BESS Performance/ Reliability Data Project Update

© 2021 Electric Power Research Institute, Inc. All rights reserved.w w w . e p r i . c o m

Steve Willard Technical Executive

April 20, 2021

BESS Performance/ Reliability Data Project UpdateDOE Energy Storage System Safety &

Reliability Forum

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© 2021 Electric Power Research Institute, Inc. All rights reserved.w w w . e p r i . c o m2

▪ EPRI Storage Performance & Reliability Overview

▪ Focus on Data and Analytics

– Data non uniformity

– Metric Reporting/Discrepancies Noted

▪ Short- and Long-Term Solutions

Agenda

How is storage really performing?



EPRI Storage Performance and Reliability Data Initiative Overview

▪ Key Gaps/Findings

– OEM performance metrics are proprietary and need verification

– Many systems don’t deliver data required for in depth analysis – other approaches have possibilities

– System data lacks uniformity and is difficult to use in analysis

– O&M Analytics are immature

▪ Solutions - Defined new metrics and tools to understand storage performance

– Developed independent degradation analyses via EPRI/PNNL Collaborative Agreement

– Developed a Data Guide with DOE to inform numerous stakeholders –new version being finalized

– Developed internal tools to ease data ingestion into analytics database

– Analyzed numerous systems and found discrepancies in reported metrics

– Informing Standards to address lack of uniformity

– Developed O&M event reporting tool - currently underway in EPRI Energy Storage Integration Council (ESIC)

Snapshot of ESIC O&M Event Tracking Tool



Storage Performance – Under the Microscope

▪ NERC: Energy Storage, Impacts of Electrochemical Utility-Scale Battery Energy Storage Systems on the Bulk Power System - February 20211

– “Data on battery storage tends to be non-uniform and lacking in consistency… necessitating a need for better reporting mechanisms for BESS data”

– “ Entities...must enhance both their data collection methods as well as their reporting methods…IEEE should update …Standards …The GADS Working Group should ensure that battery storage is accurately reflected in their data capturing protocols”

NERC: Reliability Guideline Performance, Modeling, and Simulations of BPS Connected Battery Energy Storage Systems and Hybrid Power Plants - March 20212

– “System-level BMS data related to SOC and state of health (SOH) should be accessible to the GOP, TOP, and RC (as deemed necessary) for independent evaluation to verify accuracy of reported metrics, assess operational issues, and correct any apparent miscalculations. All critical data and metrics (e.g., SOC and SOH) of the battery management system should have accuracy requirements established by the GO, which could be based on equipment standards (where applicable).”

1. https://www.nerc.com/pa/RAPA/ra/Reliability%20Assessments%20DL/Master_ESAT_Report.pdf2. https://www.nerc.com/comm/RSTC_Reliability_Guidelines/Reliability_Guideline_BESS_Hybrid_Performance_Modeling_Studies_.pdf


https://www.nerc.com/pa/RAPA/ra/Reliability%20Assessments%20DL/Master_ESAT_Report.pdf

https://www.nerc.com/comm/RSTC_Reliability_Guidelines/Reliability_Guideline_BESS_Hybrid_Performance_Modeling_Studies_.pdf


– Collaborative efforts are key to bridging numerous and challenging gaps

EPRI/DOE Collaboration – Parallel Efforts Informing Leading Edge Research

Historical Operation Future Performance

Diamond Database: Operational data collection and management Train Predictive Models:

Using historical data and battery chemistry expertise

Descriptive Analysis: Describe historical performance. Refine processes.

Predict Future Performance:

Develop Algorithms and Tools: To analyze historical system performance

Validate and Refine Predictions: Compare predictions with descriptions. Refine accordingly



Prerequisite Data for Performance Analysis

SecondMinuteHour

For Illustration Only

System

String

Module

Cell

Standby Loss and Auxiliary Losses• What are the physical and

financial costs of idle operation?

• Standby Loss as indicator of underperformance?

Increasing Temporal Resolution

Inc

rea

sin

g S

pa

tia

l R

es

olu

tio

nCycle Requirements

Mandatory periodic Reference Performance TestsSome specific operation neededIn situ measurement (no special cycles necessary)

Thermal Analysis• How effective is the system’s

thermal management system?

Energy Capacity and RTE• High-level understanding of degradation

trends. How do they compare with warranty?• Implications for future operations.

Internal Resistance Characterization• How is 𝑅𝑖𝑛𝑡

changing over time?

Differential Voltage Analysis (dV/dQ):• What degradation

mechanisms are affecting my system?

Predictive Performance Modeling• Predict future

performance with models built on historical data



85%

90%

95%

100%

0 1 2 3 4 5 6 7 8 9 10

Stat

e o

f H

eal

th (

SoH

)

Project Year

Energy Capacity Over Time: Specified, Measured, & Modeled

System-reported metrics may not tell the whole story.

Research Need: Can historical data and recent research be used to better understand and predict performance?▪ Accurately determine and refine augmentation

strategies ▪ Does system performance align with guarantees?▪ When should future operation strategy be

updated?

Energy Capacity & State of Health (SoH) Over Time: How is a system expected to perform in the future?

Desired Outcomes: More visibility into past, present, and future performance▪ Periodically check in on a system’s capabilities▪ Refine operational strategies to ensure lifetime

operation▪ Better identify and understand system

underperformance

Contractual End-of-Life (87% SoH)



Discrepancies Noted in SOH/SOC Field Measurements

▪ Key Metrics for grid operators are being reported from proprietary calculations which obfuscate understanding

▪ Improbable values may be reported by systems

▪ Independent assessments show discrepancies and highlight accuracy issues

▪ As ISO/RTO SOC Management becomes more essential, accuracy becomes increasingly important to assure SOC feasibility

PNNL Sources: PNNL Puget Sound Energy Glacier Energy Storage System, An Assessment of Battery Technical Performance, July 2019 PNNL-28379Snohomish Public Utility District MESA-1 An Assessment of Battery Technical Performance January 2018 PNNL-27237

Li-Ion (NMC): Reports SoH of 99.5% for 1.5

years. Firmware update closed apparent gapFlow Battery: Impossible decline and

recovery of SoC affect the AC output of the

entire system

Li-Ion (LFP): Large SOC swings, potentially being

calculated by BMS from voltage rather than open

circuit voltage?



Reported State of Health vs. Discharge Energy Capacity

▪ Discrepancies between system reported state of health (SoH) and measured performance metrics, like discharge energy capacity, have been documented.

▪ Periodic reference performance tests (RPTs) required

▪ Warranties/Performance Guarantees may hinge on the accuracy of this metric



EPRI/SNL Data Guidelines Document – Interim Path to Standards and Mature

Specifications

▪ Energy Storage Data Submission Guidelines

▪ Co-published with Sandia National Labs

– February 2020

▪ Link to current version https://www.epri.com/research/products/000000003002016277

▪ Intended to provide information to standard making bodies and storage stakeholders

– Discusses

▪ Overall system requirements

▪ Data Responsibility

▪ General points needed

▪ Data accuracy, quality and transmission

New Version Features:

▪ New sections on – Alarm Management

– DC Power Quality

▪ Revisions to – Points list

– Interoperability and Standards in Play

– Sensor/Metric Accuracy

▪ Draft slated for feedback discussion in next ESIC Virtual Meeting

– Tuesday April 27 (Next Week)

– Data Guidelines Breakout Session slated for 11AM PT

– See www.epri.com/esic

▪ Targeted publication in May 2021 via ESIC library (publicly available)


https://www.epri.com/research/products/000000003002016277

http://www.epri.com/esic


Tool Goals

▪ Unobtrusive to operations environment

▪ Provide platform for data analytics

▪ Easily ingestible to data repository

▪ Flexible for future development

Background

▪ Gaps in industry knowledge

– What data is relevant to reliability?

▪ Difficult system comparisons

– Across locations, types, etc.

▪ Need for Issue statistics and analytics

– Inform O&M teams & refine designs

O&M |EPRI ESIC O&M Issue Tracking Tool

Predefined, machine friendly

input fields

Resolution information

Guided inputs for natural language

processing

Notes sectio

n

Analysis

Tool to Collect Data from O&M Events Reliability Insights

Download the published O&M tool www.epri.com 3002019222




Understanding storage performance is key to future grid reliability

Targeted Standards and Interim Solutions

▪ Operational Solutions

– Short Term - Need for Reference Performance Tests

▪ One approach to independent SOH verification

▪ ESIC and PNNL Test Protocols

▪ SOC loss on standby approach

– Medium Term – Specify the acquisition for more data to assess SOH & SOC independently

– Long Term – define storage operational characteristics on a Mature Technology Basis

▪ Provide/obtain the same level of knowledge on storage that exists with other utility assets

▪ Targeted Efforts: – IEEE 1547.9, 2800, P2686, P2688, P1679.3

(flow), Future P2800.9

– NERC GADS (future)

– IEC 61850 and associated sub-standards

▪ But…Standards take time to finalize and adopt – in the interim bridge resources are needed– EPRI/SNL Data Guide V2

– EPRI Energy Storage Performance and Reliability Foresight Project

▪ Multi tool analysis and comparison – which SOC/SOH algorithm is best?

▪ Utilizing lab and field data



EPRI appreciates the continued support from Dr. ImreGyuk, DOE – Office of Electricity, Energy Storage Program and the staff from PNNL

Acknowledgement



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BESS Performance/ Reliability Data Project Update

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