IBPSA2003

In the mid 1980s the monolithic nature of building energy simulation programs led to proposals for development of so-called "kernel systems," i.e., software environments that would make available to developers basic software modules and a supporting framework that could be used to construct new building simulation software. One of the outcomes of the ensuing work was the Simulation Problem Analysis and Research Kernel (SPARK).

Simulation exercises covering long periods (e.g.. annual simulations) can produce large quantities of data. The result data set is often primarily used to determine key performance parameters such as the frequency binning of internal temperatures. Efforts to obtain an understanding for reasons behind the predicted building performance are often only carried out to a limited extent and simulation is therefore not used to its full potential.

The objective of this paper is to present an analysis of the weather data contained in a Typical Meteorological Year (TMY) and observe the effect of these data on the simulated load of a typical building. The weather data, contained in the TMY, are analysed with respect to the global and diffuse radiation falling on surfaces facing the four orientations, ambient temperature, wind speed and direction, and humidity ratio.

Agency Annex 35 “Hybrid Ventilation in New and Retrofitted Office Buildings”. It consisted in modeling a typical classroom and in predicting performance of a hybrid ventilation system compared to two traditional mechanical systems: a mechanical exhaust ventilation system and a balanced ventilation system. The hybrid system considered here was a fan assisted natural ventilation with a temperature and CO2 based control strategy.

A simulation methodology has been created for establishing the impact of increasing the insulation of the building envelope upon its global thermal performance and annual energy consumption (heating plus cooling). A particular emphasis is placed upon the consequences in terms of increased temperatures in summer leading to needs for installation of airconditioning. This will provide an important input for the revision of the Portuguese thermal regulations for buildings.

This paper presents the results of an empirical study to establish if and to which extent professionals in design community are familiar with and use building performance simulation applications. A total of 198 architects in Austria participated in this study, answering questions regarding their familiarity and experiences with performance simulations tools, problems they have encountered, and their suggestions toward improvements of such applications.

In order to reduce the environmental load (energy and materials) of buildings, a study was undertaken to develop and assess solutions for a dynamic, weather and daytime adaptable office façade. The following steps have been taken:

Conventional building control systems usually apply central control schemes that do not fully address individual occupancy differences in built environmental requirements. Recent application of personal control modules in commercial buildings presents a bi-lateral control scheme, in which a building operator and an occupant can both control the occupant’s local environmental settings, e.g., lighting, heating, cooling, and ventilation, etc. While personal controls may enhance individual comfort, they may also neutralize operators’ cost-saving efforts.

For many buildings, continuous operation of the air conditioning system is not necessary for achieving thermal comfort during the occupied periods. Depending on the building's thermal and operational characteristics the air conditioning system may be operated during a specific period of time that may partially or completely cover the occupancy period. In this case, a considerable amount of energy can be saved without compromising comfort conditions provided that the correct operation strategy is implemented.

The paper presents the advanced use of S-Functions, facilitated by the Matlab/SimuLink environment. An existing indoor climate model is implemented in an S-Function, consisting of a continuous part with a variable time step and a discrete part with a fixed time step. The heating systems, including a heat pump, an energy roof and thermal energy storage (TES) are modeled as continuous systems using SFunctions. All presented models are validated. The advantages of S-Functions are evaluated and it demonstrates the powerful and flexible use of MatLab/SimuLink.