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Last Updated on 31 Oct 2024 at 5 PM
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Idaho falls Idaho

Open-Source Software: Unlocking Economic Insights into Nuclear-Renewable Integrated Energy Systems with HYBRID

Details

Solicitation ID CW-19-15
Posted Date 31 Oct 2024 at 5 PM
Response Date 15 Mar 2026 at 3 PM
NAICS Category
Product Service Code
Set Aside No Set-Aside Used
Contracting Office Battelle Energy Alliance–doe Cntr
Agency Department Of Energy
Location Idaho falls Idaho United states 83415

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Ford Motor Company

Pleasanton Livonia Allen park Dearborn Detroit Washington

National Industries For The Blind

Wayne Earth city Alexandria

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Frankfurt am main Isando Washington Arlington

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Unlocking Economic Insights into Nuclear-Renewable Integrated Energy Systems with HYBRID

Introduction

In the evolving landscape of energy production, the HYBRID simulation framework emerges as a pivotal tool for the economic assessment of Nuclear-Renewable Integrated Energy Systems (N-R IES). It uniquely combines stochastic analysis, probabilistic optimization, and high-fidelity physical modeling to provide unparalleled insights into the economic performance of these complex systems.

Background

The integration of variable renewable energy sources into the electric grid introduces significant challenges for traditional energy dispatch and capacity planning. The limitations of existing software, relying on deterministic linear programming, fall short in capturing the intricate dynamics and uncertainties inherent in N-R IES. This gap necessitates a more sophisticated approach to accurately evaluate economic viability, especially under stochastic conditions such as fluctuating electricity demand and renewable energy availability.

Software Description

HYBRID leverages the Idaho National Laboratory's (INL) RAVEN framework, its CashFlow plugin, and the Modelica language to offer a robust toolset. It enables users to generate stochastic time series, apply probabilistic analysis, and optimize N-R IES operations and planning. The toolset includes a comprehensive library of Modelica models and RAVEN workflows that map physical performance to economic outcomes, allowing for the assembly and evaluation of various energy system configurations under stochastic conditions.

Advantages

  • Accurate Economic Viability Assessment: Incorporates stochastic elements and high-fidelity physical simulations for precise economic analysis.
  • Comprehensive Toolset: Offers a complete suite of tools for generating stochastic time series, probabilistic analysis, and optimization.
  • Flexible System Modeling: Allows for the integration of diverse energy sources and systems, including nuclear, renewables, and storage.
  • Open Source Collaboration: Facilitates broad access and collaborative development across national laboratories, academia, and industry.
  • Time and Resource Efficiency: Reduces the need for developing ad-hoc solutions, saving valuable time and resources.

Applications

  • Capacity Planning and Dispatch Optimization: Enables energy providers to optimize N-R IES configurations for cost-effective energy dispatch and capacity planning.
  • Economic Analysis in Academia and Research: Supports universities and research institutions in conducting economic analyses of N-R IES.
  • Policy and Decision Support: Aids policymakers and energy planners in understanding the economic implications of integrating renewable and nuclear energy sources.

Discover how HYBRID can transform your approach to the economic assessment of Nuclear-Renewable Integrated Energy Systems. Visit our website to explore the toolset, access resources, and join the community of innovators advancing the future of integrated energy solutions.

This software is open source and available at no cost. Download now by visiting the product's GitHub page.

INL’s Technology Deployment department focuses exclusively on licensing intellectual property and partnering with industry collaborators capable of commercializing our innovations. Our goal is to commercialize the technologies developed by INL researchers. We do not engage in purchasing, manufacturing, procurement decisions, or providing funding. Additionally, this is not a call for external services to assist in the development of this technology.