A real-time optimization method for economic and effective operation of electrostatic precipitators

Abstract

ABSTRACT Electrostatic precipitators (ESP) have been considered as the main particulate matter (PM) removal facility in the energy industry. This paper presents a real-time optimization method for a one-chamber industrial ESP in an ultra-low emission power plant with an intelligent optimization system (IOS). The IOS seeks to optimize the energy consumption of ESP subject to the outlet concentration requirement in real-time. A coordination control logic is designed to regulate the optimized operation set points with varying operation conditions. The operation optimized by the IOS is compared with the operations under PID (proportion-integral-derivative) and manual control. The results show that the IOS improves the emission compliance rate from 95% of manual control to 100% and the medium concentration is tuned to be 46.6% closer to the emission target. Furthermore, a good balance between emission and energy consumption is achieved, with 35.50% energy conservation for the same emission upper limit of 30 mg/m3. These results prove that the IOS significantly contributes to the efficient operation and economic PM removal by ESP for the energy industry. Implications Electrostatic precipitators (ESP) is one of the main PM removal facilities in coal-fired power plants. An intelligent optimization system (IOS) with prediction, optimization, and control modules is designed and constructed for the ESP in an ultra-low emission power plant. A PM removal model is used to predict the outlet concentration of the ESP. The optimal energy consumption of ESP subject to the outlet concentration requirement problem is solved by the particle swarm optimization. A closed-loop and rapping tolerant method is used to eliminate the fluctuation in time-averaged concentration. The system raised is able to ensure the compliance rate while decreasing the energy consumption of the ESP.