This paper presents a stochastic mixed-integer linear programming approach for solving the self-scheduling problem of a price-taker thermal and wind power producer taking part in a pool-based electricity market. Uncertainty on electricity price and wind power is considered through a set of scenarios. Numerical results from a case study are presented to illustrate the performance of the proposed...

This paper presents a method for evaluation of investments in small-scale wind power under uncertainty. It is assumed that the price of electricity is uncertain and that an owner of a property with wind resources has a deferrable opportunity to invest in one wind power turbine within a capacity range. The model evaluates investment in a set of projects with different capacity. It is assumed tha...

In a competitive electricity market environment, power producers and consumers need, on one hand, accurate load and/or electricity consumption forecasting tools. These tools will ensure an a-priori knowledge on the amount of energy needed for production. On the other hand, forecasting electricity prices, may play a very important role for producers and consumers when planning bidding strategies...

Given the agreed urgency of decarbonizing electricity and the need to guide decentralized private decisions, an adequate and credible carbon price appears essential. The paper defines and quantifies the useful concept of the break-even carbon price for mature zero-carbon electricity investments. It appears an attractive alternative given the difficulty of measuring the social cost of carbon, bu...

Wind offers an important alternative to coal as a source of energy for generation of electricity in China with the potential for substantial savings in carbon dioxide emissions. Wind fields derived from assimilated meteorological data are used to assess the potential for wind-generated electricity in China subject to the existing government-approved bidding process for new wind farms. Assuming ...

Forecasting prices in electricity markets is critical for consumers and producers in planning their operations and managing their price risk. We utilize the generalized autoregressive conditionally heteroskedastic (GARCH) method to forecast the electricity prices in two regions of New York: New York City and Central New York State. We contrast the one-day forecasts of the GARCH against techniqu...

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 regres...

In this paper we propose a jump-diffusion type model which recovers the main characteristics of electricity spot price dynamics in the Nordic market, including seasonality, mean-reversion and spiky behavior. We show how the calibration of the market price of risk to actively traded futures contracts allows for efficient valuation of Nord Pool's Asian-style options written on the spot electricit...