Phase cascade lattice rectifier array: an exactly solvable nonlinear network circuit

An exact analysis of a 2-D lattice network consisting of N × N sites with rectifier and AC source elements with controllable phases reveals a method for generating ripple-free DC power without the use of any filtering circuit elements. A phase cascade configuration is described in which the current ripple in a load resistor goes to zero in the large N limit, enhancing the rectification efficiency without requiring any additional capacitor or inductor based filters. The integrated modular configuration is qualitatively different from conventional rectenna arrays in which the source, rectifier and filter systems are physically disjoint. Nonlinear networks in the large N limit of source-rectifier arrays are potentially of interest to a fast evolving field of distributed power networks.MNacknowledges support from a Graduate Fellowship in the ECE department at Boston University. We thank CMaedler, R Averitt, and members of the Photonics Center staff for assistance. JC acknowledges support from the Boston University RISE summer program. (Graduate Fellowship in the ECE department at Boston University; Boston University RISE summer program)Published versio

Stabilization of structure-preserving power networks with market dynamics

This paper studies the problem of maximizing the social welfare while stabilizing both the physical power network as well as the market dynamics. For the physical power grid a third-order structure-preserving model is considered involving both frequency and voltage dynamics. By applying the primal-dual gradient method to the social welfare problem, a distributed dynamic pricing algorithm in port-Hamiltonian form is obtained. After interconnection with the physical system a closed-loop port-Hamiltonian system of differential-algebraic equations is obtained, whose properties are exploited to prove local asymptotic stability of the optimal points.Comment: IFAC World Congress 2017, accepted, 6 page

Elasticity sampling links thermodynamics to metabolic control

Metabolic networks can be turned into kinetic models in a predefined steady state by sampling the reaction elasticities in this state. Elasticities for many reversible rate laws can be computed from the reaction Gibbs free energies, which are determined by the state, and from physically unconstrained saturation values. Starting from a network structure with allosteric regulation and consistent metabolic fluxes and concentrations, one can sample the elasticities, compute the control coefficients, and reconstruct a kinetic model with consistent reversible rate laws. Some of the model variables are manually chosen, fitted to data, or optimised, while the others are computed from them. The resulting model ensemble allows for probabilistic predictions, for instance, about possible dynamic behaviour. By adding more data or tighter constraints, the predictions can be made more precise. Model variants differing in network structure, flux distributions, thermodynamic forces, regulation, or rate laws can be realised by different model ensembles and compared by significance tests. The thermodynamic forces have specific effects on flux control, on the synergisms between enzymes, and on the emergence and propagation of metabolite fluctuations. Large kinetic models could help to simulate global metabolic dynamics and to predict the effects of enzyme inhibition, differential expression, genetic modifications, and their combinations on metabolic fluxes. MATLAB code for elasticity sampling is freely available