On the market impact of wind energy forecasts

This paper presents an analysis of how day-ahead electricity spot prices are affected by day-ahead wind power forecasts. Demonstration of this relationship is given as a test case for the Western Danish price area of the Nord Pool’s Elspot market. Impact on the average price behaviour is investigated as well as that on the distributional properties of the price. By using a non-parametric regression model to assess the effects of wind power forecasts on the average behaviour, the non-linearities and time variations in the relationship are captured well and the effects are shown to be quite substantial. Furthermore, by evaluating the distributional properties of the spot prices under different scenarios, the impact of the wind power forecasts on the price distribution is proved to be considerable. The conditional price distribution is moreover shown to be non-Gaussian. This implies that forecasting models for electricity spot prices for which parameters are estimated by a least squares techniques will not have Gaussian residuals. Hence the widespread assumption of Gaussian residuals from electricity spot price models is shown to be inadequate for these model types. The revealed effects are likely to be observable and qualitatively similar in other day-ahead electricity markets significantly penetrated by wind power

Optimizing innovation, carbon and health in transport: assessing socially optimal electric mobility and vehicle-to-grid pathways in Denmark

This paper examines the social costs and benefits of potential configurations of electric vehicle deployment, including and excluding vehicle-to-grid. To fully explore the benefits and costs of different electric vehicle pathways, four different scenarios are devised with both today’s and 2030 electricity grid in Denmark. These scenarios combine different levels of electric vehicle implementation and communication ability, i.e. smart charging or full bi-directionality, and then paired with different levels of future renewable energy implementation. Then, the societal costs of all scenarios are calculated, including carbon and health externalities to find the least-cost mix of electric vehicles for society. The most cost-effective penetration of electric vehicles in the near future is found to be 27%, increasing to 75% by 2030. This would equate to a $34 billion reduction to societal costs in 2030, a decrease of 30$1,200 in 2030. However, current vehicle capital cost differences, a lack of willingness to pay for electric vehicles, and consumer discount rates are substantial barriers to electric vehicle deployment in Denmark in the near term

The impact of CO2-costs on biogas usage

The Danish government has set a target of being fossil fuel independent by 2050 implying that a high degree of inflexible renewable energy will be included in the energy system; biogas can add flexibility and potentially has a negative CO2-emission. In this paper, we investigate the socioeconomic system costs of reaching a Danish biogas target of 3.8 PJ in the energy system, and how CO2 costs affect the system costs and biogas usage. We perform our analysis using the energy systems model, Balmorel, and expand the model with a common target for raw biogas and upgraded biogas (biomethane). Raw biogas can be used directly in heat and power production, while biomethane has the same properties as natural gas. Balmorel is altered such that natural gas and biomethane can be used in the same technologies. Several CO2-cost estimates are investigated; hereunder a high estimate for the expected CO2-externality costs. We find that system costs increase with CO2-costs in most cases, while the biogas target becomes socio-economically cheaper. In the case of a very high CO2-cost, system costs decrease and biomethane becomes the primary fuel. Furthermore, biomethane functions as regulating power and the Danish fuel consumption increases due to a higher electricity export