Internship Probabilistic power flow using probabilistic forecast data

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There are different methods to perform probabilistic power flow. We are looking for a method that is compatible with the format of the input data that we have, namely quantile forecasts and if possible, compatible with the calculation core currently used in DSA, Power Grid Model.
The objective of this thesis is to develop a model that uses quantile forecasts of power injections as inputs and performs a probabilistic power flow calculation for the distribution grid. You will analyze different methods, design proof-of-concept for the most promising method, analyze and compare the results. You will discuss with the team for content and implementation topics.
Expected output
- Report of the master thesis.
- Presentation of the findings in the team (and department).
- The code developed for the thesis to be shared with DSA.
The Dynamic Safety Analyzer (DSA) team plays a central role within GaaS. We combine grid topology information, forecasts, measurements, and power-system calculations to continuously assess the current and future state of the electricity grid. These assessments provide other GaaS teams with actionable insights that support congestion management, capacity management, and operational decision-making. Because we work with large volumes of uncertain and incomplete data from many different sources, ensuring the quality, reliability, and robustness of our assessments is a critical challenge. The team consists of software developers, energy system specialists, scrum master and product owner.
Stagebureau Alliander
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