WP2 - System Modeling
The objective of this work package is, for the three demonstration buildings, to deliver validated simulation models that accurately represent at the simulation level the building and all the installed subsystems. The emphasis will be on integration of information available at the building site from sensors, to fine-tune operation and enhance the predic-tive capabilities of these models.
Building data collection
Under this task, the necessary data to setup the simulation models for the three demonstration buildings will be col-lected in close cooperation with the building owners, architects, planners, and users. Detailed information regarding the following base case data will be collected during this task:
- Local climate (e.g. temperature, illumination and humidity seasonal patterns and temperature minimum and maximum values), and microclimate.
- Location, orientation, floor plans, construction materials used, material properties.
- Data on installed renewable energy-generation elements (PV arrays, Wind generators, etc).
- HVAC systems (Heating, Ventilation, Air Conditioning), active solar systems, shading devices, natural venti-lation, lighting, control strategies.
- Operative details (schedules of occupancy, internal gains, manual shading, manual use of windows).
Based on the partners experience from modeling buildings in the past, a data-base containing all necessary informa-tion required for setting-up the three buildings’ models will be created. The use of this data-base will be two-fold: firstly, to make sure – by comparing the entered data provided at the three different buildings – that all necessary in-formation for all three buildings is available and, secondly, in order to identify the range of all physical as well as hu-man-related parameters that affect the overall EPB model’s performance. Identification of the range of all EPBs physi-cal as well as human-related parameters is crucial for the construction of an efficient AMPC BO&C system in task T3.2.
Integrated thermal modeling
Under this task the integrated thermal models for the buildings will be developed, in the selected thermal simulation toolboxes. The modeling will include:
- HVAC systems, shading and lighting, ventilation, etc.
- Active solar systems, wind generation systems, CHP, ventilation.
- Renewable energy generation systems (Wind, PV).
And all other energy affecting elements.
Predictive models using measured data, forecasts and different human & control actions
The availability of sensor data in the PEBBLE building presents an opportunity to further improve the thermal models. For example, a window opening sensor (to be installed in the TUC building) can yield data regarding the state of the window and these data can be incorporated in the model to better improve accuracy. The presence of human sensors that communicate thermal comfort preferences via appropriately constructed interfaces presents along with sensors that record physical parameters and models that can compute comfort indices provide also an opportunity for im-provement of thermal comfort models. Finally, weather forecasting models are especially important in the simulation of EPB buildings, since to a large extend weather variations can affect the availability of renewable energy. Under this task, the integration of measured data, forecasts and human actions will be integrated to the thermal models of T2.2, to yield more accurate and reliable predictive models.
Sensitivity analysis and validation
Under this task the potential of model-reduction (“just enough” accuracy) to yield more efficient simulation models will be investigated. Simulation of sensitivities of building structure and HVAC system for the buildings in accordance with owner, architect, planners and users by sensitivity analysis and optimization procedures. This could include fixed shading, better movable shading and ventilation control, better insulation especially of the roofs but also of the walls and windows, introduction of additional thermal mass (e.g. as clay plaster at the inside of the walls), reduction of in-ternal gains by the use of energy efficient appliances and recommendations for the user behavior. About 30 scenarios for sensitivities per building will be calculated and analyzed. A second goal in tandem with the first is validation of the integrated models using measured data form the past and reactions of the building to various occurrences (weather situations, user behavior changes etc. ) and uncertainties.