Active power distribution network area multi-agent autonomous collaborative optimization system and method based on target cascade method

Abstract

The invention relates to an active power distribution network area multi-agent autonomous collaborative optimization system and method based on a target cascade method, and belongs to the technical field of power system optimization. The system comprises a main body layer, a node layer and a controlled unit layer which are connected in sequence, according to the ADN area autonomous collaborative optimization method, upper-layer excitation signals, loads, tie lines, fans, photovoltaics, storage batteries and other controlled units are regarded as a main body, power supply and demand balance in the main body is considered firstly, and full excavation of the main body scheduling potential is achieved. The invention further provides an ATC-based regional autonomous-overall collaborative optimization scheduling solving method, the ATC algorithm is introduced into a power distribution network-main body multi-level system, the decomposition of a global scheduling problem is realized by decoupling tie line power, a multi-main body optimization model is further constructed, and multi-main body collaborative control in the micro-grid is realized.

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