In Attempt to Better Understanding Natural Resource: End Use or Extraction Efficiency , Which is the better ?

8/9/2019 In Attempt to Better Understanding Natural Resource: End Use or Extraction Efficiency , Which is the better ?

1/7

M. Khairul Bahri

Review Model

Which is the betterend use efficiency

orextraction efficiency?

by :

Muhamad Khairul Bahri

POSTGRADUATE PROGRAM DEVELOPMENT STUDI ES

SCHOOL OF ARCHI TECTURE, PLANNI NG AND POLI CY DEVELOPMENT

I NSTI TUT TEKNOLOGI BANDUNG

2008


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M. Khairul Bahri

Phenomenon:Efficiency in Natural Resource Utilization.Problem : Which is the better end use efficiency or extraction efficiency.

This paper is a further task of Annababette Willss End-use or extraction efficiency in natural resourceutilization: which is better ? (System Dynamics Review vol 14, 1998, page 163-188). Wills (1998) stated thatend use efficiency is socially optimal for society need.

Differ from Willss work, this paper focus on understanding dynamic interaction between two types ofefficiency. My paper conclude that from starting time, end use efficiency is a very important factor but untilits time, extraction efficiency will need more notice to support society need.

The first modified Model

sector subsitution

sector mining

sector service

service

subsitution_tim

cum_service_demand

substitution_fraction

potential_subsitution_fr

Cumulative_Use

ice_per_service_unit

umulative_Use

service_demand

price_per_service_unit

max_subsitution

unit_cost


unit service_demand

end_use_efficiency

market_size

price_subsitute

substitution_change_rate

percent_RD

Annual_demand

Annual_demand

actual_cost

effort_multiplier

ciu

fract_extraction_cost_fixed

RD_investment

mining_selling_price_to_service

mining_margin

extraction_efficiency

derivn_actual_cost

fraction_extraction_cost_dynamic

Profit_Loss

sales_revenue

operating_cost

switch_1

By modified Willss work, this model has new variables: Profit_Loss, Mining_Margin, Mining_selling_priceto service, derivn_actual_cost (the first derivative of actual cost variable) and fract_extraction_cost_dynamic.

List Variables

Endogenous Exogenous ECumulative Use, Cumulative Service

Demand (Resource)Cost Increased Unit(Resource)Maximum Subsitution Fraction (dimensionless)

Government Subsidy ontechnology development

Effort Multiplier(Dimensionless)Actual Cost(US$/ Resource)

Unit, unit cost, substitute price (US$/Resource)

Use Rate, Service Demand(Resource/year)

Subsititute Teechnology Adjustment, delayefficiency technology (year)

Price/Service Unit (US$/ Resource) Efficiency Initial (Technology)Subsitution Fraction,PotentialSubsitution Fraction (Dimensionless)

Initial Market Size (resource/year)Market Growth Rate,percent invested(dimensionless)

Cost all efficiency type (US$/technology)Sales Revenue, R-D Investment(US$/year)

All type Efficiency (Technology)Profit US$/year


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M. Khairul Bahri

In short words, this model work on two basic principles, if profit_loss > 0, then allocate it to RD_investment

and if derivn_actual_cost greater then RD allocation (research and development) for extraction also rise.

This model sums that we need interact dynamically between two efficiency, indeed extraction efficiency

need more allocation while extraction go to very expensive matter to support society need.

Time

cum_

service_

demand

0 50 100 150 20

0

500

1.000

1.500

2.000

2.500

1 2 31 2

3

12 3

12

3

1

Time

service_

demand

0 50 100 150 200

0

10

20

30

40

1 2 3

12 3

1 23

12

3

1

3

Time

price_

per_service_unit

0 50 100 150 200

0

1

2

3

4

5

6

1 2 31 2 3

12 3

12 3

3

Time

actual_cost

0 50 100 150 200

0

10

20

30

40

1 2 3 1 2 31 2

3

12

3

3

Time

substitution_

fraction

0 50 100 150 200

0,0

0,1

0,2

0,3

0,4

12 3 1 2 3

12

3

12 3

3

Time

Cumulative_

Use

0 50 100 150 200

0

200

400

600

1 2 3

12 3

12 3

12 3

1

Line 1 and 2 allocation of 15%, 20% for extraction

technology of sales revenue (switch_1=0). Whileswitch_1 set 1, line 3 show that extraction efficiency

has dynamics RD funding as the right equation.

DERIVN(actual_cost)

GRAPH(derivn_actual_cost,0,0.1,[0,0.08,0.2,0.3,0.4,0.5,0.6,0.65,0.7"Min:0;Max:1.5"])*(1-

switch_1)+switch_1*fract_extraction_cost_fixed

Time

end_

use_

efficiency

0 50 100 150 200

0,0

0,2

0,4

0,6

0,8

1,01 23

12

3

1 23

1 2 31

Time

extraction_

efficiency

0 50 100 150 200

0,0

0,2

0,4

0,6

0,8

1,01 2 3

12

3

12

3

12 3

1

The simulation shows that to fulfill society needs, we need dynamics interaction between two efficiency. The

right-above graph reveals that extraction efficiency more important since year 150.


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M. Khairul Bahri

Time

Cumulative_

Us

0 50 100 150 200

0

200

400

600

1 23

12 3

12 3

12 3

1

Time

Annual_demand

0 50 100 150 200

1

2

3

4

5

12

3

1

2

31 2 3

12

3 1

3

The second modified Model

The second modified model based on addition of profit loss variable for two sector (mining and service). If

actual costgreater then R&D for extraction costrise. In service sector, if subsitution greater then we shall

rise R&D for end use efficiency. For comprehensive view, how important combination between two

efficiency, effort equation change to be ((1+(Cumulative_Use/ciu)^8) and simulation time set to 300 years-

simulation.

Extraction Effort

Cumulative UseExtraction Cost

Sellin rice minin to service

Annual Demand

Potential Subsitution

Actual Subsitution

Market Size

-

-

-

-

RD Investment

Extraction

Service demand

-

Sales Revenue

Sector Mining

Selling price in society

Extraction Cost

Operating cost

mining

-Derivn

Extraction Cost

Extraction

Efficiency

ales Revenue

ector Service

Operating cost

service

RD Investment

End Use

-

End Use

Efficiency

-

-

Actual Subsitution

Derivn Actual

Subsitution


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M. Khairul Bahri

By looking at causal loop we simply can conclude that RD for extraction efficiency rise while actual cost

more expensively. In line with that, if subsitution rise then service sector tend to set greater RD funding for

end use technology.

End Use Efficiency-end value Extraction Efficiency-end value

Simulation 1 0,0720 0,0787

Simulation 2 0,0342 0,0553

Simulation 3 0,0698 0,0608

Simulation 4 0,0332 0,0430

Simulation 1 : variablepercen_RD_extraction danpercen_RD_end-use not increase.

Simulation 2 variablepercen_RD_extraction not increase while percen_RD_end-use increased twice;

Simulation 3 : variablepercen_RD_extraction set twice andpercen_RD_end-use no incresae;

Simulation 4 : variablepercen_RD_extraction and percen_RD_end-use set twice together.

Simulation reveals that increasing percen_RD_end-use force setting higher of extraction efficiency. This

simply give us more understanding that society need two efficiency work together dynamically.

sector market

sector subsitution

sector mining

sector service

service

previous_market_size

Cumulative_Use

umulative_Use

service_demand

market_size

Annual_demand

sales_revenue

substitution_change_rate

end_use_efficiency

unit

Annual_demand

service_demand

price_subsitute

potential_subsitution_fract

price_per_service_unit

max_subsitution


service_demand


unit_cost

erivn_actual_cost

operating_cost_sektor_service

Profit_Loss_Service

selling_price_mining_to_service

previos_ms_x_mkt_growth

ubstitution_fraction

subsitution_tim

rofit_Loss_Service


sales_revenue_service

percent_RD_extraction

cum_service_demand

initial_market_size

market_growth_rate

actual_cost

ciu

RD_extraction_te

derivn_SF

RD_end_use_tech

effort_multiplier

percent_RD_extraction

mining_margin

market_size

e_per_service_unit

end_use_efficiency

service_margin

percent_RD_end_use

selling_price_mining_to_service

operating_cost_mining_sector

Profit_Loss_Mining_Sector

selling_price_in_society


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M. Khairul Bahri

Time

service_

demand

0 50 100 150 200 250 300

0

5

10

15

20

1 23

4

1

2

3

41

2

3

4

1

2

3

4

1

2

3

4

1

2

3

4

1

2

Time

cum

_service_

demand

0 50 100 150 200 250 300

0

1.000

2.000

3.000

1 2 34

1 2 3

4 1

2

3

4

1

2

3

4

1

2

3

4

1

2

3

4

1

2

Time

price_

per_service_

unit

0 50 100 150 200 250 300

0

5

10

1 2 3 4

1

2

3

4

1 2

3

4

1 23 4 1 2 3 4 1 2 3 4 1

Time

actual_cost

0 50 100 150 200 250 300

0

50

100

150

200

1 2 3 4 12 3

41

2

3

41

2

3

4

1

2

3

4

1

2

3

4

1

2

Time

extraction_e

fficiency

0 50 100 150 200 250 300

0,0

0,2

0,4

0,6

0,8

1,012

3

4 1

23

4

1

23

41

2 34

12 3 4

12 3 4

1

Time

end_

use_

efficiency

0 50 100 150 200 250 300

0,0

0,2

0,4

0,6

0,8

1,012

3

4

1

2 3

4

1

23

41

23

41

23

41

23

41

Time

substitution_

fraction

0 50 100 150 200 250 300

0,0

0,2

0,4

0,6

0,8

1,0

12 3 4

1

2

3

4

1 2

3 4

1 2 3 41 2 3 4 1 2

Time

Cumulative_

Use

0 50 100 150 200 250 300

0

100

200

300

400

500

1 23

4

1

23

41

2 34

12

3

4

1

23

4

1

23

4

This simulation has wider conclusion that extraction, end use dan subsitution (technology) has dependent andimportant rules to fulfill society need. While non renewable resource tend to scarce , subsitution technology

will has very important concern.


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M. Khairul Bahri

sektor technology

best_extraction_technology

avg_extract_efficiency

end_use_efficiencybest_end_in_use

best_end_use_efficiency

cost_extract_tech_advance

best_extraction_tech_in

extraction_tech_change_delayed

end_use_efficiency_delayedcost_end_use_efficiency

delay_time

best_extraction_technology

extraction_technology_initial

old_extraction_tech_out

efficiency_initial

average_end_use_efficiency

old_end_use_out

technology_residence_time

delay_timeavg_extract_efficiency


extraction_tech_res_time

RD_end_use_tech

end_use_efficiency_expected

RD_extraction_tech

extraction_tech_advanced

Documents

In Attempt to Better Understanding Natural Resource: End Use or Extraction Efficiency , Which is the better ?