Power Management Strategy Based on Adaptive Neuro Fuzzy Inference System for AC Microgrid
Objective
The main objective of this project is to achieve MG power balance, decrease DG fossil fuel to minimum consumption, keep the MG voltage stability and finally tracking the maximum power point (MPP) of each RER.
Abstract
Microgrids (MGs) have been widely implemented as they increase the efficiency and resiliency of electrical networks. However, the uncertain nature of renewable energy resources (RERs) integrated into the MGs usually results in different technical problems. System stability, the most challenging problem, can be achieved via a robust power management strategy (PMS) of the MG.
This paper introduces a PMS based on adaptive neuro fuzzy inference system (ANFIS) for AC MG consisting of a diesel generator (DG), a double fed induction generator (DFIG) driven by a wind turbine (WT) and a solar photovoltaic (PV) panel. The proposed strategy aims to achieve MG power balance, decrease DG fossil fuel to minimum consumption, and keep the MG voltage stability and finally tracking the maximum power point (MPP) of each RER. Metaheuristic optimization techniques; including genetic algorithm (GA) and particle swarm optimization (PSO), are employed to train the ANFIS to accomplish the desired objectives and fulfill the generation/consumption balance.
Keywords: Microgrid, renewable energy resources, power management strategy, voltage stability, adaptive neuro fuzzy inference system, double fed induction generator, genetic algorithm, particle swarm optimization
NOTE: Without the concern of our team, please don't submit to the college. This Abstract varies based on student requirements.
Block Diagram
Specifications
Software Configuration:
Operating System : Windows 7/8/10
Application Software : Matlab/Simulink
Hardware Configuration:
RAM : 8 GB
Processor : I3 / I5(Mostly prefer)
Learning Outcomes
- Introduction to Matlab/Simulink
- What is EISPACK & LINPACK
- How to start with MATLAB
- About Matlab language
- About tools & libraries
- Application of Matlab/Simulink
- About Matlab desktop
- Features of Matlab/Simulink
- Basics on Matlab/Simulink
- How to Improve Power Quality?
- Introduction to Renewable energy sources.
- Introduction to Matlab/Simulink software
- Introduction to FACTS devices
- Design of solar PV system.
- Introduction to power converters.
- Design of Voltage source converter.
- Design of Boost converter.
- Design of MPPT controller.
- Design of UPQC.
- Design of BESS.
- How BESS works?
- Design of sim power systems tool boxes.
- Design of simulink tool boxes.
- We can learn about the generation of gate pulses to the converter.
- We can learn about the differences between Linear and nonlinear loads.
- Introduction to controllers.
- Design of PI controller.
- Introduction to open loop and closed loop control system.
- We can learn about the Clarke’s transformation.
- We can learn about the park’s transformation.
- Design of PLL.
- Introduction to PWM.
- Design of Hysteresis controller.
- Design of self-tuning filter (STF) integrated with the unit vector generator (UVG) technique.
- Project Development Skills:
- Problem analyzing skills
- Problem solving skills
- Creativity and imaginary skills
- Programming skills
- Deployment
- Testing skills
- Debugging skills
- Project presentation skills
- Thesis writing skills
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Disclaimer - Takeoff Edu Group Projects are not associated or affiliated with IEEE in any way. The IEEE Projects mentioned here are mentioned in the context of student projects, whose ideas are derived from IEEE publications, not projects of or by IEEE.
