Detailed Nonlinear Modeling and High-Fidelity Parallel Simulation of MMC With Embedded Energy Storage for Wind Farm Grid Integration

Integration of renewable energy is increasingly prevalent, yet its stochasticity may compromise the stability of the power system. In this paper, a high-voltage dc (HVDC) link model based on the modular multilevel converter with embedded energy storage (MMC-EES) is presented and, utilizing the massi...

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Main Authors: Bingrong Shang, Ning Lin, Venkata Dinavahi
Format: Article
Language:English
Published: IEEE 2024-01-01
Series:IEEE Open Access Journal of Power and Energy
Subjects:
Online Access:https://ieeexplore.ieee.org/document/10506689/
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author Bingrong Shang
Ning Lin
Venkata Dinavahi
author_facet Bingrong Shang
Ning Lin
Venkata Dinavahi
author_sort Bingrong Shang
collection DOAJ
description Integration of renewable energy is increasingly prevalent, yet its stochasticity may compromise the stability of the power system. In this paper, a high-voltage dc (HVDC) link model based on the modular multilevel converter with embedded energy storage (MMC-EES) is presented and, utilizing the massively parallel computing feature of the graphics processing unit (GPU), its efficacy in compensating a varying wind energy generation is studied. Constant power is oriented in the inverter control by incorporating a DC-DC converter with EES into its submodules. High-fidelity electromagnetic transient modeling is conducted for insights into converter control and energy management. A fully iterative solution is carried out for the nonlinear model for high accuracy. Since the sequential data processing manner of the central processing unit (CPU) is prone to an extremely long simulation following an increase of component quantity with even one order of magnitude, the massively concurrent threading of the GPU is exploited. The computational challenges posed by the complexity of the MMC circuit are effectively tackled by circuit partitioning which separates nonlinearities. In the meantime, components of an identical attribute are designed as one kernel despite inhomogeneity. The proposed modeling and computing method is applied to a multi-terminal DC system with wind farms, and significant speedups over CPU-based simulation are achieved, with the accuracy validated by the offline simulation tool PSCAD.
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spelling doaj-art-5a8ea56de90048b9ac94538d03d481ba2025-01-21T00:03:03ZengIEEEIEEE Open Access Journal of Power and Energy2687-79102024-01-011119620610.1109/OAJPE.2024.339224610506689Detailed Nonlinear Modeling and High-Fidelity Parallel Simulation of MMC With Embedded Energy Storage for Wind Farm Grid IntegrationBingrong Shang0https://orcid.org/0000-0001-5652-5824Ning Lin1https://orcid.org/0000-0002-7220-2109Venkata Dinavahi2https://orcid.org/0000-0001-7438-9547Department of Electrical and Computer Engineering, University of Alberta, Edmonton, AB, CanadaPowertech Labs Inc., Surrey, BC, CanadaDepartment of Electrical and Computer Engineering, University of Alberta, Edmonton, AB, CanadaIntegration of renewable energy is increasingly prevalent, yet its stochasticity may compromise the stability of the power system. In this paper, a high-voltage dc (HVDC) link model based on the modular multilevel converter with embedded energy storage (MMC-EES) is presented and, utilizing the massively parallel computing feature of the graphics processing unit (GPU), its efficacy in compensating a varying wind energy generation is studied. Constant power is oriented in the inverter control by incorporating a DC-DC converter with EES into its submodules. High-fidelity electromagnetic transient modeling is conducted for insights into converter control and energy management. A fully iterative solution is carried out for the nonlinear model for high accuracy. Since the sequential data processing manner of the central processing unit (CPU) is prone to an extremely long simulation following an increase of component quantity with even one order of magnitude, the massively concurrent threading of the GPU is exploited. The computational challenges posed by the complexity of the MMC circuit are effectively tackled by circuit partitioning which separates nonlinearities. In the meantime, components of an identical attribute are designed as one kernel despite inhomogeneity. The proposed modeling and computing method is applied to a multi-terminal DC system with wind farms, and significant speedups over CPU-based simulation are achieved, with the accuracy validated by the offline simulation tool PSCAD.https://ieeexplore.ieee.org/document/10506689/Energy storage systemgraphics processorshigh voltage direct currentmodular multilevel converternonlinear systemsparallel processing
spellingShingle Bingrong Shang
Ning Lin
Venkata Dinavahi
Detailed Nonlinear Modeling and High-Fidelity Parallel Simulation of MMC With Embedded Energy Storage for Wind Farm Grid Integration
IEEE Open Access Journal of Power and Energy
Energy storage system
graphics processors
high voltage direct current
modular multilevel converter
nonlinear systems
parallel processing
title Detailed Nonlinear Modeling and High-Fidelity Parallel Simulation of MMC With Embedded Energy Storage for Wind Farm Grid Integration
title_full Detailed Nonlinear Modeling and High-Fidelity Parallel Simulation of MMC With Embedded Energy Storage for Wind Farm Grid Integration
title_fullStr Detailed Nonlinear Modeling and High-Fidelity Parallel Simulation of MMC With Embedded Energy Storage for Wind Farm Grid Integration
title_full_unstemmed Detailed Nonlinear Modeling and High-Fidelity Parallel Simulation of MMC With Embedded Energy Storage for Wind Farm Grid Integration
title_short Detailed Nonlinear Modeling and High-Fidelity Parallel Simulation of MMC With Embedded Energy Storage for Wind Farm Grid Integration
title_sort detailed nonlinear modeling and high fidelity parallel simulation of mmc with embedded energy storage for wind farm grid integration
topic Energy storage system
graphics processors
high voltage direct current
modular multilevel converter
nonlinear systems
parallel processing
url https://ieeexplore.ieee.org/document/10506689/
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AT ninglin detailednonlinearmodelingandhighfidelityparallelsimulationofmmcwithembeddedenergystorageforwindfarmgridintegration
AT venkatadinavahi detailednonlinearmodelingandhighfidelityparallelsimulationofmmcwithembeddedenergystorageforwindfarmgridintegration