The continue evolution of complex power systems requires new tools and experimental setups to verify in a practical form the development of advance management systems. This work shows the different cyber-physical layers of power systems and multiple applications necessary to keep the voltage of a distribution grid inside the safe operating limits. Moreover, This paper demonstrates the integration of a voltage regulation (VR) method in an emulated distribution system operator’s (DSO) control centre (CC). The voltage regulator is based on control of photovoltaic generators production. Measurement data obtained in a real time simulator environment arrives to CC with the support of 5G communications. Hence, data can be stored in the DSO’s database. Finally, topology identification and state estimator are performed to feed information into the voltage regulation application. Hardware-in-the-loop validation has been developed to validate the VR approach.

MOTIVATION: Simulation is an essential technique for generating biomolecular data with a 'known' history for use in validating phylogenetic inference and other evolutionary methods. On longer time scales, simulation supports investigations of equilibrium behavior and provides a formal framework for testing competing evolutionary hypotheses. Twenty years of molecular evolution research have produced a rich repertoire of simulation methods. However, current models do not capture the stringent constraints acting on the domain insertions, duplications, and deletions by which multidomain architectures evolve. Although these processes have the potential to generate any combination of domains, only a tiny fraction of possible domain combinations are observed in nature. Modeling these stringent constraints on domain order and co-occurrence is a fundamental challenge in domain architecture simulation that does not arise with sequence and gene family simulation. RESULTS: Here, we introduce a stochastic model of domain architecture evolution to simulate evolutionary trajectories that reflect the constraints on domain order and co-occurrence observed in nature. This framework is implemented in a novel domain architecture simulator, DomArchov, using the Metropolis-Hastings algorithm with data-driven transition probabilities. The use of a data-driven event module enables quick and easy redeployment of the simulator for use in different taxonomic and protein function contexts. Using empirical evaluation with metazoan datasets, we demonstrate that domain architectures simulated by DomArchov recapitulate properties of genuine domain architectures that reflect the constraints on domain order and adjacency seen in nature. This work expands the realm of evolutionary processes that are amenable to simulation. AVAILABILITY AND IMPLEMENTATION: DomArchov is written in Python 3 and is available at http://www.cs.cmu.edu/~durand/DomArchov. The data underlying this article are available via the same link. SUPPLEMENTARY INFORMATION: Supplementary data are available at Bioinformatics online.

In this paper, a virtual synchronous generation (VSG) strategy is proposed for a three-phase quasi-impedance source inverter (qZSI). The main objective of the scheme is to provide inertia and damping to the inverter operation in order to add those characteristics to the system in the form of ancillary services, thus contributing a more stable operation of the microgrid where the inverter is operating. The generated references are received by linear control loops on the dc and ac sides of the three-phase qZSI. In the development of this work, the theoretical foundations of the proposal are shown. Also, to prove that the strategy helps to improve the response of the system, simulated results of the qZSI connected to a weak grid are displayed, showing data of the inverter operating in a traditional form (without inertia) and as a VSG, to make comparisons.

This paper presents the parameter identification of an equivalent circuit-based proton-exchange membrane fuel cell model. This model is represented by two electrical circuits, of which one reproduces the fuel cell's output voltage characteristic and the other its thermal characteristic. The output voltage model includes activation, concentration, and ohmic losses, which describe the static properties, while the double-layer charging effect, which delays in fuel and oxygen supplies, and other effects provide the model's dynamic properties. In addition, a novel thermal model of the studied Ballard's 1.2-kW Nexa fuel cell is proposed. The latter includes the thermal effects of the stack's fan, which significantly improve the model's accuracy. The parameters of both, the electrical and the thermal, equivalent circuits were estimated on the basis of experimental data using an evolution strategy. The resulting parameters were validated by the measurement data obtained from the Nexa module. The comparison indicates a good agreement between the simulation and the experiment. In addition to simulations, the identified model is also suitable for usage in real-time fuel cell emulators. The emulator presented in this paper additionally proves the accuracy of the obtained model and the effectiveness of using an evolution strategy for identification of the fuel cell's parameters.

A generalized and versatile approach for control of the circulating currents of Modular Multilevel Converters (MMC) has been recently proposed by using Lagrange Multipliers in the ABC frame. This approach is capable of analytically obtaining the differential current references associated with the desired operating conditions imposed to the optimization procedure. Previous implementations of this control approach have been sensitive to harmonic distortion of the control signals when applied to systems with a low number of levels, and have depended on average value calculations of sinusoidal variables, slowing down the dynamics of the control and making the tuning of the control system difficult under certain conditions. This work demonstrates that the performance of the versatile Lagrange-based control can be improved by introducing adaptive filtering based on Second Order Generalized Integrators (SOGIs) for processing the system variables needed for calculating the circulating current references. In addition to improved control dynamics and easier tuning of system controllers, the use of the adaptive filters provides inherent capability for operation under frequency variations, and is therefore suitable for control of MMCs operating in weak grids as well as for high- or medium-voltage motor drives.