Optimal Load Distribution in DG Sources Using Model Predictive Control and the State Feedback Controller for Switching Control

Abstract

The distributed energy management of interconnected microgrids, which is based on model predictive control (MPC), relies on the cooperation of all the agents (i.e., microgrids). Model predictive control or MPC is widely used in industrial applications as an effective tool for dealing with multivariable limited control problems. MPC uses an explicit system model to predict the future horizon of the system and its outputs. This predictability allows calculating the optimal order of inputs to minimize output errors over a limited horizon, which is effected by the limitations of the system. This study presents a distributed economic model predictive control method using the new state feedback controller to control the switching of interface converters and compensate for the unbalanced and nonlinear loads. In this model, the islanding mode and the reconnection of the grid are considered to improve the transient behavior of the system to achieve steady-state power distribution. It has been proposed that it could obtain better results in predictive control, utilizing similarity transform in the state matrix and its modification. First, this model is simulated on distributed generation sources with power-sharing and local loads using the state feedback controller in MATLAB Simpower. Then, the performance of the proposed method is evaluated, confirming that it is more reliable than the FS-MPC and DSVM-MPC methods.

Adaptive Intelligent Model Predictive Control for Microgrid Load Frequency

“…These data are then used to learn the type-2 fuzzy system (based on a neural network or using evolutionary algorithms). For more information on the type-2 fuzzy system and its equations, see [35,36].…”

“…Some researchers have also used secondary frequency control over the converter of renewable energy production sources to control the frequency [34]. One of the control methods that has been successful in all engineering fields is model predictive control (MPC) [35,36]. This control method is based on predicting the system behavior (from the mathematical model of the system) and generating a control signal to minimize the error.…”