Data Driven Optimization for Smart Energy Usage

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Screaming Power is an Ontario company that provides a mobile big data cloud platform for effective education of energy users on conservation, cost savings and continuous energy improvement. The proposed research is to develop a data driven decision-making method for Screaming Power's Utility and Enterprise applications, in order to generate optimal energy usage strategies in real-time using hourly meter and historical data. The ultimate goal of this method is not to fully automate the decision-making procedures, but to provide real-time recommendations that help all energy users and especially enterprises that manage multiple buildings to consume energy in a more adaptive and intelligent way to improve energy conservation and reduce carbon emissions. Different from the traditional demand side management research, the proposed research focuses on providing recommendations in real-time and with a variety of display modes. In addition, multiple optimal solutions will be provided for different user preferences and energy price/usage/weather condition scenarios. The anticipated outcomes of the research are a technical report that explains the method and demonstrates its effectiveness, as well as the computer codes realizing the method. The computer codes will be integrated into Screaming Power's mobile applications that will used by energy managers of federal government buildings in Ontario and potentially over 100,000 energy users in Ontario. The new data driven optimization method will contribute to the field of systems engineering, and it can benefit the decision-making for not only energy consumption, but also energy generation and GHG emissions tracking.