Steam Prediction at an Integrated Pulp and Paper Mill : Mondi Dynäs in Kramfors Municipality

Sammanfattning: 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.