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
Applications
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.