Imperial College London

DrAdamHawkes

Faculty of EngineeringDepartment of Chemical Engineering

Reader in Energy Systems
 
 
 
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Contact

 

+44 (0)20 7594 9300a.hawkes

 
 
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Assistant

 

Ms Quasirat Hasnat +44 (0)20 7594 7250

 
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Location

 

C502Roderic Hill BuildingSouth Kensington Campus

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Summary

 

Publications

Citation

BibTex format

@inproceedings{Sachs:2018:10.1109/CCTA.2018.8511332,
author = {Sachs, J and Massari, C and Hawkes, A and Sawodny, O},
doi = {10.1109/CCTA.2018.8511332},
pages = {46--53},
title = {Distributed Optimization for a Cost Efficient Operation of a Network of Island Energy Systems},
url = {http://dx.doi.org/10.1109/CCTA.2018.8511332},
year = {2018}
}

RIS format (EndNote, RefMan)

TY  - CPAPER
AB - © 2018 IEEE. The accumulation of energy systems, comprising of diesel generators, storage devices and renewable sources, to a large interacting network is a promising approach to achieve a low cost energy supply in remote areas. The main potential for cost reduction is through optimized operation of the network. Power management of these networks can be challenging due to sudden variations in load demand and high fluctuations in power supplied by renewables. A distributed optimization approach for efficient operation guaranteeing improved robustness towards faults, reduced complexity, and an uninterrupted energy supply is presented. The approach includes detailed component modeling to assure the satisfaction of all operation constraints during the system operation. An extended Alternating Direction Method of Multipliers approach is used for the distributed optimization separating the mixed integer linear optimization problem into sub-problems. Case studies are carried out by using real-world data to illustrate the performance and economic benefits of the proposed method in comparison to the centralized approach. Results show the effectiveness of the optimization strategy in terms of computational feasibility, accuracy, and increased robustness towards failures of individual systems and its suitability for the integration into a distributed model predictive control.
AU - Sachs,J
AU - Massari,C
AU - Hawkes,A
AU - Sawodny,O
DO - 10.1109/CCTA.2018.8511332
EP - 53
PY - 2018///
SP - 46
TI - Distributed Optimization for a Cost Efficient Operation of a Network of Island Energy Systems
UR - http://dx.doi.org/10.1109/CCTA.2018.8511332
ER -