Electricity Markets
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Work description
The increasing penetration of renewable energy sources, storage systems, and flexible loads poses new challenges to the secure and efficient operation of power networks. The SCOPF problem plays a central role in planning and operation, ensuring system security under contingencies. However, classical SCOPF formulations present high computational complexity, especially in large-scale networks. In this context, the work is expected to contribute to the development of new NLP-based approaches capable of reducing computational effort without compromising solution quality, through the introduction of slack variables and penalty terms that allow controlled constraint violations. The work will be validated using IEEE test systems and will be applicable to the real operation of modern power grids. The main activities include: - Reviewing the state of the art in SCOPF, nonlinear optimization, and relaxation methods applied to power systems. - Modeling and implementing the multi-period SCOPF formulation with the integration of renewable and storage resources. - Developing and testing relaxation and penalization modules for voltage, power flow, and generation ramping constraints. - Performing simulations on IEEE systems (9-, 30-, 118-, and 300-bus), assessing performance, scalability, and computation time. - Analyzing and comparing results with classical methodologies, quantifying efficiency improvements. - Preparing technical reports and scientific papers, as well as presenting results in scientific publications.
Minimum profile required
- Basic knowledge of mathematical optimization and power systems;- Fundamental understanding of Nonlinear Programming (NLP) and Optimal Power Flow (OPF);- Programming skills in Python;- Fluency in English (written and spoken);- Strong analytical and problem-solving skills in applied research contexts.
Preference factors
- Experience in mathematical optimization and nonlinear programming; - Knowledge of power system planning and operation, with an emphasis on optimal power flow and SCOPF; - Experience in Python programming; - Analytical skills and ability to interpret complex results in contexts of computational efficiency and scalability; - Good scientific communication and teamwork skills in applied research environments.
Application Period
Since 23 Oct 2025 to 05 Nov 2025
[Open soon]
Centre
Power and Energy Systems