Performance Analysis of Renewable Integrated IEEE Test Systems Under Normal and Cyber Attack
Implementation Plan:
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Scenario 1: IEEE-14 with AI Controller
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Step 1: Initially, we constructed the IEEE-14 bus Simulink model with hydro, solar, wind, and BESS units mapped to their buses under 11kV electric generation in each renewable energy, 220 kV transmission line and 30/20 kV Distribution line.
Step 2: Then we simulate and collect (load, PV/wind/BESS) profiles, breaker status, bus voltages/frequencies, PMU streams) data under different sequential/randomized ways to initiate normal, fault and cyber attack conditions.
Step 3: Next, we build training/validation sets from the collected data and train the Reinforcement Learning (RL) AI Controller.
Step 4: Next, we assess steady-state tracking and small-signal stability using the controller based on collected data.
Step 5: Finally, we plot performance for the following metrics:
5.1: Time vs Voltage (p.u.)
5.2: Time vs Frequency (Hz)
5.3: Time vs Active Power (P)
5.4: Time vs Reactive Power (Q)
5.5: Time vs SoC (%)
Scenario 2: IEEE-14 with PID Controller
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Step 1: Initially, we constructed the IEEE-14 bus Simulink model with hydro, solar, wind, and BESS units mapped to their buses under 11kV electric generation in each renewable energy, 220 kV transmission line and 30/20 kV Distribution line.
Step 2: Then we simulate and collect (load, PV/wind/BESS) profiles, breaker status, bus voltages/frequencies, PMU streams) data under different sequential/randomized ways to initiate normal, fault and cyber attack conditions.
Step 3: Next, we tune the PID controller parameters (Kp, Ki, Kd) using the collected data to regulate voltage, frequency, power, and SoC.
Step 4: Next, we assess steady-state tracking and small-signal stability using the controller based on collected data.
Step 5: Finally, we plot performance for the following metrics:
5.1: Time vs Voltage (p.u.)
5.2: Time vs Frequency (Hz)
5.3: Time vs Active Power (P)
5.4: Time vs Reactive Power (Q)
5.5: Time vs SoC (%)
Scenario 3: IEEE-14 with ANFIS Controller
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Step 1: Initially, we constructed the IEEE-14 bus Simulink model with hydro, solar, wind, and BESS units mapped to their buses under 11kV electric generation in each renewable energy, 220 kV transmission line and 30/20 kV Distribution line.
Step 2: Then we simulate and collect (load, PV/wind/BESS) profiles, breaker status, bus voltages/frequencies, PMU streams) data under different sequential/randomized ways to initiate normal, fault and cyber attack conditions.
Step 3: Next, we utilize an ANFIS controller (User defined or Built-in) that takes inputs during simulation and computes control actions to regulate network stability using the collected data.
Step 4: Next, we assess steady-state tracking and small-signal stability using the controller based on collected data.
Step 5: Finally, we plot performance for the following metrics:
5.1: Time vs Voltage (p.u.)
5.2: Time vs Frequency (Hz)
5.3: Time vs Active Power (P)
5.4: Time vs Reactive Power (Q)
5.5: Time vs SoC (%)
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, please provide detailed steps, parameters, models, or expected results in advance. Once the implementation is complete, changes will not be possible without prior input. Otherwise, we will proceed according to our current 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.
