Self-adaptive Robust optimization method for active distribution network considering large number of renewable energy connected grids

Abstract

The invention discloses a self-adaptive Robust optimization method for an active distribution network considering a large number of renewable energy connected grids. The method comprises the steps of estimation of a Robust feasible region, construction of a nonlinear self-adaptive function, construction of a self-adaptive Robust active-power-reactive-power optimization model, mapping of kernel function space, and solution with a cutting-plane method and an optimization operation strategy of the active distribution network. According to the method, to solve height uncertainty of the large-scale renewable energy connected grids, an idea of Robust optimization is introduced, and the safe operation of a power system under an optimal decision is guaranteed; a self-adaptive technology is introduced, and self-adaptive changes of the optimal decision with uncertain variables are achieved; a self-adaptive Robust active-power-reactive-power optimization model of the active distribution network is established, and the economy and efficiency of the distribution network under the optimal decision are ensured, a kernel function method and a cutting-plane solution strategy are adopted, the efficient and fast solution of an original problem is achieved, and the reliability, economy and safety during an operation process of the active distribution network are ensured.

Description

technical field [0001] The invention relates to an optimal operation control method of an active distribution network, in particular to an adaptive robust optimization method for an active distribution network considering the grid connection of a large number of renewable energy sources. Background technique [0002] The large-scale grid-connection of renewable energy has brought extensive influence and great challenges to the operation of the distribution network. Distributed power is a typical representative of them, and most of the renewable energy is intermittent energy, which has the characteristics of randomness and uncertainty. At present, in the operation optimization of active distribution network, there are three main methods to deal with the uncertainty of renewable energy: (1) stochastic programming; (2) fuzzy programming; (3) robust optimization. The uncertainty probability distribution adopted by stochastic programming often has a certain deviation from the ac...

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Problems solved by technology

The uncertainty probability distribution adopted by stochastic programming often has a certain deviation from the actual situation, and the economy and safety of distribution network operation cannot be reliably guaranteed; fuzzy programming is often based on the personal experience of the decision-maker, and the decision-making has a large subjectivity of the distribution network, it is difficult to ensure the safe and economical operation of the distribution network; the robust optimization expresses uncertain variables as intervals to ensure that the safety constraints can be satisfied under uncertain conditions, and because all possible situations are considered, Decision-making is often conservative, and the economy of distribution network operation is not high

[0003] Therefore, the existing active distribution network that considers the integration of a large number of renewable energy sources has shortcomings in terms of economy and security, and cannot realize active control and real-time optimization of the distribution network.

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