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This paper presents frequency containment of shipboard microgrid having renewable energy sources (RES) and energy storage systems (ESS). An accurate islanded shipboard microgrid model has been simulated with renewable energy resources like solar PV (SPV), sea wave energy, wind energy, bio-diesel generator (BDG), bio-mass combined heat and power (BCHP), solid oxide fuel cell (SOFC), aqua electrolyser (AE), and battery energy storage system (BESS). The generating units and the storage systems mentioned above are used in the system, which are built using the transfer function model. The performance of the load frequency control (LFC) scheme for the proposed Shipboard Hybrid Microgrid System (SHMG) has also been evaluated using the tuned proportional integral derivative (PID) and tilt integral derivative (TID). In order to minimize the objective function of the system model, this work employs several optimisation methods such as Selfish Herd Optimisation (SHO), Grey Wolf Optimisation Algorithm (GWO), Grasshopper Optimisation Algorithm (GOA), and Particle Swarm Optimisation (PSO) to enhance better tuning of the controller parameters based on an objective function like integral time squared error (ITSE). Analysis of the power output curves and frequency response curves from simulation for several case studies demonstrates the superiority of the proposed approach for load frequency control.

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Load Frequency Control in Shipboard Hybrid Microgrid

  • 会议论文

  • 发表日期：

    2025年

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  • Chirayu Hatibaruah,
  • Akash Sahu,
  • Pranab Kalita,
  • Subash Chandra Sahoo,
  • Kothalanka K. Pavan Kumar,
  • Smriti Jaiswal,
  • Dulal Ch. Das

摘要

This paper presents frequency containment of shipboard microgrid having renewable energy sources (RES) and energy storage systems (ESS). An accurate islanded shipboard microgrid model has been simulated with renewable energy resources like solar PV (SPV), sea wave energy, wind energy, bio-diesel generator (BDG), bio-mass combined heat and power (BCHP), solid oxide fuel cell (SOFC), aqua electrolyser (AE), and battery energy storage system (BESS). The generating units and the storage systems mentioned above are used in the system, which are built using the transfer function model. The performance of the load frequency control (LFC) scheme for the proposed Shipboard Hybrid Microgrid System (SHMG) has also been evaluated using the tuned proportional integral derivative (PID) and tilt integral derivative (TID). In order to minimize the objective function of the system model, this work employs several optimisation methods such as Selfish Herd Optimisation (SHO), Grey Wolf Optimisation Algorithm (GWO), Grasshopper Optimisation Algorithm (GOA), and Particle Swarm Optimisation (PSO) to enhance better tuning of the controller parameters based on an objective function like integral time squared error (ITSE). Analysis of the power output curves and frequency response curves from simulation for several case studies demonstrates the superiority of the proposed approach for load frequency control.