Fault Adaptive Robust Optimal Restoration Method for Flexible Distribution System

Abstract

The invention belongs to the technical field of distribution network fault recovery, and in particular relates to a fault adaptive robust optimization recovery method for a flexible power distribution system, which includes: Step 1: Establishing loss consideration based on flexible multi-state switch control and distribution network power flow The power mathematical model of the SNOP; Step 2: Taking the switch state and SNOP active power as decision variables, taking into account the SNOP’s own loss and the difference in user loss of load loss, a fault optimization recovery model with the goal of minimizing the risk of load loss is established ; Step 3: By adjusting the active power of SNOP to cope with the uncertainty of the source and load, fine-tune and optimize the optimal scheme of the switching state, taking reducing network loss and voltage deviation as the objective function, and adaptively adjusting its weight coefficient according to the magnitude of the voltage deviation , get the SNOP parameter value of network loss and voltage.

Description

technical field [0001] The invention belongs to the technical field of distribution network fault recovery, and in particular relates to a fault self-adaptive robust optimization recovery method of a flexible power distribution system. Background technique [0002] With the gradual advancement of the national new energy and electricity reform policies, a large number of distributed energy sources, electric vehicle charging devices, energy storage devices and micro-grids are connected to the distribution network, and the penetration rate continues to increase. The randomness of new energy sources and loads and the characteristics of decentralized control under the characteristics of multi-subject interests are likely to cause large fluctuations in feeder power and voltage limit violations, which pose severe challenges to the operation of distribution networks. At the same time, network reconfiguration based on tie switches is limited by issues such as switch response speed, o...

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Problems solved by technology

Yang Lijun and Lu Zhigang divided the wind power output into multiple typical scenarios, and carried out the optimal recovery of distribution network faults based on multiple scenarios. However, the scenario analysis method uses the expected value in each scenario, which cannot simulate the randomness of distributed power output well.

Chen Xinyue, Tang Wei, Chen Yu and others constructed a discrete probability model of photovoltaic power generation, and took the minimum power loss load higher than the confidence level as the objective function to establish a fault recovery model based on chance constrained programming, but the chance constrained method cannot Strictly ensure that the node voltage and branch power meet the constraints, and it is impossible to guarantee the feasibility of constraints for any element in the uncertain set

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