Graduate (Summer) Intern - Distributed Energy Systems

Job Description

The Grid Automation and Control group works on developing optimization and control models of power systems, distributed energy resources (DERs), and validating controls using hardware-in-the-loop testing facility. We are looking to hire an intern to work on a project that focusing on developing optimal sensor placement models to improve the visibility of distribution systems with high penetration of grid-edge DERs. The intern is expected to work closely with project team members on the following tasks:

• Analyze utility feeder data
• Analyze grid topologies and data corrections
• Quantify grid visibility criteria and conditions
• Determine best locations for sensor placement and communication design
• Develop and train machine learning model to estimate and forecast grid edge conditions
• Support grid applications such as DER aggregation and voltage control.

Basic Qualifications

Must be enrolled as a full-time student in a Bachelor's, Master's or PhD degree program, or graduated in the past 12 months from an accredited institution. Candidates who have earned a degree may work for a period not to exceed 12 months. Must have a minimum of a 3.0 cumulative grade point average.

Please Note:

• You will need to upload official or unofficial school transcripts as part of the application process.
• If selected for position, a letter of recommendation will be required as part of the hiring process.
• Must meet educational requirements prior to employment start date.

Additional Required Qualifications

• Demonstrated knowledge and experience with machine learning and deep learning, power system data analytics

Preferred Qualifications

• Distribution system modeling
• Distribution system monitoring and forecasting
• Detection and estimation methodologies
• Experience with real-world smart meter data processing and analytics
• Experience with CYME, OpenDSS, or similar distribution simulation packages
• Experience with machine learning