scholarly journals Real-Time False Data Detection in Smart Grid Based on Fuzzy Time Series

2019 ◽  
Vol 18 (5) ◽  
pp. 445-450
Author(s):  
Abdelkarim El Khantach ◽  
Mohamed Hamlich ◽  
Noureddine Belbounaguia
Keyword(s):  
Time Series ◽  
Smart Grid ◽  
Real Time ◽  
Fuzzy Time Series ◽  
Data Detection ◽  
Grid Based ◽  
False Data Detection

A Novel Real-Time False Data Detection Strategy for Smart Grid

2021 ◽  
Author(s):  
Debottam Mukherjee ◽  
Samrat Chakraborty ◽  
Ramashis Banerjee ◽  
Joydeep Bhunia
Keyword(s):  
Smart Grid ◽  
Real Time ◽  
Data Detection ◽  
Detection Strategy ◽  
False Data Detection

A Robust False Data Detection in Smart Grid Using Trees Decision Algorithm

2018 ◽  
Author(s):  
Abdelkarim El Khantach ◽  
Mohamed Hamlich ◽  
Nour Eddine Belbounaguia
Keyword(s):  
Smart Grid ◽  
Data Detection ◽  
Decision Algorithm ◽  
False Data Detection

Smart-Grid Based Real-Time Load Management Methodology for Power Deficient Systems

2015 ◽  
Vol 3 (6) ◽  
Author(s):  
M. Amin ◽  
A. Rasheed ◽  
A. A. Raja ◽  
A. Lateef ◽  
S. Khalid ◽  
...  
Keyword(s):  
Smart Grid ◽  
Real Time ◽  
Load Management ◽  
Grid Based

Classification for consumption data in smart grid based on forecasting time series

2016 ◽  
Vol 141 ◽  
pp. 191-201 ◽  
Author(s):  
Kálmán Tornai ◽  
Lóránt Kovács ◽  
András Oláh ◽  
Rajmund Drenyovszki ◽  
István Pintér ◽  
...  
Keyword(s):  
Time Series ◽  
Smart Grid ◽  
Consumption Data ◽  
Grid Based

scholarly journals DESCRIPTION AND IDENTIFICATION OF TEMPORAL REGULARITIES FOR FUZZY TIME SERIES WITH APPLICATION OF HYBRID OLS-PATTERNS

2018 ◽  
Vol 45 (2) ◽  
pp. 104-113
Author(s):  
D. V. Dultsev ◽  
L. I. Suchkova
Keyword(s):  
Time Series ◽  
Knowledge Base ◽  
Real Time ◽  
Fuzzy Time Series ◽  
Time Shift ◽  
Partial Data ◽  
Linear List ◽  
Fuzzy Linguistic Variable ◽  
Observable Data ◽  
Scientific Results

ObjectivesThe aim of the research is to develop the principle of storing data templates to take their temporal natureinto account, making it possible to reduce decision-making times.In order to describe and identify temporal patterns in fuzzy time series behaviour in real time, the task was set to develop a hybrid data structure that allows for a consideration of sequences of fuzzy values formed from clear observable data as well as a determination of the length of these sequences and possible uneven time intervals between the observations.MethodsThe article discussesan approach to formalising the description of temporal cause-effect relationships between events occurring at the object location as well as that of its environment, based on a set of singly-connected lists of triplets. Each triplet contains a fuzzy linguistic variable, the duration of its observation and the permitted interval of observation of insignificant data.ResultsAn algorithm for detecting knowledge base patterns in real time was developed, taking into account the possibility of a time shift in observing long sequences of identical values of the observed value. The possibility of partial data overlapping corresponding to triplets of different patterns is taken into account. The proposed hybrid pattern makes it possible to accelerate the detection of temporal regularities in the data.ConclusionScientific results are presented by the developed structure for storing information on temporal regularities in data, based on a singly linked linear list, as well as an algorithm for finding regularities in observational data using a set of OLS-patterns. The advantage of this structure and algorithm in comparison with the known ways of storing and analysing temporal data is a reduction in the amount of memory necessary for storing templates in the knowledge base, as well as the possibility of applying OLS patterns for decisionmaking purposes.

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