September 2021 - news - Mailing lists@ IFISC

IFISC News - Assessing blackout risk in the power grid with high penetration of variable renewable energies
by ifisc＠ifisc.uib-csic.es 27 Sep '21

27 Sep '21

Assessing blackout risk in the power grid with high penetration of variable renewable energies Renewable energies related to the sun or wind will be decisive in the transition to a 100% renewable energy system. These energy sources have many advantages in terms of cost, efficiency and sustainability, but they also represent a risk in terms of reliability of grid operation when deployed on a massive scale. This risk stems from their variability over different time scales, having less production in cloudy days, for example. This makes it necessary to implement additional control and storage systems compared to a grid dominated by generation with conventional energy sources. Researchers at IFISC (CSIC-UIB) have published a study in which they analyze how the risk of blackouts in the electricity grid varies when conventional power plants are progressively replaced by variable renewable energy sources (VRES), up to generation fractions with renewables above 80 percent. In the article, published in IEEE Access, they have used a model of self-organised criticality for power system outages, known as the OPA (ORNL-PSERC-Alaska) model, and have taken the Balearic electricity system with a high penetration of solar energy as a case study. They have also taken into account a small amount of wind energy, but this energy source is too variable in the Balearic Islands for it to be convenient to implement it massively. In this work, the researchers only take into account day-to-day variations in renewable production and introduce a storage capacity equivalent to three days of generation to ensure a more constant energy supply. They also assume the current consumption pattern without additional savings measures. The results of the simulations show that, starting from the current case where renewables account for 3 %, up to 30-40 percent of the conventional generation capacity can be replaced by solar PV without increasing the risk of blackouts. Furthermore, this risk is slightly reduced by the fact that solar production is more spatially distributed than conventional production (i.e. there are more production points), which reduces the load on the distribution grid. By further increasing the renewable fraction of installed capacity, keeping the total generation capacity equal to 140 percent of consumption, the risk of blackouts increases exponentially due to the lack of supply on days of low renewable production, mainly in winter. So, to increase the fraction of renewable energy above 40 percent and guarantee supply at all times to maintain the risk of blackouts at the current level, there are two options: either maintain conventional generation capacity while increasing renewable capacity, or install a large renewable overcapacity. The researchers' calculations show that, in the second case, to reach 80 percent renewable production without increasing the risk of blackouts, solar power capacity must be installed that can produce 2.5 times the annual demand during the year. Even so, in order to guarantee supply during periods of low renewable production, this scenario maintains an installed conventional capacity equivalent to 32% of consumption. Scenarios with less conventional generation would require much more long-term storage capacity. Carreras, BA, Colet, P., Reynolds-Barredo, JM, Gomila, D. Assessing blackout risk with high penetration of variable renewable energies. IEEE Access. Doi: https://doi.org/10.1109/ACCESS.2021.3114121.UIB http://ifisc.uib-csic.es/en/news/assessing-blackout-risk-power-grid-high-pe…

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IFISC News - Game theory to understand rigged economies
by ifisc＠ifisc.uib-csic.es 23 Sep '21

23 Sep '21

Game theory to understand rigged economies From Adam Smith's 'invisible hand' to the very tangible effect of corruption and market manipulation, economic systems have always been under suspicion. "The game is rigged!" is often heard as a slogan to denounce injustices or counter-intuitive behavior given the complexity of the economy. What would happen if we accept, in fact, that the market can be rigged? How would it then change the nature of the economic relations (markets, contracts, industry, etc.) in which we participate? Luís F. Seoane, CSIC researcher formerly at the Institute for Cross-Disciplinary Physics and Complex Systems (IFISC, UIB-CSIC) and currently at the National Centre for Biotechnolgy (CNB, CSIC), presents a mathematical model in the journal Physical Review X to explore these questions. He uses the game theory developed by John Nash (the main character of the film "A Beautiful Mind") to simulate economic systems in which anyone can cheat - altering the rules of the game in exchange for a set price. Can a rigged economy be stable? What is the level of intervention that can be tolerated? How does this change when the amount of money that moves in the market grows, or when the complexity of the economic system grows (introducing new possibilities for cheating)? These are some of the questions that the model raises and aims to answer. The paper uncovers a possible strategy for undoing consensus situations - for example, cases such as cartels, in which several firms join together unopposed to fix the price of their services. Also, in the case of complex economies, which have many elements that can be rigged, a very unstable regime emerges in which large gains and losses follow one another in unpredictable ways. The mathematical model suggests that such a volatile regime could be avoided if wealth grew much faster than the opportunities for cheating. "This model has a clear application for understanding real cases" says Seoane. For example, in the GameStop incident, a video game shop chain that has been heavily devalued over the past year. At the end of February, thousands of small investors synchronized through the social network Reddit to invest and raise the price of this company. The phenomenon went viral, catching large investment funds that had bet that GameStop would not stop falling. Several of these investment funds have gone bankrupt after incurring millions in debt. This was followed by cross accusations of market manipulation that are still being resolved in the courts and in the US Congress. The model considers both the coordinated actions of small investors and the short positions of investment funds as attempts to rig the company's price. Thanks to trading apps, the development of cryptocurrencies, and the proliferation of smart contracts, intervention in the economy by small investors is likely to democratize and expand. The study analyses the problems that could arise in connection with these new technologies, and aspects to which attention should be paid in order to avoid greater evils.Luís F. Seoane. Games in rigged economies. Phys. Rev. X 11, 031058. DOI: https://doi.org/10.1103/PhysRevX.11.031058Image: Carles G.O'DCSIC http://ifisc.uib-csic.es/en/news/game-theory-understand-rigged-economies/

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IFISC News - Nit de la Recerca 2021
by ifisc＠ifisc.uib-csic.es 17 Sep '21

17 Sep '21

Nit de la Recerca 2021 The European Researchers' Night is a science outreach project promoted by the European Commission as part of the Marie Sktodowska-Curie actions of the Horizon 2020 programme, and has been taking place simultaneously in more than 300 European cities since 2005. Its main objective is to bring researchers closer to citizens so that they can learn about their work, the benefits they bring to society and their impact on everyday life. On the occasion of the celebration of the European Researchers' Night, IFISC will participate in the scientific dissemination activities organised by the CSIC Representation in the Balearic Islands. The event will take place in the historic centre of Palma, at Ca n'Oleo from 18:30 to 21:00. Among the activities will be the 'Speed Dating'. This activity, aimed at the general public, will feature scientific staff from centres belonging to and associated with the CSIC Representation in the Balearic Islands, including IFISC pre-doctoral researchers María Martínez-Barbeito, Javier Galván and Annalisa Caligiuri, who will explain in 5 minutes what their research work consists of. Due to COVID regulations, seating is limited and advance booking is required, available on this form or through the Representación’s website. http://ifisc.uib-csic.es/en/news/nit-de-la-recerca-2021/

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IFISC News - Deep Neural Networks using a single neuron
by ifisc＠ifisc.uib-csic.es 14 Sep '21

14 Sep '21

Deep Neural Networks using a single neuron Deep Neural Networks (DNNs) are a useful tool for a wide range of tasks such as image classification, object detection, image resizing or text generation. They are extremely powerful, but they require sufficient computing power and large data sets to train them. Deep Neural Networks typically consist of multiple layers of neurons coupled in feed-forward architectures. In these architectures, where you can easily end up with hundreds of thousands of neurons, the information moves in only one direction: forward, from the input to the output. An international team of researchers, including scientists from IFISC (UIB-CSIC), has developed an approach to emulate a full deep neural network using only a single artificial neuron with feedback-modulated delay loops. The large network of many interacting elements is replaced by a single element, representing different elements in time by interacting with its own delayed states. The paper has been published in Nature Communications and has been selected for the Nature Communications Editors’ Highlights webpage in the section of recent multidisciplinary research called “AI and machine learning”. This new approach, named Folded-in-Time Deep Neural Network (Fit-DNN) by the authors, can reduce the required hardware drastically and offers a new perspective on how to construct trainable complex systems, since only a single neuron and several delay lines need to be implemented. Delay systems inherently possess an infinite-dimensional phase space, so just one neuron with feedback is sufficient to fold and capture the entire complexity of the network. The Fit-DNN approach is very useful for hardware implementations, where the neural network itself is built using physical substrates. In a typical DNN you would need to implement each neuron with a unique hardware element, but by capturing the behavior of the whole system with a single neuron, the need to implement a full network is removed. The authors exemplify this with an optoelectronic scheme. In this type of implementation, only one light emitter is required, plus some standard telecommunication components. Fit-DNNs allow a balance to be found between computational speed and the need for more hardware components, as it would be very expensive to implement a complete DNN. However, the approach does not reduce the training process time, since a traditional computer is still required. This Fit-DNN approach provides an alternative view on neural networks: the entire topological complexity of feed-forward multilayer neural networks can be folded into the temporal domain by the delay-loop architecture. Deep neural networks using a single neuron: folded-in-time architecture using feedback-modulated delay loops. Stelzer, Florian; Röhm, Andre; Vicente, Raul; Fischer, Ingo and Yanchuk, Serhiy. Nature Communications 12, 5164 (1-10) (2021). Doi: https://doi.org/10.1038/s41467-021-25427-4El Diari de la UIB http://ifisc.uib-csic.es/en/news/deep-neural-networks-using-single-neuron/

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IFISC News - Dynamical phase transitions in quantum Reservoir Computing
by ifisc＠ifisc.uib-csic.es 03 Sep '21

03 Sep '21

Dynamical phase transitions in quantum Reservoir Computing Information can be processed by physical, chemical and biological systems with a major example being our brain. In this context, quantum reservoir computing is a promising approach in the fields of complex systems and artificial neural networks characterized by a fast and easy training and with applications as time series processing and forecasting. Complex systems can store memory and can be used to non-linearly process input information, but understanding what is essential for a good quantum reservoir computer is key in order to achieve experimental implementations. A team of researchers of the Institute of Cross-disciplinary Physics and Complex Systems (IFISC, UIB-CSIC) has published a paper in Physical Review Letters in which they studied what dynamical natural properties of a qubit quantum network determine its ability to act as a reservoir computer. The paper shows the importance of tuning the reservoir at the onset of thermalization, which can be easily achieved by controlling the strength of the magnetic field. To do this, the researchers identified different response regimes offered by the model, being able to make dynamic phase transitions from one to another by changes of the degree disorder and transverse field strength. Indeed, a complex qubit network can be considered as a many-body system that can thermalize or display many-body localization. Bridging the context of quantum dynamical phases and neuromorphic computing, how these phenomena play a role in reservoir computing applications and implementations as in ion experiments, where these phenomena have been recently reported. An extensive analysis shows that thermalization is an essential feature for a quantum reservoir computer. Researchers also found that being at the edge of the dynamical transition can be beneficial for the model, while localization hinders information processing and spreading within the physical system. Uncovering the underlying physical mechanisms behind optical information processing capabilities of spin networks is essential for future experimental implementations and provides a new perspective on dynamical phases. Martínez Peña, Rodrigo; Giorgi, Gian Luca; Nokkala, Johannes; Soriano, Miguel C.; Zambrini, Roberta. Physical Review Letters 127, 100502 (1-7). https://doi.org/10.1103/PhysRevLett.127.100502 http://ifisc.uib-csic.es/en/news/dynamical-phase-transitions-quantum-reserv…

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IFISC News - Measuring bottlenecks in the ocean
by ifisc＠ifisc.uib-csic.es 01 Sep '21

01 Sep '21

Measuring bottlenecks in the ocean The ocean provides a fluid environment with complex patterns of flow and dispersal for the organisms that live within it. How these flows transport organisms is relevant for biodiversity with potentially important implications for ecosystem health and climate. An international team of scientists with participation of researchers from IFISC (UIB-CSIC), has published a study in Nature Communications in which they report on a new metric they have developed that can be used to characterize the dispersive nature of fluid flows, including ocean circulations, important for these diversity patterns. The method relies on the betweenness centrality, a concept that emerges from network theory, which has been used to identify and highlight bottlenecks in systems from air-transportation networks to the human brain. This has been demonstrated to be a very effective measure with which to identify nodes that act as foci for congestion, or bottlenecks, in the network. However, until now there hasn’t been a way to define betweenness outside the network framework. In their new study, the researchers link dynamical systems and network theory concepts, and extend the concept of betweenness centrality applying it to the complex fluid patterns of oceanic circulations. High betweenness indicates a region where flows converge and diverge again, the above mentioned bottlenecks but now in the ocean flow. Such oceanic confluences are very relevant since they facilitate heightened mingling and dispersal of marine microbial populations. Using modeled and observational velocity fields from the Adriatic Sea and Antarctic Circumpolar Current, two regions exhibiting very different circulation regimes, the team showed that such bottlenecks are both present and surprisingly persistent across different spatio-temporal scales illustrating the role of these areas in driving fluid transport over vast oceanic regions. The researchers anticipate that this new metric will be a useful tool in mapping and interpreting global-scale patterns of biodiversity in the ocean, suggesting promise for ecological applications. Ser-Giacomi, E.; Baudena, A.; Rossi, V.; Follows, M.; Clayton, S.; Vasile, R.; Lopez, C.; Hernandez-Garcia, E. Nature Communications 12, 4935 (1-14) (2021). DOI: 10.1038/s41467-021-25155-9El Diari de la UIB http://ifisc.uib-csic.es/en/news/measuring-bottlenecks-ocean/

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