Prof. Dr. Josep M. Guerrero
Aalborg University, Denmark
Josep M. Guerrero since 2011, he has been a Full Professor with the Department of Energy Technology, Aalborg University, Denmark, where he is responsible for the Microgrid Research Program. He is a guest Professor at the Chinese Academy of Science and the Nanjing University of Aeronautics and Astronautics; chair Professor in Shandong University; distinguished guest Professor in Hunan University; and a visiting professor fellow at Aston University, UK.
Title: Neuroscience Inspiration for Biological and Electrical Space Microgrids
Abstract: This talk will begin by introducing the control of microgrids, the parallelisms with the human brain and the research for possible sources of inspiration in the last frontiers of neuroscience. Then, control in electric power systems of satellites and space platforms will be presented, showing approaches that are extended from terrestrial microgrids and explaining the differences and challenges when it comes to apply them out in space. Further, multi-microgrid systems will be discussed for moon craters in future lunar manmade bases. Finally, the extension from the hierarchical control of microgrids to bioastronautics in the control of closed ecological systems to support with oxygen, water, and food to the astronauts and thus creating new ecosystems for the moon and future mars bases.
Prof. Dr. Ajay Roy
Lovely Professional University, India
Ajay Roy is currently associated with Lovely Professional University as Professor with more than twelve years of experience in academics. He received the Engineering degree from West Bengal University of Technology and the Ph.D. degree in electronics from Dr. B R Ambedkar National Institute of Technology, Jalandhar, India. His area of expertise includes embedded systems, robotics, wireless sensor networks, internet of things and machine learning. He has published more than forty research papers in referred journals/conferences. He has been honoured as keynote speakers and session chair to international/national conferences, faculty development programs, workshops, and webinars. He has guided 3 PhD scholars and currently guiding 9 PhD scholars. He can be contacted at email: email@example.com
Title: Real-Time Monitoring of Evaluation Landslide on IoT Platform using LoRA
Abstract:In the context of an early warning system for landslides, monitoring of prone areas is a longlasting process, little human intervention, and a resource less environment. Data changes in the monitoring area may be noticed in many days, months, or years depending on the weather characteristics. Therefore, a frequent and large amount of data of monitored area is not required to send on a cloud server. Moreover, Long-range communication provided comprehensive spectrum communication protocol and low power consumption with fewer data rates. Over the advantage of LoRa technology, we designed a customized sensor node and gateway node to monitor the changes periodically with low energy power consumption. We evaluated the distinct metrics of spreading factor, sensitivity, time-on-air, energy consumption, link budget, and battery life of sensor and gateway nodes. Finally, this study concludes with challenges faced in real-time in which the sensor data received via a customized sensor node and gateway on the cloud server
Assoc. Prof. Dr. Yolanda Vidal
Universitat Politècnica de Catalunya, Spain
Yolanda Vidal received her B.E. degree in Mathematics in 1999 and her Ph.D. degree in Applied Mathematics in 2005 from the Polytechnic University of Catalonia (UPC), Barcelona, Spain. Since 2001, she has been with the Department of Mathematics and the Barcelona East School of Engineering (EEBE), at Universitat Politècnica de Catalunya, where she is currently an Associate Professor with the Control, Data, and Artificial Intelligence research group (CoDAlab). Her research interests include structural health monitoring (SHM), condition monitoring (CM), and fault diagnosis (FD), with an emphasis on their specific application to wind turbines. Dr. Vidal is an IEEE Senior member and serves as an Editorial Board Member for international journals, such as Mathematics, Sensors, Energies, Frontiers in the Built Environment, and Frontiers in Energy Research. Dr. Vidal is the author of 50 journal articles, 18 competitive projects, 15 book chapters, 7 books, 1 invention patent, and more than 100 conference articles.
Title: Artificial Intelligence for Wind Turbine Condition Monitoring and Structural Health Monitoring
Abstract:To remain competitive, wind turbines (WTs) must be reliable machines with efficient and effective maintenance strategies. Thus, it is of paramount importance that the wind industry moves from corrective and preventive maintenance to the so-called predictive maintenance (scheduled as needed based on the asset condition). On the one hand, this talk addresses WT condition monitoring methodologies based on SCADA data. WTs generate a wealth of SCADA data from a variety of sensors, which can be effectively used to enable fault diagnosis strategies. Data-driven techniques, based on machine or deep learning, are particularly promising in this field. Furthermore, this approach is cost-efficient and readily available as no extra equipment needs to be installed in the wind turbine. On the other hand, this talk addresses the structural health monitoring (SHM) of WTs. The main purpose is to detect, locate, and characterize damage, so that maintenance operations can be performed in due time. The standard SHM approach based on guided waves (where the input excitation is known and imposed to the structure and then the output vibration is measured) cannot be straightforward applied as the excitation is not known (wind, waves, currents) neither can be imposed. A new paradigm, a vibration-response-only methodology, is developed that assumes unknown input excitations and that only the vibration response is measurable by means of different sensors.