The project investigated the integration of electric vehicle charging into existing industrial and municipal energy systems, focusing on accurate load forecasting, real‑time grid monitoring, and flexibility trading. In the case study of a city cleaning operation, the industrial lighting load was found to peak at approximately 32 kW. Forecasting of the remaining consumption areas was performed using standard load profiles. When applied to the whole set of consumption areas, the average absolute forecast error over a 15‑minute grid was 20 %. However, when the standard profiles were assigned to each consumption area individually, the error dropped to 6 %, and for the most detailed individual profiles the error fell below 1 %. These results demonstrate that a fine‑grained, area‑specific approach yields substantially higher accuracy than a blanket application of generic profiles.
The technical chain for grid‑conscious charging was built around a grid control software that continuously collects real‑time measurements from grid assets and updates forecasts of voltage and line loading. Based on these forecasts and the actual measurements, the software generates recommendations to avoid congestion. When a potential overload is detected, an event signal is sent via the OpenADR protocol to the charging infrastructure at specific grid nodes, requesting a reduction in load. The flexibility marketing component uses a forecasting engine to estimate partial load curves for various on‑site consumers such as a workshop, office, and kitchen. An optimization module then aligns the charging load with the available grid connection capacity, local distribution limits, and any peak‑load constraints of the remaining consumption. The resulting charging curves are monitored as part of a virtual power plant, with the flexibility marketer able to buy or sell electricity in 15‑minute intervals. This trading mechanism can amplify the trading volume beyond the actual energy consumed during charging, as price fluctuations in the continuous electricity market are exploited.
The project also leveraged the 3connect initiative, which brings together 18 partners across Aachen, Allgäu, and Osnabrück. 3connect builds on data from the econnect Germany lighthouse project and develops a software platform that enables operators of charging stations to implement load‑management and energy‑management concepts from a central point. The platform uses the OCPP 1.6 standard for backend control of charging sessions. During the test phase, the system is evaluated for commercial fleets, residential buildings, commercial premises, and parking operators, with particular attention to maintaining load limits for commercial customers and intelligently distributing available connection power among multiple chargers. The platform also considers on‑site renewable generation and stationary storage, expanding its applicability to a wide range of stakeholders.
The ELBE – Electrify Buildings for EVs sub‑project, funded by Hamburg Energie (grant 01MZ18014E), ran from 8 October 2018 to 30 September 2022. It focused on deploying the developed charging and flexibility solutions in real buildings, ensuring that the existing infrastructure met the technical requirements for the new system. The project’s outcomes include a demonstrator of the integrated charging and flexibility framework, performance data confirming the forecast accuracy improvements, and a validated business model for flexibility trading. The collaboration involved Hamburg Energie as the funding body, with technical partners providing the charging hardware, grid control software, and optimization algorithms. The project’s results are intended to be transferred to other municipalities and commercial operators, supporting the broader rollout of electric mobility and grid‑friendly charging practices.