Data Driven Models for HVAC Load Prediction

Consumers electric bills typically have two primary components: energy charges and demand charges. Demand charges are significantly costlier (10 times on average) than normal energy charges because of the inherent production cost to maintain the demand over a certain limit. This presentation proposes a model which can forecast upcoming demand charge events which in turn can help the consumers in optimizing their energy usages and hence help them avoid going to demand charge band.
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