Sold electricity quantity prediction method based on inventory capacities and business expansion characteristics

Abstract

The invention discloses a sold electricity quantity prediction method based on inventory capacities and business expansion characteristics. The method includes the steps that inventory capacity extraction is conducted according to the procedures of fuzzy extraction, business expansion mining clustering and fine calibration; the quantity of electricity generated by inventory loads is predicted by means of corrected inventory capacities; business expansion capacity utilization characteristics are extracted on the basis of a data statistics and data mining business expansion user electricity utilization growth curve, and the quantity of electricity generated by business expansion capacities of the ensuing year is predicted by means of the business expansion capacity utilization characteristics; the predicted value of the electricity quantity of the ensuing year can be obtained by adding the obtained quantity of the electricity generated by the inventory loads and the predicted quantity of the electricity generated by the business expansion capacities of the ensuing year. According to the method, starting from a power utilization source, capacity utilization characteristics and business expansion characteristics of different members of a selling market are extracted, internal reason and external driving factors of electricity selling market electricity quantity development and change are disclosed for dealing with the current economic situation which changes complicatedly, and scientific judgment bases are provided for the future electricity selling market development trend.

Description

technical field [0001] The invention belongs to the field of electric power, in particular to a method for predicting electricity sales based on stock capacity and characteristics of business expansion and installation. Background technique [0002] Forecasting is the basis, premise and basis for correct decision-making. Correct forecasting of regional electricity sales levels is an important basis for power companies at all levels to guide power system planning and operation. Power analysis and prediction needs to combine the past and present known economic situation, social development and electricity sales market conditions, through the analysis and research of historical data, to explore and grasp the internal relationship and development law of various relevant factors and electricity sales market, so as to The forecast of economic situation and social development during the planning period is used to calculate the future electricity demand. [0003] In fact, the rapid...

AI Technical Summary

Problems solved by technology

Its advantages are: less historical data is required, and the workload is small; the disadvantage is: it does not consider the factors of power changes, only focuses on data fitting, and does not deal with regularity enough, and is only suitable for short-term predictions with relatively uniform power changes Happening

The advantages are: less load data required for modeling, no consideration of distribution laws, no consideration of changing trends, convenient calculation, high short-term prediction accuracy, and easy inspection; The worse the accuracy

Its disadvantages are: limited by the total amount of knowledge accumulated in the database, poor adaptability to emergencies and changing conditions, it is difficult to obtain definite long-term forecast results

[0015] Through the analysis in the previous section, it is found that in the past few decades, many experts have researched and explored the analysis and prediction methods of the electricity sales market. These studies often focus on the complexity of the algorithm, and relatively ignore the in-depth analysis of the regularity of the electricity sales market itself.

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