研究目的
To propose a PID controller based on adaptive radial basis function (RBF) neural network to adjust the PID parameters adaptively, improving the response speed, anti-interference ability, and robustness of the traditional PID controller in energy storage systems for photovoltaic microgrids.
研究成果
The RBF neural network adaptive PID control strategy effectively adjusts PID parameters online, improving the dynamic characteristics of the energy storage system in photovoltaic microgrids. The simulation results demonstrate the controller's ability to stabilize the output power under varying irradiance and temperature conditions, suggesting its potential for practical applications in peak load shifting and improving the robustness of output power.
研究不足
The study is based on simulation results using MATLAB/Simulink, and real-world application may present additional challenges not accounted for in the simulation. The effectiveness of the controller in larger or more complex systems remains to be tested.
1：Experimental Design and Method Selection:
The study employs an RBF neural network adaptive PID control strategy for the energy storage system in a photovoltaic microgrid. The methodology includes the design of the RBF neural network structure, the derivation of the PID controller with anti-windup compensator, and the online adjustment of PID parameters.
2：Sample Selection and Data Sources:
A 100kW photovoltaic array simulation model is built in MATLAB/Simulink to demonstrate the effectiveness of the designed controller.
3：List of Experimental Equipment and Materials:
MATLAB/Simulink software is used for simulation.
4：Experimental Procedures and Operational Workflow:
The simulation process lasts 1000s with a sampling time of T=1s. The irradiance and temperature are varied to simulate real-world conditions.
5：1s. The irradiance and temperature are varied to simulate real-world conditions.
Data Analysis Methods:
5. Data Analysis Methods: The performance of the controller is evaluated based on the stability of the output power of the photovoltaic system under varying conditions.
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