hould enable automated efficiency analyses and optimize the operation of each heating system. The primary focus of the project is on achieving energy and CO2 savings as well as increasing comfort from the system operator's point of view (simplified operational management). Secondary objectives are cost savings and extending the service life of the heating technology. The expected energy savings are at least 10 %. The scope of the project extends to heat optimization in the operation of apartment buildings operated by housing companies. Strategically, the project focuses on monitoring, information and knowledge transfer as well as recommendations for action. These measures are mainly aimed at the system operators and not the tenants. On the one hand, operational optimization and the necessary processing by means of dashboards or a digital platform are used. For this purpose, key values such as the degree of utilization are compared with "adaptive" benchmarks, among other things. These adaptive benchmarks in accordance with VDI 3807-1 not only relate to the individual building, but are of particular interest for the entire building portfolio. The average value of the best 25% of buildings with comparable technology and use is used as a benchmark. Housing companies can thus compare the buildings and facilities with the benchmark and identify the greatest needs and potential for their own portfolio. This adaptive approach with practically achieved and therefore realistic characteristic values enables continuous adjustment of the benchmarks depending on the period and modernization measures carried out. This not only creates internal comparability, but also comparability with other companies and properties, which can encourage targeted action.

imization options from monthly and annual reports. For this purpose, important key figures such as capacity utilization, operating times, temperature curves, losses and the efficiency of the heating system are displayed. The levers identified in the project for leveraging efficiency potential included adjusting operating times and temperatures, minimizing circulation times and - for a possible boiler/heating system replacement - assistance in sizing the heating system to meet demand, which minimizes the future use of materials and avoids oversizing. Previous studies have also identified centralized domestic hot water production as frequently inefficient, which makes the use of decentralized systems for water heating (e.g. home stations) another relevant factor (also in the case of possible modernization measures by housing companies). Additional measured values are required to identify these adjusting screws. However, only a very small number of meters, as well as temperature and volume flow sensors, need to be installed and connected to an extra data logger via radio or cable. The minute-by-minute data is then temporarily stored on the data logger, encrypted and sent to a server. This is where the actual, automated processing and evaluation of the measured values takes place. The system operators can then retrieve the data from the server in real time or in aggregated form. Methodically, the measured values are processed on the basis of comparative formation using adaptive benchmarks. This allows the performance of the system to be quickly evaluated against comparable objects. The detailed processing of the actual operating parameters of the heating system then takes place either individually in real time or in the automated form of monthly or annual reports. Among other things, the reports are designed for monthly/annual comparisons of the heating center's performance. Automated recommendations for action are also provided for some optimization settings. For example, the system operators are notified if possible rest periods for the domestic hot water circulation are not fully utilized or if the operating temperatures are too high.

ilable and trends over time are to be identified. In the last scenario, characteristic values are compared with the corresponding characteristic values of all other plants. These values must all have been calculated on the same basis. The benchmark is only meaningful if a large number of systems have been examined over at least one year. The following four parameters are used in the project to provide an overview of the relevant qualities of the central heating plants. The efficiency of the heat generator is of central importance, as this component converts the supplied final energy into usable heat. The heat generators are differentiated according to the various final energy sources gas, oil, wood and electricity, but not according to year of construction or type of construction. The efficiency of the component is characterized by the annual efficiency factor (seasonal performance factor for heat pumps). It is defined as the ratio of the heat generated for use in a year to the final energy supplied to the heat generator without renewable energies. The next parameter examined is the efficiency of the central domestic hot water supply. It provides information about circulation losses and losses in the storage and loading pipe and is often the utilization path with the lowest efficiency. The efficiency is represented by the degree of utilization and is calculated by dividing the thermal energy contained in the domestic hot water consumed by the amount of heat supplied to the domestic hot water heater. The proportion of local renewable energies is also taken into account. This characteristic value represents the extent to which the building and the central heating system are powered by self-sufficient renewable energy. It is calculated from the ratio of the renewable energy provided locally in and around the building to the total of all energy supplied. Finally, the specific CO2 emissions are examined. This parameter indicates the total amount of CO2 emissions generated by the building's heat consumption. The "heat generator" and "domestic hot water supply" parameters reflect the efficiency of the system components, while the "locally generated renewable energy" and "CO2 emissions" parameters assess the sustainability of the system. In one example object of the project, an optimization potential for the efficiency of the boiler efficiency of 8 % can be seen, for domestic hot water supply an optimization potential of 9 % is calculated, although the target value is at a lower level. This is an indication that central domestic hot water preparation is generally not very efficient, as significant distribution losses cannot be avoided. The German Technical and Scientific Association for Gas and Water states that the highest levels of efficiency and final energy savings can only be achieved hygienically with a decentralized domestic hot water supply. The target value for the proportion of renewable energy is three times as high as the measured value, which corresponds to a potential of 300 %. Here too, the target value is at a low level, as the local use of renewable energy in the MFH sector (environmental heat, solar energy) is not yet widespread. In contrast to the limited degree of utilization of the central domestic hot water supply, the target value or potential for the share of renewable energies will continue to move towards 100% through appropriate modernization. The characteristic value for CO2 emissions at the property is very close to the target value, which, taking into account the low proportion of locally generated renewable energy, indicates that the building insulation is at least state of the art. For the gas boilers in the overall portfolio with an average value of all systems of 80 % annual efficiency and the best systems with 90 % annual efficiency, there is a deviation of 10 %. This also represents the average optimization potential. Savings potentials are also calculated for the central domestic hot water supply. An example building showed that higher domestic hot water temperatures and significantly lower utilization in summer can lead to a reduction in the efficiency of the central heating system by 10 percentage points. This is accompanied by an increased final energy requirement of at least 10 %. These savings, which can be achieved with few resources, or the improvements that may be possible by tapping into the potential identified, are offset by only minor ecological effects. The CO2 footprint for the components of a heat pump system (1 water meter, 2 heat meters, 8 wireless temperature sensors, 1 data logger, 1 smart meter) is estimated by the project using the help on the environmental impact of frequently used components at approx. 103.3 kg CO2eq/year. The amount of data required is also low at approx. 0.3 GB/year. Using the key figures on the environmental impact of data transmission and processing, the CO2 emissions can be estimated at approx. 0.8 kg CO2eq/year (data transmission with VDSL; server location Germany; use case virtual machine). With an emission factor of approx. 0.5 kg CO2eq/kWh¹, only approx. 208 kWh/a of electricity would have to be saved in order to offset the environmental impact.