MASCEM: a multiagent system that simulates competitive electricity markets

Praça, Isabel; Ramos, Carlos; Vale, Zita; Cordeiro, Manuel

doi:10.1109/mis.2003.1249170

Cited by 217 publications

(151 citation statements)

References 8 publications

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“…Since the agents in the system are independent of each other and their decision-making processes to achieve goals are asynchronous, the authors propose an asynchronous MAS architecture, "A-team." The MAS technique has been applied to power markets to support new market activities [53]. The developed MAS simulator, where agents represent market entities such as generators, consumers, traders, and market operators, can probe the effects of market rules and conditions by simulating the participants' strategic behavior.…”

Section: A Multiagent System Technologiesmentioning

confidence: 99%

Strategic Power Infrastructure Defense

et al. 2005

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Section: A Multiagent System Technologiesmentioning

confidence: 99%

Strategic Power Infrastructure Defense

et al. 2005

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“…The use of simulation tools has grown with the need for understanding those mechanisms and how the involved players' interaction affects the outcomes of the markets [12]. Artificial Intelligence (AI) plays an important role in this field, as multi-agent based simulation is particularly well fitted to analyze dynamic and adaptive systems with complex interactions among constituents, such as the EM [13]. This is supported by the several multi-agent modeling tools that can be fruitfully applied to the study of restructured wholesale power markets.…”

Section: Introductionmentioning

confidence: 99%

Decision Support for Energy Contracts Negotiation with Game Theory and Adaptive Learning

et al. 2015

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This paper presents a decision support methodology for electricity market players' bilateral contract negotiations. The proposed model is based on the application of game theory, using artificial intelligence to enhance decision support method's adaptive features. This model is integrated in AiD-EM (Adaptive Decision Support for Electricity Markets Negotiations), a multi-agent system that provides electricity market players with strategic behavior capabilities to improve their outcomes from energy contracts' negotiations. Although a diversity of tools that enable the study and simulation of electricity markets has emerged during the past few years, these are mostly directed to the analysis of market models and power systems' technical constraints, making them suitable tools to support decisions of market operators and regulators. However, the equally important support of market negotiating players' decisions is being highly neglected. The proposed model contributes to overcome the existing gap concerning effective and realistic decision support for electricity market negotiating entities. The proposed method is validated by realistic electricity market simulations using real data from the Iberian market operator-MIBEL. Results show that OPEN ACCESSEnergies 2015, 8 9818 the proposed adaptive decision support features enable electricity market players to improve their outcomes from bilateral contracts' negotiations.

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“…Electricity Markets bas been a challenge for Power Systems & Economics scientific communities [14]. They introduced a new degree of complexity in Power System Networks control.…”

Section: Introductionmentioning

confidence: 99%

Intelligent Training in Control Centres Based on an Ambient Intelligence Paradigm

Faria

Silva

Ramos

et al. 2010

Trends in Applied Intelligent Systems

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Abstract. This article describes a new approach in the Intelligent Training of Operators in Power Systems Control Centres, considering the new reality of Renewable Sources, Distributed Generation, and Electricity Markets, under the emerging paradigms of Cyber-Physical Systems and Ambient Intelligence. We propose Intelligent Tutoring Systems as the approach to deal with the intelligent training of operators in these new circumstances.

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MASCEM: a multiagent system that simulates competitive electricity markets

Cited by 217 publications

References 8 publications

Strategic Power Infrastructure Defense

Strategic Power Infrastructure Defense

Decision Support for Energy Contracts Negotiation with Game Theory and Adaptive Learning

Intelligent Training in Control Centres Based on an Ambient Intelligence Paradigm

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