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Energy consumption in buildings accounts for up to 40% of total energy consumption. In an effort to improve energy and environmental sustainability, buildings have been the target of a number of energy demand reduction strategies. Occupant behaviour in buildings is a key factor that significantly influences the energy consumption of buildings. Whilst researchers have focused considerable effort into understanding and developing strategies that address the impact of occupant behaviour on building energy consumption, the high-energy demand of buildings is considered a useful source of demand-side energy flexibility for the smart-grid. In addressing the influence of occupant behaviour in buildings. In harnessing the energy flexibility potentials of buildings, building energy management systems play a vital role. Traditional building energy management systems are however static and lack input of dynamic factors such as occupancy as well as occupant preference. In addition, traditional building energy management systems are limited in their ability to optimally coordinate the use of buildings energy flexibility without compromising occupant comfort on the room-level.

Modern buildings nowadays provide an enormous data now available from various sources ranging from modular wireless sensors to smart meters, analytics of these data can enhance the management of energy systems (electrical storage, PV generation, heat storage etc). Using Big Data combined with deep learning techniques offers new possibilities to better predict energy use and decentralized renewable energy production (e.g. from local weather data taking into account local phenomena such as urban heat islands). This combined with a more bottom-up approach of multi-agent systems with a gossip-based cooperative approach offers decentralized control and monitoring autonomy to further reduce the complexity of the energy system integration and makes it possible to relate the outcomes of the integral approach for urban energy system integration.

Highly glazed building envelopes are still a common feature of today's modern architecture despite the on-going raging debate on the energy and comfort performance of highly glazed buildings. It is argued by proponents of high performance and green building designs that the disadvantages of highly glazed buildings outweigh the advantages when operational. In this study, through on-site measurement and simulations, we investigated the behaviour of a recently completed naturally ventilated double-skin façade system at a building in the netherlands with a complex form and a large atrium connecting it to the core of the building. This in a way coupled with the exhaust ventilation of the offices within the building created a problematic thermal indoor environment. It was shown that the dynamic behaviour due to the large influence of the wind fluctuations and solar radiance proved to be highly complex resulting in discomfort and a higher cooling load.

Electrical energy generation and its supply through electricity networks are mainly organized in a top-down, centralized manner. Energy consumption can be predicted quite accurately at a high level which enables to pre-scheduling of production by large power plants. Traditionally, only few actors are involved in the generation, trade, and transportation of electricity, but this is changing rapidly. The increasing share of decentralized renewable energy conversion in combination with new types of buyers and suppliers will drastically alter the operation of electricity infrastructure systems. It has to become smart: the Smart Grid or more general Smart Energy System. In order to minimize uncertainty in the balance between energy supply and demand it is necessary to develop realistic user demand, building and building services installations behavior and Smart Grid interaction. Monitoring the needs of individual users is necessary to predict future states of the demand for the SES (e.g. based on user behavior). The future consumer of energy can become a producer due to the decentralized renewable energy conversion. To control this dynamic and interactive prosumer process support is needed to optimize interaction between offices and Smart Grid. The article describes the first steps towards such system

Occupant behaviour has been shown to have a large impact on the energy consumed in buildings than other thermal related process. For worthwhile energy savings, it is therefore crucial that occupant behaviour be included in the process control of building systems. For this set of control objective with the user central in the control of building systems, it is most important to detect the individual user on a specific workplace within a time span of minutes because the inertia of the building systems is in this order of his magnitude. The indoor occupancy detection system should be able to detect every individual in a spatial area and to be able to track and trace the person. Therefore an indoor occupancy detection and positioning system is being designed which, can communicate with a Building Energy Management System (BMS). The results of a first experiment are described in this paper.

Building process control without including the occupant behaviour is a sub optimal solution. New developments are ongoing to develop energy efficient control strategies to include human behavior and especially occupancy in the process control of buildings. This paper presents a short overview of available technologies for integrating occupancy in building operations. Initial results from the implementation of one of these technologies in an office building are presented as well as the framework for the use of a more intelligent multi-agent based building energy and comfort management system to achieve worthwhile energy reduction.

in tekst

Various control strategies have been adopted to improve energy efficiency in commercial office buildings, particularly the alignment of energy consumption for space conditioning and lighting patterns with human occupancy. Considerable uncertainty however exists in these patterns but advancement in information and communication technology (ICT) has made it possible to reduce these uncertainties. More fine-grained building occupants information can now be gotten in real-time for dynamic demand-driven space lighting and conditioning controls. In this paper the performance of one of such technologies; radio frequency identification (RFID) system is accessed in the determination of human occupancy and location from experiments carried out in a typical office building in the Netherlands. The correlation between energy use by office appliance and human occupancy was also investigated. Furthermore, steps that could be taken to improve energy consumption for comfort through a demand-driven process control strategy are identified.