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Research Article

Optimal dynamic frequency regulation of renewable energy based hybrid power system utilizing a novel TDF-TIDF controller

ORCID Icon, & ORCID Icon
Pages 10733-10754 | Received 13 Jun 2022, Accepted 08 Dec 2022, Published online: 19 Dec 2022
 

ABSTRACT

Insertion of intermittent natured renewable energy resources in the microgrid to decline global warming and due to highly inconsistent propulsion load, frequency control of the isolated hybrid micro-grid system (HMGs) is the key point of attraction and necessitates a highly competent and robust control strategy. Hence, in this paper, an efficient frequency control mechanism for HMGs is proposed by utilizing an efficient tilt derivative filter-tilt integral derivative filter (TDF-TIDF) controller. HMGs are composed of solar, wind, fuel cell, freezer, diesel engines, heat pumps, and loads. A recently appeared dragonfly algorithm (DFA) is employed to optimize the suggested controllers’ design variables. The dynamic analysis is exhibited with different types of energy storage units under various conditions. The conditions incorporate perturbations in demanded load and power generation through renewable energy sources. In this study, solar thermal and wind power systems are not contributing to frequency control owing to the plan of their maximum power tracking approach. The dynamic performance of different controllers such as PIDF, TIDF, PDF-PIDF, and TDF-TIDF controllers are evaluated with their design variables tuned by employing genetic algorithm, particle swarm optimization, gravitational search algorithm, quasi harmony search algorithm, grasshopper algorithm and dragonfly algorithm. The output graphs of transient responses and collected statistical data corroborate that the suggested DFA-based TDF-TIDF scheme provides least objective function value (8.1e07) compared to PDF-PIDF (4.011e06), TIDF (3.14e05) and PIDF (5.03e05), hence, more capable in reducing the oscillations quickly for the system with non-linearities. Moreover, statistical data yielded by DFA is observed superior when evaluated with other existing optimization methods.

Disclosure statement

No potential conflict of interest was reported by the authors.

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