TY - GEN
T1 - Asynchronous ADMM HEMS aggregation scheme in smart grid
AU - Yoshida, Akira
AU - Fujimoto, Yu
AU - Amano, Yoshiharu
AU - Hayashi, Yasuhiro
N1 - Funding Information:
This work is supported by the CREST, the Japan Science and Technology Agency, Gant Number JPMJCR15K5.
Funding Information:
This work is supported by the CREST, the JPMJCR15K5.
Publisher Copyright:
© 2018 University of Minho. All rights reserved.
PY - 2018
Y1 - 2018
N2 - There is a high demand that aggregating Home Energy Management System (HEMS) as demand response service. Aggregation scheme is divided into the centralized and decentralized approach. On the one hand, in a centralized fashion, a controller manages all device. On the other hand, in a decentralized fashion, a local controller manages own devices and exchanges information for achieving the global optimum. Our previous work has proposed decentralized HEMS aggregation with Alternating Direction Method of Multipliers (ADMM) to address scalability and privacy issue. The main idea of this method is that we decompose the large-scale aggregated scheduling problem into individual HEMS scheduling problem by introducing local upper limit which stands for the maximum purchasable electricity from an electrical grid. This article reports that we extend the previous decentralized HEM method to asynchronous fashion in order to improve convergence time efficiency from the practical implementation perspective. We propose the waiting ratio which represents the minimum HEMS number for updating the next local upper limit. We also evaluate the algorithm processing time with changing waiting ratio and the number of households. As a result, it is confirmed that though the result shows 53% of acceleration at the most accompanied by barely 2% increase cost, the asynchronous process does not always accelerate the processing time. It may be reasonable to suppose that the degree of acceleration is decreased, as the degree of asynchrony increases, because iteration number until fulfilling converging criteria is increased.
AB - There is a high demand that aggregating Home Energy Management System (HEMS) as demand response service. Aggregation scheme is divided into the centralized and decentralized approach. On the one hand, in a centralized fashion, a controller manages all device. On the other hand, in a decentralized fashion, a local controller manages own devices and exchanges information for achieving the global optimum. Our previous work has proposed decentralized HEMS aggregation with Alternating Direction Method of Multipliers (ADMM) to address scalability and privacy issue. The main idea of this method is that we decompose the large-scale aggregated scheduling problem into individual HEMS scheduling problem by introducing local upper limit which stands for the maximum purchasable electricity from an electrical grid. This article reports that we extend the previous decentralized HEM method to asynchronous fashion in order to improve convergence time efficiency from the practical implementation perspective. We propose the waiting ratio which represents the minimum HEMS number for updating the next local upper limit. We also evaluate the algorithm processing time with changing waiting ratio and the number of households. As a result, it is confirmed that though the result shows 53% of acceleration at the most accompanied by barely 2% increase cost, the asynchronous process does not always accelerate the processing time. It may be reasonable to suppose that the degree of acceleration is decreased, as the degree of asynchrony increases, because iteration number until fulfilling converging criteria is increased.
KW - ADMM
KW - Aggregator
KW - Asynchrony
KW - Home energy management
KW - Scheduling
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M3 - Conference contribution
AN - SCOPUS:85064182530
T3 - ECOS 2018 - Proceedings of the 31st International Conference on Efficiency, Cost, Optimization, Simulation and Environmental Impact of Energy Systems
BT - ECOS 2018 - Proceedings of the 31st International Conference on Efficiency, Cost, Optimization, Simulation and Environmental Impact of Energy Systems
PB - University of Minho
T2 - 31st International Conference on Efficiency, Cost, Optimization, Simulation and Environmental Impact of Energy Systems, ECOS 2018
Y2 - 17 June 2018 through 21 June 2018
ER -