Model Predictive Hybrid PID Control and Energy-Saving Performance Analysis of Supercritical Unit

Qingfeng Yang, Gang Chen, Mengmeng Guo, Tingting Chen, Lei Luo and Li Sun ()
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Qingfeng Yang: Dongfang Electric Qineng (Shenzhen) Technology Co., Ltd., Shenzhen 518000, China
Gang Chen: State Key Laboratory of Low-Carbon Smart Coal-Fired Power Generation and Ultra-Clean Emission, Nanjing 210023, China
Mengmeng Guo: National Engineering Research Center of Power Generation Control and Safety, School of Energy and Environment, Southeast University, Nanjing 210096, China
Tingting Chen: Dongfang Electric Qineng (Shenzhen) Technology Co., Ltd., Shenzhen 518000, China
Lei Luo: Dongfang Electric Qineng (Shenzhen) Technology Co., Ltd., Shenzhen 518000, China
Li Sun: National Engineering Research Center of Power Generation Control and Safety, School of Energy and Environment, Southeast University, Nanjing 210096, China

Energies, 2024, vol. 17, issue 24, 1-13

Abstract: In response to the escalating challenges of rapid load fluctuations and intricate operating environments, supercritical power units demand enhanced control efficiency and adaptability. To this end, this study introduces a novel model predictive hybrid PID control strategy that integrates PID with model predictive control (MPC), leveraging the operational characteristics of multi-loop systems. The proposed strategy adeptly marries the swift response of PID controllers with the foresight and optimization capabilities of MPC. A dynamic model of a supercritical unit is constructed using the subspace identification method. The model’s high precision is confirmed by its alignment with field data. Load change simulations demonstrate that the PID–MPC hybrid controller shows faster response times and more precise tracking capabilities compared to the feedforward-PID strategy. It achieves substantial improvements in the IAE index for three loops, with increases of 29.2%, 54.1%, and 57.3% over the feedforward-PID controller. An energy-saving performance analysis indicates that the proactive control actions of both the PID–MPC and MPC strategies lead to dynamic exergy efficiency and coal consumption rates with a broader range of dynamic process changes. The disturbance scenario simulation regarding the proposed controller achieves faster settling times and minimizes control deviation compared to the traditional controller.

Keywords: supercritical unit; coordination control; model predictive control; energy-saving analysis; rapid load change (search for similar items in EconPapers)
JEL-codes: Q Q0 Q4 Q40 Q41 Q42 Q43 Q47 Q48 Q49 (search for similar items in EconPapers)
Date: 2024
References: View references in EconPapers View complete reference list from CitEc
Citations: View citations in EconPapers (1)

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