CN112531789A - Dynamic reconfiguration strategy for power distribution network with distributed power supplies - Google Patents
Dynamic reconfiguration strategy for power distribution network with distributed power supplies Download PDFInfo
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- 230000003068 static effect Effects 0.000 claims abstract description 18
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- 238000011156 evaluation Methods 0.000 claims abstract description 4
- 241000894006 Bacteria Species 0.000 claims description 6
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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
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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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- 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
- Y02A—TECHNOLOGIES FOR ADAPTATION TO CLIMATE CHANGE
- Y02A30/00—Adapting or protecting infrastructure or their operation
- Y02A30/60—Planning or developing urban green infrastructure
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Abstract
The invention relates to the technical field of analysis and control of power systems, in particular to an analysis technology of a power distribution network containing a renewable distributed power source (RDG). The method comprises the following steps: A. establishing a dynamic reconstruction model taking the output maximization of the renewable distributed power supply as a target function and considering various constraints; B. establishing a renewable distributed power model to be optimized; C. performing static reconstruction on the power distribution network at a plurality of unit time intervals in one day to form an optimal switch set; D. preliminarily combining adjacent time intervals with the same topological structure; E. evaluating the reconstruction effectiveness of each time interval, and determining an optimal time interval division scheme according to the evaluation; F. and selecting the net rack with the maximum reconstruction effectiveness by adopting a bacterial foraging algorithm as the optimal net rack after time interval combination. By the dynamic reconfiguration strategy of the power distribution network of the distributed power supply, the power distribution network containing the renewable distributed power supply can be optimized and dynamically reconfigured, and the reconfiguration effect is good and the efficiency is high.
Description
Technical Field
The invention relates to the technical field of analysis and control of power systems, in particular to an analysis technology of a power distribution network containing a renewable distributed power source (RDG).
Background
The power distribution network has the characteristics of closed-loop design and open-loop operation. The reconstruction of the power distribution network is to change the topological structure of the whole network by selecting different section switches and interconnection switches to carry out the combined operation of opening and closing on the premise of meeting the related constraint conditions of the power distribution network, thereby achieving the aim of optimizing the operation of the whole power distribution network.
The power distribution network reconstruction is divided into a static reconstruction mode and a dynamic reconstruction mode. The static reconstruction is to simply use the load data of a single time period to perform the overall optimization reconstruction, and the dynamic reconstruction relates to the change of the load data of a plurality of uninterrupted time points, so as to perform the overall optimization reconstruction. In practical application, if only static reconstruction of the power distribution network is considered, the following disadvantages exist:
1. in practical situations, because the load data of each node in the system varies at all times, the same optimal network structure cannot satisfy the situation that each time is optimal. The single static reconstruction is difficult to satisfy the real-time reconstruction operation and the optimization operation.
2. The power distribution network reconfiguration operation based on the static reconfiguration needs frequent switch change-over, which is not operable in practical application.
Based on the above situation, the static reconfiguration is difficult to meet the purpose of optimizing the operation of the power distribution network, both from the economic aspect and the technical aspect. The dynamic reconstruction also comprehensively considers the practical constraint of the switch operation times on the basis of considering the fluctuation change of load data, and although the optimization complexity is far higher than that of the static reconstruction, the limitation of the model on the benefit requirement is increased, the dynamic reconstruction is more practical and has more research value under the overall comparison.
Disclosure of Invention
In view of this, the present invention aims to overcome the shortcomings of the prior art, and provides a dynamic reconfiguration strategy for improving the receiving capability of a renewable distributed power source of a distribution network, aiming at the increasingly prominent problem of wind/light abandonment under the high penetration of renewable energy sources. The strategy comprises the steps of firstly performing static reconstruction with the maximum RDG generated energy in each unit time interval as a target, preliminarily combining the extracted optimal switch combination pairs, evaluating reconstruction effectiveness of each time interval, and optimizing the output of the renewable distributed power supply by adopting an improved bacterial foraging algorithm with self-adaptive adjustment of the optimizing direction so as to improve reconstruction efficiency.
In order to achieve the purpose, the invention adopts the following technical scheme.
A dynamic reconfiguration strategy for a power distribution network including distributed power sources, the method comprising the steps of:
A. establishing a dynamic reconstruction model taking the output maximization of the renewable distributed power supply as a target function and considering various constraints;
B. establishing a renewable distributed power model to be optimized;
C. performing static reconstruction on the power distribution network at a plurality of unit time intervals in one day to form an optimal switch set;
D. preliminarily combining adjacent time intervals with the same topological structure;
E. evaluating the reconstruction effectiveness of each time interval, and determining an optimal time interval division scheme according to the evaluation;
F. and selecting the net rack with the maximum reconstruction effectiveness by adopting a bacterial foraging algorithm as the optimal net rack after time interval combination.
By adopting the dynamic reconfiguration strategy of the power distribution network containing the distributed power supply, the technical effects are as follows:
(1) a new method of merging reconstruction periods is proposed: and extracting the optimal switch combination based on static reconstruction, carrying out time interval preliminary combination, evaluating the reconstruction effectiveness of each time interval, and finally selecting the net rack with the maximum reconstruction effectiveness to determine the optimal time interval division scheme.
(2) Carrying out optimization direction self-adaptive adjustment on the traditional bacterial foraging algorithm: social cognition in the particle swarm algorithm is introduced, so that the bacteria individual moves towards the optimal individual, the moving step length is automatically adjusted, and the algorithm efficiency is improved.
Therefore, the dynamic reconfiguration strategy of the power distribution network containing the distributed power supply can optimize the dynamic reconfiguration of the power distribution network containing the renewable distributed power supply, and has good reconfiguration effect and high efficiency.
Drawings
FIG. 1 is a flow chart of the processing method of the present invention.
FIG. 2 is a schematic diagram of the dynamic reconfiguration of the present invention.
Detailed Description
The embodiments of the invention will be described in further detail below with reference to the accompanying drawings:
a dynamic reconfiguration strategy for a power distribution network including a renewable distributed power source, as shown in fig. 1, includes the following steps:
A. establishing a dynamic reconstruction model taking the output maximization of the renewable distributed power supply as a target function and considering various constraints;
the objective function of maximizing the output of the renewable distributed power supply is as follows:
in the formula:
total injected power for RDG during a day;
the total time interval before time interval division is carried out;
RDG for network access
Besides the traditional power distribution network dynamic reconstruction including power flow constraint, node voltage constraint, branch current constraint, network topology constraint and switch operation times constraint, the invention also considers RDG output and permeability constraint, so that the reconstruction problem is more rigorous.
(1) Flow restraint
In the formula:
respectively representing nodes
In that
Active and reactive power of a time period;
representing the number of network nodes;
is a branch
Conductance, susceptance;
is composed of
Time interval node
Voltage phase angle difference between.
(2) Voltage confinement
In the formula:
is a node
In that
The magnitude of the voltage of the time period,
respectively, the upper and lower limit values.
(3) Branch current constraint
In the formula:
is a branch
In that
The current value of the time period is,
its upper limit value is set.
(4) The distribution network structure must be radial all the time and there must not be islands and loops.
(5) RDG force constraints
In the formula:
is as follows
RDG is at
Upper limit of force for the time period.
(6) RDG permeability constraint
In the formula:
taking the values of the upper limit and the lower limit of the RDG permeability;
is composed of
All power sources inject power into the distribution grid during the time period.
(7) Switch action frequency constraint
In the formula:
is a switch
In that
The state of the time interval is 0 or 1;
is a switch
Upper limit of the number of actions of (1);
the upper limit value of the action times of all the switches in the reconstruction period is obtained.
B. Establishing a renewable distributed power model to be optimized;
the RDG to be optimized is a wind turbine generator set and a photovoltaic generator set, and the output power of the RDG is closely related to factors such as wind speed, light intensity and unit capacity. The invention uses Weibull distribution with the widest application range to fit the actual wind speed, and Beta distribution is used for expressing the illumination intensity.
C. Performing static reconstruction on the power distribution network at a plurality of unit time intervals in one day to form an optimal switch set;
the method adopts a solution idea of discretizing a continuous process, and performs overall coordination optimization after performing static reconstruction on the power distribution network to obtain an optimal solution of a single time section. Therefore, the first aim is to ensure the stability of the whole day
Performing static reconstruction with maximum renewable energy consumption per unit time interval, and extracting the data of each unit time interval
The optimal reconstruction net rack forms an optimal switch set in a reconstruction period
。
D. Preliminarily combining adjacent time intervals with the same topological structure;
and C, preliminarily combining adjacent time intervals with the same topological structure.
E. Evaluating the reconstruction effectiveness of each time interval, and determining an optimal time interval division scheme according to the evaluation;
according to the invention, the reconstruction effectiveness of each time interval is evaluated by comparing the RDG output promotion amount caused by the switching action in each time interval, so that the time intervals to be combined are determined. The specific operation steps are as follows:
considering that the dynamic reconstruction aims to improve the RDG output, the smaller the average RDG output improvement amount in the reconstruction period is, the less the benefit brought by the reconstruction is, and the less the reconstruction effectiveness is, and the switch change should be avoided as much as possible in the period. Therefore, the reconstruction effectiveness is defined to solve the multi-period coordination problem, and the calculation formula is as follows:
in the formula:
is as follows
Reconstruction validity of each merging period;
is as follows
The length of the merging periods, i.e., the number of unit periods involved;
is the first under the original net rack
RDG is at
The implant power of the time period.
The time interval division method based on reconstruction effectiveness mainly comprises the following steps:
(1) and optimizing the RDG output under the original net rack to obtain an RDG output curve.
(2) Performing static reconstruction with maximum consumption of renewable energy as target, and extracting the data of each unit time interval
The optimal reconstruction net rack forms the optimal switch set of the time interval
And preliminarily combining adjacent time intervals with the same topological structure.
(3) And (4) if the time period number is reduced to the optimal time period number, outputting a reconstruction result, and otherwise, turning to the step (4).
(4) And calculating the reconstruction effectiveness of each time interval, finding out the time interval with the minimum reconstruction effectiveness, combining the time interval with the adjacent previous time interval and the adjacent next time interval respectively, and selecting the reconstruction mode from the optimal switch set of the combined time interval. Each scheme can calculate reconstruction effectiveness according to equation (8), and the scheme with the minimum reconstruction effectiveness is selected as the reconstruction scheme under the k-1 segment number.
(5) And (4) adjusting the time interval serial number, saving the optimal net rack and RDG output power in each time interval, and returning to the step (3).
(6) The above process is repeated until the optimum number of time segments is reached.
The dynamic reconfiguration diagram is shown in fig. 2.
F. And selecting the net rack with the maximum reconstruction effectiveness by adopting a bacterial foraging algorithm as the optimal net rack after time interval combination.
The method optimizes the RDG output of each net rack in the search space based on the IBFA algorithm, screens out the net rack with the highest fitness and obtains the optimal net rack and the RDG output thereof.
In order to improve the efficiency of the algorithm, the invention improves the IBFA algorithm: social cognition in a PSO algorithm is introduced, bacteria individuals move towards the optimal individuals, the moving step length is automatically adjusted, the algorithm efficiency is improved, the improvement is called optimizing direction self-adaptive adjustment, and the specific calculation formula is as follows:
for convenience of description, let:
in the formula:
is as follows
The optimizing direction and step length of the bacteria after self-adaptive adjustment;
the optimal individual position of the group under the current iteration times is obtained;
is as follows
The location of individual bacteria;
function Generation [0,1]And a random number in the space between the two random numbers is used for carrying out random step length control, so that the operation amount is reduced.
Claims (3)
1. A dynamic reconfiguration strategy for a power distribution network including distributed power sources, the method comprising the steps of:
a: establishing a dynamic reconstruction model taking the output maximization of the renewable distributed power supply as a target function and considering various constraints;
b: establishing a renewable distributed power model to be optimized;
c: performing static reconstruction on the power distribution network at a plurality of unit time intervals in one day to form an optimal switch set;
d: preliminarily combining adjacent time intervals with the same topological structure;
e: evaluating the reconstruction effectiveness of each time interval, and determining an optimal time interval division scheme according to the evaluation;
f: and selecting the net rack with the maximum reconstruction effectiveness by adopting a bacterial foraging algorithm as the optimal net rack after time interval combination.
2. According to the dynamic reconstruction strategy of the power distribution network with the distributed power supply, which is described in the claim 1, a new method for combining reconstruction time periods is provided; and E, extracting the optimal switch combination based on static reconstruction, and evaluating the reconstruction effectiveness of each time interval after the time intervals are preliminarily combined:
firstly, the reconstruction effectiveness is defined to solve the multi-period coordination problem, and the calculation formula is as follows:
in the formula (I), the compound is shown in the specification,
is as follows
Reconstruction validity of each merging period;
is as follows
The length of the merging periods, i.e., the number of unit periods involved;
is the first under the original net rack
RDG is at
Injection power of a time period;
the time interval division method based on reconstruction effectiveness mainly comprises the following steps:
(1) optimizing the RDG output under the original net rack to obtain an RDG output curve;
(2) performing static reconstruction with maximum consumption of renewable energy as target, and extracting the data of each unit time interval
The optimal reconstruction net rack forms the optimal switch set of the time interval
Preliminarily combining adjacent time intervals with the same topological structure;
(3) if the number of the time periods is reduced to the optimal number of the time periods, outputting a reconstruction result, and otherwise, turning to the step (4);
(4) calculating the reconstruction effectiveness of each time interval, finding out the time interval with the minimum reconstruction effectiveness, combining the time interval with the adjacent previous time interval and the adjacent next time interval respectively, and selecting a reconstruction mode from an optimal switch set of the combined time interval; each scheme can calculate reconstruction effectiveness according to the formula (8), and the scheme with the minimum reconstruction effectiveness is selected as the reconstruction scheme under the k-1 segment number;
(5) adjusting the time interval sequence number, saving the optimal net rack and RDG output power of each time interval, and returning to the step (3);
(6) the above process is repeated until the optimum number of time segments is reached.
3. The dynamic reconfiguration strategy of the power distribution network with distributed power supplies according to claim 1, which improves the traditional bacterial foraging algorithm; in step F, in order to improve the algorithm efficiency, the present invention improves the IBFA algorithm: social cognition in a PSO algorithm is introduced, bacteria individuals move towards the optimal individuals, the moving step length is automatically adjusted, the algorithm efficiency is improved, the improvement is called optimizing direction self-adaptive adjustment, and the specific calculation formula is as follows:
for convenience of description, let:
in the formula:
is as follows
Optimizing direction after self-adaptive adjustment of individual bacteriaAnd step length;
the optimal individual position of the group under the current iteration times is obtained;
is as follows
The location of individual bacteria;
function Generation [0,1]And a random number in the space between the two random numbers is used for carrying out random step length control, so that the operation amount is reduced.
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Cited By (2)
| Publication number | Priority date | Publication date | Assignee | Title |
|---|---|---|---|---|
| CN113991742A (en) * | 2021-11-19 | 2022-01-28 | 国网重庆市电力公司 | Distributed photovoltaic double-layer collaborative optimization investment decision method for power distribution network |
| CN114050607B (en) * | 2021-10-25 | 2024-04-05 | 国网冀北电力有限公司经济技术研究院 | Construction system of reconstruction digital model of power distribution network |
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Cited By (3)
| Publication number | Priority date | Publication date | Assignee | Title |
|---|---|---|---|---|
| CN114050607B (en) * | 2021-10-25 | 2024-04-05 | 国网冀北电力有限公司经济技术研究院 | Construction system of reconstruction digital model of power distribution network |
| CN113991742A (en) * | 2021-11-19 | 2022-01-28 | 国网重庆市电力公司 | Distributed photovoltaic double-layer collaborative optimization investment decision method for power distribution network |
| CN113991742B (en) * | 2021-11-19 | 2024-04-16 | 国网重庆市电力公司 | Distributed photovoltaic double-layer collaborative optimization investment decision-making method for power distribution network |
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