Updated: Nov 8
Energy is fundamental to all human activities and its demand follows the exponential growth of the world population. Since the period of industrialization, there has been an expansion in population and technology, accompanied by an exponential increase in use of energy, largely from non-renewable sources.
Commercial buildings are responsible for 40% of total energy consumption worldwide, and almost 30% of CO2 emissions. Heating Ventilation and Air Conditioning (HVAC) systems and water heating systems represent approximately 70% of the energy consumption of commercial buildings where about 75% of the primary energy supply is based on fossil fuels.
Energy efficiency of buildings has been a widely discussed topic with the aim of reducing energy costs, improve thermal comfort and lowering the consumption of fossil fuels. One way to assess if a building is energy efficient is through Building Energy Modeling (BEM), which is typically defined as a physics-based software simulation of a building energy use.
A detailed whole building energy simulation usually starts with a 3D drawing of a building geometry where all thermal zones are defined, being also required as input a vast amount of information:
– Building geometry, construction materials and orientation;
– Neighborhood effects of surrounding buildings (usually shading);
– Envelope performance;
– HVAC, refrigeration and water heating system configurations;
– Electrical loads and lighting intensity;
– Control strategies;
– Building operation schedules (occupancy, lighting, plug-loads, thermostat settings).
All this data is taken into account and when combined with local weather information it allows us to to calculate thermal loads, system response to those loads, resulting energy use, along with related metrics like energy costs and occupant comfort.
Building energy modeling plays a significant role in the design, optimization and control of several systems in a building. Simulation models may be used to compare the cost effectiveness of energy-conservation measures during a design stageas well as evaluate various performance optimization measures during the operational stage.
However, due to the complexity of a building environment and prevalence of several nonlinear inter-relationships among the involved variables, it is difficult to achieve an accurate representation of a real-world building operation. Therefore, by reconciling model outputs with real time data from a building, we can achieve more accurate and reliable results, with the ultimate goal of creating a Digital Twin of a building.
At Bandora, we integrate data from Buildings Management Systems (BMS) with an energy simulation software (EnergyPlus) with the purpose of creating an accurate energy model, that would allow to take the correct decisions when optimizing building’s energy consumption and thermal comfort.
An energy simulation software combined with an accurate building model allows us to create a test environment to support the development of a data-driven HVAC system optimization, evaluating the outcomes of this solution in different type of buildings and HVAC system configurations. Furthermore, this simulation software is also used to generate synthetic data of real buildings, proven to be valuable in the training phase of data-driven models, when historical data is sparse or even not available.