Power flow control method based on comprehensive sensitivity

Abstract

The invention discloses a power flow control method based on comprehensive sensitivity. The method comprises the following steps: improving a comprehensive sensitivity index, and constructing positive and negative dual comprehensive sensitivity indexes of schedulable nodes; in order to reduce the dimensionality of a control variable in the screening optimization algorithm, removing partial nodes with small comprehensive sensitivity absolute values; by means of the advantage of a sensitivity method in calculation speed, rapidly screening out schedulable nodes participating in scheduling through a first optimization model; taking the screened scheduling nodes as control variables to establish a second optimization model with the minimum total adjustment amount; and fully considering various security constraints in the power grid to make the result of the output adjustment amount more accurate. According to the power grid power flow control scheme obtained by the invention, the defect of long time consumption caused by excessive control variables of a traditional optimization model is overcome in time, the power flow error caused by a traditional sensitivity method is reduced in precision, and the accuracy and efficiency of power flow control are improved.

Description

technical field [0001] The invention relates to the technical field of power grid stable operation and optimal scheduling, in particular to a power flow control method based on comprehensive sensitivity. Background technique [0002] Building a large-scale cross-regional interconnected power system has become a common trend in the development of the power industry in all countries in the world. In recent years, with the rapid development of my country's power industry, various factors such as large-scale grid interconnection, high proportion of new energy access, random equipment failures, and planned power outages have made the operation mode of the grid complex and changeable, which has brought great harm to the safe and stable operation of the grid. unprecedented challenges. [0003] According to analysis reports on the causes of many large-scale power outages around the world, it can be known that power outages mostly occur in the power flow heavy load area of ​​the powe...

AI Technical Summary

Problems solved by technology

[0005] The traditional sensitivity method of active safety correction determines the adding and subtracting output nodes through the sensitivity of the active power injection power of the node to the active power of the line, and sorts according to the absolute value of the sensitivity, but this method only determines the control node based on the sensitivity to the overloaded line , if the control node acts oppositely on the overloaded line and the heavy-loaded line, it may cause a more serious overload situation

Although the comprehensive sensitivity method considers the comprehensive control effect of the control node on the overloaded line and the heavy-loaded line, it may occur that the negative sensitivity effect of the control node on the overloaded line is smaller than the positive sensitivity effect on the heavy-loaded branch, resulting in the comprehensive sensitivity of the node being positive. , so that the control node is divided into a set of output reduction nodes, which is contrary to the fact that the node actually adds output to the overloaded line, and the overload of the overloaded line cannot be eliminated

The sensitivity method also has a serious disadvantage: the sensitivity method simplifies the nonlinear relationship between node output and line power flow into a linear relationship, and there are errors in the calculation accuracy, which is difficult to meet the power flow control accuracy requirements of large-scale power grids

[0006] Compared with the sensitivity analysis method, the optimal planning algorithm can establish a more flexible model, comprehensively consider various constraints of the safe operation of the power grid, and have high calculation accuracy. However, with the expansion of the power grid scale and the increase of control variables, dimension disasters , long calculation time, difficulty in convergence, etc.

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