AI -based dynamic plug -in battery energy storage system control: vehicle forward road to the grid
A group of researchers, Teesside University, Mudhafar Al-Saadi and Michael Short pursue sustainable and efficient energy solutions in pursuit of sustainable and efficient energy solutions. It proposed an innovative multi-AI control system for plug-in batteries in DC micro-power grids. These methods and experiments are published in the “Journal Battery” and several IEEE papers and articles. Overview a promising method enhances the management of power storage flow in the microcyllar grid, especially the dynamic vehicle to the grid (V2G) Challenge application brought by charging.
Energy is the foundation of life creation and maintenance. The main motivation behind this study is to urgently need to be sustainable and low -emission energy system applications in industry, society and transportation. These systems aims to solve climate change and fossil fuel scarcity through the decarbolization, digital and decentralization of the power system. Traditional power flow management technology usually lacks the dynamic and decentralized nature of the modern power distribution network. The innovative methods proposed by Professor AL-SAADI and Short provides solutions by using multiple enhanced learning (MARL). This is an emerging AI-based technology. It can improve automatic decision-making by learning complex input and output relationships to improve automatic decision-making to improve Efficiency and reliability DC micro -power storage.
Mudhafar Al-SAADI explained: “The impact of DC infrastructure on the control of power storage flow in micro-grids has attracted great attention. Our research aims to solve the potential losses of synchronous synchronization and subsequent control of control stability.”
Researchers emphasize that effective current management is essential for integrating renewable energy and ensuring the sustainability of decentralized power networks. One of the main challenges in this field is the accurate synchronization of the battery charging and discharge cycle, which is usually damaged under actual environmental conditions. This is due to continuous high load changes and heterogeneity and degradation of battery, so it is uncertain that dynamic dynamics are certain Insert/insertion insertion and removal of battery elements, infrastructure impact and environment (temperature) impact. The proposed multi -gene -based control system can compensate these changes in real time to ensure a balanced and stable power flow.
In their experiments, researchers showed significant improvements in various performance indicators. The proposed system realizes reduction time, enhanced the output voltage balance, reduced power consumption, and increased power flow balance. These results emphasize the effectiveness of the proposed control system in the real world. In the real world, dynamic load conditions and different infrastructure effects are common.
Professor SHORT said: “In a larger, aggregated storage system, the plug -in/disassembly/disassembly of the plug -in. Real -time compensation for DC infrastructure is the key factor of our successful control method.” The impact of DC infrastructure and battery type without preliminary estimation of key parameters need to ensure the reliability and sustainability of the micro grid.
“Electric vehicle batteries and chargers have proposed key storage assets to ensure that the grid balance and peak shaving and demand response applications of the grid (V2G) of the vehicle to the grid (V2G) can help decarbons. Our method can improve V2G performance And prevent the EV battery capacity and life unnecessary degradation.
The research team adopted a combination of simulation and hardware research to verify its recommended system. They use realistic conditions, including the long -term continuous changes of dynamic switching of load demand and heterogeneous battery connection to test the robustness and effectiveness of its control system.
In short, the multi-gene-based control system proposed by Professor Al-Saadi and SHORT represents a significant improvement in the management of power flow management in the dynamic DC micro-power grid. By solving the challenges brought by dynamic load conditions and infrastructure changes, this innovative method provides a practical and effective solution for the modern power distribution network. The discovery of this study has paved the way for further research and development of decentralized energy systems, which has made the efforts of sustainable and low -emission energy solutions for global efforts.
Journal reference
Al-SAADI, M. , & Short, m. (2023). Multi -gene control of plug -in batteries in DC micro grids based on infrastructure compensation. Battery, 9 (12), 597. https://doi.org/10.3390/batteries9120597
SHORT, M. And Al-SAADI, M. (2024) “The instantaneous recycling of energy storage balance in DC micro -grid based on MARL -based power control”. In: Collection 10TH IEEE/IFAC International Control, Decision and Information Technology Conference (Codit 2024), Malta Valetta, July 2024. “In the balance adjustment of heterogeneous bass”. In: the third papers setroad IEEE international signal, control and communication conference (SCC), Tunisia Hammamet, p. 1-6, December 1, 2023
About the author
Michael Schott It is the calculation of the British Teesside University, a professor of control engineering and system informatics in the School of Engineering and Digital Technology. He is also a guest professor at India’s Vit Chennai. He has a degree in electronics and electrical engineering (1999, Sandlan) and Dr. AI and Robotics (Sandlan). Michael’s research interests include all aspects of control engineering and system information, and are used in smart energy systems and manufacturing/process industries. He is Pi or CO-I. Of the 14 completed or undergoing funding research and innovation projects, he wrote more than 190 censorship publications in international conferences and journals. He has supervised ten doctorate degrees and won eight best paper awards and IET, IEEE and HEA researchers.
Mr. Al-Saadi It is a student of the last year of the last year of “optimizing micro -grid energy control and management energy control and management” under the supervision of Professor Michael Short in the School of Engineering and Digital Technology. Mr. Al-SaDi has a bachelor’s degree in electrical engineering from the University of Baghdad, and has obtained electrical engineering honors from Leeds Metropolitan University. He also has a master’s degree in control and electronic engineering by the British Teesside University. He wrote more than 10 censorship publications in international conferences and journals, and is currently waiting for his doctorate degree.
