Design And Application Of Power Market Analysis And Forecast System For Big Data

With the deepening of the electricity market reform in our country,electric power industry encountered new difficulties.After the reform,power system in each member became different interest subjects,the market economy are equally important as safety.How to realize the economic operation of electric power system optimization as much as possible?In addition to the market rules to formulate corresponding measures,consider to the various members of the market to provide some information on the condition of market prediction,in order to make the whole electricity market safe,stable and smooth operation,reduce caused by a lack of market conditions,also facilitate each member decision reasonably,benefit the market maximization.In this article,through big data application in the power market forecasting and analysis research,provide power market forecasting modeling guidance,issue the forecast trend calculation model,analysis forecast domestic electricity load as the company posted index prediction information,strengthen information sharing between the planning?operation and marketing,reduce the costs caused by repeated construction,reduce workload.this article also effectively improve the timeliness,reliability of the power market forecasting data processing and accuracy,and increase the use value of the data,provide a more accurate prediction of supporting data for the company leadership and management,improve the efficiency of the electric power enterprise service society.This article mainly from two aspects.First of all,the article put forward on the basis of the electric power big data platform to build electric power market analysis forecast system,using Hadoop as the core of data acquisition,distributed storage,distributed processing and other big data technology ecological system,realize the centralized management of data resources,real-time monitoring and visualization management.Secondly,this article selects based on the temperature change of residential electricity consumption habits theme as a typical application of data mining,realizes the daily maximum load and temperature of the correlation analysis,correlation analysis of residents' average daily power consumption and temperature,to master the trend of the load with the temperature change and urban and rural areas based on the temperature difference of electricity consumption,provide auxiliary analysis and decision-making for the orderly electricity measures.