Artificial Intelligence system to control renewable energy

At present, the RE curtailment towards grid balancing and security is being carried out manually by way of telecommunication mode through Sub-load despatch centres at Madurai and Erode. The manual action causes much time delay. “Hence, is the proposal to implement a pilot project on AI-based Active Grid Network Management (ANM) system for real time autonomous RE and wind generation control from the State Load Despatch Centre (SLDC), Chennai, to improve system stability,” said an official of Tamil Nadu Transmission Corporation Ltd (TANTRANSCO).

A senior official of TANTRANSCO said that the AI-based ANM would work without involvement of the power manager in the SLDC to decide on evacuate more or less wind power based on real time data from the wind power pooling stations.

TANTRANSCO has invited bids to set up a pilot on the ANM to minimise renewable energy curtailment and improve system balancing.

The proposed pilot project would be implemented in few RE sources including wind and hydro pooling control stations in Tirunelveli and Udumalpet regions, the official said. “The AI-based ANM system should facilitate more RE integration without breaching operational limits of plus and minus 250 MW and reduce deviation penalties under Deviation settlement mechanism. RE generation should be curtailed and released more quickly depending on the deviation in boundary limits,” TANTRANSCO official added.

The AI-based ANM system would incorporate a central control unit (CCU), housed in the State Load Deispatch Centre (LDC) facilitating all data monitoring, prediction, data transfer and execute control algorithms. The CCU should have the ability to monitor and control RE despatch at pooling station of the wind farm SS.

A wind power generator said that the biggest issue facing the wind power generators in the state is the backing down of the windmills by the SLDC during the peak wind generation months. “This year alone, the SLDC has curtailed the wind power evacuation to the tune of 20 per cent during the peak wind season from May to September leading to huge loss for the investors,” the wind power generator said, adding that automation of the grid management would certainly help avoid the curtailment of the wind power generation for reasons other than grid security as per the norms.