Distributed energy distribution network planning and designing method and device based on peak regulation capability

Abstract

The invention provides a distributed energy distribution network planning and designing method and device based on peak regulation capacity, and relates to the technical field of electric power grids. According to the method, the power quality data of each node in the power distribution network is calculated, distributed energy planning is performed based on the power quality data, a plurality of planning schemes are obtained, the peak regulation capability of each planning scheme is calculated, the target planning scheme is determined, and distributed energy distribution network planning design is performed based on the target planning scheme. Due to the fact that planning is carried out through the electric energy quality data and the peak regulation capacity of all the nodes in the planning and designing process, the rationality of distributed energy distribution network planning is improved, the problem that the peak regulation capacity is reduced due to the fact that the distributed energy planning position is improper is solved, and the peak regulation capacity of the power distribution network is improved.

Description

Technical Field

[0001] The present invention relates to the technical field of electric power grids, and in particular to a distributed energy distribution network planning and design method and device based on peak load regulation capability. Background Art

[0002] As the world's demand for renewable energy (including wind and solar energy) continues to increase, energy transformation has become a goal and focus of all countries. This means that reasonable distributed power (DG) planning has become very important. Distributed energy systems, with their flexibility and reliability, can reduce the dependence of traditional centralized power systems on renewable energy, while improving the sustainability and stability of power supply.

[0003] At present, in the process of distributed energy distribution network planning, the capacity of distributed energy that can be accommodated is mostly calculated by calculating the carrying capacity of the distribution network. However, this method only calculates the capacity of the entire distribution network that can carry new energy, thereby realizing the planning of distributed energy. The power quality of each node in the distribution network is not considered, resulting in difficulties in peak regulation of individual nodes in the distribution network, reduced power quality, and reduced peak regulation capacity of the distribution network. Summary of the invention

[0004] The present invention provides a distributed energy distribution network planning and design method and device based on peak-shaving capability, which can solve the problem of reduced peak-shaving capability caused by inappropriate distributed energy planning location, improve the rationality of distributed energy distribution network planning, and improve the peak-shaving capability of the distribution network.

[0005] In a first aspect, the present invention provides a distributed energy distribution network planning and design method and device based on peak-shaving capability, the method comprising: obtaining voltage data and frequency data of each node in the distribution network during a historical period; calculating the power quality data of each node in the historical period based on the voltage data and frequency data of each node in the distribution network during the historical period; performing distributed energy planning based on the power quality data of each node in the historical period, and determining multiple planning schemes; wherein each planning scheme includes access node location information and installed capacity of multiple distributed energy stations; calculating the peak-shaving capability of each planning scheme, and determining a target planning scheme based on the peak-shaving capability; and performing distributed energy distribution network planning and design based on the target planning scheme.

[0006] In one possible implementation, the power quality data includes voltage deviation, voltage imbalance rate, overvoltage frequency and frequency deviation; based on the voltage data and frequency data of each node in the distribution network during the historical period, the power quality data of each node in the historical period is calculated, including: based on the voltage data of each node in the historical period, determining the voltage deviation, voltage imbalance rate and overvoltage frequency of each node; based on the frequency data of each node in the historical period, determining the frequency deviation of each node.

[0007] In a possible implementation, based on the voltage data of each node in the historical period, the voltage deviation, voltage imbalance rate and overvoltage frequency of each node are determined, including: traversing the voltage data of each node in the historical period, determining the number of deviation moments in which voltage deviation occurs at each moment of each node, and the voltage deviation amount at each moment; calculating the average value of the voltage deviation amount at each moment to obtain the average deviation amount; performing weighted summation based on the number of deviation moments and the average deviation amount to determine the voltage deviation of each node; traversing the voltage data of each node in the historical period, determining the number of moments in which three-phase imbalance exists at each moment of each node, and the voltage difference when three-phase imbalance exists; calculating the average voltage difference of the voltage difference when three-phase imbalance exists; performing weighted summation based on the number of moments in which three-phase imbalance exists and the average voltage difference to determine the voltage imbalance rate of each node. Traversing the voltage data of each node in the historical period, obtaining the number of overvoltage moments in which overvoltage exists at each moment of each node; calculating the overvoltage frequency of each node based on the total number of moments in the historical period and the number of overvoltage moments.

[0008] In a possible implementation, distributed energy planning is performed based on power quality data of each node in a historical period, and multiple planning schemes are determined, including: based on the power quality data and the preset weights of each data, a power quality coefficient of each node is obtained, and the power quality coefficient is used to characterize the power quality regulation capability of the node; based on the power quality coefficient, in each node, multiple nodes to be planned whose power quality coefficient is greater than a set threshold are determined; based on the power quality coefficients of multiple nodes to be planned, the installed capacity of distributed energy in multiple nodes to be planned is determined; based on multiple nodes to be planned and the installed capacity of distributed energy in multiple nodes to be planned, multiple planning schemes are determined.

[0009] In one possible implementation, the peak-shaving capacity of each planning scheme is calculated, including: based on each planning scheme and a preset distribution network model, constructing a distribution network model corresponding to each planning scheme; based on the distribution network model corresponding to each planning scheme, calculating the regulation power range of each node in each planning scheme; calculating the median value of the regulation power range of each node; based on the median value of the regulation power range of each node, determining the maximum regulation power of each planning scheme, the maximum regulation power being used to characterize the peak-shaving capacity of the distribution network.

[0010] In a possible implementation, a target planning scheme is determined based on the peak-shaving capability, including: determining a planning scheme with the highest peak-shaving capability as the target planning scheme.

[0011] In one possible implementation, a target planning scheme is determined based on the peak-shaving capability, including: determining a planning scheme whose maximum regulation power is greater than a set power as a candidate scheme; calculating the power quality coefficient of each node in each candidate scheme; and determining the target planning scheme based on the power quality coefficient of each node in each candidate scheme.

[0012] In one possible implementation, distributed energy distribution network planning and design is performed based on a target planning scheme, including: determining the node locations and installed capacities of multiple distributed energy stations to be planned and designed based on the target planning scheme; generating a planning and design list based on the node locations and installed capacities of multiple distributed energy stations to be planned and designed; and outputting the planning and design list.

[0013] In a possible implementation, after calculating the peak-shaving capacity of each planning scheme and determining the target planning scheme based on the peak-shaving capacity, it also includes: obtaining the day-ahead predicted load power and the day-ahead predicted power generation power of each node in the distribution network; constructing a distribution network model corresponding to the target planning scheme; determining the power quality coefficient of each node in the distribution network model based on the day-ahead predicted load power and the day-ahead predicted power generation power, as well as the distribution network model corresponding to the target planning scheme; verifying the target planning scheme based on the power quality coefficient of each node in the distribution network model to determine the feasibility of the target planning scheme.

[0014] In a second aspect, an embodiment of the present invention provides a distributed energy distribution network planning and design device based on peak-shaving capability, the device comprising: a communication module for acquiring voltage data and frequency data of each node of the distribution network during a historical period; a data calculation module for calculating the power quality data of each node during a historical period based on the voltage data and frequency data of each node of the distribution network during a historical period; a planning and design module for performing distributed energy planning based on the power quality data of each node during a historical period, and determining multiple planning schemes; wherein each planning scheme includes access node location information and installed capacity of multiple distributed energy stations; calculating the peak-shaving capability of each planning scheme, and determining a target planning scheme based on the peak-shaving capability; and performing distributed energy distribution network planning and design based on the target planning scheme.

[0015] In one possible implementation, the power quality data includes voltage deviation, voltage imbalance rate, overvoltage frequency and frequency deviation; the data calculation module is specifically used to determine the voltage deviation, voltage imbalance rate and overvoltage frequency of each node based on the voltage data of each node in the historical period; and determine the frequency deviation of each node based on the frequency data of each node in the historical period.

[0016] In one possible implementation, the data calculation module is specifically used to traverse the voltage data of each node in the historical period, determine the number of deviation moments in which voltage deviation occurs at each node at each moment, and the voltage deviation at each moment; calculate the average value of the voltage deviation at each moment to obtain the average deviation; perform weighted summation based on the number of deviation moments and the average deviation to determine the voltage deviation of each node; traverse the voltage data of each node in the historical period, determine the number of moments in which three-phase imbalance exists at each node at each moment, and the voltage difference when three-phase imbalance exists; calculate the average voltage difference of the voltage difference when three-phase imbalance exists; perform weighted summation based on the number of moments in which three-phase imbalance exists, and the average voltage difference, to determine the voltage imbalance rate of each node; traverse the voltage data of each node in the historical period, and obtain the number of overvoltage moments in which overvoltage exists at each node at each moment; calculate the overvoltage frequency of each node based on the total number of moments in the historical period and the number of overvoltage moments.

[0017] In one possible implementation, the planning and design module is specifically used to obtain the power quality coefficient of each node based on power quality data and preset weights of each data, and the power quality coefficient is used to characterize the power quality regulation capability of the node; based on the power quality coefficient, in each node, determine multiple nodes to be planned whose power quality coefficient is greater than a set threshold; based on the power quality coefficients of multiple nodes to be planned, determine the installed capacity of distributed energy in multiple nodes to be planned; based on multiple nodes to be planned and the installed capacity of distributed energy in multiple nodes to be planned, determine multiple planning schemes.

[0018] In a possible implementation, the planning and design module is specifically used to construct a distribution network model corresponding to each planning scheme based on each planning scheme and a preset distribution network model; calculate the regulation power range of each node in each planning scheme based on the distribution network model corresponding to each planning scheme; calculate the median value of the regulation power range of each node; based on the median value of the regulation power range of each node, determine the maximum regulation power of each planning scheme, and the maximum regulation power is used to characterize the peak-shaving capacity of the distribution network.

[0019] In a possible implementation, the planning and design module is specifically used to determine the planning scheme with the highest peak-shaving capacity as the target planning scheme.

[0020] In one possible implementation, the planning and design module is specifically used to determine the planning scheme whose maximum regulation power is greater than the set power as the candidate scheme; calculate the power quality coefficient of each node in each candidate scheme; and determine the target planning scheme based on the power quality coefficient of each node in each candidate scheme.

[0021] In one possible implementation, the planning and design module is specifically used to determine the node locations and installed capacities of multiple distributed energy stations to be planned and designed based on a target planning scheme; generate a planning and design list based on the node locations and installed capacities of multiple distributed energy stations to be planned and designed; and output the planning and design list.

[0022] In a possible implementation, the communication module is also used to obtain the day-ahead predicted load power and the day-ahead predicted generation power of each node in the distribution network; the planning and design module is also used to construct a distribution network model corresponding to the target planning scheme; based on the day-ahead predicted load power and the day-ahead predicted generation power, and the distribution network model corresponding to the target planning scheme, the power quality coefficient of each node in the distribution network model is determined; based on the power quality coefficient of each node in the distribution network model, the target planning scheme is verified to determine the feasibility of the target planning scheme.

[0023] The present invention provides a distributed energy distribution network planning and design method and device based on peak-shaving capability. The present invention calculates the power quality data of each node in the distribution network, performs distributed energy planning based on the power quality data, obtains multiple planning schemes, calculates the peak-shaving capability of each planning scheme, determines the target planning scheme, and performs distributed energy distribution network planning and design based on the target planning scheme. Since the power quality data and peak-shaving capability of each node are used for planning in the planning and design process, the rationality of distributed energy distribution network planning is improved, the problem of reduced peak-shaving capability due to inappropriate distributed energy planning location is solved, and the peak-shaving capability of the distribution network is improved. BRIEF DESCRIPTION OF THE DRAWINGS

[0024] In order to more clearly illustrate the technical solutions in the embodiments of the present invention, the drawings required for use in the embodiments or the description of the prior art will be briefly introduced below. Obviously, the drawings described below are only some embodiments of the present invention. For ordinary technicians in this field, other drawings can be obtained based on these drawings without paying creative labor.

[0025] Figure 1 It is a flow chart of a distributed energy distribution network planning and design method based on peak load regulation capability provided by an embodiment of the present invention;

[0026] Figure 2 It is a structural schematic diagram of a distributed energy distribution network planning and design device based on peak load regulation capability provided by an embodiment of the present invention. DETAILED DESCRIPTION

[0027] In the following description, specific details such as specific system structures, technologies, etc. are provided for the purpose of illustration rather than limitation, so as to provide a thorough understanding of the embodiments of the present invention. However, it should be clear to those skilled in the art that the present invention may be implemented in other embodiments without these specific details. In other cases, detailed descriptions of well-known systems, devices, circuits, and methods are omitted to prevent unnecessary details from obstructing the description of the present invention.

[0028] In the description of the present invention, unless otherwise specified, " / " means "or", for example, A / B can mean A or B. "And / or" in this article is only a description of the association relationship of associated objects, indicating that there can be three relationships. For example, A and / or B can mean: A exists alone, A and B exist at the same time, and B exists alone. In addition, "at least one" and "plurality" refer to two or more. The words "first", "second", etc. do not limit the quantity and execution order, and the words "first", "second", etc. do not limit them to be different.

[0029] In the embodiments of the present application, words such as "exemplary" or "for example" are used to indicate examples, illustrations or descriptions. Any embodiment or design described as "exemplary" or "for example" in the embodiments of the present application should not be interpreted as being more preferred or more advantageous than other embodiments or designs. Specifically, the use of words such as "exemplary" or "for example" is intended to present related concepts in a concrete way for easy understanding.

[0030] In addition, the terms "including" and "having" and any variations thereof mentioned in the description of this application are intended to cover non-exclusive inclusions. For example, a process, method, system, product or device that includes a series of steps or modules is not limited to the listed steps or modules, but may optionally include other steps or modules that are not listed, or may optionally include other steps or modules that are inherent to these processes, methods, products or devices.

[0031] In order to make the purpose, technical solutions and advantages of the present invention more clear, the following will be described through specific embodiments in conjunction with the accompanying drawings of the present invention.

[0032] As described in the background technology, the current technical problem is that the peak-shaving capacity is reduced due to inappropriate planning locations of distributed energy.

[0033] To solve the above technical problems, Figure 1 As shown, an embodiment of the present invention provides a distributed energy distribution network planning and design method based on peak load regulation capability. The method includes steps S101-S104.

[0034] S101. Obtain voltage data and frequency data of each node in the distribution network during a historical period.

[0035] In some embodiments, the voltage data includes the real-time voltage of each node at each time in a historical period.

[0036] In some embodiments, the frequency data includes the real-time frequency of each node at each time during the historical period.

[0037] S102. Calculate power quality data of each node in the historical period based on voltage data and frequency data of each node in the distribution network in the historical period.

[0038] In some embodiments, the power quality data includes voltage deviation, voltage unbalance rate, overvoltage frequency, and frequency deviation.

[0039] As a possible implementation manner, the embodiment of the present invention may determine the power quality data of each node based on steps S1021 - S1026 .

[0040] S1021. Determine the voltage deviation, voltage imbalance rate and overvoltage frequency of each node based on the voltage data of each node in the historical period.

[0041] Exemplarily, the voltage deviation of each node may be determined based on steps A1-A3.

[0042] A1. Traverse the voltage data of each node in the historical period, determine the number of deviation moments when voltage deviation occurs at each node at each moment, and the voltage deviation amount at each moment.

[0043] A2. Calculate the average value of the voltage deviation at each moment to obtain the average deviation.

[0044] A3. Based on the number of deviation moments and the average deviation, a weighted sum is performed to determine the voltage deviation of each node.

[0045] Exemplarily, the voltage imbalance rate of each node may be determined based on steps B1-B3.

[0046] B1. Traverse the voltage data of each node in the historical period, determine the number of moments when three-phase imbalance exists at each node at each moment, and the voltage difference when three-phase imbalance exists.

[0047] B2. Calculate the average voltage difference when there is three-phase imbalance.

[0048] B3. Based on the number of moments when three-phase imbalance exists and the average voltage difference, a weighted sum is performed to determine the voltage imbalance rate of each node.

[0049] Exemplarily, the overvoltage frequency of each node may be determined based on steps C1 - C2 .

[0050] C1. Traverse the voltage data of each node in the historical period to obtain the number of overvoltage moments at each node at each moment.

[0051] C2. Calculate the overvoltage frequency of each node based on the total number of moments in the historical period and the number of overvoltage moments.

[0052] S1022. Determine the frequency deviation of each node based on the frequency data of each node in the historical period.

[0053] Exemplarily, the frequency deviation of each node may be determined based on steps D1 - D3 .

[0054] D1. Traverse the frequency data of each node in a set period of time, determine the number of moments when frequency deviation occurs at each moment in the set period of time for each node, and the frequency deviation amount at each moment.

[0055] D2. Calculate the average value of the frequency deviation at each moment in the set time period to obtain the average frequency deviation.

[0056] D3. Based on the number of deviation moments and the average frequency deviation, a weighted sum is performed to determine the frequency deviation of each node.

[0057] S103. Based on the power quality data of each node in the historical period, distributed energy planning is carried out to determine multiple planning schemes.

[0058] Among them, each planning scheme includes the access node location information and installed capacity of multiple distributed energy stations;

[0059] As a possible implementation manner, the embodiment of the present invention may determine multiple planning schemes based on steps S1031 - S1034 .

[0060] S1031. Obtain a power quality coefficient of each node based on power quality data and preset weights of each data.

[0061] In some embodiments, the power quality coefficient is used to characterize the power quality regulation capability of the node.

[0062] S1032. Based on the power quality coefficient, determine, in each node, a plurality of nodes to be planned whose power quality coefficient is greater than a set threshold.

[0063] S1033. Determine the installed capacity of distributed energy in the multiple nodes to be planned based on the power quality coefficients of the multiple nodes to be planned.

[0064] S1034. Determine multiple planning schemes based on multiple nodes to be planned and the installed capacity of distributed energy in the multiple nodes to be planned.

[0065] S104: Calculate the peak load regulation capability of each planning scheme, and determine the target planning scheme based on the peak load regulation capability.

[0066] As a possible implementation manner, the embodiment of the present invention can determine the peak load regulation capability of each planning scheme based on steps S1041-S1044.

[0067] S1041. Based on each planning scheme and a preset distribution network model, a distribution network model corresponding to each planning scheme is constructed.

[0068] S1042: Based on the distribution network model corresponding to each planning scheme, calculate the adjustment power range of each node in each planning scheme.

[0069] S1043. Calculate the median value of the adjustment power range of each node.

[0070] S1044. Determine the maximum regulation power of each planning scheme based on the median value of the regulation power range of each node. The maximum regulation power is used to characterize the peak regulation capability of the distribution network.

[0071] As a possible implementation manner, the embodiment of the present invention may determine the planning scheme with the highest peak load regulation capability as the target planning scheme.

[0072] As another possible implementation manner, the embodiment of the present invention may determine the target planning scheme based on steps S1045-S1047.

[0073] S1045. Determine the planning scheme whose maximum regulated power is greater than the set power as the candidate scheme.

[0074] S1046. Calculate the power quality coefficient of each node in each candidate solution.

[0075] S1047. Determine a target planning scheme based on the power quality coefficient of each node in each candidate scheme.

[0076] S105. Based on the target planning scheme, carry out distributed energy distribution network planning and design.

[0077] As a possible implementation manner, the embodiment of the present invention can perform distribution network planning and design based on steps S1051-S1053.

[0078] S1051. Based on the target planning scheme, determine the node locations and installed capacities of multiple distributed energy stations that are planned and designed.

[0079] S1052. Generate a planning and design list based on the node locations and installed capacities of the planned and designed multiple distributed energy stations.

[0080] S1053. Output the planning and design list.

[0081] The present invention provides a distributed energy distribution network planning and design method based on peak-shaving capability, by calculating the power quality data of each node in the distribution network, performing distributed energy planning based on the power quality data, obtaining multiple planning schemes, calculating the peak-shaving capability of each planning scheme, determining a target planning scheme, and performing distributed energy distribution network planning and design based on the target planning scheme. Since the power quality data and peak-shaving capability of each node are used for planning in the planning and design process, the rationality of distributed energy distribution network planning is improved, the problem of reduced peak-shaving capability due to inappropriate distributed energy planning location is solved, and the peak-shaving capability of the distribution network is improved.

[0082] Optionally, the distributed energy distribution network planning and design method based on peak load regulation capability provided in an embodiment of the present invention further includes steps S201-S204 after step S105.

[0083] S201. Obtain the day-ahead predicted load power and day-ahead predicted generation power of each node in the distribution network.

[0084] S202: Construct a distribution network model corresponding to the target planning scheme.

[0085] S203: Based on the day-ahead predicted load power and the day-ahead predicted generation power, and the distribution network model corresponding to the target planning scheme, determine the power quality coefficient of each node in the distribution network model.

[0086] S204. Based on the power quality coefficient of each node in the distribution network model, verify the target planning scheme to determine the feasibility of the target planning scheme.

[0087] In this way, after obtaining the target planning scheme, the embodiment of the present invention can verify the target planning scheme through the day-ahead predicted load power and the day-ahead predicted power generation power, determine the feasibility of the target planning scheme, and further determine whether the access node location information and installed capacity of multiple distributed energy stations in the target planning scheme are reasonable, thereby improving the rationality of the distributed energy distribution network planning and design.

[0088] It should be understood that the order of execution of the steps in the above embodiment does not necessarily mean the order of execution. The execution order of each process should be determined by its function and internal logic, and should not constitute any limitation on the implementation process of the embodiment of the present invention.

[0089] The following is an embodiment of the device of the present invention. For details not described in detail therein, reference may be made to the corresponding method embodiment described above.

[0090] Figure 2The schematic diagram of the structure of a distributed energy distribution network planning and design device based on peak load regulation capability provided by an embodiment of the present invention is shown. The device 300 includes a communication module 301 , a data calculation module 302 and a planning and design module 303 .

[0091] The communication module 301 is used to obtain the voltage data and frequency data of each node in the distribution network in the historical period.

[0092] The data calculation module 302 is used to calculate the power quality data of each node in the historical period based on the voltage data and frequency data of each node in the distribution network in the historical period.

[0093] The planning and design module 303 is used to carry out distributed energy planning based on the power quality data of each node in the historical period, and determine multiple planning schemes; each planning scheme includes the access node location information and installed capacity of multiple distributed energy stations; calculate the peak-shaving capacity of each planning scheme, and determine the target planning scheme based on the peak-shaving capacity; and carry out distributed energy distribution network planning and design based on the target planning scheme.

[0094] In one possible implementation, the power quality data includes voltage deviation, voltage imbalance rate, overvoltage frequency and frequency deviation; the data calculation module 302 is specifically used to determine the voltage deviation, voltage imbalance rate and overvoltage frequency of each node based on the voltage data of each node in the historical period; and determine the frequency deviation of each node based on the frequency data of each node in the historical period.

[0095] In one possible implementation, the data calculation module 302 is specifically used to traverse the voltage data of each node in the historical period, determine the number of deviation moments in which voltage deviation occurs at each node at each moment, and the voltage deviation at each moment; calculate the average value of the voltage deviation at each moment to obtain the average deviation; perform weighted summation based on the number of deviation moments and the average deviation to determine the voltage deviation of each node; traverse the voltage data of each node in the historical period, determine the number of moments in which three-phase imbalance exists at each node at each moment, and the voltage difference when three-phase imbalance exists; calculate the average voltage difference of the voltage difference when three-phase imbalance exists; perform weighted summation based on the number of moments in which three-phase imbalance exists, and the average voltage difference, to determine the voltage imbalance rate of each node; traverse the voltage data of each node in the historical period, and obtain the number of overvoltage moments in which overvoltage exists at each node at each moment; calculate the overvoltage frequency of each node based on the total number of moments in the historical period and the number of overvoltage moments.

[0096] In one possible implementation, the planning and design module 303 is specifically used to obtain a power quality coefficient of each node based on power quality data and preset weights of each data, and the power quality coefficient is used to characterize the power quality regulation capability of the node; based on the power quality coefficient, in each node, determine a plurality of nodes to be planned whose power quality coefficient is greater than a set threshold; based on the power quality coefficients of the plurality of nodes to be planned, determine the installed capacity of distributed energy in the plurality of nodes to be planned; based on the plurality of nodes to be planned and the installed capacity of distributed energy in the plurality of nodes to be planned, determine a plurality of planning schemes.

[0097] In one possible implementation, the planning and design module 303 is specifically used to construct a distribution network model corresponding to each planning scheme based on each planning scheme and a preset distribution network model; calculate the regulation power range of each node in each planning scheme based on the distribution network model corresponding to each planning scheme; calculate the median value of the regulation power range of each node; determine the maximum regulation power of each planning scheme based on the median value of the regulation power range of each node, and the maximum regulation power is used to characterize the peak-shaving capacity of the distribution network.

[0098] In a possible implementation, the planning and design module 303 is specifically configured to determine a planning scheme with the highest peak load regulation capability as a target planning scheme.

[0099] In one possible implementation, the planning and design module 303 is specifically used to determine the planning scheme whose maximum regulation power is greater than the set power as a candidate scheme; calculate the power quality coefficient of each node in each candidate scheme; and determine the target planning scheme based on the power quality coefficient of each node in each candidate scheme.

[0100] In one possible implementation, the planning and design module 303 is specifically used to determine the node locations and installed capacities of multiple distributed energy stations to be planned and designed based on the target planning scheme; generate a planning and design list based on the node locations and installed capacities of multiple distributed energy stations to be planned and designed; and output the planning and design list.

[0101] In a possible implementation, the communication module 301 is also used to obtain the day-ahead predicted load power and the day-ahead predicted generation power of each node in the distribution network; the planning and design module 303 is also used to construct a distribution network model corresponding to the target planning scheme; based on the day-ahead predicted load power and the day-ahead predicted generation power, and the distribution network model corresponding to the target planning scheme, the power quality coefficient of each node in the distribution network model is determined; based on the power quality coefficient of each node in the distribution network model, the target planning scheme is verified to determine the feasibility of the target planning scheme.

[0102] The above embodiments are only used to illustrate the technical solutions of the present invention, rather than to limit the same. Although the present invention has been described in detail with reference to the aforementioned embodiments, those skilled in the art should understand that the technical solutions described in the aforementioned embodiments may still be modified, or some of the technical features may be replaced by equivalents. Such modifications or replacements do not deviate the essence of the corresponding technical solutions from the spirit and scope of the technical solutions of the embodiments of the present invention, and should be included in the protection scope of the present invention.

Claims

1. A distributed energy distribution network planning and design method based on peak load regulation capability, characterized in that: include: Obtain voltage and frequency data of each node in the distribution network during the historical period; Calculating power quality data of each node in the historical period based on voltage data and frequency data of each node in the distribution network in the historical period; Based on the power quality data of each node in the historical period, distributed energy planning is performed to determine multiple planning schemes; wherein each planning scheme includes access node location information and installed capacity of multiple distributed energy stations; Calculate the peak load regulation capability of each planning scheme, and determine the target planning scheme based on the peak load regulation capability; Based on the target planning scheme, distributed energy distribution network planning and design are carried out.

2. The distributed energy distribution network planning and design method based on peak load regulation capability according to claim 1 is characterized in that: The power quality data includes voltage deviation, voltage unbalance rate, overvoltage frequency and frequency deviation; The calculating of the power quality data of each node in the historical period based on the voltage data and frequency data of each node in the distribution network in the historical period includes: Determine the voltage deviation, voltage unbalance rate and overvoltage frequency of each node based on the voltage data of each node in the historical period; Based on the frequency data of each node in the historical period, a frequency deviation of each node is determined.

3. The distributed energy distribution network planning and design method based on peak load regulation capability according to claim 2 is characterized in that: The determining of the voltage deviation, voltage imbalance rate and overvoltage frequency of each node based on the voltage data of each node in the historical period includes: Traversing the voltage data of each node in the historical period, determining the number of deviation moments at each node at each moment when voltage deviation occurs, and the voltage deviation amount at each moment; Calculate the average value of the voltage deviation at each moment to obtain the average deviation; Based on the number of deviation moments and the average deviation amount, a weighted sum is performed to determine the voltage deviation of each node; Traversing the voltage data of each node in the historical period, determining the number of moments when three-phase imbalance exists at each node at each moment, and the voltage difference when three-phase imbalance exists; Calculate the average voltage difference of the voltage differences when there is three-phase imbalance; Based on the number of moments when three-phase imbalance exists and the average voltage difference, a weighted sum is performed to determine the voltage imbalance rate of each node; Traversing the voltage data of each node in the historical period, obtaining the number of overvoltage moments at each node at each moment; Based on the total number of moments in the historical period and the number of overvoltage moments, the overvoltage frequency of each node is calculated.

4. The distributed energy distribution network planning and design method based on peak load regulation capability according to claim 1 is characterized in that: The distributed energy planning is performed based on the power quality data of each node in the historical period, and multiple planning schemes are determined, including: Based on the power quality data and the preset weight of each data, a power quality coefficient of each node is obtained, and the power quality coefficient is used to characterize the power quality regulation capability of the node; Based on the power quality coefficient, determining, in each node, a plurality of nodes to be planned whose power quality coefficient is greater than a set threshold; Determining the installed capacity of distributed energy in the plurality of nodes to be planned based on the power quality coefficients of the plurality of nodes to be planned; The multiple planning schemes are determined based on the multiple nodes to be planned and the installed capacity of distributed energy in the multiple nodes to be planned.

5. The distributed energy distribution network planning and design method based on peak load regulation capability according to claim 1 is characterized in that: The calculation of the peak load regulation capacity of each planning scheme includes: Based on each of the planning schemes and the preset distribution network model, construct a distribution network model corresponding to each planning scheme; Based on the distribution network model corresponding to each planning scheme, calculating the adjustment power range of each node in each planning scheme; Calculate the median value of the regulation power range of each node; Based on the median value of the regulation power range of each node, the maximum regulation power of each planning scheme is determined, and the maximum regulation power is used to characterize the peak regulation capability of the distribution network.

6. The distributed energy distribution network planning and design method based on peak load regulation capability according to claim 1 is characterized in that: The determining of a target planning scheme based on the peak load regulation capability includes: The planning scheme with the highest peak-shaving capacity shall be determined as the target planning scheme.

7. The distributed energy distribution network planning and design method based on peak load regulation capability according to claim 1 is characterized in that: The determining of a target planning scheme based on the peak load regulation capability includes: Determine the planning scheme whose maximum regulated power is greater than the set power as a candidate scheme; Calculate the power quality coefficient of each node in each candidate solution; The target planning scheme is determined based on the power quality coefficient of each node in each candidate scheme.

8. The distributed energy distribution network planning and design method based on peak load regulation capability according to claim 1 is characterized in that: The distributed energy distribution network planning and design based on the target planning scheme includes: Based on the target planning scheme, determine the node locations and installed capacities of multiple distributed energy stations planned and designed; Generate a planning and design list based on the node locations and installed capacities of the plurality of distributed energy stations planned and designed; Output the planning design list.

9. The distributed energy distribution network planning and design method based on peak load regulation capability according to claim 1 is characterized in that: After calculating the peak load capacity of each planning scheme and determining the target planning scheme based on the peak load capacity, the method further includes: Obtaining the day-ahead predicted load power and the day-ahead predicted generation power of each node in the distribution network; Constructing a distribution network model corresponding to the target planning scheme; Determine the power quality coefficient of each node in the distribution network model based on the day-ahead predicted load power and the day-ahead predicted generation power, and the distribution network model corresponding to the target planning scheme; Based on the power quality coefficient of each node in the distribution network model, the target planning scheme is verified to determine the feasibility of the target planning scheme.

10. A distributed energy distribution network planning and design device based on peak load regulation capability, characterized in that: include: A communication module is used to obtain voltage and frequency data of each node in the distribution network during the historical period; A data calculation module, used to calculate the power quality data of each node in the historical period based on the voltage data and frequency data of each node in the distribution network in the historical period; A planning and design module is used to carry out distributed energy planning based on the power quality data of each node in the historical period, and determine multiple planning schemes; wherein each planning scheme includes the access node location information and installed capacity of multiple distributed energy stations; calculate the peak-shaving capacity of each planning scheme, and determine the target planning scheme based on the peak-shaving capacity; and carry out distributed energy distribution network planning and design based on the target planning scheme.

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