Power to the people

To combat this problem, India launched its 24/7 Power For All program in 2016, aimed at providing every household, business and other electricity-consuming entity with round-the-clock access to power. As a joint initiative between the central and state governments, the program also imposed new and strict regulations related to energy supply and demand.

Rachit Kumar Agarwal is the Managing Partner at Mercados Energy Markets India Private Limited, India (Mercados EMI), a consultancy firm that specializes in solutions for the energy sector. He recalls the challenge: “States had to procure power beforehand. This meant they had to know precisely how much power was required every day, every hour and in 15-minute time blocks. It was a problem.”

For state governments, the key to balancing supply is accurately predicting demand. But, until recently, officials calculated predictions manually using spreadsheets. They analyzed years’ worth of historical demand data, yet calculations were off. Predictions came in too high or too low. Lacking precision, distribution companies bought too much power, leading to waste, or too little power, contributing to financial losses.

In early 2020, the states of Uttar Pradesh and Bihar, located in a region of extreme summers and winters and having some of the largest consumer bases in India, turned to Mercados EMI for help. In addition to seeking a solution that would infuse AI into the prediction process, officials wanted to better understand all of the factors that impact demand — not just historical data.

Turns out, predicting energy consumption has a lot to do with the weather.

“What came out of our detailed discussions with the utilities over six months was that accurate weather data plays a very important role in predicting demand,” recalls Mr. Agarwal. Armed with new insights, Mercados EMI created an AI-based demand forecasting solution — jouleOS® — based on Environmental Data Services, sourced from The Weather Company®, an IBM Business. The technology helps forecasters predict day-ahead energy requirements.

The IBM solution has since expanded. Now, organizations can access Weather Data APIs through the IBM Environmental Intelligence Suite, a suite of applications that combine and integrate The Weather Company Data APIs with geospatial analytics, dashboards for visualization and alerting capabilities.

To build its forecasting solution, Mercados EMI first developed a model to accurately understand demand. The model combined the state’s historical demand data with historical weather pattern data from The Weather Company History on Demand data package.

“We already had the demand data from previous years. What we required was historical weather patterns,” adds Mr. Agarwal. “So, for example, if demand is 5,000 megawatts at a particular instant, what were the weather parameters at that instant? And when the weather parameters changed, how did the demand change?”

To answer these questions and, ultimately, meet the government’s data resolution requirements, Mercados EMI applied the forecast engines of The Weather Company Enhanced Forecast data and the IBM Environmental Intelligence Suite platform. “Weather data is where we gained immense help from IBM,” adds Mr. Agarwal. “It not only provided us the return in terms of time — hourly and at 15-minute increments out to seven hours — but also within a geographic radius of 500 x 500 meters.” The 15-minute forecasts represent a significant improvement: previously, the states relied on weather data with a timeframe of three hours from publicly available open-source databases.

The models, combined with Mercados EMI’s proprietary AI engine, help distribution companies better forecast electricity demand a day ahead. Mercado EMI now offers its jouleOS technology under its Power Portfolio Optimization suite of solutions.

Today, both the states of Uttar Pradesh and Bihar use the system, with Madhya Pradesh and a state in Southern India soon to follow.