Imperial College London

DrFeiTeng

Faculty of EngineeringDepartment of Electrical and Electronic Engineering

Senior Lecturer
 
 
 
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Contact

 

+44 (0)20 7594 6178f.teng Website CV

 
 
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Location

 

1116Electrical EngineeringSouth Kensington Campus

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Summary

 

Publications

Citation

BibTex format

@article{Chai:2020:10.1002/2050-7038.12323,
author = {Chai, Y and Xiang, Y and Liu, J and Teng, F and Yao, H and Wang, Y},
doi = {10.1002/2050-7038.12323},
journal = {International Transactions on Electrical Energy Systems},
title = {Investment decision optimization for distribution network planning with correlation constraint},
url = {http://dx.doi.org/10.1002/2050-7038.12323},
volume = {30},
year = {2020}
}

RIS format (EndNote, RefMan)

TY  - JOUR
AB - With the increasing access of distributed generation (DG), the investment decision of distribution network (DN) has become a largescale portfolio optimization problem with various reconstruction strategies, which reduces the applicability of the traditional investment decision optimization model. Therefore, aiming at reliability of DN, a novel deep belief networks (DBN)based correlation constraintintegrated investment decision model is proposed in this paper. With the DBNbased correlation constraint replacing the nonlinear and nonconvex constraints in the traditional model, a new investment decision model is established aiming at maximizing the reliability index and minimizing the total investment cost. In this way, the effects of different reconstruction strategies can be analysed, from which the optimal investment reconstruction plans are identified. Finally, an example of a regional distribution network in a city is provided to verify the rapidity, feasibility, and effectiveness of the investment decision model.
AU - Chai,Y
AU - Xiang,Y
AU - Liu,J
AU - Teng,F
AU - Yao,H
AU - Wang,Y
DO - 10.1002/2050-7038.12323
PY - 2020///
SN - 2050-7038
TI - Investment decision optimization for distribution network planning with correlation constraint
T2 - International Transactions on Electrical Energy Systems
UR - http://dx.doi.org/10.1002/2050-7038.12323
UR - https://onlinelibrary.wiley.com/doi/full/10.1002/2050-7038.12323
UR - http://hdl.handle.net/10044/1/77178
VL - 30
ER -