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Authors: Hongyan Liu 1 and Jüri Vain 2

Affiliations: 1 Åbo Akademi University and Turku Centre of Computer Science, Finland ; 2 Institute of Cybernetic and Tallinn University of Technology, Estonia

ISBN: 978-989-8565-59-4

Keyword(s): Agent-Based Modeling, Computational Intelligence, Demand Response, Electricity Markets, Meta-model, Multi-Agent Systems, Real-time Pricing, Smart Grids.

Related Ontology Subjects/Areas/Topics: Agents ; Artificial Intelligence ; Artificial Intelligence and Decision Support Systems ; Distributed and Mobile Software Systems ; Enterprise Information Systems ; Industrial Applications of Artificial Intelligence ; Intelligent Agents ; Internet Technology ; Knowledge Engineering and Ontology Development ; Knowledge-Based Systems ; Multi-Agent Systems ; Software Engineering ; Strategic Decision Support Systems ; Symbolic Systems ; Web Information Systems and Technologies

Abstract: With the ongoing deployment of smart grids, price-responsive demand is playing an increasingly important role in the paradigm shifting of electricity markets. Taking a multi-agent system modeling approach, this paper presents a conceptual platform for discovering dynamic pricing solutions that reflect the varying cost of electricity in the wholesale market as well as the level of demand participation, especially regarding household customers and small and medium sized businesses. At first, an agent-based meta-model representing various concepts, relations, and structure of agents is constructed. Then a domain model can be instantiated based upon the meta-model. Finally, a simulation experiment is developed for use case demonstration and model validation. The simulation is for the supplier to obtain the profit-maximizing demand curve which has such a shape that it follows the spot price curve in inverse ratio. The result suggests that this multi-agent-based construct could contribute to 1) estimating the impacts of various time-varying tariff options on peak-period energy use through simulation, before any experimental pilots can be carried out; 2) modeling the electricity retail market evolving interactions in a systematic manner; 3) inducing innovative simulation configurations. (More)

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Paper citation in several formats:
Liu H. and Vain J. (2013). An Agent-based Modeling for Price-responsive Demand Simulation.In Proceedings of the 15th International Conference on Enterprise Information Systems - Volume 1: ICEIS, ISBN 978-989-8565-59-4, pages 436-443. DOI: 10.5220/0004417504360443

author={Hongyan Liu and Jüri Vain},
title={An Agent-based Modeling for Price-responsive Demand Simulation},
booktitle={Proceedings of the 15th International Conference on Enterprise Information Systems - Volume 1: ICEIS,},


JO - Proceedings of the 15th International Conference on Enterprise Information Systems - Volume 1: ICEIS,
TI - An Agent-based Modeling for Price-responsive Demand Simulation
SN - 978-989-8565-59-4
AU - Liu H.
AU - Vain J.
PY - 2013
SP - 436
EP - 443
DO - 10.5220/0004417504360443

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