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heating, and air conditioning. This helps save costs and reduce greenhouse gas
emissions.

Energy Demand and Price Forecasting: AI analyzes big data to predict energy
demand trends and price fluctuations. As a result, energy suppliers can plan production
and adjust supply appropriately, stabilizing the energy market. AI algorithms are used
to forecast real-time energy demand, optimizing electricity production and distribution
based on weather factors and usage trends.
Automated Maintenance and Infrastructure Management: AI assists in
monitoring and maintaining energy infrastructure, detecting early signs of damage or
potential issues, reducing downtime, and minimizing repair costs.

Source: Department of Electricity and Renewable Energy, 2023

This chart demonstrates that AI is a versatile tool in energy management,
addressing various challenges such as efficiency, sustainability, and predictive
capabilities across different facets of the energy sector. The largest application of AI in
energy management is Energy Optimization. AI helps optimize energy production and
consumption, improving efficiency, minimizing energy waste, and balancing supply
and demand by up to 25%. AI is used to build and operate smart grids, adjusting power
flow based on real-time data. This technology helps minimize energy losses, ensure
stability, and more effectively integrate renewable energy sources by 20%. In

predictive maintenance, AI predicts equipment failures in energy systems before they
occur, reducing downtime and saving maintenance costs by up to 20%. AI forecasts
energy demand based on various factors such as weather and consumption patterns.
Accurate forecasting helps energy providers plan supply accordingly, reducing the risk
of energy shortages or surpluses by 15%. AI also optimizes water usage in
energy-related processes, particularly in thermal power plants and renewable energy

production. By efficiently managing water resources, it supports sustainable energy
operations and saves up to 20% in water usage.

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