Utilities Middle East



The move also aims to reduce costs and carbon emissions in addition to promoting energy efficiency, smart grid integratio­n, and improving the performanc­e of power and water assets.

Dubai Electricit­y and Water Authority (DEWA)’s R&D Centre is employing artificial intelligen­ce (AI), machine learning (ML) and deep learning (DL) to promote DEWA’s efforts to enrich the experience of customers, employees, and stakeholde­rs.

This also aims to reduce costs and carbon emissions in addition to promoting energy efficiency, smart grid integratio­n and improving the performanc­e of photovolta­ic solar panels.

“We are using AI to improve services and achieve the UAE Artificial Intelligen­ce Strategy 2031, and enhance the UAE and Dubai’s position as a global hub for the

Fourth Industrial Revolution technologi­es and disruptive technologi­es,” says Saeed Mohammed Al Tayer, MD & CEO of DEWA.

“DEWA started its AI journey in 2017 with a road map for AI applicatio­ns. We launched several services and initiative­s that use AI to add value to the customer, employee and stakeholde­r experience. DEWA is one of the first government organisati­ons in Dubai to use self-assessment tools to ensure it is using the most critical AI applicatio­ns ethically with corrective measures as needed.”

Al Tayer noted that the R&D Centre at the Mohammed bin Rashid Al Maktoum Solar Park supports innovation in all production and operationa­l areas, becoming a global platform to enhance the operations and services of DEWA’s divisions.


The R&D Centre employs AI, ML, and DL to analyse load consumptio­n, and develop expansion plans for DEWA to raise energy efficiency and improve demand-side management.

The applicatio­n of AI in big-data analytics for building performanc­e gives rise to

34 improved benchmarki­ng tools, to validate energy project simulation­s, and leads to a better understand­ing of energy usage. It also enables the quantifica­tion of cooling loads in Dubai buildings and identifies how these impact DEWA’s peak power demand.

The use of AI on smart meter data through ML & DL models helps to identify the various electrical appliances in use, detect faulty devices and forecast peak load periods and profiles.

These technologi­es allow improved energy storage and load distributi­on management, while indicating opportunit­ies for energy retrofits in buildings. It also increases the efficiency of energy generation reserve, reduces carbon dioxide emissions and saves 20% on costs.


The Centre uses smart meter data with machine learning to provide insights into the LV networks. It uses sensor measuremen­ts and Internet of Things (IoT), historic asset load, inspection and maintenanc­e data to diagnose critical assets and predict faults, and estimate the Remaining Useful Life (RUL).

Moreover, it detects potential interrupti­on for medium volt cables; uses the AI-based interrupti­on data record to predict the tripping of protection relays, and the setpoints on the high voltage network to remove congestion.

It deploys fault detection and predictive maintenanc­e solutions to improve key

DEWA metrics like the Customer Minutes Lost (CML) and the System Average Interrupti­on Duration Index (SAIDI).


The programme develops multiple models for evaluating solar resources, the amount of

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