Stochastic optimization scheduling method for power grid in emergency situation

Abstract

The invention discloses a stochastic optimization scheduling method for a power grid in an emergency situation. The method comprises the steps of firstly, building an uncertainty model with wind poweroutput and an interruptible load response and setting a motivation factor and a penalty factor for an interruptible load to constrain an interrupt behavior of the interruptible load; secondly, with the goal of minimum total cost of stochastic optimization scheduling in the emergency situation, building a stochastic optimization scheduling model, in which the interruptible load participates, for the power grid in the emergency situation, and then generating a certain number of Sigma point sets in a multi-dimensional space by using an unscented transformation method; and finally solving a certainty optimization scheduling result of the power grid in the emergency situation on each Sigma sampling point and carrying out analysis and evaluation according to the statistical characteristics. Theinvention provides an effective, practical and scientific stochastic optimization scheduling method for the power grid in the emergency situation. The calculation accuracy and calculation cost of themodel are taken into account, guarantee of electric power and energy balance between supply and demand is facilitated and safe and stable operation of the system is maintained.

Description

Technical field [0001] The invention relates to a random optimal dispatching method for a power grid emergency scene, in particular to a random optimal dispatching method for a power grid emergency scene that takes into account the uncertainty of wind power and interruptible load. Background technique [0002] In recent years, in order to cope with the energy crisis and environmental problems, wind power, as a clean energy with higher sustainability, lower cost and more mature technology, has received extensive attention worldwide. According to the "Global Wind Power Market 2017 Annual Statistical Report" released by the Global Wind Energy Council, the newly installed capacity of global wind power in 2017 was about 52.6GW, and the cumulative installed capacity reached 539.6GW, of which China’s new installed wind power and cumulative installed capacity remained global the first. However, the volatility and intermittency of wind power will directly lead to the increase of the unce...

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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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