The innovation Hub for Affordable Heating and Cooling (i-Hub)

This project resulted in development of the Data Clearing House (DCH), a cloud-based building data management and application enablement platform.

DCH connects Internet of Things (IoT) systems from buildings and supports complex data analytics. DCH facilitates access to data driven analytics that deliver energy savings, operational cost savings and unlock new opportunities for delivering Buildings to Grid (B2G) services.

Background:

The Innovation Hub for Affordable Heating and Cooling (i-Hub) initiative was led by the Australian Institute of Refrigeration, Air Conditioning and Heating (AIRAH) in conjunction with CSIRO, Queensland University of Technology (QUT), the University of Melbourne and the University of Wollongong, and supported by Australian Renewable Energy Agency (ARENA) to facilitate the heating, ventilation, air conditioning and refrigeration (HVAC&R) industry’s transition to a low emissions future, stimulate jobs growth, and showcase HVAC&R innovation in buildings.

Project need:

The built environment sector is undergoing digital transformation due to the availability of low cost IoT sensing solutions, IoT enabled building hardware systems and advanced Information Technology (IT) infrastructure.

However, the built environment sector is lagging other markets in deriving value through digital transformation, including the use of data driven approaches for providing flexible HVAC loads in support of onsite renewables. This is primarily due to lack of an ecosystem for linking heterogeneous sources of data, sharing of data and mechanisms to use building data in a secure and equitable way, limiting new innovations in this space.

Project outputs:

DCH platform development and release

DCH development has been backed by continuous interaction and engagement with various user groups. The platform development has been driven by the strategic needs of the users:

implifying onboarding, data collection and data sharing without vendor lock-in;
facilitating easy access to data and data driven application based third party services; and
providing a secure platform that empowers data sovereignty.

DCH facilitates easy onboarding of buildings to the platform at scale. This has been achieved through the development of tools for collection and storage of heterogeneous sources of data from Building Management Systems (BMS), IoT (Internet of Things) sensors and third-party providers.

This minimises duplication of work for each building/data source. DCH’s APIs (Application Programming Interface) facilitate easy data exchange between different platforms/providers.

DCH is built on CSIRO’s award winning Senaps sensor data analytics platform and retains the core strengths of the platform such as handling of time series data in a multi tenancy framework backed by role-based permissions management.

The key technology that underpins the scalability and interoperability features of DCH are the semantic building models. Semantic models provide a ground truth for a building’s components, make building data easily discoverable and interpretable, and can be modified to reflect real-world changes.

These models conform to the Brick Schema, a standardised representation of building elements and their relationships.

HVAC Demand Response potential estimation studies

Air-conditioning is a low cost, readily available opportunity for delivering Demand Response (DR) services for electricity networks, particularly those with high penetration of renewables. Demand response takes advantage of a building’s inherent thermal storage to reduce electricity demand at peak times, with no discernible impact on the indoor operating environment.

As part of the project, the existing potential of commercial and residential air conditioning systems to provide demand response services across Australia has been estimated using a top-down approach based on disaggregation of electricity substation half-hourly data. Results indicate that peak (i.e., 99.5th percentile) demand on the National Electricity Market (NEM) could be reduced by up to 5.8% or 1.2 GW, with the time of day at which the peak occurs delayed by approximately two hours. Based on the timing of the available capacity, both residential and commercial buildings are suited to providing air-conditioning demand response.

A high-fidelity bottom-up estimation of the DR potential of two commercial building typologies (schools and office buildings) has also been carried out. Detailed representative building energy and HVAC (Heating Ventilation and Air-Conditioning) system simulation models have been constructed.

These models were combined with weather data for representative NSW climate zones and used to estimate the cooling system energy reduction resulting from short-duration 2°C increases to the air-conditioning set-point temperature across varying weather conditions and at different times of the day.

In addition, parametric analysis was conducted to better understand the influence of different parameters related to the building fabric (for example, insulation levels, window area and orientation) and the air-conditioning system on the available demand response.

Results indicate that in NSW the DR potential between 3 pm and 5 pm in office buildings is approximately 126 MW and in school buildings is 90 MW when the outdoor temperature is in the range of 31-35°C. This is equivalent to approximately 26% and 55% reductions in air-conditioning power for office and school buildings, respectively.

The HVAC Demand Response Atlas Visualisation tool

An online Tableau visualisation of DR potential across Australia has been developed along with a simple financial layer based on the Regional Reference Price of electricity.

This visualisation can be used to understand the timing and spatial variation of the potentially available air-conditioning demand response across different parts of the network.

The tool allows users to explore estimates of residential and commercial building air-conditioning wholesale demand response by electricity network region or individual electricity zone substation across most of Australia.

Users can select the month, time of day and temperature range of interest, and then view either the estimated magnitude of air-conditioning demand response, the demand response proportion of the total electricity demand, or an estimate of the regional wholesale value of the demand response.

This information may be used to help understand the current potential of air-conditioning wholesale demand response in buildings, for example to assist high level planning of HVAC demand response initiatives.

Please click here to access the tool.