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Found 7 papers, 0 papers with code
TimeGPT in Load Forecasting: A Large Time Series Model Perspective
Machine learning models have made significant progress in load forecasting, but their forecast accuracy is limited in cases where historical load data is scarce.
Optimizing the Generation and Transmission Capacity of Offshore Wind Parks under Weather Uncertainty
Offshore wind power in the North Sea is considered a main pillar in Europe's future energy system.
Modeling and Contribution of Flexible Heating Systems for Transmission Grid Congestion Management
The large-scale integration of flexible heating systems in the European electricity market leads to a substantial increase of transportation requirements and consecutively grid congestions in the continental transmission grid.
System-level Testing of the Congestion Management Capability of a Hardware-Independent Optimal Power Flow Algorithm
In this paper, a full-scale low-voltage test setup in the Smart Grid Technology Lab (SGTL) at TU Dortmund University is used to evaluate the capability of an Optimal Power Flow Algorithm (OPF) to support voltage control, congestion management, and to provide redispatch to the higher grid levels.
Implementation of Machine Learning-based DER Local Control Schemes on Measurement Devices for Counteracting Communication Failures
In addition to the regression control, the paper also explains an offline learning approach for periodic re-training of the regression models.
Adaptive and Robust Cross-Voltage-Level Power Flow Control of Active Distribution Networks
In order to validate the control parameter tuning, the adaptive control system is analyzed regarding robustness and performance using an exemplary medium voltage grid.
Power Response and Modelling Aspects of Power Electronic Loads in Case of Voltage Drops
Overall, the contributions of the paper are the identification of the basic power dynamics of power electronic loads for different voltage drops and a subsequent derivation of suitable simulation load models for voltage stability investigations.
