K u rzfassu n g sb an d - Graz University of Technology
K u rzfassu n g sb an d - Graz University of Technology
K u rzfassu n g sb an d - Graz University of Technology
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76 Energieinnovation 2006<br />
3.4.2 „Agent-based simulation for the Germ<strong>an</strong> electricity markets -<br />
An <strong>an</strong>alysis <strong>of</strong> the Germ<strong>an</strong> spot market prices in the year<br />
2001“<br />
Fr<strong>an</strong>k Sensfuß* (Fraunh<strong>of</strong>er Institut für Systemtechnik und<br />
Innovationsforschung) 1 ,<br />
Massimo Genoese* (Universität Karlsruhe/Institut für<br />
Industriebetriebslehre und Industrielle Produktion)<br />
The Germ<strong>an</strong> electricity sector has undergone considerable ch<strong>an</strong>ges throughout the past few years.<br />
Main developments are the liberalisation <strong>of</strong> electricity markets, the evolving Europe<strong>an</strong> CO 2 emissions<br />
trading scheme <strong>an</strong>d the promotion <strong>of</strong> renewable electricity generation. Policy makers <strong>an</strong>d market<br />
players have to deal with new aspects like market power, bounded rationality <strong>an</strong>d the appear<strong>an</strong>ce <strong>of</strong><br />
fluctuating energy sources. In the given environment the complex interactions between different<br />
markets <strong>an</strong>d environmental policy instruments like CO 2 emission trading become <strong>an</strong> issue <strong>of</strong><br />
increasing import<strong>an</strong>ce. A promising <strong>an</strong>d novel approach for the scientific <strong>an</strong>alysis <strong>of</strong> these new<br />
developments is the field <strong>of</strong> agent-based simulation. This paper presents a first version <strong>of</strong> the agentbased<br />
simulation platform PowerACE for the simulation <strong>of</strong> the Germ<strong>an</strong> electricity sector. In a case<br />
study the PowerACE model is used to simulate the development <strong>of</strong> market prices on the Germ<strong>an</strong> spot<br />
market in the year 2001. In order to <strong>an</strong>alyse the capabilities <strong>of</strong> the model the results are compared to<br />
the <strong>of</strong>ficial spot market results <strong>of</strong> the LPX (EEX) in the year 2001. In a second step <strong>an</strong> algorithm for the<br />
integration <strong>of</strong> start-up cost is presented <strong>an</strong>d applied to the simulation.<br />
The PowerACE simulation platform simulates import<strong>an</strong>t players within the electricity sector as<br />
computational agents. Among these are agents representing consumers, utilities, renewable agents,<br />
grid operators, government agents <strong>an</strong>d market operators. Some players like utilities are simulated<br />
using several computational agents representing different functions within the comp<strong>an</strong>y like trading or<br />
generation. An overview <strong>of</strong> the main agents involved in the simulation is given in<br />
Figure 2.<br />
Load DB<br />
loadpr<strong>of</strong>iles<br />
support<br />
Gridoperator-Trader<br />
<strong>of</strong>fer<br />
bid<br />
load<br />
support<br />
Load-Prognosis<br />
REG-Load DB<br />
REG-Capacity DB<br />
new pl<strong>an</strong>t<br />
Investment Pl<strong>an</strong>ner<br />
Household<br />
Tr<strong>an</strong>sport<br />
Services<br />
Industry+<br />
Others<br />
Contracts<br />
Dem<strong>an</strong>d+equipment(HH)<br />
Dem<strong>an</strong>d DB<br />
CO 2 Bal<strong>an</strong>ce<br />
load<br />
Supplier<br />
Saving Potential<br />
Industry DB<br />
CO 2 -Trader<br />
bids<br />
<strong>of</strong>fer<br />
bid<br />
50<br />
40<br />
30<br />
20<br />
10<br />
0<br />
50<br />
40<br />
30<br />
20<br />
10<br />
0<br />
Spotmarket<br />
hour<br />
Bal<strong>an</strong>cing Market<br />
50<br />
40<br />
30<br />
20<br />
10<br />
0<br />
bids<br />
Gridoperator<br />
hour<br />
CO 2<br />
-Market<br />
hour<br />
<strong>of</strong>fer<br />
bid<br />
<strong>of</strong>fer<br />
<strong>of</strong>fer<br />
Renewable Agents<br />
Supply-Trader<br />
Merit Order<br />
Bal<strong>an</strong>cing-Trader<br />
CO 2 -Trader<br />
Figure 2 Structure <strong>of</strong> PowerACE<br />
Merit Order<br />
Investment Pl<strong>an</strong>ner<br />
new pl<strong>an</strong>t<br />
Pl<strong>an</strong>t DB<br />
pl<strong>an</strong>t data<br />
Generator<br />
Legend<br />
Markets<br />
Renewables<br />
Dem<strong>an</strong>d<br />
Utilities<br />
Agents Objects<br />
data Flows<br />
Database<br />
In general the simulation platform c<strong>an</strong> be categorized in four modules dealing with markets, electricity<br />
dem<strong>an</strong>d, utilities <strong>an</strong>d renewable electricity generation. This paper seeks to <strong>an</strong>alyse the capability <strong>of</strong><br />
the model to simulate spot market prices in order to provide <strong>an</strong> adequate basis for future <strong>an</strong>alysis.<br />
Therefore a central part <strong>of</strong> the simulation is to provide realistic data on the electricity dem<strong>an</strong>d,<br />
1 Fraunh<strong>of</strong>er Institute for Systems <strong>an</strong>d Innovation Research, Breslauer Str. 48, 76139 Karlsruhe,<br />
Tel.: +49(0)721/6809-133; e-mail: fr<strong>an</strong>k.sensfuss@isi.fraunh<strong>of</strong>er.de http://www.isi.fhg.de/e/index.htm;
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