Enreport is a cloud-based platform that utilizes digital twins, production plans, and real-time weather data to provide precise energy consumption forecasts. This technology minimizes costly penalties and inefficiencies by aligning energy usage with actual demand, enhancing operational resilience and equipment reliability.
Funding
$120K raised to dateRaised to date based on public sources. This may differ from the amount the company actually raised and is based only on what is publicly available on the internet.
Founders
Product
Problem
Energy-intensive industries face challenges in accurately predicting energy consumption, leading to financial penalties and operational inefficiencies due to imbalances between forecasted and actual energy usage. These inaccuracies can result in increased costs and reduced equipment reliability.
Solution
Enreport is a forecasting platform that leverages digital twins, production plans, and real-time weather data to provide precise energy consumption predictions. By aligning energy usage with actual demand, Enreport minimizes penalties and inefficiencies, enhancing operational resilience and equipment reliability. The platform's forecasting models integrate virtual replicas of physical equipment with real-time data enrichment, offering a dynamic simulation of equipment behavior. This approach ensures accurate predictions by aligning theoretical models with real-world performance, enabling businesses to optimize their energy consumption and reduce costs. Enreport forecasts consumption, day-ahead, and intraday volumes, consolidating market and energy contract data for advanced market engagement.
Target Audience
The primary target audience includes energy-intensive industries seeking to optimize energy consumption, reduce costs, and improve operational resilience.
Features
- Digital twins: Virtual replicas of physical equipment or systems, combining physics-based equations with real-time data enrichment.
- Production plans: Integration of anticipated production volumes, schedules, and resource requirements.
- Weather data: Incorporation of variables like temperature, wind speed, irradiance, humidity, and cloud cover.
- Short-term forecasting: Enables optimal machine performance and minimizes downtime.
- Market engagement: Forecasts consumption, day-ahead, and intraday volumes, consolidating market and energy contract data.
- Cloud-based and on-premises deployment options.