New energy uncertainty planning method considering typical scene tolerance

Abstract

The invention relates to a new energy uncertainty planning method considering typical scene tolerance, and the method comprises the following steps: S1, carrying out the calculation according to the wind speed and illumination intensity data, and obtaining an RDG daily output curve sample; S2, randomly selecting a curve from the sample as a first curve in the initial center; S3, constructing an initial center; S4, calculating Euclidean distances from the remaining curves to K clustering centers , dividing the remaining curves into the corresponding clustering centers, and generating a K-classcurve set; S5, updating K clustering center curves; S6, judging whether a convergence condition is met or not; S7, adopting different K value clusters, calculating contour parameters of correspondingresults, and selecting an optimal cluster K value; S8, constructing a planning objective function, and establishing constraint conditions of the objective function; and S9, obtaining an optimal planning scheme of the renewable distributed energy by using a multi-objective optimization algorithm. The method guarantees that the planning result is suitable for as many operation scenes as possible.

Description

technical field [0001] The invention relates to the field of new energy, in particular to a new energy uncertainty planning method considering tolerance of typical scenarios. Background technique [0002] With the traditional fossil energy crisis and environmental pollution becoming more and more prominent, accelerating the use of distributed renewable energy (Renewable Distributed Generation, RDG) grid-connected technologies such as wind energy and solar energy has become the basic consensus and response strategy of all countries in the world. Distributed energy sources such as wind and light are affected by geographical location, natural environment, climatic conditions and other factors, and their output characteristics often have strong randomness and volatility. [0003] At present, the distribution network planning method mostly considers the optimized voltage offset level and the network loss level of the distribution network system, and the optimal scheme obtained by...

AI Technical Summary

Problems solved by technology

[0004] At present, most of the multi-objective optimization of distributed renewable energy only considers the economy and safety in a single scenario, and lacks certain considerations for the applicability of the optimization scheme in multiple uncertain scenarios, resulting in the optimal solution may only be Applicable to some scenarios, cannot

Images