Active power distribution network robustness reactive power optimization operation method

Abstract

The invention discloses an active power distribution network robustness reactive power optimization operation method, which obtains the uncertainty set of probability distribution functions when only the second moment information of wind power probability distribution is available, allows reactive power optimization strategies to meet safe operation constrains under any case in the uncertainty set, and meanwhile minimizes distribution network loss. Accordingly, a traditional reactive power optimization opportunity constraint programming model is converted into a probability distribution robustness opportunity constraint model, and random variables are separated and are taken into inequality constraints; the random variables in an optimization model are removed by comprehensively utilizing the CVaR estimation under a worst case and a dual optimization method, and are converted into a mode of only containing matrix inequalities of the second moment information; and an immune particle swarm algorithm based on linear matrix inequalities is employed for solving. The active power distribution network robustness reactive power optimization operation method solves the problem that the current wind power prediction technology for real active power distribution networks is limited, and wind power probability distribution functions can not be obtained accurately, and meets power distribution network actual demands.

Description

technical field [0001] The invention relates to a robust optimization operation method for an active network, in particular to a robust reactive power optimization operation method for a distribution network that includes wind power and only requires the second-order moment of the probability distribution function of the wind power. Background technique [0002] With the increasingly prominent energy and environmental issues, renewable energy represented by wind energy can effectively alleviate the energy crisis. However, the partial predictability, uncertainty and intermittency of wind energy have caused great difficulties and challenges to its grid connection, resulting in frequent changes in power flow and voltage of the distribution network, which will not be conducive to the stable and economic operation of the distribution network. The reactive power optimization operation of the distribution network including wind power refers to the optimal decision-making of the ope...

AI Technical Summary

Problems solved by technology

Existing studies usually assume that wind power output obeys normal distribution, Beta distribution, Laplace distribution, and Cauchy distribution. However, in actual power systems, the power generation of wind turbines is an uncontrollable random variable. It mainly depends on the randomness of the wind speed at the installation site of the wind turbine, and generally only part of the information about the probability distribution of wind power uncertainty can be obtained

Therefore, the probability distribution used to describe the uncertainty of wind power itself is an uncertain quantity. The existing research has not considered the uncertainty of the random variable of the probability distribution, so it cannot fundamentally guarantee the effectiveness of the proposed reactive power optimization scheme. sex

[0004] The solution methods for reactive power optimization include deterministic methods based on mathematical characteristics and stochastic algorithms based on intelligent computing, because power system reactive power optimization problems contain complex constraints, and their non-convex characteristics cause ordinary particle swarm optimization, genetic algorithms and taboo Search, etc. can easily fall into local optimum

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