Periodic Reporting for period 1 - iBEMS-SeLiBat (Integrated Battery and Energy Management System for Second-Life Battery energy storage)
Berichtszeitraum: 2022-12-01 bis 2023-08-31
Optimal control and safe operation, lifetime prediction and management are amongst the most important open questions in the field of battery energy storage systems and of particular importance for second-life battery storage systems. Customers currently lack confidence about the quality and remaining lifetime of second-life battery systems. In first-life BESS, cell parameters and expected lifetime are determined through expensive and often destructive lab tests executed on a subset of the battery cells. The test results are representative since all cells are new and behave in a similar way. This is not the case for second-life BESS, where each cell may have a different history and therefore a different remaining lifetime and cell parameters. A battery controlled without detailed knowledge of the state of the battery cells will not deliver its optimal value as both the operational limits and lifetime warranty need to be set in a conservative way, underusing its full commercial potential.
This project improves the way battery energy storage systems (BESS) are operated by bringing together the BMS, which traditionally performs battery pack state estimation, and the EMS, which controls the (dis)charging of the BESS, into iBEMS, an integrated battery & energy management system.
The iBEMS has access to all raw battery cell measurements normally only accessible by the BMS. The energy management and optimisation function of the iBEMS is performed leveraging the plethora of useful data from the battery cells. Traditionally, an EMS only sees the state of charge of the battery pack and this data would have been lost. The data is available in Octave’s battery cloud, which opens multiple improvements in operating the BESS, such as delivering an optimized service, building a digital twin of the cells, applying machine learning, extending the lifetime, improving monitoring and enabling predictive maintenance, all which are of particular importance for second-life battery systems.
This project improves the way battery energy storage systems (BESS) are operated by bringing together the BMS, which traditionally performs battery pack state estimation, and the EMS, which controls the (dis)charging of the BESS, into iBEMS, an integrated battery & energy management system.
The iBEMS has access to all raw battery cell measurements normally only accessible by the BMS. The energy management and optimisation function of the iBEMS is performed leveraging the plethora of useful data from the battery cells. Traditionally, an EMS only sees the state of charge of the battery pack and this data would have been lost. The data is available in Octave’s battery cloud, which opens multiple improvements in operating the BESS, such as delivering an optimized service, building a digital twin of the cells, applying machine learning, extending the lifetime, improving monitoring and enabling predictive maintenance, all which are of particular importance for second-life battery systems.
On the date of the first periodic reporting, we have fully finalised the development and tests of two second-life battery energy storage systems operated with Octave’s integrated Battery and Energy Management System (iBEMS) in two test beds, and reached TRL6. We have defined the full system requirement to develop, build and test a first iteration of a modular and versatile second-life Battery Energy Storage System, including the hardware and software required for Octave’s innovative iBEMS.
We have designed and build two different second-life Battery Energy Storage systems, using two different types of used Electric Vehicle (EV) battery modules, one 75kWh system with a 30kVA inverter and another one a 120kWh system with a 92kVA inverter. Both systems have been operational and running for several months, demonstrating multiple energy management applications and generating very granular data about the second-life battery cells. We are currently in the process of refining and optimising this design for easier assembly, quicker installation and safer maintenance.
We have setup a state-of-the art cloud infrastructure which is able to process these detailed second-life battery cell measurements coming from the battery systems operated in the field. As an example, we process cell voltage and temperature measurements of each individual cell in a battery energy storage system, which holds up to 216 cells, and with a granularity of 1 second.
We have developed the first algorithms using this granular data for state estimation and increased safety of second-life batteries. We have also created multiple dashboards to remotely monitor the systems in real time and with high granularity, allowing us to detect issues remotely and almost instantaneously.
We have also demonstrated multiple energy management applications with these second-life battery energy storage systems. Local applications, such as self-consumption and reactive power control have been demonstrated, as well day-ahead energy market price arbitraging.
We have designed and build two different second-life Battery Energy Storage systems, using two different types of used Electric Vehicle (EV) battery modules, one 75kWh system with a 30kVA inverter and another one a 120kWh system with a 92kVA inverter. Both systems have been operational and running for several months, demonstrating multiple energy management applications and generating very granular data about the second-life battery cells. We are currently in the process of refining and optimising this design for easier assembly, quicker installation and safer maintenance.
We have setup a state-of-the art cloud infrastructure which is able to process these detailed second-life battery cell measurements coming from the battery systems operated in the field. As an example, we process cell voltage and temperature measurements of each individual cell in a battery energy storage system, which holds up to 216 cells, and with a granularity of 1 second.
We have developed the first algorithms using this granular data for state estimation and increased safety of second-life batteries. We have also created multiple dashboards to remotely monitor the systems in real time and with high granularity, allowing us to detect issues remotely and almost instantaneously.
We have also demonstrated multiple energy management applications with these second-life battery energy storage systems. Local applications, such as self-consumption and reactive power control have been demonstrated, as well day-ahead energy market price arbitraging.
The results achieved so far allow to complete the remained of the project successfully and within the foreseen timeline. They pave the way for a successful commercial after the project by gradually building up the TRL level from 6 to 8 of Octave’s second-life Battery Energy Storage System and integrated Battery and Energy Management.
We have demonstrated a first prototype of our second-life Battery Energy Storage System with the developed integrated Battery and Management System. Two systems have been developed and tested, containing two types of EV battery modules at two different sites. We have submitted a patent on the mechanical design to allows for multiple types of EV batteries to be used for stationary energy.
We have demonstrated three different applications with second-life batteries: maximising self-consumption, performing reactive power control and performing day-ahead arbitraging. The batteries have been shown to perform all these objectives without major issues.
We have develop our Battery Cloud to process detailed data generated from these second-life battery systems in the field. We have implemented first state estimation algorithms. The generated data of the demonstration systems will, together with new data from new systems installed in the remainder of the project, be used to further improve the algorithms and advance the state of the art. We are in the process of applying advanced artificial intelligence to improve our understanding of second-life batteries, their safe operation and maximize their value for stationary energy storage
Third party review on certifications and norms for the developed second-life Battery Energy Storage System has been started with first positive results obtained.
We have demonstrated a first prototype of our second-life Battery Energy Storage System with the developed integrated Battery and Management System. Two systems have been developed and tested, containing two types of EV battery modules at two different sites. We have submitted a patent on the mechanical design to allows for multiple types of EV batteries to be used for stationary energy.
We have demonstrated three different applications with second-life batteries: maximising self-consumption, performing reactive power control and performing day-ahead arbitraging. The batteries have been shown to perform all these objectives without major issues.
We have develop our Battery Cloud to process detailed data generated from these second-life battery systems in the field. We have implemented first state estimation algorithms. The generated data of the demonstration systems will, together with new data from new systems installed in the remainder of the project, be used to further improve the algorithms and advance the state of the art. We are in the process of applying advanced artificial intelligence to improve our understanding of second-life batteries, their safe operation and maximize their value for stationary energy storage
Third party review on certifications and norms for the developed second-life Battery Energy Storage System has been started with first positive results obtained.