Distributed renewable energy access feeder-type microgrid control method and system

Abstract

The embodiment of the present application relates to the technical field of power grid control, and specifically discloses a feeder-type microgrid control method and system for distributed renewable energy access. The embodiment of the present application performs distributed analysis on the feeder-type microgrid, marks multiple regulated load sites, performs power consumption analysis, performs consumption distribution to generate consumption distribution data, performs consumption analysis to generate multiple consumption preferential information, and in multiple surplus time periods, respectively publishes and distributes the consumption preferential information in the multiple regulated load sites. The embodiment of the present application can mark multiple regulated load sites, perform consumption distribution to generate consumption distribution data, perform consumption analysis to generate multiple consumption preferential information, and in multiple surplus time periods, respectively publish and distribute the consumption preferential information in the multiple regulated load sites, without the need to build large-scale electric energy storage devices, thereby saving a large amount of construction cost, and effectively utilizing the existing devices to improve the utilization rate of clean energy.

Description

Technical Field

[0001] This invention belongs to the field of power grid control technology, and particularly relates to a control method and system for feeder-type microgrids with distributed renewable energy access. Background Technology

[0002] A microgrid is a small-scale power generation and distribution system composed of distributed power sources, energy storage devices, energy conversion devices, loads, monitoring and protection devices, etc. Microgrids enable the flexible and efficient application of distributed power sources, solve the grid connection problems of a large number and diverse range of distributed power sources, and promote the large-scale integration of distributed power sources and renewable energy through their use. This allows for highly reliable supply of various energy forms to loads, making it an effective way to realize an active distribution network and facilitate the transition from traditional power grids to smart grids.

[0003] Feeder-type microgrids with distributed renewable energy access are a type of microgrid. Existing feeder-type microgrids with distributed renewable energy access require the construction of multiple large-scale energy storage devices corresponding to the distributed renewable energy sources. When there is a surplus of electricity, the surplus electricity is stored. Although this can improve the utilization rate of clean energy, it requires a large construction cost and cannot effectively utilize existing equipment. Summary of the Invention

[0004] The purpose of this invention is to provide a control method and system for feeder-type microgrids with distributed renewable energy access, aiming to solve the problems mentioned in the background art.

[0005] To achieve the above objectives, the embodiments of the present invention provide the following technical solutions:

[0006] A control method for a feeder-type microgrid with distributed renewable energy access, the method specifically includes the following steps:

[0007] A distribution analysis was performed on the constructed feeder-type microgrid, and multiple regulating load locations were marked;

[0008] Electricity consumption analysis was performed on the constructed feeder-type microgrid to determine multiple surplus time periods, surplus rates, and surplus distribution areas;

[0009] According to the multiple surplus distribution areas, the multiple regulating load locations are allocated for absorption, and absorption allocation data is generated.

[0010] A absorption analysis is performed on multiple surplus rates, and multiple absorption incentive information is generated based on the absorption analysis results;

[0011] Based on the aforementioned load allocation data, during multiple surplus time periods, the release and allocation control of load allocation incentive information are carried out at multiple locations where loads are adjusted.

[0012] As a further limitation of the technical solution of this invention embodiment, the step of performing distribution analysis on the constructed feeder-type microgrid and marking multiple regulating load locations specifically includes the following steps:

[0013] Acquire grid data from a pre-built feeder microgrid;

[0014] Extract power grid distribution data from the power grid data;

[0015] The power grid distribution data is functionally identified and recorded to obtain functional identification information;

[0016] Based on the functional identification information, multiple locations for adjusting loads are marked.

[0017] As a further limitation of the technical solution of this invention embodiment, the step of performing power consumption analysis on the constructed feeder-type microgrid to determine multiple surplus time periods, surplus rates, and surplus distribution areas specifically includes the following steps:

[0018] Acquire historical power distribution data and type distribution data of the feeder-type microgrid;

[0019] Based on the type distribution data, filter the target distribution data for renewable energy;

[0020] Based on the target distribution data, extract the target distribution data for renewable energy from the historical distribution data;

[0021] Electricity consumption analysis is performed on the target power distribution data to determine multiple surplus time periods, surplus rates, and surplus distribution areas.

[0022] As a further limitation of the technical solution of this invention, the step of allocating the load to multiple regulating locations according to multiple surplus distribution areas and generating load allocation data specifically includes the following steps:

[0023] Calculate the adjustment distance between the multiple surplus distribution areas and the multiple adjustment load locations;

[0024] Arrange the multiple adjustment distances to generate distance arrangement information;

[0025] According to the distance arrangement information, the load distribution is performed on multiple locations to generate load distribution data.

[0026] As a further limitation of the technical solution of this embodiment of the invention, the step of performing absorption analysis on multiple surplus rates and generating multiple absorption incentive information based on the absorption analysis results specifically includes the following steps:

[0027] Based on the aforementioned consumption allocation data, multiple consumption scale indices corresponding to the surplus rates are determined;

[0028] The absorption environment of multiple load regulation sites is identified and analyzed to obtain multiple absorption environment indices;

[0029] By combining multiple absorption scale indices and corresponding absorption environment indices, multiple absorption prediction indices are generated;

[0030] Multiple consumption forecast indices are analyzed for preferential treatment to generate multiple consumption preferential information.

[0031] As a further limitation of the technical solution of this invention, the step of releasing and distributing preferential information on the load reduction and allocation according to the load reduction and allocation data in multiple surplus time periods and at multiple load adjustment locations specifically includes the following steps:

[0032] Based on the aforementioned power consumption and allocation data, determine the allocated power for multiple surplus time periods;

[0033] During multiple surplus periods, preferential information on load absorption is released to multiple load adjustment locations.

[0034] When multiple regulating load fields have an absorption response, corresponding allocation control is performed.

[0035] A feeder-type microgrid control system for distributed renewable energy access, the system comprising a distributed analysis and processing unit, a power consumption analysis and processing unit, a power consumption allocation and processing unit, a surplus power consumption analysis unit, and a power consumption release and control unit, wherein:

[0036] The distributed analysis processing unit is used to perform distributed analysis on the constructed feeder-type microgrid and mark multiple regulating load locations;

[0037] The power consumption analysis and processing unit is used to perform power consumption analysis on the constructed feeder-type microgrid to determine multiple surplus time periods, surplus rates, and surplus distribution areas.

[0038] The load allocation processing unit is used to allocate the load to multiple regulating load locations according to multiple surplus distribution areas, and generate load allocation data.

[0039] The surplus absorption analysis unit is used to perform absorption analysis on multiple surplus rates and generate multiple absorption incentive information based on the absorption analysis results.

[0040] The load release control unit is used to release and distribute load discount information in multiple surplus time periods and at multiple load adjustment locations according to the load allocation data.

[0041] As a further limitation of the technical solution of this embodiment of the invention, the distribution analysis and processing unit specifically includes:

[0042] The data acquisition module is used to acquire grid data of a pre-built feeder microgrid;

[0043] The data extraction module is used to extract power grid distribution data from the power grid data;

[0044] The identification and recording module is used to perform functional identification and recording on the power grid distribution data to obtain functional identification information;

[0045] The location marking module is used to mark multiple locations with adjustable loads based on the functional identification information.

[0046] As a further limitation of the technical solution of this embodiment of the invention, the absorption and distribution processing unit specifically includes:

[0047] The distance calculation module is used to calculate the adjustment distance between the multiple surplus distribution areas and the multiple adjustment load locations;

[0048] The distance arrangement module is used to arrange multiple adjustable distances to generate distance arrangement information;

[0049] The load allocation module is used to allocate the loads to multiple locations according to the distance arrangement information and generate load allocation data.

[0050] As a further limitation of the technical solution of this embodiment of the invention, the surplus absorption analysis unit specifically includes:

[0051] The scale index determination module is used to determine multiple consumption scale indices corresponding to the surplus rate based on the consumption allocation data.

[0052] The environmental index determination module is used to identify and analyze the absorption environment of multiple load regulation sites and obtain multiple absorption environment indices.

[0053] The prediction index generation module is used to integrate multiple absorption scale indices and corresponding absorption environment indices to generate multiple absorption prediction indices;

[0054] The information generation module is used to perform preferential analysis on multiple consumption forecast indices and generate multiple consumption preferential information.

[0055] Compared with the prior art, the beneficial effects of the present invention are:

[0056] This invention, through distributed analysis of a feeder-type microgrid, identifies multiple regulating load locations; performs electricity consumption analysis; allocates power consumption data; analyzes power consumption to generate multiple power consumption incentive information entries; and controls the dissemination and allocation of these incentive information entries at multiple regulating load locations during multiple surplus time periods. This method can identify multiple regulating load locations, allocate power consumption data, analyze power consumption to generate multiple power consumption incentive information entries, and then disseminate and allocate these incentive information entries at multiple regulating load locations during multiple surplus time periods. It eliminates the need for large-scale energy storage equipment, thus saving significant construction costs and effectively utilizing existing equipment, thereby improving the utilization rate of clean energy. Attached Figure Description

[0057] To more clearly illustrate the technical solutions in the embodiments of the present invention, the accompanying drawings used in the description of the embodiments or the prior art will be briefly introduced below. Obviously, the accompanying drawings described below are only some embodiments of the present invention.

[0058] Figure 1 A flowchart of the method provided by an embodiment of the present invention is shown.

[0059] Figure 2 A flowchart illustrating the distribution analysis of location marking in the method provided by an embodiment of the present invention is shown.

[0060] Figure 3 A flowchart illustrating the power consumption analysis of a microgrid in the method provided by an embodiment of the present invention is shown.

[0061] Figure 4 A flowchart of load location allocation in the method provided by an embodiment of the present invention is shown.

[0062] Figure 5 A flowchart illustrating the generation of discount information in the method provided by an embodiment of the present invention is shown.

[0063] Figure 6 A flowchart of information publishing and allocation control in the method provided by an embodiment of the present invention is shown.

[0064] Figure 7 An application architecture diagram of the system provided in an embodiment of the present invention is shown.

[0065] Figure 8 A structural block diagram of the distributed analysis and processing unit in the system provided by an embodiment of the present invention is shown.

[0066] Figure 9 A structural block diagram of the absorption and distribution processing unit in the system provided by an embodiment of the present invention is shown.

[0067] Figure 10The diagram shows the structural block diagram of the surplus absorption analysis unit in the system provided by the embodiment of the present invention. Detailed Implementation

[0068] To make the objectives, technical solutions, and advantages of this invention clearer, the invention will be further described in detail below with reference to the accompanying drawings and embodiments. It should be understood that the specific embodiments described herein are merely illustrative and not intended to limit the invention.

[0069] Understandably, a feeder-type microgrid with distributed renewable energy access is a type of microgrid. Existing feeder-type microgrids with distributed renewable energy access require the construction of multiple large-scale energy storage devices corresponding to the distributed renewable energy sources. When there is a surplus of electricity, the surplus electricity is stored. Although this can improve the utilization rate of clean energy, it requires a large construction cost and cannot effectively utilize existing equipment.

[0070] To address the aforementioned issues, this invention provides a solution by performing distribution analysis on a feeder-type microgrid, marking multiple regulating load locations; conducting electricity consumption analysis; performing load allocation to generate load allocation data; performing load analysis to generate multiple load discount information items; and disseminating and controlling the distribution of load discount information to multiple regulating load locations during multiple surplus time periods. This method can mark multiple regulating load locations, perform load allocation, generate load allocation data, perform load analysis, generate multiple load discount information items, and then disseminate and control the distribution of load discount information to multiple regulating load locations during multiple surplus time periods. It eliminates the need for large-scale energy storage equipment, thereby saving significant construction costs and effectively utilizing existing equipment, thus improving the utilization rate of clean energy.

[0071] Figure 1 A flowchart of the method provided by an embodiment of the present invention is shown.

[0072] Specifically, the control method for a feeder-type microgrid with distributed renewable energy access includes the following steps:

[0073] Step S101: Perform distribution analysis on the constructed feeder-type microgrid and mark multiple regulating load locations.

[0074] In this embodiment of the invention, a feeder-type microgrid for control analysis is determined. After the feeder-type microgrid is constructed, its grid data is stored. By acquiring the grid data of the pre-constructed feeder-type microgrid, the grid data is classified and analyzed. According to the classification and analysis results, grid distribution data is identified and extracted from the grid data. By performing distribution analysis on the grid distribution data, the distribution map of the feeder-type microgrid is determined. Based on the distribution map, the grid distribution data is functionally identified and recorded to obtain functional identification information. Then, based on the functional identification information, multiple regulating load locations are marked on the distribution map.

[0075] Specifically, in this embodiment of the invention, the location for adjusting the load can be a new energy vehicle charging parking lot, a hydrogen refueling parking lot, etc.

[0076] Specifically, Figure 2 A flowchart illustrating the distribution analysis of location marking in the method provided by an embodiment of the present invention is shown.

[0077] In a preferred embodiment of the present invention, the step of performing distribution analysis on the constructed feeder-type microgrid and marking multiple regulating load locations specifically includes the following steps:

[0078] Step S1011: Obtain grid data of the pre-built feeder microgrid.

[0079] Step S1012: Extract power grid distribution data from the power grid data.

[0080] Step S1013: Perform functional identification and recording on the power grid distribution data to obtain functional identification information.

[0081] Step S1014: Mark multiple load adjustment locations based on the functional identification information.

[0082] Furthermore, the control method for the feeder-type microgrid with distributed renewable energy access also includes the following steps:

[0083] Step S102: Perform power consumption analysis on the constructed feeder-type microgrid to determine multiple surplus time periods, surplus rates, and surplus distribution areas.

[0084] In this embodiment of the invention, during the use of the feeder-type microgrid, it is necessary to record relevant usage data, update and generate historical power distribution data and type distribution data, obtain the latest historical power distribution data and type distribution data of the feeder-type microgrid, analyze the type distribution data, determine the various energy types transmitted in the feeder-type microgrid, and mark the energy types that conform to renewable energy, then filter the target distribution data of renewable energy from the type distribution data, and then extract the target power distribution data of renewable energy from the historical power distribution data according to the target distribution data. By performing power consumption analysis on the target power distribution data, determine multiple surplus time periods, multiple corresponding surplus rates and multiple corresponding surplus distribution areas corresponding to the use of renewable energy.

[0085] Specifically, Figure 3 A flowchart illustrating the power consumption analysis of a microgrid in the method provided by an embodiment of the present invention is shown.

[0086] In a preferred embodiment of the present invention, the step of performing power consumption analysis on the constructed feeder-type microgrid to determine multiple surplus time periods, surplus rates, and surplus distribution areas specifically includes the following steps:

[0087] Step S1021: Obtain historical power distribution data and type distribution data of the feeder-type microgrid.

[0088] Step S1022: Based on the type distribution data, filter the target distribution data of renewable energy.

[0089] Step S1023: Extract target distribution data for renewable energy from the historical distribution data according to the target distribution data.

[0090] Step S1024: Perform electricity consumption analysis on the target power distribution data to determine multiple surplus time periods, surplus rates, and surplus distribution areas.

[0091] Furthermore, the control method for the feeder-type microgrid with distributed renewable energy access also includes the following steps:

[0092] Step S103: According to the multiple surplus distribution areas, the multiple regulating load locations are allocated for absorption, and absorption allocation data is generated.

[0093] In this embodiment of the invention, multiple surplus distribution origins corresponding to multiple surplus distribution areas are determined and marked, and multiple location origins corresponding to multiple regulating load locations are determined and marked. The distances between the multiple surplus distribution origins and the multiple location origins are measured and calculated to obtain multiple regulating distances. By arranging the multiple regulating distances, distance arrangement information is generated. Using the distance arrangement information as a reference, the multiple regulating load locations are allocated to generate allocation data.

[0094] Specifically, Figure 4 A flowchart of load location allocation in the method provided by an embodiment of the present invention is shown.

[0095] In a preferred embodiment of the present invention, the step of allocating the load to multiple regulating locations according to multiple surplus distribution areas and generating load allocation data specifically includes the following steps:

[0096] Step S1031: Calculate the adjustment distance between the multiple surplus distribution areas and the multiple adjustment load locations.

[0097] Step S1032: Arrange the multiple adjustment distances to generate distance arrangement information.

[0098] Step S1033: According to the distance arrangement information, the load distribution of the multiple regulating load locations is carried out to generate load distribution data.

[0099] Furthermore, the control method for the feeder-type microgrid with distributed renewable energy access also includes the following steps:

[0100] Step S104: Perform absorption analysis on the multiple surplus rates, and generate multiple absorption incentive information based on the absorption analysis results.

[0101] In this embodiment of the invention, based on the consumption allocation data, the relationship between multiple surplus rates and multiple regulating load locations is determined. Then, based on the charging or hydrogen refueling scale of the multiple regulating load locations, the consumption scale index corresponding to the multiple surplus rates is determined. Furthermore, by identifying the consumption environment of the multiple regulating load locations, the number of new energy vehicles that the multiple regulating load locations can attract is predicted, resulting in multiple consumption environment indices. By combining the multiple consumption scale indices and the corresponding consumption environment indices, multiple consumption prediction indices are generated. Finally, the multiple consumption prediction indices are used to perform preferential analysis, generating multiple consumption preferential information.

[0102] It is understandable that the consumption forecast index is the average of the corresponding consumption scale index and consumption environment index; the smaller the consumption forecast index, the greater the incentive, thus providing greater incentives to attract a wider range of vehicles to the corresponding load adjustment sites for charging or hydrogen refueling.

[0103] Specifically, Figure 5 A flowchart illustrating the generation of discount information in the method provided by an embodiment of the present invention is shown.

[0104] In a preferred embodiment of the present invention, the step of performing absorption analysis on multiple surplus rates and generating multiple absorption incentive information based on the absorption analysis results specifically includes the following steps:

[0105] Step S1041: Based on the absorption allocation data, determine the absorption scale index corresponding to multiple surplus rates.

[0106] Step S1042: Identify and analyze the absorption environment of multiple load regulation locations to obtain multiple absorption environment indices.

[0107] Step S1043: Combine the multiple absorption scale indices and the corresponding absorption environment indices to generate multiple absorption prediction indices.

[0108] Step S1044: Perform preferential analysis on the multiple consumption prediction indices to generate multiple consumption preferential information.

[0109] Furthermore, the control method for the feeder-type microgrid with distributed renewable energy access also includes the following steps:

[0110] Step S105: According to the consumption allocation data, the consumption discount information is released and allocated in multiple locations at multiple surplus time periods.

[0111] In this embodiment of the invention, based on the consumption allocation data, the allocated electricity for the surplus time periods corresponding to multiple regulating load sites is determined. Then, during the multiple surplus time periods, consumption incentive information is released to the multiple corresponding regulating load sites. The consumption incentive information can be sent to the mobile phones of new energy vehicle owners who meet the range conditions, prompting new energy vehicle owners near the regulating load sites to choose the regulating load sites for charging or hydrogen refueling, generating a consumption response. When multiple regulating load sites have a consumption response, corresponding allocation control is performed to realize direct power transmission or hydrogen production to the regulating load sites.

[0112] Specifically, Figure 6 A flowchart of information publishing and allocation control in the method provided by an embodiment of the present invention is shown.

[0113] In a preferred embodiment of the present invention, the step of publishing and distributing preferential information on the absorption and allocation of the absorption and allocation data in multiple surplus time periods at multiple load adjustment locations specifically includes the following steps:

[0114] Step S1051: Determine the allocated electricity for multiple surplus time periods according to the consumption and allocation data.

[0115] Step S1052: During the multiple surplus time periods, preferential information on load absorption is issued to multiple load adjustment locations respectively.

[0116] Step S1053: When multiple regulated load fields have an absorption response, perform corresponding allocation control.

[0117] Furthermore, Figure 7 An application architecture diagram of the system provided in an embodiment of the present invention is shown.

[0118] In another preferred embodiment of the present invention, the feeder-type microgrid control system for distributed renewable energy access includes:

[0119] The distributed analysis processing unit 101 is used to perform distributed analysis on the constructed feeder-type microgrid and mark multiple regulating load locations.

[0120] In this embodiment of the invention, a feeder-type microgrid for control analysis is determined. After the feeder-type microgrid is constructed, its grid data is stored. The distribution analysis processing unit 101 acquires the grid data of the pre-constructed feeder-type microgrid, performs data classification analysis on the grid data, identifies and extracts grid distribution data from the grid data according to the classification analysis results, and determines the distribution map of the feeder-type microgrid by performing distribution analysis on the grid distribution data. Based on the distribution map, the grid distribution data is functionally identified and recorded to obtain functional identification information. Then, based on the functional identification information, multiple regulating load locations are marked on the distribution map.

[0121] Specifically, Figure 8 A structural block diagram of the distributed analysis and processing unit 101 in the system provided by an embodiment of the present invention is shown.

[0122] In a preferred embodiment provided by the present invention, the distribution analysis and processing unit 101 specifically includes:

[0123] The data acquisition module 1011 is used to acquire grid data of a pre-built feeder microgrid.

[0124] The data extraction module 1012 is used to extract power grid distribution data from the power grid data.

[0125] The identification and recording module 1013 is used to perform functional identification and recording on the power grid distribution data to obtain functional identification information.

[0126] The location marking module 1014 is used to mark multiple locations with adjustable loads based on the functional identification information.

[0127] Furthermore, the feeder-type microgrid control system for distributed renewable energy access also includes:

[0128] The power consumption analysis and processing unit 102 is used to perform power consumption analysis on the constructed feeder-type microgrid to determine multiple surplus time periods, surplus rates, and surplus distribution areas.

[0129] In this embodiment of the invention, during the use of the feeder-type microgrid, it is necessary to record relevant usage data, update and generate historical power distribution data and type distribution data. The power consumption analysis and processing unit 102 obtains the latest historical power distribution data and type distribution data of the feeder-type microgrid, analyzes the type distribution data, determines the various energy types transmitted in the feeder-type microgrid, and marks the energy types that conform to renewable energy. Then, it filters the target distribution data of renewable energy from the type distribution data, and extracts the target power distribution data of renewable energy from the historical power distribution data according to the target distribution data. By performing power consumption analysis on the target power distribution data, it determines multiple surplus time periods, multiple corresponding surplus rates, and multiple corresponding surplus distribution areas corresponding to the use of renewable energy.

[0130] The load allocation processing unit 103 is used to allocate the load to multiple adjustable load locations according to multiple surplus distribution areas, and generate load allocation data.

[0131] In this embodiment of the invention, the absorption and allocation processing unit 103 determines and marks the surplus distribution origin corresponding to multiple surplus distribution areas, determines and marks the location origin corresponding to multiple regulating load locations, measures and calculates the distance between the multiple surplus distribution origins and the multiple location origins to obtain multiple regulating distances, arranges the multiple regulating distances to generate distance arrangement information, and uses the distance arrangement information as a reference to perform absorption and allocation on the multiple regulating load locations to generate absorption and allocation data.

[0132] Specifically, Figure 9 A structural block diagram of the absorption and distribution processing unit 103 in the system provided by an embodiment of the present invention is shown.

[0133] In a preferred embodiment of the present invention, the disposal and allocation processing unit 103 specifically includes:

[0134] The distance calculation module 1031 is used to calculate the adjustment distance between the multiple surplus distribution areas and the multiple adjustment load locations.

[0135] The distance arrangement module 1032 is used to arrange multiple adjustable distances to generate distance arrangement information.

[0136] The load distribution module 1033 is used to distribute the loads to multiple locations according to the distance arrangement information and generate load distribution data.

[0137] Furthermore, the feeder-type microgrid control system for distributed renewable energy access also includes:

[0138] The surplus absorption analysis unit 104 is used to perform absorption analysis on multiple surplus rates and generate multiple absorption incentive information based on the absorption analysis results.

[0139] In this embodiment of the invention, the surplus consumption analysis unit 104 determines the relationship between multiple surplus rates and multiple regulating load sites according to the consumption allocation data. Then, according to the charging or hydrogen refueling scale of multiple regulating load sites, it determines the consumption scale index corresponding to multiple surplus rates. Furthermore, by identifying the consumption environment of multiple regulating load sites, it predicts the number of new energy vehicles that multiple regulating load sites can attract, thereby obtaining multiple consumption environment indices. The surplus consumption analysis unit 104 integrates multiple consumption scale indices and corresponding consumption environment indices to generate multiple consumption prediction indices, and performs preferential analysis based on the multiple consumption prediction indices to generate multiple consumption preferential information.

[0140] Specifically, Figure 10 The diagram shows the structural block diagram of the surplus absorption analysis unit 104 in the system provided in the embodiment of the present invention.

[0141] In a preferred embodiment of the present invention, the surplus absorption analysis unit 104 specifically includes:

[0142] The scale index determination module 1041 is used to determine the scale index of multiple surplus rates based on the absorption allocation data.

[0143] The environmental index determination module 1042 is used to identify and analyze the absorption environment of multiple load regulation sites and obtain multiple absorption environment indices.

[0144] The prediction index generation module 1043 is used to integrate multiple absorption scale indices and corresponding absorption environment indices to generate multiple absorption prediction indices.

[0145] The information generation module 1044 is used to perform preferential analysis on multiple consumption prediction indices and generate multiple consumption preferential information.

[0146] Furthermore, the feeder-type microgrid control system for distributed renewable energy access also includes:

[0147] The load distribution control unit 105 is used to release and distribute load discount information in multiple locations at multiple surplus time periods according to the load distribution data.

[0148] In this embodiment of the invention, the power consumption release control unit 105 determines the allocated electricity for the surplus time periods corresponding to multiple regulating load sites according to the power consumption allocation data. Then, during the multiple surplus time periods, it releases power consumption incentive information to the multiple corresponding regulating load sites. The power consumption incentive information can be sent to the mobile phones of new energy vehicle owners who meet the range conditions, prompting new energy vehicle owners near the regulating load sites to choose the regulating load sites for charging or hydrogen refueling, generating a power consumption response. When multiple regulating load sites have a power consumption response, the corresponding allocation control is performed to realize direct power transmission or hydrogen production to the regulating load sites.

[0149] It should be understood that although the steps in the flowcharts of the various embodiments of the present invention are shown sequentially according to the arrows, these steps are not necessarily executed in the order indicated by the arrows. Unless explicitly stated herein, there is no strict order restriction on the execution of these steps, and they can be executed in other orders. Moreover, at least some steps in the various embodiments may include multiple sub-steps or multiple stages. These sub-steps or stages are not necessarily completed at the same time, but can be executed at different times. The execution order of these sub-steps or stages is not necessarily sequential, but can be performed alternately or in turn with other steps or at least a portion of the sub-steps or stages of other steps.

[0150] Those skilled in the art will understand that all or part of the processes in the above embodiments can be implemented by a computer program instructing related hardware. The program can be stored in a non-volatile computer-readable storage medium, and when executed, it can include the processes of the embodiments described above. Any references to memory, storage, databases, or other media used in the embodiments provided in this application can include non-volatile and / or volatile memory. Non-volatile memory can include read-only memory (ROM), programmable ROM (PROM), electrically programmable ROM (EPROM), electrically erasable programmable ROM (EEPROM), or flash memory. Volatile memory can include random access memory (RAM) or external cache memory. By way of illustration and not limitation, RAM is available in various forms, such as static RAM (SRAM), dynamic RAM (DRAM), synchronous DRAM (SDRAM), dual data rate SDRAM (DDRSDRAM), enhanced SDRAM (ESDRAM), synchronous link DRAM (SLDRAM), RAMbus direct RAM (RDRAM), direct memory bus dynamic RAM (DRDRAM), and RAMbus dynamic RAM (RDRAM), etc.

[0151] The technical features of the above embodiments can be combined in any way. For the sake of brevity, not all possible combinations of the technical features in the above embodiments are described. However, as long as there is no contradiction in the combination of these technical features, they should be considered to be within the scope of this specification.

[0152] The embodiments described above are merely illustrative of several implementations of the present invention, and while the descriptions are specific and detailed, they should not be construed as limiting the scope of the present invention. It should be noted that those skilled in the art can make various modifications and improvements without departing from the concept of the present invention, and these modifications and improvements all fall within the scope of protection of the present invention. Therefore, the scope of protection of this patent should be determined by the appended claims.

[0153] The above description is only a preferred embodiment of the present invention and is not intended to limit the present invention. Any modifications, equivalent substitutions, and improvements made within the spirit and principles of the present invention should be included within the protection scope of the present invention.

Claims

1. A control method for feeder-type microgrids with distributed renewable energy access, characterized in that, The method specifically includes the following steps: A distribution analysis was performed on the constructed feeder-type microgrid, and multiple regulating load locations were marked; Electricity consumption analysis was performed on the constructed feeder-type microgrid to determine multiple surplus time periods, surplus rates, and surplus distribution areas; According to the multiple surplus distribution areas, the multiple regulating load locations are allocated for absorption, and absorption allocation data is generated. A absorption analysis is performed on multiple surplus rates, and multiple absorption incentive information is generated based on the absorption analysis results; According to the aforementioned load allocation data, during multiple surplus time periods, the release and allocation control of load allocation incentive information is carried out at multiple load adjustment locations. Specifically, this process includes the following steps: Based on the aforementioned power consumption and allocation data, determine the allocated power for multiple surplus time periods; During multiple surplus periods, preferential information on load absorption is released to multiple load adjustment locations. When multiple regulating load fields have an absorption response, corresponding allocation control is performed; The step of performing absorption analysis on multiple surplus rates and generating multiple absorption incentive information based on the absorption analysis results specifically includes the following steps: Based on the aforementioned consumption allocation data, multiple consumption scale indices corresponding to the surplus rates are determined; The absorption environment of multiple load regulation sites is identified and analyzed to obtain multiple absorption environment indices; By combining multiple absorption scale indices and corresponding absorption environment indices, multiple absorption prediction indices are generated; Perform preferential analysis on multiple consumption forecast indices to generate multiple consumption preferential information; Based on the consumption allocation data, the relationship between multiple surplus rates and multiple regulating load sites is determined. Then, according to the charging or hydrogen refueling scale of multiple regulating load sites, the consumption scale index corresponding to multiple surplus rates is determined. Furthermore, by identifying the consumption environment of multiple regulating load sites, the number of new energy vehicles that multiple regulating load sites can attract is predicted, resulting in multiple consumption environment indices. The consumption prediction index is the average of the corresponding consumption scale index and consumption environment index. The smaller the consumption prediction index, the greater the incentive.

2. The control method for a feeder-type microgrid with distributed renewable energy access according to claim 1, characterized in that, The distribution analysis of the constructed feeder-type microgrid and the marking of multiple regulating load locations specifically include the following steps: Acquire grid data from a pre-built feeder microgrid; Extract power grid distribution data from the power grid data; The power grid distribution data is functionally identified and recorded to obtain functional identification information; Based on the functional identification information, multiple locations for adjusting loads are marked.

3. The feeder-type microgrid control method for distributed renewable energy access according to claim 1, characterized in that, The process of performing power consumption analysis on the constructed feeder-type microgrid to determine multiple surplus time periods, surplus rates, and surplus distribution areas specifically includes the following steps: Acquire historical power distribution data and type distribution data of the feeder-type microgrid; Based on the type distribution data, filter the target distribution data for renewable energy; Based on the target distribution data, extract the target distribution data for renewable energy from the historical distribution data; Electricity consumption analysis is performed on the target power distribution data to determine multiple surplus time periods, surplus rates, and surplus distribution areas.

4. The feeder-type microgrid control method for distributed renewable energy access according to claim 1, characterized in that, The step of allocating the load to multiple regulating locations according to multiple surplus distribution areas and generating load allocation data specifically includes the following steps: Calculate the adjustment distance between the multiple surplus distribution areas and the multiple adjustment load locations; Arrange the multiple adjustment distances to generate distance arrangement information; According to the distance arrangement information, the load distribution is performed on multiple locations to generate load distribution data.

5. A feeder-type microgrid control system for distributed renewable energy access, applied to the feeder-type microgrid control method for distributed renewable energy access as described in any one of claims 1-4, characterized in that, The system includes a distributed analysis and processing unit, a power consumption analysis and processing unit, a power consumption allocation and processing unit, a surplus power consumption analysis unit, and a power consumption release and control unit, wherein: The distributed analysis processing unit is used to perform distributed analysis on the constructed feeder-type microgrid and mark multiple regulating load locations; The power consumption analysis and processing unit is used to perform power consumption analysis on the constructed feeder-type microgrid to determine multiple surplus time periods, surplus rates, and surplus distribution areas. The load allocation processing unit is used to allocate the load to multiple regulating load locations according to multiple surplus distribution areas, and generate load allocation data. The surplus absorption analysis unit is used to perform absorption analysis on multiple surplus rates and generate multiple absorption incentive information based on the absorption analysis results. The load release control unit is used to release and distribute load discount information in multiple surplus time periods and at multiple load adjustment locations according to the load allocation data.

6. The feeder-type microgrid control system for distributed renewable energy access according to claim 5, characterized in that, The distribution analysis and processing unit specifically includes: The data acquisition module is used to acquire grid data of a pre-built feeder microgrid; The data extraction module is used to extract power grid distribution data from the power grid data; The identification and recording module is used to perform functional identification and recording on the power grid distribution data to obtain functional identification information; The location marking module is used to mark multiple locations with adjustable loads based on the functional identification information.

7. The feeder-type microgrid control system for distributed renewable energy access according to claim 6, characterized in that, The disposal and allocation processing unit specifically includes: The distance calculation module is used to calculate the adjustment distance between the multiple surplus distribution areas and the multiple adjustment load locations; The distance arrangement module is used to arrange multiple adjustable distances to generate distance arrangement information; The load allocation module is used to allocate the loads to multiple locations according to the distance arrangement information and generate load allocation data.

8. The feeder-type microgrid control system for distributed renewable energy access according to claim 6, characterized in that, The surplus absorption analysis unit specifically includes: The scale index determination module is used to determine multiple consumption scale indices corresponding to the surplus rate based on the consumption allocation data. The environmental index determination module is used to identify and analyze the absorption environment of multiple load regulation sites and obtain multiple absorption environment indices. The prediction index generation module is used to integrate multiple absorption scale indices and corresponding absorption environment indices to generate multiple absorption prediction indices; The information generation module is used to perform preferential analysis on multiple consumption forecast indices and generate multiple consumption preferential information.

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