水泥生产电耗预测与用电负荷优化调度技术研究

发布时间：2018-03-18 17:02

本文选题：水泥生产　切入点：电耗预测　出处：《天津理工大学》2015年硕士论文　论文类型：学位论文

【摘要】：能源消耗问题是制约企业发展的关键所在,更是关乎国民经济与社会可持续发展的重大问题。建材工业能耗约占全国工业总能耗的13%,而其中水泥制造业的能耗量高达建材工业能耗总量的76%左右。可见,对于水泥企业能耗管理问题的研究刻不容缓。水泥生产的主要消耗能源是煤炭和电力,随着生产工艺以及自动化程度的不断提高,水泥企业的煤耗指标已呈逐年下降的趋势,但水泥综合电耗仍呈递增趋势,企业用电费用开支居高不下。针对上述情况,本文以山东某水泥厂为研究对象,通过有效的数据分析和预测技术手段,建立电耗预测模型,达到能源的合理配置和利用,以此为基础,建立用电负荷调度模型,进行峰谷平用电负荷调度,在保证产量前提下,达到日用电成本最低。通过本课题的实施,实现安全、优良供能,最终达到提高整体电能利用效率、降低消耗、节约成本的目的。首先,本文从实际出发,在分析了我国水泥行业发展现状后,深入研究了水泥生产的工业流程,总结出电耗分布及单位指标。此外,针对水泥企业能耗数据过多且复杂等特点,研究了水泥企业中的能源管理系统,尤其是能源数据采集的原理与实现,为下文的建模做铺垫。其次,运用主成分分析法解得几个影响水泥生产电耗的关键因素,有效表征和替代了原始的众多影响因素,降低了模型的复杂度。同时提出了基于改进多元非线性算法的水泥电耗预测模型,提高了模型的预测精度。之后,建立基于分时电价的水泥企业用电负荷优化调度模型,利用Matlab平台的模式搜索法、单纯形法和遗传算法进行了线性规划问题的求解,并对比了三种方法的优劣。最后,根据之前所得的电耗预测值对未来全厂各工段及主要耗电设备进行峰谷平用电调度,制定出各个主要耗电环节设备的运行时刻表。本文通过算例分析验证了电耗预测模型及改进算法的有效性,使电耗预测值与实际值有较高的吻合度,对于水泥厂的电耗预测管理具有重要的参考意义。此外还验证了用电负荷优化调度模型的正确性和Matlab求解线性规划算法的优越性。从而将线性规划应用于辅助高耗能企业优化分配资源方面,降低了用电成本,具有较强的实用性。
[Abstract]:The problem of energy consumption is the key to restricting the development of enterprises. The energy consumption of the building materials industry accounts for about 13 percent of the total energy consumption in the national industry, and the energy consumption of the cement manufacturing industry is about 76% of the total energy consumption of the building materials industry. It is urgent to study the problem of energy consumption management in cement enterprises. The main energy consumed in cement production is coal and electricity. With the continuous improvement of production technology and automation, the coal consumption index of cement enterprises has been decreasing year by year. However, the comprehensive power consumption of cement is still increasing, and the expense of electricity consumption of enterprises is high. In view of the above situation, this paper takes a cement plant in Shandong province as the research object, and establishes the forecasting model of electricity consumption through effective technical means of data analysis and prediction. On the basis of the reasonable allocation and utilization of energy, the model of power load dispatching is established, and the peak and valley power load dispatching is carried out. Under the premise of ensuring the output, the daily electricity cost is the lowest. Through the implementation of this subject, the security is realized. In order to improve the efficiency of electric energy utilization, reduce consumption and save cost, this paper analyzes the present situation of cement industry in China, and deeply studies the industrial process of cement production, based on the analysis of the present situation of cement industry in China. In addition, the energy management system in cement enterprises, especially the principle and realization of energy data acquisition, is studied in view of the characteristics of excessive and complex energy consumption data in cement enterprises. Secondly, the principal component analysis method is used to solve several key factors that affect the power consumption of cement production, which effectively represent and replace many original factors. The complexity of the model is reduced. At the same time, the prediction model of cement power consumption based on improved multivariate nonlinear algorithm is proposed, which improves the prediction accuracy of the model. After that, the optimal dispatching model of electric load of cement enterprise based on time-sharing price is established. The linear programming problem is solved by using the pattern search method of Matlab platform, simplex method and genetic algorithm, and the advantages and disadvantages of the three methods are compared. According to the predicted value of electricity consumption obtained before, all sections and main power consuming equipment of the whole plant in the future will be scheduled for peak-valley flat power consumption. In this paper, the validity of the power consumption prediction model and the improved algorithm are verified by the example analysis, which makes the predicted value of electricity consumption have a high consistency with the actual value. It also verifies the correctness of power load optimal dispatching model and the superiority of Matlab in solving linear programming algorithm. Thus, linear programming is applied to auxiliary high level. With regard to the optimal allocation of resources by energy-consuming enterprises, The utility model reduces the cost of electricity consumption and has strong practicability.
【学位授予单位】：天津理工大学
【学位级别】：硕士
【学位授予年份】：2015
【分类号】：TQ172.6;TM73

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