Automatic management system of intelligent power distribution network

Abstract

The invention provides an automatic management system for an intelligent power distribution network, and relates to the technical field of power grid management, and the system comprises the steps: monitoring the power distribution network in real time, obtaining the current operation data of the power distribution network in the current time period, and determining the current operation scene of the power distribution network; judging the current operation state of the power distribution network in real time according to the current operation data and the current operation scene, and performing operation management on the power distribution network according to a preset power distribution network operation constraint item; a power distribution network model is established according to the historical operation data, and when the current operation state of the power distribution network is judged to be a fault operation state, fault equipment is positioned and isolated, and fault management is performed on the power distribution network; predicting the load demand of the power distribution network in the next operation period, and performing operation optimization management on the power distribution network in combination with operation management and fault management; automatic management of the power distribution network is effectively realized, and stable operation of the power distribution network is ensured.

Description

Technical Field

[0001] The present invention relates to the technical field of power grid management, and in particular to an intelligent power distribution network automation management system. Background Art

[0002] The distribution network is an important component of the power grid system, responsible for distributing electricity in the power grid system to various power consumption terminals. The reliability and efficiency of the distribution network directly affect the power consumption experience of the power consumption terminals. With the increasing complexity of the power grid system and the increasing number of power consumption terminals, the manual management of the distribution network is inefficient and of low quality, and cannot meet the management needs of the distribution network.

[0003] Therefore, the present invention provides an intelligent distribution network automation management system. Summary of the invention

[0004] The present invention provides an intelligent distribution network automation management system, which determines the current operating status of the distribution network in real time according to the current operating data and the current operating scenario, manages the operation of the distribution network according to preset distribution network operation constraints, establishes a distribution network model according to historical operating data, locates and isolates faulty equipment and predicts the load demand of the distribution network, effectively realizes the automated management of the distribution network and ensures the stable operation of the distribution network.

[0005] The present invention provides an intelligent distribution network automation management system, comprising: The operation monitoring module is used to monitor the distribution network in real time, obtain the current operation data of the distribution network in the current period and determine the current operation scenario of the distribution network; The operation management module is used to determine the current operation status of the distribution network in real time according to the current operation data and the current operation scenario, and to manage the operation of the distribution network according to the preset distribution network operation constraints; The fault management module is used to establish a distribution network model based on historical operation data. When the current operation state of the distribution network is determined to be a faulty operation state, the faulty equipment is located and isolated, and the distribution network is fault-managed. The prediction and optimization module is used to predict the load demand of the distribution network in the next operating period and to optimize the operation of the distribution network in combination with operation management and fault management.

[0006] According to the present invention, a smart distribution network automation management system is provided, and an operation monitoring module includes: A monitoring deployment unit is used to acquire distribution network equipment, deploy sensors at the distribution network equipment, and perform real-time monitoring of the distribution network, wherein the distribution network equipment includes: substation equipment, distribution line equipment, transformer equipment, distribution switch equipment, distribution protection equipment, and distribution meter equipment; An operation data unit is used to obtain monitoring data of the distribution network in the current period according to the sensor, perform data preprocessing and data cleaning on the monitoring data, and determine the current operation data of the distribution network in the current period, wherein the current operation data includes: current operation data, voltage operation data, power operation data, temperature operation data, position operation data and fault operation data; The operation scenario unit is used to match data in the operation scenario of the distribution network according to the current operation data to determine the current operation scenario of the distribution network.

[0007] According to an intelligent distribution network automation management system provided by the present invention, an operation scenario unit includes: An operation scenario setting block is used to obtain historical operation data of the distribution network and set the operation scenario of the distribution network, wherein the operation scenarios include: stable operation scenario, fluctuating operation scenario, overload operation scenario and fault operation scenario; The scene matching block is used to compare the current operation data with the historical operation data corresponding to the operation scene of the distribution network item by item. When the similarity of each operation data is not less than the preset matching similarity, the corresponding operation scene is determined to be the current operation scene of the distribution network.

[0008] According to the present invention, a smart distribution network automation management system, an operation management module, includes: A range determination unit, used to determine the range of operation data corresponding to each operation state according to the historical operation data corresponding to the current operation scenario; A state determination unit, used to determine the current operation state of the distribution network according to the location of the current operation data in the operation data range, wherein the current operation state includes: normal operation state, early warning operation state, alarm operation state and fault operation state; An operation constraint item unit, used for obtaining preset distribution network operation constraint items according to historical operation data corresponding to the current operation scenario, wherein the preset distribution network operation constraint items include: preset voltage constraint items, preset current constraint items, preset power constraint items and preset fault redundancy constraint items; The operation management unit is used to manage the operation of the distribution network according to the preset distribution network operation constraints and the current operation status of the distribution network, and control the current operation status of the distribution network to change to a normal operation status, wherein the operation management includes: voltage regulation, power compensation, load transfer and fault isolation.

[0009] According to the present invention, a smart distribution network automation management system, a fault management module, includes: A distribution network model unit, used to construct a distribution network model based on historical operation data; A fault management unit, configured to obtain a fault period corresponding to the faulty operation state when determining that the current operation state of the distribution network is a faulty operation state; Perform static model analysis on the fault operation status according to the distribution network model, set the minimum static model analysis period, and split the fault period; The current operation data corresponding to each segment splitting result is input into the distribution network model and the static fault equipment is located according to the preset fault detection strategy; Remove static faulty equipment from the distribution network model, input current operating data for dynamic model analysis, and locate dynamic faulty equipment; Static fault devices and dynamic fault devices are eliminated from the distribution network model, and current operation data is input to determine the current operation state of the distribution network. When it is determined that the current operation state of the distribution network is still a faulty operation state, static model analysis and dynamic model analysis are re-performed based on the distribution network model in which the static fault devices and dynamic fault devices are eliminated; When it is determined that the current operating state of the distribution network is not a faulty operating state, static faulty devices and dynamic faulty devices are summarized to determine the faulty devices in the current period of the distribution network; A fault processing unit, used to isolate the faulty device and identify the fault type of the faulty device; Execute the fault recovery strategy according to the fault type. When the fault of the faulty device is eliminated, cancel the fault isolation and reconnect the faulty device to the distribution network.

[0010] According to the present invention, a smart distribution network automation management system, a prediction optimization module, includes: A load demand prediction unit is used to obtain historical load data and current load data, extract load characteristics from the historical load data, and predict the load demand of the next operation period of the distribution network based on the current load data; According to the load demand of the distribution network in the next operation period predicted by the distribution network equipment, equipment matching is performed to determine the equipment load demand of each distribution network equipment in the next operation period; Vector construction unit, used to construct the historical time difference vector of the distribution network ,in, Indicates the h1th historical period difference; Indicates the actual time period length in the h1th historical case; represents the length of the forecast period in the h1th historical case; The prediction duration setting unit is used to set the prediction duration according to the historical time period difference vector And in combination with the duration Td of the current period of the distribution network, the duration Yt of the predicted period of the distribution network based on the duration of the current period is set; ; ; in, represents the duration correction function; Indicates that based on all The variance of Indicates the set duration; Indicates all Satisfied the number of A load demand correction unit, used to obtain a time period for reconnecting to the distribution network based on the faulty equipment in the current time period of the distribution network and the predicted faulty equipment; If the faulty equipment is reconnected to the distribution network within the forecast period, the equipment load demand of the faulty equipment in the next operating period is retained; If the faulty device is not reconnected to the distribution network within the forecast period, the equipment load demand of the faulty device in the next operating period will be transferred and distributed to other adjacent distribution network equipment, and the equipment load demand of other distribution network equipment in the next operating period will be corrected; The operation optimization unit is used to set operation optimization targets according to operation management and fault management, and perform operation optimization management of the distribution network according to the operation optimization targets, wherein the operation optimization targets include: operation management optimization targets, operation constraint optimization targets and operation load demand optimization targets.

[0011] According to the present invention, a smart distribution network automation management system, a prediction optimization module, further includes: An operation optimization evaluation unit is used to obtain the number of faulty devices after the operation optimization management of the distribution network is carried out, and determine the load loss amount of the distribution network; Obtain the load distribution of the distribution network, perform operation optimization management and evaluation on the distribution network, and obtain the optimization evaluation value of the distribution network; ;in, represents the optimized evaluation value of the distribution network; Indicates the number of faulty devices after the distribution network is optimized for operation management; Indicates the total number of distribution network equipment involved in the distribution network; Indicates the distribution network The quantitative value of the equipment load demand for optimizing the operation of a normally operating device; Indicates the distribution network Quantified value of actual equipment load data for optimizing operation management of normal operating equipment; Indicates the distribution network Quantified value of the load loss of each faulty device; When the optimization evaluation value of the distribution network is not lower than the preset optimization value, it is determined that the operation optimization management of the distribution network is qualified.

[0012] According to the present invention, a smart distribution network automation management system further includes: The operation visualization module is used to visualize the current operation scenario of the distribution network, faulty equipment, and the operation optimization management of the distribution network; Operation safety module, used to evaluate and predict the operation safety of the distribution network, and preset safety control strategies. When there is an operation risk in the operation of the distribution network, the corresponding preset safety control strategies will be automatically executed; Data encryption is performed during the operation optimization management process of the distribution network.

[0013] Compared with the prior art, the present invention has the following beneficial effects: By real-time monitoring of the distribution network, the current operating data of the distribution network in the current period is obtained and the current operating scenario of the distribution network is determined; the current operating status of the distribution network is determined in real time according to the current operating data and the current operating scenario, and the operation of the distribution network is managed according to the preset distribution network operation constraints; a distribution network model is established based on historical operation data, and when it is determined that the current operating status of the distribution network is a faulty operating status, the faulty equipment is located and isolated, and the distribution network is managed for faults; the load demand of the distribution network in the next operating period is predicted, and the operation of the distribution network is optimized in combination with operation management and fault management; the automated management of the distribution network is effectively realized, ensuring the stable operation of the distribution network.

[0014] Other features and advantages of the present invention will be described in the following description, and partly become apparent from the description, or understood by practicing the present invention. The purpose and other advantages of the present invention can be realized and obtained by the structures particularly pointed out in the written description and the accompanying drawings.

[0015] The technical solution of the present invention is further described in detail below through the accompanying drawings and embodiments. BRIEF DESCRIPTION OF THE DRAWINGS

[0016] The accompanying drawings are used to provide a further understanding of the present invention and constitute a part of the specification. Together with the embodiments of the present invention, they are used to explain the present invention and do not constitute a limitation of the present invention. In the accompanying drawings: Figure 1 It is a structural schematic diagram of an intelligent distribution network automation management system in an embodiment of the present invention. DETAILED DESCRIPTION

[0018] The preferred embodiments of the present invention are described below in conjunction with the accompanying drawings. It should be understood that the preferred embodiments described herein are only used to illustrate and explain the present invention, and are not used to limit the present invention.

[0019] Embodiment 1:

[0020] The embodiment of the present invention provides an intelligent distribution network automation management system, such as Figure 1 As shown, including: The operation monitoring module is used to monitor the distribution network in real time, obtain the current operation data of the distribution network in the current period and determine the current operation scenario of the distribution network; The operation management module is used to determine the current operation status of the distribution network in real time according to the current operation data and the current operation scenario, and to manage the operation of the distribution network according to the preset distribution network operation constraints; The fault management module is used to establish a distribution network model based on historical operation data. When the current operation state of the distribution network is determined to be a faulty operation state, the faulty equipment is located and isolated, and the distribution network is fault-managed. The prediction and optimization module is used to predict the load demand of the distribution network in the next operating period and to optimize the operation of the distribution network in combination with operation management and fault management.

[0021] In this embodiment, the current operation data refers to data used to accurately represent the operation of the power distribution network in the current period.

[0022] In this embodiment, the current operation scenario refers to the operation scenario of the distribution network in the current period.

[0023] In this embodiment, the current operating state refers to the operating state of the power distribution network in the current period.

[0024] In this embodiment, the preset power distribution network operation constraint item refers to a preset constraint item used to achieve the normal operation state of the power distribution network.

[0025] In this embodiment, the operation management refers to the management of the distribution network according to preset distribution network operation constraints and the current operation status of the distribution network.

[0026] In this embodiment, fault management refers to the management of locating and isolating faulty equipment in the distribution network.

[0027] In this embodiment, the operation optimization management refers to the management of the distribution network based on the load demand of the next operation period of the distribution network in combination with the operation management and the fault management.

[0028] In this embodiment, the historical operation data refers to the operation data of the power distribution network in the historical period.

[0029] In this embodiment, the distribution network model refers to a model constructed based on historical operation data and used to represent the distribution network.

[0030] In this embodiment, the fault operation state refers to the operation state corresponding to the fault of the distribution network, for example, 1. Line fault: including disconnection, short circuit, grounding, overload, etc. These faults may be caused by reasons such as line aging, insulation damage, weather influence, etc. 2. Equipment failure: including failure of equipment such as transformers, circuit breakers, and distribution cabinets. These faults may be caused by reasons such as equipment aging, insulation damage, and improper operation.

[0031] In this embodiment, the faulty device refers to a device that is unable to distribute power in the current period of the power distribution network.

[0032] In this embodiment, the load demand refers to the demand for load data in the next operation period of the distribution network, for example, the required load is 5000kw.

[0033] The working principle and beneficial effects of the above technical solution are: through real-time monitoring of the distribution network, the current operating data of the distribution network in the current period is obtained and the current operating scenario of the distribution network is determined; the current operating state of the distribution network is determined in real time according to the current operating data and the current operating scenario, and the distribution network is operated and managed according to the preset distribution network operation constraints; a distribution network model is established according to historical operation data, and when it is determined that the current operating state of the distribution network is a faulty operating state, the faulty equipment is located and isolated, and the distribution network is fault managed; the load demand of the distribution network in the next operating period is predicted and the operation optimization management of the distribution network is performed in combination with operation management and fault management; the automated management of the distribution network is effectively realized, ensuring the stable operation of the distribution network.

[0034] Embodiment 2:

[0035] The embodiment of the present invention provides an intelligent distribution network automation management system, an operation monitoring module, including: A monitoring deployment unit is used to acquire distribution network equipment, deploy sensors at the distribution network equipment, and perform real-time monitoring of the distribution network, wherein the distribution network equipment includes: substation equipment, distribution line equipment, transformer equipment, distribution switch equipment, distribution protection equipment, and distribution meter equipment; An operation data unit is used to obtain monitoring data of the distribution network in the current period according to the sensor, perform data preprocessing and data cleaning on the monitoring data, and determine the current operation data of the distribution network in the current period, wherein the current operation data includes: current operation data, voltage operation data, power operation data, temperature operation data, position operation data and fault operation data; The operation scenario unit is used to match data in the operation scenario of the distribution network according to the current operation data to determine the current operation scenario of the distribution network.

[0036] In this embodiment, the monitoring data refers to the data obtained by real-time monitoring of the distribution network equipment by sensors during the current period.

[0037] In this embodiment, the current operation data refers to data obtained by performing data preprocessing and data cleaning on the monitoring data of the current period, that is, data used to accurately represent the operation of the distribution network in the current period.

[0038] In this embodiment, the operation scenario refers to the operation scenario of the distribution network determined based on the operation data, which is used for subsequent classification, analysis and management of the distribution network.

[0039] In this embodiment, the current operation scenario refers to the operation scenario of the distribution network in the current period.

[0040] The working principle and beneficial effects of the above technical solution are: through real-time monitoring of the distribution network, the current operating data of the distribution network in the current period is obtained and the current operating scenario of the distribution network is determined, laying a data foundation for subsequent automated management.

[0041] Embodiment 3:

[0042] The embodiment of the present invention provides an intelligent distribution network automation management system, an operation scenario unit, including: An operation scenario setting block is used to obtain historical operation data of the distribution network and set the operation scenario of the distribution network, wherein the operation scenarios include: stable operation scenario, fluctuating operation scenario, overload operation scenario and fault operation scenario; The scene matching block is used to compare the current operation data with the historical operation data corresponding to the operation scene of the distribution network item by item. When the similarity of each operation data is not less than the preset matching similarity, the corresponding operation scene is determined to be the current operation scene of the distribution network.

[0043] In this embodiment, the historical operation data refers to the operation data of the power distribution network in the historical period.

[0044] In this embodiment, the preset matching similarity refers to a similarity set for determining whether the running scenarios match.

[0045] The working principle and beneficial effects of the above technical solution are: by obtaining the historical operation data of the distribution network, setting the operation scenario of the distribution network, and determining the current operation scenario of the distribution network, the scenario foundation is laid for the subsequent realization of automated management.

[0046] Embodiment 4:

[0047] The embodiment of the present invention provides an intelligent distribution network automation management system, an operation management module, including: An operation status determination unit is used to determine the current operation status of the distribution network in real time according to the current operation data and the current operation scenario, wherein the current operation status includes: normal operation status, early warning operation status, alarm operation status and fault operation status; Determine the operating data range corresponding to each operating state according to the historical operating data corresponding to the current operating scenario; Determine the current operating state of the distribution network according to the location of the current operating data in the operating data range; An operation constraint item unit, used for obtaining preset distribution network operation constraint items according to historical operation data corresponding to the current operation scenario, wherein the preset distribution network operation constraint items include: preset voltage constraint items, preset current constraint items, preset power constraint items and preset fault redundancy constraint items; The operation management unit is used to manage the operation of the distribution network according to the preset distribution network operation constraints and the current operation status of the distribution network, and control the current operation status of the distribution network to change to a normal operation status, wherein the operation management includes: voltage regulation, power compensation, load transfer and fault isolation.

[0048] In this embodiment, the current operating state refers to the operating state of the power distribution network in the current period, which is determined based on the current operating data and the current operating scenario.

[0049] In this embodiment, the operating data range refers to the range of operating data under each operating state, which is determined based on the historical operating data corresponding to the current operating scenario. For example, when the operating data is within the range of a1-a2, the operating state of the distribution network is determined to be a normal operating state.

[0050] In this embodiment, the preset distribution network operation constraint items refer to preset constraint items for achieving normal operation of the distribution network, such as preset voltage constraint items, preset current constraint items, preset power constraint items, and preset fault redundancy constraint items.

[0051] In this embodiment, the preset fault redundancy constraint item refers to a constraint item of the redundancy amount required by the distribution network when a device failure occurs in the distribution network.

[0052] In this embodiment, the operation management refers to the management of the distribution network based on preset distribution network operation constraints and the current operation status of the distribution network.

[0053] The working principle and beneficial effects of the above technical solution are: by determining the current operating status of the distribution network in real time based on the current operating data and the current operating scenario, and managing the operation of the distribution network according to the preset distribution network operation constraints, the automated management of the distribution network is initially realized.

[0054] Embodiment 5:

[0055] The embodiment of the present invention provides an intelligent distribution network automation management system, a fault management module, including: A distribution network model unit, used to construct a distribution network model based on historical operation data; A fault management unit, configured to obtain a fault period corresponding to the faulty operation state when determining that the current operation state of the distribution network is a faulty operation state; Perform static model analysis on the fault operation status according to the distribution network model, set the minimum static model analysis period, and split the fault period; The current operation data corresponding to each segment splitting result is input into the distribution network model and the static fault equipment is located according to the preset fault detection strategy; Remove static faulty equipment from the distribution network model, input current operating data for dynamic model analysis, and locate dynamic faulty equipment; Static fault devices and dynamic fault devices are eliminated from the distribution network model, and current operation data is input to determine the current operation state of the distribution network. When it is determined that the current operation state of the distribution network is still a faulty operation state, static model analysis and dynamic model analysis are re-performed based on the distribution network model in which the static fault devices and dynamic fault devices are eliminated; When it is determined that the current operating state of the distribution network is not a faulty operating state, static faulty devices and dynamic faulty devices are summarized to determine the faulty devices in the current period of the distribution network; A fault processing unit, used to isolate the faulty device and identify the fault type of the faulty device; Execute the fault recovery strategy according to the fault type. When the fault of the faulty device is eliminated, cancel the fault isolation and reconnect the faulty device to the distribution network.

[0056] In this embodiment, the distribution network model refers to a model constructed based on historical operation data and used to represent the distribution network.

[0057] In this embodiment, the fault period refers to a period corresponding to the faulty operating state.

[0058] In this embodiment, static model analysis refers to analysis performed by keeping the operating data unchanged and inputting it into the distribution network model, that is, analysis performed without considering the changing trend of the operating data.

[0059] In this embodiment, the minimum static model analysis period refers to the minimum analysis period for static model analysis, for example, the minimum static model analysis period t1, the operation data at a certain moment in the analysis period t1 is selected and input into the distribution network model for analysis.

[0060] In this embodiment, the preset fault detection strategy refers to a preset strategy for detecting faulty equipment in the power distribution network.

[0061] In this embodiment, the static faulty device refers to the faulty device determined by performing static model analysis.

[0062] In this embodiment, static fault devices are eliminated from the distribution network model, and current operating data is input for dynamic model analysis, which means that all current operating data within the fault period is input into the distribution network model from which static fault devices are eliminated for analysis, i.e., analysis is performed taking into account the changing trend of operating data.

[0063] In this embodiment, static fault equipment is removed from the distribution network model to simplify the analysis.

[0064] In this embodiment, the dynamic model analysis refers to an analysis performed by inputting all current operating data within the fault period into the distribution network model.

[0065] In this embodiment, the faulty device refers to a device that is unable to distribute power in the current period of the power distribution network.

[0066] In this embodiment, the fault recovery strategy refers to a strategy for performing fault elimination and recovery on a faulty device.

[0067] The working principle and beneficial effects of the above technical solution are: by establishing a distribution network model based on historical operation data, when it is determined that the current operating state of the distribution network is a faulty operating state, the faulty equipment is located and isolated, and fault management of the distribution network is performed, thereby further realizing the automated management of the distribution network.

[0068] Embodiment 6:

[0069] The embodiment of the present invention provides a smart distribution network automation management system, a prediction optimization module, including: A load demand prediction unit is used to obtain historical load data and current load data, extract load characteristics from the historical load data, and predict the load demand of the next operation period of the distribution network based on the current load data; According to the load demand of the distribution network in the next operation period predicted by the distribution network equipment, equipment matching is performed to determine the equipment load demand of each distribution network equipment in the next operation period; Vector construction unit, used to construct the historical time difference vector of the distribution network ,in, Indicates the h1th historical period difference; Indicates the actual time period length in the h1th historical case; represents the length of the forecast period in the h1th historical case; The prediction duration setting unit is used to set the prediction duration according to the historical time period difference vector And in combination with the duration Td of the current period of the distribution network, the duration Yt of the predicted period of the distribution network based on the duration of the current period is set; ; ; in, represents the duration correction function; Indicates that based on all The variance of Indicates the set duration; Indicates all Satisfied the number of A load demand correction unit, used to obtain a time period for reconnecting to the distribution network based on the faulty equipment in the current time period of the distribution network and the predicted faulty equipment; If the faulty equipment is reconnected to the distribution network within the forecast period, the equipment load demand of the faulty equipment in the next operating period is retained; If the faulty device is not reconnected to the distribution network within the forecast period, the equipment load demand of the faulty device in the next operating period will be transferred and distributed to other adjacent distribution network equipment, and the equipment load demand of other distribution network equipment in the next operating period will be corrected; The operation optimization unit is used to set operation optimization targets according to operation management and fault management, and perform operation optimization management of the distribution network according to the operation optimization targets, wherein the operation optimization targets include: operation management optimization targets, operation constraint optimization targets and operation load demand optimization targets.

[0070] In this embodiment, the historical load data refers to the load data of the distribution network in the historical period.

[0071] In this embodiment, the current load data refers to the load data of the distribution network in the current period.

[0072] In this embodiment, the load feature refers to a feature determined by extracting features from historical load data, and is used to represent a change trend of the load data.

[0073] In this embodiment, the load demand refers to the demand for load data in the next operation period of the distribution network, which is determined according to the load characteristics and the current load data prediction.

[0074] In this embodiment, the next operation time period of the distribution network can be set according to the length of the current time period.

[0075] In this embodiment, the equipment load demand refers to performing equipment matching according to the load demand of the distribution network in the next operating period predicted by the distribution network equipment, so as to determine the load demand of each distribution network equipment in the next operating period.

[0076] In this embodiment, the access period refers to the period during which the faulty device is reconnected to the power distribution network.

[0077] In this embodiment, the operation optimization target refers to a target set according to operation management and fault management for optimizing the operation of the distribution network.

[0078] In this embodiment, the operation optimization management refers to the automated management of the distribution network according to the operation optimization target, so as to ensure the stable operation of the distribution network.

[0079] The working principle and beneficial effects of the above technical solution are: by predicting the load demand of the next operating period of the distribution network and combining operation management and fault management to optimize the operation of the distribution network, the automatic management of the distribution network is effectively realized, ensuring the stable operation of the distribution network.

[0080] Embodiment 7:

[0081] The embodiment of the present invention provides an intelligent distribution network automation management system, a prediction optimization module, and further includes: An operation optimization evaluation unit is used to obtain the number of faulty devices after the operation optimization management of the distribution network is carried out, and determine the load loss amount of the distribution network; Obtain the load distribution of the distribution network, perform operation optimization management and evaluation on the distribution network, and obtain the optimization evaluation value of the distribution network; ;in, represents the optimized evaluation value of the distribution network; Indicates the number of faulty devices after the distribution network is optimized for operation management; Indicates the total number of distribution network equipment involved in the distribution network; Indicates the distribution network The quantitative value of the equipment load demand for optimizing the operation of a normally operating device; Indicates the distribution network Quantified value of actual equipment load data for optimizing operation management of normal operating equipment; Indicates the distribution network Quantified value of the load loss of each faulty device; When the optimization evaluation value of the distribution network is not lower than the preset optimization value, it is determined that the operation optimization management of the distribution network is qualified.

[0082] In this embodiment, the load distribution refers to the distribution of load data in each distribution network device.

[0083] In this embodiment, the load loss refers to the load loss of the distribution network caused by the inability of the faulty equipment to distribute electricity.

[0084] In this embodiment, the optimization evaluation value refers to a value for evaluating the operation optimization management of the distribution network based on the load distribution and load loss of the distribution network.

[0085] In this embodiment, the preset optimization value refers to an optimization value used to determine whether the operation optimization management of the distribution network is qualified.

[0086] The working principle and beneficial effect of the above technical solution are: by evaluating the operation optimization management of the distribution network, the realization of the distribution network automation management is further ensured.

[0087] Embodiment 8:

[0088] An embodiment of the present invention provides an intelligent distribution network automation management system, further comprising: The operation visualization module is used to visualize the current operation scenario of the distribution network, faulty equipment, and the operation optimization management of the distribution network; Operation safety module, used to evaluate and predict the operation safety of the distribution network, and preset safety control strategies. When there is an operation risk in the operation of the distribution network, the corresponding preset safety control strategies will be automatically executed; Data encryption is performed during the operation optimization management process of the distribution network.

[0089] In this embodiment, operational safety refers to the safety of the distribution network during operation, including the safety corresponding to the operation and the data security during automated management.

[0090] In this embodiment, the preset safety control strategy refers to a preset strategy for controlling the safety of power distribution network operation.

[0091] The working principle and beneficial effects of the above technical solution are: by evaluating and predicting the operational safety of the distribution network, automatically executing the corresponding preset security control strategy and performing data encryption processing, the security of the distribution network automation management is ensured.

[0092] Obviously, those skilled in the art can make various changes and modifications to the present invention without departing from the spirit and scope of the present invention. Thus, if these modifications and variations of the present invention fall within the scope of the claims of the present invention and their equivalents, the present invention is also intended to include these modifications and variations.

Claims

1. An intelligent distribution network automation management system, characterized in that: include: The operation monitoring module is used to monitor the distribution network in real time, obtain the current operation data of the distribution network in the current period and determine the current operation scenario of the distribution network; The operation management module is used to determine the current operation status of the distribution network in real time according to the current operation data and the current operation scenario, and to manage the operation of the distribution network according to the preset distribution network operation constraints; The fault management module is used to establish a distribution network model based on historical operation data. When the current operation state of the distribution network is determined to be a faulty operation state, the faulty equipment is located and isolated, and the distribution network is fault-managed. The prediction and optimization module is used to predict the load demand of the distribution network in the next operating period and to optimize the operation of the distribution network in combination with operation management and fault management.

2. The intelligent distribution network automation management system according to claim 1, characterized in that: Operation monitoring module, including: A monitoring deployment unit is used to acquire distribution network equipment, deploy sensors at the distribution network equipment, and perform real-time monitoring of the distribution network, wherein the distribution network equipment includes: substation equipment, distribution line equipment, transformer equipment, distribution switch equipment, distribution protection equipment, and distribution meter equipment; An operation data unit is used to obtain monitoring data of the distribution network in the current period according to the sensor, perform data preprocessing and data cleaning on the monitoring data, and determine the current operation data of the distribution network in the current period, wherein the current operation data includes: current operation data, voltage operation data, power operation data, temperature operation data, position operation data and fault operation data; The operation scenario unit is used to match data in the operation scenario of the distribution network according to the current operation data to determine the current operation scenario of the distribution network.

3. The intelligent distribution network automation management system according to claim 2, characterized in that: Run scene units, including: An operation scenario setting block is used to obtain historical operation data of the distribution network and set the operation scenario of the distribution network, wherein the operation scenarios include: stable operation scenario, fluctuating operation scenario, overload operation scenario and fault operation scenario; The scene matching block is used to compare the current operation data with the historical operation data corresponding to the operation scene of the distribution network item by item. When the similarity of each operation data is not less than the preset matching similarity, the corresponding operation scene is determined to be the current operation scene of the distribution network.

4. The intelligent distribution network automation management system according to claim 1, characterized in that: Operation management module, including: A range determination unit, used to determine the range of operation data corresponding to each operation state according to the historical operation data corresponding to the current operation scenario; A state determination unit, used to determine the current operation state of the distribution network according to the location of the current operation data in the operation data range, wherein the current operation state includes: normal operation state, early warning operation state, alarm operation state and fault operation state; An operation constraint item unit, used for obtaining preset distribution network operation constraint items according to historical operation data corresponding to the current operation scenario, wherein the preset distribution network operation constraint items include: preset voltage constraint items, preset current constraint items, preset power constraint items and preset fault redundancy constraint items; The operation management unit is used to manage the operation of the distribution network according to the preset distribution network operation constraints and the current operation status of the distribution network, and control the current operation status of the distribution network to change to a normal operation status, wherein the operation management includes: voltage regulation, power compensation, load transfer and fault isolation.

5. The intelligent distribution network automation management system according to claim 1, characterized in that: Fault management module, including: A distribution network model unit, used to construct a distribution network model based on historical operation data; A fault management unit, configured to obtain a fault period corresponding to the faulty operation state when determining that the current operation state of the distribution network is a faulty operation state; Perform static model analysis on the fault operation status according to the distribution network model, set the minimum static model analysis period, and split the fault period; The current operation data corresponding to each segment splitting result is input into the distribution network model and the static fault equipment is located according to the preset fault detection strategy; Remove static faulty equipment from the distribution network model, input current operating data for dynamic model analysis, and locate dynamic faulty equipment; Static fault devices and dynamic fault devices are eliminated from the distribution network model, and current operation data is input to determine the current operation state of the distribution network. When it is determined that the current operation state of the distribution network is still a faulty operation state, static model analysis and dynamic model analysis are re-performed based on the distribution network model in which the static fault devices and dynamic fault devices are eliminated; When it is determined that the current operating state of the distribution network is not a faulty operating state, static faulty devices and dynamic faulty devices are summarized to determine the faulty devices in the current period of the distribution network; A fault processing unit, used to isolate the faulty device and identify the fault type of the faulty device; Execute the fault recovery strategy according to the fault type. When the fault of the faulty device is eliminated, cancel the fault isolation and reconnect the faulty device to the distribution network.

6. The intelligent distribution network automation management system according to claim 1, characterized in that: Prediction and optimization modules, including: A load demand prediction unit is used to obtain historical load data and current load data, extract load characteristics from the historical load data, and predict the load demand of the next operation period of the distribution network based on the current load data; According to the load demand of the distribution network in the next operation period predicted by the distribution network equipment, equipment matching is performed to determine the equipment load demand of each distribution network equipment in the next operation period; Vector construction unit, used to construct the historical time difference vector of the distribution network ,in, Indicates the h1th historical period difference; Indicates the actual time period length in the h1th historical case; represents the length of the forecast period in the h1th historical case; The prediction duration setting unit is used to set the prediction duration according to the historical time period difference vector And in combination with the duration Td of the current period of the distribution network, the duration Yt of the predicted period of the distribution network based on the duration of the current period is set; ； ； in, represents the duration correction function; Indicates that based on all The variance of Indicates the set duration; Indicates all Satisfied the number of A load demand correction unit, used to obtain a time period for reconnecting to the distribution network based on the faulty equipment in the current time period of the distribution network and the predicted faulty equipment; If the faulty equipment is reconnected to the distribution network within the forecast period, the equipment load demand of the faulty equipment in the next operating period is retained; If the faulty device is not reconnected to the distribution network within the forecast period, the equipment load demand of the faulty device in the next operating period will be transferred and distributed to other adjacent distribution network equipment, and the equipment load demand of other distribution network equipment in the next operating period will be corrected; The operation optimization unit is used to set operation optimization targets according to operation management and fault management, and perform operation optimization management of the distribution network according to the operation optimization targets, wherein the operation optimization targets include: operation management optimization targets, operation constraint optimization targets and operation load demand optimization targets.

7. The intelligent distribution network automation management system according to claim 6, characterized in that: The prediction and optimization module also includes: An operation optimization evaluation unit is used to obtain the number of faulty devices after the operation optimization management of the distribution network is carried out, and determine the load loss amount of the distribution network; Obtain the load distribution of the distribution network, perform operation optimization management and evaluation on the distribution network, and obtain the optimization evaluation value of the distribution network; ;in, represents the optimized evaluation value of the distribution network; Indicates the number of faulty devices after the distribution network is optimized and managed; Indicates the total number of distribution network equipment involved in the distribution network; Indicates the distribution network The quantitative value of the equipment load demand for optimizing the operation of a normally operating device; Indicates the distribution network Quantified value of actual equipment load data for optimizing operation management of normal operating equipment; Indicates the distribution network Quantified value of load loss of each faulty device; When the optimization evaluation value of the distribution network is not lower than the preset optimization value, it is determined that the operation optimization management of the distribution network is qualified.

8. The intelligent distribution network automation management system according to claim 1, characterized in that: Also includes: The operation visualization module is used to visualize the current operation scenario of the distribution network, faulty equipment, and the operation optimization management of the distribution network; Operation safety module, used to evaluate and predict the operation safety of the distribution network, and preset safety control strategies. When there is an operation risk in the operation of the distribution network, the corresponding preset safety control strategies will be automatically executed; Data encryption is performed during the operation optimization management process of the distribution network.

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