CN116799867A - Distributed photovoltaic cooperative control method, system and equipment based on intra-group pre-autonomy - Google Patents
Distributed photovoltaic cooperative control method, system and equipment based on intra-group pre-autonomy Download PDFInfo
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Classifications
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- H—ELECTRICITY
- H02—GENERATION; CONVERSION OR DISTRIBUTION OF ELECTRIC POWER
- H02J—CIRCUIT ARRANGEMENTS OR SYSTEMS FOR SUPPLYING OR DISTRIBUTING ELECTRIC POWER; SYSTEMS FOR STORING ELECTRIC ENERGY
- H02J3/00—Circuit arrangements for ac mains or ac distribution networks
- H02J3/38—Arrangements for parallely feeding a single network by two or more generators, converters or transformers
- H02J3/46—Controlling of the sharing of output between the generators, converters, or transformers
- H02J3/466—Scheduling the operation of the generators, e.g. connecting or disconnecting generators to meet a given demand
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- H—ELECTRICITY
- H02—GENERATION; CONVERSION OR DISTRIBUTION OF ELECTRIC POWER
- H02J—CIRCUIT ARRANGEMENTS OR SYSTEMS FOR SUPPLYING OR DISTRIBUTING ELECTRIC POWER; SYSTEMS FOR STORING ELECTRIC ENERGY
- H02J3/00—Circuit arrangements for ac mains or ac distribution networks
- H02J3/004—Generation forecast, e.g. methods or systems for forecasting future energy generation
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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
- H02J3/24—Arrangements for preventing or reducing oscillations of power in networks
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- H—ELECTRICITY
- H02—GENERATION; CONVERSION OR DISTRIBUTION OF ELECTRIC POWER
- H02J—CIRCUIT ARRANGEMENTS OR SYSTEMS FOR SUPPLYING OR DISTRIBUTING ELECTRIC POWER; SYSTEMS FOR STORING ELECTRIC ENERGY
- H02J3/00—Circuit arrangements for ac mains or ac distribution networks
- H02J3/38—Arrangements for parallely feeding a single network by two or more generators, converters or transformers
- H02J3/381—Dispersed generators
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- H—ELECTRICITY
- H02—GENERATION; CONVERSION OR DISTRIBUTION OF ELECTRIC POWER
- H02J—CIRCUIT ARRANGEMENTS OR SYSTEMS FOR SUPPLYING OR DISTRIBUTING ELECTRIC POWER; SYSTEMS FOR STORING ELECTRIC ENERGY
- H02J2203/00—Indexing scheme relating to details of circuit arrangements for AC mains or AC distribution networks
- H02J2203/10—Power transmission or distribution systems management focussing at grid-level, e.g. load flow analysis, node profile computation, meshed network optimisation, active network management or spinning reserve management
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- H—ELECTRICITY
- H02—GENERATION; CONVERSION OR DISTRIBUTION OF ELECTRIC POWER
- H02J—CIRCUIT ARRANGEMENTS OR SYSTEMS FOR SUPPLYING OR DISTRIBUTING ELECTRIC POWER; SYSTEMS FOR STORING ELECTRIC ENERGY
- H02J2203/00—Indexing scheme relating to details of circuit arrangements for AC mains or AC distribution networks
- H02J2203/20—Simulating, e g planning, reliability check, modelling or computer assisted design [CAD]
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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
- 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
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- 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
Abstract
The application discloses a distributed photovoltaic cooperative control method, system and equipment based on intra-group pre-autonomy, which mainly relate to the technical field of distributed photovoltaic cooperative control and are used for solving the problem of lower regulation performance of the existing distributed photovoltaic cooperative method. Comprising the following steps: acquiring a power prediction data point table and a preset network topology model of a current calculation area of each distributed photovoltaic point in a preset period T under the condition of the distributed photovoltaic polymerization points; calculating power flow according to the power prediction data point table and a preset network topology model to obtain voltage values of a distributed photovoltaic aggregation point and a distribution network access point; screening a plurality of data meeting preset constraint conditions from a predicted data point table to serve as an initial solution set; further, carrying out iterative solution on a preset objective function through a preset particle swarm algorithm to obtain a particle target value; and obtaining the maximum output value of the power running state predicted value of each distributed photovoltaic point under the distributed photovoltaic polymerization point according to the particle target value, and setting the maximum output value as an optimized result value.
Description
Technical Field
The application relates to the technical field of distributed photovoltaic cooperative control, in particular to a distributed photovoltaic cooperative control method, system and equipment based on intra-group pre-autonomy.
Background
From the perspective of safe operation of the power distribution network, the problems of power flow reversal of the power distribution network and great fluctuation of voltage along with photovoltaic output power can occur along with the increase of the photovoltaic scale connected to the power distribution network, so that the voltage of the photovoltaic grid-connected point and the public connection point is increased or even out of limit, and particularly, the problems are more serious when the power load is lower and the photovoltaic power generation output power is larger. The voltage on the feed line may rise even beyond the allowed range. The voltage rise not only affects the power supply quality of local loads, but also increases the loss of power transmission and distribution equipment such as power transmission lines, transformers and the like. Therefore, the access and output of the distributed photovoltaic are required to be regulated under the condition of meeting the requirement of safe and stable operation of the power distribution network.
In the existing distributed photovoltaic adjustment scheme, when the voltage of an access point of a distribution network is out of limit, the scheme of the distributed photovoltaic adjustment on the distribution network side mainly comprises the following steps: the method comprises the following steps of (1) switching an access line and adjusting gears on a distribution network side; (2) And the distribution network side determines the active and reactive adjustment quantity of each photovoltaic polymerization point and transmits the active and reactive adjustment quantity to the polymerization point for execution.
However, the problems of the above scheme are: (1) The decision pressure of the distribution network access points is increased by carrying out algorithm calculation and analysis on the distribution network access points, and the timeliness and accuracy of adjustment are influenced by complex algorithms; (2) When the operation condition of the access point of the power distribution network is abnormal, the power distribution network is regulated, and adverse effects such as voltage fluctuation and the like are easily caused; (3) Only the received power distribution network instruction is regulated in real time, and the regulation quantity calculation algorithm is usually concentrated at a certain moment, so that the calculation resource demand quantity at the moment is suddenly increased or the efficiency is lower, and the performance requirement of the regulating device is higher.
Disclosure of Invention
Aiming at the defects in the prior art, the application provides a distributed photovoltaic cooperative control method, a system and equipment based on intra-group pre-autonomy, which are used for solving the problems that (1) the decision pressure of a distribution network access point is increased by carrying out algorithm calculation and analysis on the distribution network access point, and the timeliness and the accuracy of adjustment are influenced by complex algorithm; (2) When the operation condition of the access point of the power distribution network is abnormal, the power distribution network is regulated, and adverse effects such as voltage fluctuation and the like are easily caused; (3) The method only carries out real-time adjustment on the received power distribution network instruction, and an adjustment quantity calculation algorithm is usually concentrated at a certain moment, so that the technical problem that the calculation resource demand quantity at the moment is suddenly increased or the efficiency is lower and the performance requirement of an adjusting device is higher is solved.
In a first aspect, the application provides a distributed photovoltaic cooperative control method based on intra-group pre-autonomy, which comprises the following steps: acquiring a power prediction data point table and a preset network topology model of a current calculation area of each distributed photovoltaic point in a preset period T under the condition of the distributed photovoltaic polymerization points; calculating power flow according to the power prediction data point table and a preset network topology model to obtain voltage values of a distributed photovoltaic aggregation point and a distribution network access point; screening a plurality of data meeting preset constraint conditions from a predicted data point table to serve as an initial solution set; further, carrying out iterative solution on a preset objective function through a preset particle swarm algorithm to obtain a particle target value; obtaining an optimal output value of each power running state predicted value of the distributed photovoltaic point under the distributed photovoltaic polymerization point according to the particle target value, and setting the optimal output value as an optimal result value; the optimal output value is a value which meets a preset constraint condition and has the minimum line loss.
Further, after the maximum output value obtained from the predicted value of the power running state of each distributed photovoltaic point under the distributed photovoltaic polymerization point according to the particle target value is set as the optimized result value, the method further comprises: according to the real-time adjustment quantity of the power distribution network:and the proportion distribution formula of the regulating quantity of each photovoltaic point: />Determining real-time adjustment quantity of each distributed photovoltaic point; wherein (1)>For the real-time regulation of the distribution network, < > for>For the maximum output value of the ith distributed photovoltaic spot,/v>Real-time adjustment of the ith distributed photovoltaic point.
Further, according to the power prediction data point table and a preset network topology model, the power flow is calculated, and the method specifically comprises the following steps: and combining a preset network topology model according to the power prediction data point table, and calculating the power flow through a layered forward push back substitution method.
Further, the preset constraint condition includes: voltage range:the method comprises the steps of carrying out a first treatment on the surface of the Wherein: u is the voltage at the access point of the power distribution networkThe value is the voltage value of the kth polymerization point; and, the active force constraint range: />≤/>≤； wherein ,/>Lower limit of active output for ith distributed photovoltaic, +.>Is the upper active power limit of the ith distributed photovoltaic.
Further, the preset objective function specifically includes:, wherein ,/>For the voltage deviation value of the distributed photovoltaic polymerization point K at the last moment, +.>For the output of the nth distributed photovoltaic point at a certain moment, +.>The output at the distributed photovoltaic polymerization point k is obtained; />The accumulated value of line loss and voltage deviation in the time period t.
Further, through a preset particle swarm algorithm, carrying out iterative solution on a preset objective function to obtain a particle target value, which specifically comprises: carrying out iterative solution on a preset objective function through a preset particle swarm algorithm to obtain a predicted particle value in real time; when the variation of two adjacent predicted particle values in the iteration process is detected to be smaller than a preset variation threshold value and exceeds preset iteration times, determining the optimal value in the predicted particle values of the last time as a particle target value; the optimal particle value satisfies the preset constraint condition and has the minimum line loss.
In a second aspect, the present application provides a distributed photovoltaic collaborative control system based on intra-group pre-autonomy, the system comprising: the acquisition module is used for acquiring a power prediction data point table and a preset network topology model of a current calculation area of each distributed photovoltaic point in a preset period T under the distributed photovoltaic polymerization point; the calculation module is used for calculating power flow according to the power prediction data point table and a preset network topology model so as to obtain voltage values of the distributed photovoltaic aggregation point and the distribution network access point; the obtaining module is used for screening a plurality of data meeting preset constraint conditions from the predicted data point table to serve as an initial solution set; further, carrying out iterative solution on a preset objective function through a preset particle swarm algorithm to obtain a particle target value; the setting module is used for obtaining the maximum output value of the power running state predicted value of each distributed photovoltaic point under the distributed photovoltaic polymerization point according to the particle target value and setting the maximum output value as an optimized result value; the optimal output value is a value which meets a preset constraint condition and has the minimum line loss.
Further, the system also comprises an adjusting module, which is used for adjusting the quantity according to the real-time of the power distribution network:and the proportion distribution formula of the regulating quantity of each photovoltaic point: />Determining real-time adjustment quantity of each distributed photovoltaic point; wherein (1)>For the real-time regulation of the distribution network, < > for>For the maximum output value of the ith distributed photovoltaic spot,/v>Real-time adjustment of the ith distributed photovoltaic point.
Further, the obtaining module comprises a determining unit, a calculating unit and a calculating unit, wherein the determining unit is used for carrying out iterative solution on a preset objective function through a preset particle swarm algorithm to obtain a predicted particle value in real time; when the variation of two adjacent predicted particle values in the iteration process is detected to be smaller than a preset variation threshold value and exceeds preset iteration times, determining the optimal value in the predicted particle values of the last time as a particle target value; the optimal particle value satisfies the preset constraint condition and has the minimum line loss.
In a third aspect, the present application provides a distributed photovoltaic co-control device based on intra-cluster pre-autonomy, the device comprising: a processor; and a memory having executable code stored thereon that, when executed, causes the processor to perform a distributed photovoltaic co-control method based on intra-cluster pre-autonomy as in any of the above.
As will be appreciated by those skilled in the art, the present application has at least the following beneficial effects:
the two-stage control mode of 'in-group pre-autonomy (obtaining an optimal result value of a power running state predicted value of each distributed photovoltaic point under a distributed photovoltaic polymerization point and setting the optimal result value as an optimal output value in a period T) +real-time cooperation of a distribution network (determining the real-time adjustment quantity of each distributed photovoltaic point)' is realized, and the real-time adjustment efficiency of the distribution network is improved through in-group pre-autonomy balance; according to the predicted data, the optimal power distribution scheme of the distributed photovoltaic is updated regularly, the frequency of voltage out-of-limit is reduced, voltage fluctuation is reduced, and the power supply quality is improved; and the line loss is minimized, and then the line loss is distributed proportionally, so that fairness and economy are considered.
Drawings
Some embodiments of the present disclosure are described below with reference to the accompanying drawings, in which:
fig. 1 is a flowchart of a distributed photovoltaic collaborative control method based on intra-group pre-autonomy provided by an embodiment of the application.
Fig. 2 is a schematic diagram of an internal structure of a distributed photovoltaic cooperative control system based on intra-group pre-autonomy according to an embodiment of the present application.
Fig. 3 is a schematic diagram of an internal structure of a distributed photovoltaic cooperative control device based on intra-group pre-autonomy according to an embodiment of the present application.
Detailed Description
It should be understood by those skilled in the art that the embodiments described below are only preferred embodiments of the present disclosure, and do not represent that the present disclosure can be realized only by the preferred embodiments, which are merely for explaining the technical principles of the present disclosure, not for limiting the scope of the present disclosure. Based on the preferred embodiments provided by the present disclosure, all other embodiments that may be obtained by one of ordinary skill in the art without inventive effort shall still fall within the scope of the present disclosure.
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.
The distributed photovoltaic access related by the application is divided into 2 layers:
distribution network access points: the distributed photovoltaic is connected to nodes of the power grid, running states such as voltage and current of the distribution network are monitored in real time, and information collection instructions and adjustment control instructions can be sent downwards.
Distributed photovoltaic polymerization point: one distribution network access point may have one or more distributed photovoltaic aggregation points, and several distributed photovoltaic may be managed at a single aggregation point. The photovoltaic output information below the aggregation point can be collected and sent to the distribution network side, and meanwhile, the photovoltaic output information can receive a distribution network side instruction and send the photovoltaic output information to equipment such as a photovoltaic switch and an inverter.
The scheme is positioned at a distributed photovoltaic polymerization point, and a communication unit is arranged in a device related to the scheme, and can interact with an inverter user through HPLC or RS485 to be responsible for data acquisition, encryption and transmission of voltage, current, active power, reactive power, electric quantity, switching state and the like.
The following describes the technical scheme provided by the embodiment of the application in detail through the attached drawings.
The embodiment of the application provides a distributed photovoltaic cooperative control method based on intra-group pre-autonomy, which mainly comprises the following steps:
step 110, obtaining a power prediction data point table and a preset network topology model of a current calculation area of each distributed photovoltaic point in a preset period T under the condition of the distributed photovoltaic polymerization points.
The power prediction data point table may be a predicted value of every 15 minutes within 4 hours, expressed as a set:wherein grid is a power prediction data point table, and P is a power value. In addition, a radiation type power distribution network topology model with a distributed power supply is preset in a network topology model value.
And 120, calculating power flow according to the power prediction data point table and a preset network topology model to obtain voltage values of the distributed photovoltaic aggregation point and the distribution network access point.
The power flow is calculated according to the power prediction data point table and a preset network topology model, and the power flow can be specifically: and combining a preset network topology model according to the power prediction data point table, and calculating the power flow through a layered forward push back substitution method.
Step 130, screening a plurality of data meeting preset constraint conditions from a predicted data point table to serve as an initial solution set; and then, carrying out iterative solution on a preset objective function through a preset particle swarm algorithm so as to obtain a particle target value.
It should be noted that, the preset constraint conditions may be: voltage range:the method comprises the steps of carrying out a first treatment on the surface of the Which is a kind ofIn (a): u is the voltage value at the access point of the power distribution network and is the voltage value of the kth aggregation point; and, the active force constraint range: />≤/>≤/>； wherein ,/>Lower limit of active output for ith distributed photovoltaic, +.>Is the upper active power limit of the ith distributed photovoltaic. The preset objective function may specifically be: />, wherein ,/>For the voltage deviation value of the distributed photovoltaic polymerization point K at the last moment, +.>For the output of the nth distributed photovoltaic point at a certain moment, +.>The output at the distributed photovoltaic polymerization point k is obtained; />The accumulated value of line loss and voltage deviation in the time period t.
That is, according to the voltage values in the preset constraint conditions, n columns of values meeting the conditions are screened from grid, namelyAs an initial solution set->Wherein R is a list of values.
The iterative solution is performed on a preset objective function through a preset particle swarm algorithm to obtain a particle target value, which may be specifically: carrying out iterative solution on a preset objective function through a preset particle swarm algorithm to obtain a predicted particle value in real time; when the variation of two adjacent predicted particle values in the iteration process is detected to be smaller than a preset variation threshold value and exceeds preset iteration times, determining the optimal value in the predicted particle values of the last time as a particle target value; the optimal particle value satisfies the preset constraint condition and has the minimum line loss.
By way of example, the preset objective function is solved by a particle swarm algorithm, and the particle target value in the solving process is. If +.>The change amount of (2) is smaller than the preset change threshold value and exceeds the preset iteration number, and the particle target value is updated to be +.>. Obtaining the predicted value of the power running state of each photovoltaic point under the aggregation point k。
And 140, obtaining an optimal output value of the power running state predicted value of each distributed photovoltaic point under the distributed photovoltaic polymerization point according to the particle target value, and setting the optimal output value as an optimal result value.
It should be noted that, the optimal output value is a value that satisfies a preset constraint condition and has a minimum line loss.
Illustratively, the inverter irax value in the period T in step 130 is set to the optimized result value。
In addition, the application can also cooperate with a distribution network to receive the real-time adjustment quantity of the distribution network and adjust the distributed photovoltaic output, and as an example, the application can adjust the quantity according to the real-time adjustment quantity of the distribution network:and the proportion distribution formula of the regulating quantity of each photovoltaic point: />Determining real-time adjustment quantity of each distributed photovoltaic point; wherein (1)>For the real-time regulation of the distribution network, < > for>For the maximum output value of the ith distributed photovoltaic spot,/v>Real-time adjustment of the ith distributed photovoltaic point.
In addition, fig. 2 is a schematic diagram of a distributed photovoltaic collaborative control system based on intra-group pre-autonomy according to an embodiment of the present application. As shown in fig. 2, the system provided by the embodiment of the present application mainly includes:
the obtaining module 210 is configured to obtain, at the distributed photovoltaic aggregation points, a power prediction data point table and a preset network topology model of the current calculation area of each distributed photovoltaic point within a preset period T.
The calculation module 220 is configured to calculate a power flow according to the power prediction data point table and a preset network topology model, so as to obtain voltage values of the distributed photovoltaic aggregation point and the distribution network access point.
An obtaining module 230, configured to screen a plurality of data meeting a preset constraint condition from the predicted data point table, as an initial solution set; and then, carrying out iterative solution on a preset objective function through a preset particle swarm algorithm so as to obtain a particle target value.
The obtaining module 230 includes a determining unit 231, configured to iteratively solve a preset objective function through a preset particle swarm algorithm, and obtain a predicted particle value in real time; when the change amount of two adjacent predicted particle values in the iteration process is detected to be smaller than a preset change threshold value and exceeds the preset iteration times, determining the optimal value in the predicted particle values in the last time as the particle target value.
It should be noted that the optimum is a particle value satisfying a predetermined constraint condition and having the smallest line loss.
The setting module 240 is configured to obtain a maximum output value of the power running state predicted value of each distributed photovoltaic point at the distributed photovoltaic polymerization point according to the particle target value, and set the maximum output value as an optimized result value.
In addition, the system further comprises an adjusting module 250 for adjusting the amount according to the real-time distribution network:and the proportion distribution formula of the regulating quantity of each photovoltaic point:determining real-time adjustment quantity of each distributed photovoltaic point; wherein (1)>For the real-time regulation of the distribution network, < > for>For the maximum output value of the ith distributed photovoltaic spot,/v>Real-time adjustment of the ith distributed photovoltaic point.
In addition, the embodiment of the application also provides distributed photovoltaic cooperative control equipment based on intra-group pre-autonomy. As shown in fig. 3, the apparatus includes: a processor; and a memory having executable code stored thereon that, when executed, causes the processor to perform a distributed photovoltaic co-control method based on intra-cluster pre-autonomy as in one of the above embodiments.
Specifically, under the condition that distributed photovoltaic polymerization points are obtained by a server, a power prediction data point table and a preset network topology model of a current calculation area of each distributed photovoltaic point in a preset period T are obtained; calculating power flow according to the power prediction data point table and a preset network topology model to obtain voltage values of a distributed photovoltaic aggregation point and a distribution network access point; screening a plurality of data meeting preset constraint conditions from a predicted data point table to serve as an initial solution set; further, carrying out iterative solution on a preset objective function through a preset particle swarm algorithm to obtain a particle target value; and obtaining the maximum output value of the power running state predicted value of each distributed photovoltaic point under the distributed photovoltaic polymerization point according to the particle target value, and setting the maximum output value as an optimized result value.
Thus far, the technical solution of the present disclosure has been described in connection with the foregoing embodiments, but it is easily understood by those skilled in the art that the protective scope of the present disclosure is not limited to only these specific embodiments. The technical solutions in the above embodiments may be split and combined by those skilled in the art without departing from the technical principles of the present disclosure, and equivalent modifications or substitutions may be made to related technical features, which all fall within the scope of the present disclosure.
Claims (10)
1. A distributed photovoltaic collaborative control method based on intra-group pre-autonomy, the method comprising:
acquiring a power prediction data point table and a preset network topology model of a current calculation area of each distributed photovoltaic point in a preset period T under the condition of the distributed photovoltaic polymerization points;
calculating power flow according to the power prediction data point table and a preset network topology model to obtain voltage values of a distributed photovoltaic aggregation point and a distribution network access point;
screening a plurality of data meeting preset constraint conditions from a predicted data point table to serve as an initial solution set; further, carrying out iterative solution on a preset objective function through a preset particle swarm algorithm to obtain a particle target value;
obtaining an optimal output value of each power running state predicted value of the distributed photovoltaic point under the distributed photovoltaic polymerization point according to the particle target value, and setting the optimal output value as an optimal result value; the optimal output value is a value which meets a preset constraint condition and has the minimum line loss.
2. The intra-group pre-autonomy-based distributed photovoltaic collaborative control method according to claim 1, wherein after obtaining an optimal output value for each distributed photovoltaic point power operating state prediction value under a distributed photovoltaic polymerization point according to a particle target value is set to an optimal result value, the method further comprises:
according to the real-time adjustment quantity of the power distribution network:
，
and the proportion distribution formula of the regulating quantity of each photovoltaic point:
determining real-time adjustment quantity of each distributed photovoltaic point;
wherein ,for the real-time regulation of the distribution network, < > for>For the maximum output value of the ith distributed photovoltaic spot,/v>Real-time adjustment of the ith distributed photovoltaic point.
3. The distributed photovoltaic collaborative control method based on intra-group pre-autonomy according to claim 1, wherein calculating a power flow according to a power prediction data point table and a preset network topology model specifically comprises:
and combining a preset network topology model according to the power prediction data point table, and calculating the power flow through a layered forward push back substitution method.
4. The intra-group pre-autonomy-based distributed photovoltaic cooperative control method according to claim 1, wherein the preset constraint conditions include:
voltage range:the method comprises the steps of carrying out a first treatment on the surface of the Wherein: u is the voltage value at the access point of the power distribution network and is the voltage value of the kth aggregation point; and, a step of, in the first embodiment,
active force constraint range:≤/>≤/>； wherein ,/>Lower limit of active output for ith distributed photovoltaic, +.>Is the upper active power limit of the ith distributed photovoltaic.
5. The intra-group pre-autonomy-based distributed photovoltaic cooperative control method according to claim 1, wherein the pre-setting of the objective function specifically comprises:
, wherein ,/>For the voltage deviation value of the distributed photovoltaic polymerization point K at the last moment, +.>For the output of the nth distributed photovoltaic point at a certain moment, +.>The output at the distributed photovoltaic polymerization point k is obtained; />The accumulated value of line loss and voltage deviation in the time period t.
6. The intra-group pre-autonomy-based distributed photovoltaic cooperative control method according to claim 1, wherein the iterative solution is performed on a preset objective function through a preset particle swarm algorithm to obtain a particle target value, and specifically comprising:
carrying out iterative solution on a preset objective function through a preset particle swarm algorithm to obtain a predicted particle value in real time;
when the variation of two adjacent predicted particle values in the iteration process is detected to be smaller than a preset variation threshold value and exceeds preset iteration times, determining the optimal value in the predicted particle values of the last time as a particle target value; the optimal particle value satisfies the preset constraint condition and has the minimum line loss.
7. A distributed photovoltaic collaborative control system based on intra-group pre-autonomy, the system comprising:
the acquisition module is used for acquiring a power prediction data point table and a preset network topology model of a current calculation area of each distributed photovoltaic point in a preset period T under the distributed photovoltaic polymerization point;
the calculation module is used for calculating power flow according to the power prediction data point table and a preset network topology model so as to obtain voltage values of the distributed photovoltaic aggregation point and the distribution network access point;
the obtaining module is used for screening a plurality of data meeting preset constraint conditions from the predicted data point table to serve as an initial solution set; further, carrying out iterative solution on a preset objective function through a preset particle swarm algorithm to obtain a particle target value;
the setting module is used for obtaining the maximum output value of the power running state predicted value of each distributed photovoltaic point under the distributed photovoltaic polymerization point according to the particle target value, and setting the maximum output value as an optimized result value.
8. The distributed photovoltaic co-control system based on intra-cluster pre-autonomy according to claim 7, further comprising an adjustment module,
the method is used for adjusting the quantity according to the real-time of the power distribution network:and the proportion distribution formula of the regulating quantity of each photovoltaic point: />Determining real-time adjustment quantity of each distributed photovoltaic point; wherein (1)>For the real-time regulation of the distribution network, < > for>For the maximum output value of the ith distributed photovoltaic spot,/v>Real-time adjustment of the ith distributed photovoltaic point.
9. The distributed photovoltaic co-control system based on intra-group pre-autonomy according to claim 7, wherein the obtaining module comprises a determining unit,
the method comprises the steps of carrying out iterative solution on a preset objective function through a preset particle swarm algorithm, and obtaining a predicted particle value in real time; when the variation of two adjacent predicted particle values in the iteration process is detected to be smaller than a preset variation threshold value and exceeds preset iteration times, determining the optimal value in the predicted particle values of the last time as a particle target value; the optimal particle value satisfies the preset constraint condition and has the minimum line loss.
10. A distributed photovoltaic co-control device based on intra-cluster pre-autonomy, the device comprising:
a processor;
and a memory having executable code stored thereon that, when executed, causes the processor to perform a distributed photovoltaic co-control method based on intra-cluster pre-autonomy as in any one of claims 1-6.
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