Balancing Energy in the Smart Grid Using Distributed Value Function (DVF)

doi:10.1109/TSG.2014.2363844

2015-03-01

Fazel Naghdy

Ciufo, Philip

Montserrat Ros

DOI：10.1109/TSG.2014.2363844

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摘要

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As the penetration of renewable energy resources increases in distribution networks, so does the need to manage these resources in an effective manner. Since these resources are installed to displace carbon-based generation and to provide an income stream to the resource owner, it is important that both installation objectives (as a minimum) can be met. With all of these renewable energy resources available, the opportunity also exists to assist with the energy management of this resource-rich distribution network. However, the renewable energy resources do not produce power in a deterministic manner. The available production depends on the time of day and many other environmental factors. Accordingly, a system that is able to program and coordinate the production and storage of power in a distribution network would be of benefit to the network operator. This paper presents a multiagent system (MAS) that is responsible for the management of renewable energy resources and power storage systems connected to the distribution network of a zone substation. The MAS manages the orderly connection and disconnection of resources using a plug and play algorithm in order to minimize disturbances to the supply-and-demand balance within the distribution network. The proposed MAS design is validated using a network based on the IEEE 34-bus test feeder. The results obtained through computer simulation show that with the MAS, it is possible to manage the power resources so that there is minimal power drawn from the upstream network during periods of high demand.

Keyword:

Energy management

plug and play (PnP)

reinforcement learning (RL)

smart grid

team formation