With over 150,000km of Overhead Electrical Lines (OEL), identifying risks and threats to the electrical network is a critical task.
The recent storms that battered the Island of Ireland showed that despite our best efforts, critical infrastructure can remain vulnerable to the natural elements. Protecting our electrical network is a gigantic task, but it is one that Earth Observation technologies, coupled with GIS, can greatly assist with. Mallon colleague Sandra Molloy has created the following map.
Identifying Electrical Grid Locations at Risk from Tall Trees using Earth Observation
Strom Éowyn brought huge gusts of wind to the Island of Ireland, setting a new wind speed record of 114mph in County Galway. The storm saw widespread disruption across the country, with the high wind speeds causing millions in damage and uprooting hundreds of trees. Trees that grow next to OELs have the potential to severely impact electricity supplies should they come down in a storm.
Ireland has over 150,000km of OEL between the transmission and distribution systems. Identifying where these wires come close to large trees is a huge task. Earth Observation technologies coupled with GIS are ideally suited to identifying risks within close proximity to the electrical network.
The map below shows a rural area in the West of Ireland. Large trees over 6m high were identified using the High–Resolution Global Canopy Height dataset developed by Meta and World Resources Institute. A subset of OEL in this region has also been added to the map. The red circles on the map pinpoint where these large trees come within 6m of the OEL. This enables the parts of the grid at risk from large trees to be quickly identified.
N.B. trees or hedges with 6m of electrical equipment should not be cut without first contacting the relevant body in charge of the electrical transmission infrastructure in your area.
How can Earth Observation Protect Electricity Networks?
The map above shows it is possible to identify risks that come within close proximity to any infrastructure. The parameters used in the example above (tree height, distance from the OEL) can easily be changed to identify many different risk factors or areas of concern. This can all be done remotely and on a large scale, creating a complete picture of all possible risks to a network.
Such maps can inform decision–making, help in the early identification of at–risk areas, and lead to better resource management. Being better prepared for future storms will help maintain the electricity supply during life–threatening situations especially in rural and harder to reach areas.
Further Information
For further information about the methods used to produce the map above or to discuss you Earth Observation requirements, contact us below.
