​Maharashtra pushes for AI use in power supply to manage demand during summers 

The Maharashtra government has directed energy authorities to use artificial intelligence (AI) to ensure smooth electricity generation and uninterrupted power supply during peak summer demand.

Chief Minister Devendra Fadnavis instructed the Energy Department and related agencies to adopt AI-based systems for better monitoring, maintenance and management of power generation and distribution.

He said AI should be used to strengthen planning, reduce faults, and improve real-time response during high-demand periods.

Review meeting on peak summer demand

A detailed review meeting on electricity distribution during peak summer demand was held at Sahyadri State Guest House in Mumbai.

Senior officials including the Energy Department, Tata Power, Adani Power and BEST Undertaking were present.

Officials informed the meeting that the state’s power system is fully prepared to handle increased demand during summer and monsoon seasons.

Key arrangements include adequate coal and water availability for power generation, ongoing maintenance work, and emergency response systems.

Major infra and safety measures

The government highlighted several key measures to ensure grid stability- 

– Koyna hydroelectric project operating at full capacity up to 1800 MW as required

– Additional power purchase arrangements for emergency needs

– Strengthening of transmission systems in the Mumbai Metropolitan Region

– Active Mumbai Islanding Scheme to protect the city grid during failures

– Bhira pumped storage project in operation

– Successful completion of black start drills

– Backup control systems tested under State Load Dispatch Centre (SLDC)

– Focus on Reliability and Emergency Readiness

Officials said these systems ensure quick restoration of power in case of grid failure and prevent large-scale outages in Mumbai and across Maharashtra.

The Energy Department also confirmed that pre-monsoon maintenance work is being carried out to reduce risks of breakdowns during adverse weather conditions.

 

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