Process information
| 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 | 2023 |
| 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
|
| General comment on data set | This data set has been modeled according to the European Standard EN 15804+A2 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 | 2026 |
| 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. In module C1, a manual dismantling (no loads) is assumed, collecting losses are neglected. The transport in module C2 to the recycling plant takes place with a truck (50km). Treatment of cells (anode and cathode materials): In module C4 the average tratment and landfill emissions for hazardous waste are shown. The use of landfill gas is not taken into account. A material recycling has not benn taken into account due to a lack of data on the recycling processes. Tratment of metal components (battery case): Collecting losses are neglected. It is assumed that all metals reach the end of the waste status immediately after dismantling. This means that the loads for processing and the credits for the substitution of primary material are shown in Module D. Module D includes loads for sorting, remelting, slag treatment, landfill, filtration of dusts and dross treatment. Credits are given for the net scrap amount (amount returned minus secondary material content, minus processing losses) for the average material mix (from different alloys). Treatment of plastic components: Module C3 takes into account the grinding and thermal treatment (combustion) of the material. When calculating combustion emissions and credits, the specific calorific value of each material and the material composition are taken into account. In module D credits for the substitution of electricity (German electricity mix) and thermal energy (from natural gas) are given. |
| Flow diagram(s) or picture(s) | |
Modelling and validation
Administrative information
Environmental indicators