Microgrid power flow optimization method considering voltage stability constraint

Abstract

The invention discloses a microgrid power flow optimization method considering voltage stability constraint. The method comprises a step of establishing a voltage stability index, a step of establishing the optimization mathematical model of a micro grid considering the influences of a distributed power supply and an energy storage unit, a step of constructing a historical fitting prediction-correction interior point method considering voltage stability constraint based on a prediction-correction interior point method, a step of repeatedly calling a three-phase power flow calculation module in a solution process to carry out three-phase power flow calculation on a microgrid optimization scheme, feeding the obtained voltage stability index to the historical fitting prediction-correction interior point method to carry out optimization processing. The method has the advantages that the historical fitting prediction-correction interior point method is used to process a discrete control variable, the contradiction between the calculation accuracy and iteration efficiency is solved, the method has a better global optimization characteristic, and a prediction-correction interior point method advantage is maintained.

Description

technical field [0001] The invention relates to a power flow optimization method of a micro-grid, in particular to a power flow optimization method of a micro-grid considering voltage stability constraints. Background technique [0002] Optimal Power Flow (OPF) is one of the important means of power system operation and control, and it is also an important part of the power management system. The so-called optimal power flow is when the structural parameters and load conditions of the power system are given, through the optimization of the control variables, find the power flow that can satisfy all the specified constraints and make one or more performance indicators of the system optimal distributed. With the continuous advancement of smart grid construction, clean and efficient renewable energy power generation technology has received extensive attention. In recent years, various distributed generation (Distributed Generation, DG), distributed energy storage unit (Storage...

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Problems solved by technology

[0003] At present, the existing power flow optimization methods at home and abroad are difficult to meet the needs of microgrid development and construction, mainly in the following aspects:

[0004] 1. Most power flow optimization models fail to fully take into account the impact of distributed power and energy storage units

Although some power flow optimization methods considering the influence of DG have appeared, the modeling of DG is still rough. Generally, DG is treated as a common power source or a "negative load" without classification and equivalent values. Lack of scientific modeling of SU

[0005] 2. The voltage stability of the microgrid is greatly affected by intermittent micro-sources during grid-connected operation. Although there have been some power flow optimization methods that take into account the constraints of voltage stability, the traditional voltage stability indicators have not fully considered the microgrid. The characteristics of grid-connected operation and the role of DG and SU cannot make a better evaluation of voltage stability

[0006] 3. The micro-grid has obvious three-phase unbalance characteristics. When calculating the network loss and voltage indicators of the optimization scheme, many existing optimization methods fail to fully consider the three-phase parameters and load imbalance of the micro-grid, thus affecting calculation accuracy

[0007] 4. The microgrid optimization model has the characteristics of coexistence of continuous variables and discrete variables. The traditional mathematical programming method is difficult to deal with discrete variables, and the global optimization ability is not strong; the existing intelligent algorithm has a slow calculation speed and is easy to fall into local optimum

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