The increasing reliance on inverter-based resources in modern electricity systems is creating a critical dependence on information that goes beyond traditional physical-state observability. To address this shift, researchers Alireza Ganjovi and Saman A. Gorji have developed the Decision-Useful Observability Index, or DUOI. This new framework is designed to assess whether available information is adequate for specific planning, operational, or governance decisions.
The DUOI framework evaluates information adequacy across six distinct dimensions: technical, data, operational, economic, consumer-risk, and adaptive-governance capability. By applying this multi-dimensional approach, the researchers aim to move beyond simple physical measurements to a more nuanced understanding of information capability. The framework was tested using publicly available technical, planning, and regulatory evidence from six applications within the Australian electricity sector. This application of the DUOI provides a practical demonstration of how the index can be used to diagnose information gaps in real-world energy infrastructure.
An indicator-level evidence-to-score audit was conducted to generate dimension scores for the Australian applications. The resulting dimension scores ranged from approximately 0.45 to 0.88, highlighting significant variations in information capability across different aspects of the grid. When these dimensions were combined using an equal-weight additive method, the overall DUOI scores ranged from approximately 0.56 to 0.72. These results demonstrate that information capability is unevenly distributed across both applications and dimensions, indicating that some areas of the system are better supported by data than others.
The study notes that the six-factor product used in the framework is intrinsically scale-compressed. Consequently, multiplicative scores are not directly compared with additive scores to avoid misleading interpretations. Instead, bottlenecks are identified by examining the minimum dimension score for each application. This minimum score is interpreted alongside the full dimension profiles and a scale-comparable geometric mean.
A key finding from the Australian applications is that the dimension most closely associated with an application’s specific purpose is not necessarily its principal information bottleneck. The study emphasizes that information can be available yet remain decision-inadequate due to limitations in timeliness, accessibility, interoperability, attribution, or institutional feedback. These non-technical factors are crucial for ensuring that data can actually be used to make effective decisions.
The DUOI framework extends the concept of observability from physical-state measurement to decision-specific information capability. By doing so, it provides an auditable basis for tracing documentary evidence through indicator-level scoring to dimension-level diagnosis. This auditability is essential for identifying targeted improvements in information infrastructure and governance.
The DUOI offers a structured way to evaluate this information quality, ensuring that it meets the specific needs of various decision-making processes. By focusing on decision-usefulness, the framework aligns technical observability with practical operational and governance requirements.
The application of the DUOI to the Australian electricity sector provides valuable insights into the current state of information infrastructure in inverter-heavy grids. The uneven scores observed across the six applications suggest that there is significant room for improvement in several dimensions. By identifying these gaps, the study provides a roadmap for enhancing the decision-usefulness of observability data.
The DUOI framework offers a robust and auditable tool for assessing information capability in these complex systems.
Subject of Research: Development of the Decision-Useful Observability Index for inverter-dominated electricity systems
Article Title: Decision-useful observability for inverter-dominated electricity systems: framework development and Australian applications
Article References: Ganjovi, A., & Gorji, S. A. (2026). Decision-useful observability for inverter-dominated electricity systems: framework development and Australian applications. Energy Informatics. https://doi.org/10.1186/s42162-026-00699-6
Image Credits: AI Generated
DOI: 10.1186/s42162-026-00699-6
Keywords: electricity systems, inverter-based resources, observability, energy informatics, grid operations, data quality, decision-making, Australian energy sector, Decision-useful, inverter-dominated, electricity, systems
News Source: Denise Maddox. (October 28, 2026). New Index Measures Information Gaps in Inverter-Heavy Power Grids. Scienmag.
