CN114221351B - Voltage reactive power regulation method, device, terminal and storage medium - Google Patents

Voltage reactive power regulation method, device, terminal and storage medium Download PDF

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CN114221351B
CN114221351B CN202111583027.4A CN202111583027A CN114221351B CN 114221351 B CN114221351 B CN 114221351B CN 202111583027 A CN202111583027 A CN 202111583027A CN 114221351 B CN114221351 B CN 114221351B
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period
reactive power
reactive
cluster
power
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CN114221351A (en
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张孟琛
宣文华
高会民
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Qinhuangdao Power Supply Co of State Grid Jibei Electric Power Co Ltd
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Qinhuangdao Power Supply Co of State Grid Jibei Electric Power Co Ltd
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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
    • H02J3/12—Circuit arrangements for ac mains or ac distribution networks for adjusting voltage in ac networks by changing a characteristic of the network load
    • H02J3/16—Circuit arrangements for ac mains or ac distribution networks for adjusting voltage in ac networks by changing a characteristic of the network load by adjustment of reactive power
    • 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
    • H02J3/381—Dispersed generators
    • 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
    • H02J3/50—Controlling the sharing of the out-of-phase component
    • 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]
    • 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
    • H02J2300/00—Systems for supplying or distributing electric power characterised by decentralized, dispersed, or local generation
    • H02J2300/20—The dispersed energy generation being of renewable origin
    • H02J2300/22—The renewable source being solar energy
    • H02J2300/24—The renewable source being solar energy of photovoltaic origin
    • 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
    • H02J2300/00—Systems for supplying or distributing electric power characterised by decentralized, dispersed, or local generation
    • H02J2300/20—The dispersed energy generation being of renewable origin
    • H02J2300/28—The renewable source being wind energy
    • 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
    • H02J2300/00—Systems for supplying or distributing electric power characterised by decentralized, dispersed, or local generation
    • H02J2300/40—Systems for supplying or distributing electric power characterised by decentralized, dispersed, or local generation wherein a plurality of decentralised, dispersed or local energy generation technologies are operated simultaneously
    • Y—GENERAL TAGGING OF NEW TECHNOLOGICAL DEVELOPMENTS; GENERAL TAGGING OF CROSS-SECTIONAL TECHNOLOGIES SPANNING OVER SEVERAL SECTIONS OF THE IPC; TECHNICAL SUBJECTS COVERED BY FORMER USPC CROSS-REFERENCE ART COLLECTIONS [XRACs] AND DIGESTS
    • Y02—TECHNOLOGIES OR APPLICATIONS FOR MITIGATION OR ADAPTATION AGAINST CLIMATE CHANGE
    • Y02E—REDUCTION OF GREENHOUSE GAS [GHG] EMISSIONS, RELATED TO ENERGY GENERATION, TRANSMISSION OR DISTRIBUTION
    • Y02E10/00—Energy generation through renewable energy sources
    • Y02E10/50—Photovoltaic [PV] energy
    • Y02E10/56—Power conversion systems, e.g. maximum power point trackers
    • Y—GENERAL TAGGING OF NEW TECHNOLOGICAL DEVELOPMENTS; GENERAL TAGGING OF CROSS-SECTIONAL TECHNOLOGIES SPANNING OVER SEVERAL SECTIONS OF THE IPC; TECHNICAL SUBJECTS COVERED BY FORMER USPC CROSS-REFERENCE ART COLLECTIONS [XRACs] AND DIGESTS
    • Y02—TECHNOLOGIES OR APPLICATIONS FOR MITIGATION OR ADAPTATION AGAINST CLIMATE CHANGE
    • Y02E—REDUCTION OF GREENHOUSE GAS [GHG] EMISSIONS, RELATED TO ENERGY GENERATION, TRANSMISSION OR DISTRIBUTION
    • Y02E40/00—Technologies for an efficient electrical power generation, transmission or distribution
    • Y02E40/30—Reactive power compensation

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  • Power Engineering (AREA)
  • Supply And Distribution Of Alternating Current (AREA)

Abstract

The application provides a voltage reactive power regulation method, a device, a terminal and a storage medium. The method comprises the following steps: acquiring power grid data of each historical period of a power distribution network; determining an operation mode corresponding to each history period according to the power grid data of each history period; according to the corresponding operation mode of each history period, constructing a comprehensive evaluation objective function, a photovoltaic cluster reactive power output model and constraint conditions corresponding to each history period; and determining reactive power regulation schemes of all future time periods of the power distribution network according to the comprehensive evaluation objective function, the photovoltaic cluster reactive power output model, the constraint conditions and the preset solving algorithm corresponding to all the history time periods, so that the voltage of all nodes of the power distribution network in all the future time periods is not out of limit.

Description

Voltage reactive power regulation method, device, terminal and storage medium
Technical Field
The application relates to the technical field of harmonic wave management, in particular to a voltage reactive power regulation method, a device, a terminal and a storage medium.
Background
Passive distribution networks typically manage reactive power using an on-site balancing principle and regulate voltage by on-load voltage regulation of transformers and switching parallel capacitor banks. With the large-scale high-permeability access of the distributed power supply to the power distribution network, the randomness and uncertainty of the output of the distributed power supply are added with the characteristic of high resistance-inductance ratio of the distribution line, so that the voltage distribution of the power distribution network is complex, and the problem of voltage out-of-limit is outstanding. This new situation is not effectively solved by only relying on reactive in-situ balancing, and a more active and comprehensive voltage control strategy needs to be adopted. Therefore, a voltage reactive regulation method is needed.
Disclosure of Invention
In view of the above, the present application provides a voltage reactive power regulation method, device, terminal and storage medium, which can avoid the problem of voltage out-of-limit.
In order to achieve the above purpose, the present application mainly provides the following technical solutions:
in a first aspect, the present application provides a voltage reactive regulation method, the method comprising:
acquiring power grid data of each historical period of a power distribution network;
determining an operation mode corresponding to each history period according to the power grid data of each history period;
according to the corresponding operation mode of each history period, determining a comprehensive evaluation objective function, a photovoltaic cluster reactive power output model and constraint conditions corresponding to each history period;
and determining an optimal reactive power regulation scheme of each future period of the power distribution network according to the comprehensive evaluation objective function, the photovoltaic cluster reactive power output model, the constraint condition and a preset solving algorithm corresponding to each history period, so that the voltage of each node of the power distribution network in each future period is not out of limit.
In a second aspect, the present application provides a voltage reactive power regulating device comprising:
the acquisition unit is used for acquiring power grid data of each historical period of the power distribution network;
the first determining unit is used for determining an operation mode corresponding to each history period according to the power grid data of each history period;
The first construction unit is used for constructing a comprehensive evaluation objective function, a photovoltaic cluster reactive power output model and constraint conditions corresponding to each history period according to the corresponding operation mode of each history period;
the second determining unit is used for determining an optimal reactive power adjustment scheme of each future period of the power distribution network according to the comprehensive evaluation objective function, the photovoltaic cluster reactive power output model, the constraint condition and a preset solving algorithm corresponding to each history period, so that the voltage of each node of the power distribution network in each future period is not out of limit.
In a third aspect, the present application provides a terminal for running a program, where the terminal performs the voltage reactive regulation method according to the first aspect when running.
In a fourth aspect, the present application provides a storage medium, where the storage medium is configured to store a computer program, where the computer program when executed controls a device where the storage medium is located to perform the voltage reactive regulation method according to the first aspect.
By means of the technical scheme, the voltage reactive power regulation method, the device, the terminal and the storage medium are provided, and for a power distribution network, the change trend of power grid data of each historical period of the power distribution network is similar to the change trend of power grid data of a corresponding period of the power distribution network, so that the optimal reactive power equipment operation scheme of each future period of the power distribution network can be predicted according to the existing power grid data of each historical period, and further, the node voltage of the power distribution network in each future period is ensured not to be out of limit. In the process of predicting the optimal reactive power equipment operation scheme of each future period of the power distribution network, the operation mode is related to power, and the power is related to voltage, so that the optimal reactive power adjustment scheme of each future period of the power distribution network can be more accurately predicted according to the comprehensive evaluation objective function, the photovoltaic cluster reactive power output model and the constraint condition corresponding to each history period and constructed according to the corresponding operation mode of each history period, and the voltage of each node of each future period of the power distribution network is not out of limit.
The foregoing description is only an overview of the technical solutions of the present application, and may be implemented according to the content of the specification in order to make the technical means of the present application more clearly understood, and in order to make the above-mentioned and other objects, features and advantages of the present application more clearly understood, the following detailed description of the present application will be given.
Drawings
In order to more clearly illustrate the embodiments of the present application or the technical solutions in the prior art, the drawings that are required in the embodiments or the description of the prior art will be briefly described below, it being obvious that the drawings in the following description are only some embodiments of the present application, 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 a voltage reactive power regulation method disclosed in the present application;
FIG. 2 is a schematic flow chart of another voltage reactive regulation method disclosed in the present application;
fig. 3 is a schematic diagram of a network structure of a power distribution network disclosed in the present application;
FIG. 4a is a schematic diagram of wind power active power disclosed in the present application;
FIG. 4b is a schematic diagram of wind power active power disclosed in the present application;
FIG. 4c is a schematic diagram of wind power active power disclosed in the present application;
fig. 5 is a schematic structural diagram of a voltage reactive power adjusting device disclosed in the present application;
fig. 6 is a schematic structural diagram of another voltage reactive power regulating device disclosed in the present application.
Detailed Description
Exemplary embodiments of the present application will be described in more detail below with reference to the accompanying drawings. While exemplary embodiments of the present application are shown in the drawings, it should be understood that the present application may be embodied in various forms and should not be limited to the embodiments set forth herein. Rather, these embodiments are provided so that this disclosure will be thorough and complete, and will fully convey the scope of the disclosure to those skilled in the art.
In the related art, a passive power distribution network generally adopts an on-site balancing principle to manage reactive power, and performs voltage regulation by on-load voltage regulation of a transformer and switching of a parallel capacitor bank. With the large-scale high-permeability access of the distributed power supply to the power distribution network, the randomness and uncertainty of the output of the distributed power supply are added with the characteristic of high resistance-inductance ratio of the distribution line, so that the voltage distribution of the power distribution network is complex, and the problem of voltage out-of-limit is outstanding.
In order to solve the problem of the prominent voltage out-of-limit problem in the prior art, the embodiment of the application provides a flow diagram of a voltage reactive power regulation method, and specific implementation steps of the method are shown in fig. 1, including:
Step 101, acquiring power grid data of each historical period of a power distribution network.
The power grid data may include the number of nodes of the power distribution network, the number of nodes, the number of initial nodes of an existing line, the configuration capacity of related equipment of the power distribution network, the active power output by a certain cluster corresponding to each historical time period, the reactive power output by a certain cluster corresponding to each historical time period, the time-varying active power which can be generated by a photovoltaic cluster corresponding to each historical time period, and intelligent solving algorithm parameter settings. The intelligent solving algorithm parameters include parameters required by the nested particle swarm algorithm, such as c1 and c2 in the nested particle swarm algorithm.
In a specific embodiment of the step, grid data in a history time is obtained, and the history time is divided into a plurality of history time periods, so that the grid data of each history time period is obtained.
For example, the power grid data for the past 24 hours is acquired, and the power grid data for each past hour is obtained by dividing the day into 24 parts.
Step 102, determining an operation mode corresponding to each history period according to the power grid data of each history period.
In a specific embodiment of the present application, according to the grid data of each historical period, an operation mode corresponding to each historical period is determined, and the operation mode of the power distribution network of the period is set as an operation mode.
And step 103, constructing a comprehensive evaluation objective function, a photovoltaic cluster reactive power output model and constraint conditions corresponding to each history period according to the corresponding operation mode of each history period.
The comprehensive evaluation objective function is an evaluation index of the predicted reactive power regulation scheme, the photovoltaic cluster reactive power output model is used for adjusting data in the reactive power regulation scheme, and the constraint condition is used for constraining the data in the reactive power regulation scheme.
In the specific embodiment of the application, according to the corresponding operation mode of each history period, a comprehensive evaluation objective function, a photovoltaic cluster reactive power output model and constraint conditions corresponding to each history period are constructed.
And 104, determining an optimal reactive power regulation scheme of each future period of the power distribution network according to the comprehensive evaluation objective function, the photovoltaic cluster reactive power output model, the constraint condition and a preset solving algorithm corresponding to each history period, so that the voltage of each node of the power distribution network in each future period is not out of limit.
The reactive power equipment comprises equipment such as an optimal tap position of a transformer in a power distribution network, the number of capacitor switching groups, a distributed photovoltaic cluster reactive power operation mode, a photovoltaic inverter, a distributed double-fed induction fan, a static reactive power compensation device, a static reactive power generation device and the like.
In the embodiment of the application, for the power distribution network, the change trend of the power grid data of each historical period of the power distribution network is similar to the change trend of the power grid data of the corresponding period, so that the optimal reactive equipment operation scheme of each future period of the power distribution network can be predicted according to the existing power grid data of each historical period, and further, the node voltage of the power distribution network in each future period is ensured not to be out of limit. In the process of predicting the optimal reactive power equipment operation scheme of each future period of the power distribution network, the operation mode is related to power, and the power is related to voltage, so that the optimal reactive power adjustment scheme of each future period of the power distribution network can be more accurately predicted according to the comprehensive evaluation objective function, the photovoltaic cluster reactive power output model and the constraint condition corresponding to each history period and constructed according to the corresponding operation mode of each history period, and the voltage of each node of each future period of the power distribution network is not out of limit.
Meanwhile, in order to introduce the processes from step 101 to step 104, the embodiment of the present application further provides a flow chart of another voltage reactive power adjustment method, and the specific implementation steps of the flow chart are shown in fig. 2, including:
step 201, obtaining power grid data of each history period of a power distribution network.
In the specific implementation manner of the step, the distribution transformer area TTU is used as a terminal platform, the LVDPV accessed by the same area is used as a cluster, and cluster management and control are performed. The TTU acquires power grid data of each historical period.
It should be noted that this step is similar to step 101, and will not be described here again.
Step 202, determining an operation mode corresponding to each history period according to the power grid data of each history period.
There may be various modes of operation, such as constant reactive mode, reactive gradual mode, pure active mode. The operation mode corresponding to each history period may be one or a plurality of. For example, when the reactive power output by a certain cluster in the grid data of a certain historical period is 0, the running mode corresponding to the cluster in the historical period is a pure active mode. When the reactive power output by another cluster in the power grid data of the historical period is constant, the running mode corresponding to the cluster in the historical period is a constant reactive mode. When the reactive power output by another cluster in the power grid data of the historical period is variable, the running mode corresponding to the cluster in the historical period is a reactive gradual change mode.
In a specific embodiment of the step, the TTU obtains the power grid data of each history period and the output characteristics of each operation mode, determines the operation mode of each history period, and the operation mode of each history period is the LVDPV reactive operation mode of each history period, and solidifies the operation mode of each history period into the inverter controller. In this way, the inverter controller can set the running mode of the LVDPV cluster of the corresponding future period according to the running mode of each history period. For example, the operation mode of 24 hours is solidified into the inverter controller, when the operation mode of 1-2 points is the pure active mode, the operation mode of 1-2 points in the future can be set to the pure active mode, and then the LVDPV cluster works in the pure active mode when the current time is 1-2 points in the future.
When the operation mode includes a pure active mode, the output characteristic of the pure active mode is
Figure BDA0003426763760000061
Wherein P is DPV Representing active power, Q, of individual cluster outputs DPV Representing reactive power output by a single cluster, P (T) representing time-varying active power that the photovoltaic cluster can produce, and T representing the number of historical periods.
When the operation mode includes a constant reactive mode, the output characteristic of the constant reactive mode is
Figure BDA0003426763760000062
Wherein P is DPV Representing active power, Q, of individual cluster outputs DPV Representing reactive power output by a single cluster, lambda being a constant other than 0, P (T) representing time-varying active power that the photovoltaic cluster can produce, T representing the number of time periods.
When the operation mode includes a reactive gradation mode, the output characteristic of the reactive gradation mode is
Figure BDA0003426763760000063
Wherein P is DPV Representing active power, Q, of individual cluster outputs DPV Representing reactive power, Q, of individual cluster outputs f For the initial value of gradual change, a is the gradient slope, P (T) represents the time-varying active power which can be generated by the photovoltaic cluster, and T represents the period number.
And 203, constructing a comprehensive evaluation objective function, a photovoltaic cluster reactive power output model and constraint conditions corresponding to each history period according to the corresponding operation mode of each history period.
The photovoltaic cluster reactive power output model needs to be solved. And the comprehensive evaluation objective function is an evaluation index of the predicted reactive power regulation scheme. The constraint condition is used to constrain the data in the reactive power regulation scheme.
The photovoltaic cluster reactive power output model is as follows:
Figure BDA0003426763760000064
wherein P is LVDPV.i.t Active power output by photovoltaic cluster of node i in t time period, Q LVDPV.i.t Reactive power, P, output for photovoltaic clusters of node i of period t DPV.k.t Active power of the kth photovoltaic cluster, Q DPV.k.t Reactive power of the K photovoltaic cluster in the t time period, S is an operation mode S, omega adopted by the photovoltaic cluster DPV The method is characterized in that the method is used for collecting photovoltaic clusters, K is the Kth photovoltaic cluster in the photovoltaic cluster set, and N is used for collecting the photovoltaic clusters k (S) is whether the Kth photovoltaic cluster is operating in the operating mode S, wherein, when the Kth photovoltaic cluster is operating in the operating mode S, then N k (S) takes a value of 1, when the Kth photovoltaic cluster is not operated in the operation mode S, N k (s) has a value of 0.
The comprehensive evaluation objective function F is formed by a first objective function F aiming at the minimum voltage deviation of the nodes of the power distribution network 1 And a second objective function F targeting the minimum of the total period loss of the distribution network 2 Composition, specifically, comprehensive evaluation objective function F is
F＝αF 1 +(1-α)F 2 ；
Figure BDA0003426763760000071
Figure BDA0003426763760000072
Figure BDA0003426763760000073
Figure BDA0003426763760000074
Figure BDA0003426763760000075
Wherein alpha is a preset weight, P loss,i,t To the network loss of the node i in the t-th period, P j.t Active power flowing in for node j of the t-th period, Q j.t Reactive power flowing in for the t-th period node j; u (U) i For the node voltage of node i, U j Node voltage, delta, for node j j Voltage angle, delta of grid node j i For the voltage angle of the grid node i, gamma ij U is the feeder resistance between node i and node j i.t A median value in a voltage interval of a node i in a t-th period; u (U) 0 N is the number of nodes of the system, and m is the number of time periods.
The constraint conditions comprise power flow balance equation constraint, control variable constraint, action frequency constraint, power distribution network voltage interval constraint, reactive power output constraint of the distributed doubly-fed induction wind turbine, reactive power output constraint of the photovoltaic inverter and low-voltage photovoltaic cluster operation constraint.
Wherein, the power distribution network load flow balance equation is constrained as follows
Figure BDA0003426763760000081
Figure BDA0003426763760000082
Wherein P is i.t Active power, Q, injected for node i of the t-th period i.t Reactive power, P, injected for node i of period t G.i.t Active power injected into node i for power distribution network in t-th period, Q G.i.t Reactive power, P, respectively injected into node i for the power distribution network at the t-th period PV.i.t For the active power output by the photovoltaic power station at the node i of the t-th period, Q PV.i.t For the reactive power output by the photovoltaic power station at the node i of the t-th period, P DFIG.i.t For output of wind turbine at node i of the t-th periodActive power, Q DFIG.i.t For the reactive power output by the wind turbine generator set at the node i of the t-th period, Q SCB.i.t For the switching capacity of the reactive compensation capacitor group at the node i of the t-th period, Q SVC.i.t For the switching capacity of the reactive compensation capacitor group at the node i of the t-th period, P L.i.t For active power consumed by load at node i of the t-th period, Q L.i.t For reactive power consumed by the load at node i of the t-th period, U i.t For the voltage of the node i of the t-th period, U jt For the voltage of the node j of the t-th period, G ij B is the conductance between node i and node j ij For susceptances between node i and node j, θ ij Is U (U) i.t And U jt Phase difference, P LVDPV.i.t Active power for photovoltaic reactive contribution clusters at node i of the t-th period, Q LVDPV.i.t Reactive power for the low voltage photovoltaic reactive contribution cluster at period node i.
The control variable constraint conditions comprise transformer constraint, switching parallel capacitor bank constraint, static reactive power compensation device constraint and static reactive power generation device constraint, and are respectively as follows:
Figure BDA0003426763760000083
T t ＝1+K t ×ΔT；
Figure BDA0003426763760000084
in which Q SVC.i.min The lower limit of the output reactive power of the static reactive power compensation device connected with the node i of the t time period is Q SVC.i.max Outputting an upper limit of reactive power, Q, for a static reactive power compensation device connected to a t-th period node i SVG.i.min The lower limit of the output reactive power of the static reactive power compensation device connected with the node i of the t time period is Q SVG.i.max Outputting an upper limit of reactive power, Q, for a static reactive power compensation device connected to a t-th period node i SVG.i Connected for node iThe static reactive power compensation device outputs reactive power, K max For maximum value, K of tap position of on-load voltage-regulating transformer min For minimum value, K of tap position of on-load voltage-regulating transformer t For tap position of on-load voltage-regulating transformer in T-th period, T t For the transformer transformation ratio in the T-th period, deltaT is the unit adjustment quantity of the tap of the on-load voltage regulating transformer, N Cmax Maximum switching group number N of reactive compensation capacitor C.t For the number of reactive compensation capacitor switching groups in the t-th period,
Figure BDA0003426763760000091
switching capacity, q for reactive compensation capacitor bank in the t-th period C And switching capacity for a single group of reactive compensation capacitors.
The action times constraint is the constraint of the adjustment times of the on-load voltage regulating transformer and the reactive compensation capacitor, and the constraint condition to be satisfied is that
Figure BDA0003426763760000092
|K l,t3+1 -K l,t3 |≤L l1 ；
Figure BDA0003426763760000093
Wherein K is l,t The operation frequency of the tap of the on-load voltage regulating transformer at the t-th time is C k,t The switching times of the reactive compensation capacitor group at the t-th moment,
Figure BDA0003426763760000094
l is exclusive OR logic sign l For the maximum allowable action times of tap position of on-load voltage regulating transformer, L l1 For maximum adjustment gear number, L, of adjacent period of tap of on-load voltage regulating transformer k And (5) the maximum allowable switching times of the reactive compensation capacitor bank are obtained.
The voltage interval constraint of the power distribution network is that
Figure BDA0003426763760000095
In U min To meet the minimum voltage of the operation requirement, U max To meet the maximum voltage of the operating requirement, [ U ] i.t ]Is the voltage amplitude interval of the node i of the t-th period.
The reactive power output constraint of the distributed doubly-fed induction wind turbine is as follows
Figure BDA0003426763760000096
In which Q DFIG.max Maximum reactive power output by the wind turbine generator system, Q DFIG.min Minimum reactive power output by the wind turbine generator system, Q s,max Maximum reactive power output by the stator side of the wind turbine generator set, Q s,min Minimum reactive power output by stator side of wind turbine generator set, Q c,max Maximum reactive power output by grid-side converter of wind turbine generator, Q c,min And outputting the minimum reactive power for the grid-side converter of the wind turbine.
The reactive output constraint of the photovoltaic inverter is that
Figure BDA0003426763760000097
In which Q PV.max For maximum reactive power output by inverter, Q PV.min For minimum reactive power output by inverter, P PV Is the active power of the photovoltaic inverter, S PV The capacity of the photovoltaic inverter is about 1.0 to 1.1 times of the rated active capacity of the photovoltaic inverter.
The low-voltage photovoltaic cluster operation constraint is that
Figure BDA0003426763760000101
In the method, in the process of the invention,
Figure BDA0003426763760000102
for the remaining capacity of the kth photovoltaic cluster in run mode S, Q DPV.k.t Reactive power for the kth photovoltaic cluster for the tth period.
For different operation modes, the constructed comprehensive evaluation objective functions are generally the same, and the reactive power output model and the constraint conditions of the photovoltaic cluster are different. For example, for a pure active model, S in the constructed photovoltaic cluster reactive power output model is the pure active model adopted by the photovoltaic cluster, N k (s) is whether the Kth photovoltaic cluster operates in the pure active mode, when the Kth photovoltaic cluster operates in the pure active mode, N k (s) takes a value of 1, when the Kth photovoltaic cluster is not operating in the pure active mode, N k (s) has a value of 0. In built low-voltage photovoltaic cluster operation constraints
Figure BDA0003426763760000103
The remaining capacity of the kth photovoltaic cluster in the pure active mode.
And 204, constructing a reactive equipment operation scheme set of each history period according to the power grid data of each history period.
The reactive power installation operating scheme comprises at least one operating state of the reactive power installation, which is used for adjusting the network data. Reactive equipment in the embodiment of the application comprises equipment such as a transformer, a capacitor and an LVDPV reactive photovoltaic inverter. The operation scheme of the reactive equipment comprises the action time of the transformer, the action time of the capacitor and the like. The operation time of the transformer and the operation time of the capacitor in the reactive power equipment operation scheme are obtained based on an optimal division method. In dynamic reactive power optimization, the action sequences of the on-load voltage regulation and switching parallel capacitor bank of the transformer can be regarded as a sample sequence of ordered clustering, the maximum allowable action times are the optimal dividing number, and the action time is the optimal dividing point.
The following describes the optimal segmentation: the objective function of the optimal segmentation method is that the sum of the squares of the dispersion of the segments is minimum, and the valueThe smaller the internal difference of each segment is, the smaller the internal difference is. Sequence { x ] consisting of n ordered samples 1 ,x 2 ,L,x n Divided into k segments, in common
Figure BDA0003426763760000104
A scheme. Each scheme is denoted b [ (n, k); (i) 1 ,i 2 ,L,i k )]Wherein i is k Represents the kth division point, division scheme b [ (n, k); (i) 1 ,i 2 ,L,i k )]The corresponding objective function is
Figure BDA0003426763760000105
Wherein D (i) a ,i a+1 -1) represents the sum of squares of the deviations of the a-th segment; i.e a Is the a-th division point and has
Figure BDA0003426763760000106
In the method, in the process of the invention,
Figure BDA0003426763760000107
for the sample mean of section a, +.>
Figure BDA0003426763760000108
Has the following relation
Figure BDA0003426763760000111
In all schemes b [ (n, k); (i) 1 ,i 2 ,L,i k )]There must be an optimal segmentation to minimize the objective function value, and the optimal segmentation is recorded as
Figure BDA0003426763760000112
Or simply b * (n, k), since the objective function of the optimal segmentation is the least sum of the squares of the dispersion of the segments, the optimal k segments b * (n, k) is necessarily +.>
Figure BDA0003426763760000113
Is +.1 division ≡>
Figure BDA0003426763760000114
Adding a section +.>
Figure BDA0003426763760000115
Composition is prepared. By analogy, the optimal 2-partition b from m samples can be obtained * Optimal k-segmentation b of (m, 2) to n samples * The recurrence formula of (n, k) is
L{b * [(m,2)]＝min{D(1,j-1)+D(j,n)},2≤m≤n；
Figure BDA0003426763760000116
The specific solution process for the optimal k-segmentation is as follows.
Step one, let i=1, l, n-1, j=i+1, l, n calculate D (i, j) respectively.
Step two, according to b * A recursive formula of (m, 2), let m=2, l, n, calculates the optimal 2-partition b of m samples, respectively * (m,2)。
Step three, according to b * The recursive formula of (n, k) calculates the optimal 3-partition b of m samples, respectively * (m, 3) (m=3, l, n), the optimal 4-split b * (m, 4) (m=4, l, n), and so on until the optimal k-1 partition b * (m,k-1)(m＝k-1,L,n)。
Step four, determining the optimal k segmentation b of n samples * (n, k) segmentation points. First, the kth segmentation point is determined
Figure BDA0003426763760000117
Make it meet
Figure BDA0003426763760000118
Then find the k-1 th scoreCutting point
Figure BDA0003426763760000119
Make it meet
Figure BDA00034267637600001110
And so on, all the optimal segmentation points can be obtained
Figure BDA00034267637600001111
The reactive power equipment operation scheme in the embodiment of the application is obtained by firstly determining the action time and gear of a transformer, then optimizing the action time of a capacitor bank, and finally optimizing the number of switching banks of the capacitor bank and the reactive power output power of other reactive power resources as control variables. Thus, the action time of the transformer and the action time of the capacitor group are not identical.
Step 205, for each historical period, determining an optimal reactive power adjustment scheme in the reactive power equipment operation scheme set according to the comprehensive evaluation objective function, the photovoltaic cluster reactive power output model and the constraint condition.
The preset solving algorithm may be a nested particle swarm algorithm, or may be another optimization algorithm, which is not limited herein.
In the specific implementation mode of the step, each scheme is taken as a particle for each historical period, and an optimal reactive power regulation scheme is determined in a reactive power equipment operation scheme set by using a nested particle swarm algorithm according to a comprehensive evaluation objective function, a photovoltaic cluster reactive power output model and constraint conditions.
Specifically, the comprehensive evaluation objective function is an evaluation index, the photovoltaic cluster reactive power output model is the subjective change amount in the operation scheme, and the constraint conditions represent some objective criteria in operation. According to the photovoltaic cluster reactive power output model, the running state of the photovoltaic cluster reactive power equipment (and some other reactive power compensation equipment) is changed, and according to the objective function as an evaluation index, the constraint condition as a light-control criterion and the nested particle swarm algorithm, the optimal reactive power adjustment scheme is selected.
For example, the photovoltaic cluster reactive power output model is solved by adopting a push-forward substitution power flow calculation nested LinWPSO algorithm, and an optimal reactive power adjustment scheme is obtained. The specific solving steps are as follows:
(1) And calculating the initial value of the injection current of each node according to the distributed power supply and the load output power of the power distribution network.
(2) And obtaining the voltage value of each node of the power distribution network according to the injection current value of each node.
When the voltage value is calculated, starting from the tail end of a line according to kirchhoff current law, sequentially calculating to obtain a head end current value by using the initial value of each node current, and then updating the tail end voltage value of each branch by using the head end voltage and the line current, and sequentially calculating to obtain the voltage value of each node of the power distribution network.
(3) And carrying out iterative calculation on the output voltage interval value according to the voltage value of each node.
The iteration convergence criterion is that the deviation between the upper and lower boundary values of each node voltage interval and the last iteration result is smaller than the allowable value. If the convergence is carried out, the circulation is carried out, and the obtained voltage interval value is output; if not, repeating the step (2) until the following formula is satisfied;
|(U i ) k -(U i ) k-1 |<η
wherein η is the allowable error value; k is the number of iterations.
(4) And (5) embedding the voltage interval value into a nested particle swarm algorithm for random position and speed initialization.
The initialization comprises randomly generating the tap gear of the transformer and the number of switching groups of the capacitor, outputting active power by the side light and wind turbine generator at 10kV in each time period of the next day, injecting active power and reactive power into the power distribution network, outputting reactive power by the static reactive power compensation device and the static reactive power generation device, and distributing active power and load active power and reactive power initial population of the photovoltaic cluster.
The above-described process of randomly generating data substantially corresponds to step 204, i.e. substantially generating a plurality of reactive device operating scenarios from the grid data for each historical period and forming a reactive device operating scenario set.
(5) And carrying out iterative calculation according to the initialized values of the random position and the speed and the randomly generated population individuals.
Substituting randomly generated population individuals and the quantity obtained in the step (4) into the steps (1) - (3) to calculate the voltage interval value of each node, and selecting the minimum sum of the median value of each node voltage interval and the deviation of the voltage rated value as the fitness function.
(6) And respectively comparing the fitness function with the values corresponding to the individual historical optimal position and the global optimal position, finding out an optimal value, updating the position, the speed and the inertia weight of the particles, and performing forward push back substitution flow calculation again to obtain the fitness value of each particle.
(7) And (5) judging whether the maximum iteration times or the global optimal position are reached to meet constraint conditions, if so, outputting an optimal variable value (namely an optimal reactive power regulation scheme), otherwise, returning to the step (5).
The implementation of the present scheme is described below in a specific example.
Fig. 3 is a schematic diagram of a 31-node power distribution network and a node number in a certain area. Wherein 31 nodes are shared in the system, and W represents a wind turbine generator; PV represents distributed photovoltaic; q represents a low voltage photovoltaic cluster; c is a switching capacitor; and a static var compensator and a static var generator. The voltage grade of the distribution network is 110kV/10kV/380V, wherein the distribution network comprises a 110kV/10kV on-load voltage regulating transformer, the regulating range is 1+/-4 multiplied by 1.25 percent, 9 regulating gears such as-4, -3, … 3,4 and the like are arranged, the unit regulating quantity is 1.25 percent, and the maximum allowable action times per day is 4; the node 17 is connected with a reactive compensation capacitor 6 group, and the maximum allowable action times per day is 6; the node 29 is connected to a photovoltaic power station, and 1 static reactive power compensation device is arranged in the station; the node 22 is connected with a wind power plant, and 1 static var generator is connected in the wind power plant; the 380V side 12, 19, 26, and 30 block nodes aggregate 4 groups of low voltage photovoltaic clusters Q. And the first table is used for configuring rated capacity and intelligent solving algorithm parameter setting capacity for power distribution network related equipment. The rated capacities of the same equipment except the photovoltaic clusters are the same.
List one
Figure BDA0003426763760000131
Figure BDA0003426763760000141
The method selects a typical solar-wind-light characteristic curve and a load electricity-using curve of certain city of Hebei province as original data, wherein the wind-light characteristic curve and the load electricity-using curve are shown in figures 4a-4 b. And solving by adopting the algorithm for calculating the nested particle swarm optimization of the forward push back substitution tide provided by the application, so as to obtain the voltage amplitude condition of each period.
When the PV is connected into the power distribution network to perform power flow calculation, due to the continuous increase of the output power of the photovoltaic, voltage out-of-limit occurs in the period, and out-of-limit nodes are distributed between the nodes 13 and 18. The inverter cannot adjust the voltage of each node to a pass interval. Other voltage regulation means are therefore required to cooperate to regulate the voltage.
By adopting the power distribution network voltage reactive power optimization model provided by the application, the optimal tap position adjustment of the transformer in 24 time periods, the optimal switching group number of the reactive power compensation capacitors, the distributed power supply, the static reactive power compensation device of the station thereof, the optimal reactive power output value of the static reactive power generation device and the optimal operation mode of the photovoltaic cluster are obtained. And the second table is the action regulation result of the on-load voltage regulation and switching parallel capacitor bank of the transformer in one day. And the third table is the configuration result of the 10KV side reactive power equipment at 11-16 hours. And the fourth table is the configuration result of the reactive power operation mode of the photovoltaic cluster at 11-16 hours.
Watch II
Figure BDA0003426763760000142
Figure BDA0003426763760000151
Watch III
Figure BDA0003426763760000152
Table four
Figure BDA0003426763760000153
From the analysis of the results, the reactive power is discharged in 16 time periods to support the voltage of the power distribution network. The capacitor bank is operated at the 2 nd, 6 th, 17 th, 20 th and 24 th periods, respectively, while the on-load tap changing transformer is operated at the 4 th, 12 th, 14 th, 20 th and 24 th periods, respectively. Therefore, the voltage regulating equipment fully meets the action frequency limit set herein, and the on-load voltage regulating transformer and the reactive compensation capacitor bank can not act in the same period, so that the respective voltage regulating capability is greatly exerted. The 10kV side photovoltaic, wind turbine generator, static reactive compensation device and static reactive generation device in the station, and 380V side distributed photovoltaic cluster reactive operation mode all realize participation in reactive optimization of the power distribution network, exert reactive power adjustment capability of the power distribution network respectively, and guarantee optimal voltage operation level of the power distribution network. The dynamic optimization is an optimization adjustment which is adopted by considering the actual running condition of the power distribution network system, and the optimal result of each period can be realized although the optimal result of each period cannot be ensured.
As shown in table five, the results are compared for each model optimization. The reactive power optimization coordination model provided by the application is compared with the results of the optimization method before the optimization and only considering the reactive power adjustment of the distributed power supply. The method provided by the application is superior to other two methods in the aspect of controlling the voltage operation level of the power distribution network and the network loss.
TABLE five
Figure BDA0003426763760000161
Further, as an implementation of the method embodiments shown in fig. 1 and 3, the embodiments of the present application provide a voltage reactive power adjustment device, which can avoid that node voltages of a power distribution network in each future period do not exceed a limit. The embodiment of the device corresponds to the foregoing method embodiment, and for convenience of reading, details of the foregoing method embodiment are not described one by one in this embodiment, but it should be clear that the device in this embodiment can correspondingly implement all the details of the foregoing method embodiment. As shown in fig. 5, the apparatus includes:
an obtaining unit 501, configured to obtain grid data of each history period of the power distribution network;
a first determining unit 502, configured to determine an operation mode corresponding to each history period according to the grid data of each history period;
a construction unit 503, configured to construct a comprehensive evaluation objective function, a photovoltaic cluster reactive power output model and constraint conditions corresponding to each history period according to the corresponding operation mode of each history period;
the second determining unit 504 is configured to determine a reactive power adjustment scheme of each future period of the power distribution network according to the comprehensive evaluation objective function, the photovoltaic cluster reactive power output model, the constraint condition and a preset solving algorithm corresponding to each history period, so that each node voltage of the power distribution network in each future period is not out of limit.
Further, the operation mode includes a pure active mode, and the output characteristic of the pure active mode is that
Figure BDA0003426763760000162
Wherein P is DPV Representing active power, Q, of individual cluster outputs DPV Representing reactive power output by a single cluster, P (T) representing time-varying active power that the photovoltaic cluster can produce, and T representing the number of historical periods.
Further, the operation mode comprises a constant reactive mode, and the output characteristic of the constant reactive mode is that
Figure BDA0003426763760000171
Wherein P is DPV Representing active power, Q, of individual cluster outputs DPV Representing reactive power output by a single cluster, lambda being a constant other than 0, P (T) representing time-varying active power that the photovoltaic cluster can produce, T representing the number of time periods.
Further, the operation mode comprises a reactive power gradual change mode, and the output characteristic of the reactive power gradual change mode is that
Figure BDA0003426763760000172
Wherein P is DPV Representing active power, Q, of individual cluster outputs DPV Representing reactive power output by a single cluster, wherein a is a constant, P (T) represents time-varying active power which can be generated by the photovoltaic cluster, and T represents the number of time periods.
Further, the photovoltaic cluster reactive power output model is as follows
Figure BDA0003426763760000173
Wherein P is LVDPV.i.t Active power, Q, output for photovoltaic cluster of node i at time period t LVDPV.i.t Reactive power, P, output for photovoltaic clusters of node i of period t DPV.k.t Active power of the kth photovoltaic cluster, Q DPV.k.t Reactive power for the kth photovoltaic cluster for the tth period; s is the operation mode S, omega adopted by the photovoltaic cluster DPV The method is characterized in that the method is used for collecting photovoltaic clusters, K is the Kth photovoltaic cluster in the photovoltaic cluster set, and N is used for collecting the photovoltaic clusters k (S) is whether the Kth photovoltaic cluster is operating in the operating mode S, wherein, when the Kth photovoltaic cluster is operating in the operating mode S, then N k (S) takes a value of 1, when the Kth photovoltaic cluster is not operated in the operation mode S, N k (s) has a value of 0.
Further, the constraint conditions comprise a power distribution network load flow balance equation constraint, a control variable constraint, an action frequency constraint, a power distribution network voltage interval constraint, a distributed doubly-fed induction wind turbine reactive power constraint, a photovoltaic inverter reactive power constraint and a low-voltage photovoltaic cluster operation constraint.
Further, as shown in fig. 6, the apparatus further includes:
a second construction module 505, configured to construct a reactive equipment operation scheme set of each history period according to the grid data of each history period;
the second determining unit 504 is further configured to determine, for each historical period, an optimal reactive power adjustment scheme from the reactive power equipment operation scheme set according to the comprehensive evaluation objective function, the photovoltaic cluster reactive power output model, the constraint condition and a preset solution algorithm.
Further, the embodiment of the application also provides a processor, which is used for running a program, wherein the program executes the voltage reactive power regulation method described in the above figures 1-4.
Further, an embodiment of the present application further provides a storage medium, where the storage medium is configured to store a computer program, where the computer program controls, when running, a device where the storage medium is located to execute the voltage reactive power regulation method described in fig. 1 to 4.
In the foregoing embodiments, the descriptions of the embodiments are emphasized, and for parts of one embodiment that are not described in detail, reference may be made to related descriptions of other embodiments.
It will be appreciated that the relevant features of the methods and apparatus described above may be referenced to one another. In addition, the "first", "second", and the like in the above embodiments are for distinguishing the embodiments, and do not represent the merits and merits of the embodiments.
It will be clearly understood by those skilled in the art that, for convenience and brevity of description, specific working procedures of the above-described systems, apparatuses and units may refer to corresponding procedures in the foregoing method embodiments, which are not described in detail herein.
The algorithms and displays presented herein are not inherently related to any particular computer, virtual system, or other apparatus. Various general-purpose systems may also be used with the teachings herein. The required structure for a construction of such a system is apparent from the description above. In addition, the present application is not directed to any particular programming language. It will be appreciated that a variety of programming languages may be used to implement the teachings of the present application as described herein, and the above description of specific languages is provided for disclosure of preferred embodiments of the present application.
Furthermore, the memory may include volatile memory, random Access Memory (RAM) and/or nonvolatile memory, such as Read Only Memory (ROM) or flash memory (flash RAM), in a computer readable medium, the memory including at least one memory chip.
It will be appreciated by those skilled in the art that embodiments of the present application may be provided as a method, system, or computer program product. Accordingly, the present application may take the form of an entirely hardware embodiment, an entirely software embodiment, or an embodiment combining software and hardware aspects. Furthermore, the present application may take the form of a computer program product embodied on one or more computer-usable storage media (including, but not limited to, disk storage, CD-ROM, optical storage, and the like) having computer-usable program code embodied therein.
The present application is described with reference to flowchart illustrations and/or block diagrams of methods, apparatus (systems) and computer program products according to embodiments of the application. It will be understood that each flow and/or block of the flowchart illustrations and/or block diagrams, and combinations of flows and/or blocks in the flowchart illustrations and/or block diagrams, can be implemented by computer program instructions. These computer program instructions may be provided to a processor of a general purpose computer, special purpose computer, embedded processor, or other programmable data processing apparatus to produce a machine, such that the instructions, which execute via the processor of the computer or other programmable data processing apparatus, create means for implementing the functions specified in the flowchart flow or flows and/or block diagram block or blocks.
These computer program instructions may also be stored in a computer-readable memory that can direct a computer or other programmable data processing apparatus to function in a particular manner, such that the instructions stored in the computer-readable memory produce an article of manufacture including instruction means which implement the function specified in the flowchart flow or flows and/or block diagram block or blocks.
These computer program instructions may also be loaded onto a computer or other programmable data processing apparatus to cause a series of operational steps to be performed on the computer or other programmable apparatus to produce a computer implemented process such that the instructions which execute on the computer or other programmable apparatus provide steps for implementing the functions specified in the flowchart flow or flows and/or block diagram block or blocks.
In one typical configuration, a computing device includes one or more processors (CPUs), input/output interfaces, network interfaces, and memory.
The memory may include volatile memory in a computer-readable medium, random Access Memory (RAM) and/or nonvolatile memory, etc., such as Read Only Memory (ROM) or flash RAM. Memory is an example of a computer-readable medium.
Computer readable media, including both non-transitory and non-transitory, removable and non-removable media, may implement information storage by any method or technology. The information may be computer readable instructions, data structures, modules of a program, or other data. Examples of storage media for a computer include, but are not limited to, phase change memory (PRAM), static Random Access Memory (SRAM), dynamic Random Access Memory (DRAM), other types of Random Access Memory (RAM), read Only Memory (ROM), electrically Erasable Programmable Read Only Memory (EEPROM), flash memory or other memory technology, compact disc read only memory (CD-ROM), digital Versatile Discs (DVD) or other optical storage, magnetic cassettes, magnetic tape magnetic disk storage or other magnetic storage devices, or any other non-transmission medium, which can be used to store information that can be accessed by a computing device. Computer-readable media, as defined herein, does not include transitory computer-readable media (transmission media), such as modulated data signals and carrier waves.
It should also be noted that the terms "comprises," "comprising," or any other variation thereof, are intended to cover a non-exclusive inclusion, such that a process, method, article, or 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 apparatus. Without further limitation, an element defined by the phrase "comprising one … …" does not exclude the presence of other like elements in a process, method, article or apparatus that comprises an element.
It will be appreciated by those skilled in the art that embodiments of the present application may be provided as a method, system, or computer program product. Accordingly, the present application may take the form of an entirely hardware embodiment, an entirely software embodiment or an embodiment combining software and hardware aspects. Furthermore, the present application may take the form of a computer program product embodied on one or more computer-usable storage media (including, but not limited to, disk storage, CD-ROM, optical storage, and the like) having computer-usable program code embodied therein.
The foregoing is merely exemplary of the present application and is not intended to limit the present application. Various modifications and changes may be made to the present application by those skilled in the art. Any modifications, equivalent substitutions, improvements, etc. which are within the spirit and principles of the present application are intended to be included within the scope of the claims of the present application.

Claims (9)

1. A method of reactive voltage regulation, the method comprising:
acquiring power grid data of each historical period of a power distribution network, wherein the power grid data comprises node numbers of the power distribution network, node numbers, initial node numbers of existing lines, configuration capacity of related equipment of the power distribution network, active power output by a certain cluster corresponding to each historical period, reactive power output by a certain cluster corresponding to each historical period, time-varying active power which can be generated by a photovoltaic cluster corresponding to each historical period and intelligent solving algorithm parameter settings;
determining a photovoltaic cluster operation mode corresponding to each history period according to the power grid data of each history period;
according to the photovoltaic cluster operation mode corresponding to each history period, determining a comprehensive evaluation objective function, a photovoltaic cluster reactive power output model and constraint conditions corresponding to each history period;
according to the comprehensive evaluation objective function, the photovoltaic cluster reactive power output model, the constraint condition and the preset solving algorithm corresponding to each historical period, determining an optimal reactive power adjustment scheme of each future period of the power distribution network, and further enabling the voltage of each node of the power distribution network in each future period not to exceed the limit;
The method further comprises the steps of:
according to the power grid data of each history period, constructing a reactive equipment operation scheme set of each history period;
the method for determining the optimal reactive power regulation scheme of each future period of the power distribution network according to the comprehensive evaluation objective function, the photovoltaic cluster reactive power output model, the constraint condition and the preset solving algorithm corresponding to each historical period comprises the following steps:
and for each historical period, determining an optimal reactive power regulation scheme in the reactive power equipment operation scheme set according to the comprehensive evaluation objective function, the photovoltaic cluster reactive power output model, the constraint condition and a preset solving algorithm.
2. The method of claim 1, wherein the operating mode comprises a pure active mode having an output characteristic of
Figure QLYQS_1
；
Wherein P is DPV Representing the active power output by a single cluster,
Figure QLYQS_2
representing reactive power output by a single cluster, P (T) representing time-varying active power that the photovoltaic cluster can produce, and T representing the number of historical periods.
3. The method of claim 1, wherein the operating mode comprises a constant reactive mode, the output characteristic of the constant reactive mode being
Figure QLYQS_3
In the method, in the process of the invention,
Figure QLYQS_4
active power representing single cluster output, +. >
Figure QLYQS_5
Reactive power representing the output of a single cluster, +.>
Figure QLYQS_6
Is a constant other than 0, < >>
Figure QLYQS_7
Representing the time-varying active power that the photovoltaic cluster can produce, T representing the number of time periods.
4. The method of claim 1, wherein the operating mode comprises a reactive taper mode, an output characteristic of the reactive taper mode being
Figure QLYQS_8
In the method, in the process of the invention,
Figure QLYQS_9
active power representing single cluster output, +.>
Figure QLYQS_10
Reactive power, a being a constant, < > representing the output of a single cluster>
Figure QLYQS_11
Representing the time-varying active power that the photovoltaic cluster can produce, T representing the number of time periods.
5. The method of claim 1, wherein the photovoltaic cluster reactive power output model is
Figure QLYQS_12
In the method, in the process of the invention,
Figure QLYQS_14
active power output for photovoltaic cluster of node i of the t-th period, +.>
Figure QLYQS_16
Reactive power output for photovoltaic cluster of node i of the t-th period, +.>
Figure QLYQS_17
Active power of the kth photovoltaic cluster for the t-th period,/th>
Figure QLYQS_15
Reactive power for the kth photovoltaic cluster for the tth period; s is the operating mode S used by the photovoltaic cluster, < >>
Figure QLYQS_18
K is the Kth photovoltaic cluster in the photovoltaic cluster set, and the K is the +.>
Figure QLYQS_19
For whether the kth photovoltaic cluster is operating in the operating mode S, wherein, when the kth photovoltaic cluster is operating in the operating mode S, +. >
Figure QLYQS_20
The value is 1, when the Kth photovoltaic cluster does not operate in the operation mode S/>
Figure QLYQS_13
The value is 0.
6. The method of claim 1, wherein the constraint conditions include a power distribution network load flow balance equation constraint, a control variable constraint, a number of actions constraint, a power distribution network voltage interval constraint, a distributed doubly-fed induction wind turbine reactive power output constraint, a photovoltaic inverter reactive power output constraint, and a photovoltaic cluster operation constraint.
7. A voltage reactive power regulating device, the device comprising:
the system comprises an acquisition unit, a calculation unit and an intelligent solving algorithm parameter setting unit, wherein the acquisition unit is used for acquiring power grid data of each historical period of a power distribution network, wherein the power grid data comprises the node number, the starting node number of an existing line, the configuration capacity of related equipment of the power distribution network, the active power output by a certain cluster corresponding to each historical period, the reactive power output by a certain cluster corresponding to each historical period, the time-varying active power which can be generated by a photovoltaic cluster corresponding to each historical period;
the first determining unit is used for determining a photovoltaic cluster operation mode corresponding to each history period according to the power grid data of each history period;
The first construction unit is used for constructing a comprehensive evaluation objective function, a photovoltaic cluster reactive power output model and constraint conditions corresponding to each history period according to the photovoltaic cluster operation mode corresponding to each history period;
the second determining unit is used for determining an optimal reactive power adjustment scheme of each future period of the power distribution network according to the comprehensive evaluation objective function, the photovoltaic cluster reactive power output model, the constraint condition and a preset solving algorithm corresponding to each history period, so that the voltage of each node of the power distribution network in each future period is not out of limit;
the device also comprises a third determining unit, a second determining unit and a third determining unit, wherein the third determining unit is used for constructing a reactive equipment operation scheme set of each history period according to the power grid data of each history period;
the second determining unit is further configured to determine, for each historical period, an optimal reactive power adjustment scheme in the reactive power equipment operation scheme set according to the comprehensive evaluation objective function, the photovoltaic cluster reactive power output model, the constraint condition and a preset solving algorithm.
8. A terminal for running a program, wherein the terminal performs the voltage reactive regulation method according to any one of claims 1-6 when running.
9. A storage medium for storing a computer program, wherein the computer program when run controls a device in which the storage medium is located to perform the voltage reactive regulation method according to any one of claims 1-6.
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