Grid4C receives grant to develop smart meter algorithms
June 4, 2019
Grid4C, a Texas-based AI-powered energy analytics provider, has been awarded a non-dilutive grant by the Israel Innovation Authority for 2019 to accelerate the development and delivery of its algorithms to be embedded inside smart meters.
The algorithms make real-time decisions at the grid edge. Grid4C has partnered with smart meter vendors to provide this innovation.
The AI-powered grid edge technology can provide utilities with granular real-time predictions and actionable insights for their operations and customer-facing applications.
This core technology drives applications ranging from granular load forecasting and distributed energy resources optimisation, to home energy management at the appliance level, and the prediction, detection and diagnostics of faults for grid assets and home appliances, to improve operational planning, reduce peak demand, increase energy savings, deliver new revenue streams and increase customer engagement. These capabilities and alerts can be delivered in real time without the need to pull the smart meter reads all the way up to the MDM head-end through the AMI network.
“We are appreciative of the substantial support and trust the Israel Innovation Authority has in Grid4C and our ability to lead innovation and value delivery with AI-powered energy analytics to global energy providers at the grid edge,” said Noa Ruschin-Rimini, Grid4C founder and CEO. “By embedding the most advanced machine-learning insights directly into smart meters, we can help plan and optimise distributed energy resources in real time at the edge of the grid, prevent faults both on the grid side and on the consumers side, and help consumers manage their energy better."
Grid4C empowers energy providers and consumers by enabling the power to foresee, leveraging machine-learning capabilities to deliver accurate, granular predictions for tackling the rising challenges in the energy industry.
The plug-and-play products analyse the massive amounts of sub-hourly data collected from millions of smart meters and IoT data and, together with user data, pricing information and more, can deliver revenue streams, enhance customer value, improve the efficiency of energy operations and increase profit.
Its portfolio includes: Predictive Home Advisor, which includes non-intrusive household appliance fault prediction and load disaggregation capabilities; Predictive Operational Analytics, enabling better decisions for coordination of distributed energy resources with meter, sub-meter and asset-level forecasting; and Predictive Customer Analytics, which targets and predicts adoption of new rate plans and utility programmes.