Real-World Diagnostics and Prognostics for Grid-Connected Battery Energy Storage Systems – IEEE Spectrum

Real-World Diagnostics and Prognostics for Grid-Connected Battery Energy Storage Systems

This report is based on research conducted by The University of Sheffield.

Introduction

The global transition to renewable energy has significantly transformed power systems, challenging traditional engineering assumptions such as predictable inertia and dispatchable baseload generation. With wind and solar energy becoming dominant, grid operators now face steep ramp events, larger frequency excursions, faster transients, and extended periods with minimal fossil fuel generation.

In this evolving landscape, Battery Energy Storage Systems (BESS) have become critical for maintaining grid stability. These systems provide rapid response times, precise power control, and operational flexibility across various services. However, unlike conventional power generation, batteries are sensitive to operational history, thermal conditions, state of charge, system architecture, and degradation mechanisms. Their long-term behavior results from complex electrochemical, thermal, and control interactions.

Challenges in Battery Energy Storage Systems

Laboratory tests and simulations often fail to replicate the irregular operational conditions experienced by batteries on the grid. Real-world battery usage involves rapid power fluctuations, partial state of charge cycling, fast recovery intervals, high-rate events, and unpredictable disturbances. This discrepancy raises concerns about the reliability of degradation models, lifetime predictions, and operational strategies that have not been validated against actual grid behavior.

Sheffield’s Unique Research Facility

The University of Sheffield’s Centre for Research into Electrical Energy Storage and Applications (CREESA) operates one of the UK’s only research-led, grid-connected, multi-megawatt battery energy storage testbeds. This facility enables testing of storage technologies under full-scale, live grid conditions, bridging the gap between laboratory research and real grid operation.

Facility Features

• 11 kV, 4 MW network connection providing electrical and operational realism
• 2 MW / 1 MWh lithium titanate battery system, one of the first independent grid-connected BESS in the UK
• 100 kW second-life electric vehicle battery platform supporting reuse and circular economy models
• Support for flywheel systems, supercapacitors, hybrid architectures, and fuel-cell technologies
• Over 150 laboratory cell-testing channels, environmental chambers, and impedance spectroscopy equipment
• High-speed data acquisition and integrated control systems for diagnostics and fault response measurement

This infrastructure allows operation of storage assets on the live grid, exposing them to real market signals, frequency deviations, voltage events, and operational disturbances. Controlled experiments can replay historical grid and market signals, enabling repeatable full power testing under realistic commercial conditions.

Benchmarking with Grid-Scale Demonstration

Sheffield’s pioneering 2 MW / 1 MWh lithium titanate demonstrator was installed when the UK had no established standards for BESS connection, safety, or control. This platform has provided valuable insights into high-power battery behavior under grid stressors, demonstrating sub-second response times and synthetic inertia-like capabilities.

Research Contributions

• Hybridization studies including battery-flywheel control architectures
• Optimization of response times for new grid services
• Operator training and market integration with live asset exposure
• Development of dispatch controllers, forecasting tools, and health management systems
• Comparative benchmarking of lithium-ion chemistries, lead-acid systems, and second-life batteries

Findings reveal that real-world battery behavior often diverges from laboratory predictions due to complex electrical, thermal, and control interactions at megawatt scale. These insights inform improved system design and ensure future storage systems are engineered for actual operational conditions.

Advanced Diagnostics for Longevity

Ensuring long-term reliability of BESS requires comprehensive understanding of aging under real operating conditions. Sheffield combines high-resolution laboratory testing with empirical data from full-scale grid-connected assets to develop advanced diagnostics and prognostics.

Core Research Areas

State Estimation and Parameter Identification

• Robust estimation of State of Charge (SOC) and State of Health (SOH)
• Online parameter identification for equivalent circuit models
• Power capability prediction using transient excitation
• Data selection strategies under noise and variability

Degradation and Lifetime Modelling

• Models based on real frequency and market data
• Analysis of micro-cycling and asymmetric duty cycles
• Hybrid physics and machine learning forecasting models

Thermal and Imbalance Behavior

• Characterization of thermal gradients in containerized systems
• Understanding cell imbalance in large-scale battery strings
• Mitigation strategies at cell and module levels
• Coupled thermal-electrical behavior under fast cycling

Hybrid Systems and Multi-Technology Optimization

• Battery-flywheel coordination strategies
• Techno-economic modeling for hybrid assets
• Dispatch optimization using evolutionary algorithms
• Control schemes to extend lifetime and enhance service performance

Sheffield’s diagnostic techniques have also been applied in off-grid environments, such as collaboration with MOPO, which deploys pay-per-swap lithium-ion battery packs in low-income communities in Sub-Saharan Africa. These efforts contribute to affordable, clean, and safe energy alternatives, supporting sustainable development.

Collaboration and Global Impact

Sheffield’s research is closely integrated with industry partners, system operators, technology developers, and service providers. This collaboration enables practical engineering outcomes including improved dispatch strategies, validated control architectures, and enhanced understanding of battery degradation in real-world market operations.

The partnership between academia and industry ensures that research remains relevant to modern power systems and supports the development of best practices in lifetime modeling, hybrid system control, diagnostics, and operational optimization.

Alignment with Sustainable Development Goals (SDGs)

1. SDG 7: Affordable and Clean Energy – Advancing battery energy storage technologies supports reliable integration of renewable energy sources, enhancing access to clean and sustainable energy.
2. SDG 9: Industry, Innovation, and Infrastructure – Sheffield’s cutting-edge research infrastructure fosters innovation in energy storage systems and strengthens resilient energy infrastructure.
3. SDG 11: Sustainable Cities and Communities – Improved grid stability and energy storage solutions contribute to sustainable urban development and resilient communities.
4. SDG 12: Responsible Consumption and Production – Research into second-life batteries and circular economy models promotes sustainable resource use and waste reduction.
5. SDG 13: Climate Action – Enabling higher penetration of renewable energy through advanced storage systems supports global efforts to combat climate change.
6. SDG 17: Partnerships for the Goals – Collaboration between academia, industry, and communities exemplifies global partnerships driving sustainable development.

Conclusion

The University of Sheffield’s comprehensive approach to battery energy storage research, combining full-scale grid-connected testing, advanced diagnostics, and industry collaboration, is pivotal in developing reliable, efficient, and sustainable energy storage solutions. These efforts directly support multiple Sustainable Development Goals by promoting clean energy integration, innovation, sustainable urbanization, responsible resource use, climate action, and global partnerships.

1. Sustainable Development Goals (SDGs) Addressed or Connected

1. SDG 7: Affordable and Clean Energy
   • The article discusses battery energy storage systems (BESS) that support renewable energy integration and grid stability, which directly relates to ensuring access to affordable, reliable, sustainable, and modern energy.
2. SDG 9: Industry, Innovation and Infrastructure
   • The research and development of advanced diagnostics, prognostics, and grid-connected battery storage testbeds highlight innovation in infrastructure and industrial processes.
3. SDG 11: Sustainable Cities and Communities
   • By improving energy storage technologies and grid stability, the article supports resilient infrastructure and sustainable urban energy systems.
4. SDG 12: Responsible Consumption and Production
   • The focus on battery reuse, repurposing, circular economy models, and second-life batteries addresses sustainable consumption and production patterns.
5. SDG 13: Climate Action
   • The shift to renewable energy and reduction of fossil generation supported by battery storage contributes to combating climate change and its impacts.
6. SDG 17: Partnerships for the Goals
   • The article highlights collaboration between academia, industry, and communities, demonstrating partnerships to achieve sustainable development.

2. Specific Targets Under Identified SDGs

1. SDG 7: Affordable and Clean Energy
   • Target 7.2: Increase substantially the share of renewable energy in the global energy mix.
   • Target 7.3: Double the global rate of improvement in energy efficiency.
   • Target 7.a: Enhance international cooperation to facilitate access to clean energy research and technology.
2. SDG 9: Industry, Innovation and Infrastructure
   • Target 9.4: Upgrade infrastructure and retrofit industries to make them sustainable, with increased resource-use efficiency and greater adoption of clean and environmentally sound technologies.
   • Target 9.5: Enhance scientific research and upgrade technological capabilities of industrial sectors.
3. SDG 11: Sustainable Cities and Communities
   • Target 11.b: Increase the number of cities adopting integrated policies and plans towards inclusion, resource efficiency, mitigation and adaptation to climate change.
4. SDG 12: Responsible Consumption and Production
   • Target 12.5: Substantially reduce waste generation through prevention, reduction, recycling, and reuse.
5. SDG 13: Climate Action
   • Target 13.1: Strengthen resilience and adaptive capacity to climate-related hazards and natural disasters.
   • Target 13.3: Improve education, awareness-raising and human and institutional capacity on climate change mitigation.
6. SDG 17: Partnerships for the Goals
   • Target 17.16: Enhance the global partnership for sustainable development, complemented by multi-stakeholder partnerships.
   • Target 17.6: Enhance North-South, South-South and triangular regional and international cooperation on access to science, technology and innovation.

3. Indicators Mentioned or Implied to Measure Progress

1. SDG 7 Indicators
   • Proportion of population with access to electricity (implied by improved grid stability and energy access through battery storage).
   • Renewable energy share in the total final energy consumption (implied by integration of wind and solar supported by BESS).
   • Energy storage capacity installed (implied by multi-megawatt battery storage testbeds and systems).
2. SDG 9 Indicators
   • Research and development expenditure as a proportion of GDP (implied by university-led research and innovation).
   • Number of industrial research and development workers (implied by collaboration with industry and technology developers).
   • Technology readiness and deployment of clean energy storage systems.
3. SDG 12 Indicators
   • Waste generation per capita and proportion recycled (implied by reuse and repurposing of second-life batteries).
   • Material footprint, including circular economy metrics.
4. SDG 13 Indicators
   • Greenhouse gas emissions reduction enabled by renewable energy integration and storage.
   • Number of countries with climate change mitigation strategies incorporating energy storage technologies.
5. SDG 17 Indicators
   • Number of multi-stakeholder partnerships for sustainable development (implied by collaborations described).
   • Access to technology and knowledge sharing metrics.

4. Table: SDGs, Targets and Indicators

Source: spectrum.ieee.org