CN112421692A - Method and device for determining power correction model in early warning state - Google Patents
Method and device for determining power correction model in early warning state Download PDFInfo
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- H—ELECTRICITY
- H02—GENERATION; CONVERSION OR DISTRIBUTION OF ELECTRIC POWER
- H02J—CIRCUIT ARRANGEMENTS OR SYSTEMS FOR SUPPLYING OR DISTRIBUTING ELECTRIC POWER; SYSTEMS FOR STORING ELECTRIC ENERGY
- H02J3/00—Circuit arrangements for ac mains or ac distribution networks
- H02J3/38—Arrangements for parallely feeding a single network by two or more generators, converters or transformers
- H02J3/46—Controlling of the sharing of output between the generators, converters, or transformers
- H02J3/48—Controlling the sharing of the in-phase component
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- H—ELECTRICITY
- H02—GENERATION; CONVERSION OR DISTRIBUTION OF ELECTRIC POWER
- H02J—CIRCUIT ARRANGEMENTS OR SYSTEMS FOR SUPPLYING OR DISTRIBUTING ELECTRIC POWER; SYSTEMS FOR STORING ELECTRIC ENERGY
- H02J3/00—Circuit arrangements for ac mains or ac distribution networks
- H02J3/003—Load forecast, e.g. methods or systems for forecasting future load demand
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- H—ELECTRICITY
- H02—GENERATION; CONVERSION OR DISTRIBUTION OF ELECTRIC POWER
- H02J—CIRCUIT ARRANGEMENTS OR SYSTEMS FOR SUPPLYING OR DISTRIBUTING ELECTRIC POWER; SYSTEMS FOR STORING ELECTRIC ENERGY
- H02J2203/00—Indexing scheme relating to details of circuit arrangements for AC mains or AC distribution networks
- H02J2203/20—Simulating, e g planning, reliability check, modelling or computer assisted design [CAD]
Abstract
The application discloses a method and a device for determining a power correction model in an early warning state. Wherein, the method comprises the following steps: obtain the early warning state of alternating current-direct current hybrid power distribution network, the early warning state includes: transformer overload or line overload; classifying the early warning state to obtain a classification result, wherein the classification result comprises: the first classification result is a power value of the real-time monitoring transformer and the line; the second classification result is that load flow prediction is carried out on the alternating current-direct current hybrid power distribution network based on situation perception data, and the load rate of the transformer and the load rate of a line are predicted; and determining a power correction model corresponding to the classification result. The method and the device solve the technical problems that the alternating current-direct current hybrid power grid is low in operation efficiency and poor in power supply reliability in the early warning state caused by the fact that related parameters cannot be effectively adjusted in the related technology.
Description
Technical Field
The application relates to the electrical field, in particular to a method and a device for determining a power correction model in an early warning state.
Background
Alternating current-direct current hybrid power distribution network under the early warning state can lead to the operation of crossing the limit of distribution network after receiving the small disturbance, should cross the operation and include: the transformer is out of limit or line out of limit, that is, although the grid is in an operation state of some constraint conditions, the grid has insufficient margin to prevent the system from being out of limit under the condition of N-1, and the operation state is generally called as an early warning state. Therefore, the alternating current-direct current hybrid power grid in the early warning state is unstable, and the out-of-limit operation is easy to occur due to small disturbance, so that the operation efficiency and the power supply reliability of the alternating current-direct current hybrid power grid are influenced, and therefore, it is very important to control the stable and reliable operation of the alternating current-direct current hybrid power grid in the early warning state by adjusting related parameters.
In view of the above problems, no effective solution has been proposed.
Disclosure of Invention
The embodiment of the application provides a method and a device for determining a power correction model in an early warning state, so as to at least solve the technical problems of low operation efficiency and poor power supply reliability of an alternating current-direct current hybrid power grid in the early warning state caused by the fact that related parameters cannot be effectively adjusted in the related technology.
According to an aspect of the embodiments of the present application, there is provided a method for determining a power correction model in an early warning state, including: obtain the early warning state of alternating current-direct current hybrid power distribution network, the early warning state includes: transformer overload or line overload; classifying the early warning state to obtain a classification result, wherein the classification result comprises: the first classification result is a power value of the real-time monitoring transformer and the line; the second classification result is that load flow prediction is carried out on the alternating current-direct current hybrid power distribution network based on situation perception data, and the load rate of the transformer and the load rate of a line are predicted; and determining a power correction model corresponding to the classification result.
Optionally, determining a power correction model corresponding to the classification result includes: the method comprises the steps of determining the minimum value corresponding to an objective function by adjusting the voltage and the current of a multi-port flexible direct current device, and constructing a power correction model by taking the minimum value as a target, wherein the power correction model comprises the following steps: an objective function and constraints.
Optionally, the objective function and the constraint are:
wherein, Δ PG,iI is any node, L is total number of branches, and P is active power regulating quantity at the side of the transformerG,i、QG,i、PiRespectively the injected active power, the reactive power and the line active power of the node i; u shapeiIs the node voltage; t isG,iIs the load factor of the transformer; pD,iIs flexibleThe port of the direct current device has active power; subscripts max, min are the upper and lower limits of the limit value considering the safety margin, respectively; sNIs the combination of all topological nodes; sG、SDRespectively, a power supply injection node and a collection of nodes within the flexible dc device.
Optionally, determining a power correction model corresponding to the classification result, further includes: and determining the transformer with overload or the line with overload according to the predicted load rate of the transformer and the predicted load rate of the line, and constructing a power correction model based on situation awareness early warning, wherein the power correction model is used for adjusting the voltage and the current of the multi-port flexible direct-current device and the output of each distributed power supply so as to reduce the load rate.
Optionally, a power correction model based on situational awareness early warning is constructed with a minimum active power adjustment amount as a target, where the power correction model includes: the method comprises the following steps of (1) respectively:
wherein, Δ PGiFor regulating the active power on the transformer side, PGiInjecting power to the power supply side; pijIs the line active power; pDiActive power of each port of the flexible direct current device; sGFor the set of power supply injection side nodes, SNFor the set of all topological nodes, SDIs a collection of port nodes of a flexible DC device, CPijFor the active power supply sensitivity, Δ P, to the lineDiIn order to adjust the active power of the port of the flexible direct current device, subscripts max and min are respectively an upper limit and a lower limit of a limit value, i is any node, and (i, j) represents any branch.
According to an aspect of the embodiments of the present application, there is provided an apparatus for determining a power correction model in an early warning state, including: the acquisition module is used for acquiring the early warning state of the AC/DC hybrid power distribution network, and the early warning state comprises: transformer overload or line overload; the classification module is used for classifying the early warning state to obtain a classification result, wherein the classification result comprises: the first classification result is a power value of the real-time monitoring transformer and the line; the second classification result is that load flow prediction is carried out on the alternating current-direct current hybrid power distribution network based on situation perception data, and the load rate of the transformer and the load rate of a line are predicted; and the determining module is used for determining the power correction model corresponding to the classification result.
Optionally, determining a power correction model corresponding to the classification result includes: the method comprises the steps of determining the minimum value corresponding to an objective function by adjusting the voltage and the current of a multi-port flexible direct current device, and constructing a power correction model by taking the minimum value as a target, wherein the power correction model comprises the following steps: an objective function and constraints.
Optionally, determining a power correction model corresponding to the classification result, further includes: and determining the transformer with overload or the line with overload according to the predicted load rate of the transformer and the predicted load rate of the line, and constructing a power correction model based on situation awareness early warning, wherein the power correction model is used for adjusting the voltage and the current of the multi-port flexible direct-current device and the output of each distributed power supply so as to reduce the load rate.
According to another aspect of the application, a non-volatile storage medium is further provided, and the non-volatile storage medium includes a stored program, wherein the program controls a device in which the non-volatile storage medium is located to execute any one of the methods for determining the power correction model in the early warning state when the program is running.
According to another aspect of the application, there is also provided a processor for executing a program stored in a memory, wherein the program when executed performs any of the methods for determining a power correction model in an early warning state.
In the embodiment of the application, the early warning states are classified, and the power correction models corresponding to the types are established through classification processing, so that the purpose of adjusting parameters such as the active power and the load factor of the transformer side is achieved, the minimization of the active power of the transformer side is realized, the technical effects of the operation efficiency and the power supply reliability of the alternating current/direct current hybrid power grid are further improved, and the technical problems that the operation efficiency of the alternating current/direct current hybrid power grid is low and the power supply reliability is poor in the early warning states due to the fact that related parameters cannot be effectively adjusted in the related technology are solved.
Drawings
The accompanying drawings, which are included to provide a further understanding of the application and are incorporated in and constitute a part of this application, illustrate embodiment(s) of the application and together with the description serve to explain the application and not to limit the application. In the drawings:
FIG. 1 is a schematic flow chart diagram illustrating a method for determining a power correction model in an early warning state according to an embodiment of the present disclosure;
fig. 2 is a schematic structural diagram of an apparatus for determining a power correction model in an early warning state according to an embodiment of the present application.
Detailed Description
In order to make the technical solutions better understood by those skilled in the art, the technical solutions in the embodiments of the present application will be clearly and completely described below with reference to the drawings in the embodiments of the present application, and it is obvious that the described embodiments are only partial embodiments of the present application, but not all embodiments. All other embodiments, which can be derived by a person skilled in the art from the embodiments given herein without making any creative effort, shall fall within the protection scope of the present application.
It should be noted that the terms "first," "second," and the like in the description and claims of this application and in the drawings described above are used for distinguishing between similar elements and not necessarily for describing a particular sequential or chronological order. It is to be understood that the data so used is interchangeable under appropriate circumstances such that the embodiments of the application described herein are capable of operation in sequences other than those illustrated or described herein. Furthermore, the terms "comprises," "comprising," and "having," and any variations thereof, are intended to cover a non-exclusive inclusion, such that a process, method, system, article, or apparatus that comprises a list of steps or elements is not necessarily limited to those steps or elements expressly listed, but may include other steps or elements not expressly listed or inherent to such process, method, article, or apparatus.
In accordance with an embodiment of the present application, there is provided an embodiment of a method of determining a power correction model in an early warning state, it should be noted that the steps illustrated in the flowchart of the drawings may be performed in a computer system such as a set of computer executable instructions and that while a logical order is illustrated in the flowchart, in some cases the steps illustrated or described may be performed in an order different than here.
Fig. 1 is a method for determining a power correction model in an early warning state according to an embodiment of the present application, as shown in fig. 1, the method includes the following steps:
step S102, acquiring an early warning state of the AC/DC hybrid power distribution network, wherein the early warning state comprises the following steps: transformer overload or line overload;
step S104, classifying the early warning states to obtain a classification result, wherein the classification result comprises: the first classification result is a power value of the real-time monitoring transformer and the line; the second classification result is that load flow prediction is carried out on the alternating current-direct current hybrid power distribution network based on situation perception data, and the load rate of the transformer and the load rate of a line are predicted;
and step S106, determining a power correction model corresponding to the classification result.
In the method, firstly, the early warning state of the AC/DC hybrid power distribution network can be obtained, and the early warning state comprises the following steps: transformer overload or line overload; then, classify the early warning state to obtain a classification result, wherein the classification result comprises: the first classification result is a power value of the real-time monitoring transformer and the line; the second classification result is that load flow prediction is carried out on the alternating current-direct current hybrid power distribution network based on situation perception data, and the load rate of the transformer and the load rate of a line are predicted; and finally, determining a power correction model corresponding to the classification result, and achieving the purpose of adjusting parameters such as transformer side active power, load factor and the like, thereby realizing the minimization of the transformer side active power, further improving the technical effects of the operation efficiency and the power supply reliability of the AC/DC hybrid power grid, and further solving the technical problems of low operation efficiency and poor power supply reliability of the AC/DC hybrid power grid in an early warning state caused by the fact that related parameters cannot be effectively adjusted in the related technology.
In some optional embodiments of the present application, determining a power correction model corresponding to the classification result includes: the method comprises the steps of determining the minimum value corresponding to an objective function by adjusting the voltage and the current of a multi-port flexible direct current device, and constructing a power correction model by taking the minimum value as a target, wherein the power correction model comprises the following steps: an objective function and constraints.
Specifically, the objective function and the constraint condition are respectively:
wherein, Δ PG,iI is any node, L is total number of branches, and P is active power regulating quantity at the side of the transformerG,i、QG,i、PiRespectively the injected active power, the reactive power and the line active power of the node i; u shapeiIs the node voltage; t isG,iIs the load factor of the transformer; pD,iThe port of the flexible direct current device has active power; subscripts max, min are the upper and lower limits of the limit value considering the safety margin, respectively; sNIs the combination of all topological nodes; sG、SDRespectively, a power supply injection node and a collection of nodes within the flexible dc device.
In some optional embodiments of the present application, determining a power correction model corresponding to the classification result further includes: and determining the transformer with overload or the line with overload according to the predicted load rate of the transformer and the predicted load rate of the line, and constructing a power correction model based on situation awareness early warning, wherein the power correction model is used for adjusting the voltage and the current of the multi-port flexible direct-current device and the output of each distributed power supply so as to reduce the load rate.
Specifically falling, a power correction model based on situation awareness early warning is established by taking the minimum active power regulating quantity as a target, wherein the power correction model comprises the following steps: the method comprises the following steps of (1) respectively:
wherein, Δ PGiFor regulating the active power on the transformer side, PGiInjecting power to the power supply side; pijIs the line active power; pDiActive power of each port of the flexible direct current device; sGFor the set of power supply injection side nodes, SNFor the set of all topological nodes, SDIs a collection of port nodes of a flexible DC device, CPijFor the active power supply sensitivity, Δ P, to the lineDiIn order to adjust the active power of the port of the flexible direct current device, subscripts max and min are respectively an upper limit and a lower limit of a limit value, i is any node, and (i, j) represents any branch.
Fig. 2 is a device for determining a power correction model in an early warning state according to an embodiment of the present application, and as shown in fig. 2, the device includes:
the acquisition module 40 is used for acquiring the early warning state of the alternating current-direct current hybrid power distribution network, and the early warning state comprises: transformer overload or line overload;
the classification module 42 is configured to classify the early warning state to obtain a classification result, where the classification result includes: the first classification result is a power value of the real-time monitoring transformer and the line; the second classification result is that load flow prediction is carried out on the alternating current-direct current hybrid power distribution network based on situation perception data, and the load rate of the transformer and the load rate of a line are predicted;
and the determining module 44 is configured to determine a power correction model corresponding to the classification result.
In the device, obtain module 40 for obtain the early warning state of alternating current-direct current hybrid power distribution network, the early warning state includes: transformer overload or line overload; the classification module 42 is configured to classify the early warning state to obtain a classification result, where the classification result includes: the first classification result is a power value of the real-time monitoring transformer and the line; the second classification result is that load flow prediction is carried out on the alternating current-direct current hybrid power distribution network based on situation perception data, and the load rate of the transformer and the load rate of a line are predicted; the determining module 44 is configured to determine a power correction model corresponding to the classification result, so as to achieve the purpose of adjusting parameters such as the transformer side active power and the load factor, thereby minimizing the transformer side active power, further improving the operation efficiency and the power supply reliability of the ac/dc hybrid power grid, and further solving the technical problems of low operation efficiency and poor power supply reliability of the ac/dc hybrid power grid in an early warning state due to the fact that related parameters cannot be effectively adjusted in the related art.
In some optional embodiments of the present application, the determining the power correction model corresponding to the classification result may be: the method comprises the steps of determining the minimum value corresponding to an objective function by adjusting the voltage and the current of a multi-port flexible direct current device, and constructing a power correction model by taking the minimum value as a target, wherein the power correction model comprises the following steps: an objective function and constraints.
In some optional embodiments of the present application, determining the power correction model corresponding to the classification result may further include: and determining the transformer with overload or the line with overload according to the predicted load rate of the transformer and the predicted load rate of the line, and constructing a power correction model based on situation awareness early warning, wherein the power correction model is used for adjusting the voltage and the current of the multi-port flexible direct-current device and the output of each distributed power supply so as to reduce the load rate.
According to another aspect of the application, a non-volatile storage medium is further provided, and the non-volatile storage medium includes a stored program, wherein the program controls a device in which the non-volatile storage medium is located to execute any one of the methods for determining the power correction model in the early warning state when the program is running.
Specifically, the storage medium is used for storing program instructions for executing the following functions, and the following functions are realized:
obtain the early warning state of alternating current-direct current hybrid power distribution network, the early warning state includes: transformer overload or line overload; classifying the early warning state to obtain a classification result, wherein the classification result comprises: the first classification result is a power value of the real-time monitoring transformer and the line; the second classification result is that load flow prediction is carried out on the alternating current-direct current hybrid power distribution network based on situation perception data, and the load rate of the transformer and the load rate of a line are predicted; and determining a power correction model corresponding to the classification result.
According to another aspect of the application, there is also provided a processor for executing a program stored in a memory, wherein the program when executed performs any of the methods for determining a power correction model in an early warning state.
Specifically, the processor is configured to call a program instruction in the memory, and implement the following functions:
obtain the early warning state of alternating current-direct current hybrid power distribution network, the early warning state includes: transformer overload or line overload; classifying the early warning state to obtain a classification result, wherein the classification result comprises: the first classification result is a power value of the real-time monitoring transformer and the line; the second classification result is that load flow prediction is carried out on the alternating current-direct current hybrid power distribution network based on situation perception data, and the load rate of the transformer and the load rate of a line are predicted; and determining a power correction model corresponding to the classification result.
The above-mentioned serial numbers of the embodiments of the present application are merely for description and do not represent the merits of the embodiments.
In the above embodiments of the present application, the descriptions of the respective embodiments have respective emphasis, and for parts that are not described in detail in a certain embodiment, reference may be made to related descriptions of other embodiments.
In the embodiments provided in the present application, it should be understood that the disclosed technology can be implemented in other ways. The above-described embodiments of the apparatus are merely illustrative, and for example, the division of the units may be a logical division, and in actual implementation, there may be another division, for example, multiple units or components may be combined or integrated into another system, or some features may be omitted, or not executed. In addition, the shown or discussed mutual coupling or direct coupling or communication connection may be an indirect coupling or communication connection through some interfaces, units or modules, and may be in an electrical or other form.
The units described as separate parts may or may not be physically separate, and parts displayed as units may or may not be physical units, may be located in one place, or may be distributed on a plurality of units. Some or all of the units can be selected according to actual needs to achieve the purpose of the solution of the embodiment.
In addition, functional units in the embodiments of the present application may be integrated into one processing unit, or each unit may exist alone physically, or two or more units are integrated into one unit. The integrated unit can be realized in a form of hardware, and can also be realized in a form of a software functional unit.
The integrated unit, if implemented in the form of a software functional unit and sold or used as a stand-alone product, may be stored in a computer readable storage medium. Based on such understanding, the technical solution of the present application may be embodied in the form of a software product, which is stored in a storage medium and includes several instructions for causing a computer device (which may be a personal computer, a server, or a network device) to execute all or part of the steps of the method according to the embodiments of the present application. And the aforementioned storage medium includes: a U-disk, a Read-Only Memory (ROM), a Random Access Memory (RAM), a removable hard disk, a magnetic or optical disk, and other various media capable of storing program codes.
The foregoing is only a preferred embodiment of the present application and it should be noted that those skilled in the art can make several improvements and modifications without departing from the principle of the present application, and these improvements and modifications should also be considered as the protection scope of the present application.
Claims (10)
1. A method for determining a power correction model in an early warning state is characterized by comprising the following steps:
the method comprises the following steps of obtaining an early warning state of the AC/DC hybrid power distribution network, wherein the early warning state comprises: transformer overload or line overload;
classifying the early warning state to obtain a classification result, wherein the classification result comprises: the method comprises the steps of obtaining a first classification result and a second classification result, wherein the first classification result is a power value of a real-time monitoring transformer and a line; the second classification result is that load flow prediction is carried out on the alternating current-direct current hybrid power distribution network based on situation perception data, and the load rate of a transformer and the load rate of a line are predicted;
and determining a power correction model corresponding to the classification result.
2. The method of claim 1, wherein determining the power correction model corresponding to the classification result comprises:
the method comprises the steps of determining a minimum value corresponding to an objective function by adjusting the voltage and the current of a multi-port flexible direct current device, and constructing a power correction model by taking the minimum value as a target, wherein the power correction model comprises the following steps: an objective function and constraints.
3. The method of claim 2, wherein the objective function and the constraint are:
wherein, Δ PG,iI is any node, L is total number of branches, and P is active power regulating quantity at the side of the transformerG,i、QG,i、PiRespectively the injected active power, the reactive power and the line active power of the node i; u shapeiIs the node voltage; t isG,iIs the load factor of the transformer; pD,iThe port of the flexible direct current device has active power; subscripts max, min are the upper and lower limits of the limit value considering the safety margin, respectively; sNIs the combination of all topological nodes; sG、SDRespectively, a power supply injection node and a collection of nodes within the flexible dc device.
4. The method of claim 1, wherein determining the power correction model corresponding to the classification result further comprises:
and determining the transformer with overload or the line with overload according to the predicted load rate of the transformer and the predicted load rate of the line, and constructing a power correction model based on situation awareness early warning, wherein the power correction model is used for adjusting the voltage and the current of the multi-port flexible direct-current device and the output of each distributed power supply so as to reduce the load rate.
5. The method of claim 4, wherein a power correction model based on situational awareness warning is constructed with a minimum active power adjustment as a target, wherein the power correction model comprises: an objective function and a constraint condition, wherein the objective function and the constraint condition are respectively:
wherein, Δ PGiFor regulating the active power on the transformer side, PGiInjecting power to the power supply side; pijIs the line active power; pDiActive power of each port of the flexible direct current device; sGFor the set of power supply injection side nodes, SNFor the set of all topological nodes, SDIs a collection of port nodes of a flexible DC device, CPijFor the active power supply sensitivity, Δ P, to the lineDiIn order to adjust the active power of the port of the flexible direct current device, subscripts max and min are respectively an upper limit and a lower limit of a limit value, i is any node, and (i, j) represents any branch.
6. An apparatus for determining a power correction model in an early warning state, comprising:
the acquisition module is used for acquiring the early warning state of the AC/DC hybrid power distribution network, wherein the early warning state comprises: transformer overload or line overload;
the classification module is used for classifying the early warning state to obtain a classification result, wherein the classification result comprises: the method comprises the steps of obtaining a first classification result and a second classification result, wherein the first classification result is a power value of a real-time monitoring transformer and a line; the second classification result is that load flow prediction is carried out on the alternating current-direct current hybrid power distribution network based on situation perception data, and the load rate of a transformer and the load rate of a line are predicted;
and the determining module is used for determining the power correction model corresponding to the classification result.
7. The apparatus of claim 6, wherein determining the power correction model corresponding to the classification result comprises:
the method comprises the steps of determining a minimum value corresponding to an objective function by adjusting the voltage and the current of a multi-port flexible direct current device, and constructing a power correction model by taking the minimum value as a target, wherein the power correction model comprises the following steps: an objective function and constraints.
8. The apparatus of claim 6, wherein determining the power correction model corresponding to the classification result further comprises:
and determining the transformer with overload or the line with overload according to the predicted load rate of the transformer and the predicted load rate of the line, and constructing a power correction model based on situation awareness early warning, wherein the power correction model is used for adjusting the voltage and the current of the multi-port flexible direct-current device and the output of each distributed power supply so as to reduce the load rate.
9. A non-volatile storage medium, comprising a stored program, wherein the program, when executed, controls a device in which the non-volatile storage medium is located to perform the method for determining a power correction model in an early warning state according to any one of claims 1 to 5.
10. A processor for executing a program stored in a memory, wherein the program when executed performs the method of determining a power correction model in an early warning state according to any one of claims 1 to 5.
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