IBPSA2015

As the climate warms, the frequency and scale of extremely hot events are likely to increase. This study predicts overheating risk for the city of Sheffield, UK at a spatial resolution of 5km when the diurnal Urban Heat Island effect is included. Local Hot Summer Years for current and future years are introduced based on the outputs from the UK Climate Projections weather generator. It is found that overheating risk in the urban sites is higher than the adjacent sites and the discrepancy increases with changing climate.

Among passive strategies to reduce energy consumption in buildings, we focus on natural ventilation, which can bring an important decrease in temperature during summer depending on climate. Despite its simplicity, it needs particular attention to be efficient and can be improved with building control. In this paper, we focus on a simplified thermal model based on an electrical analogy (6R2C), coupled with a statistical airflow model and calibrated for a residential building in Mediterranean climate.

In this paper, predictive models are developed to enable the application of model predictive control (MPC) to naturally ventilated buildings. The essential component of an MPC strategy is the predictive model of the building’s thermal dynamics, which is the focus of this study. An empirical approach is taken using multilayer perceptron (MLP) neural network models. The models presented were generated using data gathered from real buildings during operation and building simulation data generated using EnergyPlus.

Most controllers in Heating, Ventilation and Airconditioning (HVAC) applications remain the Proportional-Integral (PI) type. Poorly performing control loops is a common issue, resulting in wasted energy, reduced occupant comfort, and excessive and unnecessary wear of actuators. In this paper, different methods are evaluated for assessing the controller performance in HVAC applications. Each assement method is evaluated statistically using the simulation data from Modelica based heating and cooling coil models, which denote the good and two bad controls.

Residential and commercial buildings use nearly 75% of the overall electrical energy in the U.S., and the amount of renewable energy in the grid keeps increasing. Buildings can be an important contributor to ensure a stable grid operation because they can shift their loads to reduce peak demand and flatten the ramps of load increase and decrease. Simulation models that account for building loads and building dynamics, as well as their impact on the electricity distribution grid, are essential to assess different design and control options for buildings and electrical systems.

For building performance simulations of multiple buildings, varying objectives and data availability lead to different requirements for various model applications. Flexibility regarding spatial discretization, parameterization and process automation can offer an alternative to specifically tailored models for each application. We present adaptive low order thermal network models with variable discretization regarding number of zones, number of wall elements and wall discretization.

Where modern buildings are unable to maintain the internal environment to within comfort levels they often rely on mechanical systems to become habitable. This could be due to bad design or putting the building in an environment for which it is not suited. Due to climate change it is likely that all buildings will in effect and time be moved to an environment for which it is not suited. In this work the effects of changes in climate on the internal environment will be explored and an index to define how moveable a construction might be, will be developed. 

Utilizing building performance feedback as part of the preliminary design process can suggest environmentally responsive strategies and inform subsequent architectural development. This paper will outline a workflow that utilizes an integrated set of parametric design tools to simultaneously evaluate an exterior solar screen under multiple performance criteria, such as daylighting, visual comfort, energy, peak cooling, and shading effectiveness.

In this research, we look for a control strategy of the electrochromic windows, depending on the measurement of the vertical outdoor illuminance and the outdoor temperature, for an efficient highly glazed office building in Brussels. We simulate this building in TRNSYS. We implement a Perez model in TRNSYS to assess the vertical diffuse outdoor illuminance. As the building is equipped with a dimmable lighting system, we assess the average indoor illuminance. We simulate the switching dynamics of the electrochromic window and we implement a control strategy.