Active power distribution network intelligent soft switch robust optimization modeling method taking uncertainty into consideration

Abstract

An active power distribution network intelligent soft switch robust optimization modeling method taking uncertainty into consideration includes: according to a selected power distribution system, inputting active power distribution system structure and parameters; according to the active power distribution system structure and parameters, building an active power distribution network intelligent soft switch certainty optimization model; performing second-order cone model conversion on the active power distribution network intelligent soft switch certainty optimization model, and acquiring an active power distribution network intelligent soft switch certainty optimization model compact form; according to the active power distribution network intelligent soft switch certainty optimization model compact form, setting an uncertain set of a distributed power source and load, and on this basis, building an active power distribution network intelligent soft switch robust optimization model taking uncertainty into consideration. By the method, randomness and volatility of the distributed power source and the load are fully considered to build the active power distribution network intelligent soft switch robust optimization model taking uncertainty into consideration, and a column sum constraint generation algorithm is adopted for solution to acquire an intelligent soft switch robust running strategy.

Description

technical field [0001] The invention relates to a modeling method for an intelligent soft switch of an active distribution network. In particular, it involves a robust optimization modeling method for intelligent soft switching in active distribution networks considering uncertainty. Background technique [0002] With the increasing number of schedulable resources in the distribution network, the operation control problem of the distribution network becomes more and more complex. After a large number of distributed power sources are connected to the distribution network, because their operating characteristics are greatly affected by the environment and have obvious randomness and volatility, the introduction of a large number of uncertain factors makes the distribution network face a series of new problems, such as two-way power flow , voltage over limit, network congestion, etc., among which the voltage over limit is particularly prominent. However, the adjustment means ...

AI Technical Summary

Problems solved by technology

Since the configuration of measurement terminals in the distribution network is often less and the reliability of the communication network is poor, the measurement data obtained from this often have large errors and even bad data.

Most of the existing prediction methods are based on intelligent optimization algorithms such as neural networks, and the algorithms themselves will introduce certain deviations

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