Cardiff University | Prifysgol Caerdydd ORCA
Online Research @ Cardiff 
WelshClear Cookie - decide language by browser settings

Optimal configuration of hybrid AC/DC urban distribution networks for high penetration renewable energy

Zhang, Lu, Chen, Ying, Shen, Chen, Tang, Wei, Liang, Jun ORCID: https://orcid.org/0000-0001-7511-449X and Xu, Biao 2018. Optimal configuration of hybrid AC/DC urban distribution networks for high penetration renewable energy. IET Generation, Transmission and Distribution 12 (20) , pp. 4499-4506. 10.1049/iet-gtd.2018.5722

[thumbnail of Liang J - Optimal Configuration of Hybrid ACDC ....pdf]
Preview
PDF - Accepted Post-Print Version
Download (670kB) | Preview

Abstract

Existing AC medium-voltage distribution networks are facing challenges on handling increasing loads and renewable energy integrations. However, it is very difficult to build new distribution lines in urban areas. This study proposes a configuration method of hybrid AC/DC medium-voltage distribution networks, in which some existing AC lines are converted to DC operation. Existing topologies and dispatching scenarios are considered during configuration because the overall power flow can be rescheduled in the hybrid AC/DC distribution network. Therefore, transfer capacities of the lines are fully utilised, and more renewable energies are accommodated. A bi-level programming model is established embedding chance constraint programming to consider the intermittent output of renewable energy. In the upper level, a multiple objective optimal model is proposed in order to balance investments, power losses, and the maximum load level and renewable energy capacity. In the lower level, daily operations of the newly installed VSCs are optimised by a chance constraint programming. The influences of energy storage systems on the configuration are also analysed. Simulation studies are performed to verify the proposed method.

Item Type: Article
Date Type: Publication
Status: Published
Schools: Engineering
Publisher: Institution of Engineering and Technology (IET)
ISSN: 1751-8687
Date of First Compliant Deposit: 15 February 2019
Date of Acceptance: 13 September 2018
Last Modified: 07 Nov 2023 05:23
URI: https://orca.cardiff.ac.uk/id/eprint/119585

Citation Data

Cited 16 times in Scopus. View in Scopus. Powered By Scopus® Data

Actions (repository staff only)

Edit Item Edit Item

Downloads

Downloads per month over past year

View more statistics