Ein Modell zur Mikrosimulation des Spothandels von Strom auf der Basis eines Multi-Agenten-Systems

The liberalization of electricity markets in Europe has led to a substantial change in the structure of the electricity sector. Over capacity and competition caused a new strategic orientation of electric utilities. With increasing liquidity of short-term markets spot trading of electricity is of growing importance. But, the high volatility of the spot price poses a risk to traders not to be ignored. Electric utilities need to measure their portfolio against market prices on a day to day basis. They need to integrate production and spot trading into one control loop. With the new market structure some questions arise, the answers of which are most important for the daily practitioners: What will the spot price be tomorrow? What influences the price? What are the rules price is being build of? How does the market react to unforeseen events? Within this research work a concept for a simulation model of the spot market for electricity has been developed. Built as an agent-based simulation the model represents electric utilities on an individual basis and describes the interactions of the simulated companies in terms of an interaction model and via predefined trading protocols. While analyzing the power market and the decision processes therein it became obvious that the forecast of the spot price for the following trading day plays a most important role for the trading preparations. In order to find a suitable forecasting model different examinations and comparisons of a multitude of forecasting methods have been undertaken. Thereby it was concluded, that the different forecasting models did not diverge significantly in the sense of this research work. Nevertheless a big potential for improvement of the artificial neural networks used, has been identified and was addressed. Promising results of the simulation model have been derived at on the basis of an prototype model implemented during this work. Although the prototype uses very simple models of power plants and price forecasting methods, trading decision have been modeled in a suitable way. Analysis of the results at both, the individual as well as the market level, confirm the thesis of different researchers and experts concerning the strategies of deciders in the electricity markets