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

A technology of optimal scheduling and time-space correlation, applied in wind power generation, electrical components, circuit devices, etc., can solve problems such as slow calculation speed, less applied research, and dependence on convergence efficiency

Active Publication Date: 2018-09-28
SHANGHAI UNIVERSITY OF ELECTRIC POWER
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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...

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

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Embodiment 1

[0121] The following is a detailed analysis combined with an IEEE39 node system containing a wind farm, such as figure 1shown. In order to analyze the robustness of the ensemble, different ensemble conservatism control parameters α are adopted to analyze its influence on the scheduling cost. The specific results are shown in Table 1. It can be seen from Table 1 that the scheduling results obtained by the robust unit combination optimization model under different control parameters α are all different, so the change of the uncertainty set will directly affect the scheduling decision of the robust unit combination; in addition, with the control parameter α The uncertainty interval shrinks continuously, and the power generation cost and wind curtailment penalty cost obtained by the optimization of the robust unit combination model also show a downward trend.

[0122] Table 1 Scheduling results under different control parameters α

[0123] α

Power Generation Cost / ($)...

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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...

Claims

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Application Information

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IPC IPC(8): H02J3/46H02J3/38G06Q10/06G06Q50/06
CPCG06Q10/06312G06Q50/06H02J3/386H02J3/46H02J2203/20Y02E10/76
Inventor 葛晓琳郝广东金言
Owner SHANGHAI UNIVERSITY OF ELECTRIC POWER
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