Based on the present problems existed in electric load characteristic statistical indexes, a correlation analysis method for load characteristic statistical indexes is proposed in this paper. Low-level correlation indexes are extracted by using correlation analysis, then the linkage analysis theory in econometrics is applied and the load characteristic indexes are analyzed by using vector auto-regression model. The Synchronous movement trend and causal leading relationship among electric load characteristic indexes are confirmed by co-integration test and granger-casualty analysis. The purpose of this paper is to help power decision makers grasp the alteration situation of load characteristic indexes comprehensively and analyze correlation indexes accurately, so it can enhance the monitoring, forecasting and early-warning function of electric system.
The demand for electric power data is more and more widely, and put forward higher requirements to the quality of statistical data. This paper combined with the features of electric power data. Evaluate data quality from the accuracy, completeness, uniqueness, consistency, accuracy, efficiency and timeliness seven aspects. And put forward the specific evaluation methods of each evaluation index. Then build a whole data quality evaluation process on this basis, quantitative analysis the data in the database, to acquaintance the data quality condition.
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