Energy Consumption and Analysis of Optimal Interregional And
Total Page：16
File Type：pdf, Size：1020Kb
FINAL REPORT T O NATIONAL COUNCIL FOR SOVIET AND EAST EUROPEAN RESEARC H T I T LE : Energy Consumption and Analysis o f Optimal Interregional and Internationa l l Flows in the Soviet Iron and Stee Industry AUTHOR : Dr . Craig Zu m Brunnen University of Washington CONTRACTOR : Boston University PRINCIPAL INVESTIGATOR : Dr . Jeffrey P . Osleeb Boston University COUNCIL CONTRACT NUMBER : 624-7 DATE : June 30, 198 3 The work leading to this report was supported in whole or i n part from funds provided by the National Council for Sovie t and East European Research . NCSEER March 8 3 EXECUTIV E SUMMARY Industrialization in the Soviet Union has concentrated on the iro n and steel industry . Sometimes in the past emphasis has appeared to hav e been on increasing sheer physical output rather than on reducing cost s or on increasing efficiency . But attention is turning increasingly t o the relative costs of production at various places throughout th e country, as affected by the location and quality of iron ore, cokin g coal, and other raw materials, by transportation costs of such ra w materials to iron and steel centers, by costs of processing in relatio n to scale and alternative process, and by costs of transportation t o reach the markets both domestic and foreign . This study is an attempt to analyze the optimal locations for iro n and steel production and to predict probable shifts in location of th e industry and in the amount and processes of production at both present and future centers up to the year 1990 . A mathematical model was formulated to study the costs, production , locations, and flows in the Soviet iron and steel industry . This mode l incorporated the movement of energy, raw materials , intermediate products, and steel from ultimate sources of localized raw materials t o ultimate markets for steel throughout the entire Soviet Union . Th e study included flows in 1980 and projected flows to 1990 . It involve d 'some 1,200 constraint equations . and 18,000 decision variables . Th e model, called SISEM, a spatially disaggregrated mathematical model, is a multi-stage and multi-process formulation . In general it incorporate s upper and lower production constraints by process or commodity, by node , and by year . Detailed Soviet production figures, costs, technologica l coefficients (and their projections to 1990) were incorporated whereve r possible . The model includes domestic coking coal, imports of cokin g coal, coke manufacture, iron ore, ore enrichment, ore exports, scra p metal, pig iron, steel (in six basic variants of four processes), fina l domestic and export demands for pig iron and steel, and costs o f transportation joining all of them . The major findings and speculations are as follows . The optima l supply locations for coking coal exports tends to shift increasingl y eastward to the Kuzbas and beyond both for European as well as Pacifi c exports . Like the current actual pattern, the Ukraine dominates as th e source region for Soviet iron ore exports in both model years with th e Kola Peninsula being the secondary supplier in 1980 and sharing that rol e with the KMA in 1990 . Nonetheless, the Ukraine ' s absolute export flow s decline slightly while its relative export market share drops in th e model from 92,5 percent in 1980 to 82 percent in 1990 . Also, unlike th e actual current iron ore export flow pattern, the KMA does not optimall y serve any export markets in 1980 but does export 3 .0-million ton s through Riga in 1990 . Ukrainian pig iron furnaces and those at Lipets k dominate the Soviet pig iron export markets in both years . Ukrainia n dominances in the steel export flows in 1980 are seriously challenged b y 1990 by two Urals competitors, Magnitogorsk and Chelyabinsk . The modelled completion of the BAM (Baykal-Amur Mainline railroad ) by 1990 was clearly a necessary condition to allow the proposed Chul ' ma n steel site to enter the optimal solution for 1990 as an active stee l node . Total transportation costs amount to only 5 .5 and 7 .1 per cent o f total costs for 1980 and 1990, respectively . The study has considerable bearing on technological change withi n the Soviet ferrous metallurgical industry . The model clearly indicate s that significant technological process shifts are warranted . Fo r - 1 - NCSEER March 8 3 example, the model satisfies steel demands while requiring 3 .7-millio n tons less pig iron in 1980 than the Soviets report . This situation i s attributable to the indicated switch to the production vast quantitie s of direct reduction steel for 1990 (22-million out of approximatel y 170-million tons) . In fact, the modelled pig iron production for 199 0 is still less than the reported actual tonnage for 1980 (105 .1-millio n versus 107 .3-million tons) . Krivoy Rog stands out as the clear plac e for any expanded pig iron production . Finally, none of the fiv e potential pi iron sites : Staryy Oskol, Barnaul, Tayshet, Svobodny y (981) or Tynda appears as an optimal choice . Several differences appear between the 1980 and 1990 stee l production patterns . First, all four of the proposed new stee l locations, Barnaul, Zhlobin, Chul ' man and Tayshet enter the optima l solution for 1990, the first with over 18-million tons, the second tw o with 5 .4-million and 5 .2-million tons, respectively, and Tayshet wit h 1 .3-million tons . More importantly, all of these new sites excep t Tayshet in East Siberia are shown as actively using the new direc t reduction process to produce from a low of 4 .2-million tons at Zhlobi n in Belorussia to a high of over 12 .6-million tons at Barnaul in Wes t Siberia . Second, whereas many locations are producing at capacity i n 1980, relaxed upper limits on steel plant capacities for 1990 result i n only two locations, Magnitogorsk and Krivoy Rog, operating at thei r upper limit . Several small sites fail to enter either solution, fewes t of all in 1990 . In effect, the model selects in favor of scal e economies, or in other words, the Soviets still appear to hav e unrealized potential savings to be garnered from scale economies . Third, because of the scrap supply problems the electric-ar c process using both pig iron and scrap does not produce steel in either year . Fourth, practically all of the steel produced by open-hearth furnaces i n 1980 used coke only . For 1990, however, the open-hearth furnaces ar e optimally shown as using much less coke and much more natural gas . The model in effect tested the internal consistency of the relevan t Soviet production and technological coefficient data . In this regar d the most significant finding is the scrap insufficiency problem . Scra p inputs appear as binding constraints in both runs . Simply stated usin g Soviet data one can not produce as much steel in 1980 as Sovie t statistics claim . Even allowing for the tonnage of ferro-alloys, lowe r input coefficients, etc ., a significant shortfall still would exist . The model ' s results imply that the Soviets are double counting stee l production by as much as 15 .55-million tons or 10 .5 per cent for 1980 b y reusing large quantities of on-site scrap . The scrap shortage i s dispersed throughout the Ukraine, Urals and West Siberia in 1980, bu t confined to the Urals in the 1990 run . Furthermore, other modellin g efforts indicate the magnitude of "on-site " scrap may be aroun d thirty-million tons . If true, then, the actual published Soviet crud e steel production data could overstate "useful " or net steel productio n by as much as nearly thirty-million tons, essentialy twice the quantit y suggested here . The investigation systematically assessed the impacts of projecte d changes in the availability and relative prices of energy and ra w material inputs both by type and region . Accordingly, coking coa l presents no " physical supply " problems in the model primarily becaus e coke is used in other industries beside steel and hence the model yield s large coking coal slack production values . On the other hand, th e escalating costs of Donbas coals make West Siberian coals marketabl e throughout much of the European U .S .S .R by 1990 . Although the model i s - 2 - NCSEER March 8 3 not constrained by crude iron ore or enrichment in either simulation, w e believe both are, in fact, already bottlenecks . There are some hints o f this in the 1990 run where all high-grade ore sites are forced t o operate at their maximum modelled capacities . The indicated changes i n optimal low-grade and enriched ore production suggests that the Soviet s should concentrate their expansion efforts in the KMA (Kursk Magneti c Anomaly), new deposits in northwest European Russia, Kremenchug, alon g the BAM, and much less so at Krivoy Rog and Rudnyy . Over the modelle d decade both the KMA and Ukrainian ore deposits play a significantl y larger role in Urals iron and steel production . Neither electricity nor natural gas appear to be limiting factor s overall for the foreseeable future as both have vast slack capacities . On a regional scale, however, Europe could well need both mor e electricity and gas, while the Urals may need more West Siberian gas . The relative share of the total systems cost arising from each of thes e energy inputs increases substantially from 1980 to 1990, that of natura l gas tripling and that of electricity nearly doubling .