https://hdl.handle.net/20.500.12412/2543 2026-05-06T03:07:36Z 2026-05-06T03:07:36Z Pedregal, D. J. Contreras, Javier Sánchez de la Nieta, Agustín https://hdl.handle.net/20.500.12412/5070 2024-07-12T14:32:45Z 2011-11-17T00:00:00Z

ECOTOOL: A general MATLAB forecasting toolbox with applications to electricity markets. Pedregal, D. J.; Contreras, Javier; Sánchez de la Nieta, Agustín Electricity markets are composed of different agents that make their offers to sell and/or buy energy. These agents need forecasting tools to have an accurate prediction of the prices that they will face either in the day-ahead or long-term time spans. This work presents the ECOnometrics TOOLbox (ECOTOOL), a new MATLAB forecasting toolbox that embodies several tools for identification, validation and forecasting models based on time series analysis, among them, ARIMA, Exponential Smoothing, Unobserved Components, ARX, ARMAX, Transfer Function, Dynamic Regression and Distributed Lag models. The toolbox is presented in all its potentiality and several real case studies, both on the short and medium term, are shown to illustrate its applicability.; Es la versión aceptada del documento. Se puede consultarla versión final en https://doi.org/10.1007/978-3-642-23193-3_6

2011-11-17T00:00:00Z Díaz-Pérez, Manuel Antonio Lucas-Consuegra, Antonio de Serrano Ruiz, Juan Carlos https://hdl.handle.net/20.500.12412/4933 2024-07-12T13:27:45Z 2021-01-01T00:00:00Z

Electrocatalytic Conversion of CO2 to Syngas Díaz-Pérez, Manuel Antonio; Lucas-Consuegra, Antonio de; Serrano Ruiz, Juan Carlos Technologies for the capture and subsequent conversion of CO2 into useful products have received significant attention in recent years. Among the conversion technologies available today, the electroreduction of CO2 is particularly interesting because of three main reasons. Firstly, it can be carried out at room temperature and with high efficiency. Secondly, it can make use of renewable electricity and lastly the extent of the reduction process can be modulated to produce a wide variety of interesting chemicals, with syngas (i.e. a mixture of H2 and CO with high chemical value) being particularly relevant. This chapter summarizes the most important electroreduction technologies allowing the conversion of CO2/water mixtures into syngas mixtures. The effect of the cathode composition, the configuration of the electrochemical cell, and the reaction conditions on the syngas production performance have been analyzed in detail. Finally, some examples on how the electrochemical promotion of catalysis (EPOC) effect can be used to enhance the CO2 hydrogenation reaction and drive the process to the production of syngas mixtures have been described.

2021-01-01T00:00:00Z Serrano Ruiz, Juan Carlos https://hdl.handle.net/20.500.12412/4932 2024-07-12T13:16:35Z 2017-01-01T00:00:00Z

Biomass conversion technologies: catalytic conversion technologies Serrano Ruiz, Juan Carlos Diminishing fossil fuel reserves and global warming issues are driving society toward the search for new renewable sources of energy . Lignocellulosic can significantly displace petroleum in the production of fuels . Oxygenated fuels such as ethanol and biodiesel currently dominate the fuel market although they have important limitations. The production of liquid hydrocarbon fuels from biomass is a paradigmatic transformation allowing the production of fuels chemically identical to those currently used in the transportation sector. The present chapter describes some of the catalytic strategies used to transform biomass-derived molecules into liquid hydrocarbon fuels. These strategies are first focused on decreasing the oxygen content of the original molecule such that its reactivity can be more easily controlled. In a subsequent step, the less oxygenated intermediates are upgraded via C–C coupling reactions to increase the length chain to produce a final product suitable for diesel and jet fuel applications. The present chapter offers a number of examples on biomass-derived acids such as lactic and levulinic acids and biomass sugars such as glucose catalytically transformed into liquid hydrocarbon fuels.

2017-01-01T00:00:00Z Tapia Córdoba, Alejandro Gutiérrez Reina, Daniel Rodríguez Del Nozal, Álvaro Millán Gata, Pablo https://hdl.handle.net/20.500.12412/4465 2024-10-25T08:54:51Z 2020-01-01T00:00:00Z

Application of Genetic Algorithms for Designing Micro-Hydro Power Plants in Rural Isolated Areas—A Case Study in San Miguelito, Honduras Tapia Córdoba, Alejandro; Gutiérrez Reina, Daniel; Rodríguez Del Nozal, Álvaro; Millán Gata, Pablo The use of Micro-Hydro Power Plants (MHPP) has established itself as a fundamental tool to address the problem of energy poverty in rural isolated areas, having become the most used renewable energy source not just in this field but also in big scale power generation. Although the technology used has made important advances in the last few decades, it has been generally applied to big scale hydro-power systems. This fact has relegated the use of isolated MHPPs to the background. In this context, there is still a vast area of improvement in the development of optimization strategies for these projects, which in practice remains limited to the use of thumb rules. It results in a sub-optimal use of the available resources. This work proposes the use of a Genetic Algorithm (GA) to assist the design of MHPP, finding the most suitable location of the different elements of a MHPP to achieve the most efficient use of the resources. For this, a detailed model of the plant is first developed, followed by an optimization problem for the optimal design, which is formulated by considering the real terrain topographic data. The problem is presented in both single (to minimize the cost) and multi-objective (to minimize cost while maximizing the generated power) mode, providing a deep analysis of the potentiality of using GAs for designing MHPP in rural isolated areas. To validate the proposed approach, it is applied to a set of topographic data from a real scenario in Honduras. The achieved results are compared with a baseline integer-variable algorithm and other meta-heuristic algorithms, demonstrating a noticeable improvement in the solution in terms of cost.

2020-01-01T00:00:00Z