Accenture Helps Metro de Madrid Balance Energy Efficiency and Passenger Comfort with AI-Based Self-Learning Ventilation System

Accenture (NYSE: ACN) has helped Metro de Madrid develop and implement a self-learning AI-based ventilation system that minimizes energy costs and emissions and ensures high air quality in metro stations and commuters’ comfort.

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The artificial intelligence (AI)-based system has enabled Metro de Madrid to reduce its energy costs for ventilation by 25 percent and cut CO₂ emissions by 1,800 tons annually. Accenture will present the system at this year’s MWC (formerly known as Mobile World Congress) in Barcelona, Feb. 25-28.

On average, 2.3 million commuters use Metro de Madrid’s network of 294 kilometers of track and 301 stations every day. To help passengers stay cool inside stations, particularly during the hot summer months, Metro de Madrid operates 891 ventilation fans, which were consuming as much as 80 gigawatt hours of energy annually.

The Madrid Metro Ventilation experts worked with Accenture Applied Intelligence to develop a system that took inspiration from an unusual source: the coordinated foraging behavior of a bee colony. The system deploys an optimization algorithm that leverages vast amounts of data to explore every possible combination of air temperature, station architecture, train frequency, passenger load and electricity price throughout the day. The algorithm uses both historic and simulated data, factoring in outside and below-ground temperatures over the next 72 hours. Because the algorithm uses machine learning, the system gets better at predicting the optimal balance for each station on the network over time.

The system also includes a simulation engine and maintenance module, which allows for, among other things, tracking for failures in the fans’ operation. This enables Metro de Madrid to easily monitor and manage energy consumption, identify and respond to system deficiencies, and proactively conduct equipment maintenance.

“With the help from Accenture, the innovative ventilation system has enabled us to achieve the dual benefits of lower energy costs and a reduced environment impact,” said Isaac Centellas, Head of Engineering and Maintenance Division at Metro de Madrid. “Ensuring the comfort of our passengers while being highly energy-efficient and environmentally friendly is a true win-win outcome.”

Isabel Fernández, managing director for Accenture Applied Intelligence in Spain, said, “Our self-learning ventilation system shows how organizations and society can benefit from intelligent technologies. It’s an important milestone in our work for Metro de Madrid, and we’re excited to present it to the public at this year’s MWC, where applied AI will play a bigger role than ever.”

To schedule a demo of Metro de Madrid’s self-learning ventilation system at the Accenture MWC booth (Hall 2, 2H20), contact jens.derksen@accenture.com.

About Accenture

Accenture is a leading global professional services company, providing a broad range of services and solutions in strategy, consulting, digital, technology and operations. Combining unmatched experience and specialized skills across more than 40 industries and all business functions — underpinned by the world’s largest delivery network — Accenture works at the intersection of business and technology to help clients improve their performance and create sustainable value for their stakeholders. With 469,000 people serving clients in more than 120 countries, Accenture drives innovation to improve the way the world works and lives. Visit us at www.accenture.com.

Accenture Applied Intelligence, part of Accenture Digital, applies artificial intelligence and human ingenuity at the core of business to help clients solve their most complex business problems. By deploying AI responsibly and combining it with our deep industry and analytics expertise, we enable the digital transformation of organizations, extend human capabilities, and make intelligent products and services a reality. Follow @AccentureAI and visit accenture.com/appliedintelligence.

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