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Carsten Block, John Collins, Wolfgang Ketter, and Christof Weinhardt. A Multi-Agent Energy Trading Competition. Technical Report ERS-2009-054-LIS, RSM Erasmus University, 2009.
The energy sector will undergo fundamental changes over the next ten years. Prices for fossil energy resources are continuously increasing, there is an urgent need to reduce CO2 emissions, and the United States and European Union are strongly motivated to become more independent from foreign energy imports. These factors will lead to installation of large numbers of distributed renewable energy generators, which are often intermittent in nature. This trend conflicts with the current power grid control infrastructure and strategies, where a few centralized control centers manage a limited number of large power plants such that their output meets the energy demands in real time. As the proportion of distributed and intermittent generation capacity increases, this task becomes much harder, especially as the local and regional distribution grids where renewable energy generators are usually installed are currently virtually unmanaged, lack real time metering and are not built to cope with power flow inversions (yet). All this is about to change, and so the control strategies must be adapted accordingly. While the hierarchical command-and-control approach served well in a world with a few large scale generation facilities and many small consumers, a more flexible, decentralized, and self-organizing control infrastructure will have to be developed that can be actively managed to balance both the large grid as a whole, as well as the many lower voltage sub-grids. We propose a competitive simulation test bed to stimulate research and development of electronic agents that help manage these tasks. Participants in the competition will develop intelligent agents that are responsible to level energy supply from generators with energy demand from consumers. The competition is designed to closely model reality by bootstrapping the simulation environment with real historic load, generation, and weather data. The simulation environment will provide a low-risk platform that combines simulated markets and real-world data to develop solutions that can be applied to help building the self-organizing intelligent energy grid of the future.
@TechReport{Block09ERIM,
author = "Carsten Block and John Collins and Wolfgang Ketter and Christof Weinhardt",
title = "A Multi-Agent Energy Trading Competition",
year = 2009,
abstract = "The energy sector will undergo fundamental changes
over the next ten years. Prices for fossil energy resources are
continuously increasing, there is an urgent need to reduce CO2
emissions, and the United States and European Union are strongly
motivated to become more independent from foreign energy imports.
These factors will lead to installation of large numbers of
distributed renewable energy generators, which are often
intermittent in nature. This trend conflicts with the current
power grid control infrastructure and strategies, where a few
centralized control centers manage a limited number of large power
plants such that their output meets the energy demands in real
time. As the proportion of distributed and intermittent generation
capacity increases, this task becomes much harder, especially as
the local and regional distribution grids where renewable energy
generators are usually installed are currently virtually
unmanaged, lack real time metering and are not built to cope with
power flow inversions (yet). All this is about to change, and so
the control strategies must be adapted accordingly. While the
hierarchical command-and-control approach served well in a world
with a few large scale generation facilities and many small
consumers, a more flexible, decentralized, and self-organizing
control infrastructure will have to be developed that can be
actively managed to balance both the large grid as a whole, as
well as the many lower voltage sub-grids. We propose a competitive
simulation test bed to stimulate research and development of
electronic agents that help manage these tasks. Participants in
the competition will develop intelligent agents that are
responsible to level energy supply from generators with energy
demand from consumers. The competition is designed to closely
model reality by bootstrapping the simulation environment with
real historic load, generation, and weather data. The simulation
environment will provide a low-risk platform that combines
simulated markets and real-world data to develop solutions that
can be applied to help building the self-organizing intelligent
energy grid of the future.",
institution = "RSM Erasmus University",
number = "ERS-2009-054-LIS",
address = "Rotterdam, The Netherlands",
bib2html_pubtype = {Unrefereed},
bib2html_rescat = {Trading Agents: Energy Management},
}
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