Grant: Idea to Innovation

Leaders and Followers represents a breakthrough invention in numerical optimization. It has been specifically developed for the large-scale, multi-modal search spaces created by the Internet of Things (IoT) -- a forthcoming network where every thing has an IP address and is connected to the internet. With the opportunity for advanced optimization and feedforward preference data, we can move beyond Big Data and behaviour prediction to pursue Active Data and behaviour modification.An example of Big Data and behaviour prediction is use of ""smart meters"" for measuring household electricity consumption. These unidirectional data collection devices might be able to help a utility predict that a given household often turns on its dishwasher at 3AM. More useful than behaviour prediction, an IoT dishwasher can instead communicate future usage needs. Utilities can then provide incentives to modify the actual start time to achieve global optimization objectives such as load balancing (e.g. different dishwashers start at different times) and load matching (e.g. all dishwashers operate during a period of high wind).The ability to perform advanced demand management such as load balancing and load matching can lead to significant savings for utilities. For example, the Ontario power grid experiences price fluctuations of over $40/MWh. Improvements to load balancing of as little as 5% can lead to operational savings of up to $300M/year. Further, since infrastructure is designed for peak loads, the new optimization technologies that we develop may help utilities save billions in long-term capital investment costs. More than saving money, peak generation is often high in both cost and CO2 production. The application of Active Data to energy systems can thus help individuals, corporations, and governments achieve their carbon reduction, environmental protection, and cost saving goals.