B. Dindar, Can Berk Saner, H. K. Çakmak, V. Hagenmeyer
Applied Energy
TL;DR A novel ML-based approach represents distribution system constraints using models trained on non-sensitive data, enabling the TSO to solve OPF and dispatch flexibility-providing units in a single communication round without exposing sensitive grid data.
B. Dindar, Can Berk Saner, H. K. Çakmak, V. Hagenmeyer
Applied Energy
TL;DR A novel ML-based approach represents distribution system constraints using models trained on non-sensitive data, enabling the TSO to solve OPF and dispatch flexibility-providing units in a single communication round without exposing sensitive grid data.
Can Berk Saner
2025 IEEE PES GTD Grand International Conference and Exposition Asia (GTD Asia)
TL;DR An online EV charging algorithm that considers discrete charging rates and phase current unbalance by formulating the problem as an integer polymatroid maximization with guaranteed global optimality and polynomial-time complexity.
Can Berk Saner
2025 IEEE PES GTD Grand International Conference and Exposition Asia (GTD Asia)
TL;DR An online EV charging algorithm that considers discrete charging rates and phase current unbalance by formulating the problem as an integer polymatroid maximization with guaranteed global optimality and polynomial-time complexity.
B. Dindar, Can Berk Saner, H. K. Çakmak, V. Hagenmeyer
arXiv
TL;DR This paper proposes a novel AC optimal power flow (OPF)-based method to construct a three-dimensional PQV-FOR, explicitly accounting for voltage variability and diverse flexibility-providing unit (FPU) characteristics and introduces an implicit polynomial fitting approach to analytically represent the FOR.
B. Dindar, Can Berk Saner, H. K. Çakmak, V. Hagenmeyer
arXiv
TL;DR This paper proposes a novel AC optimal power flow (OPF)-based method to construct a three-dimensional PQV-FOR, explicitly accounting for voltage variability and diverse flexibility-providing unit (FPU) characteristics and introduces an implicit polynomial fitting approach to analytically represent the FOR.
B. Dindar, Can Berk Saner, H. K. Çakmak, V. Hagenmeyer
arXiv
TL;DR A machine learning (ML)-based method in which the technical constraints of the distribution system (DS) are represented by ML models trained exclusively on non-sensitive data, preventing the transfer of sensitive information between stakeholders is prevented.
B. Dindar, Can Berk Saner, H. K. Çakmak, V. Hagenmeyer
arXiv
TL;DR A machine learning (ML)-based method in which the technical constraints of the distribution system (DS) are represented by ML models trained exclusively on non-sensitive data, preventing the transfer of sensitive information between stakeholders is prevented.
B. Dindar, Can Berk Saner, H. K. Çakmak, V. Hagenmeyer
Sustainable Energy, Grids and Networks
TL;DR A multi-agent AC optimal power flow framework enhanced with machine learning enables privacy-preserving interoperability through effective dataset generation and accurate feasible-region mapping.
B. Dindar, Can Berk Saner, H. K. Çakmak, V. Hagenmeyer
Sustainable Energy, Grids and Networks
TL;DR A multi-agent AC optimal power flow framework enhanced with machine learning enables privacy-preserving interoperability through effective dataset generation and accurate feasible-region mapping.
I. Canyakmaz, Can Berk Saner, A. Varvitsiotis
IEEE PES Innovative Smart Grid Technologies Europe (ISGT Europe)
TL;DR This work introduces the application of Physics-Informed Neural Networks (PINNs) to develop surrogate models that accurately replicate power system dynamics without exposing sensitive data, enabling privacy-preserving model sharing and system-wide dynamic simulations in power systems.
I. Canyakmaz, Can Berk Saner, A. Varvitsiotis
IEEE PES Innovative Smart Grid Technologies Europe (ISGT Europe)
TL;DR This work introduces the application of Physics-Informed Neural Networks (PINNs) to develop surrogate models that accurately replicate power system dynamics without exposing sensitive data, enabling privacy-preserving model sharing and system-wide dynamic simulations in power systems.
B. Dindar, Can Berk Saner, D. Y. Polat, H. K. Çakmak, V. Hagenmeyer
IEEE PES Innovative Smart Grid Technologies Europe (ISGT Europe)
TL;DR A machine-learning (ML)-based method to incorporate DGs located within the distribution system (DS) into dispatch decisions, adhering to data privacy by mitigating the exchange of sensitive data, such as system topology and demand profiles, between TSOs and DSOs is proposed.
B. Dindar, Can Berk Saner, D. Y. Polat, H. K. Çakmak, V. Hagenmeyer
IEEE PES Innovative Smart Grid Technologies Europe (ISGT Europe)
TL;DR A machine-learning (ML)-based method to incorporate DGs located within the distribution system (DS) into dispatch decisions, adhering to data privacy by mitigating the exchange of sensitive data, such as system topology and demand profiles, between TSOs and DSOs is proposed.
Can Berk Saner, J. Saha, D. Srinivasan
IEEE PES Innovative Smart Grid Technologies Europe (ISGT Europe)
TL;DR A bilevel programming framework models EV charge curves using piecewise linear regression and integrates them into mixed-integer scheduling to enable efficient and fair fast charging under capacity constraints.
Can Berk Saner, J. Saha, D. Srinivasan
IEEE PES Innovative Smart Grid Technologies Europe (ISGT Europe)
TL;DR A bilevel programming framework models EV charge curves using piecewise linear regression and integrates them into mixed-integer scheduling to enable efficient and fair fast charging under capacity constraints.
Can Berk Saner, J. Saha, D. Srinivasan
IEEE Transactions on Intelligent Transportation Systems
TL;DR A lexicographic and social welfare theory-inspired EV charging scheduling framework is developed for modular fast charging stations to achieve high quality-of-service under discrete module allocation, charge curve nonlinearity, and ramp rate limits.
Can Berk Saner, J. Saha, D. Srinivasan
IEEE Transactions on Intelligent Transportation Systems
TL;DR A lexicographic and social welfare theory-inspired EV charging scheduling framework is developed for modular fast charging stations to achieve high quality-of-service under discrete module allocation, charge curve nonlinearity, and ramp rate limits.
Can Berk Saner, A. Trivedi, D. Srinivasan
IEEE Transactions on Intelligent Transportation Systems
TL;DR A multi-module optimization framework is proposed for integrated planning and operation of electric bus shuttle fleets, enabling coordinated vehicle scheduling, charger deployment, charging planning, and battery degradation minimization under uncertainty.
Can Berk Saner, A. Trivedi, D. Srinivasan
IEEE Transactions on Intelligent Transportation Systems
TL;DR A multi-module optimization framework is proposed for integrated planning and operation of electric bus shuttle fleets, enabling coordinated vehicle scheduling, charger deployment, charging planning, and battery degradation minimization under uncertainty.
Your Name, James Wang, Some Other Name, John Doe
International Conference on Machine Learning (ICML) 2024 Spotlight
TL;DR Photo by Pineapple Supply Co. on Unsplash. Please put a tldr (too-long-didnt-read, 1~2 sentences) of your publication here. It is not recommended to put the actual abstract here because it is usually too long to fit in. $\LaTeX$ is supported. $a=b+c$.
Your Name, James Wang, Some Other Name, John Doe
International Conference on Machine Learning (ICML) 2024 Spotlight
TL;DR Photo by Pineapple Supply Co. on Unsplash. Please put a tldr (too-long-didnt-read, 1~2 sentences) of your publication here. It is not recommended to put the actual abstract here because it is usually too long to fit in. $\LaTeX$ is supported. $a=b+c$.
B. Dindar, Can Berk Saner, H. K. Çakmak, V. Hagenmeyer
2023 IEEE PES 15th Asia-Pacific Power and Energy Engineering Conference (APPEEC)
TL;DR A Machine Learning-Based Privacy-Preserving Optimal Power Flow (MLB-PP-OPF) framework is introduced, which enables the seamless inclusion of DGs at the distribution level in optimal power flow calculations, all while adhering to the operational limits of both systems and maintaining data privacy.
B. Dindar, Can Berk Saner, H. K. Çakmak, V. Hagenmeyer
2023 IEEE PES 15th Asia-Pacific Power and Energy Engineering Conference (APPEEC)
TL;DR A Machine Learning-Based Privacy-Preserving Optimal Power Flow (MLB-PP-OPF) framework is introduced, which enables the seamless inclusion of DGs at the distribution level in optimal power flow calculations, all while adhering to the operational limits of both systems and maintaining data privacy.
Can Berk Saner, A. Trivedi, A. Sharma, D. Srinivasan
IEEE PES Asia-Pacific Power and Energy Engineering Conference (APPEEC)
TL;DR A neural network-based battery degradation model is embedded into a mixed-integer EV charging scheduler to significantly reduce operational costs while maintaining high computational efficiency.
Can Berk Saner, A. Trivedi, A. Sharma, D. Srinivasan
IEEE PES Asia-Pacific Power and Energy Engineering Conference (APPEEC)
TL;DR A neural network-based battery degradation model is embedded into a mixed-integer EV charging scheduler to significantly reduce operational costs while maintaining high computational efficiency.
Can Berk Saner, J. Saha, A. Sharma, D. Srinivasan
2023 IEEE PES 15th Asia-Pacific Power and Energy Engineering Conference (APPEEC)
TL;DR Extensions of classical heuristic charging policies are developed for modular fast charging stations with discrete module allocation, enabling improved charge fairness and quality-of-service under non-linear EV charge curves.
Can Berk Saner, J. Saha, A. Sharma, D. Srinivasan
2023 IEEE PES 15th Asia-Pacific Power and Energy Engineering Conference (APPEEC)
TL;DR Extensions of classical heuristic charging policies are developed for modular fast charging stations with discrete module allocation, enabling improved charge fairness and quality-of-service under non-linear EV charge curves.
Can Berk Saner, J. Saha, D. Srinivasan
IEEE Transactions on Intelligent Transportation Systems
TL;DR A charge curve and BMS-aware fast charging scheduling framework based on lexicographic mixed-integer optimization achieves improved fairness and quality of service under heterogeneous customer behavior and operational uncertainty.
Can Berk Saner, J. Saha, D. Srinivasan
IEEE Transactions on Intelligent Transportation Systems
TL;DR A charge curve and BMS-aware fast charging scheduling framework based on lexicographic mixed-integer optimization achieves improved fairness and quality of service under heterogeneous customer behavior and operational uncertainty.
Charles Green*, John Doe*, Robert White, James Wang, Your Name# (* equal contribution, # corresponding author)
International Conference on Learning Representations (ICLR) 2023
TL;DR Photo by Dessy Dimcheva on Unsplash. Please keep the description of your publication as brief as possible. 1~2 sentences is ideal. Otherwise, it will look too noisy. This is a counterexample to show how the publication will look like when the abstract is too long. The tangerine is a type of citrus fruit that is orange in color, that is considered either a variety of Citrus reticulata, the mandarin orange, or a closely related species, under the name Citrus tangerina, or yet as a hybrid (Citrus × tangerina) of mandarin orange varieties, with some pomelo contribution. According to the Oxford English Dictionary (OED), the word "tangerine" was originally an adjective meaning "Of or pertaining to, or native of Tangier, a seaport in Morocco, on the Strait of Gibraltar" and "a native of Tangier." The name was first used for fruit coming from Tangier, Morocco, described as a mandarin variety. The OED cites this usage from Addison's The Tatler in 1710 with similar uses from the 1800s. The adjective was applied to the fruit, once known scientifically as "Citrus nobilis var. tangeriana" which grew in the region of Tangiers. This usage appears in the 1800s.
Charles Green*, John Doe*, Robert White, James Wang, Your Name# (* equal contribution, # corresponding author)
International Conference on Learning Representations (ICLR) 2023
TL;DR Photo by Dessy Dimcheva on Unsplash. Please keep the description of your publication as brief as possible. 1~2 sentences is ideal. Otherwise, it will look too noisy. This is a counterexample to show how the publication will look like when the abstract is too long. The tangerine is a type of citrus fruit that is orange in color, that is considered either a variety of Citrus reticulata, the mandarin orange, or a closely related species, under the name Citrus tangerina, or yet as a hybrid (Citrus × tangerina) of mandarin orange varieties, with some pomelo contribution. According to the Oxford English Dictionary (OED), the word "tangerine" was originally an adjective meaning "Of or pertaining to, or native of Tangier, a seaport in Morocco, on the Strait of Gibraltar" and "a native of Tangier." The name was first used for fruit coming from Tangier, Morocco, described as a mandarin variety. The OED cites this usage from Addison's The Tatler in 1710 with similar uses from the 1800s. The adjective was applied to the fruit, once known scientifically as "Citrus nobilis var. tangeriana" which grew in the region of Tangiers. This usage appears in the 1800s.
Your Name*, Robert White*, John Doe, Charles Green (* equal contribution)
Nature Communications 2023
TL;DR Cover image is a photo by Thomas Renaud on Unsplash. The abstract of the publication is meant to be a TLDR (very brief summary with 1~2 sentences) of your paper.
Your Name*, Robert White*, John Doe, Charles Green (* equal contribution)
Nature Communications 2023
TL;DR Cover image is a photo by Thomas Renaud on Unsplash. The abstract of the publication is meant to be a TLDR (very brief summary with 1~2 sentences) of your paper.
Your Name*#, James Wang*, Some Other Name, John Doe (* equal contribution, # corresponding author)
International Conference on Learning Representations (ICLR) 2023
TL;DR
When the cover image is not provided, it will generate a random colorful bubble images as the cover image using the bubble_visual_hash.js script.
Your Name*#, James Wang*, Some Other Name, John Doe (* equal contribution, # corresponding author)
International Conference on Learning Representations (ICLR) 2023
TL;DR
When the cover image is not provided, it will generate a random colorful bubble images as the cover image using the bubble_visual_hash.js script.
Can Berk Saner, A. Trivedi, D. Srinivasan
2022 IEEE PES 14th Asia-Pacific Power and Energy Engineering Conference (APPEEC)
TL;DR A mixed-integer linear programming framework integrates battery degradation costs into electric bus charging schedules through piecewise-linear approximation, enabling substantial lifecycle cost reduction.
Can Berk Saner, A. Trivedi, D. Srinivasan
2022 IEEE PES 14th Asia-Pacific Power and Energy Engineering Conference (APPEEC)
TL;DR A mixed-integer linear programming framework integrates battery degradation costs into electric bus charging schedules through piecewise-linear approximation, enabling substantial lifecycle cost reduction.
Can Berk Saner, R. H. C. Wei, S. A. R. Alkaff, L. W. Zheng, L. Y. Wei, A. Trivedi, D. Srinivasan
2022 IEEE PES Innovative Smart Grid Technologies - Asia (ISGT Asia)
TL;DR A vehicle and charging scheduling framework is developed for campus electric bus fleets to minimize charging costs and battery degradation under demand and time-of-use tariffs.
Can Berk Saner, R. H. C. Wei, S. A. R. Alkaff, L. W. Zheng, L. Y. Wei, A. Trivedi, D. Srinivasan
2022 IEEE PES Innovative Smart Grid Technologies - Asia (ISGT Asia)
TL;DR A vehicle and charging scheduling framework is developed for campus electric bus fleets to minimize charging costs and battery degradation under demand and time-of-use tariffs.
Can Berk Saner, A. Trivedi, D. Srinivasan
2022 IEEE PES Innovative Smart Grid Technologies - Asia (ISGT Asia)
TL;DR A receding horizon control-based EV charging scheduling methodology is proposed to jointly reduce demand and energy charges while preserving data privacy in industrial and commercial charging sites.
Can Berk Saner, A. Trivedi, D. Srinivasan
2022 IEEE PES Innovative Smart Grid Technologies - Asia (ISGT Asia)
TL;DR A receding horizon control-based EV charging scheduling methodology is proposed to jointly reduce demand and energy charges while preserving data privacy in industrial and commercial charging sites.
Can Berk Saner, A. Trivedi, D. Srinivasan
IEEE Transactions on Smart Grid
TL;DR This work presents a cooperative hierarchical multi-agent system and proposes an EV charging scheduling strategy in order to minimize the demand and energy charges while meeting the EV users’ energy requirements and satisfying the system security constraints.
Can Berk Saner, A. Trivedi, D. Srinivasan
IEEE Transactions on Smart Grid
TL;DR This work presents a cooperative hierarchical multi-agent system and proposes an EV charging scheduling strategy in order to minimize the demand and energy charges while meeting the EV users’ energy requirements and satisfying the system security constraints.
Can Berk Saner, Y. Yaslan, I. Genc
Electrical Engineering
TL;DR A stacked ensemble model that uses post-contingency wide-area synchrophasor measurements is proposed to classify the transient stability status of power systems.
Can Berk Saner, Y. Yaslan, I. Genc
Electrical Engineering
TL;DR A stacked ensemble model that uses post-contingency wide-area synchrophasor measurements is proposed to classify the transient stability status of power systems.
Can Berk Saner, M. Kesici, Y. Yaslan, V. M. I. Genc
2019 11th International Conference on Electrical and Electronics Engineering (ELECO)
TL;DR Resampling techniques are applied to address data imbalance in machine learning-based transient stability prediction and achieve improved classification accuracy.
Can Berk Saner, M. Kesici, Y. Yaslan, V. M. I. Genc
2019 11th International Conference on Electrical and Electronics Engineering (ELECO)
TL;DR Resampling techniques are applied to address data imbalance in machine learning-based transient stability prediction and achieve improved classification accuracy.
M. Kesici, Can Berk Saner, Y. Yaslan, V. I. Genc
2019 11th International Conference on Electrical and Electronics Engineering (ELECO)
TL;DR A class-weighted loss formulation is introduced for convolutional neural networks to improve early prediction of transient instability under unequal misclassification costs.
M. Kesici, Can Berk Saner, Y. Yaslan, V. I. Genc
2019 11th International Conference on Electrical and Electronics Engineering (ELECO)
TL;DR A class-weighted loss formulation is introduced for convolutional neural networks to improve early prediction of transient instability under unequal misclassification costs.
M. Kesici, Can Berk Saner, M. Mahdi, Y. Yaslan, V. M. I. Genc
2019 7th International Istanbul Smart Grids and Cities Congress and Fair (ICSG)
TL;DR A convolutional neural network-based sliding window approach is proposed for real-time event detection and classification in power systems.
M. Kesici, Can Berk Saner, M. Mahdi, Y. Yaslan, V. M. I. Genc
2019 7th International Istanbul Smart Grids and Cities Congress and Fair (ICSG)
TL;DR A convolutional neural network-based sliding window approach is proposed for real-time event detection and classification in power systems.
M. Kesici, Can Berk Saner, M. Mahdi, Y. Yaslan, V. M. I. Genc
2019 7th International Istanbul Smart Grids and Cities Congress and Fair (ICSG)
TL;DR Feature selection-based methods are used to determine optimal PMU locations for early transient instability prediction.
M. Kesici, Can Berk Saner, M. Mahdi, Y. Yaslan, V. M. I. Genc
2019 7th International Istanbul Smart Grids and Cities Congress and Fair (ICSG)
TL;DR Feature selection-based methods are used to determine optimal PMU locations for early transient instability prediction.
Can Berk Saner, S. Skarvelis-Kazakos
2018 53rd International Universities Power Engineering Conference (UPEC)
TL;DR An energy management strategy combining optimal dispatch and demand response achieves significant fuel savings in isolated Antarctic microgrids.
Can Berk Saner, S. Skarvelis-Kazakos
2018 53rd International Universities Power Engineering Conference (UPEC)
TL;DR An energy management strategy combining optimal dispatch and demand response achieves significant fuel savings in isolated Antarctic microgrids.