Optimal Voltage–Frequency Regulation in Distributed Sustainable Energy-Based Hybrid Microgrids with Integrated Resource Planning

This work is the earliest attempt to propose an integrated resource planning for distributed hybrid microgrids considering virtual-inertia support (VIS) and demand-response support (DRS) systems. Initially, three-distributed sustainable energy-based unequal hybrid microgrids are envisioned with the...

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Main Authors: Amar Kumar Barik, Dulal Chandra Das, Abdul Latif, S. M. Suhail Hussain, Taha Selim Ustun
Format: Article
Language:English
Published: MDPI AG 2021-05-01
Series:Energies
Subjects:
Online Access:https://www.mdpi.com/1996-1073/14/10/2735
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spelling doaj-eecd011736214b67839ed2d049f1601c2021-05-31T23:39:51ZengMDPI AGEnergies1996-10732021-05-01142735273510.3390/en14102735Optimal Voltage–Frequency Regulation in Distributed Sustainable Energy-Based Hybrid Microgrids with Integrated Resource PlanningAmar Kumar Barik0Dulal Chandra Das1Abdul Latif2S. M. Suhail Hussain3Taha Selim Ustun4Department of Electrical Engineering, National Institute of Technology Silchar, Assam 788010, IndiaDepartment of Electrical Engineering, National Institute of Technology Silchar, Assam 788010, IndiaDepartment of Electrical Engineering, National Institute of Technology Silchar, Assam 788010, IndiaFukushima Renewable Energy Institute, AIST (FREA), National Institute of Advanced Industrial Science and Technology (AIST), Koriyama 963-0298, JapanFukushima Renewable Energy Institute, AIST (FREA), National Institute of Advanced Industrial Science and Technology (AIST), Koriyama 963-0298, JapanThis work is the earliest attempt to propose an integrated resource planning for distributed hybrid microgrids considering virtual-inertia support (VIS) and demand-response support (DRS) systems. Initially, three-distributed sustainable energy-based unequal hybrid microgrids are envisioned with the availability of solar/wind/bioenergy resources. In order to overcome the effects of intermittency in renewable resources and low inertia, each microgrid is incorporated with DRS and VIS units for demand- and supply-side management, respectively. The proposed system is simulated in MATLAB considering real-time recorded solar/wind data with realistic loading for 12 months. A novel quasi-oppositional chaotic selfish-herd optimization (QCSHO) algorithm is proposed by hybridizing quasi-opposition-based learning and chaotic linear search techniques into the selfish-herd optimization, for optimal regulation of voltage and frequency in microgrids. Then, the system responses are compared with 7 algorithms and 5 error functions to tune PID controllers’ gains, which confirmed the superiority of QCSHO over others. Then, the study proceeds to investigate the voltage, frequency, and tie-line power coordination in 5 extreme scenarios of source and load variations in the proposed system without retuning the controllers. Finally, the system responses are analyzed for 10 different possible allocation of VIS and DRS units in different microgrids to find the most suitable combinations, and the results are recorded.https://www.mdpi.com/1996-1073/14/10/2735bio-energy generatorsdemand responsehybrid microgridsintegrated resource planningoptimization techniquessustainable energy
collection DOAJ
language English
format Article
sources DOAJ
author Amar Kumar Barik
Dulal Chandra Das
Abdul Latif
S. M. Suhail Hussain
Taha Selim Ustun
spellingShingle Amar Kumar Barik
Dulal Chandra Das
Abdul Latif
S. M. Suhail Hussain
Taha Selim Ustun
Optimal Voltage–Frequency Regulation in Distributed Sustainable Energy-Based Hybrid Microgrids with Integrated Resource Planning
Energies
bio-energy generators
demand response
hybrid microgrids
integrated resource planning
optimization techniques
sustainable energy
author_facet Amar Kumar Barik
Dulal Chandra Das
Abdul Latif
S. M. Suhail Hussain
Taha Selim Ustun
author_sort Amar Kumar Barik
title Optimal Voltage–Frequency Regulation in Distributed Sustainable Energy-Based Hybrid Microgrids with Integrated Resource Planning
title_short Optimal Voltage–Frequency Regulation in Distributed Sustainable Energy-Based Hybrid Microgrids with Integrated Resource Planning
title_full Optimal Voltage–Frequency Regulation in Distributed Sustainable Energy-Based Hybrid Microgrids with Integrated Resource Planning
title_fullStr Optimal Voltage–Frequency Regulation in Distributed Sustainable Energy-Based Hybrid Microgrids with Integrated Resource Planning
title_full_unstemmed Optimal Voltage–Frequency Regulation in Distributed Sustainable Energy-Based Hybrid Microgrids with Integrated Resource Planning
title_sort optimal voltage–frequency regulation in distributed sustainable energy-based hybrid microgrids with integrated resource planning
publisher MDPI AG
series Energies
issn 1996-1073
publishDate 2021-05-01
description This work is the earliest attempt to propose an integrated resource planning for distributed hybrid microgrids considering virtual-inertia support (VIS) and demand-response support (DRS) systems. Initially, three-distributed sustainable energy-based unequal hybrid microgrids are envisioned with the availability of solar/wind/bioenergy resources. In order to overcome the effects of intermittency in renewable resources and low inertia, each microgrid is incorporated with DRS and VIS units for demand- and supply-side management, respectively. The proposed system is simulated in MATLAB considering real-time recorded solar/wind data with realistic loading for 12 months. A novel quasi-oppositional chaotic selfish-herd optimization (QCSHO) algorithm is proposed by hybridizing quasi-opposition-based learning and chaotic linear search techniques into the selfish-herd optimization, for optimal regulation of voltage and frequency in microgrids. Then, the system responses are compared with 7 algorithms and 5 error functions to tune PID controllers’ gains, which confirmed the superiority of QCSHO over others. Then, the study proceeds to investigate the voltage, frequency, and tie-line power coordination in 5 extreme scenarios of source and load variations in the proposed system without retuning the controllers. Finally, the system responses are analyzed for 10 different possible allocation of VIS and DRS units in different microgrids to find the most suitable combinations, and the results are recorded.
topic bio-energy generators
demand response
hybrid microgrids
integrated resource planning
optimization techniques
sustainable energy
url https://www.mdpi.com/1996-1073/14/10/2735
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