Andreas Maaz

Modeling of electricity pricing in European market simulations

The increasing share of renewable energies as well as the age structure of the thermal generation stack lead to big changes in the European energy system. This paper describes a method for determining market prices for electricity based on the cost-minimal European power plant dispatch and different mark-ups. Thus, the influences of these mark-ups on simulated prices are estimated. Exemplary results are shown for Germany for a backtesting scenario of the year 2014 and a future scenario for the year 2024. The results are compared to historical price patterns and show a better match with the historic prices, but also still room for improvement.

Agent-based price simulation of the German wholesale power market

Recent and future changes in the European power generation system have a big impact on the dispatch of hydraulic and thermal generation units and on the power market. Therefore, this paper investigates the simulation of realistic spot market prices by taking into account agent bidding behavior. An agent-based market simulation method is presented and benchmarked against historic prices of the year 2012 on the German wholesale power market. Simulating cost based bidding strategies enable the model to simulate realistic price curves as well in medium price as in peak price situations.

Economic potential of water electrolysis within future electricity markets

With increasing shares of Renewable Energy Sources (RES) in Europe and especially in Germany, new technologies are required that may provide flexibility. A potential technology to use excess electricity is alkaline water electrolysis. One goal of the Horizon 2020 project ELYntegration is to analyze the profitability of electrolysers in these new market surroundings. For current and future scenarios with high RES shares, potential contribution margins are analyzed. This includes the classical business model of cross-commodity arbitrage trading as well as the provision of flexibility at control reserve markets. The assessment is based on future spot market and reserve market price calculations. The analysis shows increasing contribution margins in the future. The participation in control reserve markets however does not contribute to revenues significantly because high spreads between the spot market and hydrogen market are harnessed in the most efficient and flexible way with cross-commodity arbitrage trading.

Development of adaptive time patterns for multi-dimensional power system simulations

The changes in the European power system come with the necessity of modeling the power system in high detail. Especially, when applying stochastic simulation approaches this leads to increasing problem sizes. In this work, we introduce a methodology to reduce the size of optimization problems in the temporal dimension to achieve lower computation times. The method is based on a mixed-integer optimization reducing the modeled time intervals that can be applied to a wide variety of optimization problems. The potential of the approach is proven by a linear unit dispatch problem for the European power system in the year 2024. The comparison of an equidistant and predefined time pattern with the preceding optimization of an adaptive time pattern shows improvements in accuracy regarding the deviation in yearly power generation, which range between 20 % and 25 %, without increasing computational requirements regarding time or hardware.

Optimization of frequency containment reserve provision in M5BAT hybrid battery storage

This paper focusses on the frequency containment reserve provided by a battery storage system under the German regulatory framework. Therefore, the German equivalent to the frequency containment reserve is discussed in regards to technical requirements for units in general and the less strict requirements for batteries. The technical and operational requirements of frequency containment reserve are formulated in a mathematical model which is implemented in an existing optimization method. The objective is to optimize the trading transactions on spot and control reserve markets by maximizing the contribution margin. The results of the developed method are evaluated by an investigation program.

Addressing the question of regional generation adequacy in capacity expansion planning

Due to an upcoming shift from a power system dominated by dispatchable thermal power plants to a system shaped by renewable energy sources with intermittent feed-in the issue of generation adequacy gains in importance. Despite the European pursuit of a sustainable generation system, the claim for a certain level of security of supply remains which requires investments in new power plants in the long term. Thereby, the question arises whether generation adequacy should be addressed on a national or pan-European level. Thus, this paper evaluates three different interpretations of generation adequacy by optimizing respective least-cost development paths of the European generation stack. The results show that cross-border approaches lead to a reduced amount of new expansion compared to national concepts (−41 GW) while satisfying a comparable level of security of supply.

Value of additional Norwegian hydropower to the European electricity system

The increase of volatile generation from wind and solar power in Europe leads to a higher demand for flexibility in the electrical energy system. As part of the HydroBalance project this paper assesses the potential of Norwegian hydropower to provide this flexibility to the European energy markets by simulating to different scenarios for the expansion of hydropower in Norway. A comparison of the resulting cost reduction of variable system costs with necessary investment costs shows that there is an economic benefit of Norwegian hydropower to the European system especially when providing cross-border balancing.

Agent-based price simulation of the day-ahead- spot-market and markets for control reserve power

The day-ahead spot market and the markets for control reserve power are among the most important markets for short-term trading of power plant capacities in Germany. Especially the prices for control reserve power have been varying severely in the last years. Considering the applied pay-as-bid auction design and market power of certain market participants, strategic bidding behavior must be assumed. Such strategic behavior cannot be modelled by fundamental simulation models alone. Thus, it is necessary to simulate individual bidding curves and trading decisions of market participants in order to simulate realistic market results and prices. Therefore, the aim of this paper is to model the bidding considerations on the day-ahead and control reserve power markets, to implement them in an agent based simulation model using a reinforcement learning algorithm and to investigate the resulting market prices.