i-Hub Smart Building Data Clearing House
Improving the accuracy of PV analytics and energy analytics in buildings using open asset standards and data platform integration
Project Title
Improving the accuracy of PV analytics and energy analytics in buildings using open asset standards and data platform integration
Project Location
Melbourne, AUSTRALIA
Industry
Building, Engineering, Data
Project Duration
13 Months
Project Budget
$1M
Project Participants
VBIS, CSIRO, AIRAH, City of Melbourne, ARENA
About The Project
Large-scale adoption of technology in buildings has resulted in availability of large volume of data on the performance of HVAC and renewable generation assets. This data can be used for predicting availability of onsite generation, effectively manage HVAC operations and support decarbonisation of buildings.
While operational data exists, application of data driven analytics for accurate predictions will still require customisation of methods/models to specific systems and assets.
This project proposes the utilisation of the VBIS asset classification open standard and link them with Data Clearing House based semantic models to demonstrate the benefits of integrated asset and building tagging systems to be used by PrediQ’s analytics solutions.
Business Drive
Needs
Buildings are complex systems with highly interdependent systems and components. With buildings expected to play an increasing role in the future electricity market, it is becoming more important for building owners, operators and other domain actors (e.g. electricity network operator) to identify the impact of building components (e.g. HVAC systems, on site generation) and enable their participation in the electricity market. This requires consistent, standardised representation of building details (building metadata) and their relationships in a machine-readable way for accurate analytics implementation and insights generation that facilitate decision making.
Action
The project partners, VBIS, PrediQ and CSIRO, will develop an integrated schema that bridges the gap in the current siloed approaches to asset meta data models used in the built environment by integrating VBIS asset classification and existing Data Clearing House semantic modelling/schema.
This will enable mass deployment of Software-as-a-Service based applications through leveraging of the integrated schema to provide a model showcasing insights from traditionally siloed data to enable building operators to learn critical information about the facility they have been tasked with operating.
Outcome
The key outcomes of this project will be to provide:
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Improved management of building assets including onsite photovoltaic generation due to integrated asset classification and semantic modelling
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Operational efficiency improvements in service delivery achieved by the application developer due to availability of portable, mass deployable photovoltaic analytics and energy analytics applications
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Demonstrate the value of integrated asset classification and semantic modelling for delivery of photovoltaic analytics, energy analytics applications and asset performance optimisation.
Extra Impact
The output of this project will lead to the development of reusable analytics applications with the ability to query a standardised building model. This will remove adoption barriers and facilitate ease of deployment across multiple siloed systems in use in different buildings across a portfolio.
Technology Development and Optimisation
Technology developed and optimised through this project will be announced with project reports when reaching different stages of milestone, aiming at November 2021, March and June 2022.
Last update: July 2021