Method development for lowering supply temperatures in existing buildingsusing minimal building information and demand measurement data

Regarding climate change, the need to reduce greenhouse gas emissions is well-known. As building heating contributes to a high share of total energy consumption, which relies mainly on fossil energy sources, improving heating efficiency is promising to consider. Lowering supply temperatures of the heating systems in buildings offers a huge potential for efficiency improvements since different heat supply technologies, such as heat pumps or district heating, benefit from low supply temperatures. However, most estimations of possible temperature reductions in existing buildings are based on available measurement data on room level or detailed building information about the building's physics to develop simulation models. To reveal the potential of temperature reduction for several buildings and strive for a wide applicability, the presented method focuses on estimations for temperature reduction in existing buildings with limited input data. By evaluating historic heat demand data on the building level, outdoor temperatures and information about installed heaters, the minimal actual necessary supply temperature is calculated for each heater in the building using the LMTD approach. Based on the calculated required supply temperatures for each room at different outdoor temperatures, the overall necessary supply temperatures to be provided to the building are chosen. Thus, the minimal heatcurve possible for an existing building is deduced.The method described is applied to multiple existing office buildings at the campus of Forschungszentrum Jülich, Germany, demonstrating the fast application for several buildings with limited expenditure. Furthermore, a developed adapted heatcurve is implemented in one real building and evaluated in relation to the previously applied heatcurve of the heating system

Heat supply for office buildings: A research journey through different supply levels at the Campus ofForschungszentrum Jülich

With regard to climate change, the reduction of greenhouse gas emissions, e.g. by introducing and extending the use of renewable energy sources, plays a pivotal role. As a part of the “Energiewende”, the share of renewable energy sources in electricity generation increased rapidly so far, however other sectors, such as the heating sector, are lagging behind. In order to achieve the defined greenhouse gas emission reduction targets, corresponding measures have to be taken in all energy sectors. This especially holds true in the heating sector, which accounts for a high share in carbon dioxide emissions. In the heating sector, key challenges include the integration of renewable energies and waste heat in the heat supply as well as the increase of the efficiency in the building sector. To reduce heating demands while still ensuring thermal comfort for the occupants, different measures can be taken, ranging from design to refurbishment and automation. Due to the low rate of new construction and renovation in Germany and the European Union in general, the building stock will dominate the overall energy demand of buildings for the coming decades. Therefore, solutions which can be easily retrofitted in existing buildings are essential. Within the “Living Lab Energy Campus” (LLEC) initiative at Forschungszentrum Jülich (FZJ), these challenges are addressed by developing, demonstrating and evaluating various measures ranging from district level over building level to room level by using the real infrastructure at the campus. On the supply side at district level, the integration of waste heat of a water-cooled high performance computer from the Jülich Supercomputing Center (JSC) into a low temperature district heating network (LTDH) for the supply of heat to surrounding buildings is studied. Since the waste heat is provided at moderate temperature, heat pumps are installed in the connected buildings to raise the temperature of the supplied heat to the required temperature level of the building's heating system. Cloud-based model predictive controllers have been developed for an overall optimal operation of the LTDH, heat pumps, heat storages and heating distribution systems within the buildings. The developed control methods have been tested and evaluated using a digital twin. After start of operation of the LTDH, a scientific evaluation of different control methods as well as of the ICT setup can be conducted. Besides this, the automation system of a heating substation with heat exchanger fed by a traditional district heating network is connected to the ICTplatform and adapted for scientific monitoring and operation. To raise energy efficiency at building level, innovative cloud-based controllers as well as monitoring methods to raise user awarenesswith respect to energy demand are developed. For the evaluation of these methods, several buildings including those connected to the LTDH have been equipped on room level with radio-based sensors, measuring indoor air quality and energy demand related parameters, and actuators, allowing the local and remote control of heating systems, lighting systems and venetian blinds. Occupantscan view sensor data of their room via the web-based graphical user interface “JuControl” and provide setpoints for e.g. temperature control. The implemented setup allows the use as a testbed for a variety of different automation algorithms. The experiments having already been conducted show the opportunity to increase the energy efficiency and reveal interesting insights by data analysis.In addition to run and evaluate single measures separately, the developed ICT infrastructure also enables the combined operation of several measures in parallel across different levels and sectors, e.g. a grid-supporting heat pump operation. Finally, a first evaluation of the wide range of measures including the different characteristics regarding costs, implementation efforts and efficiency gains is shown.The general concept of each measure as well as the developed tools, methods and model libraries for optimal design and operation can be transferred to similar use cases. For wider application, also a release of the developed software elements is planned

Heat supply for office buildings: A research journey through different supply levels at the Campus of Forschungszentrum Jülich

With regard to climate change, the reduction of greenhouse gas emissions, e.g. by introducing and extending the use of renewable energy sources, plays a pivotal role. As a part of the “Energiewende”, the share of renewable energy sources in electricity generation increased rapidly so far, however other sectors, such as the heating sector, are lagging behind. In order to achieve the defined greenhouse gas emission reduction targets, corresponding measures have to be taken in all energy sectors. This especially holds true in the heating sector, which accounts for a high share in carbon dioxide emissions. In the heating sector, key challenges include the integration of renewable energies and waste heat in the heat supply as well as the increase of the efficiency in the building sector. To reduce heating demands while still ensuring thermal comfort for the occupants, different measures can be taken, ranging from design to refurbishment and automation. Due to the low rate of new construction andrenovation in Germany and the European Union in general, the building stock will dominate the overall energy demand of buildings for the coming decades. Therefore, solutions which can be easily retrofitted in existing buildings are essential.Within the “Living Lab Energy Campus” (LLEC) initiative at Forschungszentrum Jülich (FZJ), these challenges are addressed by developing, demonstrating and evaluating various measures ranging from district level over building level to room level by using the real infrastructure at the campus. On the supply side at district level, the integration of waste heat of a water-cooled high performancecomputer from the Jülich Supercomputing Center (JSC) into a low temperature district heating network (LTDH) for the supply of heat to surrounding buildings is studied. Since the waste heat is provided at moderate temperature, heat pumps are installed in the connected buildings to raise the temperature of the supplied heat to the required temperature level of the building's heating system. Cloud-basedmodel predictive controllers have been developed for an overall optimal operation of the LTDH, heat pumps, heat storages and heating distribution systems within the buildings. The developed control methods have been tested and evaluated using a digital twin. After start of operation of the LTDH, a scientific evaluation of different control methods as well as of the ICT setup can be conducted. Besides this, the automation system of a heating substation with heat exchanger fed by a traditional district heating network is connected to the ICTplatform and adapted for scientific monitoring and operation. To raise energy efficiency at building level, innovative cloud-based controllers as well as monitoring methods to raise user awareness with respect to energy demand are developed. For the evaluation of these methods, several buildings including those connected to the LTDH have been equipped on room level with radio-based sensors, measuring indoor air quality and energy demand relatedparameters, and actuators, allowing the local and remote control of heating systems, lighting systems and venetian blinds. Occupants can view sensor data of their room via the web-based graphical user interface “JuControl” and provide setpoints for e.g. temperature control. The implemented setup allows the use as a testbed for a variety of different automation algorithms. The experiments havingalready been conducted show the opportunity to increase the energy efficiency and reveal interesting insights by data analysis. In addition to run and evaluate single measures separately, the developed ICT infrastructure also enables the combined operation of several measures in parallel across different levels and sectors, e.g. a grid-supporting heat pump operation. Finally, a first evaluation of the wide range of measures including the different characteristics regarding costs, implementation efforts and efficiency gains is shown.The general concept of each measure as well as the developed tools, methods and model libraries for optimal design and operation can be transferred to similar use cases. For wider application, also a release of the developed software elements is planned