Storage, distribution network power system optimization method, system and device

Abstract

The present invention discloses a memory, a distribution network power system optimization method, a system and a device, wherein the method comprises: establishing a simulation model of the distribution network power system and setting the parameters of the simulation model; setting corresponding simulation schemes according to different causes of voltage sag; performing simulation experiments through the simulation model according to each simulation scheme, obtaining and counting the voltage sag information of each node; judging whether there is a voltage sag risk area in the distribution network power system through preset rules according to the voltage sag information; if so, updating parameters for the nodes in the voltage sag risk area in the simulation model in a way of controlling the voltage sag; if not, generating an optimization scheme for the distribution network power system according to the current structure and parameters of the simulation model. The present invention can automatically judge the voltage sag risk area in the distribution network power system and obtain the optimization scheme for the distribution network power system, thereby improving the optimization effect and efficiency of the distribution network power system.

Description

Technical Field

[0001] The present invention relates to the field of power distribution networks, and in particular to a storage device, a power distribution network power system optimization method, a system and a device. Background Art

[0002] The so-called voltage sag is the phenomenon that the effective value of the power supply voltage suddenly drops in a short period of time and then rebounds to near the normal value. This phenomenon often lasts for 0.5-30 cycles or even longer in the power system.

[0003] At present, voltage sag has been recognized as one of the most important power quality problems, which seriously affects the safety and normal operation of many electrical equipment. The causes of voltage sag are related to both the power system and the user. For example, various short-circuit faults and lightning strikes in the line are all caused by the power system; while the switching of capacitor banks, switching of transformers, starting of large-capacity induction motors, and the group starting and restarting of multiple motors are all caused by the user.

[0004] The distribution network refers to a power grid that receives electric energy from the transmission network or regional power plants and distributes it locally or step by step according to voltage to various users through distribution facilities. In the prior art, in order to find reasonable management measures to reduce the probability of voltage sag in the distribution network power system, it is generally necessary to conduct a voltage sag assessment on the distribution network power system.

[0005] The inventors have found through research that the voltage sag assessment scheme in the prior art has poor effect and efficiency when used for optimizing the power distribution network.

[0006] The information disclosed in this background technology section is only intended to enhance the understanding of the overall background of the invention and should not be regarded as an acknowledgment or any form of suggestion that the information constitutes the prior art already known to a person skilled in the art. Summary of the invention

[0007] The purpose of the present invention is to improve the optimization effect and efficiency of the power distribution network system.

[0008] The present invention provides a method for optimizing a power distribution network, comprising the steps of:

[0009] S11, establishing a simulation model of a power distribution network system as an optimization object, and setting parameters of the simulation model according to the power distribution network system;

[0010] S12, setting corresponding simulation schemes according to different causes of voltage sag; the simulation schemes include short circuit simulation, electromagnetic transient simulation and electromechanical transient simulation;

[0011] S13, performing simulation experiments through the simulation model according to each of the simulation schemes, obtaining and counting voltage sag information of each node in the power distribution network;

[0012] S14, judging whether there is a voltage sag risk area in the power distribution network according to the voltage sag information by using preset rules;

[0013] S15. If yes, in the simulation model, update the parameters of the nodes in the voltage sag risk area in a manner to control the voltage sag and return to step S12; if no, generate an optimization plan for the distribution network power system according to the current structure and parameters of the simulation model.

[0014] In the present invention, when the simulation scheme is a short circuit simulation, the setting corresponding to the simulation scheme includes:

[0015] S21, respectively set the short-circuit fault rate of each bus, transformer and line in the power distribution network system, and set the fault proportion of each short-circuit fault type in the short-circuit fault; the short-circuit fault types are single-phase grounding fault, two-phase short circuit, three-phase short circuit and two-phase grounding short circuit fault;

[0016] S22. Generate input parameters for short-circuit simulation of the simulation model according to the short-circuit failure rate and the failure proportion.

[0017] In the present invention, the short-circuit failure rates of the buses, transformers and lines in the power distribution network are respectively set, and the failure proportion of each short-circuit failure type in the short-circuit failure is set, including:

[0018] According to the reliability statistics of the distribution network, the number of faults of the busbar, transformer and line is determined, which are counted as a, b and c respectively. F is calculated according to the following formula b , F t , F l :

[0019]

[0020] Among them, F b Indicates the failure rate of all buses in the distribution network; F t Indicates the failure rate of all transformers in the distribution network; F l represents the failure rate of all lines in the distribution network; a represents the number of bus failures; b represents the number of transformer failures; c represents the number of line failures;

[0021] According to statistical data, the proportions of single-phase grounding, two-phase short circuit, three-phase short circuit and two-phase grounding short circuit faults are set to d:e:f:g respectively, and d+e+f+g=1 is satisfied.

[0022] Calculate the failure probability of different buses, transformers, and lines under different faults as F bij , F tij , F lijk ;

[0023]

[0024]

[0025]

[0026] Among them, i represents the number of each bus, transformer, and line, from 1 to x; j represents the number of different fault types, from 1 to 4, which are single-phase grounding, two-phase short circuit, three-phase short circuit and two-phase grounding short circuit; d is the proportion of single-phase grounding; e is the proportion of two-phase short circuit; f is the proportion of three-phase short circuit; g is the proportion of two-phase grounding short circuit; k is the proportion of the position of the fault distance to a certain end point of the line, that is, the distance of the fault to a certain end point of the line is % of the line length

[0027] The above meets:

[0028] In the present invention, when the simulation scheme is electromagnetic transient simulation, the setting corresponding to the simulation scheme includes:

[0029] Assume that the number of times transformers 1 to y are closed is P1, P2...Py, then the probability of transformers 1 to n being closed is:

[0030]

[0031] In the present invention, when the simulation scheme is electromechanical transient simulation, the setting of the corresponding simulation scheme includes:

[0032] Assume that the various situations of large-capacity motor starting and motor group starting are 1 to z, and their times are Q1, Q2...Qz, respectively. Then the probabilities of large-capacity motor starting and motor group starting are:

[0033]

[0034] In the present invention, when the simulation scheme is a short-circuit simulation, obtaining and counting voltage sag information of each node in the power distribution network system includes:

[0035] The voltage sag information obtained by simulating different bus, transformer and line fault types at each of the nodes 1 to n is recorded as:

[0036] U1 bij , U1 tij , U1 lijk...Un bij , tij , lijk；

[0037] In the present invention, when the simulation scheme is electromagnetic transient simulation, obtaining and counting voltage sag information of each node in the power distribution network system includes:

[0038] The voltage sag information obtained by simulating the closing of transformers 1 to y at nodes 1 to n is recorded as U11, U12, ... U1 y , ...Un1, Un2...Un y .

[0039] In the present invention, when the simulation scheme is electromechanical transient simulation, obtaining and counting voltage sag information of each node in the power distribution network system includes:

[0040] The voltage sag information obtained by simulating the starting of large-capacity motors and motor groups from nodes 1 to n is recorded as U11, U12...U1 respectively. z , ...Un1, Un2...Un z

[0041] In the present invention, judging whether there is a voltage sag risk area in the power distribution network system according to the voltage sag information by using preset rules includes:

[0042] Analyzing the mathematical expectation of voltage sag of all or part of the nodes according to the voltage sag information of each node in the power distribution network system;

[0043] Find the nodes where the voltage sag is the most serious or does not meet the voltage sag standards, and mark these nodes as voltage sag risk areas.

[0044] In the present invention, the method of controlling voltage sag includes:

[0045] Adjust relay protection and / or adjust the grid structure.

[0046] In another aspect of the present invention, there is also provided a distribution network power system optimization device, comprising:

[0047] A model building unit, used to build a simulation model of a power distribution network system as an optimization object, and set parameters of the simulation model according to the power distribution network system;

[0048] A scheme setting unit, used for setting corresponding simulation schemes according to different causes of voltage sag; the simulation schemes include short circuit simulation, electromagnetic transient simulation and electromechanical transient simulation;

[0049] A simulation experiment unit, used to perform simulation experiments through the simulation model according to each of the simulation schemes, and obtain and count the voltage sag information of each node in the power distribution network;

[0050] A risk investigation unit, configured to determine whether there is a voltage sag risk area in the power distribution network according to the voltage sag information and by using preset rules;

[0051] The optimization unit is used to update the parameters of the nodes in the voltage sag risk area in the simulation model in a way of controlling the voltage sag and return them to the simulation experiment unit; and when there is no voltage sag risk area, generate an optimization plan for the distribution network power system according to the current structure and parameters of the simulation model.

[0052] In another aspect of the present invention, a memory is provided, comprising a software program, wherein the software program is suitable for a processor to execute the steps of the above-mentioned distribution network power system optimization method.

[0053] On the other hand, an embodiment of the present invention further provides a distribution network power system optimization device, which includes a computer program stored in a memory, and the computer program includes program instructions. When the program instructions are executed by a computer, the computer executes the methods described in the above aspects and achieves the same technical effects.

[0054] Compared with the prior art, the present invention has the following beneficial effects:

[0055] In the present invention, firstly, a simulation model of the power system of the distribution network is established and the parameters of the simulation model are set; then, according to the different causes of the voltage sag, three simulation schemes, namely, short-circuit simulation, electromagnetic transient simulation and electromechanical transient simulation, are set; by performing simulation experiments according to each simulation scheme, a voltage sag information set corresponding to each simulation scheme and including the voltage sag information of each node in the power system of the distribution network can be obtained; according to the voltage sag information, it can be judged that there is a voltage sag risk area in the power system of the distribution network, so that the voltage sag risk area is simulated and governed by updating the structure and / or parameters in the simulation model; then, simulation experiments are continuously performed through the updated simulation model to verify the effect of the simulation governance, so that when there is no voltage sag risk area in the simulation model, the optimization scheme of the power system of the distribution network can be obtained according to the structure and parameters of the current simulation model.

[0056] As can be seen from the above, in the present invention, on the one hand, various factors that cause voltage sag, such as transformer closing excitation inrush current, large motor starting or motor group starting, and various short-circuit faults, are analyzed, so that a comprehensive and reliable voltage sag assessment can be performed on the distribution network power system; in addition, the present invention can also automatically determine the voltage sag risk area in the distribution network power system through a simulation model, and obtain an optimization plan for the distribution network power system, thereby improving the optimization effect and efficiency of the distribution network power system.

[0057] The above description is only an overview of the technical solution of the present invention. In order to more clearly understand the technical means of the present invention and implement it according to the contents of the specification, and to make the above and other purposes, technical features and advantages of the present invention easier to understand, one or more preferred embodiments are listed below and described in detail with the accompanying drawings as follows. BRIEF DESCRIPTION OF THE DRAWINGS

[0058] Figure 1 is a step diagram of the method for optimizing the power system of the distribution network described in the present invention;

[0059] Figure 2 It is a structural schematic diagram of the power distribution network optimization device of the present invention;

[0060] Figure 3 It is a structural schematic diagram of the power distribution network optimization system described in the present invention. DETAILED DESCRIPTION

[0061] The specific implementation modes of the present invention are described in detail below in conjunction with the accompanying drawings, but it should be understood that the protection scope of the present invention is not limited by the specific implementation modes.

[0062] Unless explicitly stated otherwise, throughout the specification and claims, the term “comprise” or variations such as “include” or “comprising”, etc., will be understood to include the stated elements or components but not to exclude other elements or components.

[0063] In this document, for the convenience of description, spatial relative terms such as "below", "below", "down", "above", "above", "upper", etc. may be used to describe the relationship between one element or feature and another element or feature in the accompanying drawings. It should be understood that the spatial relative terms are intended to include different orientations of the object in use or operation in addition to the orientation depicted in the figure. For example, if the object in the figure is turned over, the element described as being "below" or "below" other elements or features will be oriented "above" the element or feature. Therefore, the exemplary term "below" can include both below and above. Objects may also have other orientations (rotated 90 degrees or other orientations) and the spatial relative terms used in this document should be interpreted accordingly.

[0064] In this document, the terms "first", "second", etc. are used to distinguish two different elements or parts, and are not used to limit a specific position or relative relationship. In other words, in some embodiments, the terms "first", "second", etc. can also be interchangeable.

[0065] Embodiment 1

[0066] In order to test and analyze the voltage sag with complex waveform on the test object, refer to Figure 1 In an embodiment of the present invention, a method for optimizing a power distribution network is provided, comprising the steps of:

[0067] S11, establishing a simulation model of a power distribution network system as an optimization object, and setting parameters of the simulation model according to the power distribution network system;

[0068] In the embodiment of the present invention, a simulation model of the power distribution network as the optimization object is first established. In practical applications, the simulation model should at least include motors and production machinery, component models related to the motor starting mode, lines, general loads, transformers, etc., and the upstream power grid of the distribution bus can be equivalent to an external power grid or an ideal power supply model. Preferably, a simulation model of the power distribution network of the entire enterprise or the simulated area should be established.

[0069] S12, setting corresponding simulation schemes according to different causes of voltage sag; the simulation schemes include short circuit simulation, electromagnetic transient simulation and electromechanical transient simulation;

[0070] In the enterprise power grid, there are many types of causes for voltage sag, including transformer closing excitation inrush current and large motor starting or motor group starting, as well as various fault short circuits. Corresponding to the above three types of causes for voltage sag, three corresponding simulation schemes are set in the embodiment of the present invention, namely short circuit simulation, electromagnetic transient simulation and electromechanical transient simulation. The simulation scheme in the embodiment of the present invention refers to the failure probability of each device, line and component in the power distribution network, the closing probability of each transformer, and the starting condition of large-capacity motor starting or motor group starting in the power distribution network. Specifically:

[0071] When the simulation scheme is short-circuit simulation, set the corresponding simulation scheme, including:

[0072] S21. Set the short-circuit fault rate of each bus, transformer and line in the power distribution network system respectively, and set the fault proportion of each short-circuit fault type in the short-circuit fault; the short-circuit fault types are single-phase grounding fault, two-phase short circuit, three-phase short circuit and two-phase grounding short circuit fault;

[0073] First, according to the actual number of short-circuit faults of each device, the short-circuit fault rate of each bus, transformer and line in the power distribution network is set respectively. Specifically:

[0074] According to the reliability statistics of the distribution network, the number of busbar, transformer and line failures is determined, which are counted as a, b, and c respectively. Then, F is calculated according to the following formula: b , F t , F l :

[0075]

[0076] Among them, F b Indicates the failure rate of all buses in the distribution network; F t Indicates the failure rate of all transformers in the distribution network; F l represents the failure rate of all lines in the distribution network; a represents the number of bus failures; b represents the number of transformer failures; c represents the number of line failures;

[0077] In the embodiment of the present invention, short-circuit faults are divided into four types: single-phase grounding fault, two-phase short circuit, three-phase short circuit and two-phase grounding short circuit fault; when setting the fault proportion of each short-circuit fault type in the short-circuit fault, it can be specifically:

[0078] According to the reliability statistics of the distribution network power system, it is determined that the proportions of single-phase grounding, two-phase short circuit, three-phase short circuit and two-phase grounding short circuit faults are d, e, f and g respectively. At this time, the condition that needs to be met is: d+e+f+g=1.

[0079] According to the following formula, the failure probability of different busbars, transformers and lines under different faults is calculated as F bij , F tij , F lijk ;

[0080]

[0081]

[0082]

[0083] Among them, i represents the number of each bus, transformer, and line, from 1 to x; j represents the number of different fault types, from 1 to 4, which are single-phase grounding, two-phase short circuit, three-phase short circuit and two-phase grounding short circuit; d is the proportion of single-phase grounding; e is the proportion of two-phase short circuit; f is the proportion of three-phase short circuit; g is the proportion of two-phase grounding short circuit; k is the proportion of the position of the fault distance to a certain end point of the line, that is, the distance of the fault to a certain end point of the line is % of the line length

[0084] The above meets:

[0085] S22. Generate input parameters for short-circuit simulation of the simulation model according to the short-circuit failure rate and the failure proportion.

[0086] The input parameters for the simulation model generated according to the short-circuit failure rate and the failure proportion can be used to simulate various short-circuit failure situations consistent with the current distribution network power system.

[0087] Next, in the embodiment of the present invention, when the simulation scheme is electromagnetic transient simulation, setting the corresponding simulation scheme may specifically include:

[0088] Assume that the number of times y transformers (numbered 1 to y) are closed is P1, P2...Py, then the probability of each closing of n transformers (numbered 1 to n) can be calculated by the following formula:

[0089]

[0090] Next, in the embodiment of the present invention, when the simulation scheme is electromechanical transient simulation, setting the corresponding simulation scheme may specifically include:

[0091] Assume that the various situations of large-capacity motor starting and motor group starting are 1 to z, and their times are Q1, Q2...Qz, respectively. Then the probabilities of large-capacity motor starting and motor group starting are:

[0092]

[0093] When a group of motors start or a large-capacity motor starts, it is possible to cause a voltage sag. In an embodiment of the present invention, the probability of various groups of motors starting or large-capacity motors starting is determined based on the specific starting information of each motor in the power distribution network.

[0094] S13, performing simulation experiments through the simulation model according to each of the simulation schemes, obtaining and counting voltage sag information of each node in the power distribution network;

[0095] After setting up the three simulation schemes of short-circuit simulation, electromagnetic transient simulation and electromechanical transient simulation, the three simulation schemes are simulated one by one through the simulation model to obtain the voltage sag information of each node in the corresponding distribution network power system; after recording and counting the voltage sag information results of each simulation experiment, the voltage sag information set of the simulation experiment can be obtained.

[0096] In an embodiment of the present invention, when the simulation scheme is a short-circuit simulation, obtaining and counting voltage sag information of each node in the power distribution network system may specifically include:

[0097] The voltage sag information obtained by simulating different bus, transformer and line fault types for each node 1 to n is recorded as:

[0098] U1 bij , U1 tij , U1 lijk ...Un bij , tij , lijk ;

[0099] Specifically, the short-circuit simulation determines the simulated state of each bus, transformer and line in the power grid system as the input of the simulation experiment based on the short-circuit failure rate and the failure proportion, and then obtains the experimental results of the simulation experiment through the simulation model; the experimental results are a voltage sag information set composed of the voltage sag information of each node.

[0100] In an embodiment of the present invention, when the simulation scheme is electromagnetic transient simulation, obtaining and counting voltage sag information of each node in the power distribution network system may specifically include:

[0101] The voltage sag information obtained by simulating the closing of transformers 1 to y at nodes 1 to n is recorded as U11, U12, ... U1 y , ...Un1, Un2...Un y .

[0102] Specifically, the electromagnetic transient simulation determines the simulated state of whether each transformer in the power grid is closed or not in each simulation experiment according to the closing probability of each transformer as the input of this simulation experiment, and then obtains the experimental results of this simulation experiment through the simulation model; the experimental results are a voltage sag information set composed of the voltage sag information of each node.

[0103] In an embodiment of the present invention, when the simulation scheme is electromechanical transient simulation, obtaining and analyzing voltage sag information of each node in the power distribution network system may specifically include:

[0104] The voltage sag information obtained by simulating the starting of large-capacity motors and motor groups from nodes 1 to n is recorded as U11, U12...U1 respectively. z , ...Un1, Un2...Un z .

[0105] Specifically, the electromechanical transient simulation determines the combined simulation state of whether each generator in the power grid system is started or not in each simulation experiment according to the closing probability of each transformer as the input of this simulation experiment, and then obtains the experimental results of this simulation experiment through the simulation model; the experimental results are a voltage sag information set composed of the voltage sag information of each node.

[0106] S14, judging whether there is a voltage sag risk area in the power distribution network according to the voltage sag information by using preset rules;

[0107] After each simulation experiment, the corresponding voltage sag information set can be obtained. By analyzing and calculating the voltage sag information set, it can be determined whether there is a voltage sag risk area in the power distribution network during this experiment. The method can be:

[0108] S41, analyzing the mathematical expectation of voltage sag of all or part of the nodes according to the voltage sag information of each node in the power distribution network system;

[0109] S42, finding the node locations where the voltage sag is the most serious or does not meet the voltage sag standard, and marking these nodes as voltage sag risk areas;

[0110] This includes: According to the short-circuit fault analysis, the mathematical expectation value of the voltage sag caused by the short-circuit fault is obtained at each node: Assuming that the mathematical expectation of the voltage sag of nodes 1 to n under different busbar, transformer, and line fault types is U1, U2...Un, then:

[0111]

[0112] …

[0113]

[0114] According to the transformer closing analysis, the mathematical expectation value of the voltage sag caused by the transformer closing excitation inrush current is obtained: Let the mathematical expectation of the voltage sag of nodes 1 to n under different transformer closing conditions be U1, U2...Un, then:

[0115]

[0116] …

[0117]

[0118] According to the analysis of large-capacity motor starting and motor group starting, the mathematical expectation value of voltage sag caused by large motor starting or motor group starting at each node is obtained: Let the mathematical expectation of voltage sag of nodes 1 to n under different large-capacity motor starting and motor group starting be U1, U2...Un, then:

[0119]

[0120] …

[0121]

[0122] S15. If yes, in the simulation model, update the parameters of the nodes in the voltage sag risk area in a manner to control the voltage sag and return to step S12; if no, generate an optimization plan for the distribution network power system according to the current structure and parameters of the simulation model.

[0123] When the result of judging whether there is a voltage sag risk area in the distribution network power system is yes, it means that there is a voltage sag risk in the distribution network power system and it needs to be optimized; at this time, the corresponding control plan can be determined according to the type of cause and regional location of the voltage sag, for example, it can be to adjust the relay protection or adjust the grid structure, etc.; according to the control plan, the structure and parameters in the simulation model can be adjusted accordingly, and then the simulation model is updated; after the simulation model is updated, it is necessary to return to step S12 to re-perform the simulation experiment to verify whether there is still a voltage sag risk area in the updated simulation model; through continuous iterative cycles, until there is no voltage sag risk area in the updated simulation model.

[0124] When there is no voltage sag risk area in the simulation model, it means that the structure and parameters in the simulation model have reached the optimization standard and the risk of voltage sag has been eliminated. Therefore, an optimization plan for the distribution network power system can be generated based on the current structure and parameters of the simulation model.

[0125] To sum up, in the embodiment of the present invention, firstly, a simulation model of the power system of the distribution network is established and the parameters of the simulation model are set; then, according to the different causes of the voltage sag, three simulation schemes, namely, short-circuit simulation, electromagnetic transient simulation and electromechanical transient simulation, are set; by performing simulation experiments according to each simulation scheme, a voltage sag information set corresponding to each simulation scheme, including the voltage sag information of each node in the power system of the distribution network, can be obtained; according to the voltage sag information, it can be judged that there is a voltage sag risk area in the power system of the distribution network, so that the voltage sag risk area is simulated and governed by updating the structure and / or parameters in the simulation model; then, simulation experiments are continuously performed through the updated simulation model to verify the effect of the simulation governance, so that when there is no voltage sag risk area in the simulation model, the optimization scheme of the power system of the distribution network can be obtained according to the structure and parameters of the current simulation model.

[0126] From the above, it can be seen that in the embodiment of the present invention, on the one hand, various factors that cause voltage sag, such as transformer closing excitation inrush current, large motor starting or motor group starting, and various short-circuit faults, are analyzed, so that the distribution network power system can be comprehensively and reliably evaluated for voltage sag; in addition, the embodiment of the present invention can also automatically determine the voltage sag risk area in the distribution network power system through a simulation model, and obtain an optimization plan for the distribution network power system, thereby effectively improving the optimization effect and efficiency of the distribution network power system.

[0127] Embodiment 2

[0128] In another aspect of the embodiment of the present invention, a power distribution network optimization device is also provided. Figure 2 A schematic diagram showing the structure of a power distribution network optimization device provided by an embodiment of the present invention is shown. The power distribution network optimization device is Figure 1 The device corresponding to the method of the power distribution network optimization device described in the corresponding embodiment. Specifically, the power distribution network optimization device in the embodiment of the present invention includes:

[0129] The model building unit 01 is used to build a simulation model of the power distribution network system as an optimization object, and set the parameters of the simulation model according to the power distribution network system;

[0130] The scheme setting unit 02 is used to set corresponding simulation schemes according to different causes of voltage sag; the simulation schemes include short circuit simulation, electromagnetic transient simulation and electromechanical transient simulation;

[0131] The simulation experiment unit 03 is used to perform simulation experiments through the simulation model according to each of the simulation schemes, and obtain and count the voltage sag information of each node in the power distribution network system;

[0132] The risk checking unit 04 is used to determine whether there is a voltage sag risk area in the power distribution network according to the voltage sag information and preset rules;

[0133] The optimization unit 05 is used to update the parameters of the nodes in the voltage sag risk area in the simulation model in a manner to control the voltage sag and return them to the simulation experiment unit; and when there is no voltage sag risk area, generate an optimization plan for the distribution network power system according to the current structure and parameters of the simulation model.

[0134] Since the working principle and beneficial effects of the power distribution network optimization device in the embodiment of the present invention have been Figure 1 The corresponding distribution network power system optimization method is also recorded and explained, so they can be referenced by each other and will not be repeated here.

[0135] Embodiment 3

[0136] In an embodiment of the present invention, a memory is further provided, wherein the memory includes a software program, and the software program is suitable for the processor to execute Figure 1 The corresponding steps in the distribution network power system optimization method.

[0137] The embodiments of the present invention can be implemented by means of a software program, that is, by writing a program for implementing Figure 1 The corresponding software program (and instruction set) for each step in the distribution network power system optimization method is stored in a storage device, and the storage device is arranged in a computer device, so that the software program can be called by the processor of the computer device to achieve the purpose of the embodiment of the present invention.

[0138] Embodiment 4

[0139] In an embodiment of the present invention, a distribution network power system optimization device is also provided. The memory included in the distribution network power system optimization device includes a corresponding computer program product. When the program instructions included in the computer program product are executed by a computer, the computer can execute the distribution network power system optimization method described in the above aspects and achieve the same technical effect.

[0140] Figure 3 Schematic diagram of the hardware structure of the power distribution network optimization device as an electronic device in an embodiment of the present invention. Figure 3 As shown, the device includes one or more processors 610, a bus 630, and a memory 620. Taking one processor 610 as an example, the device may also include: an input device 640, and an output device 650.

[0141] The processor 610, the memory 620, the input device 640 and the output device 650 may be connected via a bus or other means. Figure 3 The connection via bus 630 is taken as an example.

[0142] The memory 620 is a non-transitory computer-readable storage medium that can be used to store non-transitory software programs, non-transitory computer executable programs, and modules. The processor 610 executes various functional applications and data processing of the electronic device by running the non-transitory software programs, instructions, and modules stored in the memory 620, that is, the processing method of the above method embodiment is implemented.

[0143] The memory 620 may include a program storage area and a data storage area, wherein the program storage area may store an operating system, an application required for at least one function; the data storage area may store data, etc. In addition, the memory 620 may include a high-speed random access memory, and may also include a non-transitory memory, such as at least one disk storage device, a flash memory device, or other non-transitory solid-state storage device. In some embodiments, the memory 620 may optionally include a memory remotely arranged relative to the processor 610, and these remote memories may be connected to the processing device via a network. Examples of the above-mentioned network include, but are not limited to, the Internet, an intranet, a local area network, a mobile communication network, and combinations thereof.

[0144] The input device 640 can receive input digital or character information and generate signal input. The output device 650 can include a display device such as a display screen.

[0145] The one or more modules are stored in the memory 620, and when executed by the one or more processors 610, perform:

[0146] S11, establishing a simulation model of a power distribution network system as an optimization object, and setting parameters of the simulation model according to the power distribution network system;

[0147] S12, setting corresponding simulation schemes according to different causes of voltage sag; the simulation schemes include short circuit simulation, electromagnetic transient simulation and electromechanical transient simulation;

[0148] S13, performing simulation experiments through the simulation model according to each of the simulation schemes, obtaining and counting voltage sag information of each node in the power distribution network;

[0149] S14, judging whether there is a voltage sag risk area in the power distribution network according to the voltage sag information by using preset rules;

[0150] S15. If yes, in the simulation model, update the parameters of the nodes in the voltage sag risk area in a manner to control the voltage sag and return to step S12; if no, generate an optimization plan for the distribution network power system according to the current structure and parameters of the simulation model.

[0151] The above product can execute the method provided by the embodiment of the present invention, and has the functional modules and beneficial effects corresponding to the execution method. For technical details not described in detail in this embodiment, please refer to the methods provided by other embodiments of the present invention.

[0152] In the several embodiments provided by the present invention, it should be understood that the disclosed systems, devices and methods can be implemented in other ways. For example, the device embodiments described above are only schematic. For example, the division of the units is only a logical function division. There may be other division methods in actual implementation, such as multiple units or components can be combined or integrated into another system, or some features can be ignored or not executed. Another point is that the mutual coupling or direct coupling or communication connection shown or discussed can be an indirect coupling or communication connection through some interfaces, devices or units, which can be electrical, mechanical or other forms.

[0153] The units described as separate components may or may not be physically separated, and the components shown as units may or may not be physical units, that is, they may be located in one place or distributed on multiple network units. Some or all of the units may be selected according to actual needs to achieve the purpose of the solution of this embodiment.

[0154] In addition, each functional unit in each embodiment of the present invention may be integrated into one processing unit, or each unit may exist physically separately, or two or more units may be integrated into one unit. The above-mentioned integrated unit may be implemented in the form of hardware or in the form of software functional units.

[0155] If the integrated unit is implemented in the form of a software functional unit and sold or used as an independent product, it can be stored in a computer-readable storage medium. Based on this understanding, the technical solution of the present invention is essentially or the part that contributes to the prior art or all or part of the technical solution can be embodied in the form of a software product. The computer software product is stored in a storage device, including several instructions to enable a computer device (which can be a personal computer, server, or network device, etc.) to perform all or part of the steps of the method described in each embodiment of the present invention. The aforementioned storage device includes: U disk, mobile hard disk, read-only memory (ROM, Read-Only Memory), random access memory (RAM, Random Access Memory), ReRAM, MRAM, PCM, NAND Flash, NOR Flash, Memristor, disk or optical disk and other media that can store program codes.

[0156] As described above, 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 thereof may be replaced by equivalents. However, these 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.

Claims

1. A method for optimizing a power distribution network, characterized in that: Includes steps: S11, establishing a simulation model of a power distribution network system as an optimization object, and setting parameters of the simulation model according to the power distribution network system; S12, setting corresponding simulation schemes according to different causes of voltage sag; the simulation schemes include short circuit simulation, electromagnetic transient simulation and electromechanical transient simulation; S13, performing simulation experiments through the simulation model according to each of the simulation schemes, obtaining and counting voltage sag information of each node in the power distribution network; S14, judging whether there is a voltage sag risk area in the power distribution network according to the voltage sag information and using preset rules; S15, if yes, in the simulation model, update parameters of the nodes in the voltage sag risk area in a manner of controlling the voltage sag and return to step S12; If not, generating an optimization scheme for the power distribution network system according to the current structure and parameters of the simulation model; The update parameters include: When the result of judging whether there is a voltage sag risk area in the power system of the distribution network is yes, it means that there is a voltage sag risk in the power system of the distribution network and optimization is required; Determine a corresponding treatment plan based on the type of cause and regional location of the voltage sag; adjust the structure and parameters in the simulation model accordingly according to the treatment plan, and then update the simulation model; after the simulation model is updated, it is necessary to return to step S12 to re-perform the simulation experiment to verify whether the updated simulation model still has a voltage sag risk area; through continuous iterative cycles, until the updated simulation model does not have a voltage sag risk area.

2. The method for optimizing the power distribution network according to claim 1, characterized in that: When the simulation scheme is a short circuit simulation, the setting corresponding to the simulation scheme includes: S21, respectively set the short-circuit fault rate of each bus, transformer and line in the power distribution network system, and set the fault proportion of each short-circuit fault type in the short-circuit fault; the short-circuit fault types are single-phase grounding fault, two-phase short circuit, three-phase short circuit and two-phase grounding short circuit fault; S22. Generate input parameters for short-circuit simulation of the simulation model according to the short-circuit failure rate and the failure proportion.

3. The method for optimizing the power distribution network according to claim 2, characterized in that: The short-circuit failure rate of each bus, transformer and line in the power distribution network is set respectively, and the failure proportion of each short-circuit failure type in the short-circuit failure is set, including: According to the reliability statistics of the distribution network, the number of faults of the busbar, transformer and line is determined, which are counted as a, b and c respectively. F is calculated according to the following formula b , F t , F l : Among them, F b Indicates the failure rate of all buses in the distribution network; F t Indicates the failure rate of all transformers in the distribution network; F l represents the failure rate of all lines in the distribution network; a represents the number of bus failures; b represents the number of transformer failures; c represents the number of line failures; According to statistical data, the proportions of single-phase grounding, two-phase short circuit, three-phase short circuit, and two-phase grounding short circuit faults are set to d:e:f:g, and d+e+f+g=1; Calculate the failure probability of different buses, transformers, and lines under different faults respectively: F bij , F tij , F lijk ; Among them, i represents the number of each bus, transformer, and line, from 1 to x; j represents the number of different fault types, from 1 to 4, which are single-phase grounding, two-phase short circuit, three-phase short circuit, and two-phase grounding short circuit; d represents the proportion of single-phase grounding; e represents the proportion of two-phase short circuit; f represents the proportion of three-phase short circuit; g represents the proportion of two-phase grounding short circuit; k represents the number of faults, that is, the distance between each fault and a certain end point of the line is respectively the length of the line. The above meets:

4. The method for optimizing the power distribution network according to claim 1, characterized in that: When the simulation scheme is electromagnetic transient simulation, the setting corresponding to the simulation scheme includes: Assume that the number of times y transformers 1 to y are closed is P1, P2...Py, then the probability of y transformers 1 to y being closed is:

5. The method for optimizing the power distribution network according to claim 1, characterized in that: When the simulation scheme is electromechanical transient simulation, the setting of the corresponding simulation scheme includes: Assume that the various situations of large-capacity motor starting and motor group starting are 1 to z, and their times are Q1, Q2...Qz, respectively. Then the probabilities of large-capacity motor starting and motor group starting are:

6. The method for optimizing the power distribution network according to claim 3, characterized in that: When the simulation scheme is a short-circuit simulation, obtaining and counting voltage sag information of each node in the power distribution network system includes: The voltage sag information obtained by simulating different bus, transformer and line fault types at each of the nodes 1 to n is recorded as: U1 bij ,U1 tij ,U1 lijh ……A bij ,A tij ,A lijh .

7. The method for optimizing the power distribution network according to claim 4, characterized in that: When the simulation scheme is electromagnetic transient simulation, obtaining and counting voltage sag information of each node in the power distribution network system includes: The voltage sag information obtained by simulating the closing of transformers 1 to y at nodes 1 to n is recorded as U11, U12, ... U1 y , ...Un1, Un2...Un y .

8. The method for optimizing the power distribution network according to claim 5, characterized in that: When the simulation scheme is electromechanical transient simulation, obtaining and counting voltage sag information of each node in the power distribution network system includes: The voltage sag information obtained by simulating the starting of large-capacity motors and motor groups from nodes 1 to n is recorded as U11, U12...U1 respectively. z , ...Un1, Un2...Un z .

9. The method for optimizing the power distribution network according to any one of claims 3 to 8, characterized in that: The determining whether there is a voltage sag risk area in the power distribution network according to the voltage sag information by using a preset rule includes: Analyzing the mathematical expectation of voltage sag of all or part of the nodes according to the voltage sag information of each node in the power distribution network system; Find the nodes where the voltage sag is the most serious or does not meet the voltage sag standards, and mark these nodes as voltage sag risk areas.

10. The method for optimizing the power distribution network according to claim 1, characterized in that: The method for controlling voltage sag includes: Adjust relay protection and / or adjust the grid structure.

11. A power system optimization device for a distribution network, characterized in that: include: A model building unit, used to build a simulation model of a power distribution network system as an optimization object, and set parameters of the simulation model according to the power distribution network system; A scheme setting unit, used for setting corresponding simulation schemes according to different causes of voltage sag; the simulation schemes include short circuit simulation, electromagnetic transient simulation and electromechanical transient simulation; A simulation experiment unit, used to perform simulation experiments through the simulation model according to each of the simulation schemes, and obtain and count the voltage sag information of each node in the power distribution network; A risk investigation unit, configured to determine whether there is a voltage sag risk area in the power distribution network according to the voltage sag information and by using preset rules; An optimization unit, used for updating parameters of nodes in the voltage sag risk area in the simulation model in a manner of controlling the voltage sag and returning the parameters to the simulation experiment unit; and generating an optimization scheme for the power distribution network according to the current structure and parameters of the simulation model when there is no voltage sag risk area; The update parameters include: When the result of judging whether there is a voltage sag risk area in the power system of the distribution network is yes, it means that there is a voltage sag risk in the power system of the distribution network and optimization is required; Determine the corresponding control plan according to the type of cause and regional location of the voltage sag; adjust the structure and parameters in the simulation model accordingly according to the control plan, and then update the simulation model; after the simulation model is updated, it is necessary to return to the plan setting unit to re-perform the simulation experiment to verify whether the updated simulation model still has a voltage sag risk area; through continuous iterative cycles, until the updated simulation model does not have a voltage sag risk area.

12. A memory, characterized in that: The method comprises a software program, wherein the software program is suitable for executing the steps of the power distribution network optimization method according to any one of claims 1 to 7 by a processor.

13. A power distribution network optimization device, characterized in that: comprising a bus, a processor and a memory as claimed in claim 12; The bus is used to connect the memory and the processor; The processor is configured to execute an instruction set in the memory.

Images