Laijun Chen

Laijun Chen


Research Focus & Metrics

Academic Career Length

20Years (2007-Present)

(Calculated once Scilit publication data is synced: current year − year of first publication + 1)

Representative Publications

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15 October 2016 in Journal of Modern Power Systems and Clean Energy
Verified
Journal Article
Open access
PDF file
LCLaijun Chen
Laijun Chen
TZTianwen Zheng
Tianwen Zheng
Shengwei MeiShengwei Mei
Shengwei Mei
XXXiaodai Xue
Xiaodai Xue
BLBinhui Liu
Binhui Liu
QLQiang Lu
Qiang Lu
As an effective approach of implementing power load shifting, fostering the accommodation of renewable energy, such as the wind and solar generation, energy storage technique is playing an important role in the smart grid and energy internet. Compressed air energy storage (CAES) is a promising energy storage technology due to its cleanness, high efficiency, low cost, and long service life. This paper surveys state-of-the-art technologies of CAES, and makes endeavors to demonstrate the fundamental principles, classifications and operation modes of CAES. Critical subsystems of CAES are elaborated exhaustively. The application prospects and further research directions are summarized to promote the popularization of CAES in smart grid and energy internet.

1 June 2020 in Journal of Cleaner Production
Verified
Journal Article
Closed access
YFYujuan Fang
Yujuan Fang
WWWei Wei
Wei Wei
SMShengwei Mei
Shengwei Mei
LCLaijun Chen
Laijun Chen
XZXuemin Zhang
Xuemin Zhang
SHShaowei Huang
Shaowei Huang

1 July 2018 in Energy
Verified
Journal Article
Closed access
TZTong Zhang
Tong Zhang
LCLaijun Chen
Laijun Chen
XZXuelin Zhang
Xuelin Zhang
SMShengwei Mei
Shengwei Mei
XXXiaodai Xue
Xiaodai Xue
YZYuan Zhou
Yuan Zhou

14 February 2015 in Science China Technological Sciences
Verified
Journal Article
Closed access
PDF file
Shengwei MeiShengwei Mei
Shengwei Mei
JWJunJie Wang
JunJie Wang
FTFang Tian
Fang Tian
LCLaijun Chen
Laijun Chen
XXXiaoDai Xue
XiaoDai Xue
XZXiaoXin Zhou
XiaoXin Zhou

11 September 2020 in IEEE Transactions on Sustainable Energy
Verified
Journal Article
Closed access
ZGZhongjie Guo
Zhongjie Guo
WWWei Wei
Wei Wei
LCLaijun Chen
Laijun Chen
Zhaoyang DongZhaoyang Dong
Zhaoyang Dong
Shengwei MeiShengwei Mei
Shengwei Mei
The high penetration of volatile renewable energy challenges power system operation. Energy storage units (ESUs) can shift the demand over time and compensate real-time discrepancy between generation and demand, and thus improve system operation flexibility and reduce renewable energy curtailment. This paper proposes two parametric optimization models to quantify how the power (MW) and energy (MWh) capacity of ESU would impact renewable energy utilization from two aspects: renewable energy curtailment and system flexibility for uncertainty mitigation. The two indicators are characterized as multivariate functions in the capacity parameters of ESUs. A severity ranking algorithm is suggested to pick up critical scenarios of fluctuation patterns from the uncertainty set; consequently, the proposed models come down to multi-parametric mixed-integer linear programs (mp-MILPs) which can be solved by a decomposition algorithm. The proposed method provides analytical expressions of the two indicators as functions in MW and MWh capacity. Such a characterization delivers abundant sensitivity information on the impact of ESU capacity parameters, and provides a powerful tool for visualization and useful reference for storage sizing. Case studies verify the effectiveness of the proposed method and demonstrate how to use the geometric information.

1 July 2020 in Energy
Verified
Journal Article
Closed access
WZWenyi Zhang
Wenyi Zhang
WWWei Wei
Wei Wei
LCLaijun Chen
Laijun Chen
BZBoshen Zheng
Boshen Zheng
SMShengwei Mei
Shengwei Mei