No abstract

No abstract

The variability in non-dispatchable power generation makes essential the improvement of production management. This study focuses on the development of an optimisation model for a renewable power unit, composed of a wind farm and a hydro-pump storage power plant, to maximise its revenue. The combination of the two technologies allows the mitigation of risks associated with wind production and electricity price variability. The problem is formulated using linear programming and encompasses the selling of electricity in the Iberian day-ahead market and through a bilateral contract. The model is tested and scrutinised with sets of real historical generation and price data. In the day-ahead market scenario, the proposed methodology leads to an average yearly increase of net revenue ranging between 5% and 20%. In the bilateral contract scenario, the coupling of the wind farm and hydropower plant can reduce the imbalances costs substantially. Furthermore, the work identifies a positive correlation between reservoir dimension, turbine capacity and revenue value. The study also detects a revenue reduction tendency related to the decrease in the volatility of electricity prices.

No abstract

Freight railroad transportation is a critical issue in an economic setting with growing concern about pollution and road congestion. With an efficient management, the rail option for freight transportation may lead to more competitive costs. In this article, we address one part of the complex issue of freight railroad transportation, which deals with the definition of train routes and, simultaneously, with the way freight is carried from its origin to its destinations. The integration of these two problems is called Train Design. A new genetic algorithm is proposed to solve this problem, which tries to find a freight processing order so that the iterative dispatch subproblems leads to a lower global cost solution. Some results show the effectiveness of the proposed algorithm.