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Towards Data-driven Demand-Response Optimization in a Campus Microgrid

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Workshop On Embedded Sensing Systems For Energy-Efficiency In Buildings (BuildSys), стр. 41--42. ACM, (2011)Demo.
DOI: 10.1145/2434020.2434032

Аннотация

We describe and demonstrate a prototype software architecture to support data-driven demand response optimization (DR) in the USC campus microgrid, as part of the Los Angeles Smart Grid Demonstration Project. The architecture includes a semantic information repository that integrates diverse data sources to support DR, demand forecasting using scalable machine-learned models, and detection of load curtailment opportunities by matching complex event patterns.

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