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A two-stage source-load scheduling method and device considering peak shaving and slope climbing requirements

A scheduling method and a technology of climbing demand, which are applied in the direction of single-grid parallel feeding arrangement, wind power generation, etc.

Active Publication Date: 2017-12-05
NORTHEAST DIANLI UNIVERSITY
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  • Description
  • Claims
  • Application Information

AI Technical Summary

Problems solved by technology

[0006] None of the above studies considered the limitation of wind power utilization by the peaking and ramping demand of the power system from the perspective of the net load curve, and did not promote wind power from the perspective of smoothing the net load curve and reducing the peaking and ramping demand of the power system containing wind power. consumption; demand response is generally introduced into the power system economic dispatch or unit combination model, and no separate demand response optimization model is established to optimize the net load curve

Method used

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  • A two-stage source-load scheduling method and device considering peak shaving and slope climbing requirements
  • A two-stage source-load scheduling method and device considering peak shaving and slope climbing requirements
  • A two-stage source-load scheduling method and device considering peak shaving and slope climbing requirements

Examples

Experimental program
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Effect test

Embodiment 1

[0047] A two-stage source-load scheduling method considering peak-shaving and ramp-up demands, see figure 1 , the scheduling method includes the following steps:

[0048] 101: Divide the net load curve according to the inflection point of the net load curve; analyze the peak-shaving demand of the power system and the climbing demand between each time period based on the net load curve;

[0049] 102: Optimizing the net load curve for each partition using a one-stage incentive demand response optimization model;

[0050] 103: When all partitions are calculated, output the optimized load curve;

[0051] 104: Based on the optimized load curve, use the two-stage scheduling model for day-ahead scheduling;

[0052] 105: When the optimal scheduling result is reasonable, that is, when all constraint conditions are met, the scheduling result is output, and the process ends.

[0053] Wherein, the scheduling method also includes:

[0054] When the calculation of all partitions has not...

Embodiment 2

[0063] The scheme in Embodiment 1 is described in detail below in conjunction with specific calculation formulas and examples, see the following description for details:

[0064] 201: Read wind power forecast output, load and power system data; subtract the power system day-ahead load forecast curve from the wind power forecast curve to obtain the net load curve of conventional thermal power units; divide the net load curve according to the inflection point of the net load curve; Analyze the peak-shaving demand of the power system and the climbing demand between each time period based on the net load curve, and calculate the peak-to-valley difference of the net load curve and the climbing demand of each time period and each partition;

[0065] 202: Optimizing the net load curve for each partition using a one-stage incentive demand response optimization model;

[0066] Among them, the net load curve of the large-scale wind power system is optimized and corrected. While reducing...

Embodiment 3

[0121] Combined with the following specific tests, the attached image 3 To verify the feasibility of the scheme in Examples 1 and 2, see the following description for details:

[0122] Taking the IEEE 36-node 10-machine power system as an example, when wind power with an installed capacity of 600MW is connected, the upper and lower limits of demand response are plus or minus 15% of the maximum load. Two scenarios are set, Scenario 1 is scheduling without considering demand response and only considering the two-stage scheduling model in step 204; Scenario 2 is considering demand response, using the two-stage optimization model in steps 202 and 204 for optimization. Comparison and reference of power system net load curves in two scenarios image 3 , the comparison of optimization results in the two scenarios is shown in Table 1:

[0123] Table 1 Comparison of optimization results in different scenarios

[0124]

[0125] Depend on image 3 It can be seen that comparing th...

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Abstract

The invention discloses a two-stage source-load dispatching method and device considering peak regulation and climbing requirements. The dispatching method comprises the following steps: partitioning a net load curve according to the inflection points of the net load curve; analyzing the peak regulation requirement of a power system and the climbing requirement of each time interval based on the net load curve; optimizing each partition of the net load curve by utilizing a stage excitation type requirement response optimization model; after all partitions are computed, outputting the optimized load curve; based on the optimized load curve, carrying out advance dispatching by utilizing a two-stage dispatching model; and when the optimized dispatching result meets all constraint conditions, outputting the dispatching result. The dispatching device comprises a partitioning module, an analysis module, a first optimization module, a first output module, a dispatching module and a second output module. The two-stage source-load dispatching method and device can effectively increase the wind power utilization ratio and are suitable for actual dispatching of a power system with large-scale wind power.

Description

technical field [0001] The invention relates to the technical field of power system analysis and scheduling, in particular to a two-stage source-load scheduling method and device considering peak-shaving and ramp-up requirements. Background technique [0002] In the "Energy Development Strategic Action Plan (2014-2020)" issued by the State Council on June 7, 2014, it was proposed to adhere to the strategic policy of "conservation, cleanliness, and safety" and to develop clean and low-carbon energy as the main direction of energy structure adjustment. . Although the accumulative grid-connected installed capacity of wind power in China reached 96.37 million kilowatts in 2014, accounting for 7% of the total installed capacity of power generation, the average wind power curtailment rate in the country reached 8%. It is highlighted that how to accommodate wind power on a large scale has become a bottleneck problem restricting the development of wind power. [0003] Wind power o...

Claims

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Application Information

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Patent Type & Authority Patents(China)
IPC IPC(8): H02J3/46
CPCY02E10/76
Inventor 李国庆陈厚合张儒峰姜涛李扬辛业春王振浩李卫国王鹤
Owner NORTHEAST DIANLI UNIVERSITY
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