Economical optimization of steam data for recovery boilers

Abstract: Pulp and paper mills are high power consuming industries. Pulp and integrated mills produce power via steam turbines in recovery boilers. Due to high power prices and the fact that biomass combusted in the recovery boiler is considered as green energy, there is today a desire to always increase the power generation when investing in new recovery boilers. In order to increase power output from the steam turbine the steam data (i.e temperature and pressure) needs to be increased. With higher steam temperature follows a higher risk of corrosion due to the non process element potassium in the boiler fuel. The uncertainties of high temperature corrosion and the unpredictable environment in the furnace makes it difficult to design recovery boilers. This results in higher investment cost and could lead to less profit for the mill buying the boiler. The question then stands whether the revenue obtained from the higher power generation, is higher than the investment made for the upgrade in order to produce the higher steam data over a certain time. And more specifically what steam data will be the most economical, when comparing revenue from power generation with investment cost? In this study, together with ÅF Industry AB, four boilers with different steam data (Boiler A: 38.5 bar, 450°C; Boiler B: 92 bar, 480°C; Boiler C: 106 bar, 500°C; Boiler D: 115 bar, 515°C) were compared. The boilers were compared for four potassium levels: 1.0wt%, 1.5wt%, 2.5wt%, 3.5wt%. And two values of power were used, 300 SEK/MWh and 700 SEK/MWh. The marginal differences between the boilers were: the amount of material used in the superheaters in order to produce different steam data; the type of material used in the superheaters and the furnace; whether an ash-treatment system was needed (in order to purge potassium from the process); the turbines and generators; whether a feed water demineralization equipment was needed; the yearly cost for make-up chemicals (due to usage of an ash-treatment system) and the amount of power generated. The boilers investment cost and net yearly revenue were compared in order to determine the marginal pay-off in years. The most economical choice of boiler for the different potassium levels for 300 SEK/MWh: 1.0wt%, Boiler D; 1.5wt%, Boiler C; 2.5wt%, Boiler B; 3.5wt%, Boiler D (A). And for 700 SEK/MWh: 1.0wt%, Boiler D; 1.5wt%, Boiler C; 2.5wt%, Boiler D (B); 3.5wt%, Boiler D. The conclusion in this thesis was that the deciding factor is whether the boiler is in need of an ash-treatment system. Higher steam data is preferable as long as ash-treatment can be avoided. However, when comparing two boilers with ash-treatment the one with higher steam data is more feasible. Low steam data, such as boiler A, will never be feasible, regardless of potassium level and value of power.