Structural Design Optimization of 25 MVA 132 kV Power ...€¦ · • Customer's requirement ......

Name : Shantanu R Torvi, Prachi Khullar, Deosharan Roy Division: CG Global R&D Centre Category: Confidential

Structural Design Optimization of 25 MVA 132 kV

Power Transformer Tank Assembly

- Shantanu R Torvi, Prachi Khullar, Deosharan Roy

CG Global R&D Centre


Contents

• Introduction

• Problem Description

• Parameter Optimization of transformer tank

• APDL macro and Optimization variables

• Integration with OptiSlang

• Results and Discussion

• Conclusion

• Future Scope

• References


Introduction

• Customer's requirement - High Quality design, High performance, low cost.

• Optimization process is a complex process.

• FEA packages and optimization softwares enhanced the designer’s capabilities.

• Structural optimization and design improvements of transformer tank assembly

using ANSYS11 and OptiSlang software.


Problem Description

• Power transformers

• The pressure and vacuum tests

• The criteria for passing the tests


Problem Description (contd..)

• The objective is to minimize the weight of transformer tank keeping it structurally safe at

the same time. This has been achieved by effective usage of ANSYS and OptiSlang

capabilities.

• Formulation of problem includes:

A. Parameterization

B. State variables and objective function

C. APDL macro

D. Integrated use of ANSYS & OptiSlang


Flowchart showing Automation of Optimization

Parameterization of Problem - Defining Design

variables, state variable and objective function

Design variables: Stiffener

thickness, width, breadth,

stiffener height etc.

State variables:

Maximum equivalent stress,

Maximum deflection

Objective Function:

Tank Mass

Defining range/limit for design variables

Constraint on permissible value of state variable

Solving the Problem for optimization

using suitable algorithm

APDL code for FE analysis

Integration with OptiSlang

Formulation of Problem


A. Parameterization

• The step on side wall was removed after optimization inputs from electrostatic analysis.

• The parameters which defined basic dimensions of transformer tank (i.e. length, height

and tank wall thickness) are left unaltered.

• Only stiffener arrangement and its geometry are the parameters which have been defined

as design variables.


A. Parameterization (contd..)

The design parameters which would be varied i.e. the driving

parameters are listed below:

• tb: stiffener thickness

• bw: stiffener breadth

• bh: stiffener height

• sl: stiffener length

• n: number of stiffeners present in

span A

• x1: distance of stiffener from side

• n2: number of stiffeners present in

span B

• x3: distance of stiffener in span B to last

stiffener in span A (as shown in figure)


B. State Variables and Objective Function

State Variable-

• The limitation on mechanical strength (stress limitation parameter)

• Instability (deflection limitation parameter)

Objective Function-

• Total mass of tank assembly

Note:

• The existing tank design is fabricated and passed the required quality tests and checks

• Hence, the vacuum test simulation results for existing tank are taken as benchmark for

comparison.


C. APDL Macro

• APDL macro has been used for modeling

transformer tank and stiffener arrangement in

ANSYS, applying boundary conditions, loads

and solving for vacuum test simulation.

• Boundary conditions and loads include:

- Full vacuum (101325 Pa) on tank inner walls

- Base and top of transformer tank constrained

in all directions

• APDL also writes final results-state variable

and objective function values in an output

text file. This is required for integration with

OptiSlang.

APDL Code

Output

From

APDL


Input and state variables are needed to be re-defined in OptiSlang.

1. The range/limit in which the input design variables can vary are defined.

2. Constraint on permissible value of state variables:

• Maximum equivalent deflection < 10 mm

• Maximum equivalent stress < 688 MPa

• bw (stiffener width) => bh (stiffener height)

D. Integrated use of ANSYS with OptiSlang


3. OptiSlang uses non deterministic optimization method such as genetic algorithm and

evolutionary strategy for providing global optimum solutions with specified constraint

functions with combination of existing finite element analysis.

D. Integrated use of ANSYS with OptiSlang (contd..)

Evolutionary Algorithm

method has been used for

calculating optimized design

parameters.

Parameterization of input & state variables

from APDL code of baseline design


Results and Discussion

Existing Design

Optimized Design



Evolutionary Algorithm method used for calculating optimized tank design parameters.

Result of optimized design set:

Graph of objective function (tank mass in kg) along Y axis against the corresponding design set number along X axis



State Variables for best design Input Variables for best design


FEA Simulation Results: Equivalent Stress plot

Existing Design

Modified Design


FEA Simulation Results: Equivalent deflection plot

Maximum deflection observed is 9.86 mm

Maximum deflection observed is 9.81 mm

Existing Design

Optimized Design


Results Summary

Properties Existing tank design Optimized tank design Improvement

Equivalent stress (MPa) 688 568.9 17.31 %

Equivalent deflection (mm) 9.86 9.81 0.5 %

Tank mass (kg) 5370.82 4838.57 9.91 %

Reduction in tank mass (kg) 532.25

• Tank was further optimized by changing the profile used on short sides and inputs from

electrostatic and electromagnetic optimization.

• Optimized transformer tank and cover design has been validated under all mandatory loading

conditions.

• Recommended optimized design achieved an overall weight reduction of 15.6 % of existing tank

weight or 1037 kg.

• It also resulted in saving 2706 liters of oil.


Conclusion

• Successful optimization of design parameters subject to constraints by adjusting 8

parameters of the tank geometry is obtained.

• Optimization of box stiffener geometry and its arrangement was achieved thereby

reducing the tank weight by 9.91 percent.

• The total displacements on the side walls and maximum equivalent stress were reduced.

• Fully automated optimization process for transformer tank is established.

• This methodology can be used for other products also with proper parameterization of problem.


Future Scope

• Objective function can be modified so as include the cost consideration.

• For instance if welding cost is also to be considered, then its value as a function of

stiffener length and numbers can be defined


References

• Oliver Konig, Marc Wintermantel. CAD-based Evolutionary Design Optimization with

CATIA V5. EVEN - Evolutionary Engineering AG, Zurich, Switzerland.

• ANSYS 11.0 Help

• OptiSlang 3.1.0 Help

• Prashant Bardia, Optimal Support Locations and Component Placement for

Electronic PCB Assembly towards minimizing Vibrations. October 2010 ANSYS India

Conference

• P Radhaswamy, P Velrajan, P Duraimurugan and T. Andrew. Automation of Aircraft

Component Roof Fitting Clamp Optimization using ANSYS Workbench 11. October

2010 ANSYS India Conference

• Fernando Batista, Hélder Mendes, and Emanuel Almeida. Structural Optimization of

Power Transformer Tank Covers. 3rd International Conference on Integrity,

Reliability and Failure, Porto/Portugal, 20-24 July 2009.


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Thank you

Structural Design Optimization of 25 MVA 132 kV Power ...€¦ · • Customer's requirement ......

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