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The Genoa Artificial Power-Exchange
Silvano Cincotti and Giulia Gallo
DOGE.I-CINEF, University of Genoa, Via Opera Pia 15, 16145 Genoa, Italy
{
silvano.cincotti,giulia.gallo
}
@unige.it
www.cinef.it
Abstract.
The paper presents the Genoa Artificial Power Exchange, an agent-
based framework for modeling and simulating power exchanges implemented in
MATLAB. GAPEX allows creation of artificial power exchanges reproducing ex-
act market clearing procedures of the most important European power-exchanges.
In this paper we present results from a simulation performed on the Italian PEX
where we have reproduced the Locational Marginal Price Algorithm based on
the Italian high-voltage transmission network with its zonal subdivisions and we
considered the Gencos in direct correspondence with the real ones. An enhanced
version of the Roth-Erev algorithm is presented so to be able to consider the pres-
ence of affine total cost functions for the Gencos which results in payoff either
positive, negative and null. A close agreement with historical real market data
during both peak- and off-peak load hours of prices reproduced by GAPEX con-
firm its direct applicability to model and to simulate power exchanges.
Keywords:
Agent-based computational economics, Electricity markets, Rein-
forcement learning, Multi-agent systems.
1
Introduction
In the last decade, large efforts have been dedicated in developing theoretical and com-
putational approaches for modeling deregulated electricity markets. Several papers have
appeared in the agent-based computational economics (hereafter ACE) literature on
wholesale electricity markets and ACE has become a reference paradigm for researchers
working on electricity market topics (see as reference examples [17], [3], [4], [1], [7],
and [22]). Generally speaking, these papers adopt a computer-based modeling approach
for studying the electricity markets as result of the interactions between heterogenous
market participants. In particular, the AMES model (Agent-based Modeling of Electric-
ity Systems, [22]) comprised a two-settlement system consisting of a day-ahead market
and a real-time one which are both cleared by means of Locational Marginal Pricing.
[21] presented a model that consists of three sequential oligopolistic energy markets
representing a wholesale gas market, a wholesale electricity market and a retail electric-
ity market. [25] simulated two markets that are cleared sequentially: a day-ahead elec-
tricity market and a market for balancing power. [6] developed a wholesale electricity
market model similar to the Australian National Electricity Market. Detailed reviews
on agent-based models applied to wholesale electricity markets can be found in [26]
and [12]. In this paper, we present the Genoa Artificial Power Exchange (GAPEX), an
agent-based framework for modeling and simulating electricity markets. In particular,
