Availability-Based Tariff for Sugar Manufacturing Industry
Power Scheduling, Deviation Management & Tariff Compliance for Sugar Manufacturing Operations
Posted by: Jagan
Date: July 23, 2026
About the Client
A multi-unit sugar manufacturing organization with captive power generation facilities generates electricity for internal consumption and exports surplus power to the grid during the crushing season. Effective monitoring of generation, export, grid drawal, and deviations is essential to maintain grid compliance, control DSM exposure, and protect revenue.
Business Challenges

- Manual collection of generation, export, and schedule data from multiple sources
- Limited real-time visibility into scheduled versus actual generation and export
- Difficulty in monitoring block-wise deviations and DSM exposure
- Delayed identification of under-generation, over-generation, and abnormal operating conditions
- Time-consuming preparation of ABT and DSM reports with data inconsistencies across teams
What We Did

We implemented a centralized Availability-Based Tariff System to provide real-time visibility into generation, export, scheduling, and deviation performance. The solution enabled automated data collection, comprehensive dashboards, reporting, and trend analysis to support faster operational and commercial decision-making.
- Captured key energy meter parameters at 30-second intervals for continuous monitoring
- Enabled centralized real-time data acquisition, monitoring, and storage
- Provided management dashboards with built-in analysis and actionable insights
- Automated yearly, monthly, daily, shift-wise, and hourly reports
- Enabled quick trend analysis to identify deviations and abnormal operating patterns
Value Delivered

- Real-time visibility into ABT, DSM, generation, and export performance
- Faster identification of schedule deviations and abnormal operating conditions
- Reduced manual effort in ABT and DSM report preparation
- Improved availability and consistency of operational and commercial data
- Better analysis of block-wise deviations and historical trends for informed decision-making
