Time-sharing and classification energy storage adjusting method

Abstract

The invention discloses a time-sharing and classification energy storage adjusting method. In order to solve the problem that an existing multi-energy storage scheduling method is low in energy utilization rate, the method comprises the following steps: obtaining full-day output data of a target network segment according to historical output data of each type of stored energy in the network segment, and dividing output time periods; establishing a time-sharing corresponding relation between the all-day output data and time periods and a classification corresponding relation between the all-day output data and energy storage categories according to energy classification; and establishing a hierarchical energy storage structure in the network segment, wherein the energy storage layer performs scheduling decision based on the time-sharing correspondence and the classification correspondence. Time-sharing and classification models in network segments are constructed to realize time-sharing calling of each energy in a power grid, so that different energy can complete energy storage or output operation more efficiently in a time period suitable for energy storage or output.

Description

Technical Field

[0001] The present invention relates to the field of energy storage regulation, and in particular to a time-sharing and classified energy storage regulation method. Background Art

[0002] Due to the extensive use of fossil fuels such as coal, oil, and natural gas, global energy consumption demand continues to grow, and a series of problems such as energy shortages and serious environmental pollution have become difficulties and challenges that the world needs to deal with together. Therefore, there is a more urgent need for a sustainable, cleaner, and more efficient energy system. The existing diversified energy regulation methods in the power grid often lack comprehensive considerations of energy types and daily regulation times, resulting in a lack of systematic scheduling methods for clean energy, electricity, and other energy in the power grid, resulting in low energy utilization.

[0003] For example, a "hybrid energy storage system based on multi-element energy storage and control" disclosed in Chinese patent literature, with publication number CN115514100B, includes: a multi-element monitoring module: used to perform real-time twin monitoring of multi-element energy storage devices through a twin energy storage model; a multi-element control module: used to adjust the power input information of multi-element energy storage devices through the microgrid management end through twin monitoring information, and determine the power distribution strategy; a multi-element energy storage module: used to adjust the input power of each energy storage device according to the power distribution strategy. The present invention jumps out of the energy storage control strategy in the existing technology, and performs real-time twin monitoring of energy storage devices through a twin energy storage model. Through twin monitoring, intelligent power management and power distribution of the microgrid can be realized, and the energy storage device can be prevented from having too much heat and the energy storage power exceeding its limit due to too high input power. Summary of the invention

[0004] The present invention mainly solves the problem of low energy utilization rate of existing multi-energy storage scheduling methods; it provides a time-sharing and classified energy storage adjustment method, which realizes the time-sharing call of various energy sources in the power grid by constructing a time-sharing and classification model within the network segment, so that different energy sources can complete energy storage or power output operations more efficiently in the time period suitable for energy storage or power output.

[0005] The above technical problems of the present invention are mainly solved by the following technical solutions: The present invention includes: obtaining the daily output data of the target network segment according to the historical output data of various types of energy storage in the network segment and dividing the output time period, establishing the time-sharing correspondence between the daily output data and the time period and the classification correspondence between the daily output data and the energy storage category according to the energy classification; establishing a hierarchical energy storage structure in the network segment, and the energy storage layer makes scheduling decisions based on the time-sharing correspondence and the classification correspondence. The advantage of dividing the time period according to the daily output data is that it can reasonably control the output of various energy sources during the peak and trough periods of electricity consumption, and can minimize energy waste and take countermeasures to improve energy utilization.

[0006] Preferably, the corresponding relationship establishment process includes: obtaining the target network segment's daily output data W, performing time-sharing and energy classification processing on the total data, and obtaining time-sharing output [Wa, Wb, Wc...Wn], where a~n represents the output period within the day; energy classification output [W1, W2, W3, W4], where 1~3 represent the main output categories, and 4 represents the common output of other categories; and then establishing sampling coordinates for the time-sharing output and classification output. By dividing the whole day into time periods and energy categories, an adaptive time-sharing output and energy classification output model is established, which is convenient for subsequent calculations and conversion of energy storage and output data.

[0007] Preferably, the sampling coordinate establishment process of the time-sharing output includes: taking the pre-established time period as the X-axis and the full-day output data W as the Z-axis, drawing a two-dimensional rectangular coordinate system according to the change of the full-day output data W in the pre-established time period, and obtaining the change slope Kn according to the curve in the coordinate system to obtain the corresponding relationship. The rectangular coordinate system corresponding to the time period and the output data can more intuitively describe the energy consumption required in the network in each time period throughout the day, thereby providing a better scheduling means for it.

[0008] Preferably, the sampling coordinate establishment process of the energy classification output includes: taking the preset energy category as the y-axis and the full-day output data W as the z-axis, drawing a two-dimensional rectangular coordinate system according to the classification specific data of the full-day output data under different energy categories, and recording the data group to obtain the classification correspondence. By establishing a rectangular coordinate system corresponding to the energy category and the output data, the utilization rate and energy output efficiency of different energy sources can be observed more intuitively, which is convenient for screening various energy sources in the network to achieve better energy supply effects.

[0009] Preferably, the coordinate establishment process further includes: using the pre-established time period as the X-axis and the preset energy category as the Y-axis, establishing a two-dimensional rectangular coordinate system according to the output energy category and the number of output energy within the pre-established time period, obtaining a preliminary corresponding relationship of time-sharing classification, and recording data. After establishing the time-sharing and classified coordinate system, establishing a corresponding rectangular coordinate system according to the time period and energy category can also more intuitively detect the production capacity and utilization rate of different energy sources in various time periods throughout the day, which is convenient for providing reasonable adjustment plans for various types of energy in the all-weather scheduling process.

[0010] Preferably, the coordinate establishment process further includes: merging all coordinate systems according to the preliminary correspondence, time-sharing correspondence and classification correspondence to obtain a three-dimensional rectangular coordinate system with the pre-established time period as the X-axis, the energy category as the Y-axis and the full-day output data W as the Z-axis, and obtaining the total correspondence of [time-sharing, classification, output] according to the recorded data information. All rectangular coordinate systems are integrated to form a three-dimensional coordinate model, and the solution relationship of the remaining variables can be obtained according to any two variables through the obtained relevant correspondence of time-sharing, classification and output, so as to obtain more accurate calculation data, thereby realizing the scheduling of unknown full-day network sources.

[0011] Preferably, the establishment of the hierarchical energy storage structure includes: dividing the energy storage into 1 to 4 categories of energy storage, wherein category 1 represents electric energy storage, category 2 represents photovoltaic energy storage, category 3 represents wind power energy storage, and category 4 represents other categories of total energy storage; the hierarchical energy storage structure has 5 layers, with layers 1 and 2 respectively operating for electric power and photovoltaic energy storage, layers 4 and 5 respectively operating for wind power and other energy storage, and layer 3 being the scheduling layer for each energy storage layer. Detailed classification of energy storage facilitates targeted calculation of its output effect, and also facilitates subsequent changes in the order of energy storage scheduling and the addition of new energy types, with strong adjustability.

[0012] Preferably, the scheduling decision based on the time-sharing correspondence and the classification correspondence includes: according to the total correspondence of [time-sharing, classification, output], the energy storage category and the corresponding output data corresponding to each time period are prepaid in the layered energy storage structure, and finally the corresponding relationship model of [energy storage category, classification output data, time period] is obtained, and the scheduling decision is completed according to the model. By obtaining the corresponding relationship between the energy storage category, classification output data and time period, the prediction information of another parameter is obtained when only two arbitrary parameters are known, so as to accurately perform electricity or energy storage scheduling.

[0013] The beneficial effects of the present invention are: 1. A time-sharing and classified energy storage regulation method of the present invention establishes models of time-sharing and energy classification, time-sharing and output data, energy classification and output data, etc., and integrates them to obtain the corresponding relationship between energy storage category, classified output data and time period, so as to realize all-weather time-sharing and energy category regulation of energy storage or output in the network, thereby avoiding energy waste and improving energy output efficiency.

[0014] 2. The present invention provides a time-sharing and classified energy storage and regulation method, which can effectively prevent partial energy storage overflow or partial output deficiency by resetting the energy storage structure, designing a multi-layer energy storage layer, and adopting an n+1 construction method to add an energy coordination layer under the multi-energy storage structure, thereby providing a guarantee for regulation. BRIEF DESCRIPTION OF THE DRAWINGS

[0015] Figure 1 It is a schematic diagram of a time-sharing and classified energy storage and regulation method of the present invention. DETAILED DESCRIPTION

[0016] The technical solution of the present invention is further specifically described below through embodiments and in conjunction with the accompanying drawings.

[0017] Example: A time-sharing and classified energy storage adjustment method of this embodiment, such as Figure 1 As shown, it includes: obtaining the daily output data of the target network segment based on the historical output data of various types of energy storage in the network segment and dividing the output time period, establishing the time-sharing correspondence between the daily output data and the time period and the classification correspondence between the daily output data and the energy storage category according to the energy classification; establishing a hierarchical energy storage structure in the network segment, and the energy storage layer makes scheduling decisions based on the time-sharing correspondence and the classification correspondence. The advantage of dividing the time period according to the daily output data is that it can reasonably control the output of various energy sources during the peak and low power consumption periods, and can minimize energy waste and take countermeasures to improve energy utilization.

[0018] The factors that affect time period data are seasonal factors, climate factors, and weather factors in a single season. After big data training, we can obtain the full-day output data in various seasons and weather conditions in each network segment, as well as the corresponding energy storage category information, so as to achieve more detailed and accurate regulation. Based on the detailed data obtained above, the energy utilization data of the target regulation network segment is predicted and analyzed. After knowing a piece of data that can meet the requirements, we can bring it into the known related information to obtain the specific energy category and energy consumption data, so as to achieve regulation.

[0019] Among them, we can refer to the photovoltaic + wind output mode in spring during the day and night, and store the electricity obtained from the hydropower output; the photovoltaic + hydropower output mode in summer during the day and night, and store the electricity obtained from the wind power output; the photovoltaic + hydropower output mode in autumn during the day, and store the electricity obtained from the wind power output, and the photovoltaic + wind power output mode in autumn night, and store the electricity obtained from the hydropower output; the photovoltaic + wind power output mode in winter during the day and night, and store the electricity obtained from the hydropower output. Different adjustment methods may be used every day in each season. Therefore, it is necessary to establish a suitable energy storage scheduling structure in consideration of energy complementarity.

[0020] The establishment of a hierarchical energy storage structure includes: dividing energy storage into 1 to 4 categories, where category 1 represents electric energy storage, category 2 represents photovoltaic energy storage, category 3 represents wind power energy storage, and category 4 represents other categories of total energy storage; the hierarchical energy storage structure has 5 layers, with layers 1 and 2 operating for electric power and photovoltaic energy storage respectively, layers 4 and 5 operating for wind power and other energy storage respectively, and layer 3 being the scheduling layer for each energy storage layer. Detailed classification of energy storage facilitates targeted calculation of its output effect, and also facilitates subsequent changes in the order of energy storage scheduling and the addition of new energy types, with strong adjustability.

[0021] The advantage of using a five-layer energy storage structure is that it provides additional transfer points so that energy will not be fully transferred too quickly, but needs to wait for the analysis results to be obtained, which can greatly avoid output errors and thus improve its conversion efficiency. The energy storage structure described above is not only determined by the digital serial number corresponding to the energy category, that is, when a certain energy source is not applicable in this season, it will be replaced by other adaptable energy sources, and the energy storage scheduling will be completed instead. In addition, the reserved 3 layers are in the center, and it will collect part of the energy storage from other layers as a reserve reserve. Once the scheduling is insufficient, it will be supplemented by reserve adjustment, and the established correspondence and related data tables will be updated.

[0022] The corresponding relationship establishment process includes: obtaining the full-day output data W of the target network segment, performing time-sharing and energy classification processing on the total data, and obtaining time-sharing output [Wa, Wb, Wc...Wn], where a~n represents the output period within the whole day; energy classification output [W1, W2, W3, W4], where 1~3 represents the main output category, and 4 represents the joint output of other categories; and then establishing sampling coordinates for time-sharing output and classification output. By dividing the whole day into time periods and energy categories, an adaptive time-sharing output and energy classification output model is established, which is convenient for subsequent calculations and conversion of energy storage and output data.

[0023] The sampling coordinate establishment process of time-sharing output includes: taking the pre-established time period as the X-axis and the full-day output data W as the Z-axis, drawing a two-dimensional rectangular coordinate system according to the change of the full-day output data W in the pre-established time period, and obtaining the change slope Kn according to the curve in the coordinate system, and obtaining the corresponding relationship. The rectangular coordinate system corresponding to the time period and output data can more intuitively describe the energy consumption required in the grid in each time period throughout the day, thereby providing a better scheduling method for it.

[0024] The process of establishing sampling coordinates for energy classification output includes: using the preset energy category as the y-axis and the full-day output data W as the z-axis, drawing a two-dimensional rectangular coordinate system based on the classification specific data of the full-day output data under different energy categories, and recording the data group to obtain the classification correspondence. By establishing a rectangular coordinate system corresponding to the energy category and output data, the utilization rate and energy output efficiency of different energy sources can be observed more intuitively, which is convenient for screening various energy sources in the grid to achieve better energy supply effects.

[0025] The coordinate establishment process also includes: using the pre-established time period as the X-axis and the preset energy category as the Y-axis, establishing a two-dimensional rectangular coordinate system according to the output energy category and the number of output energy within the pre-established time period, obtaining a preliminary correspondence between time-sharing and classification, and recording data. After establishing the time-sharing and classification coordinate system, establishing a corresponding rectangular coordinate system according to the time period and energy category can also more intuitively detect the production capacity and utilization rate of different energy sources in various time periods throughout the day, which is convenient for providing reasonable adjustment plans for various types of energy in the all-weather scheduling process.

[0026] The coordinate establishment process also includes: merging all coordinate systems according to the preliminary correspondence, time-sharing correspondence and classification correspondence, obtaining a three-dimensional rectangular coordinate system with the pre-established time period as the X-axis, the energy category as the Y-axis, and the full-day output data W as the Z-axis, and obtaining the total correspondence of [time-sharing, classification, output] according to the recorded data information. All rectangular coordinate systems are integrated to form a three-dimensional coordinate model. Through the obtained relevant correspondence of time-sharing, classification, and output, the solution relationship of the remaining variables can be obtained according to any two variables, thereby obtaining more accurate calculation data, thereby realizing the unknown full-day network source scheduling.

[0027] The scheduling decision based on the time-sharing correspondence and classification correspondence includes: according to the total correspondence of [time-sharing, classification, output], the energy storage category and corresponding output data corresponding to each time period are prepaid in the layered energy storage structure, and finally the corresponding relationship model of [energy storage category, classification output data, time period] is obtained, and the scheduling decision is completed according to the model. By obtaining the corresponding relationship between the energy storage category, classification output data and time period, the prediction information of another parameter is obtained when only two arbitrary parameters are known, so as to accurately perform electricity or energy storage scheduling.

[0028] It should be understood that the embodiments are only used to illustrate the present invention and are not used to limit the scope of the present invention. In addition, it should be understood that after reading the content taught by the present invention, those skilled in the art can make various changes or modifications to the present invention, and these equivalent forms also fall within the scope limited by the appended claims of the application.

Claims

1. A time-sharing and classified energy storage regulation method, characterized in that: include: According to the historical output data of various types of energy storage in the network segment, the daily output data of the target network segment is obtained and divided into output time periods. According to the energy classification, the time-sharing correspondence between the daily output data and the time period and the classification correspondence between the daily output data and the energy storage category are established; A hierarchical energy storage structure is established within the network segment, and the energy storage layer makes adjustment decisions based on the time-sharing correspondence and classification correspondence.

2. A time-sharing and classified energy storage and regulation method according to claim 1, characterized in that: The corresponding relationship establishment process includes: obtaining the full-day output data W of the target network segment, performing time-sharing and energy classification processing on the total data, and obtaining the time-sharing output [Wa, Wb, Wc...Wn], where a~n represents the output period within the whole day; energy classification output [W1, W2, W3, W4], where 1~3 represent the main output categories, and 4 represents the common output of other categories; and then establishing sampling coordinates for the time-sharing output and classification output respectively.

3. A time-sharing and classified energy storage and regulation method according to claim 2, characterized in that: The sampling coordinate establishment process of the time-sharing output includes: taking the pre-established time period as the X-axis and the all-day output data W as the Z-axis, drawing a two-dimensional rectangular coordinate system according to the change of the all-day output data W in the pre-established time period, and obtaining the change slope Kn according to the curve in the coordinate system to obtain the corresponding relationship.

4. A time-sharing and classified energy storage and regulation method according to claim 2, characterized in that: The process of establishing sampling coordinates of energy classification output includes: taking the preset energy category as the y-axis and the full-day output data W as the z-axis, drawing a two-dimensional rectangular coordinate system according to the classification specific data of the full-day output data under different energy categories, and recording the data group to obtain the classification correspondence.

5. A time-sharing and classified energy storage and regulation method according to claim 2, 3 or 4, characterized in that: Also includes: With the pre-established time period as the X-axis and the preset energy category as the Y-axis, a two-dimensional rectangular coordinate system is established according to the output energy category and the output energy quantity within the pre-established time period, a preliminary corresponding relationship of time-sharing classification is obtained, and data is recorded.

6. A time-sharing and classified energy storage and regulation method according to claim 5, characterized in that: Also includes: All coordinate systems are combined according to the preliminary correspondence, time-sharing correspondence and classification correspondence to obtain a three-dimensional rectangular coordinate system with the pre-established time period as the X-axis, the energy category as the Y-axis and the full-day output data W as the Z-axis. Based on the recorded data information, the total correspondence of [time-sharing, classification, output] is obtained.

7. A time-sharing and classified energy storage and regulation method according to claim 1, characterized in that: The establishment of the layered energy storage structure includes: dividing the energy storage into 1 to 4 categories, where category 1 represents electric energy storage, category 2 represents photovoltaic energy storage, category 3 represents wind power energy storage, and category 4 represents other categories of total energy storage; the layered energy storage structure has a total of 5 layers, layers 1 and 2 are respectively for electric power and photovoltaic energy storage operations, layers 4 and 5 are respectively for wind power and other energy storage operations, and layer 3 is the scheduling layer of each energy storage layer.

8. A time-sharing and classified energy storage and regulation method according to claim 1, 6 or 7, characterized in that: The scheduling decision based on the time-sharing correspondence and the classification correspondence includes: according to the overall correspondence of [time-sharing, classification, output], the energy storage category and the corresponding output data of each time period are prepaid in the layered energy storage structure, and finally the correspondence model of [energy storage category, classification output data, time period] is obtained, and the adjustment decision is completed according to the model.

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