Renewable energies Driven by Feed-on Tariffs. Photovoltaic vs Wind Energy Development in Spain

Although others regulations regarding feed-in tariffs for photovoltaics (PV) existed in Spain previously, the one that meant a paradigm change was the introduction in 2007 of law R.D.661/2007 which established a feed-in tariff of 41,75 cents/kWh if the installed capacity was greater than 100KWp and 44,04 cents/kWh if it was smaller. The high level of the subsidies together with the lack of a limit for the total installed capacity originates the well-known Spanish photovoltaic boom. In September 2008 the installed PV capacity accounted for 3.2GWp (while the official objective stated in the national renewable roadmap was only 400MWp). To avoid this situation a new law, R.D. 1578/2008, was proclaimed which established a decreasing feed-in tariff of 32 cents/kWh (for ground installations) and 34 cents/kWh (for rooftops) and it limited the annual installed capacity to 500MWp. Although it was successful in limiting the PV subsidies total costs, the successive and sudden changes in regulations resulted very harmful to the local PV industry. In this article, the strong influence of feed-in tariff in the development of PV installed capacity and market evolution in Spain will be analyzed in detail. In addition, a comparison with other subsidized technologies which installed capacity has had a smoother evolution, as wind energy, will be presented.

Modeling the evolution of item rating networks using time-domain preferential attachment

The understanding of the structure and dynamics of the intricate network of connections among people that consumes products through Internet appears as an extremely useful asset in order to study emergent properties related to social behavior. This knowledge could be useful, for example, to improve the performance of personal recommendation algorithms. In this contribution, we analyzed five-year records of movie-rating transactions provided by Netflix, a movie rental platform where users rate movies from an online catalog. This dataset can be studied as a bipartite user-item network whose structure evolves in time. Even though several topological properties from subsets of this bipartite network have been reported with a model that combines random and preferential attachment mechanisms [Beguerisse Díaz et al., 2010], there are still many aspects worth to be explored, as they are connected to relevant phenomena underlying the evolution of the network. In this work, we test the hypothesis that bursty human behavior is essential in order to describe how a bipartite user-item network evolves in time. To that end, we propose a novel model that combines, for user nodes, a network growth prescription based on a preferential attachment mechanism acting not only in the topological domain (i.e. based on node degrees) but also in time domain. In the case of items, the model mixes degree preferential attachment and random selection. With these ingredients, the model is not only able to reproduce the asymptotic degree distribution, but also shows an excellent agreement with the Netflix data in several time-dependent topological properties.

Cost-free feed-in tariffs for renewable energy deployment in Spain

Feed-in-tariff (FIT) schemes have been widely employed to promote renewable energy deployment. While FITs may be perceived by consumers as an extra cost, renewable energies cause a noticeable price reduction in wholesale electricity markets. We analyse both effects for the case of the Spanish electricity market during 2010. In particular, we examine the level of FITs that makes savings and extra costs to be similar on an hourly basis. Results are obtained for a wide range of renewable generation scenarios. It is found that FITs with null extra costs for consumers are in the range of 50–80 €/MWh. Some of the side-effects of a high penetration of renewable energy in the market are analysed in detail and discussed.