| Accurate and timely power load forecasting results can not only provide calculation basis for power project investment,but also provide data support for optimal operation decision of power grid,only by relying on more accurate electricity forecasting can the construction and safe operation of green,low-carbon new power system requirements,avoid serious power demand and power production imbalance.Power demand presents different development trends in different time periods,with complex changes,random occurrence and unpredictable characteristics,which brings great challenges to the annual power consumption forecast of provincial power grid.How to find out the internal relationship between the changing trend of electric power and various related factors is a hot research direction for the electric power system forecasters.In this paper,aiming at the problems of few forecasting and forecasting models for power consumption of Jiangxi provincial power grid,such as low information level and low accuracy,the regression model and grey system model of various data sources are adopted,relying on the information platform,based on the prediction of power consumption of Jiangxi provincial power grid and the analysis of its power consumption characteristics,the main research results are as follows:(1)the economic operation,the development of key industries,the climate and temperature conditions,and the development and change of power consumption,load and load characteristics of Jiangxi power grid are analyzed,the influence factors of electric quantity variation trend are summarized,and the multi-factor characteristics of electric quantity variation are verified.The research results show that the electricity consumption of Jiangxi power grid is affected by the industrial process characteristics of 24-hour continuous production in key pillar industries such as Non-ferrous metal,iron and steel and rare earth smelting in Jiangxi province,and the base load keeps increasing rapidly,drive the province’s industrial power consumption continues to rise.The load and power consumption of Jiangxi power grid are greatly affected by the meteorological conditions,resulting in the annual power consumption of Jiangxi power grid shows a rapid growth from July to August.(2)the database indexes of load,electricity,economy,weather and other factors that affect electricity forecast are designed,considering the influence of relevant factors,the extended grey system forecasting model and many kinds of regression analysis forecasting models are constructed,and the information platform is designed to carry out the power grid consumption forecasting in time and efficiently.(3)using the historical data of 2012-2020,the annual electricity consumption of Jiangxi power grid is analyzed and forecasted,the prediction model is optimized by analyzing the prediction results from different angles,such as error comparison,actual data check and so on.The results show that it is advantageous to analyze the trend of provincial power consumption from different influencing factors by using various data sources and different models,in particular,the application of mathematical model algorithm through the information platform can make the provincial power grid annual electricity forecast value closer to the actual value of the grid,forecasting more accurate and faster.(4)the characteristics of Jiangxi power grid,such as peak load curve,peak-valley difference,average daily load and growth rate of regional power consumption,are studied.The results show that,with the further development of household electrification and the rapid development of commercial center,the load of Jiangxi power grid presents the characteristics of peak load to maintain high-level operation;Compared with other provinces,the duration of peak power consumption period of Jiangxi provincial power grid is shorter,and the difference between peak load and trough load has been increasing,the load of Jiangxi power grid is kept in high position,and the annual load curve presents double peak phenomenon Different regions have different electricity consumption structure,and the growth of electricity consumption is not balanced,but the growth potential of electricity consumption is huge. |