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Collaborative Research
IERE’s Collaborative Research is a framework that enables participating members to contribute their technological knowledge, expertise, and personnel. Founded on the principle of sharing both costs and resources, it ensures that all members receive fair and balanced benefits from the outcomes.
Archive List
Artificial Intelligence
The goal of this initiative is to develop Artificial Intelligence (AI) programs that address the practical challenges faced by members. Each project team consists of a Data Provider and an Application Developer. The Data Provider contributes relevant datasets, while the Application Developer builds and trains AI models to analyze the data and deliver actionable insights or solutions. This collaborative framework enables members to benefit from advanced AI technologies, even if they lack in-house development capabilities.
- 2022–2024
- 2nd Round (Leader: E.ON and CLP)
- Project Details
- Four Use Cases Tackled:
- ‑ Object detection of pole mounted switches
- ‑ T&D Image Object Detection Use cases
- ‑ Predictive maintenance and health monitoring of underground cable
- ‑ Load forecasting of feeder
- 7th IERE Webinar on AI Collaboration Project (2nd Round) (March 7, 2024)
- Newsletter No. 124: 7th IERE Webinar on AI Collaboration Project (2nd Round)Members Only
- 2020–2022
- 1st Round (Leader: CLP and E.ON)
- Project Details
- Four Use Cases Tackled:
- ‑ Defect detection of high voltage electric transmission insulators
- ‑ Detection of abnormal signs in hydropower plants
- ‑ Short term load forecasting
- ‑ Optimum Pole Transformer Capacity
- 5th IERE Webinar on AI Collaboration Project (1st Round) (March 24, 2021)
- Newsletter No. 112: Summary of 5th IERE Webinar on AI Project
Members Only
Artificial Intelligence—In-depth Research Following Technology Foresight 2017 Project
Based on feedback from the TF2017 initiative, the IERE Board recommended undertaking in-depth research on Artificial Intelligence (AI) technologies, entrusting this work to young engineers and researchers within the IERE community.
- 2017–2018
- Capability of AI (Leader: Professor TERANO, Tokyo Institute of Technology)
- The selected participants engaged in discussions on AI, examining available tools, current limitations, and related challenges. They also provided recommendations on the most effective ways to apply these technologies in relevant fields.
- Executive Summary (April 16, 2019)
- Main Report (March 5, 2019)Members Only
- Supplementary Part (March 5, 2019)Members Only
- Presentation Videos & Slides: “In-depth research on Artificial Intelligence (AI)”Members Only
—LEE Chuk Wing, CLP, Kyoto Forum (May 2018)
Energy Storage
In a survey conducted among IERE members in May 2019, energy storage was selected as the next candidate for in-depth research following TF2017, after artificial intelligence, which had already been launched. IERE then decided to take this further by initiating it as a direct collaborative research project.
- 2021–2023
- Battery Energy Storage (Leader: SwRI)
The objectives are to develop a battery degradation model under “composite grid duty”—a mix of real-world operational modes such as charge/discharge cycling, peak shaving,
and frequency regulation—and to assess the associated risks of battery fire and explosion.
Project Details
Papers presented at the IEEE SysCon 2023 in Vancouver, Canada
- ・Statistical Characterization of Battery Energy Storage Systems in Mixed and Stacked Service Electrical Grid Operations | IEEE Conference Publication | IEEE Xplore
- ・Pseudo Electrochemical Impedance Spectroscopy Method for In-Situ Performance and Safety Assessment of Lithium-Ion Battery Energy Storage Systems for Grid-Scale Applications | IEEE Conference Publication | IEEE Xplore
- ・Extension of Single Particle Model with electrolyte and Temperature (SPMeT) for
Real-Time Performance and Safety Monitoring of Battery Energy Storage Systems (BESS) in Grid Service | IEEE Conference Publication | IEEE Xplore
- Presentation Videos &
Slides : “Energy Storage Project for Electric Grid”
Members Only
—Jayant SARLASHKAR, SwRI, San Antonio Workshop (May 2024)
- Presentation Slides
: “Estimating and Managing Degradation of Li-Ion BESS Under Value-Stacked Duty Cycles in Electric Grid
—Jayant SARLASHKAR, SwRI, 9th IERE Webinar (April 2025)
Hydrogen—In-depth Research Following Technology Foresight 2017 Project
Based on a questionnaire conducted in May 2019 as part of the IERE Technology Foresight project, around ten member companies expressed interest in hydrogen technologies, which were subsequently designated as a focus area for in-depth research within the IERE community.
- 2019–2020
- Scouting Phase (Leader: RWE TI)
- The primary objective of this phase was to facilitate information sharing on hydrogen and promote collaboration among members. Specifically,
the aim was to provide an international perspective on the current status of technologies, markets, and Collaborative Research activities,
while identifying the most relevant combinations of technologies and market applications. Project Details
- Summary Report Slides (March20, 2020) for Public and
IERE Members
Members Only
- （Participating members have already received the report individually.）
- Presentation Videos & Slides: “IERE-RWE Technology Scouting project on Hydrogen” Members Only
—Max VOSS, RWE Generation, 1st IERE Webinar (September 23, 2020)
- Newsletter No. 103: Summary of 20th General Meeting and 1st Webinar on Hydrogen
Members Only
Power Transformer
The end of a power transformer’s service life is closely linked to the condition of its insulation paper. Traditionally, the concentrations of carbon monoxide, carbon dioxide, and furan compounds (such as 2-furfuraldehyde) have been used as diagnostic indicators. However, these methods have inherent limitations. In recent years, methanol has emerged as an additional ageing marker for assessing insulation paper, attracting considerable industry attention and prompting active research worldwide.
- 2019–2024
- Phase 2 (Leader: ENGIE)
- The objective of this project is to analyze a collection of specific winding insulation paper material extracted during post-mortem dismantling of
selected power transformers and to establish a robust degradation model by correlating the concentrations of
temperature-corrected methanol-in-oil with the real winding paper degradation. Project Details
- Newsletter No. 120: Progress Report Meeting on Transformer Life Diagnosis Joint Research
Members Only
- 2012–2015
- Phase 1 (Leader: Hydro-Québec)
- In 2012, IERE launched a multinational Collaborative Research program on transformer insulation paper diagnostics using methanol as a novel ageing marker. Over a thousand transformers were tested across manufacturers and utilities, showing methanol appears earlier than conventional markers, enabling more sensitive fault detection. Ethanol also shows promise for high-temperature faults, while maintenance can “reset” readings, highlighting the need for multiple indicators.
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Final Report; Application of Methanol as an Innovative Aging Marker for Transformer Insulating-Paper Diagnosis (January 15, 2017)
Members Only
Other Efforts
Archive List
