PATENT CLAIM ANALYSIS

Application Number: 15963073
Application Type: Utility
Filing Date: 2018-04
Publication Date: 2018-08
Patent Classification: ["700", "191000"]

Abstract:
A method and device for modeling a long-time-scale photovoltaic output time sequence are provided. The method includes that: historical data of a photovoltaic power station is acquired, and a photovoltaic output with a time length of one year and a time resolution of 15 mins is selected ( 101 ); weather types of days corresponding to the photovoltaic output are acquired from a weather station ( 102 ), and probabilities of transfer between each type of weather are calculated respectively ( 103 ); and a simulated time sequence of the photovoltaic output within a preset time scale is generated ( 104 ), and its validity is verified ( 105 ). By the method, annual and monthly photovoltaic output simulated time sequences consistent with a random fluctuation rule of a photovoltaic time sequence may be acquired according to different requirements to provide a favorable condition and a data support for analogue simulation of time sequence production including massive new energy.

Claim (Index 2):
The method according to  claim 1 , wherein calculating the probabilities of transfer between each type of weather respectively comprises: adopting a Markov chain to simulate transfer processes of each type of weather and acquire the probabilities of transfer between each weather type, an expression being: P k = N k N 1 , ( 1 ) in formula (1), P k  being the probability of transfer of the clear weather to another weather type, k representing a weather type, N k  being a number of times of transfer and N 1  being a number of times of occurrence of the clear weather.

Metadata:
- Claim Count in Document: 32.0
- Percentile: 91.0
- Lexical Diversity: 1.89888
- Patent Class: 700.0
- Transitional Phrase Type: none
- Component Type: 0
- Foreign Priority: True
- Related Applications: ['15588550', '13784560', '14223926', '14224018', '12777224']

Analysis Scores:
- 35 USC 101 Eligibility (BERT): 0.3985020272292141
- 35 USC 102 Novelty (BERT): 0.5032571977316669
- Combined Prediction Score: 0.4089775442794593
- Mean Citation Score: 141.043582
- Max Citation Score: 147.96438999999995
- Similarity Product: 74.47634401564714

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