Sigmafine App for Thermodynamics

by Pimsoft Inc.

Empower AF with capability of evaluating thermodynamic properties of mixtures and crude oil assays.

Solution Overview

Conventionally, process engineers monitor the status of the plant by looking at measured data to understand process performance. Often however, they need to view process information that cannot be natively seen by measured data. For instance, a value such as the energy of a stream cannot be directly measured by instruments, but it can be estimated using process conditions like Temperature, Pressure and Composition. To view information that cannot be measured, it is common practice to import raw data into Excel or engineering applications. Engineers then re-work the data to generate the additional process information that is needed. This method is both time consuming and prone to human error during the manipulation of the data. In addition, the number of measured points is limited. This can lead to gaps in the inferred process information because large amounts of time need to be invested to create pseudo data points where measurements were not taken.

Born as a Sigmafine® extension to support large energy balances of refineries and petrochemical complexes, Sigmafine® App for Thermodynamics has now reached the maturity to live standalone. Natively integrated in the Asset Framework (PI AF), it leverages the OSIsoft® PI System® information and enriches assets characterization, enabling process engineers to access high value information by automatically inferring them from process measurements. On-line availability of un-measurable process data such has enthalpy, density, vaporized fraction etc. brings performance monitoring to the next level, allowing engineers to have actionable KPIs based on well proven thermodynamic methods. This results in better process insight and faster reaction time.

Solution Approach

Sigmafine® App for Thermodynamics consists of a set of functionalities readily available in AF that can add value directly to your existing assets. An extensive library of components is available within the package and source data can be directly referenced from existing AF attributes. Moreover it supports the characterization of crude oil assays based on the normal boiling point distribution. Vapor-liquid equilibrium is estimated through equations of state and an extensive set of properties can be retrieved both for the vapor and for the liquid phase (composition, molecular weight, density, enthalpy, entropy, specific heat, etc.). Sigmafine® App for Thermodynamics enables the Asset Framework to calculate key performance indicators and previously unknown process data to support process monitoring, energy balancing and energy management systems. All the desired process information consistently resides in one place in a clearly structured way. Since it is based on Asset framework of the PI System®, it makes the results available to every user that has permissions to do so and discloses the process engineer a full array of calculation and possibilities to support the daily work, still keeping them under control and adherent to corporate policies.

At-A-Glance

Features

  • Calculates unmesaurable process data such as enthalpy, density, vaporized fraction
  • Actionable KPI based on proven Thermodynamics methods and principles are now possible
  • Energy Balance calculations are now easier and more accurate
  • Handles multicomponent mixtures and evaluates vapor-liquid equilibrium and thermodynamics properties
  • Includes a database of physical properties as well as the possiblity to add new chemical species
  • Can predict Petroleum assays based on the laboratory distillaiton curve and pseudocomponents
  • PI Asset Framework 2016 and above
  • PI System Access (PSA) license
  • https://www.youtube.com/watch?v=E16JK5o-s8c

Solution Type

Advanced Analytics, Data Validation, Energy Management, Process Optimization

Industry

  • Chemical & Petrochemical
  • Oil & Gas
  • Power Generation

Business Impacts

Optimize Processes, Improve Energy Efficiencies

Category

Applications for the PI System