JOURNAL ARTICLE

Intelligent micro grid management using a multi-agent approach

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:
Computer science Grid Smart grid Fuzzy logic Distributed computing Computational intelligence Multi-agent system Electricity market Grid computing Intelligent agent Electricity Operator (biology) Semantic grid Artificial intelligence Engineering Semantic Web

Metrics

5
Cited By
0.83
FWCI (Field Weighted Citation Impact)
18
Refs
0.78
Citation Normalized Percentile
Is in top 1%
Is in top 10%

Citation History

Topics

Smart Grid Energy Management
Physical Sciences →  Engineering →  Electrical and Electronic Engineering
Electric Power System Optimization
Physical Sciences →  Engineering →  Electrical and Electronic Engineering
Microgrid Control and Optimization
Physical Sciences →  Engineering →  Control and Systems Engineering
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