Decentralized and Distributed Control for Microgrids Matlab Simulink
Title: - An Adaptive Intelligent Distributed Decentralized Protection and Control Strategy for MESH Topology based Microgrid Clusters using Intellectual Techniques
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Implementation Plan:
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Step 1: Initially we design the Multi-Microgrid with micro and load controllers (MC & LC), Distributed Microgrid Agents (DMAs), 6G base stations, Intelligent Protection and Control Agents (IPCA), and Intelligent Distributed Energy Management Agents (IDEMA).
Step 2: Then, perform the Microgrid Clustering based on the three major metrics such as stability, reliability, and scalability.
Step 3: Next, IPCA performs the fault type identification and localization by using Enhanced Multi-Layer Perceptron (EMLP).
Step 4: Next IDEAs perform the islanding detection by using Lightweight Support Vector Machine (LSVM). and also perform the optimized energy and power management scheme using Coati Optimization Algorithm (COA).
[the process based on your proposal , An Adaptive Intelligent Distributed Decentralized Protection and Control Strategy for MESH Topology based Microgrid Clusters using Intellectual Techniques]
Step 5: Finally, we display the following result,Time (Sec) Vs Power Available at PCC (Watts), Time (Sec) Vs Reactive Power (Var), Time (Sec) Vs Voltage as PCC (Volt), Time (Sec) vs Fault Identification Rate (%), Time (Sec) Vs RMS line current (A) and Time (Sec) Vs RMS line Voltage (V)
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Software Requirement:
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1. Tool: Matlab R2020a\Simulink
2. OS: Windows 10 – (64-bits)
we perform the existing process based on the title:- An Adaptive Neuro-Fuzzy Control Strategy for Improved Power Quality in Multi-Microgrid Clusters
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Please remember to use IEEE's microgrid benchmark (A Benchmark Test System for Networked Microgrids) as a test system. I am attaching it again for your attention. The attached paper contains all the data of the microgrid.
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#microgrid
#matlab
#simulink
#PhDThesis
#MicrogridResearch
#RenewableEnergy
#SustainablePower
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