Dubai Electricity and Water Authority (DEWA), powering a city of 3.5 million residents and one of the world's highest per-capita energy consumers, faced dual challenges: reducing carbon emissions to meet UAE sustainability targets while maintaining 99.99% grid reliability in a desert climate with peak summer demand. Traditional grid management couldn't balance renewable energy intermittency, cooling demand surges, and infrastructure capacity constraints.
DEWA deployed AI-powered smart grid management integrating data from 1.2 million smart meters, solar installations, weather forecasts, and building automation systems. Machine learning models predicted energy demand by district and time, optimizing power generation mix between fossil fuels, solar, and imports. The AI platform automatically adjusted grid parameters to accommodate solar generation fluctuations. Demand response programs used AI to incentivize consumption shifts to off-peak hours. Predictive maintenance prevented transformer failures before impact.
“AI enables Dubai's vision of the world's smartest and most sustainable city. We balance renewable energy, reliability, and efficiency at a scale impossible with human grid operators alone.”— Chief Innovation Officer, DEWA
This case study is based on publicly available information about Dubai Smart City.
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