15-20% cost reduction
How Cogninest AI Built a Smart Energy System to Cut Power Costs for Enterprises
Optimizing energy use and procurement with real-time forecasting and smart decision making
Static, reactive energy procurement in a volatile market
Large enterprises often face challenges in managing electricity consumption efficiently due to fluctuating market prices and lack of predictive planning. The traditional approach to energy procurement is static and reactive, resulting in missed opportunities to save on energy costs. Without accurate forecasting, companies either overpaid or underutilized energy resources. Electricity prices from sources like IEX (Indian Energy Exchange) and DISCOMs varied drastically throughout the day, creating windows of opportunity that manual processes could not exploit. Energy buying decisions were often made without data-backed insights, leading to consistently increased costs. To address these issues, the client needed a robust and intelligent Energy Management System aimed at reducing energy costs by predicting consumption and optimizing procurement strategies automatically.
- Unpredictable energy consumption without accurate forecasting models
- Price volatility across IEX and DISCOM sources throughout the day
- Manual procurement decisions made without data-backed insights
- No real-time visibility into savings opportunities
Predictive EMS with automated market-aware bidding and real-time dashboards
Cogninest AI developed a predictive EMS platform powered by machine learning and real-time pricing analytics. The system automatically forecasts energy consumption and electricity prices for the upcoming day, then determines the most cost-effective procurement strategy.
Data Ingestion
Historical data from smart meters, IEX, and DISCOM is collected daily along with weather data and usage patterns
Consumption Forecasting
ML models predict electricity consumption for the next 96 half-hour slots, analyzing patterns, seasonality, and demand fluctuations
IEX Price Prediction
Forecasts electricity prices on the Indian Energy Exchange and compares predicted prices with DISCOM offerings
Automated Bid Logic
Decision engine evaluates predicted IEX vs DISCOM prices and automatically places bids for the cheapest electricity source
Monitoring and Reporting
Dashboard displays real-time consumption, price trends, and cumulative savings. Sends alerts on price spikes and consumption anomalies. Generates daily, weekly, and monthly reports.
Data-driven procurement replaced guesswork with measurable savings
Enterprises using the EMS have reported up to 15-20% reduction in electricity procurement costs. Predictive insights enabled data-driven decision-making, replacing guesswork with precision. Automated procurement reduced the need for manual intervention and improved bidding accuracy. Real-time visibility enhanced transparency in energy consumption and cost optimization efforts. As energy prices become increasingly volatile, this data-driven solution is critical for companies aiming to optimize costs and stay sustainable. The system scales to different regions and integrates weather and IoT data for increasingly smarter predictions.