Smart Grid

Smart grid technologies are deepening the interdependence of electric power and communication systems, but that interdependence is difficult to quantify. In the case of microgrids, communication systems can be essential to maintaining stability during islanded operations. Though many power system studies assume the presence of perfect communication networks, detailed modelling of power and communication systems for dynamic studies of microgrids is rare.


Extracting the boundaries of Photovoltaic (PV) plants is essential in the process of aerial inspection and autonomous monitoring by aerial robots. This method provides a clear delineation of the utility-scale PV plants’ boundaries for PV developers, Operation and Maintenance (O&M) service providers for use in aerial photogrammetry, flight mapping, and path planning during the autonomous monitoring of PV plants. 


An optimization model with heuristic algorithm is implemented to optimize the virtual resistances of droop control for the grid-connected converters of dispatchable units, such that the power flow can be regulated. The performances of the proposed strategy are evaluated by the case studies of a 12-bus 380 V DC microogrid using matlab and a 32-bus 380 V DC microgrid using a real-time digital simulator.


We introduce a novel dataset containing a total of 61 distinct HEAs. The proposed appliances (e.g. fans, fridges, washers, etc.) are of different kinds, ages, brands and power
levels. They have been recorded in steady-state conditions in a French 50 Hz electrical grid. The measurement setup consists of an AC current probe (E3N Chauvin Arnoux) with a 10 mV/A sensitivity and a differential voltage probe with


This dataset includes high-resolution (1 s) power and reactive power profiles of household appliances. The dataset consists of ground truth data from a European household, laboratory measurements and few artificial created data. Specifically, the dataset includes data for TV, washing machine, toaster, iron, hairdryer, dish washer, PC, refrigerator, air-conditioner unit, range, dryer, heat pump (different modes of operation), BEV, water heater, light bulb and always-on load profiles.


The purpose of distribution network reconfiguration (DNR) is to determine the optimal topology of an electricity distribution network, which is an efficient measure to reduce network power losses. Electricity load demand and photovoltaic (PV) output are uncertain and vary with time of day, and will affect the optimal network topology. Single-hour deterministic DNR is incapable of handling this uncertainty and variability. Therefore, this paper proposes to solve a multi-hour stochastic DNR (SDNR).


This file is Matlab extended (.Mex). There is a frequency file measured at one second intervals.

The frequency regulation lithium battery takes into account the nonlinearity of the life and inputs the operating range of the SOC for the optimal design. The detailed calculation process will be presented in a separate paper.



This work focuses on using the full potential of PV inverters in order to improve the efficiency of low voltage networks. More specifically, the  independent per-phase control capability of PV three-phase four-wire inverters, which are able to inject different active and reactive powers in each phase, in order to reduce the system phase unbalance is considered.  This new operational procedure is analyzed by raising an optimization problem which uses a very accurate modelling of European low voltage networks.


We provide here a simple but fully functional platform for making peer to peer energy trading using the tobalaba network with block chain


Smart Grids (SG) are a novel paradigm introduced for optimizing the management of the power generation, transmission, distribution and consumption. A SG system can efficiently work only if all the components are connected through a communication network able to satisfy the SG applications requirements. Wireless communications are the most appropriate candidates for handling SG requirements due to their flexibility.