location:Home > 2024 Vol.7 Oct.N05 > Intelligent Control System for Thermal Power Plant Equipment Based on Improved PID

2024 Vol.7 Oct.N05

  • Title: Intelligent Control System for Thermal Power Plant Equipment Based on Improved PID
  • Name: William Smith
  • Company: California Miramar University,USA
  • Abstract:

    Design an intelligent control system for thermal power plant equipment based on improved PID with the aim of reducing manual intervention and enhancing the adaptability and robustness of intelligent control. The system collects operational data from different equipment in a thermal power plant through sensors, and transmits it to the upper computer in the control center through a CAN bus adapter card. The upper computer is connected to a logic operation unit, which is based on a traditional PID controller and introduces fuzzy rules to improve the traditional PID controller. At the same time, the hybrid frog leaping algorithm is used to optimize and solve the parameters of the improved PID controller. The optimal parameters are input into the improved PID controller, and the intelligent control quantity of the thermal power plant equipment is obtained through the improved PID controller without the need for manual adjustment of proportional, integral, and derivative parameters. The control quantity is transmitted to different equipment in the thermal power plant through relays, achieving intelligent control of the thermal power plant equipment. The experimental results show that the system has strong data communication and transmission capabilities for thermal power plants, and can effectively control the operation of thermal power equipment to reach standard values. At the same time, the overshoot of controlling thermal power plant equipment is relatively small, and the application effect is significant.


  • Keyword: Improving PID; Thermal power plants; Intelligent control of devices; CAN bus; Relay
  • DOI: 10.12250/jpciams2024090101
  • Citation form: William Smith.Intelligent Control System for Thermal Power Plant Equipment Based on Improved PID[J]. Computer Informatization and Mechanical System,2024,Vol.7,pp.1-6
Reference:

[1]YANG J Y, YAN W J, LUO L F, et al. Design and implementation of an intelligent monitoring system for three-station integrated wind-storage power plants [J]. Power System Protection and Control , 2022, 50 (17): 167-177.

[2]CHEN H Y, TAN B F, WU L, et al. Operation and control of the new power systems based on hierarchical clusters [J]. Proceedings of the CSEE, 2023, 43 (2): 581-595.

[3]GAO X P, ZHANG C H, SONG G B, et al. Control strategies of offshore wind power low frequency transmission system under asymmetric fault of low-frequency side [J]. Electric Power Automation Equipment, 2023, 43 (10): 160-166.

[4]SHI F J, FU T T, et al. Operation and control of new intelligent transformer in medium voltage distribution system [J]. Chinese Journal of Electron Devices, 2023, 46 (4): 1016-1021.

[5]LI J H, SONG C X, LAN F. Optimal control strategy for frequency response of isolated power system based on synergetic control [J]. Electric Power Automation Equipment, 2023, 43 (11): 133-140.

[6]ZHAO D J, GUO C Y, YE Q, et al. Reactive power decentralized cooperative control method for restraining AC overvoltage of wind farm via LCC-HVDC grid-connected system [J]. Electric Power Automation Equipment, 2024, 44 (1): 88-94.

[7]LUO L, LI Y H, LI Z X, et al. On-grid and off-grid coordinated control strategy of microgrid based on Van der Pol oscillator and PQ control [J]. Electric Power Automation Equipment , 2023, 43 (1): 130-139.

[8]FAN H L. Design of intelligent inspection system of power plant equipment based on deep learning [J]. Electronic Design Engineering, 2022,30 (1): 108-111+116.

[9]YANG X H, CHEN Y, FANG J F, et al. Turbine speed control in nuclear power plant based on improved PSO-PID controller [J]. Control Engineering of China, 2022, 29 (12): 2177-2183.

[10]JI J H, MIAO C Y, LI X G, et al. Design of fitness function for intelligent parameter tuning of PID controller on belt conveyor with PSO [J]. Journal of Mechanical Engineering, 2023, 59 (22): 444-456.

[11]JIANG L Y, WEI Q L, ZHANG F H, et al. PID controller parameter tuning based on improved particle swarm optimization algorithm [J]. Control Engineering of China, 2024, 31 (3): 470-477.

[12]LIU F C, GUO G W. Fractional order PID improved active disturbance rejection control for pneumatic variable load loading system [J]. Journal of Vibration and Shock, 2022, 41 (15): 116-121+129.

[13]ZHANG C, ZHANG Y. Double integral feedback PID load frequency control of new energy interconnected power systems [J]. Proceedings of the CSU-EPSA, 2022, 34 (10): 73-80.

[14]CHEN X, CAO T Q, DENG Y G. Fuzzy adaptive PID control based on improved tracking differentiator and feedforward [J]. Control Engineering of China, 2024, 31 (3): 553-559.

[15]WANG D, LI S Y. Two-degree-of-freedom internal model PID control for supply air temperature of constant air volume air handling unit [J]. Control Engineering of China, 2022, 29 (12): 2227-2234.


Tsuruta Institute of Medical Information Technology
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