Until just a few years ago, millions of people in rural India did not have reliable access to electricity, according to a report issued by the World Bank. Pressure to forecast demand, down to 15-minute time frames, and procure power beforehand, created lots of challenges.
For state governments, the key to balancing supply is accurately predicting demand. But, until recently, predictions have been calculated manually using spreadsheets. Lacking precision, distribution companies were buying too much power, leading to waste, or too little power, contributing to financial losses. Delhi-based Mercados EMI a leading consultancy firm that specializes in solutions for demand forecasting, chose IBM Weather Business Solutions to help predict demand with greater accuracy with more frequent updates.
“The bottom line is you have to know how much power you will consume so that you buy only as much as you require.” – Rachit Kumar Agarwal, Managing Partner
Turns out, predicting energy consumption has a lot to do with the weather. New improvements in the Weather Company Data Packages helps forecasters predict day-ahead energy requirements.
Factoring in weather data
Today, both the states of Uttar Pradesh and Bihar are using Weather Data APIs through the IBM Weather Operations Center, a suite of applications that combine and integrate the Weather Company Data Package with geospatial analytics, dashboards for visualization and alerting capabilities.
Read the full case study to find out how Mercados EMI helped India overcome their challenges by creating an AI-based demand forecasting solution based on Weather Company Data Packages.
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