CN114662333B - Smart power grids line loss detecting system based on thing networking - Google Patents
Smart power grids line loss detecting system based on thing networking Download PDFInfo
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Abstract
The invention belongs to the technical field of the Internet of things, and particularly relates to a smart grid line loss detection system based on the Internet of things. The system comprises: the system comprises a virtual connection power grid, a real connection power grid, a line loss detection part and a line adjustment part; the real-connection power grid and the virtual-connection power grid both comprise: a node; the utility grid further comprises: a real-connection wire and a real-connection switch; the virtual grid further comprises: virtual connection wires and virtual connection switches; and a real-connection wire in the real-connection power grid is connected with the nodes, and a real-connection switch is arranged on the real-connection wire between every two nodes. The system realizes the calculation of line loss by setting the virtual connection power grid and the real connection power grid, can switch in real time when the line loss occurs, and can calculate the line loss of an area according to the state of the power grid in the area, thereby realizing the accurate calculation of the line loss of the intelligent power grid line.
Description
Technical Field
The invention belongs to the technical field of Internet of things, and particularly relates to a three-dimensional model intelligent construction system and method based on a cloud platform.
Background
The internet of things (Internet of Things, ioT for short) refers to collecting any object or process needing to be monitored, connected and interacted in real time through various devices and technologies such as various information sensors, radio frequency identification technologies, global positioning systems, infrared sensors and laser scanners, collecting various needed information such as sound, light, heat, electricity, mechanics, chemistry, biology and positions, and realizing ubiquitous connection of objects and people through various possible network access, and realizing intelligent sensing, identification and management of objects and processes. The internet of things is an information carrier based on the internet, a traditional telecommunication network and the like, and enables all common physical objects which can be independently addressed to form an interconnection network.
Along with the development of the economic society in China, the electric power demand is rapidly increased, and especially, the requirement of large-scale development and utilization of clean energy sources is met, so that the safety of a power grid, the development of clean energy sources and the ecological environment face serious problems. The national power grid provides a strong power guarantee for the economic and social development, and simultaneously, the national power grid has higher requirements on the power grid energy saving and loss reduction work. The line loss rate index comprehensively reflects the loss of each link in the operation of the power grid, and the management level of each core business such as production, scheduling, marketing and the like is reflected in a centralized way. The national power grid company attaches importance to the management of electric quantity and line loss for a long time, establishes a complete electric quantity statistics and line loss management system, and carries out electric quantity statistics such as sales and the like and line loss index management, theoretical line loss calculation and the like in a normalized manner. In recent years, the electric power enterprises greatly expand the application of intelligent electric meters, continuously perfects professional information systems, promotes marketing and distribution communication, service fusion and data sharing, creates important conditions for daily synchronization line loss real-time calculation and automatic generation based on full service integration and standard data model construction, but is difficult to effectively exert the line loss rate index supervision and control effect due to lack of a unified support system.
Disclosure of Invention
Therefore, the main purpose of the invention is to provide a smart grid line loss detection system based on the internet of things, wherein the system realizes the calculation of line loss by arranging a virtual connection grid and a real connection grid, and meanwhile, when the line loss occurs, the system can switch in real time, and can calculate the line loss of a region according to the state of the grid in the region, thereby realizing the accurate calculation of the line loss of the smart grid line.
In order to achieve the above purpose, the technical scheme of the invention is realized as follows:
smart power grids line loss detecting system based on thing networking, the system includes: the system comprises a virtual connection power grid, a real connection power grid, a line loss detection part and a line adjustment part; the real-connection power grid and the virtual-connection power grid both comprise: a node; the utility grid further comprises: a real-connection wire and a real-connection switch; the virtual grid further comprises: virtual connection wires and virtual connection switches; the real-connection electric wires in the real-connection power grid are connected with the nodes, and meanwhile, a real-connection switch is arranged on the real-connection electric wires between every two nodes; the connection relation between the virtual connection wires and the nodes in the virtual connection power grid is obtained by mapping the connection relation between the nodes and the real connection wires in the real connection power grid according to a set mapping rule, so that the connection relation between the nodes and the virtual connection wires in the virtual connection power grid corresponds to the connection relation between the nodes and the real connection wires in the real connection power grid one by one and is different from each other, and virtual connection switches are arranged on the virtual connection wires between every two nodes; the line loss detection part is configured to send a control command to the real-connection power grid according to a set period to control the real-connection switch in the real-connection power grid to be opened and closed according to the set period, delay a set time value of the control command and send the control command to the virtual-connection power grid to control the virtual-connection switch in the virtual-connection power grid to be opened and closed according to the set period, acquire the running states of the virtual-connection wire, the real-connection wire and the node when the virtual-connection switch and the real-connection switch are opened and closed in real time, and judge the line loss based on the acquired running states to acquire a line loss judgment result; the line adjusting part is configured to send an adjusting command to the virtual connection power grid and the real connection power grid based on the obtained line loss judging result, and control the virtual connection switch and the real connection switch to be opened and closed so that the real connection wire with the line loss in the real connection power grid is replaced by the virtual connection wire to form a new real connection power grid, the replaced real connection wire is used as the virtual connection wire, and mapping is carried out again according to the set mapping rule based on the new real connection power grid to obtain the new virtual connection power grid.
Further, when the connection relation between the virtual connection wires and the nodes in the virtual connection power grid is mapped according to a set mapping rule through the connection relation between the nodes and the real connection wires in the real connection power grid, the mapping rule is as follows: dividing a real-connection power grid into a plurality of sub-blocks, wherein each sub-block comprises a plurality of real-connection wires and nodes; for each node in each sub-block, firstly, virtual lines are used and are connected with other nodes, then, virtual lines which are coincident with the virtual lines when being connected through real connecting wires are deleted, then, the virtual lines are randomly selected from the rest virtual lines so as to ensure that each node is connected with other nodes through one virtual line, then, all other virtual lines are deleted, and the virtual connecting wires are connected according to the connection relation corresponding to the rest virtual lines, so that mapping is completed.
Further, the line loss detection section includes: the command sending unit is configured to send a control command to the real-connection power grid according to a set period so as to control the real-connection switch in the real-connection power grid to be opened and closed according to the set period, and send the control command to the virtual-connection power grid after delaying a set time value so as to control the virtual-connection switch in the virtual-connection power grid to be opened and closed according to the set period; the data acquisition unit is configured to acquire the running states of the virtual connection wire, the real connection wire and the node in real time when the virtual connection switch and the real connection switch are opened and closed, and to perform line loss judgment based on the acquired running states, so as to obtain a line loss judgment result.
Further, the types of the nodes include: distribution transformer equipment nodes, voltage dividing nodes and electric appliance nodes.
Further, the operation states of the virtual connection wire, the real connection wire and the node include: voltage class and level, average length of line, sectional area of wire, status of distribution transformer equipment, load time distribution, load rate of unit power transformation capacity, maximum natural reactive load factor, partial pressure sales power, non-industrial GDP duty ratio and lossless power; the voltage class and hierarchy includes three categories: ultra-high voltage, and low voltage; the average length of the line is defined as the average length of all virtual wires and the average length of all real wires; the wire cross-sectional area is defined as: an average value of sectional areas of all the virtual wires and an average value of sectional areas of all the real wires; the conditions of the distribution transformer equipment are defined as: the operation state of the distribution transformer equipment node comprises: normal and abnormal; the load time distribution is defined by setting different time intervals, and the load time distribution in the different time intervals corresponds to different setting values; the partial pressure sales power is defined as the output power of the partial pressure node; the non-industrial GDP duty cycle is defined as the ratio of the number of consumer electricity divided into household electricity in the consumer node in the node to the number of industrial electricity.
Further, the data obtaining unit performs line loss judgment based on the obtained operation state, and the method for obtaining the line loss judgment result includes: if the running state of the same node under the virtual connection wire connection is the same as the running state under the real connection wire connection, judging that no line loss occurs, and taking the line loss as a line loss judging result; if the operation state of the same node under the connection of the virtual connection point is different from the operation state under the connection of the real connection wire, judging that the line loss occurs; when judging that the line loss occurs, calculating a line loss value by using a set line loss value calculation model, and comparing the calculated line loss value with a preset threshold value to judge whether the current line loss needs to be adjusted or not as a line loss judgment result.
Further, the line loss value calculation model is expressed by using the following formula:
Further, the system further comprises: the regional line loss calculation part is configured to acquire data of a plurality of different power grids in the target region and calculate the line loss rate of the target region; the electric network in the target area comprises: a real-connection power grid and a virtual-connection power grid; the method for calculating the line loss rate of the target area by the area line loss part comprises the following steps: acquiring line loss data of all power grids in a target area, wherein the line loss data of all power grids in the target area comprise line loss values and correction values influencing the generation of the line loss values; dividing line loss data of all power grids in the target area into a plurality of data sets, wherein each data set comprises line loss values in a preset range and correction values corresponding to the line loss values in the preset range; acquiring a data set, of which the association degree with a correction value to be detected is within a preset numerical range, in the plurality of data sets to obtain a target data set; obtaining a statistical line loss rate corresponding to the correction value to be detected according to the target data set, and obtaining a first statistical line loss rate; wherein the correction value includes: a combination of at least two of temperature data, GDP data, or population density data; before acquiring the data sets, of which the association degree with the correction value to be detected is within the preset numerical range, in the plurality of data sets, the method further comprises: respectively acquiring the association degree of the plurality of data sets and the correction value to be detected; and detecting whether the association degree of the plurality of data sets and the correction value to be detected is within the preset numerical range, wherein the respectively obtaining the association degree of the plurality of data sets and the correction value to be detected comprises: respectively establishing an associated prediction model and a non-associated prediction model according to line loss data of all power grids in the target area; establishing a prediction model to be associated according to the correction value to be detected; and obtaining the association degree of each data set and the correction value to be detected according to the association prediction model, the non-association prediction model and the prediction model to be associated.
Further, the association prediction model is as follows:
wherein N is i For the partitioned data set; qj, j=l, 2, … n are n different features of the data set Ni; x is X in Is N i With respect to corresponding features Q j A range of magnitudes; t is a correction matrix, which is obtained by multiplying a n-order identity matrix by a correction value.
Further, the non-associated prediction model includes:
wherein, X is P1 ,X P2 ,…，X Pn Respectively, set P about feature Q 1 ,Q 2 ,…，Q n Is referred to as a section, wherein a Pn ，b Pn Is Q j A pitch domain of j=l, 2, …, n; the obtaining the association degree of the plurality of data sets and the correction value to be detected according to the association prediction model, the non-association prediction model and the prediction model to be associated comprises the following steps: acquiring an association function between the plurality of data sets and the correction value to be detected according to the association prediction model, the non-association prediction model and the prediction model to be associated; and acquiring the association degree of the plurality of data sets and the correction value to be detected according to the association function.
The intelligent power grid line loss detection system based on the Internet of things has the following beneficial effects:
1. the efficiency is high: the line loss detection system of the invention judges through setting the virtual connection power grid and the real connection power grid, and is different from the traditional judging method, the invention can reduce the operation amount, thereby carrying out the operation of the line loss value when judging the line loss, avoiding a part of meaningless calculation, simultaneously enabling part of wires with lower line loss rate to be continuously used when judging according to the obtained line loss value, avoiding the occurrence of excessive replacement, and simultaneously improving the operation efficiency of the power grid, and completing the mutual conversion of the virtual connection power grid and the real connection power grid directly when the line loss occurs.
2. The accuracy is high: according to the invention, whether the line loss occurs is judged, and then the line loss value is calculated, wherein the line loss value is calculated based on a plurality of characteristic values, different characteristic values have different weight values, the weight values are obtained through experiments, and then the line loss is corrected, so that the calculation accuracy of the line loss is higher.
Drawings
Fig. 1 is a schematic system structure diagram of a smart grid line loss detection system based on the internet of things according to an embodiment of the present invention;
fig. 2 is a table corresponding to different operation states and weight values of a smart grid line loss detection system based on the internet of things according to an embodiment of the present invention;
fig. 3 is a schematic diagram of line adjustment performed by the intelligent power grid line loss detection system based on the internet of things according to the embodiment of the present invention.
Detailed Description
The method of the present invention will be described in further detail with reference to the accompanying drawings.
Example 1
As shown in fig. 1, a smart grid line loss detection system based on the internet of things, the system includes: the system comprises a virtual connection power grid, a real connection power grid, a line loss detection part and a line adjustment part; the real-connection power grid and the virtual-connection power grid both comprise: a node; the utility grid further comprises: a real-connection wire and a real-connection switch; the virtual grid further comprises: virtual connection wires and virtual connection switches; the real-connection electric wires in the real-connection power grid are connected with the nodes, and meanwhile, a real-connection switch is arranged on the real-connection electric wires between every two nodes; the connection relation between the virtual connection wires and the nodes in the virtual connection power grid is obtained by mapping the connection relation between the nodes and the real connection wires in the real connection power grid according to a set mapping rule, so that the connection relation between the nodes and the virtual connection wires in the virtual connection power grid corresponds to the connection relation between the nodes and the real connection wires in the real connection power grid one by one and is different from each other, and virtual connection switches are arranged on the virtual connection wires between every two nodes; the line loss detection part is configured to send a control command to the real-connection power grid according to a set period to control the real-connection switch in the real-connection power grid to be opened and closed according to the set period, delay a set time value of the control command and send the control command to the virtual-connection power grid to control the virtual-connection switch in the virtual-connection power grid to be opened and closed according to the set period, acquire the running states of the virtual-connection wire, the real-connection wire and the node when the virtual-connection switch and the real-connection switch are opened and closed in real time, and judge the line loss based on the acquired running states to acquire a line loss judgment result; the line adjusting part is configured to send an adjusting command to the virtual connection power grid and the real connection power grid based on the obtained line loss judging result, and control the virtual connection switch and the real connection switch to be opened and closed so that the real connection wire with the line loss in the real connection power grid is replaced by the virtual connection wire to form a new real connection power grid, the replaced real connection wire is used as the virtual connection wire, and mapping is carried out again according to the set mapping rule based on the new real connection power grid to obtain the new virtual connection power grid.
Specifically, the virtual connection power grid and the real connection power grid can be mutually converted, and when the real connection power grid has line loss, whether the real connection wire of the real connection power grid needs to be changed into the virtual connection wire can be judged according to the line loss value; the virtual connection wire is also an actual wire, and the connection mode is different from that of the real connection power grid; the different connection modes are adopted because in practice, the virtual connection wires and the real connection wires are connected to the nodes at the same time, and if the connection modes are the same, confusion is easily caused.
And on the other hand, when the part in the virtual connection power grid conversion is converted into the part in the real connection power grid, the replaced real connection power grid is regarded as the virtual connection power grid again, mapping is carried out again, and connection of the virtual connection power grid is completed. In the new virtual connection power grid, the replaced part can be directly detected or replaced so as to complete seamless replacement and repair of the line loss.
Example 2
On the basis of the above embodiment, when mapping the connection relationship between the virtual connection wires and the nodes in the virtual connection power grid according to a set mapping rule through the connection relationship between the nodes and the real connection wires in the real connection power grid, the mapping rule is: dividing a real-connection power grid into a plurality of sub-blocks, wherein each sub-block comprises a plurality of real-connection wires and nodes; for each node in each sub-block, firstly, virtual lines are used and are connected with other nodes, then, virtual lines which are coincident with the virtual lines when being connected through real connecting wires are deleted, then, the virtual lines are randomly selected from the rest virtual lines so as to ensure that each node is connected with other nodes through one virtual line, then, all other virtual lines are deleted, and the virtual connecting wires are connected according to the connection relation corresponding to the rest virtual lines, so that mapping is completed.
Specifically, the virtual lines are non-existing lines and are generated through a computer program, the virtual line connection simulates topological connection in the power grid, after connection is completed, the connection mode identical to that of the real connection lines is needed to be avoided, then the virtual lines are randomly selected from the rest virtual lines, each node is guaranteed to be connected with other nodes through one virtual line, then all other virtual lines are deleted, and the virtual connection lines are connected according to the connection relations corresponding to the rest virtual lines, so that mapping is completed.
Example 3
On the basis of the above embodiment, the line loss detection section includes: the command sending unit is configured to send a control command to the real-connection power grid according to a set period so as to control the real-connection switch in the real-connection power grid to be opened and closed according to the set period, and send the control command to the virtual-connection power grid after delaying a set time value so as to control the virtual-connection switch in the virtual-connection power grid to be opened and closed according to the set period; the data acquisition unit is configured to acquire the running states of the virtual connection wire, the real connection wire and the node in real time when the virtual connection switch and the real connection switch are opened and closed, and to perform line loss judgment based on the acquired running states, so as to obtain a line loss judgment result.
Specifically, when the line loss detection part detects line loss, the process can be divided into two stages, and in the first stage, the control of the virtual connection switch and the real connection switch is firstly performed to judge whether the line loss occurs or not, and then the degree of the line loss is judged.
In the first stage, after a control command is sent to the real-connection power grid, the control command firstly reaches a first real-connection wire and a first node in the real-connection power grid, after a set time value, the control command is sent to a first virtual-connection wire in the virtual-connection power grid, after the set time value, the control command is sent to a second real-connection wire and a second node, after the set time value, the control command is sent to a second virtual-connection wire in the virtual-connection power grid, and accordingly, after the control command is reciprocated, all the real-connection wires and the virtual-connection wires are traversed.
Example 4
On the basis of the above embodiment, the types of the nodes include: distribution transformer equipment nodes, voltage dividing nodes and electric appliance nodes.
Example 5
On the basis of the above embodiment, the operation states of the virtual connection wire, the real connection wire and the node include: voltage class and level, average length of line, sectional area of wire, status of distribution transformer equipment, load time distribution, load rate of unit power transformation capacity, maximum natural reactive load factor, partial pressure sales power, non-industrial GDP duty ratio and lossless power; the voltage class and hierarchy includes three categories: ultra-high voltage, and low voltage; the average length of the line is defined as the average length of all virtual wires and the average length of all real wires; the wire cross-sectional area is defined as: an average value of sectional areas of all the virtual wires and an average value of sectional areas of all the real wires; the conditions of the distribution transformer equipment are defined as: the operation state of the distribution transformer equipment node comprises: normal and abnormal; the load time distribution is defined by setting different time intervals, and the load time distribution in the different time intervals corresponds to different setting values; the partial pressure sales power is defined as the output power of the partial pressure node; the non-industrial GDP duty cycle is defined as the ratio of the number of consumer electricity divided into household electricity in the consumer node in the node to the number of industrial electricity.
Referring to fig. 2, in particular, in a practical situation, the objective of line loss management is to implement "technical line loss is optimal, management line loss is minimum, and comprehensive line loss is reasonable". The reduction of the technical line loss is realized by optimizing the network structure, adopting new technology and new equipment, improving the economic operation level of the circuit and the transformer and other technical means. The reduction of the management line loss is realized mainly by strengthening various management and reducing 'running, falling and leaking'. In comparison, through the sound line loss organization of each level, each management system is perfected, the line loss management flow is straightened, the management means such as statistics and analysis of line loss indexes are enhanced, and the effect of promoting the reduction of the management line loss is more remarkable.
Example 6
On the basis of the above embodiment, the method for obtaining the line loss determination result by the data obtaining unit based on the obtained operation state includes: if the running state of the same node under the virtual connection wire connection is the same as the running state under the real connection wire connection, judging that no line loss occurs, and taking the line loss as a line loss judging result; if the operation state of the same node under the connection of the virtual connection point is different from the operation state under the connection of the real connection wire, judging that the line loss occurs; when judging that the line loss occurs, calculating a line loss value by using a set line loss value calculation model, and comparing the calculated line loss value with a preset threshold value to judge whether the current line loss needs to be adjusted or not as a line loss judgment result.
Referring to fig. 3, specifically, this is a second stage of determining the line loss, in which the line loss value needs to be calculated, and the line loss determination in the second stage is performed according to the calculation result.
In fig. 3, the dotted line part represents the virtual connection power grid, the implementation part represents the real connection power grid, after the line loss is detected, the real connection power wire of the real connection power grid is directly disconnected, and then the virtual connection switch of the virtual connection power wire is started to complete conversion.
Example 7
On the basis of the above embodiment, the line loss value calculation model is expressed using the following formula:
wherein F is a line loss value, A is a voltage class and a hierarchy, and a is a weight value corresponding to the voltage class and the hierarchy; b is the average length of the line, and B is the corresponding weight value; c is the sectional area of the wire, and C is the corresponding weight value; d is the condition of the distribution transformer equipment, and D is the corresponding weight value; e is load time distribution, and E is a weight value corresponding to the load time distribution; f is the unit variable capacity load rate, and F is the corresponding weight value; g is the maximum natural reactive load coefficient, G is the corresponding weight value; h is the partial pressure sales power quantity, and H is the corresponding weight value; i is the non-industrial GDP duty ratio, I is the corresponding weight value; j is lossless electric quantity, J is a corresponding weight value; when the voltage class and the hierarchy are ultrahigh voltage, the value of A is 1, when the voltage class and the hierarchy are high voltage, the value of A is 0.5, and when the voltage class and the hierarchy are low voltage, the value of A is 0.2; and D takes a value of 1 when the running state of the distribution transformer equipment node is normal, and takes a value of 0 when the running state of the distribution transformer equipment node is abnormal.
Example 8
On the basis of the above embodiment, the system further includes: the regional line loss calculation part is configured to acquire data of a plurality of different power grids in the target region and calculate the line loss rate of the target region; the electric network in the target area comprises: a real-connection power grid and a virtual-connection power grid; the method for calculating the line loss rate of the target area by the area line loss part comprises the following steps: acquiring line loss data of all power grids in a target area, wherein the line loss data of all power grids in the target area comprise line loss values and correction values influencing the generation of the line loss values; dividing line loss data of all power grids in the target area into a plurality of data sets, wherein each data set comprises line loss values in a preset range and correction values corresponding to the line loss values in the preset range; acquiring a data set, of which the association degree with a correction value to be detected is within a preset numerical range, in the plurality of data sets to obtain a target data set; obtaining a statistical line loss rate corresponding to the correction value to be detected according to the target data set, and obtaining a first statistical line loss rate; wherein the correction value includes: a combination of at least two of temperature data, GDP data, or population density data; before acquiring the data sets, of which the association degree with the correction value to be detected is within the preset numerical range, in the plurality of data sets, the method further comprises: respectively acquiring the association degree of the plurality of data sets and the correction value to be detected; and detecting whether the association degree of the plurality of data sets and the correction value to be detected is within the preset numerical range, wherein the respectively obtaining the association degree of the plurality of data sets and the correction value to be detected comprises: respectively establishing an associated prediction model and a non-associated prediction model according to line loss data of all power grids in the target area; establishing a prediction model to be associated according to the correction value to be detected; and obtaining the association degree of each data set and the correction value to be detected according to the association prediction model, the non-association prediction model and the prediction model to be associated.
Specifically, the invention provides a method capable of calculating the line loss rate of the whole area, by which the accuracy of line loss judgment on a certain power grid can be verified reversely through the line loss rate in addition to the line loss rate of the area.
Example 9
On the basis of the above embodiment, the association prediction model is:
wherein N is i For the partitioned data set; qj, j=l, 2, … n are n different features of the data set Ni; x is X in Is N i With respect to corresponding features Q j A range of magnitudes; t is a correction matrix, which is obtained by multiplying a n-order identity matrix by a correction value.
Example 10
On the basis of the above embodiment, the non-associated prediction model includes:
wherein, X is P1 ,X P2 ,…，X Pn Respectively, set P about feature Q 1 ,Q 2 ,…，Q n Is referred to as a section, wherein a Pn ，b Pn Is Q j A pitch domain of j=l, 2, …, n; the obtaining the association degree of the plurality of data sets and the correction value to be detected according to the association prediction model, the non-association prediction model and the prediction model to be associated comprises the following steps: acquiring an association function between the plurality of data sets and the correction value to be detected according to the association prediction model, the non-association prediction model and the prediction model to be associated; and acquiring the association degree of the plurality of data sets and the correction value to be detected according to the association function.
It should be noted that, in the system provided in the foregoing embodiment, only the division of the foregoing functional units is illustrated, in practical application, the foregoing functional allocation may be performed by different functional units, that is, the units or steps in the embodiment of the present invention are further decomposed or combined, for example, the units in the foregoing embodiment may be combined into one unit, or may be further split into multiple sub-units, so as to complete all or the functions of the units described above. The names of the units and the steps related to the embodiment of the invention are only used for distinguishing the units or the steps, and are not to be construed as undue limitation of the invention.
It will be clearly understood by those skilled in the art that, for convenience and brevity of description, the specific working process of the storage device and the processing device described above and the related description may refer to the corresponding process in the foregoing method embodiment, which is not repeated herein.
Those of skill in the art will appreciate that the various illustrative elements, method steps described in connection with the embodiments disclosed herein may be implemented as electronic hardware, computer software, or combinations of both, and that the program(s) corresponding to the software elements, method steps may be embodied in Random Access Memory (RAM), memory, read Only Memory (ROM), electrically programmable ROM, electrically erasable programmable ROM, registers, hard disk, removable disk, QD-ROM, or any other form of storage medium known in the art. To clearly illustrate this interchangeability of electronic hardware and software, various illustrative components and steps have been described above generally in terms of their functionality. Whether such functionality is implemented as electronic hardware or software depends upon the particular application and design constraints imposed on the solution. Those skilled in the art may implement the described functionality using different approaches for each particular application, but such implementation is not intended to be limiting.
The terms "first," "another portion," and the like, are used for distinguishing between similar objects and not for describing a particular sequential or chronological order.
The terms "comprises," "comprising," or any other variation thereof, are intended to cover a non-exclusive inclusion, such that a process, method, article, or unit/apparatus that comprises a list of elements does not include only those elements but may include other elements not expressly listed or inherent to such process, method, article, or unit/apparatus.
Thus far, the technical solution of the present invention has been described in connection with the preferred embodiments shown in the drawings, but it is easily understood by those skilled in the art that the scope of protection of the present invention is not limited to these specific embodiments. Equivalent modifications and substitutions for related art marks may be made by those skilled in the art without departing from the principles of the present invention, and such modifications and substitutions will fall within the scope of the present invention.
The foregoing description is only of the preferred embodiments of the present invention and is not intended to limit the scope of the present invention.
Claims (8)
1. Smart power grids line loss detecting system based on thing networking, its characterized in that, the system includes: the system comprises a virtual connection power grid, a real connection power grid, a line loss detection part and a line adjustment part; the real-connection power grid and the virtual-connection power grid both comprise: a node; the utility grid further comprises: a real-connection wire and a real-connection switch; the virtual grid further comprises: virtual connection wires and virtual connection switches; the real-connection electric wires in the real-connection power grid are connected with the nodes, and meanwhile, a real-connection switch is arranged on the real-connection electric wires between every two nodes; the connection relation between the virtual connection wires and the nodes in the virtual connection power grid is obtained by mapping the connection relation between the nodes and the real connection wires in the real connection power grid according to a set mapping rule, so that the connection relation between the nodes and the virtual connection wires in the virtual connection power grid corresponds to the connection relation between the nodes and the real connection wires in the real connection power grid one by one and is different from each other, and virtual connection switches are arranged on the virtual connection wires between every two nodes; the line loss detection part is configured to send a control command to the real-connection power grid according to a set period to control the real-connection switch in the real-connection power grid to be opened and closed according to the set period, delay a set time value of the control command and send the control command to the virtual-connection power grid to control the virtual-connection switch in the virtual-connection power grid to be opened and closed according to the set period, acquire the running states of the virtual-connection wire, the real-connection wire and the node when the virtual-connection switch and the real-connection switch are opened and closed in real time, and judge the line loss based on the acquired running states to acquire a line loss judgment result; the circuit adjusting part is configured to send an adjusting command to the virtual connection power grid and the real connection power grid based on the obtained line loss judging result, and control the virtual connection switch and the real connection switch to be opened and closed so that the real connection wire with the line loss in the real connection power grid is replaced by the virtual connection wire to form a new real connection power grid, the replaced real connection wire is used as the virtual connection wire, and mapping is carried out again according to a set mapping rule based on the new real connection power grid to obtain the new virtual connection power grid; when the connection relation between the virtual connection wires and the nodes in the virtual connection power grid is mapped according to a set mapping rule through the connection relation between the nodes and the real connection wires in the real connection power grid, the mapping rule is as follows: dividing a real-connection power grid into a plurality of sub-blocks, wherein each sub-block comprises a plurality of real-connection wires and nodes; for each node in each sub-block, firstly, virtual lines are used and are connected with other nodes, then, virtual lines which are coincident with the virtual lines when being connected through real connecting wires are deleted, then, the virtual lines are randomly selected from the rest virtual lines so as to ensure that each node is connected with other nodes through one virtual line, then, all other virtual lines are deleted, and the virtual connecting wires are connected according to the connection relation corresponding to the rest virtual lines, so that mapping is completed.
2. The system of claim 1, wherein the line loss detection section comprises: the command sending unit is configured to send a control command to the real-connection power grid according to a set period so as to control the real-connection switch in the real-connection power grid to be opened and closed according to the set period, and send the control command to the virtual-connection power grid after delaying a set time value so as to control the virtual-connection switch in the virtual-connection power grid to be opened and closed according to the set period; the data acquisition unit is configured to acquire the running states of the virtual connection wire, the real connection wire and the node in real time when the virtual connection switch and the real connection switch are opened and closed, and to perform line loss judgment based on the acquired running states, so as to obtain a line loss judgment result.
3. The system of claim 2, wherein the class of nodes comprises: distribution transformer equipment nodes, voltage dividing nodes and electric appliance nodes.
4. The system of claim 3, wherein the operational states of the virtual wires, the real wires, and the nodes comprise: voltage class and level, average length of line, sectional area of wire, status of distribution transformer equipment, load time distribution, load rate of unit power transformation capacity, maximum natural reactive load factor, partial pressure sales power, non-industrial GDP duty ratio and lossless power; the voltage class and hierarchy includes three categories: ultra-high voltage, and low voltage; the average length of the line is defined as the average length of all virtual wires and the average length of all real wires; the wire cross-sectional area is defined as: an average value of sectional areas of all the virtual wires and an average value of sectional areas of all the real wires; the conditions of the distribution transformer equipment are defined as: the operation state of the distribution transformer equipment node comprises: normal and abnormal; the load time distribution is defined by setting different time intervals, and the load time distribution in the different time intervals corresponds to different setting values; the partial pressure sales power is defined as the output power of the partial pressure node; the non-industrial GDP duty cycle is defined as the ratio of the number of consumer electricity divided into household electricity in the consumer node in the node to the number of industrial electricity.
5. The system of claim 4, wherein the data acquisition unit performs line loss judgment based on the acquired operation state, and the method for obtaining the line loss judgment result comprises: if the running state of the same node under the virtual connection wire connection is the same as the running state under the real connection wire connection, judging that no line loss occurs, and taking the line loss as a line loss judging result; if the operation state of the same node under the connection of the virtual connection point is different from the operation state under the connection of the real connection wire, judging that the line loss occurs; when judging that the line loss occurs, calculating a line loss value by using a set line loss value calculation model, and comparing the calculated line loss value with a preset threshold value to judge whether the current line loss needs to be adjusted or not as a line loss judgment result.
6. The system of claim 5, wherein the line loss value calculation model is expressed using the following formula:
7. The system of claim 6, wherein the system further comprises: the regional line loss calculation part is configured to acquire data of a plurality of different power grids in the target region and calculate the line loss rate of the target region; the electric network in the target area comprises: a real-connection power grid and a virtual-connection power grid; the method for calculating the line loss rate of the target area by the area line loss calculation part comprises the following steps: acquiring line loss data of all power grids in a target area, wherein the line loss data of all power grids in the target area comprise line loss values and correction values influencing the generation of the line loss values; dividing line loss data of all power grids in the target area into a plurality of data sets, wherein each data set comprises line loss values in a preset range and correction values corresponding to the line loss values in the preset range; acquiring a data set, of which the association degree with a correction value to be detected is within a preset numerical range, in the plurality of data sets to obtain a target data set; obtaining a statistical line loss rate corresponding to the correction value to be detected according to the target data set, and obtaining a first statistical line loss rate; wherein the correction value includes: a combination of at least two of temperature data, GDP data, or population density data; before acquiring the data sets, of which the association degree with the correction value to be detected is within the preset numerical range, in the plurality of data sets, the method further comprises: respectively acquiring the association degree of the plurality of data sets and the correction value to be detected; and detecting whether the association degree of the plurality of data sets and the correction value to be detected is within the preset numerical range, wherein the respectively obtaining the association degree of the plurality of data sets and the correction value to be detected comprises: respectively establishing an associated prediction model and a non-associated prediction model according to line loss data of all power grids in the target area; establishing a prediction model to be associated according to the correction value to be detected; and obtaining the association degree of each data set and the correction value to be detected according to the association prediction model, the non-association prediction model and the prediction model to be associated.
8. The system of claim 7, wherein the associated prediction model:
wherein N is i For the partitioned data set; q (Q) j For data set N i J=l, 2, …, n; x is X in Is N i With respect to corresponding features Q j A range of magnitudes; t is a correction matrix, which is obtained by multiplying a n-order identity matrix by a correction value.
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