A fast reliability assessment method using optimal basis for integrated community energy systems

J Jiangang Lu R RuiFeng Zhao W Wenxin Guo (The Dermatology Department of The First Affiliated Hospital of USTC, Division of Life Sciences and Medicine) Q Qian Li Z Zeyu Liu K Kai Hou (Research Center, Pu’er People’s Hospital, School of Medicine, Kunming University of Science and Technology) H Hao Wu Y Yuli Liu (National Engineering Research Center of Lower-Carbon Catalysis Technology, Dalian Institute of Chemical Physics)

Abstract

Integrated Community Energy Systems (ICES) aim to optimize energy efficiency through the integration of diverse energy resources, encompassing electricity, heating systems, and natural gas. However, the rapid integration of renewable energy sources and the rising energy demands pose significant challenges in evaluating the reliability of ICES. This difficulty arises from the need to evaluate numerous system states to determine the minimal load curtailment. To address this issue, we propose a method based on optimal bases to enhance computational efficiency in the reliability assessments of ICES. The optimal load curtailment model is developed to facilitate system state evaluation, accounting for variations in load levels and renewable generation. Subsequently, the optimal basis is employed to accelerate this evaluation process. By matching most system states with their corresponding optimal basis based on the optimality criterion, efficient computation of optimal load curtailment is achieved through matrix multiplications, eliminating the need for time-consuming optimization algorithms. The efficacy of the optimal basis-based method is validated through comprehensive case studies.

Article Details

Journal PLoS ONE
Volume / Issue Vol. 21, Issue 2
Published February 05, 2026
Pages e0342059
ISSN 1932-6203
Publisher Public Library of Science

Journal Info

PLoS ONE

Public Library of Science

ISSN: 1932-6203 Open Access Health Sciences

Authors (8)

J

Jiangang Lu

R

RuiFeng Zhao

W

Wenxin Guo

The Dermatology Department of The First Affiliated Hospital of USTC, Division of Life Sciences and Medicine

Q

Qian Li

Z

Zeyu Liu

K

Kai Hou

Research Center, Pu’er People’s Hospital, School of Medicine, Kunming University of Science and Technology

H

Hao Wu

Y

Yuli Liu

National Engineering Research Center of Lower-Carbon Catalysis Technology, Dalian Institute of Chemical Physics