Check out the original study on the Energise South Downs website here.

Energise South Downs (ESD), a community energy organisation, works with communities to enable community owned renewable generation. They are currently working on a project to identify the best sites in Hampshire for onshore wind. This project aims to aid the transition away from fossil fuels, reducing the local carbon footprint and enhancing community resilience.

To achieve their aim, ESD need to understand the following:

ESD currently holds data of potential wind sites from 3rd party sources including the University of Southampton and WeWantWind.org. Given that different methods of modelling can produce different outputs, ESD wanted to combine the multiple data sources to find the optimum sites.

LENZA’s Data Explorer helped with this.

Using the User Upload tool in LENZA, ESD was able to upload all relevant datasets to the platform. Once imported, the data could be visualised geospatially, reconfigured and filtered, and shared amongst other users. Visualising the datasets within LENZA, alongside some additional methodologies, ESD was able to combine these resources to create a new dataset which identifies sites that can be taken to the next stage of feasibility studies. This file was then uploaded to LENZA as well, to be analysed alongside other relevant data within the application such as protected land sites and network data.

Figure 1: The 'Ancient Woodland England', 'Outstanding Natural Beauty', and 'Conservation Areas England' datasets displayed in LENZA.

Having narrowed down the search, ESD needed to understand what the best sites are in terms of grid connectivity. Depending on the size (amount of export power from generation), the proposed scheme will either connect onto the 33kV network (the feed out of a bulk supply point) or the 11kV network (the feed out of a primary substation). The closer to the circuits, the likely reduced distance of new circuit required for connection and therefore reduced cost. As such, ESD wanted to further narrow their search based on locations close to 11kV and 33kV circuits.

LENZA’s Data Explorer helped with this.

SSEN has provided valuable network data that can inform this project, which is easily accessible within the Utility Networks folder on LENZA. The 'Network Topology' dataset shows the locations of low and high voltage cables, which can be filtered to quickly identify approximate locations of 11kV and 33kV circuits.

Additionally, the Primary and BSP Substation Supply Areas datasets show the areas served by different substations, with the Primary Substation Supply Areas dataset even showing the generation headroom available for each substation. This is particularly important to consider for such a large-scale generation project.

Figure 2: The 'Network Topology' dataset in LENZA, supplied by SSEN, showing the locations of low and high-voltage cables.

Alongside this project, ESD secured funding from the charity Possible to specifically find sites for onshore wind to heat communities, with an interest in areas with higher levels of fuel poverty.

LENZA’s Data Explorer helped with this.

Within the Socio Demographic folder in LENZA, ESD was able to download the 'Fuel Poverty' dataset and layer it onto the map alongside their wind site data. Using the Filtering tool, they could filter out LSOAs with lower proportions of households experiencing fuel poverty, to clearly identify the most fuel-poor regions in the area which are near suitable sites for wind.

Figure 3: The 'Fuel Poverty' dataset in LENZA, filtered to highlight areas with higher proportions of households experiencing fuel poverty.