A Random Optimal Scheduling Method for Power Grid Emergency Scenarios

Abstract

The invention discloses a method for random optimal dispatching of a power grid emergency scene. Firstly, the uncertainty model of wind power output and interruptible load response is established; for the interruptible load, incentive factors and penalty factors are set to constrain its interruption behavior; secondly, aiming at the lowest total cost of stochastic optimal scheduling in emergency scenarios, the establishment of an Interrupt loads participate in the stochastic optimal dispatching model in the power grid emergency scenario; then use the unscented transformation method to generate a certain number of Sigma point sets in the multi-dimensional space; finally, solve the deterministic optimal dispatching in the power grid emergency scenario at each Sigma sampling point The results are analyzed and evaluated according to their statistical properties. The present invention provides an effective, practical and scientific stochastic optimization scheduling method in the emergency scene of the power grid, taking into account the calculation accuracy and calculation cost of the model, which is beneficial to ensure the balance of power supply and demand in the power system, and maintain the safe and stable operation of the system.

Description

technical field [0001] The invention relates to a method for random optimal scheduling of power grid emergency scenarios, in particular to a method for random optimal scheduling of power grid emergency scenarios considering the uncertainty of wind power and interruptible loads. Background technique [0002] In recent years, in response to the energy crisis and environmental problems, wind power, as a clean energy with high sustainability, low cost and relatively mature technology, has attracted widespread attention worldwide. According to the "Global Wind Power Market 2017 Statistical Report" released by the Global Wind Energy Council, the newly installed capacity of wind power in the world in 2017 was about 52.6GW, and the cumulative installed capacity reached 539.6GW. First. However, the volatility and intermittency of wind power will directly lead to the enhancement of the uncertainty of the grid node input power, and its weak stability and weak immunity will inevitably ...

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Problems solved by technology

[0004] According to the current research, the following outstanding deficiencies are found: (1) The assumption of the uncertainty of IL response is relatively simple, which cannot accurately reflect its real distribution law; However, in order to avoid low-probability and high-risk accidents, there are few reports on short-term optimal dispatch for uncertain IL participation in power grid emergency scenarios; (3) Monte Carlo simulation is often used to solve power grid stochastic dispatch models, although the implementation is simple , which is good for parallel computing, but the computational cost is high and the convergence rate is low

Even the improved Monte Carlo method, such as the Latin hypercube sampling method, quasi-Monte Carlo method, etc., still has certain application limitations, and it is necessary to design an uncertainty quantification that can effectively deal with high-dimensional random input variables in the power grid stochastic dispatching model (uncertainty quantification, UQ) method

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