The Innothon Challenge is a unique opportunity for Europeans or those with a Student Schengen Visa based in Europe from 18 to 28 years old only to showcase their talent to Enel Green Power.

Expires: 10 April 2023

Reward: Up to 10,000$ for the best prototype(s)

Meet the challenge!

Abstract

Enel Green Power (EGP) is a global leader in the development and management of energy production from renewable sources (wind, solar, hydroelectric, marine, and geothermal).

The Innothon challenge is focused on the realization of an autonomous robotic platform, capable of moving around renewable plants to carry out data collection, inspections, and small maintenance activities.

The Innothon Challenge is a unique opportunity for Europeans or those with a Student Schengen Visa based in Europe from 18 to 28 years old only to showcase their talent to Enel Green Power.

OVERVIEW

Over the last few years, we have pursued advances in various technologies, positioning EGP at the forefront of the energy transition. To reach our global future goal of zero emissions we will leverage technologies such as artificial intelligence (AI) and automation robotics, advances that are helping to improve the performance and efficiency of renewable energy plants.

AI algorithms can accelerate the energy transition making energy systems more efficient and smarter. AI can predict energy output, optimize energy production, and identify potential issues before they occur. This can help to maximize energy production and minimize energy losses.

AI can also be used to monitor the health of equipment in a renewable energy plant, identifying potential issues that can reduce downtime and maintenance costs, increasing the overall efficiency of the plant.

Combined with automated technologies, advanced robotics can be used to control and maintain equipment in renewable energy plants and reduce the need for human intervention, increasing overall efficiency and reducing the risk of human error.

By using AI to predict and optimize energy output, and automation to control and maintain equipment, renewable energy plants can be made more efficient, cost-effective, and reliable.

As the world continues to move towards a cleaner, more sustainable energy future, automation and AI will play an increasingly important role in making renewable energy more accessible and affordable for everyone.

BACKGROUND

With the growth of renewables the need for efficient, reliable and safe energy production has become increasingly important.

Turning to data driven tools for performance monitoring, real time diagnostics, prediction of potential future failures, operation and maintenance activities are essential for a generation plant to ensure its profitability through the maximization of the production and the reduction of unavailability events tangibly increasing the resilience of our plants and increasing the speed of reaction to possible damage that may occur.

Furthermore, they are fundamental to preserve the life span of plant components as well as to facilitate and reduce downtime, workforce intervention requirements and possible errors during Operation & Maintenance (O&M) activities. Indeed, the introduction and application of automated robotic solutions within our renewable plants would ensure the elimination of repetitive and dangerous operations by operators, increasing worker safety and speeding up execution.

Advanced robotics can be used to control and maintain equipment in renewable energy plants and reduce the need for human intervention, increasing overall efficiency and reducing the risk of human error.

Description

THE CHALLENGE

The Innothon challenge is focused on the realization of an autonomous robotic platform, capable of moving around renewable plants to carry out data collection, inspections, and small maintenance activities.

The solution must be autonomous in fulfilling the missions, pre-planned in a dedicated opensource software/dashboard where an operator can define the mission goals/constraints/path and other useful needs for the specific task.

Moreover, it should be equipped with AI features to support basic data analytics.

Acquired data/images collected must be automatically synchronized with a supervision software/dashboard at the end of the mission to produce a final report for each mission.

The possibility of live streaming of the information would be a plus.

The solution should include a manual override to take the control in case of emergency or specific need of the operator.

The system will be 100% electrical, either stand-alone (e.g. wheels, tracks, legs) or leveraging on existing structures (e.g. rails, cables, fences, PV trackers, others,...).

A solution able to be used as a multifunctional prototype that can be applied to more than one of the following use cases will be evaluated with an additional score.

EGP is interested in applications for all or any of the renewable assets (solar, wind, storage, green hydrogen, hydro and geo).

More info at openinnovability.com, meet the challenge!

Tipologia: Challenge prize

Fonte: https://openinnovability.enel.com/challenges/call/2023/2/robotics-solutions-renewable-plants

Paese: Brasile, Messico, ITALIA, Svizzera, Spagna, Australia, Norvegia, Repubblica Ceca, India, Kenya, Regno Unito, Danimarca, Cina, Germania, Cile, Sudafrica, Serbia, Francia, Finlandia, Austria, Giappone, Vietnam, Federazione Russa, Paesi Bassi, Egitto, Argentina, Singapore, Malesia, Lituania, Svezia, Israele, Canada, Corea del Sud, Stati Uniti d'America, Belgio

SSD: 01 - Scienze matematiche e informatiche, 02 - Scienze fisiche, 03 - Scienze chimiche, 04 - Scienze della terra, 05 - Scienze biologiche, 06 - Scienze mediche, 07 - Scienze agrarie e veterinarie, 08 - Ingegneria civile e Architettura, 09 - Ingegneria industriale e dell'informazione, 10 - Scienze dell'antichità, filologico-letterarie e storico-artistiche, 11 - Scienze storiche, filosofiche, pedagogiche e psicologiche, 12 - Scienze giuridiche, 13 - Scienze economiche e statistiche, 14 - Scienze politiche e sociali