Schweitzer Engineering Laboratories (SEL) is looking to solve power system optimization and control problems using data driven techniques (AI/ML) for renewable power plants and grid interconnection studies
Requirements
- Experience with studies tools like PSSE, DigSILENT, MATLAB, PSCAD or RTDS
- Expertise knowledge in design verification studies like power system optimization, power system dynamic stability studies, and Grid interconnection studies for renewable power plants
- Knowledge of electric power system steady state and dynamics , Hardware In The Loop (HIL)
- Deep understanding of electric power system optimization and control
- Experience with AI and Machine Learning Applications in Power Systems
- Knowledge of advanced mathematical and system identification techniques
- Experience with conducting linear and nonlinear optimization techniques for solving power flow problems
Responsibilities
- AI and Machine Learning Applications in Power Systems
- Optimization and Control
- Advanced Mathematical and System Identification Techniques
- Conducting linear and nonlinear optimization techniques for solving power flow problems
- Conducting steady state and dynamic simulations to analyze the stability
- Assessing the feasibility and impact of connecting new generation sources (e.g., renewable energy) to the existing grid
- Designing HIL setups to test and validate control systems and protection schemes in a simulated environment
Other
- Willing to travel both domestically and internationally a minimum of 25% based on focus area
- PhD/master’s degree or equivalent experience
- Ability to work on global projects
- Confident to work on global projects
- Mentor and develop professional staff
