Tata Steel Power

8/11/2019 Tata Steel Power

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A linear Programming Model for

Distribution of Electrical Energy in aSteel Plant


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Guiding Principle

The guiding principle of this model is

that in the case of power shortage,

power is allocated to those non-essential loads which have a higher

contribution per unit.


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Introduction Optimal allocation of electrical energy is a very

important decision with the management of asteel plant.

This case study deals with the development andimplementation of a mathematical model for

optimal allocation energy in a steel plant.

Unlike in other studies, in this case study thesteel plant ha been modeled with a profit

maximization objective and energy as a limiting

constraint.


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Historical Development of the

Company

The steel company where the modelwas developed was the largest private

company in India. Started in 1907 in the

eastern part of India, it had grown over

the years and is now the second largest

steel company in India with a sales

revenue of approximately 1.05 billion

dollars. (1992)


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Goutam Dutta 5

Basic Flow Sheet in an Integrated

Steel Plant

Iron

Making

Steel

makingCasting

Rolling

Finish

Rolling

RM

Processing


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The model is now extensively used for the following:

1.Optimal allocation of the plant capacities to the various

markets.

2.To indicate the economics of individual products on an

overall basis.

3.The potential benefit of capacity expansion proposals.4.Optimal route of a product.

5.Best use of limiting processes like a bogie bottom

pouring, normalizing and cold drawing.

6.Break-even price of critical products like scrap, coal

and coke.


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102

97

92

87

82

77

72

AVERAGEP

OWER(MEGAW

ATT)

APR 86 JAN 87 JAN 88 JAN 89 JAN 90

WITH MODERNISATION, TATA STEELS DEMAND FOR POWER

CONTINUALLY EXCEEDS THE AVAILABILITY OF POWER.

POWER DEFICIT

POWER REQUIRED BY WORKS

POWER AVAILABLE TO WORKS


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Definitions, Assumptions and

constraints (contd..)

Power balance:

The four major components in the

power balance:

1. Power generation processors.

2. Power consuming processors.

3. External power purchased.4. Fixed power requirement.


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Power Flow in the Steel Plant :

POWER HOUSE NO 2

POWER HOUSE NO 3

POWER HOUSE NO 4

POWER HOUSE NO 5

D G SETS

EXTERNAL SUPPLY

POWER

SYSTEM

CONTROL

BY

CENTRAL

CONTROL

ROOM

ESSENTIAL LOADS

NON ESSENTIAL

LOADS

ASSOCIATED

COMPANIES

CITY POWER

Power Distribution Diagram


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Problem of Power Allocation in

our Steel Plant

Supply fluctuation

Demand fluctuation

Essential loads Domestic load or city power


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Definitions, Assumptions and

constraints

Processor: A processor is a unit which producessteel, hot metal or provides service to the steel plant.

Net Realization: The net realization of he product isthe difference between the price and the totaldeduction in the form of taxes, excise duties and

other dues in the government.

Variable Cost: This is the sum of all the materialcosts and the variable portion of the conversioncost.

Contribution: The difference between the netrealization and the variable cost of the product.


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Model Formulation

The model is based on linear

programming and hierarchical

optimization


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Processor

Very similar to a facility

It converts input/inputs (raw materials) to

outputs

It will consume electricity by knowing itsgiven by parameter (KWH/ton)

It may consume oxygen (NM3/ton)

It may consume fuel (Kcal/ton)


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Materials

It may be input/ WIP/output

A processor convert one material to

another material

Every materials have net realization,

variable cost.

When a material is processed in a facility,it has yield and OHPT or TPOH that is

required in LP formulation


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Model Formulation

The model is based on linear

programming and hierarchical

optimization


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Model Formulation

Objective : Maximize the Contribution to

Profit

Contribution = Net Realization-Variable

Cost

Constraints

Material Balance

Energy Balance

Oxygen Balance


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Model

400 equations

750 variables

200 marketing bounds

MPS-TEMPO (Burroughs 6800)

VAX VMS 2-3 min

Scatter diagram showing the line of best


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500

400

300

200

100

0

0 2 4 6 8 10 12 14 16

X-Axis: PRODUCTION (THOUSAND TONNES)

Y-Axis: POWER CONSUMPTION (MILLION KWH)

Y-INTECEPT = FIXED POWER (KWH/TONNE)

SLOPE = VARIABLE POWER

CONSUMPTION (KWH/TONNE)

Scatter diagram showing the line of best

fit of the total electrical energy consumed


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Model Implementation

Marginal contribution of power

Financial benefit after 1986-87

Financial benefit per unit after 1986-87Following are the graphs representing the

above three issues.


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120

100

80

60

40

20

0

10 15 20 25 30 35 40 45

X-axis :External MW

Y-axis :Rs.10000/MW

Marginal contribution of Power

70 At low levels of availability, the marginal contribution of power is very high;


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70

60

50

40

30

20

10

035 40 45 50 55 60 65

VARIABLE POWER (MEGAWATT)

MONEYUNIT

PERMONTH

At low levels of availability, the marginal contribution of power is very high;

as power becomes abundant, its incremental contribution drops sharply


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3.0

2.5

2.0

1.5

1.0

0.5

0

1986/87 1987/88 1988/89 1989/90 1990/91 1991/92

1.06

Prodn.

Expend.1.869

Gr. Rev. 2.04

Profit 2.79

Financial benefit after 1986-87


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3.0

2.5

2.0

1.5

1.0

0.5

0

1986/87 1987/88 1988/89 1989/90 1990/91 1991/92

Profit/ton2.62

Gr.Rev./ton

1.92

Expend./ton

1.75

Financial benefit per unit after 1986-87


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Before Implementation After Implementation

MEGAWATT PRODUCTON CONTRIBUTION

AN EMPHASIS SHIFT FROM TONNES/KWH TO CONTRIBUTION/VARIABLE KWH

LED TO OPTIMAL USE OF AVAILABLE POWER

Aug 86 Sep Oct Nov Dec 86


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Implementation problems in a

developing country

Social responsibility of the company

Data consistency

Linearity of some mills Software availability

C l i


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Conclusion In addition to deciding the priority in the case of power

crisis, planning the production target marketing

strategy, the model is being used in critical situations.The implementation of the model has not only had asignificant impact on the performance of theorganization, but has also enhanced the confidence ofthe top management in using Operations Research and

Management Science Techniques for making short- andlong-term business decisions. The model has beensuccessfully tested on a steel plant as well as on a tubemanufacturing plant. Since the power shortage situationis expected to continue for at least a decade in adeveloping country like India, these types of modelscan be utilized in other steel industries and other similarindustries to improve the industrial productivity andprofitability in a constrained situation.

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