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Article

Grid Code-Dependent Frequency Control Optimization in Multi-Terminal DC Networks

1
Institute for High Voltage Technology and Power Systems, Braunschweig University of Technology, 2, 38106 Braunschweig, Germany
2
Departamento de Ingenierıa de Sistemas y Automatica, Universidad de Sevilla, 4, 41004 Seville, Spain
3
Institute of Electrical Systems and Automation Technology (IfEA), Ostfalia University of Applied Sciences, 38302 Wolfenbüttel, Germany
4
Department of Electrical Engineering, IT and Cybernetics, University of South-Eastern Norway, 40, 3679 Notodden, Norway
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Departamento de Ingeniería, Universidad Loyola Andalucía, 4, 41004 Seville, Spain
6
Electrical, Computer and Software Engineering, Ontario Tech University, Oshawa, ON L1H 7K4, Canada
*
Author to whom correspondence should be addressed.
These authors contributed equally to this work.
Energies 2020, 13(24), 6485; https://doi.org/10.3390/en13246485
Received: 6 October 2020 / Revised: 2 December 2020 / Accepted: 3 December 2020 / Published: 8 December 2020
(This article belongs to the Section A5: Smart Grids and Microgrids)
The increasing deployment of wind power is reducing inertia in power systems. High-voltage direct current (HVDC) technology can help to improve the stability of AC areas in which a frequency response is required. Moreover, multi-terminal DC (MTDC) networks can be optimized to distribute active power to several AC areas by droop control setting schemes that adjust converter control parameters. To this end, in this paper, particle swarm optimization (PSO) is used to improve the primary frequency response in AC areas considering several grid limitations and constraints. The frequency control uses an optimization process that minimizes the frequency nadir and the settling time in the primary frequency response. Secondly, another layer is proposed for the redistribution of active power among several AC areas, if required, without reserving wind power capacity. This method takes advantage of the MTDC topology and considers the grid code limitations at the same time. Two scenarios are defined to provide grid code-compliant frequency control. View Full-Text
Keywords: MTDC; frequency control; fast frequency control; low-inertia; wind power; grid code; non-synchronous generation; python-PSCAD-interface; particle swarm optimization MTDC; frequency control; fast frequency control; low-inertia; wind power; grid code; non-synchronous generation; python-PSCAD-interface; particle swarm optimization
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MDPI and ACS Style

Hoffmann, M.; Chamorro, H.R.; Lotz, M.R.; Maestre, J.M.; Rouzbehi, K.; Gonzalez-Longatt, F.; Kurrat, M.; Alvarado-Barrios, L.; Sood, V.K. Grid Code-Dependent Frequency Control Optimization in Multi-Terminal DC Networks. Energies 2020, 13, 6485. https://doi.org/10.3390/en13246485

AMA Style

Hoffmann M, Chamorro HR, Lotz MR, Maestre JM, Rouzbehi K, Gonzalez-Longatt F, Kurrat M, Alvarado-Barrios L, Sood VK. Grid Code-Dependent Frequency Control Optimization in Multi-Terminal DC Networks. Energies. 2020; 13(24):6485. https://doi.org/10.3390/en13246485

Chicago/Turabian Style

Hoffmann, Melanie, Harold R. Chamorro, Marc R. Lotz, José M. Maestre, Kumars Rouzbehi, Francisco Gonzalez-Longatt, Michael Kurrat, Lazaro Alvarado-Barrios, and Vijay K. Sood. 2020. "Grid Code-Dependent Frequency Control Optimization in Multi-Terminal DC Networks" Energies 13, no. 24: 6485. https://doi.org/10.3390/en13246485

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