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Turn-key plant simulation models are among ENEXSA´s core competencies. The Digital Twin is a virtual replica of the power plant that represents the process across the entire range of operating conditions and in all possible combinations of the equipment.
Comprehensive data interfaces allow for various applications to accurately simulate, monitor or forecast performance at the level of the overall plant as well as individual equipment.
Fuel Demand Models represent contracted performance guarantees. While the contract typically includes a limited number of guaranteed points, the bonus-penalty calculations for plant efficiency must be performed under every possible condition over the entire operating range of the power plant. This is accomplished through a physics-based simulation model (Digital Twin) that includes sub-models of all major plant components which in detail reflect the respective performance guarantees.
Planning Models based on vendor guarantee data or measured 'as built' performance information enable the plant personnel to investigate the effect of various conditions and settings. Through the Digital Twin accurate predictive studies based on scenarios of future operation can be performed. A well-trained neural net-based digital twin can produce the same key results as a thermodynamic model, but is several orders of magnitude faster, effectively enabling advanced analysis and optimization technologies.
The process of data reconciliation uses a thermodynamic model of the plant and information on the quality of the individual plant sensors together with statistical analysis to create a set of heat balance data that comes closest to the measured raw data and at the same time complies with the balances of mass and energy. Plant operations and maintenance teams benefit from reliable data and unbiased indicators of measurement quality.
This webinar provides an introduction to the basic concepts of thermodynamic process simulation and explains the necessity of heat balance analysis for conceptual design, off-design analysis and performance monitoring applications to maximise fuel efficiency. The application of a data validation model to generate a technically sound and consistent data set for process monitoring and review of the plant instruments is also covered.
Key takeaway objectives:
This webinar introduces the concept of and the key requirements for a Fuel Demand Model (FDM) for independent power plants. The use of a detailed thermodynamic model representing the entire power plant process – a so-called Fuel Demand Model – has proven to be the best solution for calculating guaranteed fuel efficiency in daily operations.
Key takeaway objectives:
– Dr. Josef Petek, Manager Commercial Operations
Explore our articles and other resources as a free download.
Physics-based modeling is the key to the correct representation of a power plant.
A digital twin of your power plant shows you current cost of operation
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