PATENT CLAIM ANALYSIS

Application Number: 16184353
Application Type: Utility
Filing Date: 2018-11
Publication Date: 2019-03
Patent Classification: ["700", "291000"]

Abstract:
An energy control system includes a facility model processor, a post VEE readings data stores, a VEE configuration engine, and a global model module. The facility model processor employs interval based energy consumption streams corresponding to a facility to develop and maintain weather-normalized baseline energy consumption data for the facility. The post VEE readings data stores tagged energy consumption data sets that are each associated with a corresponding one of said interval based energy consumption streams, each of said tagged energy consumption data sets comprising groups of contiguous interval values tagged as having been validated, wherein said groups correspond to correct data. The VEE configuration engine reads the post VEE readings data stores upon initiation of an event and, for the each of the tagged energy consumption data sets, creates anomalies having different durations using only the groups of contiguous interval values, and generates estimates for the anomalies by employing estimation techniques and, for each of the different durations, selects one of the estimation techniques for subsequent employment when performing VEE of subsequent energy consumption data for the corresponding one of the interval based energy consumption streams. The global model module receives the weather-normalized baseline energy consumption data and post VEE readings data, and develops an energy consumption model based on the weather-normalized baseline energy consumption data and the post VEE readings data, and controls overall energy consumption within the facility based on the energy consumption model by scheduling run times of one or more building elements.

Claim (Index 1):
An energy control system, comprising:\n a facility model processor, that receives interval based energy consumption streams corresponding to a facility, and that develops and maintains weather-normalized baseline energy consumption data for said facility, wherein said weather-normalized baseline energy consumption data is derived from training data for said facility; a post VEE readings data stores, that provides tagged energy consumption data sets that are each associated with a corresponding one of said interval based energy consumption streams, each of said tagged energy consumption data sets comprising groups of contiguous interval values tagged as having been validated, wherein said groups correspond to correct data; a VEE configuration engine, that reads said post VEE readings data stores upon initiation of an event and, for said each of said tagged energy consumption data sets, that creates anomalies having different durations using only said groups of contiguous interval values, and that generates estimates for said anomalies by employing estimation techniques for each of said different durations and, for said each of said different durations, that selects a corresponding one of said estimation techniques for subsequent employment when performing VEE of subsequent energy consumption data associated with said each of said different durations for said corresponding one of said interval based energy consumption streams; and a global model module, that receives said weather-normalized baseline energy consumption data and post VEE readings data, and that develops an energy consumption model based on said weather-normalized baseline energy consumption data and said post VEE readings data, and that controls overall energy consumption within said facility based on said energy consumption model by scheduling run times of one or more building elements.

Metadata:
- Claim Count in Document: 50.0
- Percentile: 98.0
- Lexical Diversity: 2.9011
- Patent Class: 700.0
- Transitional Phrase Type: open
- Component Type: 1
- Foreign Priority: False
- Related Applications: ['16184420', '15280606', '15280664', '15280622', '15280646']

Analysis Scores:
- 35 USC 101 Eligibility (BERT): 0.525914247849061
- 35 USC 102 Novelty (BERT): 0.6429691739608122
- Combined Prediction Score: 0.5376197404602362
- Mean Citation Score: 580.319902
- Max Citation Score: 642.60156
- Similarity Product: 589.4581721058513

Labels:
- Claim Label 101: 1
- Claim Label 102: 1
- Claim Label 103: 1
- Claim Label 112: 1
- Combined Label: 1
- Label 101 Adjusted: 1

Dataset: test