CN118157112A - Power supply recovery method, device, equipment and storage medium for power distribution network - Google Patents
Power supply recovery method, device, equipment and storage medium for power distribution network Download PDFInfo
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Abstract
The invention discloses a power supply recovery method of a power distribution network. The method comprises the following steps: converting the obtained information of the photovoltaic output influence factors into weather type indexes; building a photovoltaic output prediction model based on the weather type index; establishing an objective function, and constructing a power supply recovery model according to the photovoltaic output prediction model, the objective function and preset constraint conditions; converting the power supply recovery model into a mixed integer second order cone planning model and solving to obtain a power supply recovery scheme; and recovering electricity according to the power supply recovery scheme. The invention has the advantages of reasonable configuration of limited power generation in space-time dimension, reduced power failure loss and improved reliability of power supply recovery.
Description
Technical Field
The present invention relates to the field of power restoration technologies, and in particular, to a power restoration method, apparatus, device, and storage medium for a power distribution network.
Background
With the continuous development of power distribution networks, users have put higher demands on power supply reliability. After a power distribution network fault and power failure event occurs, the rapid and effective power restoration is one of key means for improving the reliability of the power distribution network. When the traditional power distribution network fails, a failure area is isolated through measures such as relay protection, and then a power failure load is transferred to other normal power supply feeder lines through switch operation. For a small-range local fault power failure accident, the traditional load transfer means can still solve, but after a large-area power failure accident occurs to a power distribution network, the traditional load transfer means can not only face frequent load transfer switch operation, but also can possibly have the problems of feeder overload, voltage out-of-limit and the like, so that the bad result of secondary load shedding is caused. Therefore, under the scene of blackout and limited power generation resources, the optimized power supply recovery strategy of the power distribution network has important significance for improving the power supply reliability.
In the prior art, although the power supply recovery of the distributed power supply under the blackout accident is realized, a part of the power supply recovery does not consider the time dimension and is based on the recovery result of a single time section; the other part accounts for the time dimension of the recovery process, the recovery effect is improved by different recovery topologies or power supply output of multiple time periods, but the influence of randomness of intermittent distributed power supply output represented by photovoltaics on power supply recovery is not considered.
Disclosure of Invention
In order to solve the technical problems, the power supply recovery method of the power distribution network is provided, the randomness of the photovoltaic output in the time dimension is considered, limited power generation is reasonably configured in the time-space dimension, the power failure loss is reduced, and the reliability of power supply recovery is improved.
In a first aspect, an embodiment of the present invention provides a power supply restoration method for a power distribution network, including:
converting the obtained information of the photovoltaic output influence factors into weather type indexes;
building a photovoltaic output prediction model based on the weather type index;
establishing an objective function, and constructing a power supply recovery model according to the photovoltaic output prediction model, the objective function and preset constraint conditions;
Converting the power supply recovery model into a mixed integer second order cone planning model and solving to obtain a power supply recovery scheme;
And recovering electricity according to the power supply recovery scheme.
Further, before converting the obtained information of the photovoltaic output influencing factor into the weather type index, the method further comprises:
initializing network parameters of a target power distribution network; the network parameters include branch numbers, head end node and tail end node numbers, line impedance and transformer transformation ratio of the line.
Further, the converting the obtained information of the photovoltaic output influencing factor into the weather type index includes:
Acquiring information of photovoltaic output influence factors, and acquiring photovoltaic output data to be judged according to the information of the photovoltaic output influence factors;
calculating Euclidean distance between the photovoltaic output data and average photovoltaic output of each weather type;
Obtaining a weather type corresponding to the photovoltaic output data according to the Euclidean distance;
And obtaining a weather type index based on the photovoltaic power station historical data and the weather type.
Further, the establishing an objective function, and establishing a power supply recovery model according to the objective function and a preset constraint condition, includes:
establishing an objective function with the maximum load weighted power supply time and the minimum system network active loss as targets;
Constructing a power supply recovery model according to the objective function and a preset constraint condition; the constraint conditions comprise limited energy constraint, photovoltaic output constraint, tide constraint, operation constraint and load state change constraint.
Further, the converting the power supply recovery model into a mixed integer second order cone planning model and solving to obtain a power supply recovery scheme includes:
performing convex constraint processing on a power flow equation in the power flow constraint, and converting the power supply recovery model into a mixed integer second-order cone planning model;
and solving the mixed integer second order cone planning model by utilizing Gurobi to obtain a power supply recovery scheme.
In a second aspect, an embodiment of the present invention provides a power supply restoration device for a power distribution network, including:
the conversion module is used for converting the acquired information of the photovoltaic output influence factors into weather type indexes;
the photovoltaic output prediction model construction module is used for constructing a photovoltaic output prediction model based on the weather type index;
the power supply recovery model construction module is used for establishing an objective function and constructing a power supply recovery model according to the photovoltaic output prediction model, the objective function and preset constraint conditions;
the power supply recovery scheme solving module is used for converting the power supply recovery model into a mixed integer second order cone planning model and solving the mixed integer second order cone planning model to obtain a power supply recovery scheme;
and the power supply recovery module is used for recovering the electricity according to the power supply recovery scheme.
Further, the method comprises the steps of:
Before the obtained information of the photovoltaic output influence factors is converted into the weather type index, the method further comprises the following steps:
Initializing network parameters of the target power distribution network; the network parameters include branch numbers, head end node and tail end node numbers, line impedance and transformer transformation ratio of the line.
Further, the method comprises the steps of:
the converting the obtained information of the photovoltaic output influence factors into weather type indexes comprises the following steps:
Acquiring information of photovoltaic output influence factors, and acquiring photovoltaic output data to be judged according to the information of the photovoltaic output influence factors;
calculating Euclidean distance between the photovoltaic output data and average photovoltaic output of each weather type;
Obtaining a weather type corresponding to the photovoltaic output data according to the Euclidean distance;
And obtaining a weather type index based on the photovoltaic power station historical data and the weather type.
In a third aspect, an embodiment of the present invention provides an electronic device, including:
A memory for storing a computer program;
a processor for executing the computer program;
Wherein the processor, when executing the computer program, implements the power restoration method for the power distribution network according to any one of the first aspect.
In a fourth aspect, an embodiment of the present invention provides a computer readable storage medium storing a computer program, where the computer program is executed to implement the power restoration method of the power distribution network according to any one of the first aspects.
Compared with the prior art, the power supply recovery method for the power distribution network has the beneficial effects that: converting the obtained information of the photovoltaic output influence factors into weather type indexes; building a photovoltaic output prediction model based on the weather type index; establishing an objective function, and constructing a power supply recovery model according to the photovoltaic output prediction model, the objective function and preset constraint conditions; converting the power supply recovery model into a mixed integer second order cone planning model and solving to obtain a power supply recovery scheme; and recovering electricity according to the power supply recovery scheme. The method for reasonably configuring the limited power generation resources in the space-time dimension is provided, longer power supply time is provided for important load, power failure loss is reduced, and reliability of power supply recovery is improved.
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In order to more clearly illustrate the technical features of the embodiments of the present invention, the drawings that are required to be used in the embodiments of the present invention will be briefly described below, and it is apparent that the drawings described below are only some embodiments of the present invention and that other drawings may be obtained according to these drawings without inventive effort for a person skilled in the art.
FIG. 1 is a schematic flow chart of an embodiment of a power restoration method for a power distribution network according to the present invention;
FIG. 2 is a schematic structural diagram of an embodiment of a power restoration device for a power distribution network according to the present invention;
fig. 3 is a schematic structural diagram of an embodiment of an electronic device provided by the present invention.
Detailed Description
The following description of the embodiments of the present invention will be made clearly and completely with reference to the accompanying drawings, in which it is apparent that the embodiments described are only some embodiments of the present invention, but not all embodiments. All other embodiments, which can be made by those skilled in the art based on the embodiments of the invention without making any inventive effort, are intended to be within the scope of the invention.
In a first aspect, the present invention provides a power supply recovery method for a power distribution network, and referring to fig. 1, a schematic flow chart of an embodiment of the power supply recovery method for a power distribution network provided by the present invention is provided.
As shown in fig. 1, the method comprises the steps of:
s1: converting the obtained information of the photovoltaic output influence factors into weather type indexes;
S2: building a photovoltaic output prediction model based on the weather type index;
S3: establishing an objective function, and constructing a power supply recovery model according to the photovoltaic output prediction model, the objective function and preset constraint conditions;
S4: converting the power supply recovery model into a mixed integer second order cone planning model and solving to obtain a power supply recovery scheme;
s5: and recovering electricity according to the power supply recovery scheme.
In specific implementation, historical data, various meteorological data and photovoltaic output influence factor information of a photovoltaic power station are obtained, the photovoltaic output influence factor information is converted into weather type indexes, the weather type indexes are taken as input, a prediction model based on a BP neural network is established, the BP neural network is trained, short-term output prediction of the photovoltaic power station is carried out by using the trained neural network model, an objective function is established, a power supply recovery model is established according to the photovoltaic output prediction model, the objective function and preset constraint conditions, the power supply recovery model is converted into a mixed integer second order cone planning model and solved, a power supply recovery scheme is obtained, and power recovery is carried out according to the power supply recovery scheme.
In summary, the obtained information of the photovoltaic output influence factors is converted into the weather type index; building a photovoltaic output prediction model based on the weather type index; establishing an objective function, and constructing a power supply recovery model according to the photovoltaic output prediction model, the objective function and preset constraint conditions; converting the power supply recovery model into a mixed integer second order cone planning model and solving to obtain a power supply recovery scheme; and recovering electricity according to the power supply recovery scheme. The limited power generation resources are reasonably configured in space-time dimension, longer power supply time is provided for important load, power failure loss is reduced, and reliability of power supply recovery is improved.
In an alternative embodiment, before the converting the obtained information of the photovoltaic output influencing factor into the weather type index, the method further includes:
initializing network parameters of a target power distribution network; the network parameters include branch numbers, head end node and tail end node numbers, line impedance and transformer transformation ratio of the line.
Specifically, network parameters of a target power distribution network are initialized, including data such as branch numbers of lines, numbers of head end nodes and tail end nodes, line impedance, transformer transformation ratio and the like.
In an alternative embodiment, the converting the obtained information of the photovoltaic output influencing factor into the weather type index includes:
Acquiring information of photovoltaic output influence factors, and acquiring photovoltaic output data to be judged according to the information of the photovoltaic output influence factors;
calculating Euclidean distance between the photovoltaic output data and average photovoltaic output of each weather type;
Obtaining a weather type corresponding to the photovoltaic output data according to the Euclidean distance;
And obtaining a weather type index based on the photovoltaic power station historical data and the weather type.
Specifically, photovoltaic power station historical data and various meteorological data are used as bases, photovoltaic output influence factors are mapped into weather type indexes, and firstly, based on weather forecast data, euclidean distance expressions are used for further classifying weather types. The euclidean distance is a distance definition, which represents the real distance between two points in a multidimensional space, and the similarity difference between different samples is judged through the euclidean distance, so that the weather types are classified:
Wherein x i is the average value of the photovoltaic output at each moment of different weather types, and y i is the photovoltaic output at each moment of a certain day, the weather types of which need to be judged.
The Euclidean distance between certain photovoltaic output data and the average photovoltaic output of the weather types is calculated, and the weather types can be further classified by comparing the Euclidean distance of the two weather types to judge which weather type the two types of generated energy are close to are more suitable. For example, the average power generation power of a photovoltaic power plant with cloudy weather forecast (less actual possible cloud quantity) at each moment is d 1 and d 2 respectively from the average power generation power with sunny weather type and the average power generation power with cloudy weather type, if d 1<d2, the weather type is closer to sunny weather, and the weather type is classified as sunny weather type; conversely, if d 1>d2 indicates that the weather type is closer to cloudy weather, the weather type is classified as cloudy weather.
After being classified by Euclidean distance, the multiplying power relation is mapped into weather type indexes according to the multiplying power relation among the photovoltaic output data under each weather type.
In an alternative embodiment, the establishing an objective function, and constructing a power supply recovery model according to the objective function and a preset constraint condition includes:
establishing an objective function with the maximum load weighted power supply time and the minimum system network active loss as targets;
Constructing a power supply recovery model according to the objective function and a preset constraint condition; the constraint conditions comprise limited energy constraint, photovoltaic output constraint, tide constraint, operation constraint and load state change constraint.
Specifically, an objective function of a power supply recovery model of the power distribution network is determined, and the main objective is that the load weighted power supply time is maximum, and meanwhile, the minimum active loss of the system network is considered. Because the two target dimensions are different, normalization processing is needed to be carried out on the two target dimensions respectively to obtain a sub-target function formula and a sub-target function formula, and a comprehensive target function is obtained by setting target weights, as follows:
maxf＝λ1f1-λ2f2；
Wherein L represents all load node sets within the power island; w i represents an important weight coefficient of the load i, represents an important weight coefficient of the period t, gives higher weight to the 1 st period after power failure in order to provide a 'stop transition time' for the important load, and the rest period is basic weight; t 0 is a time span in which the entire power restoration time range is divided into a number of time periods; a i,t represents the power supply state of a load i in a period t, which is a 0-1 variable, and the load is connected to the power distribution network through a switch, so that the power can be supplied completely or not at all, and if the load is in the power supply state, a i,t =1; Representing the network active loss of the system in a period t; s base represents a reference power of the system; lambda 1 and lambda 2 respectively represent target weight coefficients of load weighted power supply time and system network loss, and the invention takes the maximum load weighted power supply time as a main target and the minimum system network active loss as a secondary target, so lambda 1 is set to be 0.9 and lambda 2 is set to be 0.1.
And constructing a power supply recovery model according to the objective function and a preset constraint condition. Because no upper power grid supplies power in the large power outage scene, the power is supported and supplied only by local power generation resources in a power supply island, and therefore limited energy constraint needs to be considered; the random power supply represented by the photovoltaic has output fluctuation, so that the dispatching output of the photovoltaic in the power supply recovery process needs to be limited in order to reduce the adverse effect of the randomness of the random power supply on the operation of a power supply island, and the photovoltaic output constraint needs to be considered; in order to realize normal operation of the system in the power supply island and within a safe range, the flow constraint and the operation constraint of the system need to be considered; in addition, in order to avoid a phenomenon that the load state of the same node frequently changes in the restoration policy, it is necessary to consider load state change constraints. Thus, the constraints include finite energy constraints, photovoltaic output constraints, power flow constraints, operational constraints, and load state change constraints.
The limited energy constraint is specifically:
the DG/PV represents all distributed power supply sets except photovoltaic in a power supply island, including synchronous generators, distributed energy storage and mobile emergency power supplies, wherein the mobile emergency power supplies comprise mobile emergency energy storage vehicles, idle electric buses and the like, and can be used as energy storage equipment to be connected into a power distribution network through charging piles to provide power support when a blackout accident occurs; Representing the active power value of power supply i at time period t; e i,0 represents the energy resource remained by the power supply i at the beginning of the occurrence of the blackout accident, and all different energy forms are converted into electric energy forms to participate in calculation for the convenience of calculation.
The photovoltaic output constraint is specifically as follows:
Wherein, Representing the dispatching output value of the ith photovoltaic power supply in a period t; /(I)Representing a predicted force value of an ith photovoltaic power supply in a period t; e avg represents the average absolute percentage error.
The tide constraint specifically comprises the following steps:
Node KCL equation and power definition formula:
VCR equation:
Node power balancing:
The active loss of the system network is equal to the difference value between the output power of all distributed power supplies in the power supply island and the power supply power of all jiedian loads:
Wherein N and E respectively represent a node set and a line set in the power supply island; k.fwdarw.i represents a downstream node set of node i; beta ij,t represents the switching state of the line (i, j) in the period t, is a 0-1 variable, if the line is in the running state, beta ij,t＝1;Vi,t、Si,t, And/>Respectively representing the voltage of the node i, the injection power of the node i, the distributed power supply output power of the node i and the load power requirement of the node i in a period t; s ij,t and I ij,t represent the power flowing through the line (I, j) and the current flowing through the line (I, j), respectively, at the period t; z ij represents the impedance value of the line (i, j); /(I)And/>Respectively representing active loss of a system network, active power output of a limited distributed power supply of the node i and active power demand of a load of the node i in a period t.
The operating constraints include node voltage constraints, line capacity constraints, other distributed power supply output constraints, and radial topology constraints.
The node voltage constraint is specifically as follows:
Wherein, And/>Representing the lower and upper limits, respectively, of the operating voltage amplitude of node i.
The line capacity constraint is specifically:
Wherein, An apparent power upper limit for line (i, j); the function of the beta ij,t coefficient is that when line (i, j) is disconnected, its line power is equal to 0.
The output constraints of the other distributed power supplies comprise the output constraints of the synchronous generator type distributed power supplies and the output constraints of the distributed energy storage or mobile emergency power supplies, and in order to ensure the normal operation of the distributed energy storage and mobile emergency power supply equipment, the state of charge (SOC) of the distributed energy storage and mobile emergency power supply equipment needs to be set with an upper limit and a lower limit, specifically:
G, B and EV respectively represent a set of synchronous generator distributed power supplies, a set of distributed energy storage and a set of mobile emergency power supplies; And/> Respectively representing an active output upper limit value and a reactive output upper limit value of a distributed power supply connected to a node i; p i ch,max and P i dch,max represent an upper limit value of charging power and an upper limit value of discharging power of an energy storage or electric vehicle charging pile connected to the node i, respectively; χ i mim and χ i max represent the lower and upper limits, respectively, of the state of charge of the stored or mobile emergency power supply connected to node i; χ i,0 represents the state of charge of the stored energy or mobile emergency power supply connected to node i at the beginning of recovery; ρ i represents a conversion coefficient of energy into a state of charge.
The radial topological constraint is specifically as follows:
Wherein n b and n s respectively represent the total number of nodes and the total number of root nodes in the power supply island, and in general, 1 power supply island is provided with only 1 root node; gamma 1j,t denotes that the root node does not have a parent node; gamma 1j,t is a 0-1 variable, taken as 1 when j is the parent of i.
The load state change constraint is specifically:
Where α i,t-1 represents the state of the load of node i during period t-1, so that t starts from period 2 during accumulation.
In an alternative embodiment, the converting the power supply recovery model into a mixed integer second order cone planning model and solving to obtain a power supply recovery scheme includes:
performing convex constraint processing on a power flow equation in the power flow constraint, and converting the power supply recovery model into a mixed integer second-order cone planning model;
and solving the mixed integer second order cone planning model by utilizing Gurobi to obtain a power supply recovery scheme.
Specifically, in the power supply recovery model, the node KCL equation and the power definition type and the VCR equation contain variable product terms, belong to non-convex constraint, are difficult to solve in the optimization problem, can convert the non-convex constraint into the convex constraint by using a linearization or convex relaxation method, and convert the power supply recovery model into a mixed integer second-order cone planning model, so that the power supply recovery model is easier to solve by using a mature optimization solver.
Firstly, performing convex constraint processing on the node KCL equation and the power definition type, wherein the convex constraint processing comprises the following specific steps:
performing convex constraint processing on the VCR equation, wherein the convex constraint processing comprises the following specific steps of:
where v i,t＝Vi,tVi,t * and l ij,t＝Iij,tIij,t * are non-negative real variables introduced to cancel the quadratic term, M represents a positive real number with a very large value, and if line (i, j) is disconnected, i.e. β ij,t =0, no constraint is placed on X ij,t.
The power supply recovery model is converted into a mixed integer second-order cone planning model, yalmip toolboxes of a MATLAB platform can be utilized for modeling, a business solver Gurobi is called for solving, and finally a multi-source collaborative multi-period power supply recovery scheme is obtained.
In a second aspect, the present invention provides a power supply recovery device for a power distribution network, and referring to fig. 2, a schematic structural diagram of an embodiment of the power supply recovery device for a power distribution network provided by the present invention is shown.
As shown in fig. 2, the apparatus includes:
the conversion module 21 is used for converting the acquired information of the photovoltaic output influence factors into weather type indexes;
The photovoltaic output prediction model construction module 22 is configured to construct a photovoltaic output prediction model based on the weather type index;
The power supply recovery model construction module 23 is configured to establish an objective function, and construct a power supply recovery model according to the photovoltaic output prediction model, the objective function and a preset constraint condition;
The power supply recovery scheme solving module 24 is configured to convert the power supply recovery model into a mixed integer second order cone planning model and solve the mixed integer second order cone planning model to obtain a power supply recovery scheme;
And the power supply recovery module 25 is used for recovering the electricity according to the power supply recovery scheme.
In an alternative embodiment, before the converting the obtained information of the photovoltaic output influencing factor into the weather type index, the method further includes:
initializing network parameters of a target power distribution network; the network parameters include branch numbers, head end node and tail end node numbers, line impedance and transformer transformation ratio of the line.
In an alternative embodiment, the power restoration model building module includes:
the objective function establishing unit is used for establishing an objective function which aims at maximizing load weighted power supply time and minimizing active loss of a system network;
The model construction unit is used for constructing a power supply recovery model according to the objective function and preset constraint conditions; the constraint conditions comprise limited energy constraint, photovoltaic output constraint, tide constraint, operation constraint and load state change constraint.
In an alternative embodiment, the conversion module comprises:
The data acquisition unit is used for acquiring information of the photovoltaic output influence factors and acquiring photovoltaic output data to be judged according to the information of the photovoltaic output influence factors;
the distance calculating unit is used for calculating Euclidean distance between the photovoltaic output data and the average photovoltaic output of each weather type;
the data conversion unit is used for obtaining the weather type corresponding to the photovoltaic output data according to the Euclidean distance;
and the index acquisition unit is used for obtaining a weather type index based on the photovoltaic power station historical data and the weather type.
In an alternative embodiment, the power recovery scheme solving module includes:
the convex constraint processing unit is used for performing convex constraint processing on a power flow equation in the power flow constraint and converting the power supply recovery model into a mixed integer second-order cone planning model;
and the model solving unit is used for solving the mixed integer second order cone planning model by utilizing Gurobi to obtain a power supply recovery scheme.
It should be noted that, the power supply recovery device for a power distribution network provided by the embodiment of the present invention can implement all the processes of the power supply recovery method for a power distribution network described in any embodiment, and the functions and implemented technical effects of each module and unit in the device are respectively the same as those of the power supply recovery method for a power distribution network described in the embodiment, and are not repeated herein.
In a third aspect, an embodiment of the present invention provides an electronic device, and referring to fig. 3, a schematic structural diagram of the electronic device provided in the embodiment of the present invention is shown.
As shown in fig. 3, the apparatus includes:
A memory 31 for storing a computer program;
A processor 32 for executing the computer program;
Wherein the processor 32 implements the power restoration method of the power distribution network according to any of the above embodiments when executing the computer program.
Illustratively, the computer program may be partitioned into one or more modules/units that are stored in the memory 31 and executed by the processor 32 to complete the present invention. The one or more modules/units may be a series of computer program instruction segments capable of performing the specified functions, which instruction segments are used for describing the execution of the computer program in the electronic device.
The Processor 32 may be a central processing unit (Central Processing Unit, CPU), but may also be other general purpose processors, digital signal processors (DIGITAL SIGNAL Processor, DSP), application SPECIFIC INTEGRATED Circuit (ASIC), field-Programmable gate array (Field-Programmable GATE ARRAY, FPGA) or other Programmable logic device, discrete gate or transistor logic device, discrete hardware components, or the like. A general purpose processor may be a microprocessor or the processor may be any conventional processor or the like.
The memory 31 may be used to store the computer program and/or module, and the processor 32 may implement various functions of the electronic device by running or executing the computer program and/or module stored in the memory 31 and invoking data stored in the memory 31. The memory 31 may mainly include a storage program area and a storage data area, wherein the storage program area may store an operating system, an application program (such as a sound playing function, an image playing function, etc.) required for at least one function, and the like; the storage data area may store data (such as audio data, phonebook, etc.) created according to the use of the handset, etc. In addition, the memory 31 may include high-speed random access memory, and may also include non-volatile memory, such as a hard disk, memory, plug-in hard disk, smart memory card (SMART MEDIA CARD, SMC), secure Digital (SD) card, flash memory card (FLASH CARD), at least one disk storage device, flash memory device, or other volatile solid-state storage device.
It should be noted that the above electronic device includes, but is not limited to, a processor, a memory, and those skilled in the art will understand that the schematic structural diagram of fig. 3 is merely an example of the above electronic device, and does not limit the electronic device, and may include more components than those illustrated, or some components may be combined, or different components may be combined.
In a fourth aspect, an embodiment of the present invention further provides a computer readable storage medium, where a computer program is stored, where the computer program is executed to implement the power supply restoration method of the power distribution network according to any one of the foregoing embodiments.
It should be understood that the implementation of all or part of the flow in the power restoration method of the power distribution network according to the present invention may also be implemented by instructing related hardware by a computer program, where the computer program may be stored in a computer readable storage medium, and the computer program may implement the steps of the power restoration method of the power distribution network when executed by a processor. Wherein the computer program comprises computer program code, which may be in the form of source code, object code, executable files or in some intermediate form, etc. The computer readable medium may include: any entity or device capable of carrying the computer program code, a recording medium, a U disk, a removable hard disk, a magnetic disk, an optical disk, a computer Memory, a Read-Only Memory (ROM), a random access Memory (RAM, random Access Memory), an electrical carrier signal, a telecommunications signal, a software distribution medium, and so forth. It should be noted that the content of the computer readable medium can be appropriately increased or decreased according to the requirements of the jurisdiction's jurisdiction and the patent practice, for example, in some jurisdictions, the computer readable medium does not include electrical carrier signals and telecommunication signals according to the jurisdiction and the patent practice.
While the invention has been described with reference to the preferred embodiments, it will be understood by those skilled in the art that various changes in form and detail may be made therein without departing from the spirit and scope of the invention as defined by the appended claims.
Claims (10)
1. A power restoration method for a power distribution network, comprising:
converting the obtained information of the photovoltaic output influence factors into weather type indexes;
building a photovoltaic output prediction model based on the weather type index;
establishing an objective function, and constructing a power supply recovery model according to the photovoltaic output prediction model, the objective function and preset constraint conditions;
Converting the power supply recovery model into a mixed integer second order cone planning model and solving to obtain a power supply recovery scheme;
And recovering electricity according to the power supply recovery scheme.
2. The method for recovering power from a power distribution network according to claim 1, wherein before converting the obtained information of the photovoltaic output influencing factor into the weather type index, further comprising:
initializing network parameters of a target power distribution network; the network parameters include branch numbers, head end node and tail end node numbers, line impedance and transformer transformation ratio of the line.
3. The method for recovering power from a power distribution network according to claim 1, wherein said converting the obtained information of the photovoltaic output influence factor into a weather type index comprises:
Acquiring information of photovoltaic output influence factors, and acquiring photovoltaic output data to be judged according to the information of the photovoltaic output influence factors;
calculating Euclidean distance between the photovoltaic output data and average photovoltaic output of each weather type;
Obtaining a weather type corresponding to the photovoltaic output data according to the Euclidean distance;
And obtaining a weather type index based on the photovoltaic power station historical data and the weather type.
4. The power restoration method of a power distribution network according to claim 1, wherein the establishing an objective function, and constructing a power restoration model according to the photovoltaic output prediction model, the objective function and a preset constraint condition, comprises:
establishing an objective function with the maximum load weighted power supply time and the minimum system network active loss as targets;
Constructing a power supply recovery model according to the photovoltaic output prediction model, the objective function and preset constraint conditions; the constraint conditions comprise limited energy constraint, photovoltaic output constraint, tide constraint, operation constraint and load state change constraint.
5. The power restoration method as set forth in claim 4, wherein the converting the power restoration model into a mixed integer second order cone planning model and solving to obtain a power restoration scheme includes:
performing convex constraint processing on a power flow equation in the power flow constraint, and converting the power supply recovery model into a mixed integer second-order cone planning model;
and solving the mixed integer second order cone planning model by utilizing Gurobi to obtain a power supply recovery scheme.
6. A power restoration device for a power distribution network, comprising:
the conversion module is used for converting the acquired information of the photovoltaic output influence factors into weather type indexes;
the photovoltaic output prediction model construction module is used for constructing a photovoltaic output prediction model based on the weather type index;
the power supply recovery model construction module is used for establishing an objective function and constructing a power supply recovery model according to the photovoltaic output prediction model, the objective function and preset constraint conditions;
the power supply recovery scheme solving module is used for converting the power supply recovery model into a mixed integer second order cone planning model and solving the mixed integer second order cone planning model to obtain a power supply recovery scheme;
and the power supply recovery module is used for recovering the electricity according to the power supply recovery scheme.
7. The power restoration device as recited in claim 6, wherein before said converting the obtained information of the photovoltaic output influencing factor into the weather-type index, further comprises:
initializing network parameters of a target power distribution network; the network parameters include branch numbers, head end node and tail end node numbers, line impedance and transformer transformation ratio of the line.
8. The power restoration device as recited in claim 6, wherein said converting the obtained information of the photovoltaic output influencing factor into the weather type index comprises:
Acquiring information of photovoltaic output influence factors, and acquiring photovoltaic output data to be judged according to the information of the photovoltaic output influence factors;
calculating Euclidean distance between the photovoltaic output data and average photovoltaic output of each weather type;
Obtaining a weather type corresponding to the photovoltaic output data according to the Euclidean distance;
And obtaining a weather type index based on the photovoltaic power station historical data and the weather type.
9. An electronic device, comprising:
A memory for storing a computer program;
a processor for executing the computer program;
Wherein the processor, when executing the computer program, implements a power restoration method for a power distribution network according to any one of claims 1 to 5.
10. A computer readable storage medium, characterized in that the computer readable storage medium stores a computer program which, when executed, implements the power restoration method of a power distribution network according to any one of claims 1 to 5.
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