Thursday, September 1, 2016

FREE WEBINAR: Transform refinery operations for improved profitability with RefineryWise™

SimSci Webcast
Transform refinery operations for improved profitability with RefineryWise™
Tuesday, September 20, 2016 | 11 a.m. EDT / 10 a.m. CDT | Register Now

Refineries are challenged with sustaining and improving margins, and retaining knowledge from a retiring workforce. Embarking on a journey of transformation based on Refinery Digitization is imperative for improved profitability and sustainability. RefineryWise™ from Schneider Electric Industry Solutions focuses on improving refinery operations business processes and workflows. A holistic approach for the oil and gas industry, it includes performance management, technology adoption and lifecycle optimization, RefineryWise helps to improve revenue by up to 5% and lower operation costs by up to 10%. Learn how RefineryWise can be part of your business strategy to drive higher profitability.

Register now for this free, live webcast and join this esteemed group of speakers on Tuesday, September 20, 2016 at 11 a.m EDT /10 a.m CDT. Participants will be able to participate in a live question and answer session.

Friday, June 17, 2016

Announcing the release of DYNSIM 5.3.1

DYNSIM™ 5.3.1 – is now available on the Global Customer Support site


What is it?

DYNSIM™ provides rigorous process simulation platform from simulation and training offerings from SimSci. DYNSIM is a rigorous, first-principle dynamic simulator that predicts the time dependent behavior of industrial processes. A well designed DYNSIM model accurately depicts the same hydraulic, heat transfer and other equipment constraints as the actual plant.

Why is this important?

DYNSIM™ provides a single scalable application that helps:

· Lower capital costs and improve plant design—getting it right the first time

· Design checkout control systems for Programmable Logic Controllers (PLCs), Emergency Shutdown Systems (ESDs) and Distributed Control Systems (DCSs), thus providing shorter commissioning time and increased availability

· Train and certify control room and field operators in a safe environment

Simply stated, DYNSIM enables clients to rise above the dynamic challenges of designing, commissioning, controlling, and operating a process plant safely, reliably and profitably.

What is new?

DYNSIM™ 5.3.1 offers:

· Added infrastructure support for Windows 10 Enterprise, Windows 8.1 Enterprise, Java RTE 1.8, Microsoft Excel 2013, and Flexera 11.13 licensing

· Password-protect flowsheets to prevent access to sensitive (IP) information or user-added models

· A new 3-way valve model which improves data entry and can be used directly in operator training

· New functionality which expands the simulation of tower pressurization and flooding

· Enhancements to DYNSIM Power Steam turbine library, reactions in M3Header and M3Drum models, and Mixer/Splitter input


Tuesday, April 26, 2016

Critical Update for PRO/II - Announcing the release of PRO/II 9.3.4

Critical PRO/II Update: Recently a user found a defect in PRO/II where the program re-formatted the user's external drive when a specific set of steps were performed. While determining the root cause, we discovered that this defect dates back to versions 8.x, so it is imperative that you upgrade to PRO/II 9.3.4 to eliminate the occurrence of this remote possibility. Please contact your local technical support office if you have any questions.

Monday, April 4, 2016

Update to SimSci Licensing Options

Dear SimSci Software User,

This post provides an update on the licensing and security options from Flexera Software, who produces the security software that SimSci software products use for LAN, WAN, and Token Licensing. While Flexera Software FLExNetPublisher (FNP) 11.8 is currently widely used among SimSci customers, it has reached the end of limited lifecycle support. In an effort to support our customers, SimSci now supports the latest version of FlexNetPublisher, 11.13.

The SimSci team is implementing the following plan:
  • Existing FNP 11.8 security licenses will be upgraded the next time they are renewed to FNP 11.13 or the most recent version. However, we do recommend that you upgrade at your earliest opportunity to avoid any potential problems.
  • Older FLEXlm licenses will continue to work, however, if they stop working before the renewal period, they must be upgraded to FLEXlm 11.13 or latest.
  • Future installations of SimSci software will allow FNP 11.13, FNP 11.12, FNP 11.11 and respective TOKEN versions, and USB security options.
  • You can download the most recent server software installation and retrofit package to upgrade all your SimSci software from the Global Cutomer Support (GCS) site.
  • Customers migrating to Windows 10 must upgrade to FNP 11.13 immediately as previous versions of the server do not install in Windows 10.
We appreciate your patience through the migration and will do our best to minimize the impact on your use of our products. Please contact technical support if there are any problems.

Regards,

The SimSci Team

Tuesday, March 29, 2016

How does SimSci Software achieve Operational Excellence in O&G?

Customer Content verified by TechValidate.

Friday, March 18, 2016

What is Operational Excellence?



What is Operational Excellence?
Over the last few years, I have heard the term “operational excellence” become more frequently used. I always thought I knew exactly what it meant: “making your operations run at peak performance.” However, as I heard the term used more often it seemed to also be used to encompass a wider variety of applications and circumstances, so I thought I would do some research to find out exactly how “operational excellence” was defined. That turned out to be a huge undertaking since there are so many definitions. However, I was able to see some clear themes that would lead to my own definition. It is clear that results are important, as is consistency, efficiency & effectiveness. 

Taking Operational Excellence to the next level
Since my experience has been shaped by the process industries, I will say that in my opinion, this is my best guess at the definition of “operational excellence” as it applies to the process industries.
Operational Excellence is the attainment of efficient, effective & reliable operations to achieve optimal profitability for the process. However, operational excellence will only get you the results you desire if you are focused on the right business strategy.  Operational Excellence at producing product A is great, however, when product B is preferred, you are missing out.
It is also important to understand that Operational Excellence isn’t achieved overnight. It is a methodology that takes a commitment to focusing on continually improving the process, and its operator, over the long term. 

Why is Operational Excellence important to you?
One word: profitability. All business is centered around profitability; it is the revenue produced by the process that pays for your salary. 

Tools for Operational Excellence
I feel that there are four ways that SimSci software from Schneider Electric can assist you in achieving operational excellence:
·         Continuous Improvement
·         Actionable Intelligence
·         Workforce Optimization
·         Managing & Lowering Risk.

Don’t just take it from me – we surveyed our customers (using TechValidate) asking them several questions about Operational Excellence. For instance 89% of our customers feel that SimSci software helps them achieve operational excellence (TechFact). Additionally, our customers provided details on how SimSci software helped them achieve Operational Excellence. You can see in the results below that SimSci helps customers in many ways.

In the coming weeks I am going to publish blog posts on all four of these topics, so stay tuned. But in the meantime, please use the comment section to tell me what “Operational Excellence” means to you?

In September, SimSci will hold their annual event, Simulation for Business Excellence, in Pasadena, CA where the theme will be Operational Excellence. Please visit the conference website and consider attending.
http://www.simsci.com/2016NAConf.com

Tuesday, March 1, 2016

Optimizing your utility energy with MINLP in SimSci ROMeo



By: Rajkumar Vedam & Samantha Weaver of Schneider Electric

Utility energy optimization has the potential to provide significant cost savings through good management of your energy resources. Typically, energy optimization involves switching in and switching out different energy sources depending on market conditions. Traditional nonlinear programming (NLP) solvers, while powerful, are not suitable to investigate cases that require this kind of switching. Switching in or switching out energy sources changes the fundamental process equilibrium of the simulation, which will cause problems for traditional NLP solvers. In these cases, mixed integer nonlinear programming (MINLP) provides the means to optimize processes by taking into account the new nonlinear process equilibrium introduced by the changing energy sources.

Mechanics

Schneider Electric Software’s ROMeo from the SimSci brand offers a MINLP solver that can solve the advanced MINLP problems that are inherent to utility energy optimization. The MINLP problem expands the NLP problem to include a set of integer variables representing the on or off state of the different energy sources that must be accounted for. Using the powerful and reliable NLP solver in ROMeo, the MINLP solver solves a series of NLP problems, each with a unique configuration of energy sources. It uses the branch-and-bound algorithm to prune out infeasible or non-optimal solutions to arrive at the most optimal configuration of energy sources.

Figure 1: An example of a MINLP solution tree for a model application that contains 5 integer variables.

The MINLP solver is customizable and includes a set of MINLP solver tuning parameters that allow you to fine tune the MINLP solver to provide for faster and more efficient solutions. You can manage the MINLP solver tuning parameters in the same way that you manage the NLP solver tuning parameters, that is, by using the ROMeo Solver Manager.
The MINLP solver can switch on or switch off only the energy sources that you expose to the MINLP solver. ROMeo includes a non-process unit, the MINLP Switch, that you can attach to your energy sources. This allows the MINLP solver to access the variables and parameter within the energy source and selectively switch on or switch off those energy sources. In this way, you have full control of the optimization processes.

Easy Conversion between NLP and MINLP Operations

ROMeo includes a specialized MINLP calculation mode that allows you to easily switch between MINLP operations and traditional NLP operations within ROMeo. You can manage the MINLP calculation mode in the same way that you manage the other ROMeo calculation modes through ROMeo’s Mode Manager.

Easy Access to MINLP Variables

Because a single model application may have numerous MINLP-switchable energy sources—and thus numerous MINLP variables—ROMeo includes the MINLP Manager. The MINLP Manager consolidates the MINLP Switch information for easy access and configuration. It also provides a means to group the integer variables in the MINLP Switches, which reduces the computational load on the MINLP solver.

Efficient Design: Grouping

Due to the larger number of variables and NLP solutions in question, MINLP solver runs can be costly in terms of processing time. To reduce the computational load on the MINLP solver, ROMeo provides grouping mechanisms for related integer variables.
Specifically, the MINLP Manager allows you to group variables that turn on or turn off depending on the values of other integer variables. For example, if you have a Motor that turns on when another Motor turns on, you can group the integer variables for the two Motors.
You can also specify complements with the grouped variables. For example, if you have a Steam Turbine that must be off when a Motor is on, you can group the integer variables for the Steam Turbine and the Motor and set the Steam Turbine’s integer variable as a complement.
Grouping greatly improves the efficiency of finding an MINLP solutionin terms of both speed and robustnessby restricting the MINLP search to the specified constraint space.

Types of Utility Energy Optimization

The MINLP solver currently allows for three types of utility energy optimization: Utility Units, Fuel Sources, & Parallel Streams. A single ROMeo model application can include all three types. More information on all three types of energy optimization and the associated business values are found below.

Utility Units

The first type of energy optimization allows you to optimize the configuration of utility units in your plant. Your plant model may contain numerous utility units, such as Motors, Generators, and Steam Turbines. You can specify economic data for these units and attach MINLP Switches to them. The MINLP software can then switch on or switch off these units during an MINLP solver run. The MINLP solver finds the optimal set of utility units that should provide the energy requirements for your model application. You can choose to keep this MINLP solution or discard it.

Figure 2: AN MINLP model application that optimizes the utility unit configuration between a Motor, Steam Turbine, and Generator.

Fuel Sources

The second type of energy optimization allows you to optimize the fuel sources that are used in the combustion heating of your plant. Specifically, the MINLP solver can optimize the combustion fuels that are fed to a boiler. A boiler may have multiple combustion fuel sources. The MINLP solver can switch on or switch off the fuel streams based on the economic data provided for those fuel streams. This applies to both the Boiler and the ERTO Boiler models in ROMeo.

For Boilers, you can specify economic data for the fuel streams in their associated Sources and attach MINLP Switches to the streams. The MINLP solver can then switch on or switch off these process streams during an MINLP solver run. The MINLP solver finds the most economical combination of fuels and turns off any fuel streams that are not needed to meet the energy requirements of the Boiler.
 
For ERTO Boilers, if the fuel streams are external to the ERTO Boiler model in the model application, you can specify economic data for the fuel streams in their associated Sources and attach MINLP Switches to the streams. The MINLP solver can then switch on or switch off these process streams during an MINLP solver run. The MINLP solver finds the most economical combination of fuels and turns off any fuel streams that are not needed to meet the energy requirements of the ERTO Boiler.

Figure 4: An MINLP model application that optimizes the fuel sources for an ERTO Boiler with external fuel streams.

If the fuel streams are internal to the ERTO Boiler model in the model application, you can specify economic data for the fuel streams within the ERTO Boiler model and attach MINLP Switches to the variables associated with the fuel stream in the ERTO Boiler model. The MINLP solver can then switch on or switch off these process streams during an MINLP solver run. The MINLP solver finds the most economical combination of fuels and turns off any fuel streams that are not needed to meet the energy requirement of the Boiler.

Figure 5: An MINLP model application that optimizes the fuel sources for a ERTO Boiler with internal fuel streams.

Parallel Streams

The third type of energy optimization allows you to optimize parallel process streams in your plant. The parallel streams can either terminate at a common Mixer or originate from a common Splitter. You can specify economic data as you would for traditional model applications. Typically, the parallel streams are the beginning or end of parallel process trains that are similar but contain different configurations of utility units. In this case, you attach MINLP Switches to each parallel stream. The MINLP solver can switch on or switch off the parallel streams and by extension, the parallel process trains in your plant. The MINLP solver finds the optimal process train that should provide the energy requirements for your model application.


 





Figure 6: Two MINLP model application that optimize parallel process streams within a model application. The first model application (A) uses parallel streams that terminate in a common Mixer. The second model application (B) uses parallel streams that originate from a common Splitter.

Conclusion

Good management of your energy resources through utility energy optimization provides significant cost savings. The MINLP solver in ROMeo software effectively extends the range of utility optimization strategies to include dynamically switching on and off various energy resources depending on the prevailing market condition. Use ROMeo for energy optimization to optimize your utility units, your energy sources, or parallel flows to minimize your energy costs and boost your profitability.