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Session 5A: Grid Transformation

Data-driven analytics from customer EVs and smart EV workplace charging stations can provide the foundational intelligence for new microgrid control systems. Maximizing the operational performance of assets, optimizing load and meeting end users’ needs can provide new services as well as new revenue streams. By collecting data (such as electricity price, facility demand and vehicle battery state of charge), and calculating optimal plans considering specific objectives and operational constraints, the microgrid control system makes the ‘best’ near real-time decisions based on complex analytics. For these reasons, the microgrid controller should be able to interact with a cloud- based solution for predictive control, as well as the connection with the utility, increasing the reliability and accuracy of decisions taken and to optimize the DER usage. The cloud-based platform also integrates weather forecasts and can effect utility’s requests (such as demand response).

This presentation will highlight lessons learned from implementing smart EV charging at a workplace (Markham Civic Centre) by Alectra Utilities, where HVAC load forecasting, alongside PV forecasts and storage have been extensively tested using Schneider Electric’s EcoStruxure™ Microgrid Advisor platform to predict and optimize DER usage. Initial results from both technology and driver feedback and behavior will be presented.

Pratap Revuru, Smart Grid Solution Architect, Schneider Electric
Daniel Carr, Manager, Smart Grid Projects, Alectra Energy