Belsim engineering offers software and services for modeling, monitoring, and optimization of power generation plants, conventional as well as nuclear.


For the nuclear power plants the modeling does not cover the nuclear power source and the primary loop. The model is mainly focused on calculating the core thermal power with the highest confidence possible by integrating contributions from the modeling of the secondary and tertiary loops. Increased confidence in the core thermal power reconciled values allows the operator to uprate the electric power output of the plant, with important financial gains and reduced investment. The reconciliation will also help identify and (re)calibrate erroneous sensors and deliver soft sensors for parameters that are whether not measured or cannot be physically measured (e.g. core thermal power).


The only component modeled in such application is water in its cycle as transfer agent of the atomic energy released by the nuclear fuel to the steam turbine generator that transforms it into electrical power.

Belsim and its partners deliver also studies of performance monitoring and optimization for parallel steam turbine trains aiming at guiding the plant towards the most efficient utilization of its assets. As electricity power outputs of such plants is enormous, digit increases in efficiencies and/or power uprating are translated into millions of dollars per year benefits.


A software that makes the difference



ValiEnergy is the preferred module licensed and utilized for the development of this type of applications. The associated models are developed based on a rigorous description of the physical and chemical phenomena taking place in such a plant, by capturing both, processing and utility, sides of the manufacturing process involved.


For such applications, Belsim develops reports with a drill down structure where user monitors high levels performance parameters with respect to a target or with respect to the best historical performance of the installation. Deviations and underperformance with respect to target are investigated by analyzing the trends of parameters that contribute to the calculation of these high-level performance parameters. By navigating from level to level, the underperformance root cause is determined and appropriated corrective measures are taken.


The use of reconciled data for monitoring and analysis of the performance parameters gives the user the advantage of having consistent sets of data to analyze, with clearer trends and straightforward parameter interdependence traceability. Correlations are easier to pinpoint with systems for which mass and energy balances are closed and performance parameters are no longer dependent on the calculation route, as opposed to contradictory values obtained when parameter is calculated with different, unreconciled measured values.


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