Agent-based coordination techniques for matching supply and demand in energy networks
Integrated Computer-Aided Engineering - Multi-Agent Systems for Energy Management
A Reinforcement Learning Approach to Setting Multi-Objective Goals for Energy Demand Management
International Journal of Agent Technologies and Systems
Integrated Computer-Aided Engineering
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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.