T

TAR

Off-grid power plants for AI data centers

Senior Engineer - Power Systems Controls

Power Systems EngineeringConfirmed live in the last 24 hours
Full-timeAustin, TX, USANo salary listedIn-person

About the Job

Requirements

  • A Master of Science in Electrical Engineering, Power Systems, Power Electronics, or Controls with at least 5 years of relevant experience, or a Ph.D. in one of these fields with 1 to 3 years of relevant experience.
  • Hands-on PSCAD/EMTDC experience building plant-level models of inverter-based resources such as BESS, PV, or wind, including integrating OEM black-box models and running fault, ride-through, and dynamic studies.
  • Hands-on real-time HIL experience, preferably with Typhoon HIL.
  • Working knowledge of grid-forming versus grid-following inverter control, including droop, virtual synchronous machine, PLL-based current control, current limiting, and behavior during faults and load steps.
  • Ability to critically read OEM control block diagrams and model documentation, and explain why EMT results do or do not match expected behavior.
  • Understanding of islanded and low-fault-current protection, including why conventional overcurrent coordination becomes unreliable at 1.1 to 1.5 times rated fault current.
  • Proficiency in Python for study automation and data analysis.
  • Experience writing clear test procedures and technical study reports.
  • Experience with MATLAB/Simulink is a plus.
  • Extreme attention to detail and a bias for speed and rapid iteration.

Responsibilities

  • Build, maintain, and version-control the plant-level PSCAD EMT model covering grid-forming BESS PCS, PV inverters, MV collection, transformers, cables, grounding, and representative data center loads, including UPS, rectifier front ends, and load-step profiles.
  • Integrate OEM-supplied black-box and user-defined PSCAD models; check numerical stability, time-step sensitivity, initialization, and fidelity to stated OEM control behavior; document gaps and request corrected or better-documented models from OEMs.
  • Run islanded EMT studies covering black start and energization, including transformer inrush and cable charging; large load steps and load rejection; fault ride-through; fault current contribution in the 1.1 to 1.5 times rated range; unbalanced faults; and protection operation.
  • Study inverter-to-inverter and control interactions, including GFM droop and virtual-inertia sharing, GFM/GFL coexistence, sub-synchronous and harmonic oscillations, weak-grid and low-SCR behavior, and impedance-based stability screening.
  • Verify that protection settings remain selective across every operating mode and provide EMT evidence for differential, communication-assisted, or adaptive schemes.
  • Automate study cases and post-processing in Python, including batch runs, parameter sweeps, pass/fail criteria, plots, and reports.
  • Build and maintain real-time Typhoon HIL models of the islanded plant, sized and partitioned for available HIL hardware while preserving important dynamics.
  • Run controller-HIL testing of the microgrid controller (MGC/PPC), EMS functions, and, where available, OEM PCS controllers or replica panels.
  • Write HIL test procedures and automate them with Typhoon's Python API and TyphoonTest IDE for black start, mode transitions, load steps, loss of a BESS block, communications loss, setpoint dispatch, and protection trips.
  • Correlate HIL results with the PSCAD offline model and track which differences result from model reduction and which reveal real control issues.
  • Run regression testing on every MGC and OEM firmware release before it reaches site and maintain a traceable record of test results.
  • Turn EMT and HIL test cases into commissioning and acceptance test plans for the pilot and later sites.
  • Support energization, bring-up, and acceptance testing on site; capture field data and use it to recalibrate models.
  • Troubleshoot field events by reproducing them in PSCAD or on the HIL bench.
  • Act as the technical point of contact with OEMs and the EMT study consultant on model quality, study assumptions, and results; critically review external study reports.
  • Feed EMT and HIL findings into the MGC and EMS functional specifications, control philosophy, design reviews, and FMEA.
  • Work closely with the controls and automation engineer, protection engineers, and MGC and EMS vendors to ensure there are no gaps between vendors.

Desired Qualifications

  • Direct islanded, off-grid, or behind-the-meter microgrid experience, especially black start of an inverter-dominant system.
  • EMT modeling of utility-scale PV+BESS powering a large, fast-changing load such as a data center.
  • Field-validated GFM behavior, fault response, and inverter-to-inverter interactions in a real IBR-dominant plant.
  • Typhoon HIL certification or experience building automated HIL regression pipelines, including CI/CD for controls.
  • Controller-HIL or power-HIL testing of commercial microgrid controllers or BESS PCS controllers.
  • Experience with impedance-based or small-signal stability methods, including frequency scans and Nyquist criteria, alongside EMT.
  • Familiarity with PowerFactory, PSS/E, or ETAP for load flow, short-circuit, and protection studies.
  • C/C++ or Simulink Embedded Coder experience for controller code deployed to HIL or embedded targets.
  • Experience writing and executing commissioning test plans and troubleshooting bring-up in the field.
  • Experience in a test-like-you-fly culture where validation rigor is the norm, such as Tesla Energy, Fluence, SpaceX, Array, Nextracker, or comparable organizations.

About the Company

TAR

Off-grid power plants for AI data centers

TAR builds and operates behind-the-meter power plants for AI data centers that cannot wait out a utility interconnection queue. The company designs islanded microgrids pairing solar, battery storage, and gas peakers, then manufactures, installs, and runs them, handling power electronics, microgrid controls, dispatch software, and site construction in-house. Compared with grid interconnection, which can take years to clear, an off-grid plant can be sited and energized on the developer's own schedule, and TAR says it is working with a large compute provider and targets 5 GW by 2028. Its goal is to remove power as the constraint on AI buildout by owning generation end to end.

Company size
11-50
Company stage
Series A
Total funding
$147M
Headquarters
Texas, United States
Founded
2025

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