Modeling and Simulink of Grid and Market Integration of Renewable Energy Resources
Step 1: Initially, We construct a grid with renewable energy source with IEEE 30 Bus Simulink Model.
Step 2: Then, we collect Energy source data and preprocess for cleaning, managing missing values, outlier recognition, and normalization.
Step 3: Next, we forecast the renewable energy generation using AI-Biruni Earth Radius (BER) model with the Convolutional Neural Network Echo State Network (CNN-ESN) based on energy source data.
Step 4: Next, we implement Reinforcement learning-based Soft Actor Critic (SAC) agent with PSO and a rule-based controller to improve the adaptability of the grid.
Step 5: Next, we perform Dynamic pricing and manage the power using Power Grid Intelligent Pricing (PGIP) algorithm with Genetic Fire Hawk Optimization (GFHO) algorithm.
Step 6: Next, we optimize the energy storage using “Backward Approximate Dynamic Programming with Lyapunov Optimization algorithm (BADP-LOT) with Voltage Sensitivity Index Factor (VSIF) technique.
Step 7: Finally, we plot performance metrics for the following
7.1: Time vs. Voltage deviation (%)
7.2: Time vs. frequency (Hz)
7.3: Time vs. Power (KW)
7.4: Time Vs. Energy storage efficiency (%)
7.5: Number of Epochs Vs Root Mean Square Error (RMSE)
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.
We perform with an existing approach Reference 1 :- Title: Real-Time Scheduling for Optimal Energy Optimization in Smart Grid Integrated With Renewable Energy Sources
