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Spain must reduce its energy consumption by 23% and achieve 100% renewable energy in electricity generation by 2030. This paper presents the current energy scenario en Spain, and the outlooks for different renewable options, with special focus on photovoltaic (PV) solar energy. In 2012, Spain was the number two European country in terms of installed rewnewable energy power. Solar PV technology has the potential to meet Spain's future energy demand and its associated environmental challenges. This paper gives a review of solar energy economy at global scale for both PV and thermal power technologies. The Spanish energy scenario shows actual trends and progress made by solar power. Economic concepts of levelised cost of electricity and grid parity are presented. The financial analysis shows that PV electricity achieves grid parity at a plant profitability rate up to 7.26%. [ABSTRACT FROM AUTHOR]

The main objective of the work described in this paper is to offer a new method of prediction of wind speeds, whilst aware that the method develops predictions in time-scales that can vary from a few minutes to an hour. This is needed because wind energy generation is increasing its participation in energy distribution and has to compete with other energy sources that are not so variable in terms of generated active power. It is important to consider that active power demand can vary quite rapidly and different sources of electricity generation must be available. In the case of wind energy, wind speed predictions are an important tool to help producers make the best decisions when selling the energy produced. These decisions are crucial in the electricity market, because of the economic benefits for producers and consequently their profitability, depends on them. The algorithm presented in this paper is based on an artificial neural network and two types of wind data have been used to test the algorithm. In the first, data was collected from a not very windy area; in the second data was collected from a real wind farm located in Navarre (North of Spain), and the values vary from very low to high speeds. Although the algorithm was not tested with typical wind speed values measured on offshore wind farm applications, it can be concluded from the first set of results presented in this paper that the algorithm is valid for estimating average speed values. Finally, a generic algorithm for the active power generation of a wind farm is presented. [Copyright &y& Elsevier]

The repowering of already installed wind farms is considered one of the most promising and cost-effective short-term strategies to scale-up wind capacity. In this study, we apply Markowitz's mean-variance (MV) portfolio optimization theory to explore alternative repowering actions in Spain. The efficient portfolios – a direct outcome of the MV optimization – offer optimal repowering alternatives to current wind farm generation mixes. They deliver the highest possible average power output (yield) for a given level of supply risk. Different repowering scenarios are considered in this paper that range from a full restructuring of the existing wind generation mix to restricting by certain amounts the percentage of down-/uprating of each reference region. Results show that, depending on the configuration of the MV portfolio optimization problem, hourly fluctuations in the aggregate power supply can be reduced as much as 12–31%, while retaining the current level of energy productivity. In addition, for the level of energy supply risk experienced with the existing portfolio of Spanish wind farms; we can derive more efficient mixes that boost-up productivity by 16–55%. This work aims at providing valuable insight for energy policy-making in the direction of optimally repowering future renewable generation. [ABSTRACT FROM AUTHOR]

Abstract: Biomass-fueled Organic Rankine Cycle power plants in a cogeneration topping layout have been operated in Central Europe since 2000. These plants are usually integrated into a district heating system and located near to the villages whose thermal and electric energy demands are to be covered. In this paper, a technical and economic feasibility assessment of this kind of plants is presented. The energy performance has been analyzed in different scenarios. Four different typical organic fluids (two silicone oils, toluene and isopentane), subcritical and supercritical cycles and the inclusion of a recuperator have been considered. Thermal and electric energy are sold to a nearby village at competitive market prices. Spanish market prices have been used as a reference. No subsidies have been considered in the case of electricity, so that the Spanish average power pool market price has been considered. The size of the plant, the cost of biomass and the annual operation schedule have been considered for the economical analysis. According to the technical analysis, hexamethyldisiloxane (HMDSO) in recuperative cycles has turned out to be the best choice in both the subcritical and the supercritical layouts, due to its favorable global behavior (harmfulness, reliability and efficiency). The economic assessment shows a lower profitability in the case of supercritical cycles because of the fact that the increase in electric efficiency implies a decrease in the amount of produced useful heat, which is the main source of cash inflow. The size of the plant can be established according to the cost of fuel in order to achieve a similar profitability (i.e. a 1 MWe plant fueled with biomass priced at 5.5 €/MWhth has a similar internal rate of return than a 2 MWe plant fueled with biomass priced at 15.5 €/MWhth). In order to obtain a 5% internal rate of return with subcritical recuperative plants, the annual operation time must be 2750 h in the case of a 2 MWe plant fueled with biomass priced at 5.5 €/MWhth and 5500 h in the case of a 1 MWe plant fueled with biomass priced at 15.5 €/MWhth. [Copyright &y& Elsevier]

Abstract: Solar thermal electricity technologies are attractive alternatives to produce electricity by means of a renewable source. One of these technologies is parabolic trough collectors. In Spain, the sale of solar electricity to the national grid is primed. There are three main parameters that affect the behaviour of these plants: area of solar collector field, capacity of thermal storage tanks and power of the auxiliary system. In this paper, a simplified model of the plant is used to optimize the size of its components that produces the maximum yearly profit. The use of traditional methods of optimization is not possible and genetic algorithms have been used. An important feature of the model is that the minimum level of the electricity production of the block of power can be fixed. Once the optimization has been performed, the traditional parameters that characterize the dimension of the plant are analysed (the solar multiple and the capacity factor). For a gross power of 50 MW, the optimum collector area varies between 583,000 m2 and 749,860 m2 with a thermal storage between 6.55 h and 13.46 h respectively. The economic benefit is always higher than 19.30 M€ per year and the cost of the electricity produced is about 18.5 c€/kWh. [Copyright &y& Elsevier]

Abstract: This paper presents the hybridization of the fifth generation mesoscale model (MM5) with neural networks in order to tackle a problem of short-term wind speed prediction. The mean hourly wind speed forecast at wind turbines in a wind park is an important parameter used to predict the total power production of the park. Our model for short-term wind speed forecast integrates a global numerical weather prediction model and observations at different heights (using atmospheric soundings) as initial and boundary conditions for the MM5 model. Then, the outputs of this model are processed using a neural network to obtain the wind speed forecast in specific points of the wind park. In the experiments carried out, we present some results of wind speed forecasting in a wind park located at the south-east of Spain. The results are encouraging, and show that our hybrid MM5-neural network approach is able to obtain good short-term predictions of wind speed at specific points. [Copyright &y& Elsevier]