Close Go back Collapse all sections
Process Data set: Lithium iron phosphate (LiFePO4) battery (per 1kWh storage); 1kWh storage capacity (en) en de

Tags Dieser Datensatz ist Bestandteil der ├ľKOBAUDAT.
Key Data Set Information
Location DE
Geographical representativeness description The data set represents the country specific situation in Germany, focusing on the main technologies, the region specific characteristics and / or import statistics.
Reference year 2018
Name
Base name ; Quantitative product or process properties
Lithium iron phosphate (LiFePO4) battery (per 1kWh storage); 1kWh storage capacity
Use advice for data set The data set represents a cradle to gate inventory. It can be used to characterise the supply chain situation of the respective commodity in a representative manner. Combination with individual unit processes using this commodity enables the generation of user-specific (product) LCAs.
Technical purpose of product or process This product can be used in construction.
Classification number 8.4.05
Classification
Class name : Hierarchy level
  • oekobau.dat: 8.4.05 Building service engineering / Electrical / Batteries
General comment on data set This data set has been modeled according to the European Standard EN 15804 for Sustainable Building. Results are depicted in modules that allow the structured expression of results over the entire life cycle.
Uncertainty margins 10
Description Product system almost completely covered. Good technological, temporal and geographic representativeness.
Copyright Yes
Owner of data set
Quantitative reference
Reference flow(s)
Time representativeness
Data set valid until 2022
Time representativeness description Annual average
Technological representativeness
Technology description including background system Foreground system: This dataset describes a domestic battery for storage of electricity. The model is related to 1kWh of storage capacity, based on a 12KWh battery. Information on the battery: Battery supporting 6000 charging cycles. At 6000 cycles only 70% of the capacity is available. This dataset is based on a 12kWh battery and should be used for such order of magnitude for electricity storage. The round trip energy efficiency of a LFP battery is 92% = for 1kWh of electricity stored in the battery 0,92kWh can be get back. Motivation- storage of electricity from photovoltaics: The peak power of a photovoltaic system is reached at noon, while the peaks of electricity demand are in the morning and in the evening. A picture attached is showing the energy curves. Without energy storage, large amounts of electricity are fed to the grid at noon and cannot be used for own consumption. After sunset and before sunrise, large amounts have to be taken from the grid. Based on a yearly energy consumption of 4000 kWh and a 5kWp PV system, the degree of self- sufficiency is about 50 %. If a battery with more than 8kWh is added, it can reach 85%. In the attached source Photovoltaik Web, a table is showing more examples. Background system: Electricity: Electricity is modelled according to the individual country-specific situations. The country-specific modelling is achieved on multiple levels. Firstly, individual energy carrier specific power plants and plants for renewable energy sources are modelled according to the current national electricity grid mix. Modelling the electricity consumption mix includes transmission / distribution losses and the own use by energy producers (own consumption of power plants and "other" own consumption e.g. due to pumped storage hydro power etc.), as well as imported electricity. Secondly, the national emission and efficiency standards of the power plants are modelled as well as the share of electricity plants and combined heat and power plants (CHP). Thirdly, the country-specific energy carrier supply (share of imports and / or domestic supply) including the country-specific energy carrier properties (e.g. element and energy content) are accounted for. Fourthly, the exploration, mining/production, processing and transport processes of the energy carrier supply chains are modelled according to the specific situation of each electricity producing country. The different production and processing techniques (emissions and efficiencies) in the different energy producing countries are considered, e.g. different crude oil production technologies or different flaring rates at the oil platforms. Thermal energy, process steam: The thermal energy and process steam supply is modelled according to the individual country-specific situation with regard to emission standards and considered energy carriers. The thermal energy and process steam are produced at heat plants. Efficiencies for thermal energy production are by definition 100% in relation to the corresponding energy carrier input. For process steam the efficiency ranges from 85%, 90% to 95%. The energy carriers used for the generation of thermal energy and process steam are modelled according to the specific import situation (see electricity above). Transports: All relevant and known transport processes are included. Ocean-going and inland ship transport as well as rail, truck and pipeline transport of bulk commodities are considered. Energy carriers: The energy carriers are modelled according to the specific supply situation (see electricity above). Refinery products: Diesel fuel, gasoline, technical gases, fuel oils, lubricants and residues such as bitumen are modelled with a parameterised country-specific refinery model. The refinery model represents the current national standard in refining techniques (e.g. emission level, internal energy consumption, etc.) as well as the individual country-specific product output spectrum, which can be quite different from country to country. The supply of crude oil is modelled, again, according to the country-specific situation with the respective properties of the resources.
Flow diagram(s) or picture(s)
  • electronics_lithium iron phosphate lifepo4 battery.jpg Image

Indicators of life cycle

IndicatorDirectionUnit Production
A1-A3
De-construction
C1
Transport
C2
Disposal
C4
Recycling Potential
D
Input
  • 1071
  • 0
  • 0.05581
  • 11.13
  • -152.9
Input
  • 0
  • 0
  • 0
  • 0
  • 0
Input
  • 1071
  • 0
  • 0.05581
  • 11.13
  • -152.9
Input
  • 3415
  • 0
  • 0.9586
  • 70.74
  • -468.4
Input
  • 0
  • 0
  • 0
  • 0
  • 0
Input
  • 3415
  • 0
  • 0.9586
  • 70.74
  • -468.4
Input
  • 0
  • 0
  • 0
  • 0
  • 0
Input
  • 0
  • 0
  • 0
  • 0
  • 0
Input
  • 0
  • 0
  • 0
  • 0
  • 0
Input
  • 2.01
  • 0
  • 0.00004998
  • 0.012
  • -0.3323
Output
  • 0.00002266
  • 0
  • 3.582E-8
  • 1.56E-7
  • -2.048E-7
Output
  • 59.45
  • 0
  • 0.0001683
  • 16.65
  • -8.155
Output
  • 0.1309
  • 0
  • 0.000001009
  • 0.001583
  • -0.03645
Output
  • 0
  • 0
  • 0
  • 0
  • 0
Output
  • 0
  • 5.17
  • 0
  • 0
  • 0
Output
  • 0
  • 0
  • 0
  • 0
  • 0
Output
  • 0
  • 0
  • 0
  • 0
  • 0
Output
  • 0
  • 0
  • 0
  • 0
  • 0

IndicatorUnit Production
A1-A3
De-construction
C1
Transport
C2
Disposal
C4
Recycling Potential
D
  • 241.5
  • 0
  • 0.07143
  • 22.59
  • -35.29
  • 0.000001514
  • 0
  • 2.361E-17
  • 6.072E-14
  • 1.498E-11
  • 0.1004
  • 0
  • -0.00005293
  • 0.001621
  • -0.006794
  • 1.059
  • 0
  • 0.0001565
  • 0.02421
  • -0.1146
  • 0.06772
  • 0
  • 0.00003751
  • 0.004973
  • -0.007364
  • 0.01849
  • 0
  • 6.002E-9
  • 7.516E-7
  • -0.00002123
  • 3084
  • 0
  • 0.956
  • 66.74
  • -376