Outputs (23)

Multiple decomposition-aided long short-term memory network for enhanced short-term wind power forecasting. (2023)
Journal Article
BALCI, M., DOKUR, E., YUZGEC, U. and ERDOGAN, N. [2024]. Multiple decomposition-aided long short-term memory network for enhanced short-term wind power forecasting. IET renewable power generation [online], Early View. Available from: https://doi.org/10.1049/rpg2.12919

With the increasing penetration of grid-scale wind energy systems, accurate wind power forecasting is critical to optimizing their integration into the power system, ensuring operational reliability, and enabling efficient system asset utilization. A... Read More about Multiple decomposition-aided long short-term memory network for enhanced short-term wind power forecasting..

Impact of communication system characteristics on electric vehicle grid integration: a large-scale practical assessment of the UK's cellular network for the Internet of Energy. (2023)
Journal Article
ZEINALI, M., ERDOGAN, N., BAYRAM, I.S. and THOMPSON, J.S. 2023. Impact of communication system characteristics on electric vehicle grid integration: a large-scale practical assessment of the UK's cellular network for the Internet of Energy. Electricity [online], 4(4), pages 309-319. Available from: https://doi.org/10.3390/electricity4040018

The ever-increasing number of plug-in electric vehicles (PEVs) requires appropriate electric vehicle grid integration (EVGI) for charging coordination to maintain grid stability and enhance PEV user convenience. As such, the widespread adoption of el... Read More about Impact of communication system characteristics on electric vehicle grid integration: a large-scale practical assessment of the UK's cellular network for the Internet of Energy..

Optical-fibre based sensors for monitoring offshore floating photovoltaic farms. (2023)
Conference Proceeding
STEWART, C., JOSEPH, C.S.J., JOHNY, J., ERDOGAN, N., FOUGH, N. and PRABHU, R. 2023. Optical fibre-based sensors for monitoring offshore floating photovoltaic farms. In Proceedings of 2023 IEEE Oceanic Engineering Society conference and exposition (OCEANS 2023): blue ocean planet earth, 5-8 June 2023, Limerick, Ireland. Piscataway: IEEE [online], document number 10244737. Available from: https://doi.org/10.1109/OCEANSLimerick52467.2023.10244737

Solar photovoltaic farms are seeing increasing expansion into new domains (offshore) in order to harvest the sunlight as society pushes towards reaching Net Zero by 2050. However, photovoltaics are bound by physics, parameters such as temperature and... Read More about Optical-fibre based sensors for monitoring offshore floating photovoltaic farms..

A new rough ordinal priority-based decision support system for purchasing electric vehicles. (2023)
Journal Article
KUCUKSARI, S., PAMUCAR, D., DEVECI, M., ERDOGAN, N. and DELEN, D. 2023. A new rough ordinal priority-based decision support system for purchasing electric vehicles. Information sciences [online], 647, article number 119443. Available from: https://doi.org/10.1016/j.ins.2023.119443

This study proposes a novel multi-criteria decision-making (MCDM) model based on a rough extension of the Ordinal Priority Approach (OPA) to determine the order of importance of users' perspectives on Electric Vehicle (EV) purchases. Unlike conventio... Read More about A new rough ordinal priority-based decision support system for purchasing electric vehicles..

A rough Dombi Bonferroni based approach for public charging station type selection. (2023)
Journal Article
DEVECI, M., ERDOGAN, N., PAMUCAR, D., KUCUKSARI, S. and CALI, U. 2023. A rough Dombi Bonferroni based approach for public charging station type selection. Applied energy [online], 345, article 121258. Available from: https://doi.org/10.1016/j.apenergy.2023.121258

As the transition to electric mobility accelerates, charging infrastructure is rapidly expanding. Publicly accessible chargers, also known as electric vehicle supply equipment (EVSE), are critical not only for further promoting the transition but als... Read More about A rough Dombi Bonferroni based approach for public charging station type selection..

Mutation based improved dragonfly optimization algorithm for a neuro-fuzzy system in short term wind speed forecasting. (2023)
Journal Article
PARMAKSIZ, H., YUZGEC, U., DOKUR, E. and ERDOGAN, N. 2023. Mutation based improved dragonfly optimization algorithm for a neuro-fuzzy system in short term wind speed forecasting. Knowledge-based systems [online], 268, article 110472. Available from: https://doi.org/10.1016/j.knosys.2023.110472

The Dragonfly algorithm (DA) is a heuristic optimization algorithm that is commonly used for complex optimization problems. Despite its widespread application, the abundance of social behaviors in its construct can lead to poor accuracy in solutions... Read More about Mutation based improved dragonfly optimization algorithm for a neuro-fuzzy system in short term wind speed forecasting..

Cost analysis of DCFC fast charging station power rates for workplace charging. (2022)
Conference Proceeding
KUCUKSARI, S. and ERDOGAN, N. 2022. Cost analysis of DCFC fast charging station power rates for workplace charging. In Proceedings of 13th IEEE (Institute of Electrical and Electronics Engineers) PES (Power and Energy Society) Innovative smart grid technologies conference 2022 (ISGT 2022): moving to a 3-D energy landscape: decarbonized, democratized, decentralized, 24-28 April 2022, New Orleans, USA. Piscataway: IEEE [online], article 9817537. Available from: https://doi.org/10.1109/ISGT50606.2022.9817537

DC fast charging (DCFC) station becomes prominent thanks to offering faster charging service. However, they increase the peak demand, hence, the demand charge for industrial and commercial customers increases. This study analyses cost behaviors of va... Read More about Cost analysis of DCFC fast charging station power rates for workplace charging..

A hybrid power heronian function-based multicriteria decision-making model for workplace charging scheduling algorithms. (2022)
Journal Article
ERDOGAN, N., PAMUCAR, D., KUCUKSARI, S. and DEVECI, M. 2023. A hybrid power heronian function-based multicriteria decision-making model for workplace charging scheduling algorithms. IEEE transactions on transportation electrification [online], 9(1), pages 1564-1578. Available from: https://doi.org/10.1109/TTE.2022.3186659

This study proposes a new multi-criteria decision-making model to determine the best smart charging scheduling that meets electric vehicle (EV) user considerations at work-places. An optimal charging station model is incorporated into the decision-ma... Read More about A hybrid power heronian function-based multicriteria decision-making model for workplace charging scheduling algorithms..

Modeling and data analysis of electric vehicle fleet charging. (2022)
Conference Proceeding
KUCUKSARI, S. and ERDOGAN, N. 2022. Modeling and data analysis of electric vehicle fleet charging. In Proceedings of 2022 IEEE (Institute of Electrical and Electronics Engineers)/AIAA (American Institute of Aeronautics and Astronautics) Transportation electrification conference and Electric aircraft technologies symposium (ITEC+EATS), 15-17 June 2022, Anaheim, USA. Piscataway: IEEE [online], pages 1139-1143. Available from: https://doi.org/10.1109/itec53557.2022.9814047

In the transition to electric fleets around the world, electricity demand from electric vehicle (EV) fleets is expected to become significant in the future. Since fleet cars can display different charging characteristics than individual EVs, analyzin... Read More about Modeling and data analysis of electric vehicle fleet charging..

EV fleet charging load forecasting based on multiple decomposition with CEEMDAN and swarm decomposition. (2022)
Journal Article
DOKUR, E., ERDOGAN, N. and KUCUKSARI, S. 2022. EV fleet charging load forecasting based on multiple decomposition with CEEMDAN and swarm decomposition. IEEE access [online], 10, pages 62330-62340. Available from: https://doi.org/10.1109/ACCESS.2022.3182499

As the transition to electric mobility is accelerating, EV fleet charging loads are expected to become increasingly significant for power systems. Hence, EV fleet load forecasting is vital to maintaining the reliability and safe operation of the powe... Read More about EV fleet charging load forecasting based on multiple decomposition with CEEMDAN and swarm decomposition..