Patent Document ID: 9857778
Application ID: 15288707
Patent Flag: 1

Claim One:
1. A computer implemented method of forecasting power generation, the method comprising: analyzing, using the processor, a set of historical power generation data; determining, using the processor, a set of clusters, wherein each cluster of the set of clusters represents power generated during a time period, wherein the time period comprises a first portion and a second portion; receiving, using the processor, actual power generation data for the first portion of a target time period; determining, using the processor, which cluster of the set of clusters contains historical power generation data that is most similar to the actual power generation data for the first portion of the target time period, wherein each cluster represents a group of time periods that have a similar profile of power generated; forecasting, using the processor, power generation for the second portion of the target time period, using the historical power generation data of the determined cluster; obtaining supplemental power if the forecast power generation is below a threshold; analyzing, with the processor, a set of historical weather data; and receiving a weather forecast for the time period; wherein: determining a cluster of the set of clusters comprises: dividing the historical power generation data into the set of clusters based on similarity score between of the power generation data during the time period; wherein each cluster comprises a set of historical power generation data during the time period; and further wherein: calculating a similarity score comprises finding the product of a complexity measure and a Euclidean distance between the historical power generation data and the actual power generation data for the cluster; the similarity score is expressed as: 
 D ( X i ,X j )= CF ( X i ,X j )· d ( X i ,X j ), where D represents the similarity score, CF represents the complexity measure, d represents the Euclidean distance, X i represents the actual power generation data, and X j represents the historical power generation data for the cluster; each cluster of the set of clusters represents weather data for the time period and power generated during the time period; determining which cluster of the set of clusters contains historical power generation data that is most similar to the actual power generation data further comprises determining which cluster contains weather data that is most similar to the weather forecast; using the historical power generation data of the cluster to forecast power generation further comprises using the weather forecast to forecast power generation; and determining, using the processor, which cluster of the set of clusters contains historical power generation data that is most similar to the actual power generation data comprises: for each cluster of the set of clusters, calculating a similarity score between the historical power generation data for the cluster and the actual power generation data; and finding which cluster of the set of clusters has the highest similarity score.