Scenarios Generation for Multi-Agent simulation of Electricity Markets based on Intelligent Data Analysis

被引:0
作者
Santos, Gabriel [1 ]
Praca, Isabel [1 ]
Pinto, Tiago [1 ]
Ramos, Sergio [1 ]
Vale, Zita [1 ]
机构
[1] Polytech Porto ISEP IPP, Inst Engn, GECAD Knowledge Engn & Decis Support Res Ctr, Oporto, Portugal
来源
2013 IEEE SYMPOSIUM ON INTELLIGENT AGENT (IA) | 2013年
关键词
Electricity Markets; Knowledge Discovery in Databases; Machine Learning; Multi-Agent Simulators; Real Electricity Markets; Scenarios Generation;
D O I
暂无
中图分类号
TP18 [人工智能理论];
学科分类号
081104 ; 0812 ; 0835 ; 1405 ;
摘要
This document presents a tool able to automatically gather data provided by real energy markets and to generate scenarios, capture and improve market players' profiles and strategies by using knowledge discovery processes in databases supported by artificial intelligence techniques, data mining algorithms and machine learning methods. It provides the means for generating scenarios with different dimensions and characteristics, ensuring the representation of real and adapted markets, and their participating entities. The scenarios generator module enhances the MASCEM (Multi-Agent Simulator of Competitive Electricity Markets) simulator, endowing a more effective tool for decision support. The achievements from the implementation of the proposed module enables researchers and electricity markets' participating entities to analyze data, create real scenarios and make experiments with them. On the other hand, applying knowledge discovery techniques to real data also allows the improvement of MASCEM agents' profiles and strategies resulting in a better representation of real market players' behavior. This work aims to improve the comprehension of electricity markets and the interactions among the involved entities through adequate multi-agent simulation.
引用
收藏
页码:5 / 12
页数:8
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