Development and implementation of a LabVIEW based SCADA system for a meshed multi-terminal VSC-HVDC grid scaled platform

This project is oriented to the development of a Supervisory, Control and Data Acquisition (SCADA) software to control and supervise electrical variables from a scaled platform that represents a meshed HVDC grid employing National Instruments hardware and LabVIEW logic environment. The objective is to obtain real time visualization of DC and AC electrical variables and a lossless data stream acquisition. The acquisition system hardware elements have been configured, tested and installed on the grid platform. The system is composed of three chassis, each inside of a VSC terminal cabinet, with integrated Field-Programmable Gate Arrays (FPGAs), one of them connected via PCI bus to a local processor and the rest too via Ethernet through a switch. Analogical acquisition modules were A/D conversion takes place are inserted into the chassis. A personal computer is used as host, screen terminal and storing space. There are two main access modes to the FPGAs through the real time system. It has been implemented a Scan mode VI to monitor all the grid DC signals and a faster FPGA access mode VI to monitor one converter AC and DC values. The FPGA application consists of two tasks running at different rates and a FIFO has been implemented to communicate between them without data loss. Multiple structures have been tested on the grid platform and evaluated, ensuring the compliance of previously established specifications, such as sampling and scanning rate, screen refreshment or possible data loss. Additionally a turbine emulator was implemented and tested in Labview for further testing

Real-Time Hardware-In-the-Loop Testing of IEC 61850 GOOSE based Logically Selective Adaptive Protection of AC Microgrid

The real-time (RT) hardware-in-the-loop (HIL) simulation-based testing is getting popular for power systems and power electronics applications. The HIL testing provides the interactive environment between the actual power system components like control and protection devices and simulated power system networks including different communication protocols. Therefore, the results of the RT simulation and HIL testing before the actual implementation in the field are generally more acceptable than offline simulations. This paper reviews the HIL testing methods and applications in the recent literature and presents a step-by-step documentation of a new HIL testing setup for a specific case study. The case study evaluates improved version of previously proposed communication-dependent logically selective adaptive protection algorithm of AC microgrids using the real-time HIL testing of IEC 61850 generic object-oriented substation event (GOOSE) protocol. The RT model of AC microgrid including the converter-based distributed energy resources and battery storage along with IEC 61850 GOOSE protocol implementation is created in MATLAB/Simulink and RT-LAB software using OPAL-RT simulator platform. The Ethernet switch acts as IEC 61850 station bus for exchanging GOOSE Boolean signals between the RT target and the actual digital relay. The evaluation of the round-trip delay using the RT simulation has been performed. It is found that the whole process of fault detection, isolation and adaptive setting using Ethernet communication is possible within the standard low voltage ride through curve maintaining the seamless transition to the islanded mode. The signal monitoring inside the relay is suggested to avoid false tripping of the relay.©2021 Institute of Electrical and Electronics Engineers. This work is licensed under a Creative Commons Attribution 4.0 License. For more information, see https://creativecommons.org/licenses/by/4.0/This work was mainly carried out in the SolarX research project funded by the Business Finland under Grant No. 6844/31/2018. Some part of this work was carried out during the VINPOWER research project funded by the European Regional Development Fund (ERDF), Project No. A73094. The financial support provided through these projects is greatly acknowledged.fi=vertaisarvioitu|en=peerReviewed

Networked control system with MANET communication and AODV routing

The industries are presently exploring the use of wired and wireless systems for control, automation, and monitoring. The primary benefit of wireless technology is that it reduces the installation cost, in both money and labor terms, as companies already have a significant investment in wiring. The research article presents the work on the analysis of Mobile Ad Hoc Network (MANET) in a wireless real-time communication medium for a Networked Control System (NCS), and determining whether the simulated behavior is significant for a plant or not. The behavior of the MANET is analyzed for Ad-hoc on-demand distance vector routing (AODV) that maintenances communication among 150 nodes for NCS. The simulation is carried out in Network Simulator (NS2) software with different nodes cluster to estimate the network throughput, end-to-end delay, packet delivery ratio (PDR), and control overhead. The benefit of MANET is that it has a fixed topology, which permits flexibility since mobile devices may be used to construct ad-hoc networks anywhere, scalability because more nodes can be added to the network, and minimal operating expenses in that no original infrastructure needs to be developed. AODV routing is a flat routing system that does not require central routing nodes. As the network grows in size, the network can be scaled to meet the network design and configuration requirements. AODV is flexible to support different configurations and topological nodes in dynamic networks because of its versatility. The advantage of such network simulation and routing behavior provides the future direction for the researchers who are working towards the embedded hardware solutions for NCS, as the hardware complexity depends on the delay, throughput, and PDR

Co-simulation techniques based on virtual platforms for SoC design and verification in power electronics applications

En las últimas décadas, la inversión en el ámbito energético ha aumentado considerablemente. Actualmente, existen numerosas empresas que están desarrollando equipos como convertidores de potencia o máquinas eléctricas con sistemas de control de última generación. La tendencia actual es usar System-on-chips y Field Programmable Gate Arrays para implementar todo el sistema de control. Estos dispositivos facilitan el uso de algoritmos de control más complejos y eficientes, mejorando la eficiencia de los equipos y habilitando la integración de los sistemas renovables en la red eléctrica. Sin embargo, la complejidad de los sistemas de control también ha aumentado considerablemente y con ello la dificultad de su verificación. Los sistemas Hardware-in-the-loop (HIL) se han presentado como una solución para la verificación no destructiva de los equipos energéticos, evitando accidentes y pruebas de alto coste en bancos de ensayo. Los sistemas HIL simulan en tiempo real el comportamiento de la planta de potencia y su interfaz para realizar las pruebas con la placa de control en un entorno seguro. Esta tesis se centra en mejorar el proceso de verificación de los sistemas de control en aplicaciones de electrónica potencia. La contribución general es proporcionar una alternativa a al uso de los HIL para la verificación del hardware/software de la tarjeta de control. La alternativa se basa en la técnica de Software-in-the-loop (SIL) y trata de superar o abordar las limitaciones encontradas hasta la fecha en el SIL. Para mejorar las cualidades de SIL se ha desarrollado una herramienta software denominada COSIL que permite co-simular la implementación e integración final del sistema de control, sea software (CPU), hardware (FPGA) o una mezcla de software y hardware, al mismo tiempo que su interacción con la planta de potencia. Dicha plataforma puede trabajar en múltiples niveles de abstracción e incluye soporte para realizar co-simulación mixtas en distintos lenguajes como C o VHDL. A lo largo de la tesis se hace hincapié en mejorar una de las limitaciones de SIL, su baja velocidad de simulación. Se proponen diferentes soluciones como el uso de emuladores software, distintos niveles de abstracción del software y hardware, o relojes locales en los módulos de la FPGA. En especial se aporta un mecanismo de sincronizaron externa para el emulador software QEMU habilitando su emulación multi-core. Esta aportación habilita el uso de QEMU en plataformas virtuales de co-simulacion como COSIL. Toda la plataforma COSIL, incluido el uso de QEMU, se ha analizado bajo diferentes tipos de aplicaciones y bajo un proyecto industrial real. Su uso ha sido crítico para desarrollar y verificar el software y hardware del sistema de control de un convertidor de 400 kVA

Embedded Parallel Computing Platform for Real-Time Recognition of Power Quality Disturbance Based on Deep Network

Systems powered by scattered sustainable power sources are highly susceptible to disturbances in the quality of power. Power Quality Disturbances (PQD) signals can degrade the functionality of grid-powered appliances. The older techniques for recognizing thePQD signals involve feature extraction. Manual analysis needs to set up a digital signal processor platform, which may lead to a time-complex process and errors in accuracy. Real-time PQD (RPQD) recognition techniques have advanced Embedded Parallel Computing Platform(EPCP), various signal processing methods, artificial intelligence, and Deep Network (DN) methodologies to recognize RPQD signals successfully in real-time scenarios using EPCP-RPQD-DN. Initially, the proposed algorithm implements hybridized Deep Belief Network and Long Short-Term Memory (DBN-LSTM) to accurately recognize the real-time PQD signals. Secondly, the DBN module maximizes the input signal features for the generation of PQD in a fixed period by training phase directly from raw PQD input signals and forwards it to the LSTM module. Third, in LSTM, the time series nature of PQD signals is easily analyzed using three layers, allowing it to run on the EPCP model. The PQD sample signals are employed to train the DBN in a central monitoring server. A series of PQD signals generated by the EPCP simulation environment is carried out to validate the effectiveness of the EPCP-RPQD-DN approach. Real-time simulation of electromagnetic fault conditions in the power system by Real Time Digital Simulator (RTDS) hardware. Experimental evaluation shows that DN learning improves accuracy rate, reduces computational overhead, and minimizes error rate compared to existing approaches

A two teraflop swarm

© 2018 Jones, Studley, Hauert and Winfield. We introduce the Xpuck swarm, a research platform with an aggregate raw processing power in excess of two teraflops. The swarm uses 16 e-puck robots augmented with custom hardware that uses the substantial CPU and GPU processing power available from modern mobile system-on-chip devices. The augmented robots, called Xpucks, have at least an order of magnitude greater performance than previous swarm robotics platforms. The platform enables new experiments that require high individual robot computation and multiple robots. Uses include online evolution or learning of swarm controllers, simulation for answering what-if questions about possible actions, distributed super-computing for mobile platforms, and real-world applications of swarm robotics that requires image processing, or SLAM. The teraflop swarm could also be used to explore swarming in nature by providing platforms with similar computational power as simple insects. We demonstrate the computational capability of the swarm by implementing a fast physics-based robot simulator and using this within a distributed island model evolutionary system, all hosted on the Xpucks

Towards the Evolution of Novel Vertical-Axis Wind Turbines

Renewable and sustainable energy is one of the most important challenges currently facing mankind. Wind has made an increasing contribution to the world's energy supply mix, but still remains a long way from reaching its full potential. In this paper, we investigate the use of artificial evolution to design vertical-axis wind turbine prototypes that are physically instantiated and evaluated under approximated wind tunnel conditions. An artificial neural network is used as a surrogate model to assist learning and found to reduce the number of fabrications required to reach a higher aerodynamic efficiency, resulting in an important cost reduction. Unlike in other approaches, such as computational fluid dynamics simulations, no mathematical formulations are used and no model assumptions are made.Comment: 14 pages, 11 figure