Frequency regulation of hybrid shipboard microgrid system using butterfly optimization algorithm synthesis fractional‐order controller

Abstract

Inclusion of intermittent natured renewable energy resources in microgrid to reduce global warming, especially in shipboard power system and due to highly fluctuating propulsion load, frequency control strategy of isolated shipboard hybrid microgrid (ISHMG) is major point of attraction. Hence, a power system of marine vessel with dish‐stirling solar thermal system (DSTS), wind‐driven generation (WDG), solid oxide fuel cell (SOFC), super‐conducting magnetic energy storage (SMES), two different AC‐loads, and propulsion loads are considered as an ISHMG. The main objective of this paper is reducing the mismatch between generation and demand with the help of fractional‐order proportional integral‐derivative (FOPID) controller. To improve the frequency control, the tuning of the controller coefficients plays a major role as the controller's performance fully dependent on the parameters. Accordingly, the recently developed butterfly optimization algorithm (BOA) has been used to optimize the FOPID controller's parameters. Comparative analysis of several techniques like FA, PSO, GOA, SSA, and BOA used for PID, PI, FOPID controllers' optimization, and sensitivity analysis under different parametric variation has been presented to prove the stability of the ISHMG model. Analyzing all the results, it is found that BOA‐based FOPID controller is performing the frequency control far better than other techniques.

Enhancement of a Hybrid Electric Shipboard Microgrid’s Frequency Stability With Triangulation Topology Aggregation Optimizer-Based 3DOF-PID-TI Controller

“…While several LFC works have been proposed for conventional MG and conventional power grids, there is a dearth of research on how to deal with LFC in marine/shipboard MGs. Different techniques for resolving the frequency control problem in several shipboard MG systems have been developed in recent studies [30][31][32]. In order to reduce frequency deviations brought on by variations in load, Ref.…”

Optimal Load Frequency Control of a Hybrid Electric Shipboard Microgrid Using Jellyfish Search Optimization Algorithm

“…Recent studies [29][30][31] proposed different algorithms for solving the issue of frequency control in different shipboard MG systems. Reference [29] introduces a coordinated control technique that utilizes an SSA-optimized hybrid fuzzy fractional-order PI-fractional-order PID (FFOPI-FOPID) to decrease frequency deviations caused by load changes.…”

“…Reference [29] introduces a coordinated control technique that utilizes an SSA-optimized hybrid fuzzy fractional-order PI-fractional-order PID (FFOPI-FOPID) to decrease frequency deviations caused by load changes. The GOA and butterfly optimization algorithm (BOA) are used to tune the controller gains of fuzzybased PID with a filter and fractional-order controller in [30,31], respectively.…”

Special issue on: AI/data‐based modeling, control, and operation of smart grid power systems

“…The target is to showcase advanced methodologies to address the identified control challenges in fast‐evolving smart grid frameworks. A multiloop frequency controller augmented with fractional‐order calculus with in‐depth qualitative analysis for smart grid has been presented 1,2 . The challenging area in EV charging stations with PV array and distribution network, 3 optimal power flow with renewables integrated smart grid, 4 security assessment of grid‐connected society during grid failure or blackouts, 5 resilient power quality control framework for an autonomous microgrid, 6 and detection of false data injection attacks in smart grid 7 have been addressed to cope with challenging issues in smart grid operation/control continuum.…”

“…A multiloop frequency controller augmented with fractional-order calculus with in-depth qualitative analysis for smart grid has been presented. 1,2 The challenging area in EV charging stations with PV array and distribution network, 3 optimal power flow with renewables integrated smart grid, 4 security assessment of grid-connected society during grid failure or blackouts, 5 resilient power quality control framework for an autonomous microgrid, 6 and detection of false data injection attacks in smart grid 7 have been addressed to cope with challenging issues in smart grid operation/control continuum.This SI has explored the possible emerging control frameworks in different research domains to counteract challenges and ensure the high resiliency of smart grid systems employing different AI methodologies, a step forward to meeting net-zero carbon footprint. From the readers' perspective, an extensive comprehensive overview of salient features of advanced control/operation of smart grids has been included.This SI has been made and floated during/post-COVID-19 pandemic when all aspects of our daily life were affected.…”