Identify Substations with Available Capacity to Target Land Search

This case study describes the successful implementation of an automated solution to collect monthly available capacity data from substations in Spain, as reported by REE and the different distributors. The solution identifies substations with available capacity that are not subject to REE capacity contests and locates them on a map. This automation allows developers of photovoltaic assets to focus their land search efforts on those areas with the best chances of success. The implementation of this solution has optimised the identification of priority substations, reduced the effort required by the development team and streamlined the process of identifying viable land where capacity is available.

CHALLENGES

The client faced the following challenges:

Heterogeneity of Data: Manually collecting and consolidating disparate substation capacity data reported by the various different distributors and REE required time and effort.
Priority Identification: Manually identifying substations with available capacity not subject to capacity contests was a difficult and complicated process, given the heterogeneity of the information reported by the distributors.
Map Location: Locating these substations on a map to begin the process of searching for viable land was a laborious task, due to the different formats of geographical information from various sources.

SOLUTION

Quintas Analytics developed and implemented a comprehensive automated solution to address the above challenges:

Automatic Data Integration: A system was designed to automatically collect and homogenise substation capacity data from REE and reported distributors on a monthly basis.
Automatic Identification: The solution identified substations with available capacity that was not subject to REE capacity tenders.
Location Map: An interactive map was created that harmonised the different geolocation formats reported by the distributors and marked the identified substations, allowing for a clear spatial visualisation.

RESULTS AND BENEFITS

Implementing the solution had a significant impact on operational efficiency and decision making:

1. Time Saving: The automation of the collection and consolidation of the information reported by REE and the distributors reduced the time and effort required by the team.
2. Focused Identification: The automated solution made it possible to accurately identify priority substations.
3. Visual Localisation: The interactive map improved spatial visualisation and streamlined strategic decision making in the search for viable land.
4. Resource Optimisation: Developers were able to focus their efforts on more promising areas as soon as the available capacity was reported by the distributors.
5. Error Reduction: Automation reduced the risk of human error in the identification, homogenisation and analysis of data reported by REE and distributors.

CONCLUSIONS

The solution implemented for the automated identification of substations with available capacity and their location on a map for PV asset development proved a great success in improving operational efficiency and streamlining the search process for viable land. The automation of processes, integration of data and its representation on an interactive map provided essential tools for effective and agile management of available capacity in asset development. This solution sets a valuable example for the management of similar projects in the solar energy sector in Spain.

Identify Substations with Available Capacity to Target Land Search

CONTEXT

CHALLENGES

SOLUTION

RESULTS AND BENEFITS

CONCLUSIONS

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