Day-ahead optimization scheduling method considering space-time correlation constraint of wind farm

Abstract

The invention relates to a day-ahead optimization scheduling method considering a space-time correlation constraint of a wind farm, comprising the steps of: 1) building a robust unit commitment mathematical model which considers a power generation cost and a wind curtailment cost; 2) for a space clustering effect and a time smoothing effect of wind power, building a uncertainty set considering space and time constraint of the wind power; and 3) decomposing the mathematical model into a unit commitment main problem, a security feasibility inspection sub-problem and a wind power maximum utilization sub-problem, establishing a coupling relationship between the main problem and the sub-problems through a C&CG (Column and Constraint Generation) algorithm, and performing solving to obtain an optimization scheduling scheme. In comparison with the prior art, the day-ahead optimization scheduling method of the invention has the advantages of quick speed, reliability, high applicability, comprehensive consideration, good optimization effect, and so on.

Description

technical field [0001] The invention relates to the field of wind farm scheduling, in particular to a day-ahead optimal scheduling method considering the time-space correlation constraints of wind farms. Background technique [0002] Reducing dependence on fossil energy and vigorously developing clean energy represented by wind power have become the general consensus of the international community to deal with global climate change. China's energy development-related policies propose that by 2030, wind power and other renewable resources will generate 20% of the power generation, and a high proportion of wind power grid integration has become an inevitable trend in my country's power development. However, as the proportion of wind power in the grid continues to rise, its randomness and intermittency have brought severe challenges to the unit combination problem and aggravated its uncertainty. Under the high proportion of wind power access, the traditional deterministic unit...

AI Technical Summary

Problems solved by technology

The Benders algorithm is usually used to solve the robust unit combination, but its convergence efficiency depends on the quality of the dual solution, and it is easy to encounter the problem of slow calculation speed

For large-scale alternate iterative calculations, column and constraint generation algorithms can identify key variables affected by uncertain factors, and dynamically create new variables and constraints for the main problem, but the application of this algorithm in robust unit combinations is relatively limited. few

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