English

This paper presents the Key Factors methodology that supports energy managers in determining the optimal building operation strategy in relation to both energy consumption and thermal comfort. The methodology is supported by the utilisation of calibrated building energy simulation models that match measured data gathered by an extensive measurement framework. The paper outlines the proposed methodology defining the underpinning concepts and illustrating the performance metrics required to capture the effect of different building operation strategies.

The present work focuses on investigating ways to enhance the energetic performance of buildings i.e. on proposing control strategies for managing energy in buildings. Therefore, control algorithms were tested using a prototype, composed of a building mock-up, a monitoring system and a data post-treatment software. The data acquisition system allows recording both mock-up indoor/outdoor temperatures and energy consumption. Two resistors serve as renewable and fossil fuel energy sources respectively.

In a simulation-powered building systems control approach, presently available control options are virtually projected onto a future time step via numeric simulation. Subsequently, the respective (performance-relevant) consequences are predicted, compared, and ranked, thus providing the basis for optimal control actions. A proof of concept for this approach has been presented in previous research.

The necessity of innovation on the field of renewable energy systems imposes on the industry to develop faster and faster new products or product assemblies while managing perfectly the quality of the products. In order to accelerate this process, a first version of a dynamic emulation test method has been developed. Since the test bench emulates the building that is connected to the system being tested, the test can be carried out under “quasi”-realistic, dynamic conditions: dynamic weather conditions and occupancy profiles are used as well as a simulated building and heating/cooling syste

ESP-r is a powerful tool for simulating building environments and their various mechanical and electrical systems. It has potential for investigating and optimising the thermal performance of enclosed areas of ships and other ocean vessels. ESP-r allows the various elements of an environment such as geometry, topology, occupancy and ventilation systems to be considered in a dynamic, integrated manner.

The paper deals with the use of computer simulations both for the design support of a new buildings and HVAC system development and for the optimisation of the system control strategy in the building.

A detailed model for the simulation of boilers using oil, gas, pellets or wood chips has been developed and compared with measurements. Approaches of different complexity for the simulation of steady state flue gas losses were tested. The more physical approaches are able to reproduce measured data better than the simpler empirical models, but they also require more model parameters to be determined and a higher simulation effort. Cycling behaviour of the simple one-node thermal mass approach of the model was compared with measured cycling behaviour of a pellet boiler.

Integrated performance simulation of buildings and heating, ventilation and air-conditioning (HVAC) systems can help reducing energy consumption and increasing level of occupant comfort. However, no singe building performance simulation (BPS) tool offers sufficient capabilities and flexibilities to accommodate the ever-increasing complexity and rapid innovations in building and system technologies. One way to alleviate this problem is to use co-simulation.

For engineering applications one-dimensional models of urban ponds are suitable in order to assess the energy potential for heating and cooling of buildings. This paper presents an intercomparison of two of such models, together with in-situ measurements. Water temperatures are presented for a period of 13 diurnal cycles, as well as an inter-comparison between the heat fluxes of the two models. Stratification effects are shown by the Richardson numbers. Both models are applicable for assessment of the energy capture potential, despite different models for the heat fluxes.

Schumann solution for the heating (cooling) of onedimensional packed beds by the passage of a hot (cool) fluid is extended by the incorporation of a small solid thermal conductivity by means of using  perturbation methods based on the Laplace transform and a Picard iteration for the Green’s functions for the heat transfer of both phases.