Chaotic butterfly optimization algorithm based cascaded PI‐TID controller for frequency control in three area hybrid microgrid system

Abstract

The work represents a unique methodology for control of frequency in three area independent and interconnected hybrid microgrid systems. The proposed hybrid microgrids consist of solar chimney (SC), combined solar gas turbine (CSGT), bio‐diesel operated generator (BDOG), DC link, energy storage units such as battery energy storage unit (BESU), super‐magnetic energy storage unit (SMESU), and redox flow battery (RFB) based. Integration of generating units such as SC, CSGT, BDOG, SMESU, RFB, and DC link in three area hybrid microgrid is also a unique work. A newly developed chaotic butterfly optimization algorithm (CBOA) is applied so as to obtain the optimized standards of the cascaded PI‐TID controller employed with dispatchable generating units. Comparative analysis of different algorithms and controllers is achieved to establish the dominance of the anticipated control strategy. The impact of each component on the system is examined while taking into account various real‐time scenarios. Finally, the efficacy of cascaded PI‐TID controller tuned using CBOA is established by sensitivity analysis with significant changes in source and load circumstances.

Load frequency control in deregulated power system with renewable energy sources: Hybrid GOA‐SNN technique

“…Debnath et al, 12 have developed a control action of the traditional type PID controller; a non-integer type PID controller was used. Bhuyan et al, 13 has presented a novel way for frequency control in 3 region-independent and linked hybrid microgrid (MG) systems. The hybrid MGs employed solar chimneys (SC), biodiesel operated generators (BDOG), combined solar gas turbines (CSGT), DC links, and energy storage units like redox flow batteries (RFB), battery energy storage units (BESU), and super-magnetic energy storage units (SMESU).…”

A Novel Prairie Dog-Based Meta-Heuristic Optimization Algorithm for Improved Control, Better Transient Response, and Power Quality Enhancement of Hybrid Microgrids

“…A robust LFC-based African vulture optimization algorithm has been proposed by the authors for optimizing a hybrid MG's frequency response under variable renewable source conditions [18]. Some of the other popular techniques used for PQ enhancement in MG are Aquila optimizer [19], fuzzy logic controller [20], adaptive-network fuzzy inference [21], green leaf-hopper flame optimization [22], SVM-based random subspace [23], chaotic butterfly optimization [24], deep convolutional neural network [25], artificial neural network [26], wavelet-fuzzy [27], support vector machine [28], model predictive control [29], stochastic dynamic programming [30], quantum teaching learning-based optimization [31], multiagent system [32], crow search optimization technique [33], amended penguin optimization algorithm [34], and squirrel search algorithm [5]. Thorough study and analysis of popular contemporary algorithms available in the literature have been conducted.…”