PATENT CLAIM ANALYSIS

Application Number: 15961073
Application Type: Utility
Filing Date: 2018-04
Publication Date: 2018-08
Patent Classification: ["700", "291000"]

Abstract:
A method for dispatching buildings, including: generating data sets, each having energy values along with corresponding time and outside temperature values, wherei the energy values are shifted by one of a plurality of lag values relative to the corresponding time and outside temperature values; performing a machine learning model analysis on the each of the data sets; determining a least valued residual that indicates a corresponding energy lag for each of the buildings, the corresponding energy lag describes a transient energy consumption period preceding a change in outside temperature; using outside temperatures, model parameters, and energy lags for all of the buildings to estimate a cumulative energy consumption for the buildings, and to predict a dispatch order reception time for the demand response program event; and employing the dispatch order reception time to prepare actions required to control the each of the buildings to optimally shed energy specified in a dispatch order.

Claim (Index 9):
The system as recited in  claim 8 , wherein said plurality of lag values indicates shifts of said energy consumption values to different time and outside temperature values.

Metadata:
- Claim Count in Document: 53.0
- Percentile: 91.0
- Lexical Diversity: 2.11538
- Patent Class: 700.0
- Transitional Phrase Type: none
- Component Type: 0
- Foreign Priority: False
- Related Applications: ['15903596', '14984785', '15903533', '14674021', '14984706']

Analysis Scores:
- 35 USC 101 Eligibility (BERT): 0.5331948224542629
- 35 USC 102 Novelty (BERT): 0.5928573185636986
- Combined Prediction Score: 0.5391610720652065
- Mean Citation Score: 504.50663600000007
- Max Citation Score: 507.22586
- Similarity Product: 480.98166615192406

Labels:
- Claim Label 101: 1
- Claim Label 102: 1
- Claim Label 103: 1
- Claim Label 112: 0
- Combined Label: 1
- Label 101 Adjusted: 1

Dataset: test