Active safety verification method for power transmission network line based on extreme learning machine

Abstract

The invention belongs to the field of power system operation and control, and especially relates to an active safety verification method for a power transmission network line based on an extreme learning machine. The method provided by the invention gives consideration to a problem that a conventional heuristic-type active safety correction method based on sensitivity cannot be good in quickness and precision of strategy formulating adjustment at the same time, and the method provided by the invention balances the quickness and precision. The method comprises the steps: carrying out the analysis and learning of operation data of a power grid in different states based on the extreme learning machine, and obtaining the sensitivity of injection power of each node to a power transmission line; building an active safety correction model for the sensitivity of the power transmission line based on the injection power of the nodes; finally solving the active safety correction model through a particle swarm intelligent algorithm, and obtaining a generator and a load adjustment scheme.

Description

technical field [0001] The invention belongs to the field of power system operation and control, and relates to an active power safety correction method for transmission network lines based on an extreme learning machine. Background technique [0002] The development of smart grid and large power grid interconnection technology has played a major role in solving the uneven distribution of energy in my country and improving the robustness of the power grid. Require. Studies have shown that cascading faults are an important cause of blackouts. Faulty components cause power flow shifts, which will cause normal operating lines to become heavy-loaded and overloaded. This is an important factor for the spread of cascading faults. Therefore, to carry out active power safety correction on the operating transmission line in the state of heavy load and overload, the dispatching department needs to take fast and effective generator output adjustment and load shedding measures to restor...

AI Technical Summary

Problems solved by technology

The optimization planning algorithm establishes a mathematical model of active safety correction, sets the objective function and various constraints, and uses mathematical analysis methods to solve the mathematical model to obtain correction measures. This kind of method is comprehensive and has good safety and economy. However, there may be problems such as too long solution time, too many adjustment devices, and difficult to meet the power flow convergence conditions; the sensitivity method calculates the sensitivity of the generator to the overloaded line, and then obtains correction measures according to the overload of the line. This method can quickly obtain adjustments The adjustment measures eliminate the overload, and there is no power flow convergence problem, but the accuracy of the sensitivity will directly affect the effectiveness of the correction scheme

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