Forecasting next day’s electricity demand in units!

Our Bureau Hyderabad | Updated on December 28, 2020

AP deploys ‘day-ahead’ model using artificial intelligence and machine learning technologies

APTransco has deployed a day-ahead electricity forecasting model system that uses Artificial Intelligence and Machine Learning technologies.

Developed by AP State Load Dispatch Centre, this solution can forecast next day’s electricity demand in units, including day-ahead electricity demand (in MW) on every 15-minute basis. This enables the transmission network to take the right decisions on electricity demand and supply, management of grid and minimising power purchase cost.

According to a statement from AP Energy Conservation Mission, Google, with the support of World Bank, has offered to further work on the forecasting model with AP State Load Dispatch Centre (SLDC).

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For wind and solar too

With the deployment of the forecasting model, APTransco plans to develop day-ahead forecast models for wind energy, solar energy, market prices, Central Stations, the surplus power and grid frequency.

It is developing a least-cost electricity dispatch model that will tell how much electricity should be dispatched every 15 minutes next day from each generating station covering thermal, solar, wind and gas plants and market purchases. All these deployments are aimed at minimising power purchase cost.

The load dispatch centres in India are now using a manual forecast mechanism which is not accurate and leads to overdrawal or underdrawal of power.

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“Electricity demand forecast is a big task for State Load Dispatch Centre to prepare for purchase or sale of power the next day. The load-demand mismatch leads to over or underdrawal from national grid which entails heavy penalties and sometimes leads to power cuts as well,” an APSLDC official said.

APSLDC plans to transfer the forecast model to start-up companies willing to commercialise the product.

Energy Secretary Srikant Nagulapalli said the State aims at building an efficient and financially robust power sector to address future power demand and cost-effective power supply to consumers.

Published on December 28, 2020

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