Ayda Demir | Texas Tech University (original) (raw)
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Norwegian University of Science and Technology
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Papers by Ayda Demir
Sustainability, Mar 5, 2024
This article is an open access article distributed under the terms and conditions of the Creative... more This article is an open access article distributed under the terms and conditions of the Creative Commons Attribution (CC BY
This study presents a deep learning-assisted operation model for interconnected autonomous networ... more This study presents a deep learning-assisted operation model for interconnected autonomous networks based on state logic to address dynamic local and global objectives simultaneously. The interconnected independent power systems depend on each other through common power pool sharing to maintain a reliable power delivery to the end users. The usual practice is to pursue a global objective for the entire interconnected systems. However, intermittent energy resources create unique local operation challenges for each system, compelling their operators to solve dynamic local objectives in addition to the global objective to enhance their operations. Consequently, a novel distributed operation approach incorporating Deep Learning and Mixed Integer Non-Linear Programing is formulated in this study to address both dynamic local and global objectives for the entire system. The resulting model is solved in two stages considering each system’s state logic, demand response, load management, and...
2023 IEEE Power and Energy Conference at Illinois (PECI)
2022 IEEE International Conference on Big Data (Big Data)
2022 IEEE 46th Annual Computers, Software, and Applications Conference (COMPSAC)
Sustainability, Mar 5, 2024
This article is an open access article distributed under the terms and conditions of the Creative... more This article is an open access article distributed under the terms and conditions of the Creative Commons Attribution (CC BY
This study presents a deep learning-assisted operation model for interconnected autonomous networ... more This study presents a deep learning-assisted operation model for interconnected autonomous networks based on state logic to address dynamic local and global objectives simultaneously. The interconnected independent power systems depend on each other through common power pool sharing to maintain a reliable power delivery to the end users. The usual practice is to pursue a global objective for the entire interconnected systems. However, intermittent energy resources create unique local operation challenges for each system, compelling their operators to solve dynamic local objectives in addition to the global objective to enhance their operations. Consequently, a novel distributed operation approach incorporating Deep Learning and Mixed Integer Non-Linear Programing is formulated in this study to address both dynamic local and global objectives for the entire system. The resulting model is solved in two stages considering each system’s state logic, demand response, load management, and...
2023 IEEE Power and Energy Conference at Illinois (PECI)
2022 IEEE International Conference on Big Data (Big Data)
2022 IEEE 46th Annual Computers, Software, and Applications Conference (COMPSAC)