Multi-scheduling-interval distributed energy scheduling method and system containing random wind energy

Abstract

The invention belongs to the field of distributed energy scheduling, and provides a multi-scheduling-interval distributed energy scheduling method and system containing random wind energy. The methodcomprises the following steps: calculating a corresponding communication weight matrix according to a pre-designed network communication connection topological graph of a thermal power generating unit/wind power generating unit in a smart power grid, so that each generator set node and a neighbor generator set node thereof perform information interaction based on the communication weight matrix; and continuously solving the optimal scheduling model based on generator set node interaction information and an ADMM method of dynamic average consistency, and finally obtaining the optimal distribution power of each generator set. The optimal scheduling model is the cumulative sum of thermal power generating unit cost functions and wind power generating unit cost functions of all scheduling intervals.

Description

technical field [0001] The invention belongs to the field of distributed energy scheduling, and in particular relates to a multi-scheduling interval distributed energy scheduling method and system for smart grids including random wind energy. Background technique [0002] The statements in this section merely provide background information related to the present invention and do not necessarily constitute prior art. [0003] With the continuous increase of traditional energy consumption and serious environmental damage, new energy represented by wind energy will become an important part of the future smart grid because of its cleanliness and renewability. Due to the randomness and intermittent nature of wind energy, the energy management after wind power is integrated into the grid has become a major technical problem worthy of study. The inventors have found that the current energy scheduling method containing random wind energy has the following problems: [0004] 1) Tra...

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Problems solved by technology

[0004]1) Most of the traditional energy dispatching adopts centralized management strategy, that is, there is a control center to centralize the dispatching of the participating generating units, but the centralized energy management method has scalability Poor performance, poor robustness to single node faults, etc.

[0005]2) Most of the existing distributed energy management methods focus on the study of distributed energy scheduling in a single interval, but there are few studies on the scheduling of multiple intervals

As the number of generating units participating in scheduling increases, the decision information dimension of the policy interaction will also increase, and the resulting communication and storage costs will also increase

[0007]4) Most of the existing multi-dispatch interval distributed energy management methods are aimed at the situation where the objective function is a quadratic function, although there are also cases where the objective function is a general convex function A distributed strategy based on dynamic average consistency, but it needs to introduce a penalty function to eliminate the decision variable constraints of the generator set, and it is difficult to select appropriate values ​​for the parameters introduced

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