A web based energy cloud platform for campus smart grid for understanding energy consumption profile and predicting future energy demand

This paper proposes a web based energy cloud platform framework for analyzing energy consumption behavior of campus environment, forecasting future energy demand and controlling some power hungry appliances when electricity demand overpasses generation. In addition to that, one of the key objectives of our work is to incorporate a rule based data filtering logic with this web based energy cloud platform; so that, data associated with energy consumption behavior analysis could be reduced. This work is mainly based on our previously developed ThingsGate platform, which facilitates IoT (Internet of Thing) management on wireless Access Point (AP) and its execution. This paper also provides some insightful discussion on some technical aspects of access networks which should be taken into consideration for ensuring Quality of Service (QoS) of smart grid traffic (e.g. control messages). Our discussion would be useful for successfully deployment of smart grid in a campus environment.

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