An Energy-Saving Solution for Hydrogen Conductivity Measurement Systems in Thermal Power Plant Boiler Water Based on Deep Regeneration Technology Using Ion-Exchange Resins

Abstract

To address discontinuous boiler water hydrogen conductivity measurement, low resin exchange output, high plant energy consumption, and frequent offline regeneration of resin columns in thermal power plants, an accuracy-constrained energy consumption optimization model for deep regeneration of ion exchange resins was developed. Based on the traditional hydrogen-type cation exchange resin column measurement process, the model integrates hydrogen generation through ionization, ion migration, online resin reset, and four-channel independent regeneration control, forming a closed-loop framework of “capacity identification—trend determination—liquid volume and time optimization— accuracy-constrained control.” Real-time parameters, including flow rate, pressure, temperature, hydrogen conductivity, regeneration voltage, and current, are collected to identify resin exchange-capacity decay, determine regeneration timing and triggering conditions, and optimize regeneration power and cycle duration. The optimization is constrained by a measurement error of ≤3% and a cation removal efficiency of ≥99.9%. A 30-day test on Huayuan Unit 1 and Unit 3 at 20 test points showed that the average effective resin exchange quantity increased from 0.97 mmol·mL−1 to 1.50 mmol·mL−1, the average failure interval extended from 7.7 days to 29.3 days, and total system energy consumption decreased from 173.4 kWh to 112.5 kWh, representing a 35.12% reduction. After deep regeneration, the average relative error decreased to 1.14%, and the effective data rate increased to 99.36%. These results indicate that the model reduces regeneration and maintenance energy consumption while ensuring the accuracy of boiler water hydrogen conductivity measurement.