On February 24, researchers Jackie Huynh (PNNL) and Yuliya Preger (SNL) delivered a requested presentation on the “Role of Energy Storage in AI Data Centers” at the quarterly meeting of the Federal Consortium for Advanced Batteries (FCAB). FCAB brings together program managers from dozens of federal agencies from Departments including Energy, War, Commerce, and State to accelerate the development of a domestic industrial base for advanced batteries. FCAB sought insights on how data center growth may affect U.S. energy storage demand. Over 50 federal employees and program managers attended the call.

This material is based upon work supported by the U.S. Department of Energy, Office of Electricity (OE), Energy Storage Division.

Henry Guan, Tim Wilcox, Waylon Clark, and Charlie Hanley from Sandia National Laboratories attended the ribbon cutting event on February 10 for a battery energy storage project in Baton Rouge, Louisiana. The project, located at the IBEW Local 995 facility in Baton Rouge, is one of 20 microgrids, called Community Lighthouses, that have been installed around the state of Louisiana. This project was supported by Sandia’s Energy Storage Demonstrations team through the Energy Storage for Resilience Hubs (ES4RH) program. The team provided technical support for project deployment as well as cost share funding for the project. This project is one of seven Lighthouses that Sandia is supporting through the ES4RH program. The event was well attended and had participation from State and local officials (State Senator and State Representative, Mayor, City Council members), Eric Hsieh from DOE Office of Electricity, and local organizations and community members. Press was also present and the event was on the local news. The IBEW facility serves as a critical staging, coordination, and recovery center for linemen during disasters, improving statewide emergency response and grid restoration efforts. The project enhances the facility’s resilience and ability to operate during disasters through use of battery energy and distributed generation. It also demonstrates affordability and cost effectiveness by offsetting site usage when not being used for resilience. The first 17 operational lighthouses have already generated nearly $200k in gross utility savings.

This material is based upon work supported by the U.S. Department of Energy, Office of Electricity (OE), Energy Storage Division.

The online monitoring of battery energy storage systems (ESSs) is crucial to detecting sensor anomalies that could have detrimental impacts on the system’s safety, reliability, and availability. Model-based anomaly detection mechanisms could be integrated into battery management systems (BMSs) with modeling and estimation capabilities. However, previous model-based anomaly detection mechanisms have been tested only on small stacks of batteries or single cells.

On January 30, 2026, the article title “Scaling Up Online Model-Based Anomaly Detection Methods for Use in Large Battery Stacks” by Victoria A. O’Brien and Rodrigo D. Trevizan was published in the IEEE Industry Applications Magazine. The article follows O’Brien’s successful presentation of the paper “A Comparison of Online Model-Based Anomaly Detection Methods for a Lithium-Ion Battery Cell” at the 2024 International Symposium on Power Electronics, Electrical Drives, Automation and Motion (SPEEDAM).  The article addresses a critical research gap by comparing four model-based anomaly detection methods for simulated stacks of 12 and 36 series-connected battery cells. The work evaluates the viability of four model-based anomaly detectors: the Chi-Squared test, Cumulative Sum algorithm (CUSUM), additive Chi-Squared test (ACST), and mean Shewhart control chart. The comparison focuses on false positive rates, detection accuracy, and computational burden. The CUSUM algorithm demonstrated superior performance, achieving a false positive rate of 0%, a detection accuracy of 99.6%, and maximum computational times of 0.0162 seconds and 0.0909 seconds per iteration for the 12-cell and 36-cell stacks, respectively. This study suggests that model-based anomaly detection algorithms can effectively scale for high-voltage battery management system applications, offering high accuracy, low false alarms, and manageable computational demands. The IEEE Industry Applications Magazine publishes articles that advance technological innovation and practical applications within industry. Research featured in the magazine reaches beyond the academic community to industry professionals.

Citation: V. A. O’Brien and R. D. Trevizan, “Scaling Up Online Model-Based Anomaly Detection Methods for Use in Large Battery Stacks: Addressing Challenges in Online Monitoring of Battery Systems,” in IEEE Industry Applications Magazine, doi: 10.1109/MIAS.2025.3648148. [Online] Available: https://ieeexplore.ieee.org/document/11366229

This material is based upon work supported by the U.S. Department of Energy, Office of Electricity (OE), Energy Storage Division.

On January 28, Sandia’s Energy Storage Demonstration Projects team was invited to Albuquerque Public Schools’ Water and Energy Conservation Committee meeting where APS celebrated the completed commissioning and full operation of the Atrisco Heritage Academy High School Battery Energy Storage System project. Sandia was recognized for their partnership throughout the project and Sandia’s Henry Guan attended the celebration. The project is a battery energy storage deployment project installed to demonstrate energy savings and affordability through the use of batteries for peak demand reduction. The battery, in combination with distributed generation will maintain the school’s peak demand below 500 kW, resulting in a project savings of over $3.5M over the life of the project. Sandia partnered with APS on the technoeconomic evaluation of battery energy storage; engineering support in system procurement, design, and commissioning; and cost share funding.

This material is based upon work supported by the U.S. Department of Energy, Office of Electricity (OE), Energy Storage Division.

On January 20, 2026, Sandia researchers Niranjan Bhujel and Ujjwol Tamrakar published the chapter titled “Optimization Framework for Frequency and Parameter Estimation in Low-Inertia Power Systems for Fast-Frequency Support” in the book “Power System Inertia, Strength, and RoCoF.” The chapter is based on the work performed by Niranjan Bhujel and Ujjwol Tamrakar on the development of fast frequency support and inertia estimation of microgrids. Microgrids can strengthen grid resilience and help mitigate disturbances by operating while the main grid is down and functioning as a grid resource for faster system response and recovery. However, microgrids can experience higher frequency excursions —  temporary deviations in grid frequency caused by a mismatch in electricity demand and supply — due to low inertia. The developed frequency support approach reduces frequency excursion which helps to increase power quality in the microgrids. Further, inertia estimation helps monitoring the system. The book chapter can be useful for research working on microgrids stability, power quality, fast frequency support, etc.

Citation: D. A. Copp, N. Bhujel, U. Tamrakar, and R. Tonkoski, “Optimization framework for frequency and parameter estimation in low-inertia power systems for fast-frequency support,” in Power System Inertia, Strength, and RoCoF, F. Shahnia, Y. Liu, and P. A. Pegoraro, Eds. Singapore: Springer Nature Singapore, 2026, pp. 115–139, ISBN: 978-981-95-3708-2. DOI: 10.1007/978-981-95-3708-2_5. [Online]. Available: https://doi.org/10.1007/978-981-95-3708-2_5.

This material is based upon work supported by the U.S. Department of Energy, Office of Electricity (OE), Energy Storage Division.

On January 5, 2026, Dilip Pandit and a team of researchers at Sandia National Laboratories released a Python-based open source software tool called QuESt PCM: A Production Cost Modeling Tool with High-Fidelity Models of Energy Storage Systems, now available on GitHub. This tool is designed for evaluating power system operations with advanced modeling of diverse energy storage technologies. Production cost models (PCM) are computational tools that simulate power system operations by optimizing the commitment and dispatch of generation resources to meet demand at least cost, while respecting technical and reliability constraints. QuESt PCM is an open-source power system production cost modeling tool designed for high-fidelity representation of energy storage systems (ESS). Built in Python, it uses the Pyomo optimization interface to formulate technology-specific storage models and to capture diverse storage operational constraints. The tool also models market participation capabilities of storage systems, helping assess their impacts on day-ahead and real-time price signals. This tool is part of QuESt 2.0: Open-source Platform for Energy Storage Analytics.

Accurate analysis of system operations under a diverse portfolio of energy storage technologies and their varying market participation strategies requires detailed techno-economic modeling. QuESt PCM provides a market simulation framework that enables users to represent different storage technologies with high fidelity and evaluate their operational behavior across multiple market participation modes. By capturing the technical constraints and economic drivers of storage, the tool supports a comprehensive assessment of power systems with significant storage penetration. QuESt PCM can assist regulators, utilities, state agencies, and independent system operators in evaluating long-term storage investments that are both economically viable and aligned with evolving grid reliability and flexibility needs. As an open-source platform, it also serves the broader research community by enabling transparency, customization, and continued methodological advancement.

This material is based upon work supported by the U.S. Department of Energy, Office of Electricity (OE), Energy Storage Division.

On January 5 and 6, 2026, several Sandians participated in the 14th IEEE Electrical Energy Storage Applications and Technologies (EESAT) conference held at the Omni Tucson National Resort & Spa in Tucson, Arizona. Rodrigo Trevizan served as the Technical Chair and moderated Technical Session 5 – Electric Vehicle Integration. David Rosewater acted as the webmaster for the conference and moderated Technical Session 4 – Energy Storage Safety and Security. Ujjwol Tamrakar moderated Technical Session 2 – Energy Storage Performance, while Raymond Byrne moderated Technical Session 3 – Energy Storage Planning and Operation. Will McNamara moderated both Panel Session 1 – Energy Storage in Arizona: Impacts of Data Centers and AI and Panel Session 2 – Perspectives on LDES. Additionally, Daniel L. Villa, David Rosewater, Dilip Pandit, and Cody Newlun gave oral and poster presentations at the conference.

Will McNamara organized the panel “Energy Storage in Arizona: Impacts of Data Centers and AI” which included Kate Gallego, Mayor of Phoenix; Lea Marquez Peterson, Arizona Corporation Commission; Brian Sherman, Chief Executive Officer – The NSF Futures Engine in the Southwest; Blaise Caudill, Deputy Director of the Governor’s Office of Resiliency and Energy Policy Advisor; and Chris Lindsey, Tucson Electric Power (TEP).

A second panel organized by McNamara, “Perspectives on Long-Duration Energy Storage (LDES),” included multiple industry and non-profit panelists. These two panels were featured prominently on the EESAT agenda due to the importance of the topics covered and the prominence of the panelists representing Arizona-centric issues.

Since 2000, the EESAT conference has been a premier technical forum for advances in energy storage technologies and applications. The technical program showcases advances in electricity storage technologies, including new battery chemistries, power conversion systems, and energy management systems. The event is intended to provide a collaborative environment to address pressing technical energy storage challenges and opportunities within the energy sector to support policymakers, researchers, and industry professionals.

This material is based upon work supported by the U.S. Department of Energy, Office of Electricity (OE), Energy Storage Division.

In December 2025, Ujjwol Tamrakar, a researcher within Sandia’s Sandia Energy Storage Technology and Systems Department, was recognized as the outstanding associate editor of 2025 for IEEE Open Access Journal of Power and Energy. IEEE Open Access Journal of Power and Energy (OAJPE) is a technical journal containing articles focusing on the development, planning, design, construction, maintenance, installation, and operation of equipment, structures, and power systems. Being recognized as an outstanding associate editor highlights the commitment towards upholding high quality of scientific and technical publication for the journal and serving the scientific community.

This material is based upon work supported by the U.S. Department of Energy, Office of Electricity (OE), Energy Storage Division.

Sandia advanced the national deployment of energy storage systems for grid security by delivering webinars on “Energy Storage Safety and Reliability Trends” to around 60 utility regulators and state energy commissioners. Community safety concerns are a major barrier to energy storage deployment. These webinars leveraged Sandia’s extensive Office of Electricity-funded research, from chemical safety to standards, to address the concerns of key decision makers in energy storage deployment. Attendees were particularly interested in information related to emissions from failed systems and cybersecurity. The webinars were delivered by Yuliya Preger to ESTAP (Energy Storage Technology Advancement Partnership) working groups.

Citation: Y. Preger, “Energy Storage Safety and Reliability Trends,” Energy Storage Technology Advancement Partnership (ESTAP) working groups. Presented in webinars to ~60 utility regulators and state energy commissioners, Sandia National Laboratories, [Online].

This material is based upon work supported by the U.S. Department of Energy, Office of Electricity (OE), Energy Storage Division.

On November 20, 2025, Victoria O’Brien delivered a guest lecture entitled “Cybersecurity for Battery Energy Storage Systems” for the graduate-level course, Energy Storage for the Electric Grid, at Columbia University. The lecture provided an overview of cybersecurity fundamentals, identified and discussed threats in the energy sector, and explored theoretical and practical applications of cyberattack detection algorithms for battery energy storage systems. The session sparked engagement and discussions about cybersecurity across faculty, teaching assistants, and students in attendance.

Citation: V. O’Brien, “Cybersecurity for Battery Energy Storage Systems,” guest lecture, Energy Storage for the Electric Grid, Columbia University, New York, NY, USA, Nov. 20, 2025.

This material is based upon work supported by the U.S. Department of Energy, Office of Electricity (OE), Energy Storage Division