Numerical and experimental study of an active control logic for modifying the acoustic performance of single-layer panels

2021 ◽  
pp. 116608
Author(s):  
Francesco Ripamonti ◽  
Anthony Giampà ◽  
Riccardo Giona ◽  
Ling Liu ◽  
Roberto Corradi
Energies ◽  
2021 ◽  
Vol 14 (15) ◽  
pp. 4650
Author(s):  
Martha N. Acosta ◽  
Francisco Gonzalez-Longatt ◽  
Juan Manuel Roldan-Fernandez ◽  
Manuel Burgos-Payan

The massive integration of variable renewable energy (VRE) in modern power systems is imposing several challenges; one of them is the increased need for balancing services. Coping with the high variability of the future generation mix with incredible high shares of VER, the power system requires developing and enabling sources of flexibility. This paper proposes and demonstrates a single layer control system for coordinating the steady-state operation of battery energy storage system (BESS) and wind power plants via multi-terminal high voltage direct current (HVDC). The proposed coordinated controller is a single layer controller on the top of the power converter-based technologies. Specifically, the coordinated controller uses the capabilities of the distributed battery energy storage systems (BESS) to store electricity when a logic function is fulfilled. The proposed approach has been implemented considering a control logic based on the power flow in the DC undersea cables and coordinated to charging distributed-BESS assets. The implemented coordinated controller has been tested using numerical simulations in a modified version of the classical IEEE 14-bus test system, including tree-HVDC converter stations. A 24-h (1-min resolution) quasi-dynamic simulation was used to demonstrate the suitability of the proposed coordinated control. The controller demonstrated the capacity of fulfilling the defined control logic. Finally, the instantaneous flexibility power was calculated, demonstrating the suitability of the proposed coordinated controller to provide flexibility and decreased requirements for balancing power.


1984 ◽  
Vol 108 (1-2) ◽  
pp. 155-172 ◽  
Author(s):  
V.K. Gairola ◽  
H. Kern

2018 ◽  
Vol 59 (3) ◽  
Author(s):  
Dan Hlevca ◽  
Patrick Gilliéron ◽  
Francesco Grasso

Author(s):  
Alexander N. BUSYGIN ◽  
Andrey N. BOBYLEV ◽  
Alexey A. GUBIN ◽  
Alexander D. PISAREV ◽  
Sergey Yu. UDOVICHENKO

This article presents the results of a numerical simulation and an experimental study of the electrical circuit of a hardware spiking perceptron based on a memristor-diode crossbar. That has required developing and manufacturing a measuring bench, the electrical circuit of which consists of a hardware perceptron circuit and an input peripheral electrical circuit to implement the activation functions of the neurons and ensure the operation of the memory matrix in a spiking mode. The authors have performed a study of the operation of the hardware spiking neural network with memristor synapses in the form of a memory matrix in the mode of a single-layer perceptron synapses. The perceptron can be considered as the first layer of a biomorphic neural network that performs primary processing of incoming information in a biomorphic neuroprocessor. The obtained experimental and simulation learning curves show the expected increase in the proportion of correct classifications with an increase in the number of training epochs. The authors demonstrate generating a new association during retraining caused by the presence of new input information. Comparison of the results of modeling and an experiment on training a small neural network with a small crossbar will allow creating adequate models of hardware neural networks with a large memristor-diode crossbar. The arrival of new unknown information at the input of the hardware spiking neural network can be related with the generation of new associations in the biomorphic neuroprocessor. With further improvement of the neural network, this information will be comprehended and, therefore, will allow the transition from weak to strong artificial intelligence.


2013 ◽  
Author(s):  
Pasquale Ambrosio ◽  
Francesco Braghin ◽  
Ferruccio Resta ◽  
Francesco Ripamonti

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