Two-stage robust optimization power system operation flexibility capacity evaluation method

Abstract

The invention relates to the technical field of power system operation control methods, in particular to a two-stage robust optimization power system operation flexibility capacity evaluation method, which comprises the following steps of: constructing a scheduling model of an adjustable robust interval, and setting constraint conditions of the scheduling model of the adjustable robust interval; then improving the scheduling model of the adjustable robust interval, setting a corresponding constraint condition, finally carrying out linear conversion on the two models, and solving by adopting a CCG algorithm to obtain a feasible region and an optimal solution of the power system. The method can effectively evaluate the operation flexibility capacity of the system, and has the following advantages: (1) good economy: the method can effectively reduce the operation cost of the system, reduce the conservative property of the scheduling decision, and further improve the flexibility and economy of the scheduling decision of the system; and (2) high scheduling performance: the flexibility of pre-scheduling of the system reserve capacity is evaluated through wind curtailment and load shedding, and the flexibility of system operation scheduling is effectively improved.

Description

technical field [0001] The invention relates to the technical field of power system operation control methods, and relates to a two-stage robust optimization power system operation flexibility capacity evaluation method. Background technique [0002] In order to reduce greenhouse gas emissions and achieve sustainable development, the use of renewable energy, such as wind and light, as a non-polluting and clean energy, has been vigorously promoted around the world. The dual-carbon target proposed by China requires large-scale renewable energy. Energy participation can only be achieved. The grid connection of highly intermittent renewable energy has led to the transformation of the power system from a deterministic system to a strongly uncertain system. This transformation has led to new challenges in the operation of the power system. Slope and system backup requirements, improving system operation flexibility has become a current research hotspot. In the study of flexibili...

AI Technical Summary

Problems solved by technology

In the study of flexibility, the uncertainty of renewable energy output is firstly modeled. The main modeling methods are stochastic optimization method and robust optimization method. The former stochastic optimization method describes the output of renewable energy with a deterministic probability distribution. characteristics, it has good economy in application, but it is difficult to solve and the scene is complex, which restricts the wide application of stochastic optimization method

Images