sys.online|est.2009|serving AU / UK / CA / GLOBAL
Renewable Energy
MATLAB/Simulink
Video Output

AI-Based Energy Management for Smart-Grid EV Charging Using Supervised MLP-ANN MATLAB Simulink

Renewable-energy and microgrid simulation workflow for PV, BESS, EV charging and grid-forming inverter control. This page is structured for engineering students, OEM teams and PhD research scholars looking for simulation output references, waveform explanation and model implementation support.

SIMULATION_OUTPUT — AI-Based Energy Management for Smart-Grid EV Charging Using Supervised MLP-ANN MATLAB Simulink.mp4

PROJECT_THUMBNAIL

AI-Based Energy Management for Smart-Grid EV Charging Using Supervised MLP-ANN MATLAB Simulink project thumbnail image
Contents are for representative purposes, actual content may vary.

Project Objective

Renewable-energy and microgrid simulation workflow for PV, BESS, EV charging and grid-forming inverter control. The objective is to present a verified simulation workflow with clear output interpretation, model-study direction and project documentation support.

Software Used

MATLAB/Simulink, scopes, control blocks, signal logging and waveform analysis.

Control / Algorithm Methodology

droop control, energy-management logic, MPPT/charging coordination, grid-forming voltage-frequency regulation and microgrid dynamic control.

Expected Waveform Outputs

DC-link voltage, battery SOC, PV power, inverter voltage/current, frequency, load sharing, power balance and transient response.

Applications

smart grids, islanded microgrids, EV charging infrastructure, PV-BESS systems, OEM studies and PhD renewable-energy research.

Simulation Model Explanation

The model can be used to study controller behaviour, transient performance, input/output response and result quality under representative operating conditions. The project page supports model verification, research report preparation, waveform interpretation and implementation discussion for Renewable Energy workflows.

Result Interpretation

Result interpretation focuses on stable response, improved regulation, reduced error or harmonic content, and useful comparison between reference command and measured simulation output. The displayed video and thumbnail provide a quick visual check before contacting for the full model, code, explanation or documentation.

Need this simulation model?

Share the project title, software version, required outputs and deadline. We support OEM-style validation, PhD research implementation, report writing and waveform explanation.

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