Performance Analysis of Detection and Prevention of Cyber Attacks on Smart Grid Connected Inverter
Implementation plan:
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Step 1: Initially, We construct a Micro Grid physical system Simulink Model
Step 2: Then, we collect electrical measurement data from sensors and actuators in smart inverters within a microgrid system.
Step 3: Next, we detect the cyber attacks using Graph Neural Networks (GNN) with random Denial-of-Service (DoS) based on collected data.
Step 4: Next, we Classify the time series anomalies using the BiGRU-LSTM deep learning model.
Step 5: Next, we distribute the communication load using the Multi-Agent Reinforcement Learning (MARL) method.
Step 6: Next, we Implement an Adaptive Countermeasure Response Mechanism using ANFIS to dynamically adjust grid operation and mitigate cyber threats.
Step 7: Finally, we plot performance metrics for the following
7.1: Time vs. Detection Accuracy (%)
7.2: Time vs. Current (A)
7.3: Time vs. Voltage (V)
7.4: Time vs. Communication Overhead (kbps)
Software Requirements:
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1. Development Tool: Matlab-R2023a/Simulink or above
2. Operating System: Windows-10 (64-bit) or above
Note:
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1) If the plan does not meet your requirements, provide detailed steps, parameters, models, or expected results in advance. Once implemented, changes won’t be possible without prior input; otherwise, we’ll proceed as per our implementation plan.
2) If the plan satisfies your requirement, Please confirm with us.
3) Project based on Simulation only, not a real time project.
4) Please understand that any modifications made to the confirmed implementation plan will not be made after the project development.
