CSIRO is trialling intelligent, self-learning, interconnected controllers to manage energy demand and reduce greenhouse gas emissions from homes and businesses.
The goal of the project – an initiative of the Energy Transformed Flagship – is optimal management of energy demand and consumption, taking into account individual consumer preferences such as:
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comfort – for example, heating and cooling
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energy costs – ensuring that energy services are commercially viable and affordable.
Locally distributed controllers are particularly effective when some energy is generated at the building or in a nearby district, such as from photovoltaic cells or wind generators.
Distributed energy
Distributed energy refers to clean local generation and demand management at customer sites.
These technologies provide an 'early action' approach to greenhouse-gas reductions because they are available now. They can be introduced into present-day grids without special network technology or market developments.
Smart neighbourhoods
When installed in homes and businesses the controllers:
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sense conditions such as temperature
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control appliances and small local electricity generators, based on customer preferences
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receive information such as customer preferences, price signals and weather conditions, and communicate with neighbouring sites and remote electricity utilities
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process the information to determine immediate and future optimum actions.
Each house and business has a controller that communicates with all major appliances, and with identical controllers in nearby houses in the network.
Customers can reduce demand by more careful scheduling of appliance use, and through real-time control they participate in and get paid for demand responses based on network and market signals.
Each house and business has a controller that communicates with all major appliances, and with identical controllers in nearby houses in the network. The controllers also communicate with the electricity company, to find out when peaks in demand are expected, and with the meteorological office, for weather forecasts.
Last, the controller confers with the building occupants, to find out individual preferences, and accommodate those.
The result will be 'smart neighbourhoods' where houses work together – and individually – to ensure that they operate as efficiently as possible to minimise power drawn from the grid, especially during times of peak demand.
We have demonstrated the intelligent controllers in a mini-grid at CSIRO's Newcastle Energy Centre.
The mini-grid contains heating, ventilation, air-conditioning, and refrigeration appliances; and receives electricity generated by photovoltaic, wind, and micro-turbine. It also receives data feeds on weather and electricity pricing.
Our technology is now ready to be trialled in real homes.
There are four streams to current research:
Domestic energy management
Intelligent controllers are being developed to help manage appliances efficiently, integrate renewable generation, and inform customers about options and consequences of different energy choices. Home energy management can be coordinated across multiple households for aggregated benefits.
CSIRO is providing software and methods that integrate with devices from a hardware partner organisation.
Virtual power station
Anticipating large-scale adoption of renewable generation in our suburbs and towns, new data and models for local-scale variation and diversity of solar photovoltaic and wind generation are being developed and trialled.
This will allow bidding strategies to achieve market value for the total renewable output provided by customers’ rooftop or backyard generation.
Mini-grids
Urban, industrial, and rural areas can be independent of the national electricity grid, or achieve specific energy requirements while remaining grid-connected, by adopting local generation sources and new management and control technologies.
This technology is particularly relevant for remote communities and developing nations. It also lays the foundation for local self-management of smart grids.
Simulation
Models based on specific demographic, appliance, local generation, and social research data are being developed to help forecast the system behaviour of networks with large amounts of managed demand and local generation.
Software simulation tools use these models to provide the means to answer questions about scalability of large demand-side systems and the services they may provide to networks, retailers, and new aggregation businesses.
Partners
Read more about CSIRO's research in Energy.
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