Trine Krogh Boomsma

Renewable energy investments under different support schemes: A real options approach

This paper adopts a real options approach to analyze investment timing and capacity choice for renewable energy projects under different support schemes. The main purpose is to examine investment behavior under the most extensively employed support schemes, namely, feed-in tariffs and renewable energy certificate trading. We consider both multiple sources of uncertainty under each support scheme and uncertainty with respect to any change of support scheme, and we obtain both analytical (when possible) and numerical solutions. In a Nordic case study based on wind power, we find that the feed-in tariff encourages earlier investment. Nevertheless, as investment has been undertaken, renewable energy certificate trading creates incentives for larger projects. In our baseline scenario and taking the fixed feed-in tariff as a base, the revenue required to trigger investments is 61% higher with renewable certificates. At the same time, investment capacity is 61% higher.

Bidding in sequential electricity markets: The Nordic case

For electricity market participants trading in sequential markets with differences in price levels and risk exposure, it is relevant to analyze the potential of coordinated bidding. We consider a Nordic power producer who engages in the day-ahead spot market and the hour-ahead balancing market. In both markets, clearing prices and dispatched volumes are unknown at the time of bidding. However, in the balancing market, the market participant faces an additional risk of not being dispatched. Taking into account the sequential clearing of these markets and the gradual realization of market prices, we formulate the bidding problem as a multi-stage stochastic program. We investigate whether higher risk exposure may cause hesitation to bid into the balancing market. Furthermore, we quantify the gain from coordinated bidding, and by deriving bounds on this gain, assess the performance of alternative bidding strategies used in practice.

Impact of forecast errors on expansion planning of power systems with a renewables target

This paper analyzes the impact of production forecast errors on the expansion planning of a power system and investigates the influence of market design to facilitate the integration of renewable generation. For this purpose, we propose a programming modeling framework to determine the generation and transmission expansion plan that minimizes system-wide investment and operating costs, while ensuring a given share of renewable generation in the electricity supply. Unlike existing ones, this framework includes both a day-ahead and a balancing market so as to capture the impact of both production forecasts and the associated prediction errors. Within this framework, we consider two paradigmatic market designs that essentially differ in whether the day-ahead generation schedule and the subsequent balancing re-dispatch are co-optimized or not. The main features and results of the model set-ups are discussed using an illustrative four-node example and a more realistic 24-node case study.

Renewable generation expansion under different support schemes: A stochastic equilibrium approach

Abstract Following the deregulation of electricity markets, a current challenge of policy makers is to facilitate the transition to a sustainable power system at the highest welfare for society. In this paper we investigate the efficiency of different support schemes, such as a feed-in tariff, a feed-in premium and tradable green certificates, with respect to incentivizing the required investments in renewable generation. We consider a number of generation expansion problems, and formulate stochastic equilibrium models that account for uncertainty in demand and renewable supply, the risk-aversion of investors and the competitiveness of the market. The problem of the policy maker is formulated as a mathematical program with equilibrium constraints (MPEC) and as a non-linear complementarity problem (NCP) for the feed-in schemes and the certificate market, respectively. Our models are solved for a small illustrative example and a larger case study based on the Danish power system. The results confirm that the main driver for the optimal choice of renewable support scheme is the aversion of power producers towards price and volume risk, while the competitiveness of the market rarely affects such choice.

Short-term balancing of supply and demand in an electricity system: forecasting and scheduling

Until recently, the modelling of electricity system operations has mainly focused on hour-by-hour management. However, with the introduction of renewable energy sources such as wind power, fluctuations within the hour result in imbalances between supply and demand that are undetectable with an hourly time resolution. Ramping restrictions on production units and transmission lines contribute further to these imbalances. In this paper, we therefore propose a model for optimising electricity system operations within the hour. Taking a social welfare perspective, the model aims at reducing intra-hour costs by optimally activating so-called manual reserves based on forecasted imbalances. Since manual reserves are significantly less expensive than automatic reserves, we expect a considerable reduction in total costs of balancing. We illustrate our model in a Danish case study and investigate the effect of an expected increase in installed wind capacity. We find that the balancing costs do not outweigh the benefits of the inexpensive wind power, and that the savings from activating manual reserves are even larger for the high wind capacity case.

The degree of rationality in actual bidding of hydropower at Nord Pool

In deregulated electricity markets, power producers bid to sell tomorrows generation in day-ahead auctions. We analyse bids submitted by three medium to large sized Norwegian reservoir hydropower producers over four two-week periods in 2011. Being price takers, the producers maximize their profits by bidding their marginal cost. Additionally, production must respect both external market rules and internal technical and hydrological restrictions when bidding. Patterns in the submitted bids are found and explanations for the bidding behavior are given. Furthermore, potential irrationalities in the bidding are revealed.

Valuation of power plants

Abstract In this paper we develop continuous-time stochastic control models for valuation and operation of three stylised types of power plants in an electricity market: a renewable plant, a conventional plant and a storage plant. Examples of these types of power plants are respectively wind turbines, gas-fired generation units and hydroelectric facilities. We demonstrate how to derive analytical or quasi-analytical solutions in spite of many details in modeling. In particular, we model uncertainty in electricity prices and in production input/output when it is relevant for the technology considered. Input/output is assumed to follow a diffusion process, whereas the price process may include jumps. Our models account for special characteristics of the technologies, including a non-Normal distribution of wind speeds as well as start-up and shut-down costs of thermal units. We use our models to assess the impact of conjectured future market conditions such as increasing average price level, price volatility and correlation between renewable production and electricity prices.

Electricity capacity expansion in a Cournot duopoly

This paper adopts a real options approach to analyze marginal investments in power markets with heterogeneous technologies and time-varying demand. We compare the investment behavior of two firms in a Cournot duopoly to a central planners when two categories of power plants are available; base and peak load power plants. We find that producers exercise market power and the prices increase. Furthermore, the peak load plants become relatively more valuable and the share of installed peak load capacity exceeds the peak load share in a perfectly competitive market. In a numerical example, we show that this results in welfare losses above 10 %, and significantly larger reduction in the consumer surplus. Further, we examine the effect of analyzing power markets without time-varying demand and find that this underestimates investments in peak load capacity.