79 research outputs found

    Power system stability enhancement through the optimal, passivity-based, placement of SVCs

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    Over the last decades, several techniques have been proposed for the optimal placement of FACTS devices across power systems. Although these techniques were shown to improve \il{power system} operation, they are usually computationally intractable while having serious inherent limitations. In this paper, we present a novel approach to guide the SVC location identification in order to enhance power system stability. Specifically, the proposed method exploits findings in passivity-based control analysis and design in order to address the most vulnerable -in terms of passivity- buses of the system and consequently the optimal locations for SVC installation. We then show how the incorporation of SVCs at the aforementioned buses can passivate the system and provide \il{guarantees} for increased stability. Furthermore, we provide a brief discussion regarding the sizing and the number of required SVC devices in order to guarantee such stability improvement. Finally, we illustrate our results with simulations on the IEEE 68 bus system and show that both the dynamic response and the damping of the system are significantly improved

    Primary Frequency Regulation with Load-Side Participation-Part II: Beyond Passivity Approaches

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    We consider the problem of distributed generation and demand control for primary frequency regulation in power networks, such that stability and optimality of the power allocation can be guaranteed. It was shown in [1] that by imposing an input strict passivity condition on the net supply dynamics at each bus, combined with a decentralized condition on their steady state behaviour, convergence to optimality can be guaranteed for broad classes of generation and demand control dynamics in a general network. In this paper we show that by taking into account additional local information, the input strict passivity condition can be relaxed to less restrictive decentralized conditions. These conditions extend the classes of generation and load dynamics for which convergence to optimality can be guaranteed beyond the class of passive systems, thus allowing to reduce the conservatism in the analysis and feedback design.ER

    In silico evolution of diauxic growth

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    The glucose effect is a well known phenomenon whereby cells, when presented with two different nutrients, show a diauxic growth pattern, i.e. an episode of exponential growth followed by a lag phase of reduced growth followed by a second phase of exponential growth. Diauxic growth is usually thought of as a an adaptation to maximise biomass production in an environment offering two or more carbon sources. While diauxic growth has been studied widely both experimentally and theoretically, the hypothesis that diauxic growth is a strategy to increase overall growth has remained an unconfirmed conjecture. Here, we present a minimal mathematical model of a bacterial nutrient uptake system and metabolism. We subject this model to artificial evolution to test under which conditions diauxic growth evolves. As a result, we find that, indeed, sequential uptake of nutrients emerges if there is competition for nutrients and the metabolism/uptake system is capacity limited. However, we also find that diauxic growth is a secondary effect of this system and that the speed-up of nutrient uptake is a much larger effect. Notably, this speed-up of nutrient uptake coincides with an overall reduction of efficiency. Our two main conclusions are: (i) Cells competing for the same nutrients evolve rapid but inefficient growth dynamics. (ii) In the deterministic models we use here no substantial lag-phase evolves. This suggests that the lag-phase is a consequence of stochastic gene expression

    Nodal dynamics, not degree distributions, determine the structural controllability of complex networks

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    Structural controllability has been proposed as an analytical framework for making predictions regarding the control of complex networks across myriad disciplines in the physical and life sciences (Liu et al., Nature:473(7346):167-173, 2011). Although the integration of control theory and network analysis is important, we argue that the application of the structural controllability framework to most if not all real-world networks leads to the conclusion that a single control input, applied to the power dominating set (PDS), is all that is needed for structural controllability. This result is consistent with the well-known fact that controllability and its dual observability are generic properties of systems. We argue that more important than issues of structural controllability are the questions of whether a system is almost uncontrollable, whether it is almost unobservable, and whether it possesses almost pole-zero cancellations.Comment: 1 Figures, 6 page

    The interplay of intrinsic and extrinsic bounded noises in genetic networks

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    After being considered as a nuisance to be filtered out, it became recently clear that biochemical noise plays a complex role, often fully functional, for a genetic network. The influence of intrinsic and extrinsic noises on genetic networks has intensively been investigated in last ten years, though contributions on the co-presence of both are sparse. Extrinsic noise is usually modeled as an unbounded white or colored gaussian stochastic process, even though realistic stochastic perturbations are clearly bounded. In this paper we consider Gillespie-like stochastic models of nonlinear networks, i.e. the intrinsic noise, where the model jump rates are affected by colored bounded extrinsic noises synthesized by a suitable biochemical state-dependent Langevin system. These systems are described by a master equation, and a simulation algorithm to analyze them is derived. This new modeling paradigm should enlarge the class of systems amenable at modeling. We investigated the influence of both amplitude and autocorrelation time of a extrinsic Sine-Wiener noise on: (i)(i) the Michaelis-Menten approximation of noisy enzymatic reactions, which we show to be applicable also in co-presence of both intrinsic and extrinsic noise, (ii)(ii) a model of enzymatic futile cycle and (iii)(iii) a genetic toggle switch. In (ii)(ii) and (iii)(iii) we show that the presence of a bounded extrinsic noise induces qualitative modifications in the probability densities of the involved chemicals, where new modes emerge, thus suggesting the possibile functional role of bounded noises
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