Research Engineer II – Bulk Power System Modeling

Pacific Northwest National Laboratory•Portland, OR

10h

About The Position

Pacific Northwest National Laboratory (PNNL) is seeking a creative and interdisciplinary Power Systems Research Engineer to conduct applied research in bulk electric system modeling, transmission planning, and grid analytics. This role will involve developing and applying power-flow, contingency-analysis, transfer-analysis, and optimization methods to evaluate current and future transmission system performance under changing generation, load, and infrastructure conditions. The position will contribute to nationally significant studies supporting grid reliability, resilience, and energy transition objectives. The work includes building and using research-grade software workflows, automating commercial and open-source power-system simulation environments, analyzing large-scale transmission planning cases, and translating technical findings into actionable insights for DOE, utilities, system operators, and other stakeholders. The staff member will work in interdisciplinary teams spanning power systems, software engineering, data science, and applied mathematics. This position is intended for a Level 2 researcher who can independently execute well-defined technical tasks, contribute to study design, document methods and results, and grow into leadership of large tasks, projects, or focused research components.

Requirements

BS/BA and 2 years of relevant experience OR MS/MA OR PhD

Nice To Haves

Foundational knowledge of electric power systems, including transmission planning, power-flow analysis, contingency analysis, renewable integration, or related grid operations concepts.
Demonstrated programming experience in Python, MATLAB, Julia, C++, C#, or comparable languages for engineering analysis, automation, modeling, or data processing.
Ability to work collaboratively in multidisciplinary research teams and communicate technical results through written reports, presentations, or publications.
Graduate-level training or research experience in electrical engineering with emphasis in power systems, transmission planning, renewable energy integration, machine learning, optimization, or related areas.
Experience using or automating transmission analysis tools such as PowerWorld, PSS/E, PSLF, OPAL-RT/RT-LAB, MATLAB/Simulink, AVEVA PI, or comparable modeling and simulation platforms.
Hands-on experience conducting steady-state contingency analysis, outage studies, transfer analysis, transient stability studies, or power-flow studies on bulk electric system models.
Experience developing software tools that automate power-system simulations, manage large study runs, process simulation outputs, or create reproducible analysis pipelines.
Knowledge of optimization methods relevant to power systems, including economic redispatch, optimal power flow, transmission upgrade screening, or related planning applications.
Familiarity with inverter-based resources, renewable integration, energy storage, microgrids, grid-forming and grid-following controls, or dynamic load modeling.
Experience applying machine learning or deep learning methods to power-system problems, such as dynamic model parameterization, forecasting, screening, or surrogate modeling.
Experience with large-scale regional or interregional transmission studies, offshore wind transmission studies, reliability or resilience analyses, or national-scale grid modeling efforts.
Ability to develop clear technical visualizations, one-line diagrams, dashboards, or other communication products that support engineering decision-making.
Strong technical writing and communication skills, including experience preparing research presentations, sponsor deliverables, conference papers, theses, or peer-reviewed manuscripts.
Ability to thrive in an applied research environment with evolving study assumptions, multiple simultaneous projects, and collaboration across organizations.

Responsibilities

Develop, run, and interpret bulk power system studies, including steady-state power flow, N-1 and selected higher-order contingency analysis, transfer capability analysis, congestion and overload assessment, and mitigation strategy evaluation.
Design, implement, and maintain Python-based workflows that automate power-system simulation tools such as PowerWorld, PSS/E, PSLF, or comparable platforms for large-scale planning and operations studies.
Contribute to transmission planning studies involving renewable and offshore wind integration, interregional transfer capability, resource deliverability, transmission element upgrades, and grid resilience.
Apply optimization, data-driven modeling, and machine learning techniques to power-system planning problems such as economic redispatch, optimal power flow, upgrade screening, dynamic model parameterization, and uncertainty analysis.
Develop and validate reusable software tools, scripts, models, and visualization products that improve study reproducibility, scalability, and stakeholder understanding.
Analyze large and complex power-system datasets, including planning cases, contingency results, outage scenarios, time-series measurements, and simulation outputs.
Collaborate with interdisciplinary teams and external partners, including national laboratories, DOE sponsors, utilities, independent system operators, universities, and industry stakeholders.
Prepare technical reports, presentations, peer-reviewed publications, and sponsor-facing briefings that clearly communicate methods, assumptions, findings, and limitations.
Contribute to proposal development, scoping of new research directions, and the maturation of analytical capabilities aligned with DOE and PNNL mission areas.
Work effectively in a team environment while independently managing assigned tasks, meeting project milestones, and following PNNL operational, safety, cybersecurity, and project management requirements.