Fractional-Order Control Techniques for Renewable Energy and Energy-Storage-Integrated Power Systems: A Review

Author:

Alilou Masoud1ORCID,Azami Hatef1ORCID,Oshnoei Arman2ORCID,Mohammadi-Ivatloo Behnam13ORCID,Teodorescu Remus2ORCID

Affiliation:

1. Faculty of Electrical and Computer Engineering, University of Tabriz, Tabriz 51666-16471, Iran

2. Department of Energy, Aalborg University, 9220 Aalborg, Denmark

3. Department of Electrical Engineering, School of Energy Systems, LUT University, 53850 Lappeenranta, Finland

Abstract

The worldwide energy revolution has accelerated the utilization of demand-side manageable energy systems such as wind turbines, photovoltaic panels, electric vehicles, and energy storage systems in order to deal with the growing energy crisis and greenhouse emissions. The control system of renewable energy units and energy storage systems has a high effect on their performance and absolutely on the efficiency of the total power network. Classical controllers are based on integer-order differentiation and integration, while the fractional-order controller has tremendous potential to change the order for better modeling and controlling the system. This paper presents a comprehensive review of the energy system of renewable energy units and energy storage devices. Various papers are evaluated, and their methods and results are presented. Moreover, the mathematical fundamentals of the fractional-order method are mentioned, and the various studies are categorized based on different parameters. Various definitions for fractional-order calculus are also explained using their mathematical formula. Different studies and numerical evaluations present appropriate efficiency and accuracy of the fractional-order techniques for estimating, controlling, and improving the performance of energy systems in various operational conditions so that the average error of the fractional-order methods is considerably lower than other ones.

Funder

University of Tabriz

Publisher

MDPI AG

Subject

Statistics and Probability,Statistical and Nonlinear Physics,Analysis

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