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Agent-based simulation of electricity markets - a literature review

 
: Sensfuß, F.; Ragwitz, M.; Genoese, M.; Möst, D.
: Fraunhofer-Institut für System- und Innovationsforschung -ISI-, Karlsruhe

:
Volltext urn:nbn:de:0011-n-661574 (484 KByte PDF)
MD5 Fingerprint: 3963dae7376b60d70e01f31a24f64a27
Erstellt am: 10.1.2008


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Karlsruhe: Fraunhofer ISI, 2007, 38 S.
Working Paper Sustainability and Innovation, S5/2007
 
Englisch
Bericht, Elektronische Publikation
Fraunhofer ISI ()

Abstract
Liberalisation, climate policy and promotion of renewable energy are challenges to players of the electricity sector in many countries. Policy makers have to consider issues like the market power, bounded rationality of players and the appearance of fluctuating energy sources in order to provide adequate legislation. Furhermore the interactions between markets and environmental policy instruments become an issue of increasing importance. A promising approach for the scientific analysis of these developments is the field of agent-based simulation. The goal of this article is to provide an overview of the current work applying the methodology to the analysis of electricity markets.

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Contents S.5-6
1 Introduction S.1-5
2 Models to analyse market power and market design S.6-15
- 2.1 Analysis of the market power of utilities: Evolution to multimarket models S.6-9
- 2.2 Using agent-based simulation to measure market efficiency S.9-12
- 2.3 Analysis of market efficiency in congested electricity grids S.12-13
- 2.4 Analysis of market design: Linking simulation models S.13-14
- 2.5 Summary S.14-15
3 Models with focus on agent decisions and learning S.16-21
- 3.1 Analysis of the impact of agent learning on simulation results S.17-18
- 3.2 Application of fundamental models to support agent decisions S.18-19
- 3.3 Increasing realism by improved agent architecture S.19-20
- 3.4 Integration of the consumer perspective: Consumer contract choice S.20-21
- 3.5 Summary S.21
4 Models for the coupling of long-term and short-term simulations S.22-27
- 4.1 Development of an agent-based simulation with multiple time scales S.23-24
- 4.2 Integration of emission calculations into a multi-time-scale simulation S.24-25
- 4.3 Integration of investment decisions, CO2-emission trading and renewable support schemes S.25-26
- 4.4 Integration of macroeconomic aspects S.26-27
- 4.5 Summary S.27
5 Conclusions S.28-29
References S.30