Peer-Reviewed Publications

Preprint

  • Semmelmann, L., Kimbrough, S. O., Staudt, P. (2026). Aggregator Price Guarantees for Households with Flexibility Potential and Thermal Building Inertia.

2025

  • Premer, L. D. R., Pergantis, E. N., Semmelmann, L., Ziviani, D., & Kircher, K. J. (2026). Model predictive control lowers barriers to adoption of heat-pump water heaters: A field study. Energy Conversion and Management, 348, 120723.

  • Semmelmann, L., Kaiser, K., Heider, A., Kircher, K. J., Hug, G., & Weinhardt, C. (2025). [Analyzing the Impact of Dynamic Tariff Adoption and Regulatory Options on Distribution Grids with an Open-Source Framework. In Proceedings of the 16th ACM International Conference on Future and Sustainable Energy Systems (pp. 515-533).

  • Miskiw, K. K., Ludwig, J., Semmelmann, L., & Weinhardt, C. (2025). Continuous Intraday Trading: An Open-Source Multi-Market Bidding Framework for Energy Storage Systems. In Proceedings of the 16th ACM International Conference on Future and Sustainable Energy Systems (pp. 277-292).

  • Semmelmann, L., & Brudermueller, T. (2025). Rapidly Trainable Large-Scale Probabilistic Heat Pump Load Forecasting: A Kernel Density Estimation Approach. In Proceedings of the 16th ACM International Conference on Future and Sustainable Energy Systems (pp. 727-732).

2024

  • Semmelmann, L., Hertel, M., Kircher, K. J., Mikut, R., Hagenmeyer, V., & Weinhardt, C. (2024). The impact of heat pumps on day-ahead energy community load forecasting. Applied Energy, 368, 123364.

  • Semmelmann, L., Konermann, M., Dietze, D., & Staudt, P. (2024). Empirical field evaluation of self-consumption promoting regulation of household battery energy storage systems. Energy Policy, 194, 114343.

  • Semmelmann, L., Dresselhaus, J., Miskiw, K. K., Ludwig, J., & Weinhardt, C. (2024). An Algorithm for Modelling Rolling Intrinsic Battery Trading on the Continuous Intraday Market. ACM SIGENERGY Energy Informatics Review, Volume 4, Issue 5, October 2024.

  • Semmelmann, L., Resch, O., Henni, S., & Weinhardt, C. (2024). Privacy-preserving peak time forecasting with Learning to Rank XGBoost and extensive feature engineering. IET Smart Grid, 7(2), 172-185.

  • Premer, L. R., Semmelmann, L., Pergantis, E. N., Groll, E. A., Ziviani, D., & Kircher, K. J. (2024). Field demonstration of predictive heat pump water heater control. In 8th International High Performance Buildings Conference at Purdue.

2023

  • Semmelmann, L., Jaquart, P., & Weinhardt, C. (2023). Generating synthetic load profiles of residential heat pumps: a k-means clustering approach. Energy Informatics.

  • Semmelmann, L., Schmid, D., Henni, S., Heider, A., Schachler, B., & Weinhardt, C. (2023, October). On the impact of heat pump installations and peak blocking strategies on grid expansion costs. In 2023 IEEE PES Innovative Smart Grid Technologies Europe (ISGT EUROPE) (pp. 1-6). IEEE.

2022

  • Semmelmann, L., Henni, S., & Weinhardt, C. (2022). Load forecasting for energy communities: A novel LSTM-XGBoost hybrid model based on smart meter data. Energy Informatics, 5(1), 1-21.

2021

  • Kucevic, D., Semmelmann, L., Collath, N., Jossen, A., & Hesse, H. (2021). Peak shaving with battery energy storage systems in distribution grids: a novel approach to reduce local and global peak loads. Electricity, 2(4), 573-589.