Title :
Agent-Based Approach to Handle Business Complexity in U.S. Wholesale Power Trading
Author :
Sueyoshi, Toshiyuki ; Tadiparthi, Gopalakrishna Reddy
Author_Institution :
Dept. of Manage., New Mexico Inst. of Min. & Technol., Socorro, NM
fDate :
5/1/2007 12:00:00 AM
Abstract :
This study documents the practicality of an agent-based approach by examining how two groups of agents handle business complexity related to power trading. Three important findings are identified in this research. First, the proposed approach can estimate fluctuations of electricity prices as well as other well-known methods such as neural networks and genetic algorithms. Second, multiple learning capabilities incorporated in adaptive agents do not have an advantage over limited learning capabilities in predicting the market price of electricity. Finally, a theoretical extension of multiple learning capabilities may have potential for developing the agent-based approach for power trading
Keywords :
genetic algorithms; neural nets; power engineering computing; power markets; power system economics; software agents; US wholesale power trading; adaptive agents; agent-based approach; business complexity; electricity market price; electricity price fluctuation estimation; genetic algorithms; multiple learning capabilities; neural networks; Assembly systems; Computer science; Electronic mail; Fluctuations; Genetic algorithms; Machine learning; Neural networks; Numerical analysis; Operations research; Power markets; Agent-based approach; machine learning; numerical analysis; power trading;
Journal_Title :
Power Systems, IEEE Transactions on
DOI :
10.1109/TPWRS.2007.894856