Skip to main navigation Skip to search Skip to main content

POSE: Phase I: Toward an Open-Source Ecosystem for Power Systems Research, Education, and Industry Applications

Project: Research

Abstract & Details

Description

Award ID: 2346213

Computer software is crucial for power systems engineering related to the power grid. As an infrastructure providing essential services, power networks are mission critical. In the design and analysis of power systems, simulations largely precede real-world experiments that are expensive and risk inherent. Although industry applications are centered around commercial software, open-source software is gaining popularity for quickly prototyping new solutions to emerging problems. This project will explore pathways for establishing and sustaining an open-source ecosystem to create advanced, robust, and flexible software for power grid applications. The project will bring together stakeholders to build a vision for the rapid translation of innovations by providing an open-source ecosystem that reduces effort duplication and promotes code reuse. The broader impacts include (1) accelerating the pace of innovation and technology translation for power systems engineering, and (2) engaging stakeholders in an open-source ecosystems that will contribute to industry software to enhance grid efficiency and resilience. In this project, the research team will conduct scoping activities for an open-source ecosystem (OSE) centered around the open-source ANDES software for power grid analysis. Specifically, the goals are to: (1) identify fundamental and critical needs in data, features, and packages to align the interests of potential contributors to the ecosystem, (2) create strategies and plans for high-impact activities to establish the OSE by attracting users and contributors and facilitating distributed development, (3) define an organizational structure for sustaining the OSE by empowering and incentivizing stakeholders, including users and contributors from academia, research laboratories and industry, and (4) identify long-term funding and industry engagement strategies that yield expanded user and contributor bases for sustained impacts. This project aspires to propel power system engineering toward a future where open-source collaboration unlocks innovation for energy applications. This project is jointly funded by the Established Program to Stimulate Competitive Research (EPSCoR) and the Pathways to Enable Open-Source Ecosystems (POSE) Program which seeks to harness the power of open-source development for the creation of new technology solutions to problems of national and societal importance. This award reflects NSF's statutory mission and has been deemed worthy of support through evaluation using the Foundation's intellectual merit and broader impacts review criteria.

NSF Program Director: Florence Rabanal
StatusActive
Effective start/end date06/15/2405/31/27

Funding

  • (POSE) NSF Pathways to Enable Open-Source Ecosystems: $299,606.00

Active Fiscal Year

  • FY2024
  • FY2026
  • FY2025
  • FY2027

Start Fiscal Year

  • FY2024

TIP Programs

  • (POSE) NSF Pathways to Enable Open-Source Ecosystems

Key Technology Areas

  • Advanced Energy and Industrial Efficiency Technologies
  • (confidence score: 100%)
  • Advanced Computing and Semiconductors
  • (confidence score: 83%)

Technology Foci

  • Advanced Energy Generation Technologies
  • (confidence score: 100%)
  • Advanced Transmission and Distribution systems
  • (confidence score: 100%)
  • Advanced Computer Software
  • (confidence score: 97%)

Congressional District at Award

  • District n. 03 of Oklahoma

Current Congressional District

  • District n. 03 of Oklahoma

United States

  • Oklahoma

Core Based Statistical Area (CBSA)

  • Stillwater, OK

County

  • County: Payne, OK

EPSCoR Jurisdiction

  • Yes

Fingerprint

Explore the research topics touched on by this project. These labels are generated based on the underlying awards/grants. Together they form a unique fingerprint. Learn more about Elsevier's Fingerprint Engine here: https://beta.elsevier.com/products/elsevier-fingerprint-engine