A micro-grid-oriented distributed energy dynamic scheduling method and system

Abstract

The application relates to a micro-grid-oriented distributed energy dynamic scheduling method and system, and relates to the technical field of micro-grid scheduling. The application relates to a micro-grid-oriented distributed energy dynamic scheduling method and system, and relates to the technical field of micro-grid scheduling. The application relates to a micro-grid-oriented distributed energy dynamic scheduling method and system, and relates to the technical field of micro-grid scheduling. The application relates to a micro-grid-oriented distributed energy dynamic scheduling method and system, and relates to the technical field of micro-grid scheduling. The application relates to a micro-grid-oriented distributed energy dynamic scheduling method and system, and relates to the technical field of micro-grid scheduling. The application relates to a micro-grid-oriented distributed energy dynamic scheduling method and system, and relates to the technical field of micro-grid scheduling. The application relates to a micro-grid-oriented distributed energy dynamic scheduling method and system, and relates to the technical field of micro-grid scheduling. The application relates to a micro-grid-oriented distributed energy dynamic scheduling method and system, and relates to the technical field of micro-grid scheduling. The application relates to a micro-grid-oriented distributed energy dynamic scheduling method and system, and relates to the technical field of micro-grid scheduling. The application relates to a micro-grid-oriented distributed energy dynamic scheduling method and system, and relates to the technical field of micro-grid scheduling. The application relates to a micro-grid-oriented distributed energy dynamic scheduling method and system, and relates to the technical field of micro-grid scheduling. The application relates to a micro-grid-oriented distributed energy dynamic scheduling method and system, and relates to the technical field of micro-grid scheduling. The application relates to a micro-grid-oriented distributed energy dynamic scheduling method and system, and relates to the technical field of micro-grid scheduling. The application relates to a micro-grid-oriented distributed

Description

Technical Field

[0001] This invention relates to the field of microgrid dispatching technology, and in particular to a method and system for dynamic dispatching of distributed energy resources for microgrids. Background Technology

[0002] A microgrid is a small-scale power system consisting of distributed power sources, energy storage devices, local loads, and control and protection systems. Microgrids improve the reliability and security of power supply in local areas and are suitable for remote areas, industrial parks, or scenarios with high requirements for power supply reliability.

[0003] When scheduling a microgrid, it is generally necessary to first collect and monitor data such as distributed power sources, energy storage devices, local loads, and the status of the main grid in real time, so as to make short-term forecasts of the load and the main grid. Then, based on the forecast results, the grid-connected or islanded operation mode is determined. Subsequently, with the goals of economy, environmental protection, and reliability, an optimized scheduling scheme is formulated under the conditions of power balance and equipment constraints. Then, the scheme is converted into equipment control commands and executed. Finally, the operation strategy is dynamically adjusted according to the real-time deviation between the forecast and the actual output and the fault situation to ensure stable power supply to the microgrid.

[0004] Because the output of renewable energy sources such as photovoltaics is greatly affected by weather, short-term forecasting errors may lead to power imbalances, resulting in significant errors when scheduling microgrids. Summary of the Invention

[0005] To facilitate precise scheduling of microgrids, this invention provides a method and system for dynamic scheduling of distributed energy resources in microgrids.

[0006] In a first aspect, the present invention provides a method for dynamic scheduling of distributed energy resources in microgrids, employing the following technical solution:

[0007] A distributed energy dynamic dispatch method for microgrids includes:

[0008] Real-time collection of distributed power source data, energy storage device data, local load data, and main power grid operation data;

[0009] Demand operation mode is determined based on the distributed power source data, the energy storage device data, the local load data, and the main power grid operation data;

[0010] Retrieve the environmental conditions of the energy storage location from the data of the energy storage device;

[0011] Retrieve the power source location and environmental information from the distributed power source data;

[0012] Environmental scheduling impact information is generated by combining the environmental conditions of the power source location and the environmental conditions of the energy storage location;

[0013] The scheduling control information is generated by combining the environmental scheduling impact information with the demand operation mode, and then output to perform energy scheduling.

[0014] Optionally, the method for generating the environmental scheduling impact information includes:

[0015] Retrieve the power environment type and power environment parameters from the power location environment;

[0016] When the power environment type is consistent with the preset power generation reference environment type, the energy storage environment type and energy storage environment parameters are retrieved from the energy storage location environment.

[0017] The environmental difference value is determined based on the power environment type and the energy storage environment type;

[0018] An environmental difference fluctuation curve is generated based on the environmental difference value, the power supply environment parameters, and the energy storage environment parameters.

[0019] Differential fluctuation scheduling information is generated based on the environmental differential fluctuation curve, and the differential fluctuation scheduling information is used as the environmental scheduling impact information.

[0020] Optionally, the method for generating the differential fluctuation scheduling information includes:

[0021] Retrieve the power source location point from the aforementioned power source location environment conditions;

[0022] Retrieve the energy storage location point from the environmental conditions of the energy storage location;

[0023] A position fluctuation reference curve is generated by combining the power source location point and the energy storage location point;

[0024] The curve deviation value and the curve deviation location point are determined based on the environmental difference fluctuation curve and the location fluctuation reference curve.

[0025] Determine the numerical values ​​of the deviation positions based on the curve deviation position points;

[0026] Based on the numerical values ​​of the deviation positions and the curve deviation values, curve deviation scheduling information is generated, and the curve deviation scheduling information is used as the difference fluctuation scheduling information.

[0027] Optionally, the method for generating the position fluctuation reference curve includes:

[0028] The transmission path information is determined based on the power source location and the energy storage location.

[0029] Retrieve the bend points along the path from the transmission path information;

[0030] Based on the transmission path information and preset fluctuation impact characteristics, the location points of influence around the path are identified;

[0031] Calculate the distance between the bend points along the path and the surrounding points that influence the path, and use this distance as the bend influence distance value;

[0032] The length of the affected path is generated based on the influence location points around the path and the distance value of the bending influence;

[0033] Calculate the distance between the power source location point and the energy storage location point and use it as the power source energy storage distance value;

[0034] A fluctuation distance prediction curve is generated by combining the influence path length value and the power storage distance value, and the fluctuation distance prediction curve is used as the location fluctuation reference curve.

[0035] Optionally, the method for generating the path length value includes:

[0036] Retrieve the impact type from the surrounding impact points of the path;

[0037] Determine the baseline distance value for the impact based on the impact type;

[0038] The influence reference range is determined based on the distance between the influence location points around the path and the influence reference value;

[0039] When the bending impact distance value is greater than the impact reference distance value, the transmission path information is selected for coverage based on the impact reference range to form impact coverage path information;

[0040] The influence coverage path length value is retrieved from the influence coverage path information, and the influence coverage path length value is used as the influence path length value.

[0041] Optionally, the method for generating the path length value further includes:

[0042] When the bending impact distance value is not greater than the impact reference distance value, the bending coverage range is determined by combining the impact location points around the path with the bending impact distance value.

[0043] The bend coverage area and the bend location points along the path are selected to bend the edge of the bend coverage area.

[0044] The edge distance value is determined based on the location point of the bent coverage edge and the bent coverage range;

[0045] The edge range increment is determined based on the edge distance value;

[0046] The bending coverage area is adjusted by increasing the value of the edge range to form a bending adjustment range;

[0047] The transmission path information is selected for coverage based on the bending adjustment range to form bending coverage path information;

[0048] The bending coverage path length value is retrieved from the bending coverage path information, and the bending coverage path length value is used as the influence path length value.

[0049] Optionally, the method for generating the fluctuation distance prediction curve includes:

[0050] The initial values ​​of the fluctuation frequency and fluctuation amplitude are determined based on the power storage distance value.

[0051] Calculate the ratio between the influence path length value and the power storage distance value, and use it as the influence path ratio value;

[0052] Determine the proportional frequency adjustment value and the proportional amplitude adjustment value based on the aforementioned influence path proportional value;

[0053] The initial value of the fluctuation frequency is adjusted based on the proportional frequency adjustment value to form a fluctuation frequency correction value;

[0054] The initial value of the fluctuation range is adjusted based on the proportional amplitude adjustment value to form a fluctuation range correction value;

[0055] The fluctuation frequency correction value and the fluctuation amplitude correction value are curve-based to form the fluctuation distance prediction curve.

[0056] Optionally, the method for generating the curve deviation scheduling information includes:

[0057] The type of deviation is determined based on the location of the deviation point on the curve.

[0058] Determine the reference value for the type unit based on the aforementioned deviation type;

[0059] Calculate the product between the curve deviation value and the type unit reference value, and use it as the curve deviation reference value;

[0060] When the number of deviation positions is greater than the preset number of deviation references, the difference between the number of deviation positions and the preset number of deviation references is calculated and used as the number deviation value.

[0061] A reference value for the number deviation is determined based on the aforementioned number deviation value;

[0062] Calculate the sum between the curve deviation reference value and the number deviation reference value, and use it as a comprehensive reference value for multiple numbers;

[0063] Multiple number scheduling information is determined based on the comprehensive reference values ​​of the multiple numbers, and the multiple number scheduling information is used as the curve deviation scheduling information.

[0064] Optionally, the method for generating the curve deviation scheduling information further includes:

[0065] When the number of deviation positions is not greater than the preset number of deviation references, the deviation time point is determined based on the curve deviation value.

[0066] The adjacent interval time value is determined based on the aforementioned deviation time point;

[0067] Determine the interval time reference value based on the adjacent interval time value;

[0068] Calculate the sum between the interval time reference value and the curve deviation reference value, and use it as a small number of comprehensive reference values;

[0069] Based on the aforementioned comprehensive reference values, the scheduling information for the fewest individuals is determined, and this scheduling information is used as the curve deviation scheduling information.

[0070] Secondly, the present invention provides a distributed energy dynamic dispatching system for microgrids, employing the following technical solution:

[0071] A distributed energy dynamic dispatch system for microgrids includes:

[0072] The data acquisition module is used to collect data from distributed power sources, energy storage devices, local loads, and the main power grid.

[0073] The memory stores a program for implementing a distributed energy dynamic dispatching method for microgrids as described in any one of the first aspects;

[0074] The processor loads and executes programs stored in memory.

[0075] In summary, the present invention has at least one of the following beneficial technical effects:

[0076] 1. By collecting distributed power source data, energy storage device data, local load data, and main grid operation data in real time and determining the demand operation mode, and by retrieving the environmental conditions of the power source location and the energy storage location respectively to determine the environmental scheduling impact information, and then generating scheduling control information based on the environmental scheduling impact information and the demand operation mode and outputting it for energy scheduling, the scheduling can be adjusted in real time according to the weather conditions, which facilitates precise scheduling of the microgrid.

[0077] 2. By retrieving the power environment type and parameters from the power source location environment, when the power environment type is consistent with the preset power generation benchmark environment type, the power environment type and energy storage environment parameters are retrieved, and the environmental difference value is determined by the power environment type and energy storage environment type. Then, an environmental difference fluctuation curve is generated by the environmental difference value, power environment parameters and energy storage environment parameters. The environmental difference fluctuation curve is used to generate difference fluctuation scheduling information and serve as environmental scheduling impact information, thereby improving the accuracy of the obtained environmental scheduling impact information.

[0078] 3. By retrieving power source location points from the environmental conditions of the power source location and energy storage location points from the environmental conditions of the energy storage location, and then combining them to generate a location fluctuation reference curve, the curve deviation value and curve deviation location point are determined by comparing the environmental difference fluctuation curve with the location fluctuation reference curve. The number of deviation locations is determined by the number of deviation locations, and then the curve deviation scheduling information is generated by combining the number of deviation locations with the curve deviation value and used as the difference fluctuation scheduling information, thereby improving the accuracy of the obtained difference fluctuation scheduling information. Attached Figure Description

[0079] Figure 1 This is a flowchart of a method for dynamic scheduling of distributed energy resources for microgrids.

[0080] Figure 2 This is a flowchart illustrating the method for generating environmental scheduling impact information.

[0081] Figure 3 This is a flowchart of the method for generating differential fluctuation scheduling information. Detailed Implementation

[0082] The present invention will now be described in further detail with reference to the accompanying drawings and embodiments.

[0083] A dynamic dispatching method for distributed energy resources in microgrids is proposed. This method collects distributed power source data, energy storage device data, local load data, and main grid operation data in real time to determine the demand operation mode. It also retrieves environmental conditions at the power source location and energy storage location, and analyzes the environmental dispatching impact information based on the distance between the power source location and energy storage location, as well as the bend location. Then, it generates dispatching control information based on the environmental dispatching impact information and the demand operation mode, and outputs it for energy dispatching. This allows for real-time adjustments to the dispatching based on weather conditions, facilitating precise dispatching of the microgrid.

[0084] Reference Figure 1 This invention discloses a method for dynamic scheduling of distributed energy resources in microgrids, comprising:

[0085] S1: Real-time collection of distributed power source data, energy storage device data, local load data, and main power grid operation data.

[0086] Distributed power generation data refers to the operating status, output characteristics, and related environmental parameters of various distributed generation devices within a microgrid. Distributed power generation data is obtained by collecting data from these devices.

[0087] Energy storage device data refers to data such as the operating status, energy storage and conversion capabilities of energy storage devices within a microgrid. Energy storage device data is obtained through data collection from energy storage devices.

[0088] Local load data refers to the historical power consumption data of all electrical devices within the coverage area of ​​a microgrid (such as communities, industrial parks, and islands). Local load data is obtained by collecting data from devices such as smart meters or edge computing gateways within the microgrid's coverage area.

[0089] Main grid operation data refers to the operating status of the external main grid connected to the microgrid and the interaction data between the main grid and the microgrid. Main grid operation data is obtained by querying the main grid's energy management system.

[0090] S2: Determine the demand operation mode based on distributed power source data, energy storage device data, local load data, and main grid operation data.

[0091] Among them, the demand operation mode refers to the mode corresponding to the operation of the microgrid.

[0092] By analyzing distributed power source data, energy storage device data, and local load data, the supply and demand balance within the microgrid is determined. Then, based on the main grid operation data and preset decision objectives and constraints, it is determined whether the main grid needs to be connected, thereby determining the grid-connected mode or off-grid mode as the demand operation mode.

[0093] The preset decision-making objectives include economic requirements, reliability requirements, safety requirements, and environmental protection requirements. The preset constraints include power balance constraints, equipment safety constraints, and main grid interaction constraints.

[0094] S3: Retrieve the environmental conditions of the energy storage location from the energy storage device data.

[0095] Among them, the environmental conditions of the energy storage location refer to the type and parameters of the weather conditions surrounding the location of the energy storage device. Energy storage device data includes the environmental conditions of the energy storage location.

[0096] By retrieving data from the energy storage device to obtain information about the energy storage location and environment, it becomes easier to use the energy later.

[0097] S4: Retrieve the location and environmental conditions of the power source from the distributed power source data.

[0098] Among them, the environmental conditions of the power source location refer to the type and parameters of the weather conditions surrounding the location of the distributed power source. Distributed power source data includes environmental conditions of the power source location.

[0099] By retrieving the location and environmental information of the power source through distributed power data, it is convenient for subsequent use.

[0100] S5: Generate environmental scheduling impact information by combining the environmental conditions of the power source location and the energy storage location.

[0101] Among them, environmental dispatch impact information refers to the impact information corresponding to the need to adjust the dispatch based on the environment in which distributed power sources and energy storage devices are located.

[0102] By analyzing the environmental conditions of the power source location and the energy storage location, environmental scheduling impact information is generated, which facilitates subsequent use.

[0103] S6: Generates scheduling control information based on environmental scheduling impact information and demand operation mode, and outputs the scheduling control information for energy scheduling.

[0104] Among them, dispatch control information refers to the control information used to control the operation of the microgrid.

[0105] By combining environmental scheduling impact information with demand operation mode, specific scheduling parameters are adjusted according to the demand operation mode using environmental scheduling impact information to form scheduling control information, and the scheduling control information is output for energy scheduling. This allows for real-time adjustment of scheduling based on weather conditions, facilitating precise scheduling of the microgrid.

[0106] To further ensure the rationality of environmental scheduling impact information, it is necessary to conduct further separate analysis and calculation of the environmental scheduling impact information, which will be explained in detail through the following steps.

[0107] Reference Figure 2 The method for generating environmental scheduling impact information includes the following steps:

[0108] S51: Retrieve power environment type and power environment parameters from power location environment information.

[0109] Among them, the power environment type refers to the type of weather around the location of the distributed power source, and the power environment parameters refer to the parameters of the weather around the location of the distributed power source. The environmental conditions of the power source location include the power environment type and the power environment parameters.

[0110] The power supply location and environment conditions are used to retrieve the power supply environment type and parameters, which facilitates subsequent use.

[0111] S52: When the power supply environment type is consistent with the preset power generation reference environment type, retrieve the energy storage environment type and energy storage environment parameters from the energy storage location environment.

[0112] The power generation baseline environment type refers to the environmental type that allows for normal power generation. The power generation baseline environment type is obtained through pre-input.

[0113] Energy storage environment type refers to the type of weather conditions surrounding the location of the energy storage device, while energy storage environment parameters refer to the parameters of the weather conditions surrounding the location of the energy storage device. The environmental conditions of the energy storage location include both the energy storage environment type and the energy storage environment parameters.

[0114] The energy storage environment type and parameters can be retrieved based on the location and environmental conditions of the energy storage site, making it convenient for subsequent use.

[0115] S53: Determine the environmental difference value based on the power supply environment type and the energy storage environment type.

[0116] Among them, the environmental difference value refers to the degree of difference between the types of weather conditions surrounding the distributed power source and the energy storage device.

[0117] By inputting the power environment type and energy storage environment type into a preset environment type database, the power environment type index and energy storage environment type index are obtained through matching. Then, the difference between the power environment type index and the energy storage environment type index is calculated to obtain the environment difference value, which is convenient for subsequent use.

[0118] Different environment types correspond to different environment type indices. The environment type database pre-stores a mapping table of different environment types and their corresponding environment type indices, and the environment type database is preset by the operator according to actual needs.

[0119] S54: Generate environmental difference fluctuation curves based on environmental difference values, power supply environment parameters, and energy storage environment parameters.

[0120] Among them, the environmental difference fluctuation curve refers to the curve corresponding to the fluctuation changes in the environmental weather around the distributed power source and the energy storage device.

[0121] By calculating the difference between parameters of the same type in the power supply environment parameters and energy storage environment parameters, and performing normalization processing to form the initial value of the real-time environment, the initial value of the real-time environment is then adjusted according to the environmental difference value, and an environmental difference fluctuation curve is generated based on the time series.

[0122] For example, when both the power supply environment parameters and the energy storage environment parameters include temperature and humidity parameters, the temperature difference between the power supply environment parameters and the energy storage environment parameters is calculated to obtain the temperature difference. Then, the humidity difference between the power supply environment parameters and the energy storage environment parameters is calculated to obtain the humidity difference. Finally, the temperature difference and humidity difference are weighted and normalized to form the initial real-time environmental value. The weighting coefficients in the weighted normalization process are preset by the operator according to actual needs.

[0123] S55: Generate differential fluctuation scheduling information based on the environmental differential fluctuation curve, and use the differential fluctuation scheduling information as environmental scheduling impact information.

[0124] Among them, differential fluctuation scheduling information refers to the scheduling information corresponding to the scheduling of microgrid operation based on the fluctuation of environmental differences.

[0125] By analyzing environmental variation fluctuation curves, variation fluctuation scheduling information is generated, and this information is used as environmental scheduling impact information to improve the accuracy of the obtained environmental scheduling impact information.

[0126] To further ensure the rationality of the differential fluctuation scheduling information, it is necessary to perform further separate analysis and calculation on the differential fluctuation scheduling information, which will be explained in detail through the following steps.

[0127] Reference Figure 3 The method for generating differential fluctuation scheduling information includes the following steps:

[0128] S551: Retrieve the power location point from the power location environment.

[0129] Here, the power source location refers to the location of the distributed power source. The environmental conditions of the power source location include the power source location.

[0130] The power supply location can be retrieved based on the environmental conditions to facilitate subsequent use.

[0131] S552: Retrieve energy storage location points from the environmental conditions of the energy storage location.

[0132] Here, the energy storage location refers to the location of the energy storage device. The environmental conditions of the energy storage location include the energy storage location itself.

[0133] The location of the energy storage facility can be retrieved based on the environmental conditions of the energy storage location, making it convenient for subsequent use.

[0134] S553: ​​Generates a position fluctuation baseline curve by combining the power source location point and the energy storage location point.

[0135] Among them, the location fluctuation baseline curve refers to the baseline curve corresponding to the location fluctuation of distributed power sources and energy storage devices when the weather changes.

[0136] By analyzing the power source location and energy storage location, a location fluctuation baseline curve is generated for convenient subsequent use.

[0137] To further ensure the rationality of the position fluctuation baseline curve, it is necessary to perform further separate analysis and calculation on the position fluctuation baseline curve, which will be explained in detail through the steps shown below.

[0138] The method for generating the position fluctuation baseline curve includes the following steps:

[0139] S5531: Determine the transmission path information based on the power source location and the energy storage location.

[0140] Among them, transmission path information refers to the path information that needs to be taken when transmitting from distributed power sources to energy storage devices.

[0141] By inputting the power source location and energy storage location into a preset path database, transmission path information can be obtained through matching, which facilitates subsequent use.

[0142] The path database pre-stores a lookup table of different power source locations, energy storage locations, and their corresponding transmission path information. The path database is retrieved after the operator inputs the information in advance.

[0143] S5532: Retrieve the bend points along the path from the transmission path information.

[0144] Among them, the path bend locations refer to the locations where there are bends in the path. The transmitted path information includes the path bend locations.

[0145] By retrieving locations with bends from the transmission path information and using them as bend points along the path, it becomes easier to use them later.

[0146] S5533: Identify the location points of influence around the path based on the transmission path information and the preset fluctuation influence characteristics.

[0147] Among them, fluctuation impact characteristics refer to the features of buildings and vegetation around the transmission path that can have a fluctuation impact on energy dispatch. Fluctuation impact characteristics are obtained after pre-input. Fluctuation impact characteristics include narrow gaps between buildings that easily generate convection, tall and densely foliaged trees, etc.

[0148] The location points around the path that affect energy dispatch are the locations around the path that cause fluctuations in energy dispatch.

[0149] By matching the preset fluctuation impact characteristics with the surrounding conditions of the transmission path information, and taking the matching locations as the impact points around the path, it is convenient for subsequent use.

[0150] S5534: Calculate the distance between the bend points along the path and the surrounding points that affect the path, and use this distance as the bend influence distance value.

[0151] Among them, the bending impact distance value refers to the distance between the bending point along the path and the surrounding impact points.

[0152] The distance between the bend points along the path and the surrounding points that affect the path is calculated and used as the bend influence distance value for convenient subsequent use.

[0153] S5535: Generate the influence path length value based on the influence location points around the path and the influence distance value of the bend.

[0154] The impact path length value refers to the path length corresponding to the impact on the transmission path.

[0155] By analyzing the influence points around the path and the distance values ​​of the bends, the length value of the affected path is generated for subsequent use.

[0156] To further ensure the rationality of the impact path length value, it is necessary to perform a further separate analysis and calculation on the impact path length value, which will be explained in detail through the steps shown below.

[0157] The methods that affect the generation of path length values ​​include the following steps:

[0158] S55351: Retrieve the impact type from the surrounding impact location points of the path.

[0159] The impact type refers to the type of fluctuation in energy dispatch caused by surrounding points along the path. The impact type can be either buildings or vegetation.

[0160] The type of influence can be retrieved by identifying the location points around the path, which facilitates subsequent use.

[0161] S55352: Determine the baseline distance value for impact based on the type of impact.

[0162] The impact baseline distance value refers to the maximum impact distance generated by an impact type. Different impact types correspond to different impact baseline distance values.

[0163] By inputting the impact type into the preset impact baseline distance database, the impact baseline distance value is obtained for easy subsequent use.

[0164] The impact baseline distance database pre-stores a lookup table of different impact types and their corresponding impact baseline distance values. The impact baseline distance database is retrieved by the operator through input.

[0165] S55353: Determine the influence benchmark range based on the distance between the influence location points around the path and the influence benchmark.

[0166] The influence baseline range refers to the baseline range covered by the influence points around the path when they exert their influence.

[0167] By using the points around the path that influence the location as the center and the distance to the influence reference as the radius, a circular coverage area is formed and used as the influence reference range for convenient subsequent use.

[0168] S55354: When the bending impact distance value is greater than the impact reference distance value, the transmission path information is selected based on the impact reference range to form the impact coverage path information.

[0169] Among them, the impact coverage path information refers to the straight-line path corresponding to the affected area after it is covered.

[0170] When the bending impact distance value is greater than the impact reference distance value, it means that only the straight path is covered. Therefore, the impact coverage path information is formed by selecting the part of the path covered by the impact reference range in the transmission path information, which is convenient for subsequent use.

[0171] S55355: Retrieve the influence coverage path length value from the influence coverage path information and use the influence coverage path length value as the influence path length value.

[0172] The affected coverage path length value refers to the length of the path corresponding to the coverage area affected. The affected coverage path information includes the affected coverage path length value.

[0173] By retrieving the influence coverage path length value from the influence coverage path information and using the influence coverage path length value as the influence path length value, the accuracy of the obtained influence path length value is improved.

[0174] S553541: When the distance affected by the bend is not greater than the distance affected by the baseline, the bend coverage area is determined by combining the surrounding affected locations and the distance affected by the bend.

[0175] The bending coverage area refers to the area that is also covered by the bending part.

[0176] When the distance affected by the bend is not greater than the distance affected by the baseline, it means that the bend location is also covered.

[0177] By using the points around the path that influence the location as the center and the distance of the bend as the radius, a circular coverage area is formed and used as the bend coverage area, which is convenient for subsequent use.

[0178] S553542: Select the edge location of the bend coverage area based on the bend location points along the path.

[0179] Among them, the bending coverage edge location point refers to the bending location point of other path routes that are located within the bending coverage area and close to the edge area.

[0180] By selecting the bend points along the path within the bend coverage area as initial selection points, and then selecting the initial selection point corresponding to the maximum distance between the bend points and the surrounding affected points as the selection edge points of the bend coverage area, it is convenient for subsequent use.

[0181] S553543: Determine the edge distance value based on the location point of the bend coverage edge and the bend coverage area.

[0182] The edge distance value refers to the distance between the location of the bend coverage edge and the nearest edge of the bend coverage area.

[0183] The nearest edge of the bend coverage area is determined by the location of the bend coverage edge, and the distance between the two is calculated as the edge distance value for convenient subsequent use.

[0184] S553544: Determine the edge range increment based on the edge distance value.

[0185] The edge range increment refers to the increase value required when the range needs to be expanded. Increasing the edge distance value will lead to an increase in the edge range increment value.

[0186] The calculation is performed by multiplying the edge distance value with a preset increment factor, and the result is used as the edge range increment for convenient subsequent use.

[0187] The increment factor is a proportional parameter used to convert edge distance values ​​into edge range increment values. The increment factor is preset by the operator according to actual needs.

[0188] S553545: Adjust the bend coverage area by increasing the edge range value to form a bend adjustment range.

[0189] The bending adjustment range refers to the range corresponding to the bending coverage area after adjustment.

[0190] By adding an edge range increment to the radius corresponding to the bending coverage area, a new range is formed and used as the bending adjustment range for convenient subsequent use.

[0191] S553546: Based on the bending adjustment range, the transmission path information is selected to form bending coverage path information.

[0192] Among them, the bend coverage path information refers to the bend path corresponding to the affected area after coverage.

[0193] By selecting a portion of the transmission path information that is subject to bending adjustment and using it as the bending coverage path information, it is convenient for subsequent use.

[0194] S553547: Retrieve the bending coverage path length value from the bending coverage path information, and use the bending coverage path length value as the influencing path length value.

[0195] The bend coverage path length value refers to the length of the bend path that is being covered. The bend coverage path information includes the bend coverage path length value.

[0196] By retrieving the length value of the bend coverage path through the bend coverage path information, and using the bend coverage path length value as the influencing path length value, the accuracy of the obtained influencing path length value is improved.

[0197] S5536: Calculate the distance between the power source location point and the energy storage location point and use it as the power source energy storage distance value.

[0198] Among them, the power source energy storage distance value refers to the distance between the power source location point and the energy storage location point.

[0199] The distance between the power source location and the energy storage location is calculated and used as the power storage distance value for future use.

[0200] S5537: Generate a fluctuation distance prediction curve by influencing the path length value and the power storage distance value, and use the fluctuation distance prediction curve as the location fluctuation reference curve.

[0201] Among them, the fluctuation distance prediction curve refers to the curve that predicts the fluctuation situation based on the influence distance and the distance between the power source and the energy storage.

[0202] By analyzing the influence path length and power storage distance, a fluctuation distance prediction curve is generated, which is then used as the location fluctuation reference curve, thereby improving the accuracy of the obtained location fluctuation reference curve.

[0203] To further ensure the rationality of the fluctuation distance prediction curve, it is necessary to perform further separate analysis and calculation on the fluctuation distance prediction curve, which will be explained in detail through the steps shown below.

[0204] The method for generating the fluctuation distance prediction curve includes the following steps:

[0205] S55371: Determine the initial values ​​of fluctuation frequency and fluctuation amplitude based on the power storage distance.

[0206] Among them, the initial value of fluctuation frequency refers to the initial number of fluctuations per unit time under the power storage distance value, and the initial value of fluctuation amplitude refers to the initial amplitude value of fluctuations under the power storage distance value.

[0207] Different power storage distances correspond to different initial values ​​for fluctuation frequency and fluctuation amplitude. As the power storage distance increases, the initial value of fluctuation frequency decreases, while the initial value of fluctuation amplitude first decreases and then increases.

[0208] By inputting the power storage distance value into a preset initial fluctuation database, the initial values ​​of fluctuation frequency and fluctuation amplitude are obtained for easy subsequent use.

[0209] The initial fluctuation database pre-stores different power storage distance values ​​and their corresponding initial fluctuation frequency and amplitude values. The operator obtains and stores the corresponding initial fluctuation frequency and amplitude values ​​by experimenting with different power storage distance values.

[0210] S55372: Calculate the ratio between the influence path length value and the power storage distance value and use it as the influence path ratio value.

[0211] Among them, the influence path ratio value refers to the ratio between the influence path length value and the power storage distance value.

[0212] Calculating the proportion of the impact path facilitates subsequent use.

[0213] S55373: Determine the proportional frequency adjustment value and proportional amplitude adjustment value based on the proportional value of the influence path.

[0214] The influence path ratio value refers to the adjustment value that needs to be adjusted in terms of frequency based on the influence path ratio value. The ratio magnitude adjustment value refers to the adjustment value that needs to be adjusted in terms of magnitude based on the influence path ratio value.

[0215] The product of the influence path ratio and the preset frequency adjustment coefficient is calculated and used as the proportional frequency adjustment value, and the product of the influence path ratio and the preset amplitude adjustment coefficient is calculated and used as the proportional amplitude adjustment value, which facilitates subsequent use.

[0216] The frequency adjustment factor is used to convert the influence path ratio value into a proportional frequency adjustment value, while the amplitude adjustment factor is used to convert the influence path ratio value into a proportional amplitude adjustment value. Both the frequency adjustment factor and the amplitude adjustment factor are preset by the operator according to actual needs.

[0217] S55374: Adjust the initial value of the fluctuation frequency based on the proportional frequency adjustment value to form a fluctuation frequency correction value.

[0218] Among them, the fluctuation frequency correction value refers to the frequency value after adjusting the initial fluctuation frequency value.

[0219] The sum of the proportional frequency adjustment value and the initial value of the fluctuation frequency is calculated, and the calculation result is used as the fluctuation frequency correction value for convenient subsequent use.

[0220] S55375: Adjust the initial value of the fluctuation range based on the proportional amplitude adjustment value to form a fluctuation range correction value.

[0221] Among them, the fluctuation range correction value refers to the amplitude value corresponding to the initial fluctuation range value after adjustment.

[0222] The sum of the proportional amplitude adjustment value and the initial value of the fluctuation amplitude is calculated, and the calculation result is used as the fluctuation amplitude correction value for convenient subsequent use.

[0223] S55376: Curveize the fluctuation frequency correction value and the fluctuation amplitude correction value to form a fluctuation distance prediction curve.

[0224] Specifically, by using the fluctuation frequency correction value as the frequency of the curve fluctuation and the fluctuation amplitude correction value as the amplitude of the curve fluctuation, a fluctuation distance prediction curve is formed, which facilitates the improvement of the accuracy of the obtained fluctuation distance prediction curve.

[0225] S554: Determine the curve deviation value and the curve deviation location point based on the environmental difference fluctuation curve and the location fluctuation reference curve.

[0226] Among them, the curve deviation value refers to the deviation value corresponding to the existence of deviation in the curve, and the curve deviation position point refers to the position point corresponding to the existence of deviation in the curve.

[0227] By comparing the environmental difference fluctuation curve with the location fluctuation baseline curve, the location where the comparison shows deviation is taken as the curve deviation location point, and the specific deviation value is taken as the curve deviation value, which facilitates subsequent use.

[0228] S555: Determine the number of deviation positions based on the curve deviation position points.

[0229] Among them, the number of deviation positions refers to the number of values ​​corresponding to the deviation positions of the curve.

[0230] By calculating the deviation points of the curve and using the count results as the number of deviation points, it is convenient for subsequent use.

[0231] S556: Generate curve deviation scheduling information based on the number of deviation positions and the curve deviation value, and use the curve deviation scheduling information as differential fluctuation scheduling information.

[0232] Among them, curve deviation scheduling information refers to the control information corresponding to scheduling based on curve deviation.

[0233] By analyzing the numerical values ​​of deviation positions and curve deviation values, curve deviation scheduling information is generated, and this information is used as differential fluctuation scheduling information to improve the accuracy of the obtained differential fluctuation scheduling information.

[0234] To further ensure the rationality of the curve deviation scheduling information, it is necessary to perform further separate analysis and calculation on the curve deviation scheduling information, which will be explained in detail through the following steps.

[0235] The method for generating curve deviation scheduling information also includes the following steps:

[0236] S5561: Determine the type of deviation based on the location of the curve deviation.

[0237] Among them, deviation type refers to the type to which the deviation belongs, including deviation type at fluctuating points and deviation type at non-fluctuating points.

[0238] By retrieving the type of the location of the deviation point on the curve, the type of deviation can be determined, which facilitates subsequent use.

[0239] S5562: Determine the reference value of the type unit based on the deviation type.

[0240] The type unit reference value refers to the reference parameter value that needs to be adjusted when there is a deviation in the curve position corresponding to the deviation type. Different deviation types correspond to different type unit reference values.

[0241] By inputting the deviation type into a preset unit reference table, a reference value for the specified unit type can be obtained for convenient subsequent use.

[0242] The unit reference table is pre-stored with different deviation types and their corresponding unit reference values. The unit reference table is obtained after pre-input.

[0243] S5563: Calculate the product between the curve deviation value and the type unit reference value and use it as the curve deviation reference value.

[0244] Among them, the curve deviation reference value refers to the reference parameter value corresponding to the scheduling based on the curve deviation value.

[0245] The product of the curve deviation value and the type unit reference value is calculated and used as the curve deviation reference value for convenient subsequent use.

[0246] S5564: When the number of deviation positions is greater than the preset number of deviation references, calculate the difference between the number of deviation positions and the preset number of deviation references and use it as the number deviation value.

[0247] The deviation baseline value refers to the minimum number of values ​​required for scheduling adjustments based on the number of items. The deviation baseline value is obtained through pre-input. The number deviation value refers to the deviation value corresponding to a deviation in the number of items.

[0248] When the number of deviation positions is greater than the preset deviation baseline number, it means that the scheduling needs to be adjusted according to the number. Therefore, the difference between the number of deviation positions and the preset deviation baseline number is calculated and used as the number deviation value for convenient use later.

[0249] S5565: Determine the reference value for the number deviation based on the number deviation value.

[0250] Among them, the number deviation reference value refers to the reference parameter value corresponding to the scheduling adjustment when the number deviation is adjusted.

[0251] The product of the number deviation value and the preset number deviation coefficient is calculated and used as a reference value for the number deviation, which is convenient for subsequent use.

[0252] The count deviation coefficient is a coefficient used to convert the count deviation value into a count deviation reference value. The count deviation coefficient is obtained after pre-input.

[0253] S5566: Calculate the sum between the curve deviation reference value and the number deviation reference value and use it as the comprehensive reference value for multiple numbers.

[0254] Among them, the comprehensive reference value of multiple numbers refers to the comprehensive reference value of scheduling based on curve deviation and number deviation.

[0255] The sum of the curve deviation reference value and the number deviation reference value is calculated and used as a comprehensive reference value for multiple numbers, which facilitates subsequent use.

[0256] S5567: Determine multiple number scheduling information based on multiple comprehensive reference values, and use the multiple number scheduling information as curve deviation scheduling information.

[0257] Among them, multi-number scheduling information refers to the control information for scheduling when there is a deviation between multiple numbers. Different comprehensive reference values ​​for multiple numbers correspond to different multi-number scheduling information.

[0258] Multiple data reference values ​​are input into a preset multiple data scheduling database to obtain multiple data scheduling information, which is convenient for subsequent use.

[0259] The multi-number scheduling database pre-stores a lookup table of different multi-number comprehensive reference values ​​and corresponding multi-number scheduling information, which is obtained after pre-input.

[0260] S55681: When the number of deviation positions is not greater than the preset number of deviation references, the deviation time point is determined based on the curve deviation value.

[0261] The deviation time point refers to the time point corresponding to the curve deviation value.

[0262] When the number of deviation positions is not greater than the preset number of deviation benchmarks, it means that the scheduling will not be adjusted based on the number of deviations. Therefore, the time point corresponding to the curve deviation value is retrieved and used as the deviation time point for convenient use later.

[0263] S55682: Determine the adjacent interval time value based on the deviation time point.

[0264] The adjacent interval time value refers to the time interval between the deviations of two adjacent curves.

[0265] The time interval between two adjacent deviation time points is calculated, and the calculation result is used as the adjacent interval time value for convenient subsequent use.

[0266] S55683: Determine the reference value of the interval time based on the adjacent interval time values.

[0267] The interval time reference value refers to the reference value for scheduling based on the interval time.

[0268] The product of adjacent interval time values ​​and preset interval time coefficients is calculated and used as a reference value for the interval time, which facilitates subsequent use.

[0269] The interval time coefficient is a coefficient used to convert adjacent interval time values ​​into an interval time reference value. The interval time coefficient is preset by the operator according to actual needs.

[0270] S55684: Calculate the sum between the interval time reference value and the curve deviation reference value and use it as a small number of comprehensive reference values.

[0271] Among them, the fewer comprehensive reference values ​​refer to the comprehensive reference values ​​for scheduling based on curve deviation and interval time.

[0272] The sum of the interval time reference value and the curve deviation reference value is calculated and used as a small number of comprehensive reference values ​​for convenient subsequent use.

[0273] S55685: Determine the number of scheduling information based on the number of comprehensive reference values, and use the number of scheduling information as the curve deviation scheduling information.

[0274] Among them, the few-number scheduling information refers to the control information for scheduling when there are few deviations.

[0275] By inputting a small number of comprehensive reference values ​​into a preset small number scheduling database, small number scheduling information can be obtained for convenient subsequent use.

[0276] The small-number scheduling database pre-stores a lookup table of different small-number comprehensive reference values ​​and corresponding small-number scheduling information, which is obtained after pre-input.

[0277] Based on the same inventive concept, embodiments of the present invention provide a distributed energy dynamic dispatching system for microgrids, comprising:

[0278] The data acquisition module is used to collect data from distributed power sources, energy storage devices, local loads, and the main power grid.

[0279] The memory stores a program for implementing a distributed energy dynamic dispatching method for microgrids as described above.

[0280] The processor loads and executes programs stored in memory.

[0281] Those skilled in the art will clearly understand that, for the sake of convenience and brevity, the above-described division of functional modules is used as an example. In practical applications, the above functions can be assigned to different functional modules as needed, that is, the internal structure of the device can be divided into different functional modules to complete all or part of the functions described above. The specific working process of the system, device, and unit described above can be referred to the corresponding process in the foregoing method embodiments, and will not be repeated here.

[0282] The above description is merely a preferred embodiment of the present invention. The scope of protection of the present invention is not limited to the above embodiments. All technical solutions falling within the scope of the present invention's concept are within the scope of protection of the present invention. It should be noted that for those skilled in the art, any improvements and modifications made without departing from the principles of the present invention should also be considered within the scope of protection of the present invention.

Claims

1. A method for dynamic dispatch of distributed energy resources in microgrids, characterized in that, include: Real-time collection of distributed power source data, energy storage device data, local load data, and main power grid operation data; Demand operation mode is determined based on the distributed power source data, the energy storage device data, the local load data, and the main power grid operation data; Retrieve the environmental conditions of the energy storage location from the data of the energy storage device; Retrieve the power source location and environmental information from the distributed power source data; Environmental scheduling impact information is generated by combining the environmental conditions of the power source location and the environmental conditions of the energy storage location; The scheduling control information is generated by combining the environmental scheduling impact information with the demand operation mode, and the scheduling control information is output for energy scheduling. The method for generating environmental scheduling impact information includes: Retrieve the power environment type and power environment parameters from the power location environment; When the power environment type is consistent with the preset power generation reference environment type, the energy storage environment type and energy storage environment parameters are retrieved from the energy storage location environment. The environmental difference value is determined based on the power environment type and the energy storage environment type; An environmental difference fluctuation curve is generated based on the environmental difference value, the power supply environment parameters, and the energy storage environment parameters. Based on the environmental difference fluctuation curve, difference fluctuation scheduling information is generated, and the difference fluctuation scheduling information is used as the environmental scheduling impact information. The method for generating the differential fluctuation scheduling information includes: Retrieve the power source location point from the aforementioned power source location environment conditions; Retrieve the energy storage location point from the environmental conditions of the energy storage location; A position fluctuation reference curve is generated by combining the power source location point and the energy storage location point; The curve deviation value and the curve deviation location point are determined based on the environmental difference fluctuation curve and the location fluctuation reference curve. Determine the numerical values ​​of the deviation positions based on the curve deviation position points; Based on the numerical values ​​of the deviation positions and the curve deviation values, curve deviation scheduling information is generated, and the curve deviation scheduling information is used as the difference fluctuation scheduling information.

2. The method for dynamic dispatch of distributed energy resources for microgrids according to claim 1, characterized in that, The method for generating the position fluctuation reference curve includes: The transmission path information is determined based on the power source location and the energy storage location. Retrieve the bend points along the path from the transmission path information; Based on the transmission path information and preset fluctuation impact characteristics, the location points of influence around the path are identified; Calculate the distance between the bend points along the path and the surrounding points that influence the path, and use this distance as the bend influence distance value; The length of the affected path is generated based on the influence location points around the path and the distance value of the bending influence; Calculate the distance between the power source location point and the energy storage location point and use it as the power source energy storage distance value; A fluctuation distance prediction curve is generated by combining the influence path length value and the power storage distance value, and the fluctuation distance prediction curve is used as the location fluctuation reference curve.

3. The method for dynamic dispatch of distributed energy resources for microgrids according to claim 2, characterized in that, The method for generating the path length value includes: Retrieve the impact type from the surrounding impact points of the path; Determine the baseline distance value for the impact based on the impact type; The influence reference range is determined based on the distance between the influence location points around the path and the influence reference value; When the bending impact distance value is greater than the impact reference distance value, the transmission path information is selected for coverage based on the impact reference range to form impact coverage path information; The influence coverage path length value is retrieved from the influence coverage path information, and the influence coverage path length value is used as the influence path length value.

4. The method for dynamic dispatch of distributed energy resources for microgrids according to claim 3, characterized in that, The method for generating the path length value also includes: When the bending impact distance value is not greater than the impact reference distance value, the bending coverage range is determined by combining the impact location points around the path with the bending impact distance value. The bend coverage area and the bend location points along the path are selected to bend the edge of the bend coverage area. The edge distance value is determined based on the location point of the bent coverage edge and the bent coverage range; The edge range increment is determined based on the edge distance value; The bending coverage area is adjusted by increasing the value of the edge range to form a bending adjustment range; The transmission path information is selected for coverage based on the bending adjustment range to form bending coverage path information; The bending coverage path length value is retrieved from the bending coverage path information, and the bending coverage path length value is used as the influence path length value.

5. A method for dynamic dispatch of distributed energy resources for microgrids according to claim 2, characterized in that, The method for generating the fluctuation distance prediction curve includes: The initial values ​​of the fluctuation frequency and fluctuation amplitude are determined based on the power storage distance value. Calculate the ratio between the influence path length value and the power storage distance value, and use it as the influence path ratio value; Determine the proportional frequency adjustment value and the proportional amplitude adjustment value based on the aforementioned influence path proportional value; The initial value of the fluctuation frequency is adjusted based on the proportional frequency adjustment value to form a fluctuation frequency correction value; The initial value of the fluctuation range is adjusted based on the proportional amplitude adjustment value to form a fluctuation range correction value; The fluctuation frequency correction value and the fluctuation amplitude correction value are curve-based to form the fluctuation distance prediction curve.

6. The method for dynamic dispatch of distributed energy resources for microgrids according to claim 1, characterized in that, The method for generating the curve deviation scheduling information includes: The type of deviation is determined based on the location of the deviation point on the curve. Determine the reference value for the type unit based on the aforementioned deviation type; Calculate the product between the curve deviation value and the type unit reference value, and use it as the curve deviation reference value; When the number of deviation positions is greater than the preset number of deviation references, the difference between the number of deviation positions and the preset number of deviation references is calculated and used as the number deviation value. A reference value for the number deviation is determined based on the aforementioned number deviation value; Calculate the sum between the curve deviation reference value and the number deviation reference value, and use it as a comprehensive reference value for multiple numbers; Multiple number scheduling information is determined based on the comprehensive reference values ​​of the multiple numbers, and the multiple number scheduling information is used as the curve deviation scheduling information.

7. A method for dynamic dispatch of distributed energy resources for microgrids according to claim 6, characterized in that, The method for generating curve deviation scheduling information further includes: When the number of deviation positions is not greater than the preset number of deviation references, the deviation time point is determined based on the curve deviation value; The adjacent interval time value is determined based on the aforementioned deviation time point; Determine the interval time reference value based on the adjacent interval time values; Calculate the sum between the interval time reference value and the curve deviation reference value, and use it as a small number of comprehensive reference values; Based on the aforementioned comprehensive reference values, the scheduling information for the fewest individuals is determined, and this scheduling information is used as the curve deviation scheduling information.

8. A distributed energy dynamic dispatch system for microgrids, characterized in that, include: The data acquisition module is used to collect data from distributed power sources, energy storage devices, local loads, and the main power grid. The memory stores a program for implementing a distributed energy dynamic dispatching method for microgrids as described in any one of claims 1 to 7; The processor loads and executes programs stored in memory.

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