DocumentCode :
2020379
Title :
Intelligent micro grid management using a multi-agent approach
Author :
Oliveira, P. ; Pinto, Tiago ; Praca, Isabel ; Vale, Zita ; Morais, H.
Author_Institution :
GECAD - Knowledge Eng. & Decision Support Res. Center, IPP - Polytech. of Porto, Porto, Portugal
fYear :
2013
fDate :
16-20 June 2013
Firstpage :
1
Lastpage :
6
Abstract :
Recent changes in electricity markets (EMs) have been potentiating the globalization of distributed generation. With distributed generation the number of players acting in the EMs and connected to the main grid has grown, increasing the market complexity. Multi-agent simulation arises as an interesting way of analysing players´ behaviour and interactions, namely coalitions of players, as well as their effects on the market. MASCEM was developed to allow studying the market operation of several different players and MASGriP is being developed to allow the simulation of the micro and smart grid concepts in very different scenarios This paper presents a methodology based on artificial intelligence techniques (AI) for the management of a micro grid. The use of fuzzy logic is proposed for the analysis of the agent consumption elasticity, while a case based reasoning, used to predict agents´ reaction to price changes, is an interesting tool for the micro grid operator.
Keywords :
artificial intelligence; distributed power generation; fuzzy logic; multi-agent systems; power engineering computing; power markets; smart power grids; AI techniques; MASCEM; MASGriP; agent consumption elasticity; artificial intelligence techniques; distributed generation; electricity markets; fuzzy logic; intelligent microgrid management; microgrid operator; multiagent approach; smart grid concepts; Artificial intelligence; Biological system modeling; Distributed power generation; Elasticity; Electricity supply industry; Microgrids; Smart grids; Artificial Intelligence; Electricity Markets; Micro Grid; Multi-agent Simulation; Smart Grid;
fLanguage :
English
Publisher :
ieee
Conference_Titel :
PowerTech (POWERTECH), 2013 IEEE Grenoble
Conference_Location :
Grenoble
Type :
conf
DOI :
10.1109/PTC.2013.6652263
Filename :
6652263
Link To Document :
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