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Adaptive Multiagent Model Based on Reinforcement Learning for Distributed Generation Systems

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2 Author(s)
Daniel Divényi ; Dept. of Electr. Power Eng., Budapest Univ. of Technol. & Econ., Budapest, Hungary ; Andr's D'n

Distributed generation have been widely spread in the last decades raising a lot of questions regarding the safe and high-quality operation of the power systems. The investigation of these questions requires a proper model considering the different technical, economical and legal aspects. The goal of our research was to develop a multiagent system where rational agents control each distributed generation unit. Based on intelligent agent-program the agents are able to optimize their operations taking several viewpoints into account, like fulfilling the contractual obligations, considering the technical constraints and maximizing the realized profit in a continuously varying market environment. This paper describes a simple reinforcement learning method resulting in an adaptive agent-program. The agents are informed about their realized profits and they apply this information to evaluate their former decisions and to adjust the parameters of their agent-program. The verification of the model proved that the developed agent-program provides acceptable results compared to the real productions.

Published in:

2012 23rd International Workshop on Database and Expert Systems Applications

Date of Conference:

3-7 Sept. 2012