The 2015 Power Trading Agent Competition

2015 ◽  
Author(s):  
Wolfgang Ketter ◽  
John Collins ◽  
Prashant P. Reddy ◽  
Mathijs de Weerdt
Keyword(s):  
Power Trading ◽  
Trading Agent

The 2016 Power Trading Agent Competition

2016 ◽  
Author(s):  
Wolfgang Ketter ◽  
John Collins ◽  
Mathijs de Weerdt
Keyword(s):  
Power Trading ◽  
Trading Agent

The 2020 Power Trading Agent Competition

2020 ◽  
Author(s):  
Wolfgang Ketter ◽  
John Collins ◽  
Mathijs de Weerdt
Keyword(s):  
Power Trading ◽  
Trading Agent

The 2014 Power Trading Agent Competition

2014 ◽  
Author(s):  
Wolfgang Ketter ◽  
John Collins ◽  
Prashant P. Reddy ◽  
Mathijs de Weerdt
Keyword(s):  
Power Trading ◽  
Trading Agent

The 2017 Power Trading Agent Competition

2017 ◽  
Author(s):  
Wolfgang Ketter ◽  
John Collins
Keyword(s):  
Power Trading ◽  
Trading Agent

scholarly journals CrocodileAgent 2018: Robust agent-based mechanisms for power trading in competitive environments

2019 ◽  
Vol 16 (1) ◽  
pp. 105-129
Author(s):  
Demijan Grgic ◽  
Hrvoje Vdovic ◽  
Jurica Babic ◽  
Vedran Podobnik
Keyword(s):  
Smart Grid ◽  
Energy Systems ◽  
Agent Based ◽  
The Third ◽  
Grid Simulation ◽  
Competitive Environments ◽  
Power Trading ◽  
Net Profit ◽  
Sustainable Energy Systems ◽  
Trading Agent

Besides the smart grid, future sustainable energy systems will have to employ a smart market approach where consumers are able choose one of many different energy providers. The Power Trading Agent Competition (Power TAC) provides an open source, smart grid simulation platform where brokers compete in power brokerage. This paper presents CrocodileAgent, which competed in the Power TAC 2018 finals as a broker agent. The main focus in the design and development of CrocodileAgent 2018 was the creation of smart time-of-use tariffs to reduce peak-demand charges. CrocodileAgent 2018 was ranked third in Power TAC 2018 Finals, with a positive final profit and a positive result in each of three game types. In addition, CrocodileAgent 2018 had the highest percentage of ?profitable games? (91%) from among all competing agents, the second highest level of ?net profit per standard deviation? (0.48) and the third highest ?net profit per subscriber? (79 monetary units).

The 2018 Power Trading Agent Competition

2017 ◽  
Author(s):  
Wolfgang Ketter ◽  
John Collins ◽  
Mathijs de Weerdt
Keyword(s):  
Power Trading ◽  
Trading Agent

A Design of a Network Model to the Electric Power Trading System Using Web Services

2004 ◽  
Vol 124 (1) ◽  
pp. 176-181
Author(s):  
Tomoaki Maruo ◽  
Keinosuke Matsumoto ◽  
Naoki Mori ◽  
Masashi Kitayama ◽  
Yoshio Izumi
Keyword(s):  
Web Services ◽  
Electric Power ◽  
Network Model ◽  
Trading System ◽  
Power Trading

Cross-provincial Cross-region Power Trading Optimization Modeling

2020 ◽  
Vol 13 (8) ◽  
pp. 1183-1189
Author(s):  
Jing-wen Chen ◽  
Yan Xiao ◽  
Hong-she Dang ◽  
Rong Zhang
Keyword(s):  
Network Flow ◽  
Optimal Allocation ◽  
Route Optimization ◽  
Regional Power ◽  
Power Resources ◽  
Gray Theory ◽  
Power Trading ◽  
Study Results ◽  
Multi Agent ◽  
Regional Economic Disparities

Background: China's power resources are unevenly distributed in geography, and the supply-demand imbalance becomes worse due to regional economic disparities. It is essential to optimize the allocation of power resources through cross-provincial and cross-regional power trading. Methods: This paper uses load forecasting, transaction subject data declaration, and route optimization models to achieve optimal allocation of electricity and power resources cross-provincial and cross-regional and maximize social benefits. Gray theory is used to predict the medium and longterm loads, while multi-agent technology is used to report the power trading price. Results: Cross-provincial and cross-regional power trading become a network flow problem, through which we can find the optimized complete trading paths. Conclusion: Numerical case study results has verified the efficiency of the proposed method in optimizing power allocation across provinces and regions.

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