smart grids
Electric Vehicles Charging Station with Photovoltaic Panels
This dataset contains the model and simulation output results in Matlab/Simulink of a three-phase grid-connected charging station with PV panels for electric vehicles realized in a work submitted to the 13th IEEE International Conference and Exposition on Electrical and Power Engineering EPEi 2024, Iasi, Romania, October 17-19, 2024 (https://www.epe.tuiasi.ro/).
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The IEEE 24 bus system is modelled in Digsilent’s Power factory, and normal operating data points are generated under quasi dynamic simulation and N-2 contingencies. An optimization problem to generate false data injection attack vectors are then modelled using MATLAB. This data contains normal, contingency and attack data points for the necessary variables in a power network. The attack data has 5 parts, with each part generated by a different type of attack.
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Following the success of the previous editions at WCCI 2018 (Rio de Janeiro, Brazil) and CEC/GECCO 2019 (New Zealand and Prague, Czechia) we are launching a more challenging algorithm competition at major international conferences in the field of computational intelligence. This WCCI & GECCO 2020 competition proposes two testbeds in the energy domain:
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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.
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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.
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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.
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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.
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This dataset contains heavy-machinery data from the Brazilian industrial sector. The data was collected in a poultry feed factory located in the state of Minas Gerais, Brazil. Its process can be summarized to creating pellets of ration for poultry from corn or soybeans and added nutrients. The factory produces at fullscale over the entire year, thus it has well-behaved usage patterns at any time. It operates from Mondays through Fridays (and occasionally on Saturdays, in case production is below the monthly target) on a daily three-turn shift from 10:00 PM to 05:00 PM.
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The distributed generation, along with the deregulation of the Smart Grid, have created a great concern on Power Quality (PQ), as it has a direct impact on utilities and customers, as well as effects on the sinusoidal signal of the power line. The a priori unknown features of the distributed energy resources (DER) introduce non-linear behaviours in loads associated to a variety of PQ disturbances.
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