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Load Characteristic Analysis And Load Forecast Research Of Chongqing Changshou Power

Posted on:2017-10-24Degree:MasterType:Thesis
Country:ChinaCandidate:Y WangFull Text:PDF
GTID:2322330533950036Subject:Electrical engineering
Abstract/Summary:PDF Full Text Request
For a long time, the power load forecasting is a very important topic in the research of power market, especially in recent years, the scale of power grid is constantly expanded, and the factors that need to be considered in the study of power grid load are also increasing. Increase in summer season, air conditioning load, power consumption reached the maximum power into the period of Fenggu in recent years; with the development of industry, industrial consumption is also increasing; some unpredictable and recurring natural disasters, causing many unforeseen difficulties on the measurement of power load; and from the statistics the grid data in recent years, the power load rate and utilization hours are reduced in different degree, so that the grid safety and economic operation difficulties with our further increase. Want to control our country investment in power grid project, improve efficiency of power generation equipment and fuel maximum, between the hydropower and thermal power generation in accordance with a certain proportion of redivides, to save energy and reduce pollution emission targets, so the analysis and forecast of load work is very important for us; the large electricity enterprise,benefit is very much, on the one hand above the power supply equipment to reduce investment, on the other hand can also cut the peak of Pinggu implementation of Power Grid Corp, and because the peak and valley price,so that large electricity companies can arrange the production work, can also reduce production costs; finally for ordinary people, the power load forecasting can ensure that users in the peak use of high quality power and ensure their With the demand of electricity, and then the residents of the home electrical equipment service life has also been improved.One of the foundation and guarantee of power system load forecasting is scientific and accurate power sector to make the right decision, it will have the relevant departments to formulate plans for power system of power economy reasonable, effective cost control; according to the results of data grid, the development of the power planning scheme is powerful for relevant departments to provide reliable data sources; very good management the electricity to the plan, needs analysis of the situation, to promote the marketization of power industry; conducive to the dispatching department of power ahead of schedule, not only conducive to the power of public revenue, and enhance efficiency is also a great help; to ensure the stable operation of the power grid is also very powerful.This paper presents a method for predicting the load, which is a foundation of the grey model, through the continuous improvement of theprediction that the preferred way to the weighted index, breaking the original load arrangement, then study by day types and weather conditions for the influence of bus, based on the grey correlation degree the theory is based on the feature vector, then find some optimal similar day, finally the historical load samples of the selected on the bus load. According to the distance of the small, near the large law, in the selection of load samples, select the relatively large impact of the bus to the nearest principle, and vice versa. This method not only makes full use of the useful information of the data in the sample, but also reduces the random nature of the data in the sample, and it also can weaken the influence of the abnormal value. Through the calculation of case study in a county of Chongqing city power supply company, fully demonstrated the power load classification is practical and scientific, and also to a certain extent,reflect the proposed load forecasting method, has the very high practical benefits.
Keywords/Search Tags:Load forecasting, load forecasting system, networking technologies, gray model, load characteristics analysis
PDF Full Text Request
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