Many power plants in Germany and Europe are approaching the end of their technical lifetime. Moreover, the increasing wind and solar power generation reduces the operation times of thermal power plants, making future investments in new generation capacity uncertain under current market conditions. Consequently, the future development of security of power supply is unclear. In this paper, we assess the impact of stochastic fluctuations in power plant availability, renewable generation, and grid load on the future security of supply in Germany. We model variations in power plant availability by application of a combined Mean-reversion Jump-diffusion approach. On the basis of that and using Monte-Carlo methods, we simulate 300 different time series of availability. These profiles are fed into the fundamental power system model REMix, applied to evaluate the appearance of supply shortfalls in hourly resolution. We assess 6 scenarios for the year 2025, differing in renewable generation and demand profiles, as well as grid infrastructure. Geographical focus of the analysis is Germany, but the electricity exchange with its European neighbours is modelled as well. Our results show that the choice of the power plant availability profile can change the loss of load expectation and loss of load hours by up to 50%. However, the influence of load and renewable generation profiles is found to be significantly higher. Assuming that no new conventional power plants are built and existing plants are decommissioned at the end of their empirical lifetime, we identify supply gaps of up to 2.7GW in Germany.

In this paper, we identify and analyze parameters that determine the profitability of wind power operators in the German market premium model. Based on an empirical analysis of different German wind power profiles from 2007 to mid-2012, we are able to show that the profitability significantly depends on the correlation of the wind power portfolio with the overall wind power feed-in and prediction error in Germany. Significant differences between the wind forecast errors clearing cost of the analyzed portfolios can be identified. Our analysis shows that a wind power operator would profit in most cases from a reduced forecast error, which could be achieved through an improved forecast model and an increased share of the intraday cleared error. Furthermore significant locational portfolio advantages and disadvantages can be identified when comparing the different market values. In general, the empirical analysis shows that a premium of 3.5 €/MWh is suitable to cover the cost of an imperfect forecast. Taking further into account that for 2012 a premium of 12 €/MWh was granted; the direct marketing option can be evaluated as highly attractive, which is furthermore indicated by the rapid increase of the directly marketed wind power and photovoltaic generation.

Due to very ambitious energy-political goals, the German energy sector is currently undergoing a transition. The resulting challenges are identified in this two-part contribution, before suggesting and discussing possible solutions. While the first part is devoted to electricity generation in renewable and conventional plants, this second part focusses on the demand side and infrastructure, followed by the discussion of energy systems analysis as a suitable methodological approach to these problems. The infrastructure is the area within the energy sector with the most challenges, which is why network models on all voltage levels will become more important. Already today bottlenecks can be observed and in the future an increased requirement for network expansion or spatially-distributed storage capacity is expected. Although ecologically not advantageous, the curtailment of renewable energy production will be at least partly unavoidable. Finally, on the demand side economic and other socio-economic motivations are required for the realization of significant energy efficiency potentials. Electric vehicles can considerably increase the fraction of flexible load in the household sector. Industrial companies are currently the only customers with dynamic tariffs; a large challenge is represented by transferring these customer models to the household and service sectors and thereby exploiting demand elasticities.

The effectiveness of the energy-only market (EOM) in providing sufficient incentives for investments is intensively discussed in Europe. While supporters claim that an improved EOM can guarantee generation adequacy, energy suppliers in particular favor the introduction of a capacity market to finance power plant investments. However, there is a lack of quantitative assessment of market design options taking into account individual decisions of market players. Existing studies mainly include a system view based on a central planner optimization. This paper on the other hand is based on an agent-based simulation model for the German electricity market. This method can explicitly incorporate individual investment decisions and aggregate them to present a holistic view of the system.Our results show that an EOM extended with a strategic reserve can incentivize investments, and guarantee supply security in a market with high share of renewable energies. However, the generation adequacy can be more easily achieved with a capacity market. Furthermore, the cost advantage of an EOM diminishes in the long-term, as scarcity prices in the EOM lead to similar system costs as with a capacity market. (C) 2016 Elsevier Ltd. All rights reserved.

Angesichts des geplanten Ausstiegs aus der Kernenergie und einem weiter wachsenden Anteil erneuerbarer Energien mit zum Teil geringen Beitragen zur gesicherten Erzeugungsleistung stellt sich die Frage, wie die Versorgungssicherheit in Deutschland und insbesondere in Suddeutschland aus heutiger Perspektive in den kommenden Jahren gewahrleistet werden kann. Ausgehend von derzeitigen Marktbedingungen, dem geplanten Ausbau erneuerbarer Energien sowie den bestehenden und heute im Bau befindlichen Kraftwerken diskutiert der vorliegende Beitrag Ergebnisse statischer Leistungsbilanzen und modellbasierter Szenarienanalysen hinsichtlich des Zeitpunkts und der Quantitat moglicher Deckungslucken in der Stromversorgung.

In order to deal with the effects of the "Energiewende", in November of 2014 the German government outlined the future regulatory framework of the national electricity market. Among the suggested new measurements is a strategic reserve that will be used in situations of peak demand when in the spot market clearing cannot be achieved. The size of this strategic reserve is expected to be around 5 GW, approximately 5% of the current peak load. In this paper, for the first time a detailed agent-based simulation model is used to analyze the effects of the implementation of a strategic reserve on electricity prices and investments. The results show that this instrument considerably improves the security of supply and its yearly costs range from 50 to 300 million Euros depending on market scarcity. However, in extreme situations, e.g., high penetration of fluctuating renewable energy sources and very volatile cash flows for investors, capacity markets might provide more efficient ways to ensure security of supply.

In the context of wholesale electricity markets, agent-based models have shown to be an appealing approach. Given its ability to adequately model interrelated markets with its main players and considering detailed data, agent-based models have already provided valuable insights in related research questions, e.g. about adequate regulatory frameworks. In this paper, an agent-based model with an application to the German and French market area is presented. The model is able to analyze short-term as well as long-term effects in electricity markets. It simulates the hourly day-ahead market with limited interconnection capacities between the regarded market areas and determines the market outcome as well as the power plant dispatch. Yearly, each agent has the possibility to invest in new conventional capacities which e.g. allows assessing security of supply related questions in future years. Furthermore, the model can be used for participatory simulations where humans take the place of the models agents. In order to adapt to the ongoing changes in electricity markets, e.g. due to the rise of renewable energies and the integration of European electricity markets, the model is constantly developed further. Future extensions include amongst others the implementations of an intraday market as well as the integration of additional market areas.

Today’s liberalized wholesale electricity markets are generally considered to be highly complex systems. This is due to, among other things, the specific characteristics of the commodity electricity (e.g. instantaneous balancing of supply and demand, limited storability) and the fact that electricity can only be transported by a transmission grid with limited capacities. Other factors that increase the complexity are the various interrelated markets where electricity or related products can be traded (e.g. day-ahead market, future market) and the influence of other volatile markets such as the market for carbon emission allowances.

In this paper, the development of an interconnected German and French electricity market until 2030 is analyzed by applying an agent-based simulation model for wholesale electricity markets. National day-ahead markets are modeled and coupled considering limited transmission capacities. The results show that coupling the German and French market areas is effectively contributing to balance extreme load situations. Furthermore, based on the endogenous investment planning, mainly new combined cycle gas turbine plants are installed in Germany and France. However, despite incentives for investors to install new generation capacity, the model results indicate that in the coming years few situations will occur in which the residual demand cannot be fully met. Given the static consideration of the hourly electricity demand, the exchange flows with other countries and hydroelectric plants with seasonally operated reservoirs in this paper, effects and interactions of these flexibility options on the electricity system need to be analyzed in more detail in future research.

Increasing the share of intermittent renewable electricity generation will require additional flexibility in the electricity system. While energy storage can provide such flexibility, studies about the economics of power storage often conclude that there is no business case for large-scale storage applications. In this paper, we present a new approach on how to assess the benefits of energy storage. Key improvements have been made in two areas: Firstly, the agent-based market simulation model PowerACE has been enhanced to make use of optimization methods (MILP) for the unit commitment of the agents, enabling us to quantify the economic benefit of flexibility at supply-agent level. Secondly, we have considerably extended the common unit commitment problem (Carrion and Arroyo, IEEE Trans Power Syst 21(3):1371–1378, 2006), so that we can now model the provision of positive and negative balancing power and the dispatch of storage units. We compare the flexibility offered by thermal power plants to that offered by storage units for the four major German electricity generating companies under two different scenarios. The results for 2030 indicate that it would be more profitable to build up to 4,800 MW storage capacity in the German market rather than investing in flexible combined cycle gas turbine plants or hard coal-fired units. The increasingly fluctuating residual load implies that inflexible power plants will be penalized. Using storage units, the power plants of an existing portfolio can be dispatched in a more efficient way, i.e. with less operation in part load and avoiding start-up or shutdown events.

This paper proposes an agent-based model for the German wholesale electricity market that accounts for short-time uncertainty factors such as power plant outages or fluctuating renewable energy sources. The model is highly detailed using hourly values for the national demand and the feed-in from renewable energy sources as well as daily prices for carbon, coal, gas and oil. Each power plant in Germany with a capacity of more than 10 MW is considered in the model. Generation companies are represented by agents that submit bids into the market based on variable costs, start-up costs and minimal startup times of their generation capacities. In order to validate the model, a simulation is run which demonstrates that the model is well capable of replicating historical market results.

Due to very ambitious energy-political goals, the German energy sector is currently undergoing a transition. The resulting challenges are identified in this two-part contribution, before suggesting and discussing possible solutions. This first part is devoted to electricity generation in renewable and conventional plants. The second part focusses on the demand side and infrastructure, followed by a discussion of energy systems analysis as a suitable methodological approach to these problems. The greatest challenge for the energy sector is the integration of renewable energy (RE) into the existing energy system. Thereby support policies must be adjusted to regional particularities and other policy measures. The objective is to improve the competitiveness of these technologies and to integrate them into the energy market and system.