Dynamic control of intermittent renewableenergy fluctuations in two-layer power grids

In this work we model the dynamics of power grids in terms of a two-layer network, and use the Italian high voltage power grid as a proof-of-principle example. The first layer in our model represents the power grid consisting of generators and consumers, while the second layer represents a dynamic communication network that serves as a controller of the first layer. The dynamics of the power grid is modelled by the Kuramoto model with inertia, while the communication layer provides a control signal Pc i for each generator to improve frequency synchronization within the power grid. We propose different realizations of the communication layer topology and of the control signal, and test the control performances in presence of generators with stochastic power output. When using a control topology that allows all generators to exchange information, we find that a control scheme aimed to minimize the frequency difference between adjacent nodes operates very efficiently even against the worst scenarios with the strongest perturbations. On the other hand, for a control topology where the generators possess the same communication links as in the power grid layer, a control scheme aimed at restoring the synchronization frequency in the neighborhood of the controlled node turns out to be more efficient.

Performance Evaluation of Single-Phase On-Board Charger with Advanced Controller

The increasing mobility of electric vehicles has inspired vehicle growth to power grid technology. Such as vehicle to grid technology allows to transfer the power from the electric vehicle battery to the power grid. This enable speak load shaving, load leveling, voltage regulation, and improved stability of the power system. To develop the vehicle to grid technology requires a specialized EV battery charger, which permits the bi-directional energy transfer between the power grid and the electric vehicle battery. There is a specific control strategy used for a bi-directional battery charger. The proposed control strategy is used for charge and discharge battery of EV. The charger strategy has two parts: 1) Bidirectional AC-DC Converter in two-way Communication System. 2) Bidirectional DC-DC Buck-Boost Converter. There are two modes of operation for a bidirectional ac-dc converter: for G2V, rectifying mode is used, and for V2G, inverter mode is used. The suggested charge strategy not only allows for two-directional power flow but also provides power quality management of the power grid. Fuzzy logic controller (FLC) transforms linguistic control topology evaluations knowledge into an automated control topology using FLC. The FLC is more stable, has less overshoot, and responds quickly. The operation of a standard PI controller and a FLC was compared in this study using MATLAB and Simulink, and different time domain characteristics were compared as toshow that the FLC had a smaller overshoot and a faster response than the PI controller. Keywords: Bi-directional AC-DC converter, bi-directional DC-DC Buck-Boost converter, electric vehicles (EVs), on-board battery charger (OBC), grid to vehicle (G2V), vehicle to grid (V2G).

Impacts of Heat and Mass Flux on MHD Flow and Heat Transfer of Radiative Nanofluid Past an Exponentially Shrinking/stretching Sheet With Viscous and Ohmic Dissipations

In this paper, a distributed formation flight control topology for Leader-Follower formation structure is presented. Such topology depends in the first place on online generation of the trajectories that should be followed by the agents in the formation. The trajectory of each agent is planned during execution depending on its neighbors and considering that the desired reference trajectory is only given to the leader. Simulation using MATLAB/SIMULINK is done on a formation of quadrotor UAVs to illustrate the proposed method. The topology shows very good results in achieving the formation and following the reference trajectory.

Formation Flight Control of Multi-UAV System Using Neighbor-based Trajectory Generation Topology

In this paper, a distributed formation flight control topology for Leader-Follower formation structureis presented. Such topology depends in the first place on online generation of the trajectories that should befollowed by the agents in the formation. The trajectory of each agent is planned during execution depending onits neighbors and considering that the desired reference trajectory is only given to the leader. Simulation usingMATLAB/SIMULINK is done on a formation of quadrotor UAVs to illustrate the proposed method. Thetopology shows very good results in achieving the formation and following the reference trajectory.