Supervisor: Helena Sax
Earliest start: immediately
Type: Master Thesis

The increasing integration of renewable energy sources challenges power system operation. Decentralized renewable energy generation lead to an increase in average transmission distances and a higher utilization of the transmission grid to balance geographical mismatches between supply and demand. Maintaining system security requires costly redispatch measures. Corrective redispatch offers a way to increase grid operation efficiency by allowing higher line loadings after contingencies, e.g. a line outage. To comply with pre-contingency line limits again, corrective actions, e.g. the adjustment of controllable assets after a contingency to relieve overloads, are taken. However, conventional centralized corrective redispatch decisions often suffer from communication delays.
Concept and Objectives
This work investigates **local control laws** for corrective (also known as curative) redispatch actions, which can provide **faster system responses** compared to centralized decision-making. Such control schemes can predefine local rules that determine corrective actions directly based on local measurements, ensuring rapid reaction without requiring communication. Building on previous research on corrective redispatch via **power flow redirection using HVDC lines**, this thesis will **expand the work to include Grid Boosters**, which are large-scale battery storage systems capable of relieving transmission lines during overloads. Integrating these assets introduces new degrees of freedom but also new dynamics, particularly regarding their state of charge and response time.
Research Questions

1. How can existing local control laws for HVDC redispatch be extended to include **Grid Boosters**?
2. What is the impact of fast-acting local control on **transient stability** and dynamic system behavior?

Research impact This work will provide insights into:

• Improved **grid utilization** without requiring immediate infrastructure expansion,
• Reduced **redispatch costs**, enabling more **cost-efficient and sustainable grid operation**,
• Enhanced **stability and resilience** through faster local corrective action.

Supervisor: Helena Sax
Earliest start: immediately
Type: Bachelor Thesis

With the increasing number of converter-based renewable energy sources, the security of converter control systems becomes a major concern. Manipulation or misconfiguration of converter parameters (e.g., control gains or droop coefficients) can threaten grid stability. Grey-box converter models could offer an opportunity to identify such parameter changes from measurement data, without knowing the exact control structure of the converter.
Methodology

1. **Model setup:** Reproduce a simplified nonlinear grey-box converter model (see 10.36227/techrxiv.171639117.73358192/v1)
2. **Data generation:** Generate system response data for various operating conditions and include normal and manipulated scenarios
3. **Parameter estimation:** Use the grex-box model to perform parameter estimation based on system response data
4. **Rule-based anomaly detection:** Develop rule-based detection logic to identify if the estimated parameters were manipulated to destabilize the grid
5. **Evaluation:** Evaluate the approach for selected case studies (e.g., normal vs. manipulated converter control parameters).