energy conservation policy in indian cement industry

8/10/2019 Energy Conservation Policy in Indian Cement Industry

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A Report on

Analysis of options for Energy

Conservation Policy in Indian Cement

Industry

Submitted to Arvind Sudarshan

ECON F343

Economic Analysis of Public Policy

Prabeen Ghadia

2011B3A4382P

BIRLA INSTITUTE OF TECHNOLOGY AND SCIENCE,PILANI RAJASTHAN-333031



Introduction

The success of any programme such as the one on energy conservation greatly

depends upon correct identification of various program plan sub-elements,

specially the objectives and consequently evolving appropriate policy options tofulfil those objectives. Options always come from different areas; the important

thing is to unify them to create an integrated policy. The options always revolve

around the objectives and their importance can be decided by using certain

features having certain linkages with the objective measures and the activities

features of the programme plan. Based on the options finalised, activities are

identified and scheduled.

The next big decision that the decision makers face is to choose the correct

option. They normally take many considerations related to technological,

political, economic and social factors or a combination of these factors. The

policy formulation for energy conservation in an industrial sector depends on

many considerations, such as: the present technological status, new

developments, and quality of inputs like coal and raw materials, availability of

power, transportation facilities, manpower, managerial skills, financial

resources, the product, the market dynamics, government regulations and local

factors.

Methodology for analysis

It has two steps; one is the identification of options for achieving the desired

objectives and second is the evaluation of options and their prioritisation. Policy

formulation is the process of generating a framework of preferences of options

for the given objectives.

There are two methods used to analyse for the energy conservation policy,

Delphic Hierarchy process (DHP) and Fuzzy Set Methodology (FSM).

1.

Delphic Hierarchy Process : It consists of two parts; one is Delphi

methodology which is used to identify various options and features and

second is Analytic Hierarchy process which is used for an indepth study

to the decide on the weightages attached to each feature.

Delphi is the systematic method for obtaining the experts’ views on a

subject. The 3 features of this method are anonymity, controlled feedback

and statistical group response. The exercise is done by a monitor team

who prepare a questionnaire for obtaining response of the experts



engaged in different but related activities to the subject. The important

aspect of this technique is that each expert has enough time to give their

considered views on the subject without being influenced by others who

are participating in the survey. The responses of the experts when

received are aggregated by the monitor team using statistical methods of

analysis and are then sent for second round of response. The process is

repeated is three or four rounds by which various divergent views of the

experts narrow down and consensus emerges on various issues.

2.

Fuzzy Set methodology: This method is used to incorporate both

quantitative and qualitative view points of the interest groups in the

decision making process . Ranks of the options are achieved through a

dominance matrix designed for the purpose. In order to represent the

views of each of the interest group, a position matrix is prepared from the

response of all the experts in the groups by giving the values to the

qualitative assessment. By raising the membership values to the power of

the assigned weight, some of the biases in the matrix can be eliminated.

The most useful aggregation of the various matrices is the pessimistic

aggregation This results in a matrix of worst-case membership values and

is the intersection operation. The other two aggregations are optimistic

and mean aggregation. Taking the values from these aggregations, three

separately weighted position matrices, the optimistic, pessimistic and

mean position matrix are prepared.

An n*n matrix ‘D’ called dominance matrix is prepared to display the

dominance structure between all possible pairs of options. The element

dij is the number of features for which menmbership values of option j

dominates or is greater than option i.If the Kth colun is summed, the total

number of dominances of option K over all other options is obtained.

Simialrly, if the Kth row is summed, the number of times the Kth option

is being dominated by all the other options is determined. Most

favourable options have higher column sums and lower row sums. The

rank of the options is normally decided by examining the ranks obtained

from the extent of dominance and alos the extent of being dominated by

other options.

Hadley Criterion : One could adopt tany of the alternatives of dominance,

i.e. pessimistic, the safest course of action; the optimistic, the most

wanted course of action and the mean, the middle course of action. Soo



the decision makers use Hadley criterion of cautious optimism to decide

the best course of action. If A is the dominance weight of the option as

determined from optimistic dominance matrix and B the dominance

weight of the option as determined from the pessimistic dominance

matrix and a be the coefficient of optimism, then the weight of the option

is determined as :

W = a A +(1-a) B

A sensitivity analysis is made by taking different values of a and

considering different alternatives. Sensitivity analysis provides various

schemes for the hierarchy of options. The most appealing scheme is

selected and referred to the experts for feedback which is further adopted

as a policy framework.

The Case of the Indian Cement Industry

Identification of options: The monitor team identified 21 energy

conservation options (ECOs) keeping view the objectives of program

plan. 34 experts were identified from the interest groups like cement

producers, cement machinery manufacturers, research institutes,

consultants, technological institutes, government departments. They were

requested to give weightage using a scale of 0-10, 10 being the most

important option. The experts themselves added a few more options and

changed their view after 1 round giving a more concrete result.

The monitor team used Delphi technique to obtain the responses from the

experts of each group in the form of position matrices. Taking the

qualitative judgements of the position matrices, the monitor team made

all the dominance matrices.

Schemes

ECOs

100%

opt

80%

opt

60 %

opt

50%

opt

40%

opt

20%

opt

0%

opt

Avg

1 2 2 2 2 2 2 3 4

2 9 7 5 4 4 4 5 2

3 1 1 1 1 1 1 1 1

4 12 12 12 12 14 11 11 14

5 3 5 8 7 9 13 16 6

6 7 9 9 8 8 10 12 13

7 8 6 6 6 6 5 6 5

8 10 10 7 6 5 4 4 3

9 15 14 14 15 16 15 15 1710 17 16 13 13 12 7 8 10



11 20 20 19 19 20 19 19 20

12 11 11 11 10 11 8 9 8

13 5 4 4 5 7 6 7 7

14 6 8 10 9 10 12 14 18

15 4 3 3 3 3 3 2 916 13 13 12 11 13 9 10 11

17 19 19 18 18 19 18 19 15

18 16 17 15 14 15 14 13 12

19 18 18 17 17 18 16 17 16

20 14 15 16 16 17 17 18 19

A sensitivity analysis is done by working out the weightages of options with

different weightages of optimistic dominance along with related pessimisticdominance, say, 20, 40, 50, 60, 80, 100% through optimistic dominance

matrices. In this way 8 schemes were built according to different coefficient of

optimism. The most appropriate scheme has been found to be scheme 3, 60%

optimism and 40% pessimism.

The final policy framework was built on the ranks given by the experts. The

results were given for further feedback but it didn’t bring any major change.

Sl.

no

Item Avg

wt

Rank

(round

1)

Avg

wt

Rank

(round

2)

Final

Rank

(FSM)1 Use of Energy efficient equipment 8.12 3 8.04 1 2

2 Energy Audit 7.88 4 8.02 2 5

3 Top management involvement 10 1 7.77 3 1

4 Fiscal incentives for energyconservation

7.24 6 7.42 4 12

5 Development of energy efficienttechnology

7.24 6 7.22 5 8

6 Management of direct energy waste 7.28 5 7.22 5 9

7 Upgradation of technology 7.16 8 7.2 6 6

8 Energy performance monitoring on acontinuous basis

7.2 7 7.16 7 7

9 Load Management and load scheduling 10 1 7 8 14

10 Operational improvement at unit 6.84 10 6.9 9 13

11 Creation of funds on soft terms 7 9 6.7 10 19

12 Instrumentation and automation 6.66 12 6.66 11 11

13 Creation of posts of chief energyconservation

9 2 6.59 12 4

14 Control and monitoring of quality of

coal and power installation

6.84 10 6.58 13 3

15 Rationalisation and Standardisation 6.72 11 6.58 13 10



16 Organisation of energy management 10 1 6.54 14 12

17 Preparation of energy conservation planfor 5 year period

6.44 15 6.52 15 18

18 Training of Personnel 6.56 13 6.52 15 15

19 Increasing awareness of energy

conservation

6.48 14 6.52 15 17

20 Management of Indirect energy waste 6.16 16 6.38 16 16

21 Licencing policy conforming tominimum energy efficient standards

6.16 16 6.2 17 20

22 Creation of motivation by institution ofawards

6.08 17 5.94 18 21

23 Development of energy efficient model plants

8 4 5.93 19 22

24 Creation of data bank 5.72 19 5.78 20 23

25 Adoption of energy conservation law 5.69 20 5.4 21 24

26 Basic technical education in energymanagement

6 18 5.11 22 25

27 Implant R&D 6 18 4.86 23 2628 Use of appropriate guide norms 4 22 4.86 23 26

29 Substitution of source of energy 4.6 21 4.76 24 27

30 Institutional R&D 6 18 4.73 25 28

Conclusion

The identification of the energy conservation options is of paramount

importance to decision making process for a sound policy framework for energy

conservation I the cement industry. The joint use of Delphi Hierarchy processand Fuzzy set methodology has been demonstrated through a case study to

determine the ECOs and to derive the priorities amongst them in a multi person

decision making situation using multiple criteria for evaluation.

energy conservation policy in indian cement industry

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