Periodic tree pruning comes with high associated costs in all countries and its schedule. Additionally, is difficult to program due to the unknown growth speed of different plants. Because of this, a new need arises: the optimization of vegetation maintenance activities through the use of Vegetation Growth Estimation systems, to decide the proper trimming frequency for each area as a function of its peculiar kind of vegetation and climate. Expected benefits of the system include:
- Optimisation of vegetation trimming activities considering the peculiarities of each area;
- Reduction of maintenance costs as a consequence of the above mentioned benefit;
- Scheduled vegetation trimming on demand;
- Better control over the outsourced work.
The scope of this Challenge is to identify an algorithm capable to estimate, as accurately as possible, the plants’ growth considering historical meteorological observations and forecasting in the area under evaluation, collected information on the essence and other elements (such as ground composition) which can affect the vegetation growth.
In general, the Vegetation Growth Estimation algorithm should satisfy the following Solution Requirements:
- Be based on collected data (must have), provided by LiDAR/photo/video inspections and georeferenced vegetation maps, such as:
- Different vegetation species;
- Historical weather conditions and altitude;
- Ground geography (also taking into account different perimeters such as Europe, Asia and Latin America …), composition, altitude and slope.
- Plants growth detected between two consequential inspections.
- Other variables that could affect vegetation growth.
- Elaborate growth forecasts that will be used to prevent violations of the clearance profiles close to the power lines (must have);
- Elaborate its forecasts by areas (must have);
- Have a Maintenance Management Tool (nice to have) that considers the above mentioned data and forecasts to:
- Elaborate maintenance plans/actions prioritized and grouped by area, taking into consideration also technical and economic constraints, width of the clearance profiles close to the power lines and different trimming prescriptions of every area (due to regional or national law constrains, due to particular situation such as national park or protected areas, etc);
- Monitor maintenance works and update the state of the vegetation after the trimming activities carried out by subcontractors.
- Improve the following Key Performance Indicators (KPI):
- OPerational EXpenses (OPEX) reduction/increase*;
- Number of failure events on the overhead lines due to vegetation;
- Number of incidents due to lack of guard distances.
*the use of this system could lead to an increase of the trimming activities w.r.t. the current periodical interventions. Even if in this case maintenance costs would increase, failure events due to vegetation could be avoided.
- Any proposed solution should have at least TRL 4 (Technology Readiness Level), which means: design, development and lab testing of components / processes. Results provide evidence that performance targets may be based on projected or modeled systems.
[innovation], [technology], [artificial intelligences], [algorithm], [IoT], [growth-sensor], [growth prediction], [satellites], [drones], [robots], [self-driving cars], [predictive maintenance], [safety], [maintenance efficiency]
The submitted proposals should include:
- Video - it is appreciated if the Solvers will submit a video that summarises the proposal and allows Enel to do a quick initial screening of proposals
- Collaboration Proposal including:
- A description of the proposed system with an explanation of how the Solver proposes to address all the Solution Requirement. The Solver can withhold proprietary information, if necessary, but should provide convincing evidence for ENEL to appreciate the merits of the approach and be comfortable that the solution can effectively work;
- A brief discussion of capabilities and relevant prior experience that are relevant for the development of the solution and success of the post-Challenge collaboration;
- The Solver should explain what they can provide and what might be required of the Seeker. For example: “I can provide with the expertise, but I would need the Seeker to facilitate access to data”;
- A brief overview of the proposed path forward along with a plan for validation (e.g. deliverables, timelines, milestones, and cost estimates);
- The Solver should indicate the TRL (Technology Readiness Level) of the solution.
- General Information about the Solver including:
- The key contact person for this Challenge (including phone number and email address).
- Organization/Company name and address (including website, if available)
(NOTE: For most Challenges, Solvers are not allowed to include personal contact information; however, for an eRFP Challenge, it is required.)