The most important energy carrier at an integrated pulp and paper mill is steam, it is essential to power components and machinery. The components create variations in the steam grid network, variations that exceed the capacity of the steam accumulator. To avoid steam shortages, production leans towards having the accumulator nearly filled, eventually leading to periods with over production. Abundantly produced steam must be released from the steam grid network, and this is done without energy recovery. The purpose has therefore been to create a computer model with the ability to predict steam consumption for the entire mill. The prediction shall eventually be used in the control systems for steam producers and the accumulator. By knowing future steam demand, production can be planned more efficiently and so can the accumulation level of steam. This will allow a greater range of operation since the predictor can provide information on when significant steam demand changes will occur. The most important energy carrier at an integrated pulp and paper mill is steam, it is essential to power components and machinery. The components create variations in the steam grid network, variations that exceed the capacity of the steam accumulator. To avoid steam shortages, production leans towards having the accumulator nearly filled, eventually leading to periods with over production. Abundantly produced steam must be released from the steam grid network, and this is done without energy recovery. The purpose has therefore been to create a computer model with the ability to predict steam consumption for the entire mill. The prediction shall eventually be used in the control systems for steam producers and the accumulator. By knowing future steam demand, production can be planned more efficiently and so can the accumulation level of steam. This will allow a greater range of operation since the predictor can provide information on when significant steam demand changes will occur.By creating separate predictor models for the largest steam consumers, the final predictor consists of four minor predictor models. The first is related to five batch digesters, the second to one of the two paper machines (PM5), the third to the other paper machine (PM6), finally the forth to all other consumers. The separate predictors have been created by gathering historical process data connected to their operation. Analyses and correlations have been made to show what has significant effects on their steam consumption. The final predictor has shown the possibility of having an R2 above 0.7 for up to one hour ahead. Even though, it is possible to have 60 minutes of accurate prediction. Reliable prediction ranges are determined for the four separate predictors. The reliable prediction range for the two paper machines has a potential of 15 minutes and the R2 is still above 0.8 for that time ahead. The predictions for digesters have an R2 above 0.6 for up to 25 minutes ahead. The steam demand from other components can be predicted with an average error of no more than 9% for 60 minutes ahead. / Vid ett integrerat massa- och pappersbruk är ånga den mest vitala energibäraren, den brukas av maskiner och komponenter för massa- och papperproduktionen. Komponenternas arbetscykler skapar svängningar på ångnätet som överstiger vad den installerade ångackumulatorn kan hantera. För att möta det svängande behovet produceras ånga i en sådan takt att ackumulatorn ska hålla hög nivå. Något som skapar perioder med överproduktion och full ackumulator vilket leder till att ånga måste friblåsas förutan energiåtervinning. Av denna anledning har syftet med detta arbete varit att ta fram en prediktionsmodell som kan förse bruket med pålitlig prognos för ångförbrukning. Kunskap om framtida prognoser ska såsmåningom implementeras i styrningen för ackumulatorn samt ångproducenter. Prognoserna ska underlätta att mer effektivt möta kommande behov, större reglerutrymme i ackumulatorn samt mer anpassad produktion. Den färdigställda prediktionsmodellen består av fyra mindre modeller grundade utefter de mest påverkande komponenterna. Den första tillhör de fem batch kokarna, den andra ansvarar för pappermaskin 5 (PM5). Tredje är till pappersmaskin 6 (PM6), slutligen en prediktor för övriga förbrukare. Prediktorerna har skapats utefter teoretiska behov samt relevant historisk data som påverkat energianvändningen. Analyser av korrelationer mellan olika parametrar har skapat prediktionsförmåga för dessa prediktorer. Den kompletta prediktionsmodellen uppvisar potential att leverera pålitlig prognos med förklaringsgrad R2 över 0.7 upp till 60 minuter fram i tiden. Trots att 60 minuters pålitlig prediktion är möjlig kan den inte garanteras. Pålitlig prediktionstid bestämms utifrån vardera enskild prediktor. Pappersmakinera påvisar pålitlig prediktionsförmåga upp till 15 minuter där R2 hålls ovan 0.8 inom den tiden. Kokeriets prediktionstid är 25 minuter där R2 har värden över 0.6. Övriga komponenter påvisar liten skillnad inom 60 minuters prediktionstid. Det genomsnittliga prediktionsfelet överstiger ej 9% inom den tiden.