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Electrical Engineering and Systems Science > Systems and Control

arXiv:2312.03603 (eess)
[Submitted on 6 Dec 2023 (v1), last revised 2 May 2024 (this version, v2)]

Title:Voltage Restoration in MVDC Shipboard Microgrids with Economic Nonlinear Model Predictive Control

Authors:Saskia Putri, Ali Hosseinipour, Xiaoyu Ge, Faegheh Moazeni, Javad Khazaei
View a PDF of the paper titled Voltage Restoration in MVDC Shipboard Microgrids with Economic Nonlinear Model Predictive Control, by Saskia Putri and 4 other authors
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Abstract:Future Naval Microgrids (MGs) will include hybrid energy storage systems (ESS), including battery and supercapacitors to respond to emerging constant power loads (CPLs) and fluctuating pulsed power loads (PPLs). Voltage regulation of naval microgrids and power sharing among these resources become critical for success of a mission. This paper presents a novel control strategy using nonlinear model predictive controller embedded with a complex droop control architecture for voltage restoration and power sharing in medium voltage DC (MVDC) Naval MGs. The complex droop control ensures allocating supercapacitors (SCs) for high-frequency loads (i.e., PPLs), while battery energy storage system (BESS) and auxiliary generators share the steady-state load (i.e., CPL). Compared to state-of-the-art control of the naval ship MGs that relies on linear models, the proposed method incorporates the nonlinear behavior of the MGs in the closed-loop control framework via nonlinear model predictive control (NMPC). A reduced order representation of the MVDC dynamic is employed as the prediction model, augmented with a multi-objective, constraints-based, optimal control formulation. The results demonstrate the effectiveness of the proposed control framework for voltage restoration and power sharing of resources in naval MGs.
Subjects: Systems and Control (eess.SY)
Cite as: arXiv:2312.03603 [eess.SY]
  (or arXiv:2312.03603v2 [eess.SY] for this version)
  https://doi.org/10.48550/arXiv.2312.03603
arXiv-issued DOI via DataCite

Submission history

From: Saskia Putri Ms. [view email]
[v1] Wed, 6 Dec 2023 16:47:10 UTC (1,769 KB)
[v2] Thu, 2 May 2024 03:14:33 UTC (1,769 KB)
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