor thermal comfort (OTC) directly impacts on health and wellbeing of inhabitants while it increases cooling energy demand of buildings. In this regards, different computational models and tools are developed to investigate the impact of built environments on pedestrian thermal comfort. However, in most of these models, the coeffects of solar radiation and local wind velocity are not simultaneously investigated where models are either simplified on solar calculations when are focused on wind or vice versa. This paper proposes a novel simulation framework to develop a high-resolution, but computationally efficient procedure, to couple radiative and convective fluxes in outdoor environments using computational fluid dynamics (CFD) and building energy simulation (BES) approaches. The workflow is implemented in Grasshopper platform fed by outputs of ANSYS-Fluent as the CFD tool and EnergyPlus as the BES tool. The performance of the framework is evaluated using a case study, representing a simplified neighbourhood on a typical hot day. In comparison with the traditional models, results highlight on a considerable change in the OTC values using the proposed model. Results show that the alteration is highly related to the temporal aspects and OTC results experience changes from 5% to 40% in compared to the original OTC values. [ABSTRACT FROM AUTHOR]

[Display omitted] Improving the performance of building envelope is essential to energy conservation and emission reduction. Adaptive building envelope (ABE) has the potential to effectively reduce building energy consumption at a lower cost. Movable window insulation is an instantiation of the ABE with great application potential in buildings, but it has not been systematically studied. Trying to fill this gap, this paper proposes an automatic control system and a manual control rule for movable window insulation. The energy consumption of double-glazed windows, triple-glazed windows, movable insulation with automatic/manual control, and electrochromic windows is compared in different scenarios using building energy simulation (BES). In some scenarios, the optimal solar heat gain coefficient (SHGC) for windows with movable insulation is higher than that required by the building code. Triple-glazed windows are only effective in reducing the heating energy, while electrochromic windows are only effective in reducing the cooling energy. Infiltration has a great impact on the performance of movable insulation. The net preset value (NPV) analysis shows that movable insulation has a great application potential in Minneapolis, Atlanta, and Phoenix, while triple-glazed windows are only viable in some cases in Minneapolis. Electrochromic windows are not a profitable investment at their current prices. [ABSTRACT FROM AUTHOR]