Active power distribution network frame planning method on the basis of bi-level planning

Abstract

The present invention discloses an active power distribution network frame planning method on the basis of a bi-level planning. The active power distribution network frame planning method on the basis of the bi-level planning comprises the following steps: the first step, bi-level planning model constitution; the second step, gene code; the third step, formation of an original scheme; the fourth step, individual good and bad evaluation; the fifth step, genetic operation; and the sixth step, selection of an optimal scheme. According to the invention, a model is established about an active power distribution network frame planning problem on the basis of a bi-level planning concept, and an improved genetic algorithm is used for solution. Compared with a traditional active power distribution network frame planning method, the bi-level planning concept and the improved genetic algorithm are led in the active power distribution network frame planning method on the basis of a bi-level planning to solve problems. In respect of modeling, the bi-level planning model adopted by the invention is converted to a bi-level planning problem, namely an upper layer planning problem is the construction of a line and the lower layer planning problem is minimum active power output excised amount of distributed generation under the network frame.

Description

[0001] technical field [0002] The invention relates to a network frame planning of a power distribution system, in particular to a method for planning an active distribution network network frame based on double-layer planning. Background technique [0003] Two-level programming is a planning and management problem with two levels of systems. The upper-level decision-making only guides the lower-level decision-makers through its own decisions, and does not directly intervene in the lower-level decision-making; while the lower-level decision-making needs to take the upper-level decision as a parameter. make decisions within the domain. [0004] Bi-level programming is much more complicated than single-level programming, mainly in three aspects: nonlinearity, non-convexity, and non-uniqueness of the underlying response. The two-level planning is hierarchical and the upper and lower levels are mutually restricted and closely integrated. The characteristics are as follows: ...

AI Technical Summary

Problems solved by technology

The first model does not require the lower-level planning to have a unique optimal solution for each given upper-level decision variable, because even though the lower-level planning has different optimal solutions, the corresponding optimal values ​​are the same, and the upper-level planning The problem is always deterministic; in the second model, the lower-level planning requires a unique optimal solution for each upper-level decision variable. If there are multiple different solutions to a sub-programming problem, it may make the upper-level planning problem uncertain. Sexual issues, which limit the scope of application of the model

Images