The “Power of Disambiguation”
- Data Reconciliation
- Mass Balance
- Energy Balance
- Power Generation
- District Heating
- Scheduled Execution
- ERP Integration
- Multi Site Integration
- Automatic Calculation
- 500 000 $/year – EBITDA improvement
- Sigmafine Server
- Sigmafine Thermodynamics Extension
- Sigmafine Integration Framework
- PI-AF Server
- MS SQL Server
- Pimsoft SPA (Italy)
Automatic Data Validation and reconciliation transforms power and heat production in the face of business and regulatory challenges
A multi-site power and heat producer in the Netherlands applied automatic data validation and balancing analytics to develop an efficient work method for faster transaction and trade of electricity and heat as well as early warning identification system of critical heat and power producing units and their associated measurements.
Business and regulatory challenges
The Power industry, like so many other commodities, is experiencing declining prices, poorer quality resources, lower emissions emission limits, rising regulatory requirements and, now with agile customers who have no barrier to change supplier, thus forcing companies to remove any inefficiencies across the value chain from raw to material purchase through to supplied products to maintain competitive prices.
Simultaneous to the tightening of resources and regulatory requirements placed on the power industry, is the low investment yet high ROI big data software analytics, including Sigmafine automatic data validation and reconciliation which now provides process opportunities to go beyond measurement accuracies, be more proactive in quality metering and deliver early identification and warning of poor performing assets.
Instead of documenting Sigmafine features and functionalities, summarised below is result of business value, opportunities discovered as well as implementation method used that effectively demonstrates how digital technology can reduce losses and costs while improving asset utilisation, integrity, streamlined business process and profitability.
Our example is Uniper N.V, based in The Netherlands, has been on a journey to automate its business process starting from data received by vendors throughout the operations, and finally to delivered products (power and heat). In 2014, E.ON Benelux, now Uniper N.V, embarked on a business transformation enabled by digital technologies to streamline their business process which supports their trade and performance monitoring program.