Gert Boxem’s research while affiliated with Eindhoven University of Technology and other places

Occupant behaviors influence the energy consumption of dwelling mechanical ventilation systems significantly. There is still a lack of effective method to analyze the occupant behaviors in adjusting the mechanical ventilation systems in buildings. Therefore, this study proposes a data mining-based method to reveal the occupant behavior patterns and the motivations behind. A first derivative Gaussian filter-based approach is developed to detect when an occupant increases or decreases the mechanical ventilation flowrate without direct measurements. A logistic regression-based statistical analysis approach is developed to find the crucial factors influencing the behaviors of increasing and decreasing ventilation flowrate. A K-means clustering-based analysis approach is introduced to further find the motivations behind the behaviors. The proposed data mining-based method discovers the ventilation behaviors and the crucial factors influencing them successfully for the occupants from the 10 dwellings located in a Dutch community. The motivation patterns of the ventilation flowrate adjustment behaviors are further revealed based on the discovered crucial factors. The discovered insights are useful to provide more accurate assumptions and inputs for the mechanical ventilation system models. It is also helpful to generate tailored design, refurbishment and control strategies.

Increasing demand for energy and emphasis on environmental sustainability has started to revolutionize the existing energy infrastructure within the built environment. In parallel, more distributed energy systems are rapidly springing up. These changes inevitably influence the design, operation and management of buildings. Recently, the energy and environmental evaluation of buildings for long-term decision-making and planning has shifted the boundaries from single buildings towards neighborhood scale. This is because buildings as a cluster can enhance the incorporation of distributed energy systems when realizing energy neutrality in the long run. However, when assessing the energy and environmental performance of infrastructural developments at the neighborhood level, the life-cycle aspect of energy systems is rarely considered. To understand the overall impacts from production to end-of-life stage, it is essential to assess the energy and environmental performance of clean energy initiatives from a life-cycle perspective. This paper proposes a novel decision support methodology by means of life cycle performance design-based approach to facilitate the planning process to realize energy neutral neighborhoods. The assessment methodology is developed based on scenario analysis through computational simulations. This is followed by a deterministic evaluation and the results let the decision-makers to select a suitable clean energy development scenario. The uncertainty of the selected scenario is scrutinized by performing a probabilistic sensitivity analysis using Monte Carlo simulations. A pragmatic case study has been analyzed and the results demonstrate the feasibility of exercising the proposed methodology in practice. The recommendations and limitations of realizing energy neutral neighborhoods are depicted subsequently.

Occupants’ behavior could bring significant impact on the performance of built environment. Methods of analyzing people’s behavior have not been adequately developed. The traditional methods such as survey or interview are not efficient. This study proposed a data-driven method to analyze the occupants’ behavior, supported by a specific case of analyzing people’s adjustment to ventilation system in a Dutch community. In the individual level, to analyze the motivation of a single person, a logistic regression based approach was proposed to classify occupants’ behavior of increasing/decreasing the ventilation flowrate and then reveal the motivations behind. In the community level, the behavior motivations derived from different occupants were compared. Three motivational behavior patterns, namely the environment-driven type, the time-driven type and the mixed-type were summarized. The proposed mining method is useful to discover and develop occupant behavior models.

Using the flexibility within energy generation, distribution infrastructure, renewable energy sources, and the built environment is the ultimate sustainable strategy within the built environment. However, at the moment this flexibility on the building level has yet to be defined. The new IEA Annex 67 is just starting to define this specific flexibility. Our research is aimed at developing, implementing, and evaluating new process control strategies for improving the energy interaction within a building, its environment, and the energy infrastructure by effectively incorporating occupant needs for health (ventilation) and comfort heating/cooling. An integral approach based on general systems theory is used that divides the whole system into different layers from user up to centralized power generation. A bottom-up approach, starting from the user up to the smart grid, offers new possibilities for buildings’ energy flexibility. To make use of the dynamic possibilities offered by the flexibility, new intelligent process control concepts are necessary. Multiagent systems, in combination with building energy management systems, can offer the required additional functionalities. The approach is tested in a case-study building.

The transition from the traditional electrical power grid to the smart grid calls for a paradigm shift to accommodate bi-directional flow of power, information and the use of available useful flexibility between consumers, their buildings, and the grid. As buildings are considered a potential source of demand side flexibility it therefore becomes paramount that measures be put in place to ensure the useful building flexibility is delivered to the smart grid. However, this should be done without compromising the traditional functionality of buildings, which includes safety, thermal comfort and maintaining an acceptable indoor air quality. In this paper, through a systematic review of relevant literature, requirements for coordinating the interaction between building’s useful energy flexibility and the grid are outlined. Secondly, based on performance analysis and measurements from an averaged sized test case office building, the useful flexibility for grid services is quantified. Thirdly, an autonomous coordination framework for leveraging the useful demand side flexibility from buildings is proposed.

Due to their significant energy demand, buildings are critical in efforts towards attaining the much needed operational flexibility in electrical power grid occasioned by increased decentralized renewable energy integration. In a departure from past studies which are often biased towards power systems performance, this paper presents key building performance implications when used within the context of electricity demand-side management (DSM) programs to provide power systems flexibility services to the smart-grid. Focusing on office buildings and using an average-sized office building as test-bed, their potential as a source of demand-side flexibility in terms of building specific parameters such as power demand, energy consumption, limits of operational flexibilities, systems’ response times, indoor comfort, comfort recovery time and availability are evaluated and discussed. Analysis of field study data demonstrates that office buildings could effectively serve as a source of power flexibility. However, variation in indoor air quality and thermal comfort performance across various zones within the building may complicate estimation of demand side flexibility potential, its acceptability and operation at building level. This emphasizes the need of taking into consideration case study based specifics when using buildings to service power flexibility requirement.

Electricity 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, and this forms the basis for prescheduling the production by large power plants. 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 the new types of consumers will drastically alter the operation of electricity systems. Office buildings will become a potential source of energy flexibility which can be offered to the grid as a virtual power plant (VPP). In order to minimize uncertainty in the balance between energy supply and demand, it is necessary to develop realistic user behavior, installations behavior, and smart grid interaction. Monitoring the needs and preferences of users is necessary to predict future states of the demand for the smart energy systems (SES; e.g., based on weather forecasts and user behavior). The consumer of energy can become a producer due to the decentralized renewable energy conversion. To control this dynamic and interactive process automated prosumer support is needed to optimize interaction between offices and the smart grid. The chapter describes the first steps towards such systems.

In the changing electricity power supply chain, demand response from buildings is a crucial control resource. Whereas numerous studies exist on peak load reduction activities using buildings, few represent building side perspectives. The result is oversimplification of analyses and a near silence on building side considerations. This study uses the building centred productiveness concept to analyse demand response potential of zonal set point temperature operation strategies for a cooling system of an office building during summer. The analysis is based on virtual tests using HAMBase/Simulink simulations validated with onsite measurements in July and August 2013. Findings indicate most promising potentials for zonal set point temperature operation strategies that incorporate forced free cooling during lunch break. For ambient temperature up to 35 °C, productivity loss for the most thermally exposed building zone remain below 10% for validated simulations if zonal set point temperature operation strategy incorporate forced free cooling at lunchtime. The study makes a specific contribution in cost effective evaluation of peak load reduction potential when using zonal set point temperature operation strategies during cooling operations for office buildings. Index Terms-peak load reduction, cooling system, productiveness, buildings, zonal set point temperature.

Toward efforts to improve sustainability of energy supply and to achieve worthwhile reduction in greenhouse gas emissions, in addition to the increased use of renewable energy sources in buildings, more emphasis is being placed on the need for improved control, management and coordination of building operations and its interaction with the smart-grid. Multi-agent system (MAS), due to its distributed and autonomous properties is considered a viable tool for improving the coordination and management of interactions between buildings and components of the smart-grid. This paper provides an overview of the application of multi-agent systems in building operations for coordination of various building processes and buildings interaction with the smart-grid. By first reviewing the notions of agents, its potentials and key attributes, the paper identifies key areas in building operation where its application provides improved performance. Furthermore, the paper provides a discussion on the knowledge gaps, challenges with its uptake in practical building application as well as opportunity for concentrated research.