The most popular urban power grid focuses on load

2022-07-31
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Abstract: to carry out the power construction and transformation in rural counties, it is necessary to do a good job in planning and design, and doing a good job in load forecasting is the primary task of doing a good job in planning and design. Only by mastering accurate and reliable load forecasting data can the power construction and transformation be carried out reasonably. Power load forecasting is the basic work in power planning, and its accuracy directly affects the quality of power planning

key words: urban power load forecasting to carry out the power construction and transformation of rural counties, we must first do a good job in planning and design, and doing a good job in load forecasting is the primary task of doing a good job in planning and design. Only by mastering accurate and reliable load forecasting data can we reasonably carry out the power construction and transformation. Power load forecasting is the basic work in power planning, and its accuracy directly affects the quality of power planning. Methods and analysis of electric load forecasting are divided into two categories, namely, comprehensive forecasting and single forecasting. Comprehensive forecasting is directly used to forecast the total power demand and maximum load of the whole or the whole region. This kind of prediction is based on the proportional relationship between electric power and the national economy and the degree of adaptation. The forecast is rough and prospective. It is mainly used for medium - and long-term forecasts. The single prediction is a more detailed prediction, which will generate samples due to the heat generated by friction. The technical conditions meet the relevant provisions of gb5137.1 standard. The synthetic method is used to search for more accurate data for near-term and short-term prediction. (1) Unit consumption method of industrial output value: the unit consumption method, i.e. the unit product power consumption method, is to obtain the total power consumption of the total output of a certain product through the average unit product power consumption of a certain product and the output of the product. The unit consumption method requires a lot of detailed statistical work. (2) Electricity elasticity coefficient method: electricity elasticity coefficient is the ratio between the average growth rate of electricity and GDP. According to the growth rate of GDP, The total electricity consumption at the end of the planning period can be obtained by combining the power elasticity coefficient. The TORLON Pai with wear resistance grade has no comparable performance in the lubricating environment. Like the unit consumption method, the power elasticity coefficient method needs to do detailed statistical work. (3) Zonal load density method: the zonal load density prediction method firstly divides the area to be predicted into multiple functional areas according to the development in recent years, economic development objectives and power planning objectives, then forecasts each functional area with the load density method, and finally adds them to obtain the total predicted power consumption. (4) Time series method: time series analysis method is a method to find the law of load change with time based on the past load statistical data, and establish a time series model to infer the future load value. Its basic assumption is that the law of load change in the past will continue to the future, that is, the future is the continuation of the past. (5) Correlation analysis method: correlation analysis method is a method to find the causal relationship between load and influencing factors, establish correlation analysis model, and predict through statistical analysis and processing of observed data. It is characterized by decomposing the factors affecting the prediction object, and estimating the future quantitative state of the prediction object in the investigation of the changes of various factors. (6) Per capita electricity index conversion algorithm: the per capita electricity index conversion algorithm refers to selecting - regions similar to the region in terms of human and geographical conditions, economic development and power consumption structure as the comparison object. By analyzing and comparing the past and current per capita electricity indexes of the two regions, the predicted value of per Capita Electricity in the region is obtained, and then the predicted value of total electricity consumption is obtained in combination with population analysis. 2 pay attention to the collection, arrangement and analysis of load forecasting data. The accuracy of load forecasting is not only related to the forecasting method, but also directly related to the mastered data and its analysis and application. Great importance must be attached to planning. 2.1 collect accumulated data (1) past and present data: County and township production power: focus on collecting industrial and agricultural production plans and development data, power consumption, output value, unit power consumption, load quota, natural growth rate, elasticity coefficient, etc. At the same time, determine the load coefficient, simultaneous coefficient and maximum load utilization hours involved in load forecasting. Domestic power consumption of counties and townships: collect classified power consumption and power load. For the power consumption of lighting and household appliances, a sampling survey shall be conducted to determine the automatic shutdown protection for the number of existing and developed;. (2) Development data: collect the national economic development objectives (gross industrial and agricultural output value, etc.) in the local forecast level year, rural electrification requirements, users' power utilization applications, local economic development intentions and data on the development trend of required power, etc. 2.2 sorting out the analysis data mainly analyzes whether the growth of urban and rural domestic power consumption is compatible with the income of urban and rural residents. For the measured load data of industries, substations, lines and so on, sort out and draw various daily and annual load curves, and analyze the change rules of daily and annual load rates. By using the above methods, we can better solve the load and electricity forecast in the near future and future years in the planning, so that the planning is based on a more accurate basis, we can correctly establish the power construction and transformation projects, and define the long-term, medium-term and short-term goals. As far as the current focus is concerned, the power construction and transformation in rural counties should focus on load forecasting

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