Oliver Woll

Gas Storage Valuation Under Limited Market Liquidity: An Application in Germany

Natural gas storages may be valuated by applying real options theory. However it is crucial, not to ignore that most evolving gas spot markets, like the German spot market, lack of liquidity. In this context, considering storage operators as price takers does not account for interdependencies of storage operations and market prices. This paper offers a novel approach to storage valuation taking into account the effect of management decisions on market prices. The within this paper proposed methodology determines the optimal production schedule and value by determining the stochastic differential equation describing the storage value and then applying a finite difference scheme. We find that limited liquidity lowers the storage value and reduces withdrawal and injection amounts. Further, we observe decreasing reservation prices for injection and withdrawing for growing illiquidity resulting in a left shift of injection and withdrawing threshold prices.

Optimization of Dispersed Energy Supply —Stochastic Programming with Recombining Scenario Trees

The steadily increasing share of wind energy within many power generating systems leads to strong and unpredictable fluctuations of the electricity supply and is thus a challenge with regard to power generation and transmission. We investigate the potential of energy storages to contribute to a cost optimal electricity supply by decoupling the supply and the demand. For this purpose we study a stochastic programming model of a regional power generating system consisting of thermal power units, wind energy, different energy storage systems, and the possibility for energy import. The identification of a cost optimal operation plan allows to evaluate the economical possibilities of the considered storage technologies.

Mean-Risk Hedging Strategies in Electricity Markets with Limited Liquidity

This article investigates mean risk hedging with respect to limited liquidity and studies the impact of different risk measures on the hedging strategies. For motivation and application purposes hedging in electricity markets is chosen, because the relevant hedging markets are characterized by limited liquidity. We enhance the approach in Woll and Weber (2015) to a mean-risk optimization under limited liquidity, including the risk measures absolute and relative Value and Conditional Value at Risk (VaR and CVaR). It can be shown that for position independent measures (Variance, relative VaR, relative CVaR) liquidity has no influence on the minimum risk hedging strategies, whereas for position dependent measures (absolute VaR, absolute CVaR) liquidity has an impact on the minimum risk hedging strategies. The article gives the mathematical formulations of the problems and discusses the economic relevance of the different models. In addition, we apply the analyzed concepts to the German Electricity markets.

Decision problems including limited liquidity in electricity markets

In most electricity markets, a key restriction for portfolio optimization is the limited liquidity. Hence, standard models for decision problems have to be adapted to cope with this situation. This paper shows an approach dealing with this situation by including a liquidity function into the standard mean- variance model going back to Markowitz. This leads to a quadratic optimization problem which is solved by using the Lagrange method. The main purpose of this paper is to analyse the optimal hedging strategies for power generators. For this, three different case studies are regarded to recognize several effects like dependency on the planning horizon or the interdependencies of electricity markets and the markets for fossil-fuels or CO2 certificates. Therefore, the case of base electricity on the German power exchange EEX, the case of coal at the API and the CO2 certificates are considered.

Disentangling irregular cycles in economic time series

Cycles play an important role when analyzing market phenomena. In many markets, both overlaying (weekly, seasonal or business cycles) and time-varying cycles (e.g. asymmetric lengths of peak and off peak or variation of business cycle length) exist simultaneously. Identification of these market cycles is crucial and no standard detection procedure exists to disentangle them. We introduce and investigate an adaptation of an endogenous structural break test for detecting at the same time simultaneously overlaying as well as time-varying cycles. This is useful for growth or business cycle analysis as well as for analysis of complex strategic behavior and short-term dynamics.