An Optimization Method to Boost the Resilience of Power Networks with High Penetration of Renewable Energies

Bingchun Mu, Xi Zhang*, Xuefei Mao, Zhen Li

*Corresponding author for this work

Research output: Chapter in Book/Report/Conference proceedingConference contributionpeer-review

3 Citations (Scopus)

Abstract

This paper proposes a new method to enhance the resilience of power systems with high penetrations of renewable energies. Firstly, the resilience enhancement is configured as maintaining as much electric energy to critical loads in a fixed number of post-disaster periods by properly coordinating the available resources. Secondly, an optimal decision-making method is proposed to maximize the power supply of critical loads and to minimize the instability risks considering the randomness of the output power of renewable energies. The power consumption of loads and power generation of generators and spinning reserve ratios of the renewable energy at each period are taken as controllable variables. Constraints include spinning reserve, power flow constraints, power consumption/generation limits. The interior-point method is used to solve the formulated optimization problem. It is found that a balance should be sought between decreasing stability risks and increasing the maintained loads in extreme environments. Numerical simulations verified the effectiveness and superiority of the proposed optimization method in restoring power supply and boosting grid resilience after disasters.

Original languageEnglish
Title of host publicationNeural Computing for Advanced Applications - Second International Conference, NCAA 2021, Proceedings
EditorsHaijun Zhang, Zhi Yang, Zhao Zhang, Zhou Wu, Tianyong Hao
PublisherSpringer Science and Business Media Deutschland GmbH
Pages3-16
Number of pages14
ISBN (Print)9789811651878
DOIs
Publication statusPublished - 2021
Event2nd International Conference on Neural Computing for Advanced Applications, NCAA 2021 - Guangzhou, China
Duration: 27 Aug 202130 Aug 2021

Publication series

NameCommunications in Computer and Information Science
Volume1449
ISSN (Print)1865-0929
ISSN (Electronic)1865-0937

Conference

Conference2nd International Conference on Neural Computing for Advanced Applications, NCAA 2021
Country/TerritoryChina
CityGuangzhou
Period27/08/2130/08/21

Keywords

  • Power grid resilience optimization
  • Renewable energy
  • Spinning reserve

Fingerprint

Dive into the research topics of 'An Optimization Method to Boost the Resilience of Power Networks with High Penetration of Renewable Energies'. Together they form a unique fingerprint.

Cite this