Multi-target random dynamic economic dispatch method based on scenario decoupling and asynchronous iteration

Abstract

The invention discloses a multi-target random dynamic economic dispatch method based on scenario decoupling and asynchronous iteration. The method herein includes the following steps: 1. assigning relevant computing parameters; 2. establishing a multi-target random dynamic economic dispatch model; 3. using scenario decoupling and asynchronous iteration to improve the interior point method to resolve the multi-target random dynamic economic dispatch model. According to the invention, the method uses the scenario method translates the problem of multi-target random dynamic economic dispatch to the problem of large-scale multi-target deterministic dynamic economic dispatch, translates the problem of large-scale multi-target deterministic dynamic economic dispatch to the problem of a series of large-scale single object non-linear planning by means of the normal boundary cross method, conducts resolution by using the nonlinear primal-dual interior point algorithm, and avoids the generation of dense matrix, such that the matrix in the entire computing process is sparse, is better compatible with economy and environmental protection in operating a power grid, and therefore is a dispatch plan with higher operation benefits.

Description

technical field [0001] The invention relates to a multi-objective random dynamic economic scheduling method based on scenario decoupling and asynchronous iteration for day-ahead operation scheduling of provincial power systems, and belongs to the technical field of electrical engineering. Background technique [0002] The dynamic economic dispatch problem after the wind farm is connected to the power system is actually a stochastic optimization problem. Early research in this area utilized chance-constrained models and robust optimization models. Chance-constrained models are not precise enough considering randomness, while robust optimization models are conservative in their calculation results. Recently, Argonne National Laboratory in the United States has studied stochastic programming with the idea of ​​using a scene tree model to generate a large number of random error scenarios, and using a supercomputer to perform precise calculations on the problem. At present, the...

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Problems solved by technology

However, this problem cannot be solved by using some commercial software such as GAMS / CONOPT solver or traditional interior point method

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