Non-chronological quantitative evaluation method of new energy consumption capacity based on probability and statistics theory

Abstract

The invention discloses a non-sequential quantitative evaluation method of new energy consumption capacity based on the theory of probability and statistics, comprising the following steps: step 1, establishing a non-sequence calculation model of new energy consumption capacity based on the system to be evaluated; step 2, calculating the new energy Probability distribution of curtailment power; step 3, calculate the new energy curtailment rate λ, and complete the quantitative evaluation of new energy consumption capacity through the new energy curtailment rate λ. The quantitative evaluation method of the present invention can provide guidance for the actual work of scheduling operation; the use of convolution calculation to replace the traditional timing simulation process can avoid the repeated sampling and calculation process in the traditional Monte Carlo simulation method, without affecting the accuracy. , which greatly improves the calculation efficiency, and provides an effective way to quickly evaluate the new energy consumption capacity of the system.

Description

technical field [0001] The invention belongs to the field of power grid control, and in particular relates to a non-sequential quantitative evaluation method for new energy consumption capacity based on probability statistics theory. Background technique [0002] At present, scholars at home and abroad have carried out a series of research on the capacity of new energy consumption. However, the existing research results are difficult to provide reference for the actual power grid regulation and operation. The main reasons are as follows: [0003] First, most of the existing research focuses on the construction planning of new energy installed capacity and its optimal power generation plan with conventional units, and how to quantify the impact of factors such as the peak-shaving rate of conventional units, the proportion of self-provided power plants, and the DC transmission plan in actual operation. There are few studies on energy consumption capacity, and it is impossible ...

AI Technical Summary

Problems solved by technology

[0003] First, most of the existing research focuses on the construction planning of new energy installed capacity and its optimal power generation plan with conventional units, and how to quantify the impact of factors such as the peak-shaving rate of conventional units, the proportion of self-provided power plants, and the DC transmission plan in actual operation. There are few studies on energy consumption capacity, and it is impossible to make guiding suggestions for the practical application of power dispatching;

[0004] Second, most of the algorithms proposed in current research are based on the timing simulation method based on Monte Carlo simulation. In actual calculation, repeated sampling and timing simulation are time-consuming and inefficient

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