An adaptive agent-based system for deregulated smart grids. Issue 2 (June 2016)

• Record Type: Journal Article
• Authors: Capodieci, Nicola; Pagani, Giuliano; Cabri, Giacomo; Aiello, Marco
• Is Part Of: Service oriented computing and applications. Volume 10:Issue 2(2016:Jun.)
• Page Start: 185
• Page End: 205
• Publication Date: 2016-06
• Subjects: Agents -- Smart grid -- Energy market; Electronic data processing -- Distributed processing -- Periodicals; Web services -- Periodicals; Electronic commerce -- Periodicals; 004
• DOI: 10.1007/s11761-015-0180-3
• Languages: English
• ISSNs: 1863-2386

Abstract

Abstract The power grid is undergoing a major change due mainly to the increased penetration of renewables and novel digital instruments in the hands of the end users that help to monitor and shift their loads. Such transformation is only possible with the coupling of an information and communication technology infrastructure to the existing power distribution grid. Given the scale and the interoperability requirements of such future system, service-oriented architectures (SOAs) are seen as one of the reference models and are considered already in many of the proposed standards for the smart grid (e.g., IEC-62325 and OASIS eMIX). Beyond the technical issues of what the service-oriented architectures of the smart grid will look like, there is a pressing question about what the added value for the end user could be. Clearly, the operators need to guarantee availability and security of supply, but why should the end users care? In this paper, we explore a scenario in which the end users can both consume and produce small quantities of energy and can trade these quantities in an open and deregulated market. For the trading, they delegate software agents that can fully interoperate and interact with one another thus taking advantage of the SOA. In particular, the agents have strategies, inspired from game theory, to take advantage of a service-oriented smart grid market and give profit to their delegators, while implicitly helping balancing the power grid. The proposal is implemented with simulated agents and interaction with existing Web services. To show the advantage of the agent with strategies, we compare our approach with the "base" agent one by means of simulations, highlighting the advantages of the proposal.