Frontiers in Energy Research (Mar 2023)

Optimal real-time tuning of autonomous distributed power systems using modern techniques

  • Shamik Chatterjee,
  • Ahmed Nura Mohammed,
  • Sachin Mishra,
  • Naveen Kumar Sharma,
  • Ali Selim,
  • Mohit Bajaj,
  • Mahmoud Rihan,
  • Salah Kamel,
  • Salah Kamel

DOI
https://doi.org/10.3389/fenrg.2023.1055845
Journal volume & issue
Vol. 11

Abstract

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This work considers using a novel heuristic population-based evolutionary algorithm [viz., the moth flame optimization (MFO) algorithm] to regulate the conventional controller installed in an autonomous power system (APS). The moth flame optimization algorithm intends to produce the optimal magnitudes of the proportional-integral-derivative plus second derivative (PIDD2) controller parameters along with its first- and second-order low-pass filter constraints (installed in the investigated autonomous power system). The present task includes a comparison of the voltage response profiles of the investigated system obtained by the proposed moth flame optimization-based proportional-integral-derivative plus second derivative controller and those obtained by other algorithms (conveyed in current state-of-the-art literature) based on a proportional-integral controller. A fast-acting Sugeno fuzzy logic (SFL) technique is used to achieve the dynamic online results of the investigated autonomous power system model for online, off-nominal operational circumstances. Under step perturbations, the time-domain transient investigation in reference to voltage and/or mandate of load for the proposed autonomous power system model is inspected. Additionally, the robustness of the proposed moth flame optimization-based proportional-integral-derivative plus second derivative controller is investigated to test its behavior. An investigation has been provided by varying the model components of the studied autonomous power system model. It may be reported, as per the results obtained from the simulation, that the proposed moth flame optimization-based proportional-integral-derivative plus second derivative controller is an effective control strategy for the autonomous power system. The current research effort indicates that the proposed moth flame optimization algorithm, along with Sugeno fuzzy logic, may be useful for the actual time process of an autonomous power system.

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