K.-S. Tam (USA)
Data modeling, energy demand.
Conventionally, electricity usage patterns are handled in the time domain. This paper demonstrates the efficacy and benefits of a new data model to store and process these patterns using harmonics. It is demonstrated that daily and weekly patterns can be accurately represented by their essential harmonics. Storing shape information in the form of essential harmonics instead of time-domain data is demonstrated to result in significant savings in data storage requirement, especially for patterns of long time period such as weekly patterns. These savings are important in the coming years as customers, electricity suppliers and utilities will have to deal with more electricity usage data. The essential harmonics display trends that can be used as the new basis to categorize electric loads and to support new business such as load aggregation. The new data model also supports automated discovery of hidden trends and relationships.
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