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Solar micro-grid scheduling method based on crow algorithm and pattern search algorithm

A technology of a pattern search algorithm and a scheduling method, which is applied in the field of solar microgrid scheduling based on the crow algorithm and the pattern search algorithm, can solve the problems of low solution quality, low computing efficiency, and high cost of microgrid scheduling methods, and achieves low cost, The effect of high computational efficiency and superior solution quality

Active Publication Date: 2021-06-29
申电能源股份有限公司
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  • Description
  • Claims
  • Application Information

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Problems solved by technology

[0004] Purpose of the invention: The purpose of this invention is to provide a solar microgrid scheduling method based on the crow algorithm and the pattern search algorithm, to solve the problem of high cost and poor solution quality of the microgrid scheduling method Low, low computational efficiency and other issues

Method used

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  • Solar micro-grid scheduling method based on crow algorithm and pattern search algorithm
  • Solar micro-grid scheduling method based on crow algorithm and pattern search algorithm
  • Solar micro-grid scheduling method based on crow algorithm and pattern search algorithm

Examples

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Embodiment 2

[0105]Example 2 studies the effect of solar irradiance on cold sunny days. In this weather, the rate of solar power generation is relatively low. Table 2 is the result obtained in a cold sunny day simulation problem, which proves that the performance of the hybrid CS-PS optimization algorithm proposed in this patent is much better than other algorithms. Figure 5 and Figure 6 Shows the hourly dispatch of gensets and renewable generation. The results show that the main grid handles less electricity on warm sunny days than in the previous case. The reduction in power trading results in a reduction in operating costs, as the PV generates less electricity during the day. In this case, due to the relatively low market price, the battery energy storage system is charged at intervals of 1-7. However, utilizing MT to provide the power required for battery charging is considered the best option. Batteries, on the other hand, can power the system for 9-16 hours during certain peri...

Embodiment 3

[0108] Example 3 presents and discusses the results obtained for a data simulation problem of a warm cloudy day. To this end, the objective function values ​​reported by different optimization algorithms are shown in Table 3. It can be seen from the table that the hybrid CS-PS optimization algorithm proposed in this patent has a better solution than other methods. Figure 7 and Figure 8 The hourly schedule of different units is shown. Due to the low power generation of solar photovoltaic panels, compared with the research of the first two examples, the total operating cost is also lower than that of the first two examples, as Figure 7 shown. In addition, MT does not operate within a certain time interval, so the transaction power with the upstream network is relatively small. During the 9-16 time period, the battery also provided lower power. FCs and MTs generate more electricity than other units because of their associated lower operating costs.

[0109] table 3

[0...

Embodiment 4

[0111] Example 4 studies the influence of solar irradiance on solar power generation and MG operation in cold cloudy days. As shown in Table 7, the solution obtained by using the hybrid CS-PS optimization algorithm proposed in this patent is obviously better than other optimization algorithms. Figure 9 and Figure 10 The hourly schedule of different units is shown. Due to the lower solar irradiance on cold cloudy days, the output power of PV panels is also lower. It is worth noting that compared with the previous three example studies, the total operating cost of MG is also greatly reduced. The battery charges over 0-8 hours and provides power to the system until time slot 16. The MT operates at rated capacity, and the load demand is provided through power trading with the main grid, and power is also provided by other units. MT and FC account for a higher proportion of supply load demand than other units, helping to reduce MG's operating costs.

[0112] Table 4

[0113...

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Abstract

The invention discloses a solar micro-grid scheduling method based on a crow algorithm and a pattern search algorithm, a micro-grid is composed of a distributed generator set DG, and the generator set comprises a micro turbine MT, a solar photovoltaic panel PV, a battery FC and a wind turbine WT. The scheduling method comprises the following steps: (1) obtaining a cost-oriented objective function and constraint conditions of the solar micro-grid; (2) obtaining a first optimal scheduling scheme of the generator set by adopting a crow algorithm; and (3) taking the first optimal scheduling scheme as an initial value, and obtaining a second optimal scheduling scheme of the generator set by using a pattern search algorithm. The scheduling method is low in cost, excellent in solution quality, high in calculation efficiency and good in robustness.

Description

technical field [0001] The invention relates to a solar microgrid scheduling method, in particular to a solar microgrid scheduling method based on a crow algorithm and a pattern search algorithm. Background technique [0002] With the continuous construction of the micro-grid, the shortcomings of the micro-grid are gradually revealed. Due to the wide variety of distributed power generation units and other energy storage units in the micro-grid, the control complexity is high and the control is difficult; secondly, the micro-grid. Distributed power generation units are greatly affected by the weather, and the randomness makes it difficult to control the power quality of the microgrid, and it is easy to cause a large impact on the large grid when connected to the large grid; finally, the photovoltaic power generation and wind power generation in the microgrid are intermittent. In the peak period of power consumption on the user side, it is easy to rely on the independent power...

Claims

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Application Information

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Patent Type & Authority Applications(China)
IPC IPC(8): H02J3/38H02J3/46H02J3/32G06F30/20G06N3/00G06F111/04
CPCH02J3/381H02J3/466H02J3/32G06F30/20G06N3/006H02J2300/24H02J2300/30H02J2300/28H02J2203/20G06F2111/04Y02E70/30Y02E10/76Y02E10/56
Inventor 姜明新贾银洁王海燕王文豪
Owner 申电能源股份有限公司
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