{"language":[{"iso":"eng"}],"publisher":"Elsevier BV","article_type":"original","article_number":"100227","date_updated":"2026-02-03T12:58:44Z","type":"journal_article","keyword":["DC-grid","Droop control","Grid-serving behaviour","Grid stability","Bidirectional charging","Sequential decision","MILP optimisation"],"author":[{"last_name":"Rahlf","first_name":"Henning Christoph","orcid":"0009-0006-8106-2132","full_name":"Rahlf, Henning Christoph","id":"56955"},{"orcid":"0009-0005-4727-7511","full_name":"Knorr, Lukas","first_name":"Lukas","last_name":"Knorr","id":"90391"},{"full_name":"Althoff, Simon","last_name":"Althoff","first_name":"Simon"},{"last_name":"Meschede","first_name":"Henning","orcid":"0000-0002-1538-089X","full_name":"Meschede, Henning","id":"86954"}],"citation":{"ama":"Rahlf HC, Knorr L, Althoff S, Meschede H. Analysis of bidirectional EV charging infrastructures within industrial DC grids. <i>Smart Energy</i>. Published online 2026. doi:<a href=\"https://doi.org/10.1016/j.segy.2026.100227\">10.1016/j.segy.2026.100227</a>","mla":"Rahlf, Henning Christoph, et al. “Analysis of Bidirectional EV Charging Infrastructures within Industrial DC Grids.” <i>Smart Energy</i>, 100227, Elsevier BV, 2026, doi:<a href=\"https://doi.org/10.1016/j.segy.2026.100227\">10.1016/j.segy.2026.100227</a>.","ieee":"H. C. Rahlf, L. Knorr, S. Althoff, and H. Meschede, “Analysis of bidirectional EV charging infrastructures within industrial DC grids,” <i>Smart Energy</i>, Art. no. 100227, 2026, doi: <a href=\"https://doi.org/10.1016/j.segy.2026.100227\">10.1016/j.segy.2026.100227</a>.","apa":"Rahlf, H. C., Knorr, L., Althoff, S., &#38; Meschede, H. (2026). Analysis of bidirectional EV charging infrastructures within industrial DC grids. <i>Smart Energy</i>, Article 100227. <a href=\"https://doi.org/10.1016/j.segy.2026.100227\">https://doi.org/10.1016/j.segy.2026.100227</a>","short":"H.C. Rahlf, L. Knorr, S. Althoff, H. Meschede, Smart Energy (2026).","chicago":"Rahlf, Henning Christoph, Lukas Knorr, Simon Althoff, and Henning Meschede. “Analysis of Bidirectional EV Charging Infrastructures within Industrial DC Grids.” <i>Smart Energy</i>, 2026. <a href=\"https://doi.org/10.1016/j.segy.2026.100227\">https://doi.org/10.1016/j.segy.2026.100227</a>.","bibtex":"@article{Rahlf_Knorr_Althoff_Meschede_2026, title={Analysis of bidirectional EV charging infrastructures within industrial DC grids}, DOI={<a href=\"https://doi.org/10.1016/j.segy.2026.100227\">10.1016/j.segy.2026.100227</a>}, number={100227}, journal={Smart Energy}, publisher={Elsevier BV}, author={Rahlf, Henning Christoph and Knorr, Lukas and Althoff, Simon and Meschede, Henning}, year={2026} }"},"title":"Analysis of bidirectional EV charging infrastructures within industrial DC grids","status":"public","abstract":[{"text":"Industrial electrification is increasing to reduce fossil fuel dependence, alongside a growing share of volatile renewables.\r\nA secure and reliable energy supply is crucial for industry, leading to a shift from centralised to decentralised grid structures.\r\nDC microgrids becoming increasingly popular in industry, since they enable energy recuperation from braking, reduce components and cables, and integrate storage and local generation to manage supply interruptions or peak loads.\r\nEVs add further synergies by serving as mobile storage units, helping to store and redistribute locally generated renewable energy.\r\nThis paper analyses how EV integration in droop-controlled DC grids can contribute to a more stable, low-emission and peak-reduced load profile to the supply grid through load shifting and bridge interruptions.\r\nA droop-controlled DC grid model has been developed, incorporating an EV charging park based on probability functions.\r\nScalable scenarios allow for diverse condition analysis using an energy management system that utilises fuzzy logic and sequential MILP optimisation.\r\nIt has been shown that a 7% improvement of coefficient represented grid-serving behaviour is possible by load shifting.\r\nIt has also been demonstrated that an optimised EMS can reduce the demand-based CO2 emissions by 41kg for a representative day compared to a fuzzy logic EMS.\r\nAt the same time peak load is decreased yielding a more constant residual load.\r\nThese results highlight the potential of a controlled bidirectional charging infrastructure in DC grids and underscore the need to explicitly consider charging processes to ensure a residual load as constant as possible.","lang":"eng"}],"date_created":"2026-02-02T14:45:17Z","_id":"63838","doi":"10.1016/j.segy.2026.100227","quality_controlled":"1","publication":"Smart Energy","year":"2026","publication_identifier":{"issn":["2666-9552"]},"user_id":"56955","department":[{"_id":"644"}],"publication_status":"published"}