Enhancement the Frequency Stability and Protection of Interconnected Microgrid Systems Using Advanced Hybrid Fractional Order Controller

Abstract

Substituting conventional energy sources with new renewable sources is crucial issue nowadays in energy generation systems to face climate changes and increased load demands. Due to the increased penetration levels of renewable sources in power systems, the benefits of the high-inertia of conventional sources are being insufficient. The resulting low-inertia power systems introduce several stability, reliability, and coordination problems for power system operation and control. Therefore, this paper tackles the coordination assessment and enhancement between digital frequency relays using a new fractional order load frequency controller equipped with superconducting magnetic energy storage (SMES) virtual inertia system. The improved coordination method is established using optimized fractional order controller based on slime mould optimization algorithm (SMA). The proposed SMA-based design method benefits the adaptive weights of SMA algorithm. The proposed design is generalized to be applied on single area and multi-area interconnected power systems as well. Compared to existing literature, this paper presents an advanced fractional order controller with coordinated operation with existing protection relays. The obtained results show the coordination shortcomings of renewable energy based microgrids with traditional control systems. However, improved design and coordination are obtained using the proposed SMA-optimized fractional order controllers. The superiority and feasibility of the proposed analysis and methods are verified on different case studies using single and multiple interconnected areas.INDEX TERMS Coordination, digital frequency relay, fraction order control, load frequency controllers, slime mould algorithm (SMA), renewable energy microgrids.

Design Optimization of Improved Fractional-Order Cascaded Frequency Controllers for Electric Vehicles and Electrical Power Grids Utilizing Renewable Energy Sources

“…Additional LFC proposals have been proposed in the literature, such as the sliding mode LFC, machine and deep learning-based LFC, linear matrix inequalities (LQR), etc. [9]. Additionally, type-2 fuzzy modelling and control methods have been shown to have better performance in the literature.…”

SOS Approach for Practical Stabilization of Tempered Fractional-Order Power System

“…In fractional calculus, non-integer order integrals and differential operators are studied, as well as their applications. Fractional-order models are more accurate and efficient than classical models, and non-integer derivative operators are essential for describing physical events, for example, [1][2][3][4]. There has been considerable research on the benefits of fractional calculus in a wide range of fields, including applied mathematics, biology, mechanics, finance, engineering and control theory [5][6][7][8][9][10][11][12][13][14][15][16][17].…”

New Cascaded 1+PII2D/FOPID Load Frequency Controller for Modern Power Grids including Superconducting Magnetic Energy Storage and Renewable Energy

“…Two modified versions of manta ray foraging optimizations algorithm (MRFO) using chaotic map, and the weighting factor (named CMRFO and WCMRFO) have been proposed in [42] for EV-based interconnected microgrids. A coordination strategy between protection devices and TFOID with PI as virtual inertia controller has been provided in [43], in which the SMA has been proposed for optimizing the employed control schemes.…”

“…The paper is concluded in Section 6. I JBO [25] PID - [28] PI, PID ARO [26] Nonlinear PI DO [27] I, PI PSO [30] Fuzzy PIDD2 GBO [40] iFOI GWO [35] FOPID SCA Have more parameters to tune [36] FOPID MDWA FO-based Possess higher flexibility compared to IO ones [37] FOPIDF ICA LFC with Have improved disturbance mitigation compared to IO [38] TFOID AEO single input Have reduced rejection of existing disturbances [50] TID MRFO [39] FOPIDA GWO [41] TFOID SMA [42] TFOID CMRFO, WCM-RFO [43] TFOID with PI SMA [31] PD-PI ESMOA Possess high number of parameters to tune [32] 2DOF PID TLBO Cascaded LFC Have more flexibilities (degree of freedom) in design [33] PD-PID BA with multiple Provide better disturbance mitigation due to using cascaded loops [34] PI-PDF DTBO inputs can mitigate high as well as low frequency disturbances [44] 3DOF TID SSA Have better performance than single input LFC methods [45] FO-IDF ICA [46] PI-TDF SSA [29] PD-PIDA (STATCOM) ARO [47] FOPI-IDDF CSA [48] 1+PD/FOPID MRFO [49] 3DOF…”