GE Vernova – Advanced Predictive Controls Intern

Job Description Summary

Job Description

Collaborate with GE Vernova’s Controls & Electrical Systems teams and MIT partners to design and implement innovative control strategies for variable grid strength and dynamic load demands.
Intern 1 (Grid/Controls – load flow, parameter estimation, scenarios)
- Grid modeling (in GE PSLF)and studies: Build and validate a power system model; run ≥10 load-flow and dynamic scenarios (varying SCR, renewables 20–80%, AI DC step/ramp loads). Outcome: quantified voltage profiles, congestion, losses, and stability margins.
- Parameter estimation: Identify key plant/control parameters (governor, AVR, PSS) from operational/PMU data or simulations with ≤5–10% error (NRMSE ≥0.9). Deliver a calibrated model with uncertainty bounds.
- Control strategy prototype: Design and simulate an adaptive/predictive control update that improves frequency/voltage recovery time by ≥20% and limits overshoot to ≤5% across scenarios.
Scenario playbook: Produce a controls adaptation playbook for weak-grid and high-ramp AI load events, with trigger conditions, setpoint/limit adjustments, and rollback criteria.

Intern 2 (ML/System ID – data-driven modeling, predictive control)
- Data pipeline: Curate a clean, labeled dataset (signals, events, load profiles); document data quality metrics (missingness, latency, drift).
- System identification/modeling: Develop and validate a predictive model (e.g., state-space/N4SID, ARX, or ML) with ≤5–10% MAPE on key outputs (e.g., bus voltage, frequency, torque) and calibrated time constants.
- Predictive control prototype: Implement an MPC or equivalent controller using the learned model; demonstrate closed-loop stability and constraint handling with control latency ≤100 ms in simulation/HIL.
- Performance gains: Show ≥15–25% reduction in oscillations or curtailment during AI load ramps and improved stability margin (e.g., damping ratio +10%).
Explainability and governance: Provide feature importance/ablation results, model risk/assumptions, and retraining criteria for production handoff.

Project Outcomes:

Deliver validated models and control prototypes that address electrical and mechanical challenges from renewables and AI data center integration on power plants and grids, with clear evidence of stability/resilience gains.
Intern1 Deliverables: Model files and scripts, study report with KPIs, control design rationale, and a reproducible runbook.
Intern2 Deliverables: Trained models, evaluation notebooks, controller prototype, and concise documentation.

Shared outcomes (both interns): 
- Communication: Midterm and final presentations to internal stakeholders and MIT collaborators; 8–10 page tech note plus a 1-page executive summary.
- Integration: Joint demo where ML model informs scenario/control tuning in the grid model; side-by-side baseline vs. improved results.
- Documentation and handoff: Versioned artifacts, how-to guides, and issue/risk log to enable continuity after the internship.
- Stakeholder impact: Clear mapping from findings to operational decisions (setpoints, limits, protection coordination) and next-step recommendations.

Primary Skills Developed:

•    Lead the development of advanced controls and electrical system scenarios for variable grid strength adaptation.
•    Gain exposure to cutting-edge research in power system control, predictive modelling, and real-time system optimization.
•    Work directly with MIT and GE Vernova experts to address real-world challenges and deliver impactful solutions for the energy sector.
•    Build expertise in power generation operational challenges, control techniques, and next-generation energy system integration.

Basic Qualifications:

•    Currently pursuing a master’s in electrical engineering, Mechanical Engineering, Controls Engineering, Computer Science, or a related field.

•    Minimum of 4.0 GPA out of 5.0.

Desired Qualifications:

•    Foundational knowledge and Demonstrated interest on advanced control concepts & Load flow calculations for power systems (academic, research, or project-based).

•    Exposure to machine learning techniques applied to system modelling and control (coursework, academic projects, or research experience).
•    Strong analytical and problem-solving skills, with experience in data-driven modelling, simulation, or algorithm development as part of studies or projects.
•    Ability to work collaboratively in multidisciplinary and research-driven environments.
•    Proficiency in programming languages such as C/C++, Python, R, or similar, for algorithm development, data analysis, and simulation.

•    Exposure to power plant control systems, grid modelling, and turbine control operational challenges.
•    Familiarity with AI data Center load profiles and their impact on electrical grid and power plant operations.
•    Working knowledge of model-based engineering and real-world power system simulation tools.
•    Strong communication and presentation skills for cross-functional and academic collaboration.

Benefits Available to you:

Addressing the climate crisis is an urgent global priority, and at GE Vernova, we take our responsibility seriously. That is the singular mission of GE Vernova: to continue electrifying the world while simultaneously working to help decarbonize it. In order to meet this mission, we provide varied, competitive benefits to help support our workforce: Our Culture | GE Vernova (gecareers.com)

The pay for this position is $34/hr.

This position is also eligible for:

• Relocation Assistance: Co-op/Interns will be reimbursed for reasonable, proper, and documented expenditures incurred while initially reporting to work and returning to school/home upon completion of the assignment. Employees with a permanent address greater than 50 miles away from the work location are eligible.
• Housing Allowance: Co-op/Interns employees receive a weekly housing allowance to help off-set living expenses when the co-op/Intern’s permanent residence is at least 50 miles away from the work location.
• Employee Assistance Program, providing 24/7 confidential assessment, counseling and referral services
• GE Retirement Savings Plan (RSP) after their accumulated service reaches 90 days, and they meet any other eligibility requirements as defined in the plans. (Eligibility occurs on the 1st of the month following the 90th day.)

General Electric Company, Ropcor, Inc., their successors, and in some cases their affiliates, each sponsor certain employee benefit plans or programs (i.e., is a Sponsor”). Each Sponsor reserves the right to terminate, amend, suspend, replace, or modify its benefit plans and programs at any time and for any reason, in its sole discretion. No individual has a vested right to any benefit under a Sponsor’s welfare benefit plan or program. This document does not create a contract of employment with any individual.

Inclusion

At GE Vernova, we believe in the value of your unique identity, background and experiences. We are committed to fostering an inclusive culture, where everyone feels empowered to do their best work because they feel accepted, respected and that they belong.  Click here to learn more: https://jobs.gecareers.com/vernova/global/en/i-d-e

Additional Information