Outputs (18)

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..

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..

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..

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..

A multi-objective optimization model for EVSE deployment at workplaces with smart charging strategies and scheduling policies. (2022)
Journal Article
ERDOGAN, N., KUCUKSARI, S. and MURPHY, J. 2022. A multi-objective optimization model for EVSE deployment at workplaces with smart charging strategies and scheduling policies. Energy [online], 254(Part A), article number 124161. Available from: https://doi.org/10.1016/j.energy.2022.124161

This study proposes a multi-objective optimization model to determine the optimal charging infrastructure for a transition to plug-in electric vehicles (PEVs) at workplaces. The developed model considers all cost aspects of a workplace charging stati... Read More about A multi-objective optimization model for EVSE deployment at workplaces with smart charging strategies and scheduling policies..

Offshore wind speed short-term forecasting based on a hybrid method: swarm decomposition and meta-extreme learning machine. (2022)
Journal Article
DOKUR, E., ERDOGAN, N., SALARI, M.E., KARAKUZU, C. and MURPHY, J. 2022. Offshore wind speed short-term forecasting based on a hybrid method: Swarm decomposition and meta-extreme learning machine. Energy [online], 248, article 123595. Available from: https://doi.org/10.1016/j.energy.2022.123595

As the share of global offshore wind energy in the electricity generation portfolio is rapidly increasing, the grid integration of large-scale offshore wind farms is becoming of interest. Due to the intermittency of wind, the stability of power syste... Read More about Offshore wind speed short-term forecasting based on a hybrid method: swarm decomposition and meta-extreme learning machine..

Co-simulation of optimal EVSE and techno-economic system design models for electrified fleets. (2022)
Journal Article
ERDOGAN, N., KUCUKSARI, S. and CALI, U. 2022. Co-simulation of optimal EVSE and techno-economic system design models for electrified fleets. IEEE access [online], 10, pages 18988-18997. Available from: https://doi.org/10.1109/ACCESS.2022.3150359

As the transition to electric mobility is expanding at a rapid pace, operationally feasible and economically viable charging infrastructure is needed to support electrified fleets. This paper presents a co-simulation of optimal electric vehicle suppl... Read More about Co-simulation of optimal EVSE and techno-economic system design models for electrified fleets..