Comparative analysis of Direct and Indirect Model Reference Adaptive Control by Extended Kalman Filter
Volume-3 | Issue-3
Smart Wires and Modular FACTS Controllers for Smart Grid Applications: A Review
Volume-3 | Issue-4
Integrated Renewable Energy Management System for Reduced Hydrogen Consumption using Fuel Cell
Volume-3 | Issue-1
Wireless Power Transfer Device Based on RF Energy Circuit and Transformer Coupling Procedure
Volume-3 | Issue-3
Artificial Intelligence based Business Process Automation for Enhanced Knowledge Management
Volume-3 | Issue-2
Unmanned Aerial Vehicle with Thermal Imaging for Automating Water Status in Vineyard
Volume-3 | Issue-2
Design of Effective Smart Communication System for Impaired People
Volume-2 | Issue-4
Automated Multimodal Fusion Technique for the Classification of Human Brain on Alzheimer’s Disorder
Volume-3 | Issue-3
Prediction of Energy Consumption by Ships at the port using Deep Learning
Volume-3 | Issue-2
A Novel Adaptive Fuzzy MPPT Algorithm under Changing Atmospheric Conditions
Volume-3 | Issue-4
Power Transfer Capability Recognition in Deregulated System under Line Outage Condition Using Power World Simulator
Volume-3 | Issue-4
Transformer Oil Diagnostic Tests Analysis using Statistical Correlation Technique
Volume-4 | Issue-3
Design of Inverter Voltage Mode Controller by Backstepping Technique for Nonlinear Power System Model
Volume-3 | Issue-4
Automated Multimodal Fusion Technique for the Classification of Human Brain on Alzheimer’s Disorder
Volume-3 | Issue-3
Performance Analysis of Multiple Pico Hydro Power Generation
Volume-2 | Issue-2
Energy Efficient Data Mining Approach for Estimating the Diabetes
Volume-3 | Issue-2
Wireless Power Transfer Device Based on RF Energy Circuit and Transformer Coupling Procedure
Volume-3 | Issue-3
Prediction of Energy Consumption by Ships at the port using Deep Learning
Volume-3 | Issue-2
A Novel Adaptive Fuzzy MPPT Algorithm under Changing Atmospheric Conditions
Volume-3 | Issue-4
Unmanned Aerial Vehicle with Thermal Imaging for Automating Water Status in Vineyard
Volume-3 | Issue-2
Volume - 3 | Issue - 1 | march 2021
Published
12 May, 2021
In order to increase the utilization of artificial intelligence in smart grids, it is necessary to have an accurate state estimation. This criterion is an essential aspect, along with other functionalities for successful control and monitoring. As the internet and utility network form an increasing interconnectivity, it leaves the state estimators in a state of vulnerability to various attacks like bad data detection and false data injection. Though there are many research-works done on detectors for false data detection, depending on the contingencies, the counter measure will also vary. A sudden change physically will have a high impact on the available data, resulting in incorrect classification of the future instances. As a means of addressing this issue, we have analyzed the differences between data manipulation change and physical grid change for better understanding. Focusing on distribution change, we used outage and have introduced analysis of historical data. The goal is to determine the important aspects thereby identifying the scope. We have also used statistical hypothesis and dimensionality reduction for testing purpose. We have used IEEE 14 bus system for evaluation based on the scenario of attack: under concept drift and without concept drift. The result shows a more accurate output when compared with the other previously existing methodologies using concept drift.
KeywordsMachine Learning Line outage Data Integrity attacks Smart Grid False data injection
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