As part of the global energy transition, optimizing power systems is a key challenge. There are several approaches to set up electricity markets. In North America, the market model is locational and encompasses network security constraints. This is a so-called nodal market where electricity prices vary based on geographic location of the assets due to transmission constraints and local resource availability. The clearing of such market is a complex process requiring an integrated optimizer combining Optimal Power Flow models (DC/linearized/AC), AC Power Flow, sensitivity analysis and sometimes, contingency analysis.
The goal of this internship is to model such a market by relying on and extending existing models from Crystal Optimization Engine and to implement the iterative workflow necessary for such optimization.
The intern will have to:
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Study nodal energy markets mechanisms and modelling
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Model optimal power flows
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Understand calculations performed for assessment of network security
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Implement the solution inside the optimization engine
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Benchmarks the developed solution on realistic instances
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