SILO is a system designed to increase efficiency of industrial processes. It uses artificial intelligence methods to both optimize the process and gather knowledge about it. SILO can be considered as an additional operator who is constantly gaining knowledge about the process and thus keeps on increasing the efficiency of his work. Implementation of SILO in a coal-fired power station to optimize combustion process results in reduction of coal consumption (increase in boiler efficiency) and minimization of environmental emissions of such pollutants as nitrogen oxides (NOx), carbon monoxide and carbon dioxide (CO, CO2), sulfur oxides (SOx) and mercury.
Features
- On-line learning of a process based on current measurements
- Direct and fast adaptation to current process state
- Direct and fast adaptation to non-stationary process characteristics
- No need for manual model creation
- No need for tuning SILO models
- Easy modification of optimization task and goal
- Easy system management based on WWW interface
- Support for management, engineers and operators
- Fleet optimization solution
Applications
SILO is used in large-scale industrial processes optimization such as:
- Combustion process in power boiler
- Operation of FGD, SCR and SNCR systems
- Chemical and petrochemical processes
Benefits
- Increase of combustion process efficiency leading to the reduction of power generation costs
- Minimization of NOx, CO and SO2 emissions and therefore reduction of costs related to emissions control regulations
- Avoiding the higher cost of emission mitigation systems
- Increase of plant controllability
- No need for manual model creation process resulting in significant implementation cost reduction
- No need for tuning SILO models and therefore reduction of costs related to tuning of the base control structure
- Higher flexibility in the plant modernization and development
- Full integration with DCS – process safety, operators graphics