Lithium ion battery energy storage system for augmented wind power plants

Research output: Book/ReportPh.D. thesisResearch

Abstract

Future large Wind Power Plants (WPP) will be intended to function like today's conventional power plants seen from the transmission system point of view, by complying with future, more stringent, grid codes and providing ancillary services. This is possible to achieve by integrating WPPs with Battery Energy Storage Systems (BESSs) into the so called Virtual Power Plants (VPP). Relatively new energy storage technologies based on Lithium ion (Li-ion) batteries are constantly improving their performance and are becoming attractive for stationary energy storage applications due to their characteristics such as high power, high efficiency, low self-discharge, and long lifetime.
The family of the Li-ion batteries is wide and the selection of the most appropriate Liion chemistries for VPPs is one of the topics of this thesis, where different chemistries are compared and the most suitable ones for VPP integration are selected based on the accelerated lifetime tests.
The knowledge of the BESS lifetime is a key factor for their integration with WPPs. This is because an accurate knowledge of the BESS lifetime is a crucial factor in the project planning stage for the investigation on the BESS investment profitability. Moreover, the information about the BESS State of Health (SOH), at every point, is very important since the performance of the Li-ion BESS is changing with its age. In applications, the replacement of the BESS takes place usually before the end of their actual life, depending if the batteries are able to meet several performance requirements, which are application dependent. Furthermore, for the VPP, the degradation or failure of the interconnected BESS can lead to costly downtime.
Thus, an accurate estimation of the battery cells lifetime becomes mandatory. However, lifetime degradation of the Li-ion batteries is a complex process where many different degradation processes are involved and degradation is dependent on the battery operational conditions. Moreover, Li-ion battery cells are degrading slowly and the process of their ageing is time and resource consuming. Thus, the main purpose of this thesis is the development of a lifetime model, for a LiFePO4/C, battery based on accelerated laboratory cycle and calendar lifetime tests under different stress factors and stress levels, which are characteristic for the selected services of the VPP.
The developed Li-ion battery lifetime model is a used for the investigation on the lifetime of Li-ion BESS under different operational conditions for two selected services that the VPP could provide: primary frequency regulation and wind power forecast accuracy improvement. Different energy management strategies for these services are studied and different battery operational conditions are investigated. Moreover, simple economic analyses are performed; using the developed Li-ion battery lifetime model, for assessing
the profitability of the considered services provided by the VPP.
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Future large Wind Power Plants (WPP) will be intended to function like today's conventional power plants seen from the transmission system point of view, by complying with future, more stringent, grid codes and providing ancillary services. This is possible to achieve by integrating WPPs with Battery Energy Storage Systems (BESSs) into the so called Virtual Power Plants (VPP). Relatively new energy storage technologies based on Lithium ion (Li-ion) batteries are constantly improving their performance and are becoming attractive for stationary energy storage applications due to their characteristics such as high power, high efficiency, low self-discharge, and long lifetime.
The family of the Li-ion batteries is wide and the selection of the most appropriate Liion chemistries for VPPs is one of the topics of this thesis, where different chemistries are compared and the most suitable ones for VPP integration are selected based on the accelerated lifetime tests.
The knowledge of the BESS lifetime is a key factor for their integration with WPPs. This is because an accurate knowledge of the BESS lifetime is a crucial factor in the project planning stage for the investigation on the BESS investment profitability. Moreover, the information about the BESS State of Health (SOH), at every point, is very important since the performance of the Li-ion BESS is changing with its age. In applications, the replacement of the BESS takes place usually before the end of their actual life, depending if the batteries are able to meet several performance requirements, which are application dependent. Furthermore, for the VPP, the degradation or failure of the interconnected BESS can lead to costly downtime.
Thus, an accurate estimation of the battery cells lifetime becomes mandatory. However, lifetime degradation of the Li-ion batteries is a complex process where many different degradation processes are involved and degradation is dependent on the battery operational conditions. Moreover, Li-ion battery cells are degrading slowly and the process of their ageing is time and resource consuming. Thus, the main purpose of this thesis is the development of a lifetime model, for a LiFePO4/C, battery based on accelerated laboratory cycle and calendar lifetime tests under different stress factors and stress levels, which are characteristic for the selected services of the VPP.
The developed Li-ion battery lifetime model is a used for the investigation on the lifetime of Li-ion BESS under different operational conditions for two selected services that the VPP could provide: primary frequency regulation and wind power forecast accuracy improvement. Different energy management strategies for these services are studied and different battery operational conditions are investigated. Moreover, simple economic analyses are performed; using the developed Li-ion battery lifetime model, for assessing
the profitability of the considered services provided by the VPP.
Original languageEnglish
PublisherDepartment of Energy Technology, Aalborg University
StatePublished - 2012
Publication categoryResearch
ID: 76468579