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Process modelling and industrial energy use in developing countries—The steel industry in India
OMEGA Int. I of Mgmt Sci.. Vol. 13, No. 4. pp. 295-306, 1985 Printed in Great
Britain. All rights reserved
0305-0483/85$3.00+0.00 Copyright~ 1985PergamonPress Ltd
Process Modelling and Industrial Energy Use in Developing CountriesThe Steel Industry in India G ANANDALINGAM University of Virginia, USA D
BHATTACHARYA
Tata Energy Research Institute, New Delhi, India (Receiced October 1984; in rerisedform February 1985)
A process model is used to study energy use and conservation in the steel industry in India. Production is modelled by a set of inter-connected process activities, each of which defines unique relationships between process output and a number of inputs. Contrary to that in process models for the U.S., we do not assume cost minimizing behavior. Simulation results show that although a number of cost-efl'eetive energy conservation measures exist, none of them would lead to significant reductions in energy use. Effective policy for the Indian Steel industry would require combining the strategies.
established, decision makers in LDC's are faced with the choice of investing in energy conserINDUSTRIAL energy demand has grown faster vation retrofits or in modifying sections of the than energy consumption in other sectors of the production process by substituting energy economy in most developing countries. As less efficient technologies for older technologies that developed countries (LDC's) industrialize, a are less efficient. For instance, many LDC's are larger component o f investment goes into converting from open hearth furnaces to basic energy intensive sectors such as steel, cement oxygen furnaces for making steel, while mainand aluminium. In addition to the mix of prod- taining older technologies for the rest of the ucts, the increase in industrial energy use also steel production system. Decisions regarding energy conservation depends on the technologies used to produce retrofits or process changes should be made them. Ever since the tremendous increases in the oil after a systematic analysis of the industry, which price in the 1970's, new manufacturing tech- examines the flow of materials and energy nologies and processes have become more through the industry. We need an approach energy efficient. Hence LDC's that invest newly whereby activities in the different sections of an in some sectors have the choice of buying old industry are modelled explicitly as are the intertechnologies cheaply or in investing in new action between the different activities. Industrial energy efficient technologies, which cost more. process models have been used for a number of Many developing countries have opted for the years to represent energy and material flows latter decision. For instance, refinery operation within an industry in considerable detail and to and fertilizer production are more energy analyze the effects of technological alternatives efficient on the average in India than in most [5, 7]. In our study, we adopt the industrial western countries. In industries which are well process modelling approach to analyze tech295 INTRODUCTION
296
Anandalingam. Bhattacharya--Steel Industry in India
nology alternatives for industrial energy use in developing countries. As a representative case study, we chose to examine energy conservation possibilities in the Indian iron and steel industry. The iron and steel industry is generally one of the most energy intensive industries, and therefore for any country with a domestic iron and steel industry or a country that plans to build up its own industry in the future, decisions made in this industry with respect to process choice, conservation and output levels may greatly affect the overall energy balance. In most developing countries, the iron and steel industry contributes 20 to 40~/oof industrial energy use. The industry is composed of processes with a high degree of interconnectedness and complexity. This interconnectedness requires a systems model for technology evaluation, since the full impact on the system of changes in one process will go beyond the bounds of the process itself. Hence an analysis of the iron and steel industry will be important in terms of its role in the industrial sector of most LDC's and will provide a methodology that has yet to be used in analyzing industrial energy use in developing countries. An additional reason for using the iron and steel industry is that there is a vast amount of process data for this industry. The iron and steel industry in the U.S. has been analyzed in considerable detail using process models. The first integrated model of the steel industry appeared in Fabians' article [4] where he modelled the industry in a mathematical programming framework. Since then, many articles and books have appeared which use a variety of programming formulations to analyze technology choice [14], environmental impacts [10] and energy use [8, 12]. All these models assume that the steel industry behaves as a cost minimizer. In most developing countries, the steel industry is oligopolistic and often is a public enterprise. In either case, cost minimizing behavior is unlikely to take place. In addition, the use of the linear programming framework leads to corner solution, which may not be appropriate in the context of a developing country. Given restrictions in the increase of capital availability, process changes and investment in new technologies will take place slowly in most LDC's. Hence decision makers in developing countries are interested in analyzing energy and
material use during the transition period from the present situation to some more energy "efficient' (through not necessarily "optimal') situation in the future. Optimal solutions from a linear program will not provide the decision makers with tools that they require. In this paper, the iron and steel industry process model is analyzed using policy simulations. We analyze the impact on energy and material use of a combination of different technologies and evaluate the production cost of each technology. The decision maker is given a menu of technology alternatives to choose from for planning energy conservation in the Indian iron and steel industry. THE INDIAN IRON AND STEEL INDUSTRY
Orerview The Indian iron and steel industry is composed of six large integrated mills and a few mini-steel plants. Public sector controls five out of the six integrated steel mills and sets wholesale prices for all the steel marketed in the country. The public sector steel mills are at Bhilai, Bokaro, Durgapur, Burnpur and Rourkela; the Bokaro steel mill, built by the Russians is the largest and the most modern. Tata Iron and Steel Company, the private sector mill is at Jamshedpur. In 1983-84 fiscal year (which ended in March), Indian crude steel production from the public sector was 5.9 million metric tons, out of which 57~ was from Open Hearth furnaces (OHF) and 43~ from Basic Oxygen furnaces (BOF) (see Table 1). The total production capacity of the public sector was approximately 9.4 million tonnes with another 3.0 million tonnes expected to be completed this year. Out of the present production capacity, 57~ used OHF and 43~o used BOF (see Table 1). All new capacity additions are in BOF and it is expected that next year (i.e. 1984-85), BOF would be 56~ of the total capacity. Primary rolled products in 1983-84, excluding those from the private sector plant, were composed of 57~ blooms and 43~ slabs. Projections of steel requirements to 1989-1990 shows that this distribution would change to 53~ blooms and 47~ slabs. Public sector steel production is also expected to increase to 15.8 million tonnes (34~o OHF, 68~ BOF), with the
Omega. Vol. 13, No. 4
297
Table I. Annual production and capacity (10 n tonnes) in Indian steel industry, 1983-84 Production Open hearth
Capacity
Basic oxygen
Open hearth
Basic oxygen
-1.7 --0.85
2.5 -1.0 1.6 0.3
1.5p 2.5 + 1.5 p --1.5
Public sector Bhilai Bokaro Burnpur Durgapur Rourkela
1.8 -0.5 0.8 0.25
J
TISCO Jamshedpur
N~A
2.0
N/A
N A - - n o t available. P--projected for next year. Source: [t 3].
new steel mill at Vizhagapatnam accounting for 53~'o of the additional production (see Table 2). Energy use and conservation
The Indian iron and steel industry consumes more energy per tonne of crude steel than most developed countries. Estimations using 1980 data show that on the average, Indian steel was produced at an average cost of 9.5 GCal/tonne compared to 6.1 GCal/tonne in the U.S. and 4-2 GCal/tonne in Japan [1]. Coking coal is the major 'energy' source and accounts for 75-85% of energy consumption in the steel industry. The other components of energy use are non-coking coal (10-13~o), fuel oil (3.5-8.0%) and electricity (2.0--3.5%) [2]. Overall in the Indian steel industry, coking plants account for 14.1% of energy use, blast furnaces 38.7%, sintering plants 6.2%%0, steel mills 8.3%, rolling mills 16.9%, and other processing centers, 6.6%. Approximately 9.2% of energy is wasted [9]. The greater energy intensity of Indian Steel can be explained by technological, economic and non-economic factors. The most important factor in the Indian steel industry is technological: compared to most developed countries, a larger component of steel making in India is made up of the more energy intensive
open-hearth process. Hence, the energy 'conservation' option that would have the best returns in the long-run is investment in the more energy efficient basic oxygen furnaces. Other energy conservation options in the Indian iron and steel industry includes: Othe use of larger blast furnace units which are more energy efficient; Othe substitution of sinter for lump iron ore. Increased sinter use also tends to reduce consumption of coke which is scarce in India and which has a high level of embodied energy. Ocoal dust injection into blast furnaces which would substitute for some of the coking coal reducing coking coal consumption: an additional benefit is the use of an otherwise wasted product; Odry quenching of coke in coke ovens as opposed to the present practice of wet quenching, the heated air could be used in a cogeneration system to produce electricity; Orecovery of energy associated with byproduct gases from the basic oxygen furnaces using waste heat recovery systems or cogeneration systems; Oincorporation of continuous casting of steel.
Table 2. Projected annual steel production, 1989-90 (106 tonnes) Open hearth
Basic oxygen
Blooms
Slabs
2.5 -1.0 1.6 0.3 --
1.5 4.0 --1.5 3.4
2.2 -0.67 1.4 -3.2
1.4 3.5 0.23 -1.5 --
N/A
N/A
Public sector Bhilai Bokaro Burnpur Durgapur Rourkela Vizhagapatnam
J
TISCO Jamshedpur
Source: [ 131.
2.0
Anandalingam, Bhattacharya--Steel Industry in India
298
At present there are no continuous casting mills in the Indian steel industry.
the form of ingots for rolling and casting into blooms and slabs. Steel scrap from the mills are recycled into the open hearth furnaces.
Reduction in coke use is extremely important in India due to its limited supply. In addition to coal dust injection, coking coal could be conserved by washing it before use and blending it with non-coking coal in appropriate proportions to obtain coke that is useable in the steel industry. Such practices are being followed to some extent in India.
Basic structure of the model In a process analysis model, production is viewed as a set of activities, each of which defines a unique relationship between an output and a number o f inputs. These relationships are given in physical terms such as coking coal consumption rates, process heat and electricity requirements and rates of production of scrap, by-product gases, etc. In our model, the process relationships are represented by a set of inputoutput coefficients which are obtained from technical data [6]. Although non-linearities do exist in steel production, all relationships are assumed to be linear. All variables are defined in Table 3 and values of input-output coefficients are given in Table 4. Detailed model descriptions appear in the following sections. It should be noted that the production activities are labelled according to the numbers that appear in Fig. 1. Numerical subscripts on the variables relate to the different production processes in the iron and steel industry.
T H E IRON AND STEEL PROCESS M O D E L
The integrated mill The basic production activities in the Indian iron and steel industry are given in Fig. 1. The various stages of production are inter-related through input-output relationships. Coke ovens supply coke to the blast furnaces. In addition, the by-product coke-oven gas is used as a fuel source in the blast furnace. The blast furnace supplies hot metal to the steel furnaces. Gas from these furnaces is used together with cokeoven gas as a fuel source in the steel making furnaces. The steel furnaces supply raw steel in
l SINTE2RING , PLANT
E31 BLAST FURNACE
Ore fine
ScroD"
Fuel and electricity
Sinter
4
6
BASIC OXYGEN
BLOOMING MILL
'~
Fuel elec
Scrap Blooms
Fuel electric Iron ore
Imported coke Fuel
electricity
Coke
_
7
SLABBING MiLL
Blast Furnoce gas
I
Steel ingots
( hot metol}~"
I COK E OVEN
Coking cool
5
OPEN HEARTH
PiEj iron
Fuel
=
elec
Scrap
Coke oven gas
Fig. !. Iron and steel industry production processes.
Fuel elec
SloPs
Scrap]
Omega. Vol. 13, No. 4 Table 3. Variables in process model Variable
Definition
Coke ocen CC, E~ G, GC, H~ HO,
Coking coal used Electricity used Coke oven gas produced Gross coke produced Process heat used Heat content-Co gas
Sintering plant E, F, G'C, H, OF, S,.
Electricity used Limestone-flux used Coke dust Process heat used Iron ore fines used Sinter produced
Blast furnace E3 Fs Gj GC s H3 HA s IO s PI 3 S3
Electricity consumed Limestone-flux used Blast furnace gas produced Gross coke used Process heat used Hot-air used Iron ore used Pig-iron produced Sinter used
Basic o.~vgen furnace E~ FA 4 O~ PI4 SC 4 ST4
Electricity used Ferro-alloys used Oxygen used Pig-iron (hot metal) used Steel scrap used Crude steel produced
Open hearth fiwnace E5 l: 5 FA 5 H5 IO5 ()5 PI 5 SCs ST 5
Electricity used Limestone-flux used Ferro-alloys used Process heat used Treated iron ore used Oxygen used Pig-iron (hot metal) used Steel scrap used Crude steel produced
Blooming mill Es FS6 H6 SC6 ST6
Electricity used Finished steel (blooms) produced Process heat used Steel scrap produced Crude steel used
Slabbing mill E7 FS 7 H7 SC~ ST 7
Electricity used Finished steel (Slabs) Produced Process heat used Steel scrap produced Crude steel used
Given projections of bloom and slab requirements in the future, the model uses the linear input-output structure to simulate in turn, quantities of steel ingots required in the blooming and slabbing mills; total steel output; steel being produced by the BOF and OHF; pig iron required in the BOF and OHF; total pig iron output; iron ore, sinter and coke required by the blast furnace; ore fine used by the sintering plant; and coking coal used in the coke oven. In addition to simulating the flow of materials through the system, we obtain fuel and elec-
299
tricity requirements and the production of a variety of by-products including gases, and scrap.
Coke production In the blast furnace a chemical agent is needed to reduce the oxides of iron; this agent is carbon which is provided by coke. Coke is produced by heating coking (metallurgical) coal in the absence of air to a temperature at which the major part of the non-carbon components of the coal (i.e. water, sulphur and volatile matter) are driven off. During the coking process, large amounts of gas are generated; only around 25% of the coal is carburated. The Table 4. Parameter values in process model Parameter
Value
Coke oren acc~ aet ag t ah I aho~
1.2956 tonne'tonne 39.64 kwh:tonne 390 nM s tonne 0.8968 GCal/tonne 0.0042 GCal;nM 3
Sintering plant ae z at', age,. ah, aof,
41.84 kWh~ tonne 0.3514 tonnes/tonne O.1088 tonnes/tonne 0.0219 GCal/tonne 0.7878 tonnes/tonne
Blast furnace ac s a% afs ag 3 ah s aha~ aho s aio s as s
0.849 tonnes/tonne 25.85 kWhr/tonne 0.2157 tonnes/tonne 2612 nMS tonne 0.7255 GCal/tonne 2800 nMS:tonne 0.00085 GCal/nM s 1.0558 tonnes:onne 0.6797 tonnes/tonne
Basic oxygen furnaces ae~ afa4 an4 apa as4
28.24 kWhr tonne 0.012 tonnes:tonne 53.15 MS tonne 1.072 tonnes tonne 0.190 tonnes tonne
Open hearth furnace ae 5 af 5 afa 5 ah s ai S an s aps a%
22.43 kWhr tonne 0.050 tonnes:tonne 0.022 tonnes: tonne 0.739 GCal'tonne 0.175 tonnes/tonne 22.43 M~/tonne 1.239 tonnes/tonne 0.271 tonnes/tonne
Blooming mill ae~ ah 6 asc6 ast~
26.04 kWhr/tonne 0.0,31 GCal:tonne 0.125 tonnes:tonne 1.1252 tonnes/tonne
Slabbing mill ae7 ah7 aSC~ ast 7
Source." JNU Report [6].
45.71 kWhr tonne 0.361 GCal/tonne 0.178 tonnes: tonne 1.1725 tonnes tonne
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Anandalingam, Bhattacharya--Steel Industry in India
coke-oven gas is treated to remove by-products like tar and is used as a fuel elsewhere in the plant. Inputs into the coke ovens consist of coking coal (CC~). electricity (Ej) and heat (H~). All these inputs are required in constant proportion to the gross coke produced (GC1). CCI = acct' GCI
(1)
E~ = ae~-GCt
(2)
Hi = aht G C t
(3)
In addition, the coke oven gas produced (G~) is also in constant proportion to the output of gross coke Gt = agL'GC~
(4)
The heat content of the coke oven gas is given by: HOI = ahol 'GI
(5)
where ah~ is the calorific value. The gross coke produced consists of coke used in the blast furnace (GC3) and coke fines used in the sintering plant (GC2). GCt = GC: + GC 3
(6)
Sintering plant In the sintering plant, fine iron ore particles are agglomerated into a porous mass that is suitable to be charged into the blast furnace. The sintering machine is charged with a mixture of iron ore fines (OF2), coke dust (GC_,) and limestone (F2) in proportion to the sinter that is produced (S,). OF, = aof,' S,
(7)
GC, = agc2 S,.
(8)
F_, = af2.S 2
(9)
In addition, process heat is required in order to produce the high temperatures required for agglomeration. The heat requirement (H z) is also in proportion to the sinter produced, as in the electricity (E2) required for the various motors: H, = ah.,. $2
(10)
E, = ae2"S2
(11)
Blast furnace The blast furnace produces pig iron/raw iron
(PI 3) from either lumps or pellets of iron ore and sinter ($3). These inputs are primarily composed of iron oxide which is reduced to raw iron under high temperature in the blast furnace. The carbon needed tbr the reduction is added on the form of coke (GC3). In order to attain the high temperature needed for the reduction of the iron oxide, and the melting of the metallic iron, hot air (HA3) and oxygen (03) are injected under pressure at the bottom of the furnace. In addition to the hot pig iron, a by-product gas is produced which has an energy content around one-fifth that of coke oven gas. One of the major impurities in the iron ore (and in the coke) is silica, which leads to ash formation in the furnaces. Limestone (F 3) is used as a binding agent to remove the silica in the form of slag. We assume that all these inputs are in constant proportion to the hot-metal (pig iron) produced: (IO3)
IO 3 = aio3. PI3
(12)
S 3 = as3. PI 3
(13)
GC 3 = ac3.Pl 3
(14)
af 3• PI 3
(15)
F 3=
HA 3 = aha3' PI3
(16)
03 = a03' PI3
(17)
Process heat (H3) and electricity (E3) are also required in proportion to the pig-iron produced: H 3 = ah3-PI 3
(18)
E 3 = ae3. PI 3
(19)
The energy efficiency of blast furnaces depend very critically on the Fe (Iron) content of iron ore [11]. However, in the Indian context, the iron ore has a very high Fe content and, in any case, there is very little variation in the concentration. For example, during the period from 1970-71 through 1978-79, the percentage Fe content in the annual ore use at the blast furnaces of the Durgapur steel plant, had a mean of 61.4 and a standard deviation of 0.58 (SAIL statistics [13]). All public sector steel plants in India have well equipped ore storage and handling yards where different grades of iron ore can be blended in order to yield ores with more or less fixed Fe content. It should be noted, however, that blast furnace performance is sensitive to the relative proportions of sinter and lump ore in the blast furnace charge. We
Omega, Vol. I3, No. 4 explore this relationship in the section of the paper that deals with the simulations. We assume in this study that all coke and sinter that is required in the blast furnace are produced within the integrated steel mill, i.e. in addition to equation (6) which accounts for coke usage, sinter use is given by: S 3 = S~
(20)
In order to manufacture raw steel, the pig iron is used in the BOF (PIa) and the O H F (PIs). In the Indian mills, we assume that very little pig iron is sold by itself, i.e.; PI3 = PI4 + P15
(2l)
The iron making process also produces an off-gas that has a high calorific value. The quantity of the gas, G 3, is proportional to the hot metal produced: G.~ = ag3" Plj
(22)
The heat content of the blast furnace gas is given by: HO3 = aho3"G3 (23) where aho3 is the calorific value. Raw steel manufacturing Pig iron produced in the blast furnace is transformed into steel in either a (BOF) or an (OHF) furnace. Based on actual data in the Indian steel industry, we assume constant coefficients for hot-metal and scrap input into the O H F and BOF processes. Energy consumption, especially in the O H F process, is highly sensitive to scrap ratios [11]. However in the period 1970-71 through 1978-79, the scrap ratio remained virtually constant in the Indian case. For example in the Bhilai steel plant, where steel is produced by the O H F process, the scrap ratio (for the nine years) had a mean of 0.259 and a standard deviation of 0.005 (SAIL statistics [I 3]). The corresponding figures for hot metal input coefficients were 0.79 and 0.01 respectively. It should also be noted that, in the public sector steel plants, the entire scrap input is produced within the plant--there is no purchase. All of this would change if the Indian steel industry were to invest significantly in mini steel mills. This is not expected in the near future. Basic oxygen furnace. In the basic oxygen process, pure oxygen is injected into a charge of melted pig iron and steel scrap through a water
301
cooled lance. The oxygen reduces the melting time, increases the temperature and increases the rate of oxidation. The only source of heat is the heat in the hot metal and the heat generated by the reactions between the oxygen and the metalloids in the hot metal. In order to strengthen the steel, ferro-alloys are added in the steel making furnaces. The inputs pig iron (PI~), scrap (SC4), oxygen (O~) and ferro-alloys (FA~) are assumed in constant proportion to the ingot steel produced (STy) from the basic oxygen furnace: PI~ = ap4' STz
(24)
SC4 = as,t" ST4
(25)
O~ = ao~. ST~
(26)
FA4 = afa4" ST~
(27)
The only external energy source is electricity (E4) which is given by: E4 = ae4- ST4 (28) Open hearth furnace. The open hearth furnace consists of a shallow refractory lined rectangular room with openings at both ends. These openings are interchangeably used for injection of preheated air and evacuation of exhaust gases. During the steel making cycle, preheated air together with fuel is blown into the furnace from one end. After some time, the exhaust gases leave the furnace and heat up some brick chambers. The heat of the bricks is used to pre-heat the fresh incoming air. The process is relatively time consuming compared to the BOF. Major inputs into the open-hearth furnace consist of the hot pig-iron from the blast furnace (PIs), steel scrap from the steel finishing mills (SC5) and treated iron ore 005). Some oxygen (O5), limestone (Fs) and ferro-alloy (FAs) are also used in the steel manufacturing process. All the inputs are consumed in constant proportion to the ingot steel produced in the open hearth furnace (STs):
PI5 = aps" ST5
(29)
SC5 = ass- ST5
(30)
IO5 = ais" ST5
(31)
05 = aos- ST5
(32)
F 5 = afs. ST 5
(33)
FA 5 = afa 5- ST 5
(34)
Anandalingam, BhattachaG'a--Steel Industry in India
302
Process heat (H 0 and electricity requirements are also in proportion to the steel produced:
furnace (03) and in the BOF (OA and O H F (05), i.e.:
H5 = ahs" ST5
(35)
Os = 03 + 04 + 05
E5 = aes" ST5
(36)
Auto-generation of electricity and air blast. All Indian iron and steel mills produce in-house all the air blast that is needed and part of the electricity. The in-house production of air blast and electricity is an integrated process in which high pressure steam produced in a boiler (i.e. quantity HPS) is used in part (i.e. HPS,) in a power station to produce electricity (Eg) and in part (i.e. HPS~) in a blowing station to produce air blast (HAg). The steam required for each is in proportion to the output of each, i.e.:
Steel finishing The steel is either finished in the form of blooms or slabs using rolling mills. In addition to steel ingots, the major input into the steel finishing processes is electricity. The steel ingot may require some heat in order to prevent cooling. The steel ingots are heated in furnaces (soaking pits) prior to primary rolling. These soaking pits are fired with a mixture of CO gas and BF gas. Scrap produce in the steel finishing mills is recirculated within the plant. Blooming mill. Material and energy flow in the blooming mill is given by: ST 6 --- ast6. FS 6
(37)
H6 L_ ah 6. FS 6
(38)
E6 = aer' FS6
(39)
SC6 = ascr" FS6
(40)
Slabbing mill. Material and energy flow in the blooming mill is given by:
(48)
HPS, = as,.E9
(49)
HPSa = as~ .HA 9
(50)
and HPS = HPS~+ HPS~
(51)
In order to produce the high pressure steam, non-coking coal is burnt as a fuel in the boiler. The quantity of non-coking coal required is in proportion to the total steam produced: NC9 = ancg- HPS
(52)
We also assume that all the hot-air used in the steel mill is produced in-house; i.e.;
ST 7 = ast 7• FS 7
(41)
H7 = ah7" FS7
(42)
E7 = ae7" FS7
(43)
Material and fuel balance equation
SC 7 = asc 7- FS 7
(44)
The total heat produced within the steel mill (PH) by the coke oven gas is HO~ and by the blast furnace gas is HO3. Total process heat consumption (CH) occurs in the coke oven (H~), sintering plant (H_,), blast furnace (H3), open-hearth furnace (Hs), blooming mill (Hr) and slabbing mill (HT). The difference between the quantity of heat produced and that used has to be purchased (QH):
The steel produced by the different processes are inputs into the finishing mills: i.e.; ST 4 + ST 5 = ST 6 + ST 7
(45)
The total steel scrap used by the steel making furnaces are obtained from the finishing mills: SC4 + SC5 = SC6 + SC7
(46)
HA9 = HAs
PH = HO, + HO3
Auxiliary processes Oxygen plant. The oxygen plant produces oxygen (Os) (and nitrogen) by cryogenic distillation of air. The major input is electricity (Es), which is required in proportion to the oxygen produced: Es = aes' Os
(47)
The oxygen produced is used in the blast
(53)
(54)
7
¢ H = Y H,
(55)
O H = C H - PH
(56)
Total electricity consumed (CE) is given by: 7
CE = ~ E~ i~l
(57)
Omega, Vol. 13, No. 4
303
Table 5. Calibration of simulation model, base year results
Open hearth steel Basic furnace steel Hot metal Sinter Coking coal Iron ore
Model results 106 tonnes
Actual 10~ tonnes
Discrepancy (?g of actual)
3.35 2.55 6.88 4.68 8.41 11.59
3.35 2.55 7.40 6.05 8.70 12.21
0.0 0.0 -7.0 - 22.6 -3.3 -5.1
The total electricity that needs to be purchased (QE): is the difference between that required (CE) and that produced in-house (Eg): QE = CE - E9
(58)
SIMULATION RESULTS Preliminaries
At present, (i.e. 1983-84) the integrated steel mills in India produce 2.85 million tonnes (metric tons) of blooms and 2.26 million tonnes of slabs from 5.9 million tonnes of steel; 0.79 million tonnes of scrap are produced in the roiling mills of the crude steel production, 56.8~ is from OHF and 43.2~ from BOF. We used present production levels in the Indian steel industry to obtain simulation results on the other activities. Results are given in Table 5. Model results for the base year are generally lower than the actual activity levels. With the exception of sinter consumption, all discrepancies are below approximately 5~. Specific sinter consumption (i.e. per unit of molten iron produced) reported by the industry was lower (by 12.1~) than the author's estimate of the weighted average of specific sinter consumption in each of the steel mills. If the weighted average was used, then the discrepancy between model results and actual values will be approximately 10~, which is an acceptable level of error in simulation studies. We decided to use the specific sinter consumption reported by the industry for the present study. The impact of the discrepancy on energy use is estimated to be less than 0.01~/o. Analysis of energy use and conservation
We used the steel industry process model to analyze energy and materials use due to growth strategies and several energy conservation activities. The main thrust of our study was to provide results on the impact of government
policies energy conservation in the entire iron and steel industry in India. Growth. The Indian government has plans to increase steel production capacity to 17.8 million tonnes in 1989-90 from the present 11.4 million tonnes. Our contention, which is generally accepted by steel industry analysts in India, is that the production capacity will reach 17.8 million tonnes only in 1993-94, ten years from now. If we assume that capacity utilization will remain at 52~, the same level as in 1983-84, then steel production is projected to grow by 4.6~ on the average during the next ten years. Given this growth scenario, by 1993-94 the steel industry will require 13.2 million tonnes of coking coal, 0.8 million tonnes of non-coking coal and 1672 Mwhr of electricity ceteris parabus (Table 6). These are all large magnitudes, especially coking coal for which there is only a limited level of reserves in India. Total material costs for producing the required 9.25 million tonnes of crude steel will be Rs. 11.9 billion in year 1993-94. Conservation--Shifting from open hearth to basic oxygen furnaces. Most of the new capacity that the government of India is planning is expected to be in systems that use BOF. By 1993-94, the level of steel produced in basic oxygen furnaces is expected to grow to 70~ (from the present 43.2~o) and open hearth steel is projected to decline to 30~o of total production (from the present 56.8~). If production capacity is changed to 70~ basic oxygen furnaces, the consumption of coking coal and process heat in 1993-94 goes down compared to the Business As Usual Case by 3.9 and 11.9~ respectively (Table 6). Electricity consumption goes up 6.8~. Total energy use decreases by 5.1~, a fairly insignificant amount. Use of other materials such as iron ore, sinter, ferro-alloys, etc. all decrease and total cost of production goes down by an insignificant 4.5~. Conservation--Increasing sinter use. When
304
Anandalingarn, Bhattacharya--Steel Industry in India Table 6. Results of policy simulations, 1993-94 Policy scenarios Cokingcoal(106tonnes) Non coking coal ([0~tonnes) Electricity (MWhr) Process heat (106GCal) Total energy (10OGCal) Sinter (106 tonnes) Iron ore (106 tonnes) Ferro-alloys (106 tonnes) Total cost (109 Rupees)
BAU
70 BOF
SSC
CDI
DQC
70 + SSC
t3.18 0.78 1672 21.00 93.00 7.37 18.17 0.t6 1[.87
12.67 0.77 1785 t8.51 88.30 7.06 17.07 0.14 II.34
11.64 0.79 1702 19.97 84.69 9.17 19.64 0.16 11.26
10.54 4.16 [672 21.00 99.93 7.37 18.17 0.16 11.41
12.67 0.72 t273 18.51 86.73 8.29 17.07 0.14 11.11
11.20 0.77 1813 17.52 80.3t 8.82 18.48 0.14 [0.76
BAU--business as usual (ceteris paribus). 70 BOF--70% basic oxygen, 30% open hearth. SSC--increasing sinter use---
more sinter is used in the blast furnace, less iron ore is required to produce the same quantity of pig-iron (hot metal). Thus, less coke is required as a reducing agent. Hence one way to reduce coke use is to increase the use of sinter. In Indian steel mills, there is a clear trade-off between specific sinter use (i.e. per tonne of hot metal) and specific coke use (Fig. 2). We examine the policy of using 25% more sinter per tonne of hot metal. Specific sinter assumption will then increase to 0.85 from 0.68 while specific coke consumption will decrease to 0.75 from 0.85. Increasing sinter use will lead to a reduction in coking coal use which is greater than the policy of increasing the proportion of BOF (Table 6). In addition changes in the use of inputs that have embodied energy are: coking
,$ o
== o
"10
•u
08
c
06
~ 04 "2_ 0 2
g
I
I
02
Q4
Spectf~c
sinter
I
I
06
08
I
I
10
1 2
L 1.4
consumphon (tonnes/tonne)
Fig. 2. Sinter vs c o k e tradeoff in I n d i a n blast furnaces.
coal use decreases by ll.7%, non-coking coal use remains the same, electricity use increases by 1.8% and process heat decreases by 4.9%. Overall energy use decreases by 8.9% which is more significant than before. Total production cost goes down by 5.1%, a small change. Conservation--Coal dust injection. When coal dust is injected through the tuyeres of the blast furnace, it acts as a reducing agent in the production of crude steel; subsequently less coke is required. Indian coal, however, has a very high ash content. Hence we use specifications for coal with 9% ash and assume that for every tonne of coke that is replaced, 1.282 tonnes of coal dust would be required. We investigate the impact of reducing coke consumption by 20?/0 by using coal dust injection. The use of non-coking coal increases to 4.16 million tonnes, a change of 3.38 million tonnes; all of this comes from the addition of coal dust. While the consumption of all other inputs remain the same, total energy use increases from the BAU case by 7.5%; total cost decreases by 3.9%. Clearly coal dust injection will not lead to overall conservation of energy, only a savings in the use of coking coal. For a country like India where coking coal is in short supply, conservation of coking coal is an important strategy. For the steel industry as a whole, this strategy will also lead to a savings in the production cost. Conservation--Dry quenching of coke. Hot coke that is produced is usually quenched in a liquid medium to bring it to useful temperatures. If the hot coke is 'dry' quenched, i.e. quenched in air or using a gaseous medium, the heat transferred to a medium can be recovered using waste heat boilers. Steam generated by
Omega, ~bl. 13, No. 4
these waste heat boilers can either be used for process heat or for producing electricity. In most steel plants, the gases produced as byproducts in the coking oven and blast furnace provide enough process heat for the steel making processes. Hence, the waste heat that is recovered from dry quenching coke is used primarily to produce electricity. In one of the new Indian steel mills (at Vizhagapatnam), there is at present a proposal to adopt a Soviet design for dry quenching coke. In a typical Soviet dry quenching unit, 21MW of electricity is produced for a coke throughout of 4990 tonnes/day (1.821 × 106 tonnes/year). Using these figures and the assumption that energy from the 'power plant' is used at the same rate as the level of capacity utilization, we estimate that 52.32 kwhr of electricity is produced per annual tonne of coke. The total energy consumption with the dry quenching of coke is 86.73 x 106 GCal, a reduction of 6.7~o. Total production cost also decreases by 6.4~, the largest reduction in production cost among all the conservation options. The electricity produced by the dry quenching of coke substitutes for approximately 23.9°0 of total electricity required by the steel making process. This magnitude of electricity is quite significant. Conservation--Combination of sinter use and basic o.Lvgenfi~rnances. A final strategy that was analyzed assumed a policy of increased sinter use and the transformation of steel making in BOF. As before, we assumed that sinter use would increase by 25~ and by 1993-94, the proportion of BOF would by 70~/o. Clearly the combined strategy was the best with regard to all criteria. Total energy use decreased by 13.6~o and production cost decreased by 9.4~°~ as compared to the BAU case. Coking coal consumption was lower than in all strategies with the exception of the coal dust injection strategy where we assumed that coking coal use would decrease by 20%. Coking coal consumption decreases by approximately 15~ in this strategy. Inuestrnent costs
In the study so far, we have not explicitly modelled investment costs for the different energy conservation options. This work is in the process of being completed. Some preliminary
305
findings are apparent from the preceding analysis. The difference in production cost between continuing with 43.2/0 , o/ BOF or increasing it to 70~o is 430 million (Table 5). Assuming that operating and maintenance (O & M) costs for both scenarios remains the same (which it should be) then the investment cost for the new BOF should not exceed 4.02 billion at an equipment life-time of 20 years and 10% interest rate, (i.e. capital recovery factor = 0.107). Dry quenching of coke will lead to a cost saving of 760 million. Hence investment costs for the technology for dry quenching of coke and for producing electricity should not exceed 7.10 billion. Incremental use of sinter and coal dust injection are both conservation practices that are practically costless. However should more sintering plants and coal dust injection facilities be required, the investment costs should not exceed Rs. 5.70 billion and Rs. 4.30 billion respectively, to be economical. CONCLUDING REMARKS It seems apparent from our simulation results that none of the policy options that we examined would lead to significant levels of energy conservation by themselves. Increased use of sinter results in the largest reduction in the use of coking coal and total energy, the former by 11.7~ and the latter by 8.9~. If strategies are combined, then there will be considerable scope for energy conservation in the Indian steel industry. If the industry changed its production structure so that BOF formed 70~ of crude steel production and increased the use of sinter, the coking coal and energy use decreases by 15 and 14% respectively. Overall, however, it appears that the Indian steel industry has limited scope for saving energy although aggregate analysis in other studies showed a high level of energy intensity. Although the percentage change in energy and coking coal use was low, the absolute reductions were quite significant. For instance, the decrease in energy and coking coal use in the best option (i.e. use of sinter) was 8.3 million GCal and 1.54 million tonnes respectively. This is especially true in the case of production costs. The savings in production costs per year could easily justify spending up to 4 billion in OHF
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Anandalingam, Bhattacharya--Steel Industry in India
a n d 7 billion for the t e c h n o l o g y for dry, quenching o f coke. A c t u a l investment costs are expected to be lower. In this study, we did not include energy c o n s u m p t i o n by the auxiliary processes such as the p r o d u c t i o n o f bulk oxygen because we did not expect it to be significant. In view o f o u r finding t h a t investing in B O F d o e s n o t lead to m u c h energy savings, full c o n s i d e r a t i o n o f energy c o n s u m e d by the oxygen p r o d u c t i o n p r o cess might even reverse the c o m p a r a t i v e efficiency o f O p e n H e a r t h a n d Basic O x y g e n processes. T w o o t h e r issues also need to be addressed. W e have a s s u m e d that c a p a c i t y utilization rem a i n s at 52~o t h r o u g h o u t the time h o r i z o n o f the study. S h o u l d there be increasing energy a n d e c o n o m i c scale efficiencies, the greatest imp r o v e m e n t s in energy use w o u l d c o m e from higher levels o f c a p a c i t y utilization. Since we used a linear m o d e l in this study, we implicitly m a d e the a s s u m p t i o n that there were c o n s t a n t scale economies, that is, the energy efficiency was i n v a r i a n t with respect to c a p a c i t y utilization. T h e m a i n reason for this r a t h e r restrictive a s s u m p t i o n was the lack o f sufficient d a t a on how the p a r a m e t e r s (Table 4) o f the m o d e l varied with the level o f c a p a c i t y utilization. Inclusion o f c a p a c i t y utilization c o n s i d e r a t i o n s has p r o v e d to be a difficult p r o b l e m for those w o r k i n g on d e v e l o p i n g c o u n t r i e s [3]. F i n a l l y it should be p o i n t e d o u t t h a t the focu3 o f the study was on energy c o n s e r v a t i o n . Clearly the goal o f energy-efficiency is o n l y one o f m a n y objectives that a p l a n n e r or the industry w o u l d be interested in. A m o r e c o m p l e t e multi-objective m o d e l is left for future work.
ACKNOWLEDGEMENTS An earlier version of this paper was presented at the 26th International Meeting of the Institute of Management Sciences, Copenhagen, Denmark. The research for this study was conducted when the first author was a Visiting Fellow at Tata Energy Research Institute, New Delhi on a
Rockefeller Foundation International Relations Fellowship. None of the at~liated institutions necessarily agree with the contents of this paper. We thank an anonymous referee for constructive comments and criticisms. REFERENCES 1. Anandalingam G (1983) Policy incentives for industrial energy conservation. Energy Mgmt 7(4), 317-329. 2. Bhattacharya D (1985) Energy analysis of Indian integrated iron and steel plants. Indian Eastern Eng Annual Volume. New Delhi, (forthcoming). 3. Blitzer CR, Clark PB and Taylor L (1977) EconomyWide Models and Development Planning. Oxford University Press. 4. Fabian T (1958) A linear programming model of integrated iron and steel production. Mgmt Sci. 17(7), 415-429. 5. Howe SO, Pitati DA and Sparrow FT (1980) Process modeling and industrial energy use. Report No. BNL 28838, Brookhaven National Laboratory, Upton, New York. 6. Jawaharlal Nehru University (198t) Problem of production and investment planning in Indian iron and steel industry. Hindustan Steel Limited, Case Study, unpublished report, Department of Planning, New Delhi. 7. Manne AS and Markowitz HM (1963) Studies in Process Analysis. John Wiley, New York. 8. Missirian G (1978) Energy utilization in the U.S. iron and steel industry: a linear programming analysis. Unpublished PhD Dissertation, University of California, Berkeley. 9. Mohanty RP and Swain D (1982) Energy management problems of Indian steel ptants. Energy Mgmt 6(3), 167-182. 10. Russell CS and Vaughn WJ (1974) Environmental quality problems in iron and steel production. Discussion Paper, Resources for the Future, Washington, D.C. I I. Russell CS and Vaughn WJ (1976) Steel Production: Processes, Products and Residuals. Johns Hopkins University Press, Baltimore. 12. Sparrow FT, Pilati D, Dougherty T, McBreen E and Juang LL (1980) Iron and steel process model. Report No. BNL 51073, Brookhaven National Laboratory, Upton, New York. 13. Steel Authority of India Limited-SAIL. Operational Statistics: Public Seclor Steel Plants. (Many volumes, various years). 14. Tsao CS and Day RN (1971) A process analysis model of the U.S. steel industry. Mgmt Sci. 17(10), B588-B608.
Professor G Anandalingam, Department of Systems Engineering, University of Virginia, Charlottesville, Virginia 22901, USA
ADDRESS FOR CORRESPONDENCE:
Britain. All rights reserved
0305-0483/85$3.00+0.00 Copyright~ 1985PergamonPress Ltd
Process Modelling and Industrial Energy Use in Developing CountriesThe Steel Industry in India G ANANDALINGAM University of Virginia, USA D
BHATTACHARYA
Tata Energy Research Institute, New Delhi, India (Receiced October 1984; in rerisedform February 1985)
A process model is used to study energy use and conservation in the steel industry in India. Production is modelled by a set of inter-connected process activities, each of which defines unique relationships between process output and a number of inputs. Contrary to that in process models for the U.S., we do not assume cost minimizing behavior. Simulation results show that although a number of cost-efl'eetive energy conservation measures exist, none of them would lead to significant reductions in energy use. Effective policy for the Indian Steel industry would require combining the strategies.
established, decision makers in LDC's are faced with the choice of investing in energy conserINDUSTRIAL energy demand has grown faster vation retrofits or in modifying sections of the than energy consumption in other sectors of the production process by substituting energy economy in most developing countries. As less efficient technologies for older technologies that developed countries (LDC's) industrialize, a are less efficient. For instance, many LDC's are larger component o f investment goes into converting from open hearth furnaces to basic energy intensive sectors such as steel, cement oxygen furnaces for making steel, while mainand aluminium. In addition to the mix of prod- taining older technologies for the rest of the ucts, the increase in industrial energy use also steel production system. Decisions regarding energy conservation depends on the technologies used to produce retrofits or process changes should be made them. Ever since the tremendous increases in the oil after a systematic analysis of the industry, which price in the 1970's, new manufacturing tech- examines the flow of materials and energy nologies and processes have become more through the industry. We need an approach energy efficient. Hence LDC's that invest newly whereby activities in the different sections of an in some sectors have the choice of buying old industry are modelled explicitly as are the intertechnologies cheaply or in investing in new action between the different activities. Industrial energy efficient technologies, which cost more. process models have been used for a number of Many developing countries have opted for the years to represent energy and material flows latter decision. For instance, refinery operation within an industry in considerable detail and to and fertilizer production are more energy analyze the effects of technological alternatives efficient on the average in India than in most [5, 7]. In our study, we adopt the industrial western countries. In industries which are well process modelling approach to analyze tech295 INTRODUCTION
296
Anandalingam. Bhattacharya--Steel Industry in India
nology alternatives for industrial energy use in developing countries. As a representative case study, we chose to examine energy conservation possibilities in the Indian iron and steel industry. The iron and steel industry is generally one of the most energy intensive industries, and therefore for any country with a domestic iron and steel industry or a country that plans to build up its own industry in the future, decisions made in this industry with respect to process choice, conservation and output levels may greatly affect the overall energy balance. In most developing countries, the iron and steel industry contributes 20 to 40~/oof industrial energy use. The industry is composed of processes with a high degree of interconnectedness and complexity. This interconnectedness requires a systems model for technology evaluation, since the full impact on the system of changes in one process will go beyond the bounds of the process itself. Hence an analysis of the iron and steel industry will be important in terms of its role in the industrial sector of most LDC's and will provide a methodology that has yet to be used in analyzing industrial energy use in developing countries. An additional reason for using the iron and steel industry is that there is a vast amount of process data for this industry. The iron and steel industry in the U.S. has been analyzed in considerable detail using process models. The first integrated model of the steel industry appeared in Fabians' article [4] where he modelled the industry in a mathematical programming framework. Since then, many articles and books have appeared which use a variety of programming formulations to analyze technology choice [14], environmental impacts [10] and energy use [8, 12]. All these models assume that the steel industry behaves as a cost minimizer. In most developing countries, the steel industry is oligopolistic and often is a public enterprise. In either case, cost minimizing behavior is unlikely to take place. In addition, the use of the linear programming framework leads to corner solution, which may not be appropriate in the context of a developing country. Given restrictions in the increase of capital availability, process changes and investment in new technologies will take place slowly in most LDC's. Hence decision makers in developing countries are interested in analyzing energy and
material use during the transition period from the present situation to some more energy "efficient' (through not necessarily "optimal') situation in the future. Optimal solutions from a linear program will not provide the decision makers with tools that they require. In this paper, the iron and steel industry process model is analyzed using policy simulations. We analyze the impact on energy and material use of a combination of different technologies and evaluate the production cost of each technology. The decision maker is given a menu of technology alternatives to choose from for planning energy conservation in the Indian iron and steel industry. THE INDIAN IRON AND STEEL INDUSTRY
Orerview The Indian iron and steel industry is composed of six large integrated mills and a few mini-steel plants. Public sector controls five out of the six integrated steel mills and sets wholesale prices for all the steel marketed in the country. The public sector steel mills are at Bhilai, Bokaro, Durgapur, Burnpur and Rourkela; the Bokaro steel mill, built by the Russians is the largest and the most modern. Tata Iron and Steel Company, the private sector mill is at Jamshedpur. In 1983-84 fiscal year (which ended in March), Indian crude steel production from the public sector was 5.9 million metric tons, out of which 57~ was from Open Hearth furnaces (OHF) and 43~ from Basic Oxygen furnaces (BOF) (see Table 1). The total production capacity of the public sector was approximately 9.4 million tonnes with another 3.0 million tonnes expected to be completed this year. Out of the present production capacity, 57~ used OHF and 43~o used BOF (see Table 1). All new capacity additions are in BOF and it is expected that next year (i.e. 1984-85), BOF would be 56~ of the total capacity. Primary rolled products in 1983-84, excluding those from the private sector plant, were composed of 57~ blooms and 43~ slabs. Projections of steel requirements to 1989-1990 shows that this distribution would change to 53~ blooms and 47~ slabs. Public sector steel production is also expected to increase to 15.8 million tonnes (34~o OHF, 68~ BOF), with the
Omega. Vol. 13, No. 4
297
Table I. Annual production and capacity (10 n tonnes) in Indian steel industry, 1983-84 Production Open hearth
Capacity
Basic oxygen
Open hearth
Basic oxygen
-1.7 --0.85
2.5 -1.0 1.6 0.3
1.5p 2.5 + 1.5 p --1.5
Public sector Bhilai Bokaro Burnpur Durgapur Rourkela
1.8 -0.5 0.8 0.25
J
TISCO Jamshedpur
N~A
2.0
N/A
N A - - n o t available. P--projected for next year. Source: [t 3].
new steel mill at Vizhagapatnam accounting for 53~'o of the additional production (see Table 2). Energy use and conservation
The Indian iron and steel industry consumes more energy per tonne of crude steel than most developed countries. Estimations using 1980 data show that on the average, Indian steel was produced at an average cost of 9.5 GCal/tonne compared to 6.1 GCal/tonne in the U.S. and 4-2 GCal/tonne in Japan [1]. Coking coal is the major 'energy' source and accounts for 75-85% of energy consumption in the steel industry. The other components of energy use are non-coking coal (10-13~o), fuel oil (3.5-8.0%) and electricity (2.0--3.5%) [2]. Overall in the Indian steel industry, coking plants account for 14.1% of energy use, blast furnaces 38.7%, sintering plants 6.2%%0, steel mills 8.3%, rolling mills 16.9%, and other processing centers, 6.6%. Approximately 9.2% of energy is wasted [9]. The greater energy intensity of Indian Steel can be explained by technological, economic and non-economic factors. The most important factor in the Indian steel industry is technological: compared to most developed countries, a larger component of steel making in India is made up of the more energy intensive
open-hearth process. Hence, the energy 'conservation' option that would have the best returns in the long-run is investment in the more energy efficient basic oxygen furnaces. Other energy conservation options in the Indian iron and steel industry includes: Othe use of larger blast furnace units which are more energy efficient; Othe substitution of sinter for lump iron ore. Increased sinter use also tends to reduce consumption of coke which is scarce in India and which has a high level of embodied energy. Ocoal dust injection into blast furnaces which would substitute for some of the coking coal reducing coking coal consumption: an additional benefit is the use of an otherwise wasted product; Odry quenching of coke in coke ovens as opposed to the present practice of wet quenching, the heated air could be used in a cogeneration system to produce electricity; Orecovery of energy associated with byproduct gases from the basic oxygen furnaces using waste heat recovery systems or cogeneration systems; Oincorporation of continuous casting of steel.
Table 2. Projected annual steel production, 1989-90 (106 tonnes) Open hearth
Basic oxygen
Blooms
Slabs
2.5 -1.0 1.6 0.3 --
1.5 4.0 --1.5 3.4
2.2 -0.67 1.4 -3.2
1.4 3.5 0.23 -1.5 --
N/A
N/A
Public sector Bhilai Bokaro Burnpur Durgapur Rourkela Vizhagapatnam
J
TISCO Jamshedpur
Source: [ 131.
2.0
Anandalingam, Bhattacharya--Steel Industry in India
298
At present there are no continuous casting mills in the Indian steel industry.
the form of ingots for rolling and casting into blooms and slabs. Steel scrap from the mills are recycled into the open hearth furnaces.
Reduction in coke use is extremely important in India due to its limited supply. In addition to coal dust injection, coking coal could be conserved by washing it before use and blending it with non-coking coal in appropriate proportions to obtain coke that is useable in the steel industry. Such practices are being followed to some extent in India.
Basic structure of the model In a process analysis model, production is viewed as a set of activities, each of which defines a unique relationship between an output and a number o f inputs. These relationships are given in physical terms such as coking coal consumption rates, process heat and electricity requirements and rates of production of scrap, by-product gases, etc. In our model, the process relationships are represented by a set of inputoutput coefficients which are obtained from technical data [6]. Although non-linearities do exist in steel production, all relationships are assumed to be linear. All variables are defined in Table 3 and values of input-output coefficients are given in Table 4. Detailed model descriptions appear in the following sections. It should be noted that the production activities are labelled according to the numbers that appear in Fig. 1. Numerical subscripts on the variables relate to the different production processes in the iron and steel industry.
T H E IRON AND STEEL PROCESS M O D E L
The integrated mill The basic production activities in the Indian iron and steel industry are given in Fig. 1. The various stages of production are inter-related through input-output relationships. Coke ovens supply coke to the blast furnaces. In addition, the by-product coke-oven gas is used as a fuel source in the blast furnace. The blast furnace supplies hot metal to the steel furnaces. Gas from these furnaces is used together with cokeoven gas as a fuel source in the steel making furnaces. The steel furnaces supply raw steel in
l SINTE2RING , PLANT
E31 BLAST FURNACE
Ore fine
ScroD"
Fuel and electricity
Sinter
4
6
BASIC OXYGEN
BLOOMING MILL
'~
Fuel elec
Scrap Blooms
Fuel electric Iron ore
Imported coke Fuel
electricity
Coke
_
7
SLABBING MiLL
Blast Furnoce gas
I
Steel ingots
( hot metol}~"
I COK E OVEN
Coking cool
5
OPEN HEARTH
PiEj iron
Fuel
=
elec
Scrap
Coke oven gas
Fig. !. Iron and steel industry production processes.
Fuel elec
SloPs
Scrap]
Omega. Vol. 13, No. 4 Table 3. Variables in process model Variable
Definition
Coke ocen CC, E~ G, GC, H~ HO,
Coking coal used Electricity used Coke oven gas produced Gross coke produced Process heat used Heat content-Co gas
Sintering plant E, F, G'C, H, OF, S,.
Electricity used Limestone-flux used Coke dust Process heat used Iron ore fines used Sinter produced
Blast furnace E3 Fs Gj GC s H3 HA s IO s PI 3 S3
Electricity consumed Limestone-flux used Blast furnace gas produced Gross coke used Process heat used Hot-air used Iron ore used Pig-iron produced Sinter used
Basic o.~vgen furnace E~ FA 4 O~ PI4 SC 4 ST4
Electricity used Ferro-alloys used Oxygen used Pig-iron (hot metal) used Steel scrap used Crude steel produced
Open hearth fiwnace E5 l: 5 FA 5 H5 IO5 ()5 PI 5 SCs ST 5
Electricity used Limestone-flux used Ferro-alloys used Process heat used Treated iron ore used Oxygen used Pig-iron (hot metal) used Steel scrap used Crude steel produced
Blooming mill Es FS6 H6 SC6 ST6
Electricity used Finished steel (blooms) produced Process heat used Steel scrap produced Crude steel used
Slabbing mill E7 FS 7 H7 SC~ ST 7
Electricity used Finished steel (Slabs) Produced Process heat used Steel scrap produced Crude steel used
Given projections of bloom and slab requirements in the future, the model uses the linear input-output structure to simulate in turn, quantities of steel ingots required in the blooming and slabbing mills; total steel output; steel being produced by the BOF and OHF; pig iron required in the BOF and OHF; total pig iron output; iron ore, sinter and coke required by the blast furnace; ore fine used by the sintering plant; and coking coal used in the coke oven. In addition to simulating the flow of materials through the system, we obtain fuel and elec-
299
tricity requirements and the production of a variety of by-products including gases, and scrap.
Coke production In the blast furnace a chemical agent is needed to reduce the oxides of iron; this agent is carbon which is provided by coke. Coke is produced by heating coking (metallurgical) coal in the absence of air to a temperature at which the major part of the non-carbon components of the coal (i.e. water, sulphur and volatile matter) are driven off. During the coking process, large amounts of gas are generated; only around 25% of the coal is carburated. The Table 4. Parameter values in process model Parameter
Value
Coke oren acc~ aet ag t ah I aho~
1.2956 tonne'tonne 39.64 kwh:tonne 390 nM s tonne 0.8968 GCal/tonne 0.0042 GCal;nM 3
Sintering plant ae z at', age,. ah, aof,
41.84 kWh~ tonne 0.3514 tonnes/tonne O.1088 tonnes/tonne 0.0219 GCal/tonne 0.7878 tonnes/tonne
Blast furnace ac s a% afs ag 3 ah s aha~ aho s aio s as s
0.849 tonnes/tonne 25.85 kWhr/tonne 0.2157 tonnes/tonne 2612 nMS tonne 0.7255 GCal/tonne 2800 nMS:tonne 0.00085 GCal/nM s 1.0558 tonnes:onne 0.6797 tonnes/tonne
Basic oxygen furnaces ae~ afa4 an4 apa as4
28.24 kWhr tonne 0.012 tonnes:tonne 53.15 MS tonne 1.072 tonnes tonne 0.190 tonnes tonne
Open hearth furnace ae 5 af 5 afa 5 ah s ai S an s aps a%
22.43 kWhr tonne 0.050 tonnes:tonne 0.022 tonnes: tonne 0.739 GCal'tonne 0.175 tonnes/tonne 22.43 M~/tonne 1.239 tonnes/tonne 0.271 tonnes/tonne
Blooming mill ae~ ah 6 asc6 ast~
26.04 kWhr/tonne 0.0,31 GCal:tonne 0.125 tonnes:tonne 1.1252 tonnes/tonne
Slabbing mill ae7 ah7 aSC~ ast 7
Source." JNU Report [6].
45.71 kWhr tonne 0.361 GCal/tonne 0.178 tonnes: tonne 1.1725 tonnes tonne
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Anandalingam, Bhattacharya--Steel Industry in India
coke-oven gas is treated to remove by-products like tar and is used as a fuel elsewhere in the plant. Inputs into the coke ovens consist of coking coal (CC~). electricity (Ej) and heat (H~). All these inputs are required in constant proportion to the gross coke produced (GC1). CCI = acct' GCI
(1)
E~ = ae~-GCt
(2)
Hi = aht G C t
(3)
In addition, the coke oven gas produced (G~) is also in constant proportion to the output of gross coke Gt = agL'GC~
(4)
The heat content of the coke oven gas is given by: HOI = ahol 'GI
(5)
where ah~ is the calorific value. The gross coke produced consists of coke used in the blast furnace (GC3) and coke fines used in the sintering plant (GC2). GCt = GC: + GC 3
(6)
Sintering plant In the sintering plant, fine iron ore particles are agglomerated into a porous mass that is suitable to be charged into the blast furnace. The sintering machine is charged with a mixture of iron ore fines (OF2), coke dust (GC_,) and limestone (F2) in proportion to the sinter that is produced (S,). OF, = aof,' S,
(7)
GC, = agc2 S,.
(8)
F_, = af2.S 2
(9)
In addition, process heat is required in order to produce the high temperatures required for agglomeration. The heat requirement (H z) is also in proportion to the sinter produced, as in the electricity (E2) required for the various motors: H, = ah.,. $2
(10)
E, = ae2"S2
(11)
Blast furnace The blast furnace produces pig iron/raw iron
(PI 3) from either lumps or pellets of iron ore and sinter ($3). These inputs are primarily composed of iron oxide which is reduced to raw iron under high temperature in the blast furnace. The carbon needed tbr the reduction is added on the form of coke (GC3). In order to attain the high temperature needed for the reduction of the iron oxide, and the melting of the metallic iron, hot air (HA3) and oxygen (03) are injected under pressure at the bottom of the furnace. In addition to the hot pig iron, a by-product gas is produced which has an energy content around one-fifth that of coke oven gas. One of the major impurities in the iron ore (and in the coke) is silica, which leads to ash formation in the furnaces. Limestone (F 3) is used as a binding agent to remove the silica in the form of slag. We assume that all these inputs are in constant proportion to the hot-metal (pig iron) produced: (IO3)
IO 3 = aio3. PI3
(12)
S 3 = as3. PI 3
(13)
GC 3 = ac3.Pl 3
(14)
af 3• PI 3
(15)
F 3=
HA 3 = aha3' PI3
(16)
03 = a03' PI3
(17)
Process heat (H3) and electricity (E3) are also required in proportion to the pig-iron produced: H 3 = ah3-PI 3
(18)
E 3 = ae3. PI 3
(19)
The energy efficiency of blast furnaces depend very critically on the Fe (Iron) content of iron ore [11]. However, in the Indian context, the iron ore has a very high Fe content and, in any case, there is very little variation in the concentration. For example, during the period from 1970-71 through 1978-79, the percentage Fe content in the annual ore use at the blast furnaces of the Durgapur steel plant, had a mean of 61.4 and a standard deviation of 0.58 (SAIL statistics [13]). All public sector steel plants in India have well equipped ore storage and handling yards where different grades of iron ore can be blended in order to yield ores with more or less fixed Fe content. It should be noted, however, that blast furnace performance is sensitive to the relative proportions of sinter and lump ore in the blast furnace charge. We
Omega, Vol. I3, No. 4 explore this relationship in the section of the paper that deals with the simulations. We assume in this study that all coke and sinter that is required in the blast furnace are produced within the integrated steel mill, i.e. in addition to equation (6) which accounts for coke usage, sinter use is given by: S 3 = S~
(20)
In order to manufacture raw steel, the pig iron is used in the BOF (PIa) and the O H F (PIs). In the Indian mills, we assume that very little pig iron is sold by itself, i.e.; PI3 = PI4 + P15
(2l)
The iron making process also produces an off-gas that has a high calorific value. The quantity of the gas, G 3, is proportional to the hot metal produced: G.~ = ag3" Plj
(22)
The heat content of the blast furnace gas is given by: HO3 = aho3"G3 (23) where aho3 is the calorific value. Raw steel manufacturing Pig iron produced in the blast furnace is transformed into steel in either a (BOF) or an (OHF) furnace. Based on actual data in the Indian steel industry, we assume constant coefficients for hot-metal and scrap input into the O H F and BOF processes. Energy consumption, especially in the O H F process, is highly sensitive to scrap ratios [11]. However in the period 1970-71 through 1978-79, the scrap ratio remained virtually constant in the Indian case. For example in the Bhilai steel plant, where steel is produced by the O H F process, the scrap ratio (for the nine years) had a mean of 0.259 and a standard deviation of 0.005 (SAIL statistics [I 3]). The corresponding figures for hot metal input coefficients were 0.79 and 0.01 respectively. It should also be noted that, in the public sector steel plants, the entire scrap input is produced within the plant--there is no purchase. All of this would change if the Indian steel industry were to invest significantly in mini steel mills. This is not expected in the near future. Basic oxygen furnace. In the basic oxygen process, pure oxygen is injected into a charge of melted pig iron and steel scrap through a water
301
cooled lance. The oxygen reduces the melting time, increases the temperature and increases the rate of oxidation. The only source of heat is the heat in the hot metal and the heat generated by the reactions between the oxygen and the metalloids in the hot metal. In order to strengthen the steel, ferro-alloys are added in the steel making furnaces. The inputs pig iron (PI~), scrap (SC4), oxygen (O~) and ferro-alloys (FA~) are assumed in constant proportion to the ingot steel produced (STy) from the basic oxygen furnace: PI~ = ap4' STz
(24)
SC4 = as,t" ST4
(25)
O~ = ao~. ST~
(26)
FA4 = afa4" ST~
(27)
The only external energy source is electricity (E4) which is given by: E4 = ae4- ST4 (28) Open hearth furnace. The open hearth furnace consists of a shallow refractory lined rectangular room with openings at both ends. These openings are interchangeably used for injection of preheated air and evacuation of exhaust gases. During the steel making cycle, preheated air together with fuel is blown into the furnace from one end. After some time, the exhaust gases leave the furnace and heat up some brick chambers. The heat of the bricks is used to pre-heat the fresh incoming air. The process is relatively time consuming compared to the BOF. Major inputs into the open-hearth furnace consist of the hot pig-iron from the blast furnace (PIs), steel scrap from the steel finishing mills (SC5) and treated iron ore 005). Some oxygen (O5), limestone (Fs) and ferro-alloy (FAs) are also used in the steel manufacturing process. All the inputs are consumed in constant proportion to the ingot steel produced in the open hearth furnace (STs):
PI5 = aps" ST5
(29)
SC5 = ass- ST5
(30)
IO5 = ais" ST5
(31)
05 = aos- ST5
(32)
F 5 = afs. ST 5
(33)
FA 5 = afa 5- ST 5
(34)
Anandalingam, BhattachaG'a--Steel Industry in India
302
Process heat (H 0 and electricity requirements are also in proportion to the steel produced:
furnace (03) and in the BOF (OA and O H F (05), i.e.:
H5 = ahs" ST5
(35)
Os = 03 + 04 + 05
E5 = aes" ST5
(36)
Auto-generation of electricity and air blast. All Indian iron and steel mills produce in-house all the air blast that is needed and part of the electricity. The in-house production of air blast and electricity is an integrated process in which high pressure steam produced in a boiler (i.e. quantity HPS) is used in part (i.e. HPS,) in a power station to produce electricity (Eg) and in part (i.e. HPS~) in a blowing station to produce air blast (HAg). The steam required for each is in proportion to the output of each, i.e.:
Steel finishing The steel is either finished in the form of blooms or slabs using rolling mills. In addition to steel ingots, the major input into the steel finishing processes is electricity. The steel ingot may require some heat in order to prevent cooling. The steel ingots are heated in furnaces (soaking pits) prior to primary rolling. These soaking pits are fired with a mixture of CO gas and BF gas. Scrap produce in the steel finishing mills is recirculated within the plant. Blooming mill. Material and energy flow in the blooming mill is given by: ST 6 --- ast6. FS 6
(37)
H6 L_ ah 6. FS 6
(38)
E6 = aer' FS6
(39)
SC6 = ascr" FS6
(40)
Slabbing mill. Material and energy flow in the blooming mill is given by:
(48)
HPS, = as,.E9
(49)
HPSa = as~ .HA 9
(50)
and HPS = HPS~+ HPS~
(51)
In order to produce the high pressure steam, non-coking coal is burnt as a fuel in the boiler. The quantity of non-coking coal required is in proportion to the total steam produced: NC9 = ancg- HPS
(52)
We also assume that all the hot-air used in the steel mill is produced in-house; i.e.;
ST 7 = ast 7• FS 7
(41)
H7 = ah7" FS7
(42)
E7 = ae7" FS7
(43)
Material and fuel balance equation
SC 7 = asc 7- FS 7
(44)
The total heat produced within the steel mill (PH) by the coke oven gas is HO~ and by the blast furnace gas is HO3. Total process heat consumption (CH) occurs in the coke oven (H~), sintering plant (H_,), blast furnace (H3), open-hearth furnace (Hs), blooming mill (Hr) and slabbing mill (HT). The difference between the quantity of heat produced and that used has to be purchased (QH):
The steel produced by the different processes are inputs into the finishing mills: i.e.; ST 4 + ST 5 = ST 6 + ST 7
(45)
The total steel scrap used by the steel making furnaces are obtained from the finishing mills: SC4 + SC5 = SC6 + SC7
(46)
HA9 = HAs
PH = HO, + HO3
Auxiliary processes Oxygen plant. The oxygen plant produces oxygen (Os) (and nitrogen) by cryogenic distillation of air. The major input is electricity (Es), which is required in proportion to the oxygen produced: Es = aes' Os
(47)
The oxygen produced is used in the blast
(53)
(54)
7
¢ H = Y H,
(55)
O H = C H - PH
(56)
Total electricity consumed (CE) is given by: 7
CE = ~ E~ i~l
(57)
Omega, Vol. 13, No. 4
303
Table 5. Calibration of simulation model, base year results
Open hearth steel Basic furnace steel Hot metal Sinter Coking coal Iron ore
Model results 106 tonnes
Actual 10~ tonnes
Discrepancy (?g of actual)
3.35 2.55 6.88 4.68 8.41 11.59
3.35 2.55 7.40 6.05 8.70 12.21
0.0 0.0 -7.0 - 22.6 -3.3 -5.1
The total electricity that needs to be purchased (QE): is the difference between that required (CE) and that produced in-house (Eg): QE = CE - E9
(58)
SIMULATION RESULTS Preliminaries
At present, (i.e. 1983-84) the integrated steel mills in India produce 2.85 million tonnes (metric tons) of blooms and 2.26 million tonnes of slabs from 5.9 million tonnes of steel; 0.79 million tonnes of scrap are produced in the roiling mills of the crude steel production, 56.8~ is from OHF and 43.2~ from BOF. We used present production levels in the Indian steel industry to obtain simulation results on the other activities. Results are given in Table 5. Model results for the base year are generally lower than the actual activity levels. With the exception of sinter consumption, all discrepancies are below approximately 5~. Specific sinter consumption (i.e. per unit of molten iron produced) reported by the industry was lower (by 12.1~) than the author's estimate of the weighted average of specific sinter consumption in each of the steel mills. If the weighted average was used, then the discrepancy between model results and actual values will be approximately 10~, which is an acceptable level of error in simulation studies. We decided to use the specific sinter consumption reported by the industry for the present study. The impact of the discrepancy on energy use is estimated to be less than 0.01~/o. Analysis of energy use and conservation
We used the steel industry process model to analyze energy and materials use due to growth strategies and several energy conservation activities. The main thrust of our study was to provide results on the impact of government
policies energy conservation in the entire iron and steel industry in India. Growth. The Indian government has plans to increase steel production capacity to 17.8 million tonnes in 1989-90 from the present 11.4 million tonnes. Our contention, which is generally accepted by steel industry analysts in India, is that the production capacity will reach 17.8 million tonnes only in 1993-94, ten years from now. If we assume that capacity utilization will remain at 52~, the same level as in 1983-84, then steel production is projected to grow by 4.6~ on the average during the next ten years. Given this growth scenario, by 1993-94 the steel industry will require 13.2 million tonnes of coking coal, 0.8 million tonnes of non-coking coal and 1672 Mwhr of electricity ceteris parabus (Table 6). These are all large magnitudes, especially coking coal for which there is only a limited level of reserves in India. Total material costs for producing the required 9.25 million tonnes of crude steel will be Rs. 11.9 billion in year 1993-94. Conservation--Shifting from open hearth to basic oxygen furnaces. Most of the new capacity that the government of India is planning is expected to be in systems that use BOF. By 1993-94, the level of steel produced in basic oxygen furnaces is expected to grow to 70~ (from the present 43.2~o) and open hearth steel is projected to decline to 30~o of total production (from the present 56.8~). If production capacity is changed to 70~ basic oxygen furnaces, the consumption of coking coal and process heat in 1993-94 goes down compared to the Business As Usual Case by 3.9 and 11.9~ respectively (Table 6). Electricity consumption goes up 6.8~. Total energy use decreases by 5.1~, a fairly insignificant amount. Use of other materials such as iron ore, sinter, ferro-alloys, etc. all decrease and total cost of production goes down by an insignificant 4.5~. Conservation--Increasing sinter use. When
304
Anandalingarn, Bhattacharya--Steel Industry in India Table 6. Results of policy simulations, 1993-94 Policy scenarios Cokingcoal(106tonnes) Non coking coal ([0~tonnes) Electricity (MWhr) Process heat (106GCal) Total energy (10OGCal) Sinter (106 tonnes) Iron ore (106 tonnes) Ferro-alloys (106 tonnes) Total cost (109 Rupees)
BAU
70 BOF
SSC
CDI
DQC
70 + SSC
t3.18 0.78 1672 21.00 93.00 7.37 18.17 0.t6 1[.87
12.67 0.77 1785 t8.51 88.30 7.06 17.07 0.14 II.34
11.64 0.79 1702 19.97 84.69 9.17 19.64 0.16 11.26
10.54 4.16 [672 21.00 99.93 7.37 18.17 0.16 11.41
12.67 0.72 t273 18.51 86.73 8.29 17.07 0.14 11.11
11.20 0.77 1813 17.52 80.3t 8.82 18.48 0.14 [0.76
BAU--business as usual (ceteris paribus). 70 BOF--70% basic oxygen, 30% open hearth. SSC--increasing sinter use---
more sinter is used in the blast furnace, less iron ore is required to produce the same quantity of pig-iron (hot metal). Thus, less coke is required as a reducing agent. Hence one way to reduce coke use is to increase the use of sinter. In Indian steel mills, there is a clear trade-off between specific sinter use (i.e. per tonne of hot metal) and specific coke use (Fig. 2). We examine the policy of using 25% more sinter per tonne of hot metal. Specific sinter assumption will then increase to 0.85 from 0.68 while specific coke consumption will decrease to 0.75 from 0.85. Increasing sinter use will lead to a reduction in coking coal use which is greater than the policy of increasing the proportion of BOF (Table 6). In addition changes in the use of inputs that have embodied energy are: coking
,$ o
== o
"10
•u
08
c
06
~ 04 "2_ 0 2
g
I
I
02
Q4
Spectf~c
sinter
I
I
06
08
I
I
10
1 2
L 1.4
consumphon (tonnes/tonne)
Fig. 2. Sinter vs c o k e tradeoff in I n d i a n blast furnaces.
coal use decreases by ll.7%, non-coking coal use remains the same, electricity use increases by 1.8% and process heat decreases by 4.9%. Overall energy use decreases by 8.9% which is more significant than before. Total production cost goes down by 5.1%, a small change. Conservation--Coal dust injection. When coal dust is injected through the tuyeres of the blast furnace, it acts as a reducing agent in the production of crude steel; subsequently less coke is required. Indian coal, however, has a very high ash content. Hence we use specifications for coal with 9% ash and assume that for every tonne of coke that is replaced, 1.282 tonnes of coal dust would be required. We investigate the impact of reducing coke consumption by 20?/0 by using coal dust injection. The use of non-coking coal increases to 4.16 million tonnes, a change of 3.38 million tonnes; all of this comes from the addition of coal dust. While the consumption of all other inputs remain the same, total energy use increases from the BAU case by 7.5%; total cost decreases by 3.9%. Clearly coal dust injection will not lead to overall conservation of energy, only a savings in the use of coking coal. For a country like India where coking coal is in short supply, conservation of coking coal is an important strategy. For the steel industry as a whole, this strategy will also lead to a savings in the production cost. Conservation--Dry quenching of coke. Hot coke that is produced is usually quenched in a liquid medium to bring it to useful temperatures. If the hot coke is 'dry' quenched, i.e. quenched in air or using a gaseous medium, the heat transferred to a medium can be recovered using waste heat boilers. Steam generated by
Omega, ~bl. 13, No. 4
these waste heat boilers can either be used for process heat or for producing electricity. In most steel plants, the gases produced as byproducts in the coking oven and blast furnace provide enough process heat for the steel making processes. Hence, the waste heat that is recovered from dry quenching coke is used primarily to produce electricity. In one of the new Indian steel mills (at Vizhagapatnam), there is at present a proposal to adopt a Soviet design for dry quenching coke. In a typical Soviet dry quenching unit, 21MW of electricity is produced for a coke throughout of 4990 tonnes/day (1.821 × 106 tonnes/year). Using these figures and the assumption that energy from the 'power plant' is used at the same rate as the level of capacity utilization, we estimate that 52.32 kwhr of electricity is produced per annual tonne of coke. The total energy consumption with the dry quenching of coke is 86.73 x 106 GCal, a reduction of 6.7~o. Total production cost also decreases by 6.4~, the largest reduction in production cost among all the conservation options. The electricity produced by the dry quenching of coke substitutes for approximately 23.9°0 of total electricity required by the steel making process. This magnitude of electricity is quite significant. Conservation--Combination of sinter use and basic o.Lvgenfi~rnances. A final strategy that was analyzed assumed a policy of increased sinter use and the transformation of steel making in BOF. As before, we assumed that sinter use would increase by 25~ and by 1993-94, the proportion of BOF would by 70~/o. Clearly the combined strategy was the best with regard to all criteria. Total energy use decreased by 13.6~o and production cost decreased by 9.4~°~ as compared to the BAU case. Coking coal consumption was lower than in all strategies with the exception of the coal dust injection strategy where we assumed that coking coal use would decrease by 20%. Coking coal consumption decreases by approximately 15~ in this strategy. Inuestrnent costs
In the study so far, we have not explicitly modelled investment costs for the different energy conservation options. This work is in the process of being completed. Some preliminary
305
findings are apparent from the preceding analysis. The difference in production cost between continuing with 43.2/0 , o/ BOF or increasing it to 70~o is 430 million (Table 5). Assuming that operating and maintenance (O & M) costs for both scenarios remains the same (which it should be) then the investment cost for the new BOF should not exceed 4.02 billion at an equipment life-time of 20 years and 10% interest rate, (i.e. capital recovery factor = 0.107). Dry quenching of coke will lead to a cost saving of 760 million. Hence investment costs for the technology for dry quenching of coke and for producing electricity should not exceed 7.10 billion. Incremental use of sinter and coal dust injection are both conservation practices that are practically costless. However should more sintering plants and coal dust injection facilities be required, the investment costs should not exceed Rs. 5.70 billion and Rs. 4.30 billion respectively, to be economical. CONCLUDING REMARKS It seems apparent from our simulation results that none of the policy options that we examined would lead to significant levels of energy conservation by themselves. Increased use of sinter results in the largest reduction in the use of coking coal and total energy, the former by 11.7~ and the latter by 8.9~. If strategies are combined, then there will be considerable scope for energy conservation in the Indian steel industry. If the industry changed its production structure so that BOF formed 70~ of crude steel production and increased the use of sinter, the coking coal and energy use decreases by 15 and 14% respectively. Overall, however, it appears that the Indian steel industry has limited scope for saving energy although aggregate analysis in other studies showed a high level of energy intensity. Although the percentage change in energy and coking coal use was low, the absolute reductions were quite significant. For instance, the decrease in energy and coking coal use in the best option (i.e. use of sinter) was 8.3 million GCal and 1.54 million tonnes respectively. This is especially true in the case of production costs. The savings in production costs per year could easily justify spending up to 4 billion in OHF
306
Anandalingam, Bhattacharya--Steel Industry in India
a n d 7 billion for the t e c h n o l o g y for dry, quenching o f coke. A c t u a l investment costs are expected to be lower. In this study, we did not include energy c o n s u m p t i o n by the auxiliary processes such as the p r o d u c t i o n o f bulk oxygen because we did not expect it to be significant. In view o f o u r finding t h a t investing in B O F d o e s n o t lead to m u c h energy savings, full c o n s i d e r a t i o n o f energy c o n s u m e d by the oxygen p r o d u c t i o n p r o cess might even reverse the c o m p a r a t i v e efficiency o f O p e n H e a r t h a n d Basic O x y g e n processes. T w o o t h e r issues also need to be addressed. W e have a s s u m e d that c a p a c i t y utilization rem a i n s at 52~o t h r o u g h o u t the time h o r i z o n o f the study. S h o u l d there be increasing energy a n d e c o n o m i c scale efficiencies, the greatest imp r o v e m e n t s in energy use w o u l d c o m e from higher levels o f c a p a c i t y utilization. Since we used a linear m o d e l in this study, we implicitly m a d e the a s s u m p t i o n that there were c o n s t a n t scale economies, that is, the energy efficiency was i n v a r i a n t with respect to c a p a c i t y utilization. T h e m a i n reason for this r a t h e r restrictive a s s u m p t i o n was the lack o f sufficient d a t a on how the p a r a m e t e r s (Table 4) o f the m o d e l varied with the level o f c a p a c i t y utilization. Inclusion o f c a p a c i t y utilization c o n s i d e r a t i o n s has p r o v e d to be a difficult p r o b l e m for those w o r k i n g on d e v e l o p i n g c o u n t r i e s [3]. F i n a l l y it should be p o i n t e d o u t t h a t the focu3 o f the study was on energy c o n s e r v a t i o n . Clearly the goal o f energy-efficiency is o n l y one o f m a n y objectives that a p l a n n e r or the industry w o u l d be interested in. A m o r e c o m p l e t e multi-objective m o d e l is left for future work.
ACKNOWLEDGEMENTS An earlier version of this paper was presented at the 26th International Meeting of the Institute of Management Sciences, Copenhagen, Denmark. The research for this study was conducted when the first author was a Visiting Fellow at Tata Energy Research Institute, New Delhi on a
Rockefeller Foundation International Relations Fellowship. None of the at~liated institutions necessarily agree with the contents of this paper. We thank an anonymous referee for constructive comments and criticisms. REFERENCES 1. Anandalingam G (1983) Policy incentives for industrial energy conservation. Energy Mgmt 7(4), 317-329. 2. Bhattacharya D (1985) Energy analysis of Indian integrated iron and steel plants. Indian Eastern Eng Annual Volume. New Delhi, (forthcoming). 3. Blitzer CR, Clark PB and Taylor L (1977) EconomyWide Models and Development Planning. Oxford University Press. 4. Fabian T (1958) A linear programming model of integrated iron and steel production. Mgmt Sci. 17(7), 415-429. 5. Howe SO, Pitati DA and Sparrow FT (1980) Process modeling and industrial energy use. Report No. BNL 28838, Brookhaven National Laboratory, Upton, New York. 6. Jawaharlal Nehru University (198t) Problem of production and investment planning in Indian iron and steel industry. Hindustan Steel Limited, Case Study, unpublished report, Department of Planning, New Delhi. 7. Manne AS and Markowitz HM (1963) Studies in Process Analysis. John Wiley, New York. 8. Missirian G (1978) Energy utilization in the U.S. iron and steel industry: a linear programming analysis. Unpublished PhD Dissertation, University of California, Berkeley. 9. Mohanty RP and Swain D (1982) Energy management problems of Indian steel ptants. Energy Mgmt 6(3), 167-182. 10. Russell CS and Vaughn WJ (1974) Environmental quality problems in iron and steel production. Discussion Paper, Resources for the Future, Washington, D.C. I I. Russell CS and Vaughn WJ (1976) Steel Production: Processes, Products and Residuals. Johns Hopkins University Press, Baltimore. 12. Sparrow FT, Pilati D, Dougherty T, McBreen E and Juang LL (1980) Iron and steel process model. Report No. BNL 51073, Brookhaven National Laboratory, Upton, New York. 13. Steel Authority of India Limited-SAIL. Operational Statistics: Public Seclor Steel Plants. (Many volumes, various years). 14. Tsao CS and Day RN (1971) A process analysis model of the U.S. steel industry. Mgmt Sci. 17(10), B588-B608.
Professor G Anandalingam, Department of Systems Engineering, University of Virginia, Charlottesville, Virginia 22901, USA
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