Imperial College London
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Professor Yujian Ye

Faculty of Engineering, Department of Electrical and Electronic Engineering

Honorary Lecturer
 
 
 
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Contact

 

yujian.ye11

 
 
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Location

 

1105Electrical EngineeringSouth Kensington Campus

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Summary

 

Publications

Citation

BibTex format

@article{Li:2020:10.1016/j.epsr.2020.106764,
author = {Li, J and Ye, Y and Strbac, G},
doi = {10.1016/j.epsr.2020.106764},
journal = {Electric Power Systems Research},
title = {Stabilizing peer-to-peer energy trading in prosumer coalition through computational efficient pricing},
url = {http://dx.doi.org/10.1016/j.epsr.2020.106764},
volume = {189},
year = {2020}
}
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RIS format (EndNote, RefMan)

TY  - JOUR
AB  - Load balancing issues in distribution networks have emerged alongside the large-scale deployment of distributed renewable generation sources. In light of this challenge, peer-to-peer (P2P) energy trading constitutes a promising approach for delivering secure and economic supply-demand balance when faced with variable load and intermittent renewable generation through matching energy demand and supply locally. However, state-of-the-art mechanisms for governing P2P energy trading either fail to suitably incentivize prosumers to participate in P2P trading or suffer severely from the curse of dimensionality with their computational complexity increase exponentially with the number of prosumers. In this paper, a P2P energy trading mechanism based on cooperative game theory is proposed to establish a grand energy coalition of prosumers and a computationally efficient pricing algorithm is developed to suitably incentivize prosumers for their sustainable participation in the grand coalition. The performance of the proposed algorithm is demonstrated by comparing it to state-of-the-art mechanisms through numerous case studies in a real-world scenario. The superior computational performance of the proposed algorithm is also validated.
AU  - Li,J
AU  - Ye,Y
AU  - Strbac,G
DO  - 10.1016/j.epsr.2020.106764
PY  - 2020///
TI  - Stabilizing peer-to-peer energy trading in prosumer coalition through computational efficient pricing
T2  - Electric Power Systems Research
UR  - http://dx.doi.org/10.1016/j.epsr.2020.106764
VL  - 189
ER  -
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