Adaptive Control of Distributed Energy Management: A Comparative Study

Demand-side management is a technology for managing electricity demand at the point of use. Enabling devices to plan, manage and reduce their electricity consumption can relieve the network during peak demand periods. We look at a reinforcement learning approach to set a quota of electricity consump...

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Bibliographic Details
Main Authors: Zeman, A., Prokopenko, M., Ying Guo, Rongxin Li
Format: Conference Proceeding
Language:English
Subjects:
Adaptive control
Costs
Energy consumption
Energy management
Error analysis
Learning
Noise level
Stability
Stress
Technology management
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Summary:Demand-side management is a technology for managing electricity demand at the point of use. Enabling devices to plan, manage and reduce their electricity consumption can relieve the network during peak demand periods. We look at a reinforcement learning approach to set a quota of electricity consumption for a network of devices. This strategy is compared with homeotaxis - a method which achieves coordination through minimizing the persistent time-loop error.These policies are analyzed with increasing levels of noise to represent loss of communication or interruption of device operability. Whilst the policy trained using reinforcement learning proves to be most successful in reducing cost, the homeotaxis method is more successful in reducing stress on devices and increasing stability.
ISSN:1949-3673
DOI:10.1109/SASO.2008.60