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When and where it counts: enhancing demand response in electric vehicle charging

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  • Sobhy, Ahmed S.M.
  • Caesary, Desy
  • Kim, Hana
  • Eom, Jiyong

Abstract

Electric vehicles (EVs) offer a promising solution for mitigating the intermittency of renewable energy through flexible charging. Demand Response (DR) has been tested as one of the key demand-side solutions to capture the flexibility potential of EVs in Korea. This study evaluates the effects of DR interventions focusing on temporal factors and station-level characteristics that are often overlooked in existing literature. Using panel data from 558 EV charging stations (EVCSs) in Korea that participated in the DR program (November 9, 2022–April 30, 2023), we develop a CatBoost-based predictive model to estimate counterfactual consumption and isolate DR impacts at the station level. Results show that EVCSs with automatic controls achieve an average reduction of 11.8 % during event hours, while manual adjustments in charging patterns yield only a 0.4 % reduction, underscoring the limitations of voluntary user compliance. Moderately visited EVCSs exhibit the largest reductions in load, suggesting that station-level characteristics such as occupancy rate play a crucial role in DR effectiveness. Analysis reveals that stations with occupancy rates between 25 % and 63 % demonstrate the most substantial consumption reductions, indicating an optimal operational range for DR program effectiveness. DR interventions were the most effective during evening hours for EVCSs with automatic controls, whereas manual adjustments showed no significant variation by time. In addition, intervention effects during the evening hours differ across seasons. These findings provide insights for the development of DR programs that consider temporal variations and imply the need for automation of EVCSs to enhance grid flexibility.

Suggested Citation

  • Sobhy, Ahmed S.M. & Caesary, Desy & Kim, Hana & Eom, Jiyong, 2025. "When and where it counts: enhancing demand response in electric vehicle charging," Applied Energy, Elsevier, vol. 401(PB).
  • Handle: RePEc:eee:appene:v:401:y:2025:i:pb:s0306261925014692
    DOI: 10.1016/j.apenergy.2025.126739
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    1. Wooyoung Jeon & Sangmin Cho & Seungmoon Lee, 2020. "Estimating the Impact of Electric Vehicle Demand Response Programs in a Grid with Varying Levels of Renewable Energy Sources: Time-of-Use Tariff versus Smart Charging," Energies, MDPI, vol. 13(17), pages 1-22, August.
    2. Byungsung Lee & Haesung Lee & Hyun Ahn, 2020. "Improving Load Forecasting of Electric Vehicle Charging Stations Through Missing Data Imputation," Energies, MDPI, vol. 13(18), pages 1-15, September.
    3. Siobhan Powell & Gustavo Vianna Cezar & Liang Min & Inês M. L. Azevedo & Ram Rajagopal, 2022. "Charging infrastructure access and operation to reduce the grid impacts of deep electric vehicle adoption," Nature Energy, Nature, vol. 7(10), pages 932-945, October.
    4. Pan, Yue & Zhang, Limao, 2020. "Data-driven estimation of building energy consumption with multi-source heterogeneous data," Applied Energy, Elsevier, vol. 268(C).
    5. Jiehong Lou & Xingchi Shen & Deb A. Niemeier & Nathan Hultman, 2024. "Income and racial disparity in household publicly available electric vehicle infrastructure accessibility," Nature Communications, Nature, vol. 15(1), pages 1-12, December.
    6. Andrea Mazza & Angela Russo & Gianfranco Chicco & Andrea Di Martino & Cristian Giovanni Colombo & Michela Longo & Paolo Ciliento & Marco De Donno & Francesca Mapelli & Francesco Lamberti, 2024. "Categorization of Attributes and Features for the Location of Electric Vehicle Charging Stations," Energies, MDPI, vol. 17(16), pages 1-32, August.
    7. Siavash Asiaban & Nezmin Kayedpour & Arash E. Samani & Dimitar Bozalakov & Jeroen D. M. De Kooning & Guillaume Crevecoeur & Lieven Vandevelde, 2021. "Wind and Solar Intermittency and the Associated Integration Challenges: A Comprehensive Review Including the Status in the Belgian Power System," Energies, MDPI, vol. 14(9), pages 1-41, May.
    8. Maltais, Louis-Gabriel & Gosselin, Louis, 2022. "Forecasting of short-term lighting and plug load electricity consumption in single residential units: Development and assessment of data-driven models for different horizons," Applied Energy, Elsevier, vol. 307(C).
    9. Bartusch, Cajsa & Alvehag, Karin, 2014. "Further exploring the potential of residential demand response programs in electricity distribution," Applied Energy, Elsevier, vol. 125(C), pages 39-59.
    10. Vassilios Bazinas & Bent Nielsen, 2022. "Causal Transmission in Reduced-Form Models," Econometrics, MDPI, vol. 10(2), pages 1-25, March.
    11. Ghimire, Sujan & Deo, Ravinesh C. & Casillas-Pérez, David & Salcedo-Sanz, Sancho, 2024. "Two-step deep learning framework with error compensation technique for short-term, half-hourly electricity price forecasting," Applied Energy, Elsevier, vol. 353(PA).
    12. Alain Poulin & Marie-Andrée Leduc & Michaël Fournier, 2022. "Statistical Analysis of Baseline Load Models for Residential Buildings in the Context of Winter Demand Response," Energies, MDPI, vol. 15(12), pages 1-14, June.
    13. Schmidt, Marc & Staudt, Philipp & Weinhardt, Christof, 2020. "Evaluating the importance and impact of user behavior on public destination charging of electric vehicles," Applied Energy, Elsevier, vol. 258(C).
    14. Daiva Stanelyte & Neringa Radziukyniene & Virginijus Radziukynas, 2022. "Overview of Demand-Response Services: A Review," Energies, MDPI, vol. 15(5), pages 1-31, February.
    15. Matteo Muratori, 2018. "Impact of uncoordinated plug-in electric vehicle charging on residential power demand," Nature Energy, Nature, vol. 3(3), pages 193-201, March.
    16. Saberi-Beglar, Kasra & Zare, Kazem & Seyedi, Heresh & Marzband, Mousa & Nojavan, Sayyad, 2023. "Risk-embedded scheduling of a CCHP integrated with electric vehicle parking lot in a residential energy hub considering flexible thermal and electrical loads," Applied Energy, Elsevier, vol. 329(C).
    17. Motoaki, Yutaka & Yi, Wenqi & Salisbury, Shawn, 2018. "Empirical analysis of electric vehicle fast charging under cold temperatures," Energy Policy, Elsevier, vol. 122(C), pages 162-168.
    18. Sugar, Catherine A. & James, Gareth M., 2003. "Finding the Number of Clusters in a Dataset: An Information-Theoretic Approach," Journal of the American Statistical Association, American Statistical Association, vol. 98, pages 750-763, January.
    19. Rishabh Ghotge & Yitzhak Snow & Samira Farahani & Zofia Lukszo & Ad van Wijk, 2020. "Optimized Scheduling of EV Charging in Solar Parking Lots for Local Peak Reduction under EV Demand Uncertainty," Energies, MDPI, vol. 13(5), pages 1-18, March.
    20. Fretzen, Ulrich & Ansarin, Mohammad & Brandt, Tobias, 2021. "Temporal city-scale matching of solar photovoltaic generation and electric vehicle charging," Applied Energy, Elsevier, vol. 282(PA).
    21. Cesar Diaz-Londono & Luigi Colangelo & Fredy Ruiz & Diego Patino & Carlo Novara & Gianfranco Chicco, 2019. "Optimal Strategy to Exploit the Flexibility of an Electric Vehicle Charging Station," Energies, MDPI, vol. 12(20), pages 1-29, October.
    22. Kamalanathan Ganesan & João Tomé Saraiva & Ricardo J. Bessa, 2019. "On the Use of Causality Inference in Designing Tariffs to Implement More Effective Behavioral Demand Response Programs," Energies, MDPI, vol. 12(14), pages 1-20, July.
    23. Thomas Shering & Eduardo Alonso & Dimitra Apostolopoulou, 2024. "Investigation of Load, Solar and Wind Generation as Target Variables in LSTM Time Series Forecasting, Using Exogenous Weather Variables," Energies, MDPI, vol. 17(8), pages 1-23, April.
    24. Qiao Yu & Tristan Que & Lara J. Cushing & Gregory Pierce & Ke Shen & Mayank Kejriwal & Yuan Yao & Yifang Zhu, 2025. "Equity and reliability of public electric vehicle charging stations in the United States," Nature Communications, Nature, vol. 16(1), pages 1-13, December.
    25. Guilherme Gloriano de Souza & Ricardo Ribeiro dos Santos & Ruben Barros Godoy, 2025. "Optimizing power grids: A valley-filling heuristic for energy-efficient electric vehicle charging," PLOS ONE, Public Library of Science, vol. 20(1), pages 1-36, January.
    26. Zhou, Sheng & Wang, Yu & Zhou, Yuyu & Clarke, Leon E. & Edmonds, James A., 2018. "Roles of wind and solar energy in China’s power sector: Implications of intermittency constraints," Applied Energy, Elsevier, vol. 213(C), pages 22-30.
    27. Koenker, Roger W & Bassett, Gilbert, Jr, 1978. "Regression Quantiles," Econometrica, Econometric Society, vol. 46(1), pages 33-50, January.
    28. Varghese, Ann Mary & Menon, Nikhil & Ermagun, Alireza, 2024. "Equitable distribution of electric vehicle charging infrastructure: A systematic review," Renewable and Sustainable Energy Reviews, Elsevier, vol. 206(C).
    29. Ghanbari Motlagh, Saheb & Oladigbolu, Jamiu & Li, Li, 2025. "A review on electric vehicle charging station operation considering market dynamics and grid interaction," Applied Energy, Elsevier, vol. 392(C).
    30. Cheng, Fang & Liu, Hui, 2024. "Multi-step electric vehicles charging loads forecasting: An autoformer variant with feature extraction, frequency enhancement, and error correction blocks," Applied Energy, Elsevier, vol. 376(PB).
    31. Nico Brinkel & Thijs Wijk & Anoeska Buijze & Nanda Kishor Panda & Jelle Meersmans & Peter Markotić & Bart Ree & Henk Fidder & Baerte Brey & Simon Tindemans & Tarek AlSkaif & Wilfried Sark, 2024. "Enhancing smart charging in electric vehicles by addressing paused and delayed charging problems," Nature Communications, Nature, vol. 15(1), pages 1-10, December.
    32. Lee, Eunjung & Lee, Kyungeun & Lee, Hyoseop & Kim, Euncheol & Rhee, Wonjong, 2019. "Defining virtual control group to improve customer baseline load calculation of residential demand response," Applied Energy, Elsevier, vol. 250(C), pages 946-958.
    33. Antonopoulos, Ioannis & Robu, Valentin & Couraud, Benoit & Kirli, Desen & Norbu, Sonam & Kiprakis, Aristides & Flynn, David & Elizondo-Gonzalez, Sergio & Wattam, Steve, 2020. "Artificial intelligence and machine learning approaches to energy demand-side response: A systematic review," Renewable and Sustainable Energy Reviews, Elsevier, vol. 130(C).
    34. Yang, Xiong & Peng, Zhenhan & Wang, Pinxi & Zhuge, Chengxiang, 2023. "Seasonal variance in electric vehicle charging demand and its impacts on infrastructure deployment: A big data approach," Energy, Elsevier, vol. 280(C).
    35. Lisa Göberndorfer & Milica Savanovic & Georg Jäger, 2024. "Charging Rush Hour: Modeling Peak Electricity Demand for Charging a Fully Electric Fleet," SAGE Open, , vol. 14(4), pages 21582440241, November.
    36. Gaillard, Pierre & Goude, Yannig & Nedellec, Raphaël, 2016. "Additive models and robust aggregation for GEFCom2014 probabilistic electric load and electricity price forecasting," International Journal of Forecasting, Elsevier, vol. 32(3), pages 1038-1050.
    37. Alexandra Märtz & Uwe Langenmayr & Sabrina Ried & Katrin Seddig & Patrick Jochem, 2022. "Charging Behavior of Electric Vehicles: Temporal Clustering Based on Real-World Data," Energies, MDPI, vol. 15(18), pages 1-26, September.
    38. Naireeta Deb & Rajendra Singh & Richard R. Brooks & Kevin Bai, 2021. "A Review of Extremely Fast Charging Stations for Electric Vehicles," Energies, MDPI, vol. 14(22), pages 1-27, November.
    39. Kreft, Markus & Brudermueller, Tobias & Fleisch, Elgar & Staake, Thorsten, 2024. "Predictability of electric vehicle charging: Explaining extensive user behavior-specific heterogeneity," Applied Energy, Elsevier, vol. 370(C).
    40. Zanvettor, Giovanni Gino & Fochesato, Marta & Casini, Marco & Lygeros, John & Vicino, Antonio, 2024. "A stochastic approach for EV charging stations in demand response programs," Applied Energy, Elsevier, vol. 373(C).
    41. Hsu, Chih-Wei & Fingerman, Kevin, 2021. "Public electric vehicle charger access disparities across race and income in California," Transport Policy, Elsevier, vol. 100(C), pages 59-67.
    42. Emmanuel Binyet & Ming-Chuan Chiu & Hsin-Wei Hsu & Meng-Ying Lee & Chih-Yuan Wen, 2022. "Potential of Demand Response for Power Reallocation, a Literature Review," Energies, MDPI, vol. 15(3), pages 1-30, January.
    43. Hussain, Shahid & Irshad, Reyazur Rashid & Pallonetto, Fabiano & Hussain, Ihtisham & Hussain, Zakir & Tahir, Muhammad & Abimannan, Satheesh & Shukla, Saurabh & Yousif, Adil & Kim, Yun-Su & El-Sayed, H, 2023. "Hybrid coordination scheme based on fuzzy inference mechanism for residential charging of electric vehicles," Applied Energy, Elsevier, vol. 352(C).
    44. Frew, Bethany A. & Becker, Sarah & Dvorak, Michael J. & Andresen, Gorm B. & Jacobson, Mark Z., 2016. "Flexibility mechanisms and pathways to a highly renewable US electricity future," Energy, Elsevier, vol. 101(C), pages 65-78.
    45. Josef Meiers & Georg Frey, 2023. "A Case Study of the Use of Smart EV Charging for Peak Shaving in Local Area Grids," Energies, MDPI, vol. 17(1), pages 1-25, December.
    46. Koichiro Ito & Takanori Ida & Makoto Tanaka, 2018. "Moral Suasion and Economic Incentives: Field Experimental Evidence from Energy Demand," American Economic Journal: Economic Policy, American Economic Association, vol. 10(1), pages 240-267, February.
    47. Robert Thorndike, 1953. "Who belongs in the family?," Psychometrika, Springer;The Psychometric Society, vol. 18(4), pages 267-276, December.
    48. Qiu, Yueming Lucy & Wang, Yi David & Iseki, Hiroyuki & Shen, Xingchi & Xing, Bo & Zhang, Huiming, 2022. "Empirical grid impact of in-home electric vehicle charging differs from predictions," Resource and Energy Economics, Elsevier, vol. 67(C).
    49. Hwang, Foo Shen & Confrey, Thomas & Reidy, Colin & Picovici, Dorel & Callaghan, Dean & Culliton, David & Nolan, Cathal, 2024. "Review of battery thermal management systems in electric vehicles," Renewable and Sustainable Energy Reviews, Elsevier, vol. 192(C).
    50. Hopkins, Emma & Potoglou, Dimitris & Orford, Scott & Cipcigan, Liana, 2023. "Can the equitable roll out of electric vehicle charging infrastructure be achieved?," Renewable and Sustainable Energy Reviews, Elsevier, vol. 182(C).
    51. Yong, Jin Yi & Tan, Wen Shan & Khorasany, Mohsen & Razzaghi, Reza, 2023. "Electric vehicles destination charging: An overview of charging tariffs, business models and coordination strategies," Renewable and Sustainable Energy Reviews, Elsevier, vol. 184(C).
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