基于SCADA系统的商业负荷能效管理

发布时间：2018-09-10 20:55

【摘要】：随着传统行业竞争的日益加剧，为了获得更多的利润，企业不得不加强成本的管理，作为成本支出中第三大项的电力成本支出越来越受到管理者的重视。特别是随着能源危机的暴发，国家加强宏观调控，对电力进行能效管理已经成为企业不容忽视的问题。目前，大部分的能效管理研究都是针对电力系统供电段，少数一些学者从建筑设计的角度阐述了商业建筑的节能方法，本文在总结和学习已有科研成果的基础上，，对商业负荷的能效管理进行了研究，提出建立一个以负荷预测模型为核心，采用统计过程控制方法设置报警模式的能耗监控平台。详尽、准确的负荷特性分析是提高负荷预测精度的必要前提，也是能耗监测平台可以正常运行的先决条件。因此，本文首先对商业负荷进行了特性分析，指出相对于电力系统负荷，商业负荷具有明显的商业周期性、基负荷小、波动性大的特点，并根据不同的周期性和波动性，将各子负荷划分为无规律大波动负荷、规律大波动负荷以及规律小波动负荷等三类。考虑到数据中存在噪声且噪声易淹没于负荷曲线的毛刺中，本文基于噪声和信号具有不同的传播频率假设，利用小波软阀值降噪法对历史数据进行降噪预处理。为提高大波动负荷的预测精度，本文采用了组合模型对负荷进行预测。首先，利用小波多分辨率分析法将降噪后的负荷分解为不同频率的分量；然后，利用支持向量回归模型对各分量分别进行回归预测，最后，各分量的预测值经小波重构后得到负荷的预测值。本文利用实例，验证了该模型的可行性和有效性。本文最后将应用于企业生产质量管控的SPC方法引入到商业负荷的能耗管控领域，与前文建立的组合模型相结合，构建了一个能耗监控平台。该监控平台可以实时对异常负荷进行预警，使能耗处于合理管控区域，为商业负荷的能效管理提供了一个切实可行的方法。
[Abstract]:With the increasing competition in traditional industries, in order to obtain more profits, enterprises have to strengthen the cost management. As the third largest item of the cost expenditure, the electric power cost expenditure is paid more and more attention by the managers. Especially with the outbreak of energy crisis, it has become an important problem for enterprises to strengthen macro-control and energy efficiency management. At present, most of the research on energy efficiency management is aimed at the power supply section of power system. A few scholars expound the energy saving methods of commercial buildings from the point of view of architectural design. In this paper, the energy efficiency management of commercial load is studied, and a monitoring platform of energy consumption based on load forecasting model and alarm mode is established by means of statistical process control method. Detailed and accurate analysis of load characteristics is a necessary prerequisite for improving the accuracy of load forecasting and is also a prerequisite for the normal operation of the energy consumption monitoring platform. Therefore, this paper firstly analyzes the characteristics of commercial load, and points out that compared with power system load, commercial load has obvious commercial periodicity, small base load and large volatility, and according to different periodicity and volatility, The subloads are divided into three categories: irregular large fluctuating load, regular large fluctuating load and regular small fluctuating load. Considering that there is noise in the data and the noise is easily submerged in the burr of the load curve, based on the assumption of different propagation frequency of the noise and the signal, the wavelet soft threshold de-noising method is used to pre-process the noise reduction of the historical data. In order to improve the forecasting accuracy of large fluctuating load, the combined model is used to forecast the load. Firstly, wavelet multi-resolution analysis method is used to decompose the noise reduction load into components with different frequencies. Then, the support vector regression model is used to predict each component separately. The predicted value of each component is obtained by wavelet reconstruction. The feasibility and validity of the model are verified by an example. In the end of this paper, the SPC method which is applied to enterprise production quality control is introduced into the field of energy consumption control of commercial load, and a platform of energy consumption monitoring is constructed by combining with the combination model established above. The platform can warn the abnormal load in real time, make the energy consumption in the reasonable control area, and provide a feasible method for the energy efficiency management of the commercial load.
【学位授予单位】：华侨大学
【学位级别】：硕士
【学位授予年份】：2013
【分类号】：TM73

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