The need to achieve sustainability is driving a major transformation of the energy sector. The traditional top-down approach to electricity supply and grid management is being strongly disrupted by a range of forces including distributed renewables, retail market liberalization, and the need for energy consumers to adapt their behavior to the availability of renewable energy sources. We introduce Power TAC, a competitive simulation that challenges researchers to build autonomous trading agents that tackle the complex decision processes a retailer will need to face in future competitive retail electricity markets.
%0 Journal Article
%1 CollinsKetter14ki
%A Collins, John
%A Ketter, Wolfgang
%D 2014
%J KI -- Künstliche Intelligenz
%K v1205 springer paper ai business network optimize economy agent simulation energy
%N 3
%P 191-198
%R 10.1007/s13218-014-0311-6
%T Smart Grid Challenges for Electricity Retailers
%V 28
%X The need to achieve sustainability is driving a major transformation of the energy sector. The traditional top-down approach to electricity supply and grid management is being strongly disrupted by a range of forces including distributed renewables, retail market liberalization, and the need for energy consumers to adapt their behavior to the availability of renewable energy sources. We introduce Power TAC, a competitive simulation that challenges researchers to build autonomous trading agents that tackle the complex decision processes a retailer will need to face in future competitive retail electricity markets.
@article{CollinsKetter14ki,
abstract = {The need to achieve sustainability is driving a major transformation of the energy sector. The traditional top-down approach to electricity supply and grid management is being strongly disrupted by a range of forces including distributed renewables, retail market liberalization, and the need for energy consumers to adapt their behavior to the availability of renewable energy sources. We introduce Power TAC, a competitive simulation that challenges researchers to build autonomous trading agents that tackle the complex decision processes a retailer will need to face in future competitive retail electricity markets.},
added-at = {2014-09-14T14:04:12.000+0200},
author = {Collins, John and Ketter, Wolfgang},
biburl = {https://www.bibsonomy.org/bibtex/29c0d6afc960397e66a77051545ccbab6/flint63},
doi = {10.1007/s13218-014-0311-6},
file = {SpringerLink:2014/CollinsKetter14ki.pdf:PDF},
groups = {public},
interhash = {774c5237befe1361d5aef99c4d91e931},
intrahash = {9c0d6afc960397e66a77051545ccbab6},
issn = {0933-1875},
journal = {KI -- K\"{u}nstliche Intelligenz},
keywords = {v1205 springer paper ai business network optimize economy agent simulation energy},
month = {#aug#},
number = 3,
pages = {191-198},
timestamp = {2018-04-16T12:07:18.000+0200},
title = {Smart Grid Challenges for Electricity Retailers},
username = {flint63},
volume = 28,
year = 2014
}