Intelligent agents for negotiations in market games. II. Application [electricity supply]

Krishna, V. Murali; Ramesh, V.

doi:10.1109/pica.1997.599431

Cited by 3 publications

(1 citation statement)

References 12 publications

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“…Krishna and Ramesh designed agents that suggest bidding strategies using human behavior [3,4]. Recently, fuzzy logic is broadly used in decision-making.…”

Section: Litrature Reviewmentioning

confidence: 99%

Reinforcement Learning Based Supplier-Agents for Electricity Markets

Rahimi-Kian

Tabarraei

Sadeghi

Proceedings of the 2005 IEEE International Symposium On, Mediterrean Conference on Control and Automation Intelligent Control,

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Bidding strategies play important roles in maximizing the profits of power suppliers in competitive electricity markets. Therefore, it will be an advantage for a supplier to search for optimal bidding strategies in the market. In this paper the problem of designing Fuzzy Reinforcement Learning (FRL) supplier-agents that compete in forward electricity markets (e.g. Day-Ahead energy market) to maximize their revenues is studied. An IEEE 30-bus power system with 6 generators (supplier-agents) and three demand areas with stochastic loads are used for our simulation studies. This model is applicable to different types of commodity markets with numerous supply and demand agents.Index Terms--Bidding strategy, electricity market, fuzzy reinforcement learning, supplier agents.

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“…Krishna and Ramesh designed agents that suggest bidding strategies using human behavior [3,4]. Recently, fuzzy logic is broadly used in decision-making.…”

Section: Litrature Reviewmentioning

confidence: 99%