Data-driven, agile energy system planning and operation processes

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Agile planning and operation processes for buildings and districts by integrating real-time dataIn this challenge, we propose developing, testing, and validating an automated workflow for exploiting real-time data streams from a third pary cloud for energy planning in Sympheny's software. The objective is to demonstrate the potential advantages of an "agile" energy planning approach. Agile planning and operation processes for buildings and districts by integrating real-time dataTypically, energy planning workflows for buildings and districts rely on standards-based assumptions and highly aggregated estimations of energy demands, technology performance, etc. This results insufficiently accurate predictions of system performance and ultimately sub-optimal design decisions, creating missed opportunities for energy and CO2 savings. Nowadays, facility managers and property owners have access to increasing quantities of sensor data from their building systems and infrastructure. This includes, for instance, high-resolution, high-density, real-time readings of energy flows, storage levels, and energy demands. These new data sources provide a rich basis for generating improved estimates of anticipated performance. However, a systematic approach for incorporating this data into energy planning workflows is currently lacking.Sympheny is a startup company offering cloud-based software to support the energy planning of sites from the size of a building to a city. Using novel optimization-based planning workflows, Sympheny's software aids energy planners to quickly and accurately identify the optimal energy supply solution for any site. Belimo is a global provider of intelligent HVAC components and systems. Via the Belimo Cloud, real-time and historical data from Belimo HVAC systems can be accessed and deployed for different purposes. Sympheny's powerful, data-hungry algorithms are ideally complemented by rich data resources unleashed by the Belimo Cloud. The combination of Sympheny's algorithms and Belimo's data can enable energy planners to easily and effectively deploy the full scope and depth of available data resources in their planning workflows.In this challenge, we propose developing, testing, and validating an automated workflow for exploiting data streams from the Belimo Cloud for energy planning in Sympheny's software. The objective is to demonstrate the potential advantages of an "agile" energy planning approach. Models trained on the real-time operational data of a site will be used to drive an incremental planning process. The algorithm suggests possible enhancement steps to achieve an overarching goal, e.g. net zero CO2 emissions, as cost-effectively as possible. The impact of each development step is identified and evaluated through real-time data sourcing. Based on this new knowledge, the next development step is suggested by the algorithm. This process is continued until the overall goal is achieved. The step-by-step approach minimises project risks. The latest available technologies can also be taken into account in each development step and the solution path can be adapted if necessary.Via this new, agile transformation approach, predicted and realized system performance will be better aligned, the newest technology solutions effectively considered and energy and CO2 savings opportunities optimally exploited.To start this challenge, we aim to (1) develop data integration between an external real-time data cloud (e.g. Belimo Cloud) and the Sympheny SaaS platform. (2) Subsequently, demonstrate the feasibility in a demonstrator (e.g. NEST) through a PoC and finally (3) implement the field application with a pilot customer. We are looking for experts and partners who support or co-develop our project for all three development steps.

Project Idea Metadata

• Project Idea Name: Data-driven, agile energy system planning and operation processes
• Date: 4/8/2021 7:24:38 AM
• Administrators:

Project Idea Description

Agile planning and operation processes for buildings and districts by integrating real-time data

Typically, energy planning workflows for buildings and districts rely on standards-based assumptions and highly aggregated estimations of energy demands, technology performance, etc. This results insufficiently accurate predictions of system performance and ultimately sub-optimal design decisions, creating missed opportunities for energy and CO2 savings. Nowadays, facility managers and property owners have access to increasing quantities of sensor data from their building systems and infrastructure. This includes, for instance, high-resolution, high-density, real-time readings of energy flows, storage levels, and energy demands. These new data sources provide a rich basis for generating improved estimates of anticipated performance. However, a systematic approach for incorporating this data into energy planning workflows is currently lacking.

Sympheny is a startup company offering cloud-based software to support the energy planning of sites from the size of a building to a city. Using novel optimization-based planning workflows, Sympheny's software aids energy planners to quickly and accurately identify the optimal energy supply solution for any site. Belimo is a global provider of intelligent HVAC components and systems. Via the Belimo Cloud, real-time and historical data from Belimo HVAC systems can be accessed and deployed for different purposes.

Sympheny's powerful, data-hungry algorithms are ideally complemented by rich data resources unleashed by the Belimo Cloud. The combination of Sympheny's algorithms and Belimo's data can enable energy planners to easily and effectively deploy the full scope and depth of available data resources in their planning workflows.

In this challenge, we propose developing, testing, and validating an automated workflow for exploiting data streams from the Belimo Cloud for energy planning in Sympheny's software. The objective is to demonstrate the potential advantages of an "agile" energy planning approach. Models trained on the real-time operational data of a site will be used to drive an incremental planning process. The algorithm suggests possible enhancement steps to achieve an overarching goal, e.g. net zero CO2 emissions, as cost-effectively as possible. The impact of each development step is identified and evaluated through real-time data sourcing. Based on this new knowledge, the next development step is suggested by the algorithm. This process is continued until the overall goal is achieved. The step-by-step approach minimises project risks. The latest available technologies can also be taken into account in each development step and the solution path can be adapted if necessary.

Via this new, agile transformation approach, predicted and realized system performance will be better aligned, the newest technology solutions effectively considered and energy and CO2 savings opportunities optimally exploited.

To start this challenge, we aim to (1) develop data integration between an external real-time data cloud (e.g. Belimo Cloud) and the Sympheny SaaS platform. (2) Subsequently, demonstrate the feasibility in a demonstrator (e.g. NEST) through a PoC and finally (3) implement the field application with a pilot customer. We are looking for experts and partners who support or co-develop our project for all three development steps.

Agile planning and operation processes for buildings and districts by integrating real-time data

In this challenge, we propose developing, testing, and validating an automated workflow for exploiting real-time data streams from a third pary cloud for energy planning in Sympheny's software. The objective is to demonstrate the potential advantages of an "agile" energy planning approach.