Robust Control Design for Voltage and Frequency Fluctuation Control under Substantial Load Variation of Islanded Microgrid System

The use of standalone microgrids is rapidly increasing due to their advantages in terms of environmental, economic, and technical aspects. However, the microgrid is vulnerable to frequency and voltage oscillation because of its separation from the main grid, the uncertainties of loads, and the use of uncertain renewable energy sources such as wind and solar energy. Therefore, the need for a dynamic controller arises to regulate voltage and frequency. This paper presents Double Integral Sliding Mode Control (DISMC) and Artificial Neural Network (ANN) based on the Feed Forward Bayesian Regularization (FF-BR) algorithm. DISMC is developed to control voltage and steady-state error. The ANN based on the FF-BR algorithm is adapted to regulate the current. These controllers enhance the performance of droop control for inverter base Distributed Generation (DG) units in an islanded microgrid system. The controllers are designed based on the islanded microgrid dynamic model and load variations. The suggested control algorithm is implemented in Matlab/Simulink. The performance of the controller is evaluated under variable loads and uncertainties. The results are then compared with droop control with the Proportionate Integral (PI) controller. The performance of the proposed controllers is seen to outdo the existing PI method in the regulation of voltage and frequency.

کلیدواژه ها:

Distributed generation ، double integral sliding mode control ، droop control ، bayesian regularization ، photo voltaic