Building integrated photovoltaic (BIPV) applications are key to increase the share of renewable energy in the built environment. A large potential for BIPV deployment is related to building facades. The assessment of BIPV facades depends on the accurate modelling of exterior convective heat transfer coefficients (eCHTC). However, eCHTC models commonly used in BIPV modelling tend to be simplified. This paper proposes a simulation framework that combines detailed computational fluid dynamics with a multi-physics BIPV model to investigate the influence of eCHTC on the performance of BIPV facades (cell temperature and power). The evaluation is performed for different building geometries, wind speeds, wind directions, solar irradiations, and ambient temperatures. The results show that local variations in eCHTC can cause variations in cell temperature up to 42 °C between the BIPV modules across the facade. These temperature differences are associated with differences in power up to 17% across the BIPV facade. In general, lower temperatures (and higher power output) occur near the edges of the facade while higher temperatures (and lower power output) occur at the middle and at the bottom of the facade. Therefore, a detailed assessment of wind effects is recommended in order to verify the local operating conditions of the BIPV modules. The framework and findings presented in this work are relevant for applications in which the knowledge of the local behaviour is important, such as degradation studies.@en

Building integrated photovoltaic (BIPV) systems provide an opportunity for renewable energy generation in the built environment. In order to quantify the BIPV potential, numerical models of varying levels of complexity have been developed. This paper investigates how the complexity of BIPV models affects their predictions. The study starts with a detailed multi-physics BIPV model that combines a high-resolution one-diode model with physics-based thermal and airflow models. Next, simplifications are introduced into the model. The model predictions are compared to experimental data from a BIPV curtain wall installed in a test building in Leuven, Belgium. The results show that the detailed BIPV model is capable of estimating the BIPV daily energy yield with an average difference of 6.2 % (2.0 % for clear sky days) and the back-of-module temperature with an average difference of 1.74 °C. The use of a linear power model instead of a high-resolution one-diode model affects the average differences, but not significantly: 8.7 % for daily energy yield predictions (4.5 % for clear sky days) and 1.71 °C for temperature predictions. The use of two different empirical temperature correlations instead of a physics-based approach increases the average temperature difference to 3.5 and 4.4 °C. The average difference in daily energy yield increases to 10.2 and 10.4 %, respectively (5.9 and 5.5 % for clear sky days). These findings indicate that the detailed version of multi-physics BIPV model provides the best agreement with experimental data, but it is still possible to reduce the model complexity with acceptable accuracy.@en

To assess the impact of implementing energy efficiency and renewable energy measures, urban building energy models are emerging. In these models, due to the lack of data, the natural variability of the existing building stock is often highly underestimated and uncertainty on the simulated energy use arises. Therefore, this work proposes a probabilistic building characterization method to model the variability of the existing residential building stock. The method estimates realistic distributions of five input variables: U-values of the floor, external walls, windows and roof as well as window-to-wall ratio, based on known data (location, geometry and construction year). First, quantile regression has been implemented to generate the uncorrelated distributions based on the Flemish energy performance certificates database. The accuracy of the marginal distributions is good, as the empirical coverage on the 50%, 80%, 90% and 98% prediction interval deviates 0.6% at most. However, it is needed to include the correlations between these variables. Hence, three main methods to build multivariate distributions from marginal distributions and to draw correlated samples are implemented and extensively compared. The Gaussian copula method is put forward as the preferred method. Considering the mean-maximum discrepancy (MMD), this method performs eight times better than the uncorrelated case (MMD of 0.0027 versus 0.0228).

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With the increasing integration of multiple energy carriers in district energy systems, an accurate simulation of the district energy demand becomes more crucial. To reduce the required computational power, the district energy demand is often quantified through a limited set of archetype buildings, representing the whole district. As the temporal behaviour is important to assess district energy systems, stochastic occupant models should be included in the simulation. However, obtaining representative set-point temperature profiles for archetype buildings is not straightforward, as all buildings respond differently to their demanded set-point temperature due to their thermal inertia. Hence, this paper proposes and compares three techniques to obtain the representative occupant behaviour for the archetype building, by focussing on 847 single-family dwellings. Including a smart occupant aggregation method allows to decrease the percentage error in annual energy demand for space heating between the full and the archetype simulation from around 7.5% to around 2%, depending on the building model and evaluation method.

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Building integrated photovoltaic (BIPV) systems may be catalyzers of sustainable, near-zero energy buildings. To maximize the benefits of employing BIPV, it is important to integrate them properly into the grid of the building. The discussion on AC versus DC distribution for microgrid and nanogrid backbones is currently revisited as the level of penetration of renewable sources, electric vehicles and DC loads is constantly increasing. This paper tackles this question and provides guidelines using a validated simulation framework. The study compares DC (48 V and 380 V) and AC (230 V/50 Hz) topologies integrated into a ten-story office building with façade-integrated BIPV. Annual simulations are carried out for five locations with different climatic conditions and comparisons are made in terms of system- and component-level efficiency, system losses, self-sufficiency, self-consumption and CO2 emission. The analysis shows that the DC topologies perform better than the AC one, especially for the locations with high solar energy yield compared to the cooling and heating loads. Further, a parametric analysis is performed to determine the optimal sizing of the building grid components, DC and AC alike. Finally, different scenarios of battery energy storage system capacity are examined in order to test the sensitivity of the performed analysis.@en

Building integrated photovoltaic (BIPV) is a key concept for the realisation of sustainable buildings. Despite the progress in BIPV modelling, the use of sensitivity analysis (SA) is still scarce in the BIPV literature. SA can help the modeller to identify which model inputs influence the model outputs the most. This paper presents a simulation framework that combines global SA methods with a multi-physics BIPV model. The analysis focuses on the performance of naturally ventilated BIPV facade elements (cell temperature and power). Building performance indicators, such as the total heat flux to the building interior and the building wall temperature, are also analysed. Inputs to the SA include convective heat transfer coefficients, cavity airflow rate, and weather conditions. As expected, the SA results were found to be highly dependent on the range selected for the inputs. For a narrow variation in weather conditions, the exterior convective heat transfer coefficient was identified as the input with the strongest influence on the BIPV performance. Results also showed that cavity ventilation becomes more important as the exterior convective heat transfer decreases. These findings indicate the need for accurate models to represent exterior convective heat transfer in BIPV facades and corroborate the importance of cavity ventilation.@en

Building-integrated photovoltaics (BIPV) is seen as a key technology to reduce the environmental impact and net power consumption of buildings. The integration of PV into building components, such as façade, window, roof or shading elements, leads to a distributed generation over the building envelope with a profound impact on the electrical installation. Designing the electrical system with string inverters and a possible wide variety of module sizes and technologies is a challenging task. To overcome this issue, Module-Level Converters (MLCs) can be used. A supplementary benefit is that the consequences of partial shading can strongly be reduced. This paper investigates whether the current generation of MLCs is suited for embedment in facade BIPV modules. The PV output is categorized and compared to the input parameters of the converters. Besides the discrepancy between the physical dimensions of the converters and the desired installation location, thermal and electrical measurements on a prototype BIPV curtain wall element reveal that daily energy losses can be as high as 50% due to thermal overload when used in a moderate climate such as Belgium. The paper concludes by discussing further standardization of BIPV module-level converters.@en

Building integrated photovoltaic (BIPV) systems are considered a promising solution to increase the share of renewable energy in the built environment. To evaluate the BIPV performance at the building level, the implementation of BIPV models in building performance simulation tools is an essential step. This paper presents the development of a multi-physics BIPV model for the simulation of BIPV facades within the openIDEAS framework for building and district energy simulations. The model couples a high-resolution electrical model to physics-based thermal and airflow models. The combination of these two modelling approaches is not common in BIPV models, particularly for building performance simulations. The model predictions are compared to three months of experimental data from a naturally ventilated BIPV module installed in the facade of a test building in Leuven, Belgium. A good agreement is obtained in terms of both BIPV energy yield and temperature. The error in daily energy yield estimations is on average below 3 % and the error in the monthly energy yield is below 2%. The back-of-module temperature is predicted with a MAE lower than 2 °C and RMSE lower than 5 °C.@en

This paper presents the first steps towards a District Energy Simulation Test (DESTEST), which is part of IBPSA Project 1. The goal is to develop a test sequel for district energy simulations, inspired by principles of the BESTEST. It aims at providing a means to validate District Energy System models. The description of the DESTEST cases and the simulation results of extensively verified models will be available as a reference for verification. By presenting the research plan, goal and first results, the district energy simulation community is informed about the project's intentions, offering a chance for feedback and collaboration.

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European legislation on building performance and energy efficiency pushes the shift towards minimizing the environmental footprint of buildings. Building-integrated photovoltaics (BIPV) is a promising technology that can accelerate the transition to energy-neutral buildings. Quantifying the potential of BIPV is crucial and one means of obtaining those results is through simulation. The state-of-the-art tools offer either thermal or electrical specialization; in particular, balance of system components (BOS) such as power converters have not been studied in detail within the building simulations BIPV domain. In this paper, a multi-physics model of a BIPV integrated DC/DC converter is developed in the Modelica language, taking into account the thermal and electrical couplings inherent to power electronic systems. The model has been validated using representative outdoor BIPV measurements and a DC/DC converter prototype. It has been found that the proposed model provides reasonable accuracy and outperforms an equivalent power conditioning model in TRNSYS. To demonstrate the model’s functionality, two case studies are performed. First, the temperature-dependence of the converter’s efficiency and losses is quantified and analyzed and, second, the prominent contributors to the converter losses are identified and discussed.@en

Abstract: Building integrated photovoltaic (BIPV) systems are considered as a promising technology to achieve low energy buildings. Although a significant body of literature is available on BIPV modelling and validation, sensitivity analysis (SA) has not been extensively explored in a systematic way. SA provides insight on how the model responds to variations on its inputs, being thus an integral part of modelling approaches. In this paper, a variance-based SA is performed to identify the dominant parameters on the performance of ventilated facade-BIPV modules, evaluated in terms of power output and cell temperature. This work uses a multi-physics BIPV model previously validated with experimental data from two BIPV setups. Convective heat transfer coefficients (CHTCs) and parameters associated to ventilation are the inputs to the SA. Results show that the heat transfer to the exterior environment and to the cavity interior have the largest influence on both power and cell temperature. Furthermore, the effects of interactions among the inputs have been found to account for most of the output variability.@en

Building integrated photovoltaic (BIPV) technology has gained attention as a solution to achieve low energy buildings. However, unlike conventional PV applications, BIPVs typically operate at non-optimal orientation, imposed by the building geometry. Moreover, the building integration reduces the heat exchange to the exterior, leading to higher temperatures. This paper investigates the performance of BIPV modules in different locations by simulating a representative office room in a high-rise building having a BIPV facade. The locations considered are Riyadh (Saudi Arabia), Seville (Spain), Naples (Florida, USA), Cape Town (South Africa), and Munich (Germany). The facade is vertical and faces the equator for all locations. Results show the highest annual BIPV energy yield occurs in Seville, followed by Cape Town, Riyadh, and Naples. In terms of monthly yields, the highest values are observed in Riyadh and Seville in wintertime. Monthly yield is more uniform over the year in Munich, while important differences between summer and winter have been obtained for Riyadh. These results confirm the influence of the latitude on the BIPV yield, with equator-facing facades in high latitudes receiving up to 40 % less irradiation compared to a horizontal surface, with important reductions especially in the summer. In these locations, the use of west and east facades may be necessary to achieve a balanced profile over the year. Moreover, the highest average cell temperatures occur in Riyadh, Naples and Seville, while lowest temperatures are verified in Cape Town and Munich, which is consistent with the corresponding ambient temperatures. Finally, with lower BIPV temperatures and relatively high solar irradiation, Cape Town achieves the highest performance ratio (PR) values. Conversely, the combination of high solar irradiation and high temperatures leads to lower PR values in Riyadh and Seville.@en

Building-Integrated Photovoltaics (BIPV) replace traditional building elements with power generating elements through the use of solar cells. One of the targets for this technology is to place the module-level power converter into the photovoltaic module's frame to achieve an integrated system. Temperature is the most influential parameter for a converter's reliability, its damage caused on the components needs to be studied in detail. In this paper, a reliability comparison based on a four-day mission profile has been made in order to assess the most reliable frame position for this converter to be placed in as all of them possess a different temperature profile. The results show that placing the converter in the lateral bottom of the frame is significantly more reliable than the mid or top position. In addition, a lifetime analysis is performed on the converter's dc-link capacitor in order to demonstrate the required methodology. In future work, this can be extended towards other sensitive components when appropriate lifetime models become available. These lifetime estimations can then be combined to achieve an overall BIPV system lifetime assessment.@en