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Centralized Airflow Control to Reduce Output Power Variation in a Complex OWC Ocean Energy Network

Author

Listed:
  • Sunil Kumar Mishra
  • Bhargav Appasani
  • Amitkumar Vidyakant Jha
  • Izaskun Garrido
  • Aitor J. Garrido

Abstract

A centralized airflow control scheme for a complex ocean energy network (OEN) is proposed in this paper to reduce the output power variation (OPV). The OEN is an integrated network of multiple oscillating water columns (OWCs) that are located at different geographical sites connected to a common electrical grid. The complexity of the OWC-OEN increases manifolds due to the integration of several OWCs and design of controllers become very challenging task. So, the centralized airflow control scheme is designed in two stages. In control stage-1, a proportional-integral- (PI-) type controller is designed to provide a common reference command to control stage-2. In control stage-2, the antiwindup PID controllers are implemented for the airflow control of all the OWCs simultaneously. In order to tune the large number of control parameters of this complex system, a fitness function based on integral squared error (ISE) is minimized using the widely adopted particle swarm optimization (PSO) technique. Next, the simulation results were obtained with random wave profiles created using the Joint North Sea Wave Project (JONSWAP) irregular wave model. The OPV of the proposed OWC-OEN was reduced significantly as compared to the individual OWC. It was further observed that the OPV of the proposed scheme was lower than that achieved with uncontrolled and MPPT controlled OWC-OEN. The effect of communication delay on the OPV of the proposed OWC-OEN scheme was also investigated with the proposed controller, which was found to be robust for a delay up to 100 ms.

Suggested Citation

  • Sunil Kumar Mishra & Bhargav Appasani & Amitkumar Vidyakant Jha & Izaskun Garrido & Aitor J. Garrido, 2020. "Centralized Airflow Control to Reduce Output Power Variation in a Complex OWC Ocean Energy Network," Complexity, Hindawi, vol. 2020, pages 1-16, August.
    • Handle: RePEc:hin:complx:2625301
    DOI: 10.1155/2020/2625301
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    Cited by:

    1. Deepak Kumar Gupta & Amitkumar V. Jha & Bhargav Appasani & Avireni Srinivasulu & Nicu Bizon & Phatiphat Thounthong, 2021. "Load Frequency Control Using Hybrid Intelligent Optimization Technique for Multi-Source Power Systems," Energies, MDPI, vol. 14(6), pages 1-16, March.
    2. Deepak Kumar Gupta & Ankit Kumar Soni & Amitkumar V. Jha & Sunil Kumar Mishra & Bhargav Appasani & Avireni Srinivasulu & Nicu Bizon & Phatiphat Thounthong, 2021. "Hybrid Gravitational–Firefly Algorithm-Based Load Frequency Control for Hydrothermal Two-Area System," Mathematics, MDPI, vol. 9(7), pages 1-15, March.
    3. Sunil Kumar Mishra & Amitkumar V. Jha & Vijay Kumar Verma & Bhargav Appasani & Almoataz Y. Abdelaziz & Nicu Bizon, 2021. "An Optimized Triggering Algorithm for Event-Triggered Control of Networked Control Systems," Mathematics, MDPI, vol. 9(11), pages 1-22, May.
    4. Sunil Kumar Mishra & Amitkumar V. Jha & Bhargav Appasani & Nicu Bizon & Phatiphat Thounthong & Pongsiri Mungporn, 2023. "Ocean Wave Energy Control Using Aquila Optimization Technique," Energies, MDPI, vol. 16(11), pages 1-21, June.

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