Periodic Reporting for period 3 - PRELUDE (Prescient building Operation utilizing Real Time data for Energy Dynamic Optimization)
Periodo di rendicontazione: 2023-06-01 al 2024-11-30
The issue being addressed in the PRELUDE project is the fact that real operation of buildings often deviates from expectations, both with regards to energy use (high energy use) and indoor environment (poor indoor climate) and that we need better tools and we need to become better in using existing data to assess the magnitude of the problems, find performance gaps and provide solutions and promote data-driven awareness. The answer to these issues is to high extend in the acquisition of data and production of higher-level information from this data that can serve assessment of building performance through first analysis, and then predictions, optimizations and control strategies addressing different smartness and automation levels of buildings that compose building stock.
Work that has been carried out in the project in the first year of operation focuses on several aspects related to demonstration activities, development of PRELUDE technologies, first coordination between technologies-demonstration cases and integration of these through middleware solution.
With respect to demonstration activities, pilot buildings have been screened with regards to their current status. Also, additional monitoring equipment has been identified, installation of it has already stared in more advanced pilots while in some it is still pending. Moreover, first identification of suitable PRELUDE technologies/solution in respective pilot buildings has been detected together with first identification of data requirements to apply these technologies. Challenges and expected outcomes in each demonstration case have been identified. Finally, implementation plan for technologies validation has been prepared for living laboratory in which technologies will be implemented and then validated.
Regarding development of PRELUDE technologies most of the activities has starter and are progressing. The advancement in the tasks is different and depends on exact time each of the tasks has started and resources that have been already used. Among main achievements can be mentioned that:
- Tool for renovation roadmap has been r developed includes smart technologies and access to EPIQR price database and user-friendly web interface.
- Renovation selector tool has been developed to support data-driven selection of renewable solutions.
- Weather prediction model has been developed and applied to the weather data sets of all pilot buildings locations. Also, utilization of weather predictions has been identified.
- PREDYCE python tool that allows management of free running strategies in EnergyPlus is developed for low tech and high-tech buildings.
- Occupancy and behavioral models were tested and validated
- Indoor and outdoor correlation models have been obtained. Algorithm for rules of operation has been developed and tested in several pilot buildings.
- Data driven predictive maintenance model has been developed.
- Comfort and energy module have been finalized and required inputs and expected outputs are identified. The method shall estimate comfort for 24 h ahead, collect user feedback and support scheduling of main devices. The method still has some uncertainty due to simplicity of the model.
- Energy balance forecasting has been finalized with use of data from the living lab case building and later applied to real operational pilot cases.
- Definition of Measurement and Verification options for all pilot cases has been completed, applied and reported.
- Middleware solution (FusiX) is developed, it is launched on cloud. First communication was established for living lab building and proceed for all pilot buildings. Here also the first identification of information model (input/output) has been identified for PRLEUDE technologies and data base structure has been proposed.
- Algorithms for disaggregation of DHW and space heating from total heat logged in smart heat meters are being validated in PRELUDE. methods to preprocess large data sets has been developed and web-based tool to visualize and assess district heating connected buildings has been developed. Method for explicit fault collection has been developed and implemented in real environment. Data-driven methods have been proposed to facilitate automated fault detection and diagnosis.
- Data-driven method has been developed to predict district heating consumption and to be able to keep data privacy.
- PRLEUDE portal has been established to facilitate user and professional’s awareness about energy and indoor climate in the buildings to take corrective measures.
With respect to demonstration activities, pilot buildings have been screened with regards to their current status. Also, additional monitoring equipment has been identified, installation of it has already stared in more advanced pilots while in some it is still pending. Moreover, first identification of suitable PRELUDE technologies/solution in respective pilot buildings has been detected together with first identification of data requirements to apply these technologies. Challenges and expected outcomes in each demonstration case have been identified. Finally, implementation plan for technologies validation has been prepared for living laboratory in which technologies will be implemented and then validated.
Regarding development of PRELUDE technologies most of the activities has starter and are progressing. The advancement in the tasks is different and depends on exact time each of the tasks has started and resources that have been already used. Among main achievements can be mentioned that:
- Tool for renovation roadmap has been r developed includes smart technologies and access to EPIQR price database and user-friendly web interface.
- Renovation selector tool has been developed to support data-driven selection of renewable solutions.
- Weather prediction model has been developed and applied to the weather data sets of all pilot buildings locations. Also, utilization of weather predictions has been identified.
- PREDYCE python tool that allows management of free running strategies in EnergyPlus is developed for low tech and high-tech buildings.
- Occupancy and behavioral models were tested and validated
- Indoor and outdoor correlation models have been obtained. Algorithm for rules of operation has been developed and tested in several pilot buildings.
- Data driven predictive maintenance model has been developed.
- Comfort and energy module have been finalized and required inputs and expected outputs are identified. The method shall estimate comfort for 24 h ahead, collect user feedback and support scheduling of main devices. The method still has some uncertainty due to simplicity of the model.
- Energy balance forecasting has been finalized with use of data from the living lab case building and later applied to real operational pilot cases.
- Definition of Measurement and Verification options for all pilot cases has been completed, applied and reported.
- Middleware solution (FusiX) is developed, it is launched on cloud. First communication was established for living lab building and proceed for all pilot buildings. Here also the first identification of information model (input/output) has been identified for PRLEUDE technologies and data base structure has been proposed.
- Algorithms for disaggregation of DHW and space heating from total heat logged in smart heat meters are being validated in PRELUDE. methods to preprocess large data sets has been developed and web-based tool to visualize and assess district heating connected buildings has been developed. Method for explicit fault collection has been developed and implemented in real environment. Data-driven methods have been proposed to facilitate automated fault detection and diagnosis.
- Data-driven method has been developed to predict district heating consumption and to be able to keep data privacy.
- PRLEUDE portal has been established to facilitate user and professional’s awareness about energy and indoor climate in the buildings to take corrective measures.
Project has managed to develop all promised technologies. These technologies have been firstly developed and validated and afterwards demonstrated in the selected pilot buildings. Project concept for modular technologies and technology flexibility to buildings has been proven, however, not without challenges. Neutral approach for data collection solution secured that all pilot buildings could be connected to middle ware that could transmit data and feed the models and make selected data visible through PRELUDE portal.
Project was very successful in disseminating the scientific work and more articles are in the pipeline and foreseen beyond the project duration.
The data secured during project duration will serve for date-driven model developments beyond the project duration.
The data logging systems and hardware will remain in some of the pilot buildings. However, this is individual and depends on costs to maintain the monitoring and the data collection infrastructure.
Several bilateral agreements between project stakeholders have been identified in WP9 and are foreseen to result in further cooperations.
Project was very successful in disseminating the scientific work and more articles are in the pipeline and foreseen beyond the project duration.
The data secured during project duration will serve for date-driven model developments beyond the project duration.
The data logging systems and hardware will remain in some of the pilot buildings. However, this is individual and depends on costs to maintain the monitoring and the data collection infrastructure.
Several bilateral agreements between project stakeholders have been identified in WP9 and are foreseen to result in further cooperations.