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Research on Heat Load Forecasting and Optimization of Operation and Regulation of District Heating System

Author: WangQingFeng
Tutor: LinYiQing
School: Shandong University
Course: Engineering Thermophysics
Keywords: Central heating Operation Regulation Nonlinear Programming Thermal load forecasting Artificial Neural Networks
CLC: TU995
Type: Master's thesis
Year: 2010
Downloads: 330
Quote: 10
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Abstract


Urban central heating has become a major form of northern China in winter heating, and rapid development. Urban central heating systems heat consuming large number of lower taste, usually below 120 ℃ low heat, but mainly in high-grade primary energy supply, it has a large potential for energy saving. Especially in the heating system running, through the implementation of the Operation Regulation, so that the system is running optimally, and improve the economic efficiency of the heating system and energy saving, is the urgent need to address the problem of heating the field, and the associated theoretical and applied research has been concerned. Quality, use of a heating network in the city's central heating system, and tune this way of regulating the status quo, the lowest energy costs to run the constraints of the operating characteristics of the heating pipe network optimization objectives, the establishment of water flow and supply and return water temperature to the the variable central heating system a heating network operating energy costs equation by solving the equation to get the guidance of a heating network quality, the amount of adjustment of the optimal operating parameters. Analysis using nonlinear programming method provides ideas and numerical methods to analyze and solve the equation, and select the appropriate method in the different stages of solving equations established software system used to solve the equations. Analysis of the calculation results prove subject operating energy cost equation in the guidance of the central heating system, a heating network quality, volume adjustment, adjusted than centralized quality with better energy efficiency, at the same time confirmed with nonlinear programming solving method developed software system running energy costs of heating network equation than using the Matlab toolbox and step method efficiency higher, more accurate results. Become a central heating system running regulating the premise and basis of the actual heat load forecast for the city's central heating system, taking into account the heating system in the actual operation of the process of heating heat load many influencing factors between nonlinear and dynamic relations are characterized by the use of artificial neural network technology to achieve the two heat exchanger of a district station heat load forecasts, proposed to establish the structure and parameters of the BP neural network method, and the development of software systems engineering examples heat load, forecast results show that BP neural network able to obtain high accuracy to meet the general application requirements for thermal load forecasting. This article select Visual C # programming language and the Microsoft Visual studio 2008 program design platform to achieve the above algorithm and program them as have the significant characteristics, such as oriented object technology, graphical user interface and software deployment, etc., after the software system of follow-up R \u0026 D good basic framework.

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CLC: > Industrial Technology > Building Science > Municipal Engineering > Urban central heating
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