A method for on-line monitoring and determining a calorific value of a solid fuel that is currently combusted in a boiler that comprises a combustion chamber with a steam production system, to which the solid fuel is fed from at least one mill connected to a hopper, characterised in that the method comprises the following steps: - measuring, on-line during the operation of the boiler, operational data of the boiler, and operational data of at least one mill; - wherein the operational data of the boiler are measured by means of sensors (15-1, 15-2, 15-3, 15-4) and comprise at least one of: temperature, pressure, steam flow; wherein the operational data of the at least one mill are measured by means of sensors and comprise at least one of: mill power, air pressure upstream of the mill, solid fuel feeder revolutions, air temperature upstream of the mill, temperature of the dust-air mixture downstream of the mill; - collecting historical data of measurements of the calorific value of the solid fuel and the operational data of a power block, wherein the operational data of the power block include at least one of: lower heating value, mill characteristics, fuel flow rate and boiler efficiency, operational parameters of turbine, including flows, pressures and temperatures for live steam, superheated steam and secondary steam, operational data of the boiler, operational data of at least one mill, composition of exhaust gases, power of the block; - calculating energy balances of the steam production system, based on the collected historical data and depending on the amount of thermal energy input to the turbine generator set (Qin) divided by the boiler efficiency; - iteratively determining an efficiency of the boiler based on the historical data by: - determining sets of mill characteristics depending on a calorific value of the solid fuel and operational data of the mill while combusting that solid fuel, wherein the mill characteristics include at least one operational parameter selected from the group consisting of: mill power, air pressure upstream of the mill, solid fuel feeder revolutions, air temperature upstream of the mill, temperature of the dust-air mixture downstream of the mill; - determining a fuel mass flux based on the set of mill characteristics; and - determining the actual calorific value of the fuel for the historical data; - training a model based on artificial intelligence algorithms to predict the calorific value using the historical data of fuel calorific value and measured operational data of the boiler; and - determining in real time, using the trained model, the calorific value of the solid fuel that is currently combusted. - measuring, on-line during the operation of the boiler, operational data of the boiler, and operational data of at least one mill; - wherein the operational data of the boiler are measured by means of sensors (15-1, 15-2, 15-3, 15-4) and comprise at least one of: temperature, pressure, steam flow; wherein the operational data of the at least one mill are measured by means of sensors and comprise at least one of: mill power, air pressure upstream of the mill, solid fuel feeder revolutions, air temperature upstream of the mill, temperature of the dust-air mixture downstream of the mill; - collecting historical data of measurements of the calorific value of the solid fuel and the operational data of a power block, wherein the operational data of the power block include at least one of: lower heating value, mill characteristics, fuel flow rate and boiler efficiency, operational parameters of turbine, including flows, pressures and temperatures for live steam, superheated steam and secondary steam, operational data of the boiler, operational data of at least one mill, composition of exhaust gases, power of the block; - calculating energy balances of the steam production system, based on the collected historical data and depending on the amount of thermal energy input to the turbine generator set (Qin) divided by the boiler efficiency; - iteratively determining an efficiency of the boiler based on the historical data by: - determining sets of mill characteristics depending on a calorific value of the solid fuel and operational data of the mill while combusting that solid fuel, wherein the mill characteristics include at least one operational parameter selected from the group consisting of: mill power, air pressure upstream of the mill, solid fuel feeder revolutions, air temperature upstream of the mill, temperature of the dust-air mixture downstream of the mill; - determining a fuel mass flux based on the set of mill characteristics; and - determining the actual calorific value of the fuel for the historical data; - determining sets of mill characteristics depending on a calorific value of the solid fuel and operational data of the mill while combusting that solid fuel, wherein the mill characteristics include at least one operational parameter selected from the group consisting of: mill power, air pressure upstream of the mill, solid fuel feeder revolutions, air temperature upstream of the mill, temperature of the dust-air mixture downstream of the mill; - determining a fuel mass flux based on the set of mill characteristics; and - determining the actual calorific value of the fuel for the historical data; - training a model based on artificial intelligence algorithms to predict the calorific value using the historical data of fuel calorific value and measured operational data of the boiler; and - determining in real time, using the trained model, the calorific value of the solid fuel that is currently combusted.