Renewable energy systems play a key role in decarbonising the energy grid, and including them in a building LCA or carbon assessment is increasingly common. This article explains how to find the right datasets in One Click LCA and how to handle cases where an exact match is not available.

As a general rule, if you have an EPD for the product, search for the EPD number first. If the data is eligible for use in your calculation tool, it will most likely already be in the database.

Systems meeting the criteria can be found by free-text search or using the pre-defined material filter: Installations and Systems, then selecting the sub-filter Energy Production Systems From Renewable Energy.

Two generic PV panel datasets are available:

Both datasets use area (m²) as the functional unit, so you can enter either the total panel area or, if working from panel count, multiply the number of panels by the area of each panel to get a total m² quantity.

When comparing datasets, note that the peak output figure given in the description (Wp, or WattPeak) represents the panel's rated capacity under standard test conditions, not its annual energy generation. It is provided for specification matching, not energy modelling.

If you have a manufacturer EPD for the specific panel being installed, search for the EPD number first; product-specific data will always be more representative than a generic dataset.

Four solar water heater datasets are available for residential applications:

Choose the dataset that matches the collector type and configuration on your project. If the tank size or collector area differs from the dataset, you can scale by the collector area ratio as a reasonable approximation, since collector area is the primary driver of system mass.

Heat pumps are increasingly the primary heating and cooling technology for low-carbon buildings and can be considered a renewable-adjacent system where the heat source is the ground, air or water. The following datasets are available:

If your system capacity falls between available datasets, scale from the nearest capacity using the mass ratio as a proxy. The material composition of heat pumps is broadly consistent within a technology type, so this approach gives a reasonable result.

Biomass boilers cover two application scales. Residential units are available at 15 kW (160.6 kg), 30 kW (164.4 kg) and 50 kW (168.3 kg). Industrial units are available at 140 kW (318.9 kg), 300 kW (334.2 kg) and 1000 kW (401 kg).

For projects including on-site energy storage alongside renewable generation, battery datasets are available for six chemistries: lithium iron phosphate (LFP), nickel cobalt manganese (NCM), sintered NiCd, plastic-bonded NiCd, NiMH, and sealed lead-acid (12 V/7.2 Ah). These cover the range from residential battery systems to commercial and industrial storage installations.

DC surge protective devices for PV string circuits are available at 600 V DC/20 kA (0.35 kg) and 1000 V DC/20 kA (0.40 kg), for modelling the protection equipment associated with PV arrays. A DC SPD for battery storage systems is also available at 48 V DC/10 kA (0.30 kg).

Wind turbine EPDs from specific manufacturers are available in the database and can be found by searching for "wind turbine" directly. If the turbine specified for your project has a published EPD, search for the EPD number first to check whether it is already included.

Where no EPD is available for the specific turbine being modelled, the recommended approach is to identify the main components by mass from the manufacturer's technical specification, typically the tower (structural steel), nacelle (steel, copper and aluminium), rotor blades (glass or carbon fibre composite), and foundation (reinforced concrete), and enter these as separate quantities using the corresponding generic material datasets. This will give a reasonable estimate of the embodied impact even without a unit-level dataset.

For renewable energy systems not covered by the categories above, search by product name to check whether a matching dataset exists. If not, the material composition approach described for wind turbines applies: identify the dominant materials by mass, and use the corresponding generic material datasets to build up the system's footprint from its bill of materials.

If the panel type has not been specified, use the monocrystalline dataset as a default. Monocrystalline panels have a slightly higher peak output per m² (224 Wp versus 210 Wp) and are the more common choice in current commercial and residential projects. The mass per m² is identical for both datasets at this stage, so the LCA result will not differ significantly.

Yes. The residential label reflects the scale of the unit, not a restriction on building type. For larger commercial installations with multiple collectors, multiply the number of units by the relevant unit dataset, or use the collector area ratio to scale if the configuration differs from the dataset.

Check the dataset description for the specific unit. Refrigerant charge is a relatively small proportion of total system mass but can have a disproportionate climate impact depending on the refrigerant type. If refrigerant is not included in the dataset and the charge is known, it can be added separately using the relevant refrigerant material dataset.