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DC/DC Converters Optimized for Energy Storage in Smart Grids

A special issue of Energies (ISSN 1996-1073). This special issue belongs to the section "A1: Smart Grids and Microgrids".

Deadline for manuscript submissions: 10 April 2025 | Viewed by 1353

Special Issue Editors


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Guest Editor
College of Energy and Electrical Engineering, Hohai University, No. 1 Xikang Road, Gulou District, Nanjing 210098, China
Interests: renewable energy grid control; power electronic; energy storage

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Guest Editor
Department of Automation, Hangzhou Dianzi University, Hangzhou 310018, China
Interests: power systems; integrated energy systems; optimal planning; smart grids
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Special Issue Information

Dear Colleagues,

During the last decade, smart grids have improved security defense capabilities, flexibility, and compatibility through intelligent means in order to strengthen the development, transmission, and consumption of clean energy, as well as to counter the increasingly frequent natural disasters and external interference. Energy storage technology is a crucial component of this process.

This Special Issue aims to enhance energy storage utilization in and the fault-crossing capability of smart grids by optimizing DC/DC converters, which are important components of energy storage technology.

The topics of interest for publication include, but are not limited to:

  • the optimization of topologie;
  • the control and fault-crossing capability of DC/DC converters;
  • the modeling, analysis, and design of DC/DC converters for energy storage in smart grids;
  • control optimization.

Dr. Chuyang Wang
Dr. Jia Liu
Guest Editors

Manuscript Submission Information

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Please visit the Instructions for Authors page before submitting a manuscript. The Article Processing Charge (APC) for publication in this open access journal is 2600 CHF (Swiss Francs). Submitted papers should be well formatted and use good English. Authors may use MDPI's English editing service prior to publication or during author revisions.

Keywords

  • smart grids
  • energy storage
  • DC/DC converters
  • control optimization

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Published Papers (1 paper)

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Research

16 pages, 7292 KiB  
Article
Novel Frequency Regulation Scenarios Generation Method Serving for Battery Energy Storage System Participating in PJM Market
by Yichao Zhang, Amjad Anvari-Moghaddam, Saeed Peyghami and Frede Blaabjerg
Energies 2024, 17(14), 3479; https://doi.org/10.3390/en17143479 - 15 Jul 2024
Viewed by 1002
Abstract
As one of the largest frequency regulation markets, the Pennsylvania-New Jersey-Maryland Interconnection (PJM) market allows extensive access of Battery Energy Storage Systems (BESSs). The designed signal regulation D (RegD) is friendly for use with BESSs with a fast ramp rate but limited energy. [...] Read more.
As one of the largest frequency regulation markets, the Pennsylvania-New Jersey-Maryland Interconnection (PJM) market allows extensive access of Battery Energy Storage Systems (BESSs). The designed signal regulation D (RegD) is friendly for use with BESSs with a fast ramp rate but limited energy. Designing operating strategies and optimizing the sizing of BESSs in this market are significantly influenced by the regulation signal. To represent the inherent randomness of the RegD signal and reduce the computational burden, typical frequency regulation scenarios with lower resolution are often generated. However, due to the rapid changes and energy neutrality of the RegD signal, generating accurate and representative scenarios presents challenges for the methods based on shape similarity. This paper proposes a novel probability-based method for generating typical regulation scenarios. The method relies on the joint probability distribution of two features with a 15-min resolution, extracted from the RegD signal with a 2 s resolution. The two features can effectively portray the characteristic of RegD signal and its influence on BESS operation. Multiple regulation scenarios are generated based on the joint probability distributions of these features at first, with the final typical scenarios chosen based on their probability distribution similarity to the actual distribution. Utilizing regulation data from the PJM market in 2020, this paper validates and analyzes the performance of the generated typical scenarios in comparison to existing methods, specifically K-means clustering and the forward scenarios reduction method. Full article
(This article belongs to the Special Issue DC/DC Converters Optimized for Energy Storage in Smart Grids)
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