Study on two‐stage optimal scheduling of DC distribution networks considering flexible load response

Abstract Due to the aim of developing sustainable energy systems, promoting the large‐scale accommodation of distributed renewable energy sources (DRESs) and flexible loads in DC distribution networks (DCDNs) is significant. The uncertainty of DRESs and the insufficient use of flexible loads pose a...

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Main Authors: Lei Chen, Man Yang, Yuqi Jiang, Shencong Zheng, Yifei Li, Xiaoyan You, Hongkun Chen
Format: Article
Language:English
Published: Wiley 2024-11-01
Series:IET Electric Power Applications
Subjects:
Online Access:https://doi.org/10.1049/elp2.12515
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author Lei Chen
Man Yang
Yuqi Jiang
Shencong Zheng
Yifei Li
Xiaoyan You
Hongkun Chen
author_facet Lei Chen
Man Yang
Yuqi Jiang
Shencong Zheng
Yifei Li
Xiaoyan You
Hongkun Chen
author_sort Lei Chen
collection DOAJ
description Abstract Due to the aim of developing sustainable energy systems, promoting the large‐scale accommodation of distributed renewable energy sources (DRESs) and flexible loads in DC distribution networks (DCDNs) is significant. The uncertainty of DRESs and the insufficient use of flexible loads pose a considerable challenge to the economical and safe operation of DCDNs. To address the challenge, this paper puts forward a two‐stage optimal scheduling model for the DCDNs considering flexible load response. The proposed model realises joint economic optimisation and reactive power optimisation, which is solved by the hybrid NSGAII‐MOPSO algorithm and the CPLEX. The performance of the proposed model in the modified Institute of Electrical and Electronics Engineers 33‐node system with the DCDNs is validated under different scenarios. The hybrid NSGAII‐MOPSO performs better in obtaining the Pareto front than the NSGA‐II and MOPSO individually. Compared to the traditional scheduling model, the proposed model can realise the power coordination of the flexible loads and energy storage systems to reduce the negative impact of uncertainty of DRESs while decreasing operating costs and carbon emissions by 3.94% and 36.4%. In addition, the proposed model can alleviate the network losses and ensure the node voltage for the DCDNs. Hence, the efficiency of the proposed model has been confirmed.
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issn 1751-8660
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language English
publishDate 2024-11-01
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series IET Electric Power Applications
spelling doaj-art-221bb5fc0d6541dba6be7a98d543bbc72025-08-20T02:28:29ZengWileyIET Electric Power Applications1751-86601751-86792024-11-0118111690170110.1049/elp2.12515Study on two‐stage optimal scheduling of DC distribution networks considering flexible load responseLei Chen0Man Yang1Yuqi Jiang2Shencong Zheng3Yifei Li4Xiaoyan You5Hongkun Chen6School of Electrical Engineering and Automation Wuhan University Wuhan ChinaSchool of Electrical Engineering and Automation Wuhan University Wuhan ChinaSchool of Electrical Engineering and Automation Wuhan University Wuhan ChinaSchool of Electrical Engineering and Automation Wuhan University Wuhan ChinaSchool of Electrical Engineering and Automation Wuhan University Wuhan ChinaSchool of Electrical Engineering and Automation Wuhan University Wuhan ChinaSchool of Electrical Engineering and Automation Wuhan University Wuhan ChinaAbstract Due to the aim of developing sustainable energy systems, promoting the large‐scale accommodation of distributed renewable energy sources (DRESs) and flexible loads in DC distribution networks (DCDNs) is significant. The uncertainty of DRESs and the insufficient use of flexible loads pose a considerable challenge to the economical and safe operation of DCDNs. To address the challenge, this paper puts forward a two‐stage optimal scheduling model for the DCDNs considering flexible load response. The proposed model realises joint economic optimisation and reactive power optimisation, which is solved by the hybrid NSGAII‐MOPSO algorithm and the CPLEX. The performance of the proposed model in the modified Institute of Electrical and Electronics Engineers 33‐node system with the DCDNs is validated under different scenarios. The hybrid NSGAII‐MOPSO performs better in obtaining the Pareto front than the NSGA‐II and MOPSO individually. Compared to the traditional scheduling model, the proposed model can realise the power coordination of the flexible loads and energy storage systems to reduce the negative impact of uncertainty of DRESs while decreasing operating costs and carbon emissions by 3.94% and 36.4%. In addition, the proposed model can alleviate the network losses and ensure the node voltage for the DCDNs. Hence, the efficiency of the proposed model has been confirmed.https://doi.org/10.1049/elp2.12515DC power transmissiondistributed power generationPareto optimisation
spellingShingle Lei Chen
Man Yang
Yuqi Jiang
Shencong Zheng
Yifei Li
Xiaoyan You
Hongkun Chen
Study on two‐stage optimal scheduling of DC distribution networks considering flexible load response
IET Electric Power Applications
DC power transmission
distributed power generation
Pareto optimisation
title Study on two‐stage optimal scheduling of DC distribution networks considering flexible load response
title_full Study on two‐stage optimal scheduling of DC distribution networks considering flexible load response
title_fullStr Study on two‐stage optimal scheduling of DC distribution networks considering flexible load response
title_full_unstemmed Study on two‐stage optimal scheduling of DC distribution networks considering flexible load response
title_short Study on two‐stage optimal scheduling of DC distribution networks considering flexible load response
title_sort study on two stage optimal scheduling of dc distribution networks considering flexible load response
topic DC power transmission
distributed power generation
Pareto optimisation
url https://doi.org/10.1049/elp2.12515
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