TY - JOUR
T1 - Flexibility index for a distributed energy system design optimization
AU - Yang, Sheng
AU - Liu, Beilin
AU - Li, Xiaolong
AU - Liu, Zhiqiang
AU - Liu, Yue
AU - Xie, Nan
AU - Ren, Jingzheng
N1 - Funding Information:
The work described in this paper was fully supported by a grant from the China NSF project (No. 22008265) and the Fundamental Research Funds for the Central Universities of Central South University (No. 2022ZZTS0145). The work described in this paper was also supported by a grant from Research Institute for Advanced Manufacturing (RIAM), The Hong Kong Polytechnic University (PolyU) (Project No. 1-CD4J, Project ID: P0041367), a grant from Research Centre for Resources Engineering towards Carbon Neutrality (RCRE), The Hong Kong Polytechnic University (PolyU) (Project No.1-BBEC, Project ID: P0043023), and a grant from Research Grants Council of the Hong Kong Special Administrative Region, China-General Research Fund (Project ID: P0042030, Funding Body Ref. No: 15304222, Project No. B-Q97U).
Publisher Copyright:
© 2023 Elsevier Ltd
PY - 2023/12
Y1 - 2023/12
N2 - Flexibility plays a critical role in the design of distributed energy systems (DESs) as it encompasses various aspects related to demand, storage, and supply. To optimize the capacity configuration of DESs effectively, a novel flexibility index (FI) is proposed in this study. The FI is constructed based on the fuzzy best-worst method with considerations for economy, autonomy, energy efficiency, and environmental friendliness, aligning with the characteristics of the DES. Considering FI, particle swarm optimization is employed to determine the optimal design scheme for the DES. A case study involving a swimming pool in Changsha City is conducted to demonstrate the reliability of the proposed optimization scheme. Furthermore, a multi-objective optimization model based on non-dominated sorting genetic algorithm-II and technique of ordering preferences for ideal solution similarity algorithms is developed with different objective functions. The results show that the system optimized considering flexibility maintains better performance, with system flexibility, renewable energy penetration, and off-grid degree indices of 0.824, 0.780, and 0.757 respectively. In addition, the optimization of system configuration considering flexibility can dynamically respond to diverse energy demands, maintaining lower operation and maintenance costs ($11223.75 per year), and lower CO2 emissions (91800kgCO2 per year). The quantified FI presented in this study provides a user-friendly and reliable optimization index for the design of DESs.
AB - Flexibility plays a critical role in the design of distributed energy systems (DESs) as it encompasses various aspects related to demand, storage, and supply. To optimize the capacity configuration of DESs effectively, a novel flexibility index (FI) is proposed in this study. The FI is constructed based on the fuzzy best-worst method with considerations for economy, autonomy, energy efficiency, and environmental friendliness, aligning with the characteristics of the DES. Considering FI, particle swarm optimization is employed to determine the optimal design scheme for the DES. A case study involving a swimming pool in Changsha City is conducted to demonstrate the reliability of the proposed optimization scheme. Furthermore, a multi-objective optimization model based on non-dominated sorting genetic algorithm-II and technique of ordering preferences for ideal solution similarity algorithms is developed with different objective functions. The results show that the system optimized considering flexibility maintains better performance, with system flexibility, renewable energy penetration, and off-grid degree indices of 0.824, 0.780, and 0.757 respectively. In addition, the optimization of system configuration considering flexibility can dynamically respond to diverse energy demands, maintaining lower operation and maintenance costs ($11223.75 per year), and lower CO2 emissions (91800kgCO2 per year). The quantified FI presented in this study provides a user-friendly and reliable optimization index for the design of DESs.
KW - Distributed energy system
KW - Flexibility
KW - Fuzzy best-worst method
KW - Single-objective optimization
UR - http://www.scopus.com/inward/record.url?scp=85173715176&partnerID=8YFLogxK
U2 - 10.1016/j.renene.2023.119423
DO - 10.1016/j.renene.2023.119423
M3 - Journal article
AN - SCOPUS:85173715176
SN - 0960-1481
VL - 219
JO - Renewable Energy
JF - Renewable Energy
M1 - 119423
ER -