The Economics of Wholesale Electricity Markets

This dissertation is based on four articles. Chapter 2 is based on Growitsch and Müsgens (2005). In this chapter, we analyze the development of household electricity prices since the liberalization of the market in 1998. The chapter covers all components of the price, the wholesale component, and the transportation and distribution networks. We also discuss the developments of taxes and subsidies in the electricity market. The main result is that the liberalization appears to have had no significant impact on total consumer prices, as prices in 2004 are nearly the same as in 1998. However, a deeper analysis reveals significant differences between the price components: wholesale prices, which are at the focus of the other chapters in this dissertation, decreased significantly directly after the liberalization took place, but increased from 2001 to 2004. The latter effect is discussed in chapter 3. Despite this increase, wholesale prices are still lower in 2004 than they were in 1998. The costs for transportation and distribution networks decreased slightly but steadily over time. The prices of other cost components (Renewable energy act, CHP subsidies, taxes ), however, rose sharply after the liberalization. This result has serious implications, as it means that insubstantial reductions in household prices do not reveal much about the success of liberalization or the behavior of the electricity supply industry. Chapter 3 is based on Müsgens (2007). The chapter presents a model to calculate system marginal costs in electricity markets. The model is a dynamic linear optimization model including start-up costs, hydro storage and pump storage dispatch, and international power exchange in the equations. We apply this model to the German power exchange for the period from June 2000 to June 2003 and perform a competitive benchmarking study. We find that prices are very close to our model-derived competitive benchmark in a first period until August 2001: the difference between prices and benchmark is only 2% in this period. In the following period, observed market prices rise significantly; this rise is not reflected in the competitive benchmark: prices are nearly 50% above the competitive benchmark in this second period. We also show that this deviation mainly comes from the high demand periods in which capacity is scarce. This is in accordance with the theories of market power. Furthermore, the chapter contains several scenarios quantifying the price effects of non-convexities and other dynamic elements. Chapter 4 is based on Müsgens and Neuhoff (2005). As in chapter 3, we present a linear optimization model to determine the optimal dispatch. The model is extended to allow the analysis of the uncertainty brought into the market by wind power generation. We represent uncertainty by applying stochastic programming with recourse. We parameterize the model with historical data from the German power market and find that the short term costs for the integration of wind power are low, as there is sufficient capacity during most periods to provide balancing services. Chapter 5 is based on Kuntz and Müsgens (2005). The chapter presents a formal in-depth analysis of the effects of start-up costs on electricity markets. The chapter starts from a simplified version of the optimization problem in chapter 4. Using appropriate transformations (dualization of the original problem, rephrasing the dual and reconverting it into a modified primal problem), we can prove that the impact of start-up costs on the average price is very small, which was already suggested by the empirical analyses in chapters 3 and 4. Chapter 6 concludes the dissertation

A hybrid model for day-ahead electricity price forecasting: Combining fundamental and stochastic modelling

The accurate prediction of short-term electricity prices is vital for effective trading strategies, power plant scheduling, profit maximisation and efficient system operation. However, uncertainties in supply and demand make such predictions challenging. We propose a hybrid model that combines a techno-economic energy system model with stochastic models to address this challenge. The techno-economic model in our hybrid approach provides a deep understanding of the market. It captures the underlying factors and their impacts on electricity prices, which is impossible with statistical models alone. The statistical models incorporate non-techno-economic aspects, such as the expectations and speculative behaviour of market participants, through the interpretation of prices. The hybrid model generates both conventional point predictions and probabilistic forecasts, providing a comprehensive understanding of the market landscape. Probabilistic forecasts are particularly valuable because they account for market uncertainty, facilitating informed decision-making and risk management. Our model delivers state-of-the-art results, helping market participants to make informed decisions and operate their systems more efficiently

Policy choices and outcomes for offshore wind auctions globally

Offshore wind energy is rapidly expanding, facilitated largely through auctions run by governments. We provide a detailed quantified overview of utilised auction schemes, including geographical spread, volumes, results, and design specifications. Our comprehensive global dataset reveals heterogeneous designs. Although most auction designs provide some form of revenue stabilisation, their specific instrument choices vary and include feed-in tariffs, one-sided and two-sided contracts for difference, mandated power purchase agreements, and mandated renewable energy certificates. We review the schemes used in all eight major offshore wind jurisdictions across Europe, Asia, and North America and evaluate bids in their jurisdictional context. We analyse cost competitiveness, likelihood of timely construction, occurrence of strategic bidding, and identify jurisdictional aspects that might have influenced auction results. We find that auctions are embedded within their respective regulatory and market design context, and are remarkably diverse, though with regional similarities. Auctions in each jurisdiction have evolved and tend to become more exposed to market price risks over time. Less mature markets are more prone to make use of lower-risk designs. Still, some form of revenue stabilisation is employed for all auctioned offshore wind energy farms analysed here, regardless of the specific policy choices. Our data confirm a coincidence of declining costs and growing diffusion of auction regimes