收稿日期: 2015-05-07
修回日期: 2015-06-23
网络出版日期: 2016-05-30
Remote Intelligent Monitoring Strategy of Heat-Supply Network Based on Kingview
Received date: 2015-05-07
Revised date: 2015-06-23
Online published: 2016-05-30
针对集中供热系统中热网的耦合性、非线性、滞后性等控制难点,结合节能环保的理念,为换热站设计了基于Kingview的热网远程监控系统.依托Kingview和现场PLC联合开发高级控制策略,实现远程监控中心对小区供暖系统温度、压力、流量、阀门开度参数的现场采集和实时调节,提升了供暖系统的控制精度与供暖效果.采用fuzzy-PID控制、温度补偿控制、热负荷预算、无线远传等关键技术,实现了热力水利工况的良好运行.构建优化目标函数及非线性规划算法,得出一次热网参数的最优运行解,提升能源利用率与系统稳定性.经过一年运行表明,该设计增强了热网控制系统的智能化程度,提高了能源利用率,对集中供热系统质量与并调具有实际指导意义.
隋修武, 余保付, 葛辉, 田松 . 基于Kingview的热网远程智能监控策略研究[J]. 应用科学学报, 2016 , 34(3) : 352 -360 . DOI: 10.3969/j.issn.0255-8297.2016.03.012
To deal with control difficulties of coupling, nonlinearity and hysteresis in a centralized heat supply system of a heat-supply network, a remote monitoring system of heat-supply network based on Kingview is designed. It combines the concepts of energy conservation and environmental protection. Advanced control strategies are developed based on Kingview and a local PLC to realize site collection of district heating system parameters such as temperature, pressure, flow and valve opening. Thus accuracy of the heating control and quality of heating are improved. It is possible to achieve a good running condition of thermal water conservancy via fuzzy-PID control, temperature compensation control, thermal load budget, wireless remote, and other techniques. An optimization objective function and a nonlinear programming algorithm are established, and optimal operation solutions obtained with heating network parameters that can improve energy efficiency and system stability. Operation of a whole year shows that the design enhances the system's intelligent control, and has excellent energy efficiency. It is significant in adjusting quality, improving energy efficiency, and raising operation and management standards of urban central heating systems.
Key words： load budget; remote monitoring; temperature compensation; Kingview; fuzzy-PID
[1] 刘文琦,杨建华,林艳. 集中供热网智能控制方法研究[J]. 大连理工大学学报,2004,44(3):563-567. Liu W Q, Yang J H, Lin Y. Study on district heating network intelligent control[J]. Journal of Dalian University of Technology, 2004, 44(3):563-567. (in Chinese)
[2] Antoine C T. Conception et optimisation de systemes energetiques hybrides pour communautes durables[D]. Montreal:Ecole Polytechnique, 2012.
[3] Muhammet K. Determination of energy saving and optimum insulation thicknesses of the heating piping systems for different insulation materials[J]. Energy and Buildings, 2014(69):278-284.
[4] Mahlia T M I, Taufiq B N, Ismail H M, Masjuki H H. Correlation between thermal conductivity and the thickness of selected insulation materials for building wall[J]. Energy and Buildings, 2007(39):182-187.
[5] Chou H. Optimization interior area thermal resistance model to analyze the heat transfer characteristics of the insulation pipe with arbitrary shape[J]. Energy Conversion and Management, 2007(44):2915-2939.
[6] Mattias V, Jan D. A method for the simulation and optimization of district heating systems with meshed Networks[J]. Energy Conversion and Management, 2014(89):555-567.
[7] Hariharan G, Dragoljub K. Economic optimization of combined cycle district heating systems[J]. Sustainable Energy Technologies and Assessments, 2014(7):91-100.
[8] Pawel P, Andrzej Z. Complex analysis of the optimal coefficient of the share of cogeneration in district heating systems[J]. Energy, 2013(62):12-22.
[9] Ning J, Shelleyb D J, Doyleb S, Smith R. Heat exchanger network retrofit with a fixed network structure[J]. Applied Energy, 2014(127):25-33.
[10] Paola B, Dario R. Support vector regression for link load prediction[J]. Computer Networks, 2009(53):191-201.
[11] Chen L, Zhang Q L, Qi W G, Li J. Heat load prediction for heat supply system based on RBF neural network and time series crossover[C]//Proceedings of the 7th International Conference on Machine Learning and Cybemetics, 2008:784-788.
[12] 周守军. 基于管网动态模型的城市集中供热系统参数预测及运行优化研究[D]. 济南:山东大学,2012.
[13] Andrzej Z, Pawel G. Optimal coefficient of the share of cogeneration in district heating systems[J]. Energy, 2012(4):220-227.
[14] 齐晓军,田海. 串级模糊控制器在换热站监控系统中的设计[J]. 电气传动,2015, 45(1):58-63. Qi X J, Tian H. Design of the cascade fuzzy controller in a heat exchange station monitoring system[J]. Electric Drive, 2015, 45(1):58-63. (in Chinese)
[15] 江丛兴. 一种集中供热热网采暖温度补偿调节方法[P]. 黑龙江:CN102252364A, 2011-11-23.
[16] Traian A, Jan E, Visa K. Conjugate gradient algorithm for optimization under unitary matrix constraint[J]. Signal Processing, 2009(89):1704-1714.
[17] 田海,刘辉,张冰. 换热站智能控制系统的设计与实现[J]. 测控技术,2013(8):67-74. Tian H, Liu H, Zhang B. Design and implementation of intelligence control system for heatexchanging station[J]. Measurement & Control Technology, 2013(8):67-74. (in Chinese)
[18] Wang Z Y, Guo C X Jiang Q X. A fault diagnosis method for transformer integrating rough set with fuzzy rules[J]. Transaction of the Institute of Measurement and Control, 2006(28):243-246.
/
| 〈 |
|
〉 |
