Get Real: Applying Agent-Based Modeling To
Electricity Market Policy Making In Illinios
Electric utility systems around the world continue to
evolve from regulated, vertically integrated monopoly structures to open markets
that promote competition among suppliers and provide consumers with a choice
of services. Decentralized decision-making is one of the key features of
the new deregulated markets. Many of the modeling tools for power systems
analysis that were developed over the last two decades are based on the implicit
assumption of a centralized decision-making process. Although these tools
are very detailed and complex and will continue to provide many useful insights
into power systems operation, they are limited in their ability to adequately
analyze the intricate web of interactions among all the market forces prevalent
in the new markets. Driven by these observations, Argonne National Laboratory’s
Center for Energy, Environmental, and Economic Systems Analysis (CEEESA) has
developed a new deregulated market analysis tool, the Electricity Market Complex
Adaptive Systems (EMCAS) model. Unlike those of conventional electric system
models, the EMCAS agent-based modeling and simulation (ABMS) techniques do
not postulate a single decision maker with a single objective for the entire
system. Rather, agents are allowed to establish their own objectives and
apply their own decision rules. Each EMCAS agent maintains a private logit
model which is used to project future market conditions. Each agent then
uses a private genetic algorithm to make decisions based on their statistical
models. With its agent-based approach, EMCAS is specifically designed to analyze
multi-agent markets and allow testing of regulatory structures before they
are applied to real systems. A detailed example of an EMCAS simulation created
for the Illinois Commerce Commission that was applied to real policy making
will be provided. This example will describe the types of agents created,
the sources of data used to populate the agents, methods of verification and
validation applied to the resulting model, the analysis results found, and
the resulting real world policy implications.
This work is sponsored by the U.S. Department of Energy
under
contract number W-31-109-ENG-38 and
the Illinois Commerce Commission.
M. North, C. Macal, D. Cirillo, T. Veselka, G. Conzelmann, and V. Koritarov
Corresponding author address:
Michael North
Argonne National Laboratory
north@anl.gov.
macal@dis.anl.gov