A power prediction method and system for a microgrid group

Abstract

The invention discloses a method and a system for predicting power of a microgrid group. The method comprises steps: a microgrid graph theory model is built according to a communication relation between sub microgrids in the microgrid group; according to an intelligent agent node consistency theory and in combination with a micro Calman filter prediction algorithm, a power prediction algorithm for distributed prediction for needed power by a total grid of the microgrid group is determined; on the basis of the already-built communication relation graph theory topology, each sub microgrid in the microgrid group integrates grid needed power information of a local sub microgrid system and an adjacent sub microgrid system and uses a prediction algorithm to distributively perform short-term prediction on the needed power by the total grid of the microgrid group in the local sub microgrid system. Short-term prediction is carried out on the overall grid needed power of the microgrid group formed by multiple microgrids, and strong guarantee is provided for aspects of stable operation and power dispatching for the microgrid group power sharing system.

Description

technical field [0001] The invention belongs to the field of grid power, and in particular relates to a power prediction method and system for a micro grid group. Background technique [0002] In the past few decades, the scale of the power grid has continued to expand, and it has gradually developed into a super-large interconnected network system with centralized power generation and long-distance power transmission. However, with the continuous increase of long-distance power transmission, the dependence of the receiving power grid on external power continues to increase, the stability and security of power grid operation tend to decline, and it is difficult to meet diversified power supply needs. On the other hand, concerns about the gradual depletion of global conventional energy sources and environmental pollution have become increasingly prominent. In view of this, environmentally friendly, efficient and flexible distributed power generation is widely favored. At pre...

AI Technical Summary

Problems solved by technology

In the wireless sensor network, the distributed prediction algorithm is mainly used to predict the state value of a certain process in the network to achieve the effect of positioning and tracking; while in the power system, it is mainly applied to the distributed predictive control, firstly through the load The forecasting method predicts the load value at the next moment, and then establishes a transfer function model through the distributed control idea to automatically adjust the power generation, thus realizing the distributed predictive control. Although the distributed idea is reflected in the entire control algorithm, but It is not reflected in distributed prediction but in distributed control, so strictly speaking, there is no perfect distributed prediction algorithm in the field of power system to complete the prediction of a certain parameter of a complex large system

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