CN115800397A - Power distribution station topology optimization method, system, equipment and medium - Google Patents
Power distribution station topology optimization method, system, equipment and medium Download PDFInfo
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Abstract
The invention belongs to the technical field of power systems, and discloses a power distribution station topology optimization method, which comprises the following steps: coding a basic loop in a power distribution area by adopting a real number coding mode based on a sequential loop matrix to obtain a power distribution area topology optimization model; solving the topological optimization model of the power distribution area according to the improved top-over-meaning competition algorithm to obtain an optimal topological optimization model of the power distribution area; and optimizing each operation parameter in the power distribution area by using the optimal power distribution area topology optimization model. According to the method, the power distribution area topological optimization model is constructed by adopting a coding mode based on the sequence ring matrix, the power distribution area topological optimization model is optimally solved by adopting an improved empire state meaning competition algorithm, and the optimal power distribution area topological optimization model is obtained to optimize the power distribution area, so that the topological optimization speed is effectively increased, the safe operation margin of the power distribution area is maximized, and the safe and stable operation of the power distribution area is ensured.
Description
Technical Field
The invention relates to the technical field of power systems, in particular to a power distribution station topology optimization method, a power distribution station topology optimization system, power distribution station topology optimization equipment and a power distribution station topology optimization medium.
Background
In 2021, the national energy agency formally issues a notification about publishing a list of distributed photovoltaic development test points on the roof of the whole county (city and district), so that the development of distributed photovoltaic is greatly promoted in a policy incentive manner, and the installed scale and the access proportion of the distributed photovoltaic in a low-voltage distribution network (distribution area) are continuously increased. As a clean energy source, the photovoltaic power generation system can bring huge power generation benefits when being connected into a power distribution area in a high proportion, but due to the uncertainty of the photovoltaic power generation system, a series of problems that the network safety and the stability are damaged, such as voltage out-of-limit, line overload, electric energy quality reduction and the like, can be brought. Therefore, in order to avoid the above problems and maximize the safe operation margin of the distribution substation, it is urgently needed to establish a safe operation evaluation index of the distribution substation and to develop an effective topology optimization method of the distribution substation.
At present, the research on topology optimization of a 10kV voltage-class power distribution network is rich and mature, objective functions mostly concentrate on network loss, voltage deviation and load balance, single-objective optimization or multi-objective optimization is often performed according to actual needs, the research on the voltage-class topology optimization of a power distribution station area is rare, and the establishment of evaluation indexes capable of further reflecting the safe operation state of the power distribution station area is lacked. The binary coding mode can generate a large number of infeasible solutions, the solving efficiency is reduced, and the optimizing effect is influenced.
Aiming at the defects, the invention firstly establishes a power distribution area safe operation margin evaluation index and a topology optimization model, and further adopts an empire-meaning competition algorithm based on sequence ring matrix coding and Cauchy variation improvement to solve a power distribution area topology optimization result so as to improve the power distribution area safe operation margin and ensure the power distribution area safe and stable operation.
Disclosure of Invention
The embodiment of the invention provides a power distribution area topology optimization method, a system, equipment and a medium, which can improve the safety operation margin of a power distribution area and ensure the safety and stable operation of the power distribution area.
The following presents a simplified summary in order to provide a basic understanding of some aspects of the disclosed embodiments. This summary is not an extensive overview and is intended to neither identify key/critical elements nor delineate the scope of such embodiments. Its sole purpose is to present some concepts in a simplified form as a prelude to the more detailed description that is presented later.
According to a first aspect of the embodiments of the present invention, a power distribution substation topology optimization method is provided.
In one embodiment, the power distribution grid topology optimization method includes:
coding a basic loop in a power distribution area by adopting a real number coding mode based on a sequential loop matrix to obtain a power distribution area topology optimization model;
solving the power distribution area topological optimization model according to an improved top-over-meaning competition algorithm to obtain an optimal power distribution area topological optimization model;
and optimizing each operation parameter in the power distribution area by using the optimal power distribution area topology optimization model.
In one embodiment, the operating parameters include at least one of: the system comprises a power distribution network area topology connection information parameter, a power distribution network line model parameter, a power distribution network resistance reactance parameter, a power distribution network node load level parameter, a power distribution network distributed photovoltaic access node parameter and a power distribution network distributed photovoltaic node output level parameter.
In one embodiment, the encoding processing of the basic loop in the power distribution network is performed by using a real number encoding mode based on a sequential loop matrix, and the obtaining of the topology optimization model of the power distribution network area comprises the following steps: reordering basic ring loops in a power distribution area according to the connection sequence of each row of branch circuits in the topological structure of the power distribution area to obtain a sequence basic ring matrix, and taking the sequence basic ring matrix as a model decision variable; determining a voltage safety margin and a current safety margin according to the evaluation index of the safety operation margin of the power distribution transformer area, and establishing a model fitness function according to the voltage safety margin and the current safety margin; and constructing a topological optimization model of the power distribution area according to the model decision variable, the model fitness function and the constraint condition of the power distribution area.
In one embodiment, the encoding processing is performed on the basic loop in the power distribution network by using a real number encoding mode based on the sequential loop matrix, and the obtaining of the power distribution station area topology optimization model further includes: before the sequential basic ring matrix is used as a model decision variable, repeated branches of each matrix row in the sequential basic ring matrix are removed, each branch in the sequential basic ring matrix is only corresponding to one matrix row, and a section switch of the sequential basic ring matrix is positioned in the matrix row with the minimum power distance.
In one embodiment, based on the voltage safety margin and the current safety margin, a calculation formula for establishing a model fitness function is as follows:
max f(x)＝α·U margin +(1-α)·I margin
in the formula, N b The number of nodes and branches of the distribution area, U i For the actual operating voltage of node i, U max At the maximum allowed voltage, I i Is the actual operating current of branch I, I max In order to ensure the maximum value of the current allowed by safety, alpha is a weight, and alpha belongs to the maximum value of the current[0,1]，U margin Is a voltage safety margin; i is margin For current safety margin, f (x) is the model fitness function.
In one embodiment, the constraints include: the power balance constraint condition, the voltage operation constraint condition, the current operation constraint condition, the distributed photovoltaic output constraint condition, the power distribution area topological connectivity constraint condition and the switch action frequency constraint condition.
In one embodiment, solving the power distribution area topology optimization model according to an improved top-over-ambiguity competition algorithm to obtain an optimal power distribution area topology optimization model includes: taking the number of disconnecting switches in the power distribution area topological optimization model as a national dimension, taking the positions of the disconnecting switches in the power distribution area topological optimization model as national positions, and initializing the country; calculating the fitness function of each initialized country according to the model fitness function of the power distribution station area topology optimization model; sequencing the fitness function of each initialized country, dividing each initialized country into an empire country and a colonial country according to a sequencing result, and batching the colonial countries corresponding to the momentum of the empire country to form an initial empire group; carrying out assimilation and revolution operation on each empire country in each initial empire country group, and calculating the strength of the empire country group after the assimilation and revolution operation; according to the strength of each empire country group, carrying out mutual competition among the empire country groups, and dividing the water into the weakest empire countries; and judging whether the iteration termination condition is reached, and taking the iterated empire country group as an optimal power distribution area topology optimization model under the condition that the iteration termination condition is reached.
According to a second aspect of an embodiment of the present invention, a power distribution grid topology optimization system is provided.
In one embodiment, the power distribution grid topology optimization system includes:
the optimization model building module is used for coding a basic loop in the power distribution area by adopting a real number coding mode based on a sequential loop matrix to obtain a power distribution area topology optimization model;
the optimization model solving module is used for solving the power distribution area topology optimization model according to an improved top-over-ambiguity competition algorithm to obtain an optimal power distribution area topology optimization model;
and the model optimization processing module is used for optimizing each operation parameter in the power distribution area by using the optimal power distribution area topology optimization model.
In one embodiment, the operating parameters include at least one of: the system comprises a power distribution network area topology connection information parameter, a power distribution network line model parameter, a power distribution network resistance reactance parameter, a power distribution network node load level parameter, a power distribution network distributed photovoltaic access node parameter and a power distribution network distributed photovoltaic node output level parameter.
In one embodiment, the optimization model building module comprises: the system comprises a variable determination submodule, a function determination submodule and a model construction submodule, wherein the variable determination submodule is used for reordering basic loop circuits in a power distribution area according to the connection sequence of each row of branches in a topological structure of the power distribution area to obtain a sequential basic loop matrix, and the sequential basic loop matrix is used as a model decision variable; the function determination submodule is used for determining a voltage safety margin and a current safety margin according to the evaluation index of the safe operation margin of the power distribution area, and establishing a model fitness function according to the voltage safety margin and the current safety margin; and the model construction submodule is used for constructing a power distribution area topology optimization model according to the model decision variable, the model fitness function and the constraint condition of the power distribution area.
In an embodiment, the variable determination submodule is further configured to, before the sequential basic loop matrix is used as the model decision variable, remove repeated branches in each matrix row in the sequential basic loop matrix, so that each branch in the sequential basic loop matrix corresponds to only one matrix row, and the section switch of the sequential basic loop matrix is located in the matrix row with the smallest power distance.
In one embodiment, the function determination sub-module establishes a calculation formula of a model fitness function according to the voltage safety margin and the current safety margin as follows:
maxf(x)＝α·U margin +(1-α)·I margin
in the formula, N b The number of nodes and the number of branches of the power distribution area are U i For the actual operating voltage of node I, umax is the maximum allowed voltage, I i Is the actual operating current of branch I, I max To ensure the maximum value of current allowed by safety, alpha is weight, and alpha belongs to [0,1 ]]，U margin Is a voltage safety margin; i is margin For current safety margin, f (x) is the model fitness function.
In one embodiment, the constraints include: the power balance constraint condition, the voltage operation constraint condition, the current operation constraint condition, the distributed photovoltaic output constraint condition, the power distribution area topological connectivity constraint condition and the switch action frequency constraint condition.
In one embodiment, the optimization model solving module comprises: the system comprises a country initialization submodule, a function calculation submodule, an empire country group initialization submodule, an empire country strength calculation submodule, an empire country competition submodule and an iteration judgment submodule, wherein the country initialization submodule is used for taking the number of disconnecting switches in a power distribution area topology optimization model as a country solution dimension, taking the positions of the disconnecting switches in the power distribution area topology optimization model as country positions and initializing countries; the function calculation submodule is used for calculating the fitness function of each initialized country according to the model fitness function of the power distribution area topology optimization model; the empire country group initialization submodule is used for sequencing the fitness function of each initialization country, dividing each initialization country into an empire country and a colonial country according to a sequencing result, and batching colonial countries corresponding to the momentum of the empire country to form an initial empire country group; the empire country potential force calculation submodule is used for carrying out assimilation and revolution operations on each empire country in each initial empire country group and calculating the potential force of the empire country group after the assimilation and revolution operations; the empire country competition submodule is used for carrying out mutual competition among empire country groups according to the strength of each empire country group, and the empire country competition submodule is used for dividing the weakest empire country; and the iteration judgment submodule is used for judging whether an iteration termination condition is reached or not, and taking the iterated empire group as an optimal power distribution station topology optimization model under the condition that the judgment result is that the iteration termination condition is reached.
According to a third aspect of embodiments of the present invention, there is provided a computer apparatus.
In some embodiments, the computer device comprises a memory storing a computer program and a processor implementing the steps of the above method when executing the computer program.
According to a fourth aspect of embodiments of the present invention, there is provided a computer-readable storage medium.
In an embodiment, the computer-readable storage medium has stored thereon a computer program which, when being executed by a processor, carries out the steps of the above-mentioned method.
The technical scheme provided by the embodiment of the invention has the following beneficial effects:
according to the method, the power distribution area topological optimization model is constructed by adopting a coding mode based on the sequence ring matrix, the optimal solution is carried out on the power distribution area topological optimization model by adopting an improved empire-meaning competition algorithm, and the optimal power distribution area topological optimization model is obtained to carry out optimization processing on the power distribution area, so that the appearance of an infeasible solution is effectively avoided, the topological optimization speed is increased, the safe operation margin of the power distribution area is maximized, and the safe and stable operation of the power distribution area is ensured.
It is to be understood that both the foregoing general description and the following detailed description are exemplary and explanatory only and are not restrictive of the invention, as claimed.
Drawings
The accompanying drawings, which are incorporated in and constitute a part of this specification, illustrate embodiments consistent with the invention and together with the description, serve to explain the principles of the invention.
Fig. 1 is a schematic flow diagram illustrating a method for power distribution grid topology optimization in accordance with an exemplary embodiment;
FIG. 2 is a schematic diagram illustrating a power distribution grid topology optimization system in accordance with an exemplary embodiment;
FIG. 3 is a schematic block diagram of a computer device shown in accordance with an exemplary embodiment.
Detailed Description
The following description and the drawings sufficiently illustrate specific embodiments herein to enable those skilled in the art to practice them. Portions and features of some embodiments may be included in or substituted for those of others. The scope of the embodiments herein includes the full ambit of the claims, as well as all available equivalents of the claims. The terms "first," "second," and the like, herein are used solely to distinguish one element from another without requiring or implying any actual such relationship or order between such elements. In fact, a first element could be termed a second element, and vice versa. Also, the terms "comprises," "comprising," or any other variation thereof, are intended to cover a non-exclusive inclusion, such that a structure, apparatus, or device that comprises a list of elements does not include only those elements but may include other elements not expressly listed or inherent to such structure, apparatus, or device. Without further limitation, an element defined by the phrases "comprising one of 8230; \8230;" 8230; "does not exclude the presence of additional like elements in a structure, device, or apparatus that comprises the element. The various embodiments are described in a progressive manner, with each embodiment focusing on differences from the other embodiments, and with like parts being referred to one another.
The terms "longitudinal," "lateral," "upper," "lower," "front," "rear," "left," "right," "vertical," "horizontal," "top," "bottom," "inner," "outer," and the like herein, as used herein, are defined as orientations or positional relationships based on the orientation or positional relationship shown in the drawings, and are used for convenience in describing and simplifying the description, but do not indicate or imply that the device or element being referred to must have a particular orientation, be constructed and operated in a particular orientation, and thus should not be construed as limiting the present invention. In the description herein, unless otherwise specified and limited, the terms "mounted," "connected," and "connected" are to be construed broadly, and may include, for example, mechanical or electrical connections, communications between two elements, direct connections, and indirect connections via intermediary media, where the specific meaning of the terms is understood by those skilled in the art as appropriate.
Herein, the term "plurality" means two or more, unless otherwise specified.
Herein, the character "/" indicates that the preceding and following objects are in an "or" relationship. For example, A/B represents: a or B.
Herein, the term "and/or" is an associative relation describing an object, and means that there may be three relations. For example, a and/or B, represents: a or B, or A and B.
It should be understood that, although the steps in the flowchart are shown in order as indicated by the arrows, the steps are not necessarily performed in order as indicated by the arrows. The steps are not performed in the exact order shown and described, and may be performed in other orders, unless explicitly stated otherwise. Moreover, at least some of the steps in the figures may include multiple sub-steps or multiple stages that are not necessarily performed at the same time, but may be performed at different times, and the order of performance of the sub-steps or stages is not necessarily sequential, but may be performed in turn or alternately with other steps or at least some of the sub-steps or stages of other steps.
The various modules in the apparatus or system of the present application may be implemented in whole or in part by software, hardware, and combinations thereof. The modules can be embedded in a hardware form or independent from a processor in the computer device, and can also be stored in a memory in the computer device in a software form, so that the processor can call and execute operations corresponding to the modules.
The embodiments and features of the embodiments of the invention may be combined with each other without conflict.
Fig. 1 illustrates an embodiment of a power distribution grid topology optimization method of the present invention.
In this optional embodiment, the power distribution grid topology optimization method includes:
step S101, coding basic loops in a power distribution area by adopting a real number coding mode based on a sequential loop matrix to obtain a power distribution area topology optimization model;
step S103, solving the power distribution area topological optimization model according to an improved top-over-meaning competition algorithm to obtain an optimal power distribution area topological optimization model;
and S105, optimizing each operation parameter in the power distribution area by using the optimal power distribution area topology optimization model.
In one embodiment, the operating parameters include at least one of: the distribution network node load level parameter comprises a distribution network area topology connection information parameter, a distribution network line model parameter, a distribution network resistance reactance parameter, a distribution network node load level parameter, a distribution network distributed photovoltaic access node parameter and a distribution network distributed photovoltaic node output level parameter.
In one embodiment, when a real number coding mode based on a sequential ring matrix is adopted to perform coding processing on basic ring loops in a power distribution network to obtain a power distribution area topology optimization model, the basic ring loops in the power distribution area can be reordered according to the connection sequence of each row of branches in a power distribution area topology structure to obtain a sequential basic ring matrix, repeated branches in each matrix row in the sequential basic ring matrix are removed, each branch in the sequential basic ring matrix is made to correspond to only one matrix row, a section switch of the sequential basic ring matrix is located in the matrix row with the smallest power distance, and the sequential basic ring matrix after removal processing is used as a model decision variable; determining a voltage safety margin and a current safety margin according to the evaluation index of the safe operation margin of the power distribution area, and establishing a model fitness function according to the voltage safety margin and the current safety margin; and constructing a power distribution station topology optimization model according to the model decision variables, the model fitness function and the constraint conditions of the power distribution station.
In particular, in radial distribution networks, the loop consisting of a tie switch and several section switches is called the basic loop. Defining the basic ring matrix as B RM ＝(m ij ) n×m Wherein n is the number of basic rings, m is the maximum number of the segmented switches in all the basic rings, and the rows with the segmented switch number less than m are complemented by 0. Non-zero element m ij And the branch number of the jth section switch of the ith basic ring is shown.
Reordering each row of the basic ring matrix according to the branch connection order in the topology structure, and then changing into the sequential basic ring matrix O BRM ＝(m ij ) n×m . But sequential basic ring matrix O BRM Repeated branches may exist in each row, if different loops are disconnected and the same branch is formed, the loops still can be formed, radial constraint of a power distribution station area is not met, and a solution formed by corresponding decision variables is an infeasible solution. To avoid the appearance of infeasible solutions to improve reconstruction speed, the sequential fundamental ring matrix O needs to be applied BRM The repeated branches in each row are removed, so that each branch exists in one row at most.
The specific removal rule is as follows: for the occurrence in the sequential fundamental Ring matrix O BRM A section switch S in multiple rows in the sequential basic ring matrix O BRM In the position of m i1j1 ,m i2j2 ,m i3j3 ,…,m iNjN Wherein N is the repeated occurrence number of the branch, and the end node of the branch is N t . When the section switch is turned off and the corresponding contact switch of each row is turned on, n is calculated t Power moment of (T) 1 ,T 2 ,T 3 ,…,T N Where the minimum value of the power moment is T min . Then order
I.e. in the sequential basic ring matrix O BRM Only the row with the smallest power moment is left with the switches S of the remaining rows being assigned 0.
And a power moment T t The specific calculation method is as follows:
wherein L is t For the reverse path formed by the set of branches and the set of nodes traversed by the power flow from the node to the point of entry of the loop in which it is located, W t Is the generalized load of node t, Z t Is a reverse path L t The sum of the impedances of all the upper branches,
is the conjugate of the node load.
Adding the interconnection switch into the sequential basic ring matrix O after the repeated branch is removed BRM The corresponding position of the corresponding row becomes the final sequential ring matrix O BRM 。
And when the model fitness function is established, according to the voltage safety margin and the current safety margin, a calculation formula for establishing the model fitness function is as follows:
max f(x)＝α·U margin +(1-α)·I margin
in the formula, N b The number of nodes and the number of branches of the power distribution area are U i Is the actual operating voltage of node i, U max At the maximum allowed voltage, I i Is the actual operating current of branch I, I max To ensure the maximum value of current allowed by safety, alpha is weight, and alpha belongs to [0,1 ]]，U margin Is a voltage safety margin; i is margin For the current safety margin, f (x) is the model fitness function.
In one embodiment, the constraints include: the power balance constraint condition, the voltage operation constraint condition, the current operation constraint condition, the distributed photovoltaic output constraint condition, the power distribution area topological connectivity constraint condition and the switch action frequency constraint condition. The method comprises the following specific steps:
for the constraint condition of power balance, the calculation formula is as follows:
in the formula, P i ,Q i Respectively injecting active power and reactive power into the node i; u shape i 、U k The voltage amplitudes of the nodes i and k are respectively; g ik 、B ik Respectively the real part and the imaginary part of the system admittance matrix; theta.theta. ik The voltage angle difference between the nodes i and k, and N is the number of nodes.
For the voltage operation constraint condition, the calculation formula is as follows:
U min ≤U i ≤U max
in the formula of U max Is the maximum allowed voltage; u shape i The voltage amplitude of the node i; u shape min Is the minimum value of the allowed voltage.
For the current operation constraint condition, the calculation formula is as follows:
I i ≤I max
in the formula I i Is the actual operating current of branch I, I max The maximum current allowed for safety.
For the constraint condition of distributed photovoltaic output, the calculation formula is as follows:
0≤P i,pv ≤P max,pv
in the formula, P i,pv Actual output, P, for distributed photovoltaic connected to node i max,pv The maximum output of the distributed photovoltaic system connected with the node i.
For the constraint condition of topological connectivity of the power distribution station area, the network topology before and after the switching action needs to meet the radial constraint: for the constraint condition of the number of switching actions, the number of switching actions should be less than the set maximum number of actions.
In one embodiment, solving the power distribution area topology optimization model according to an improved top-over-sense competition algorithm to obtain an optimal power distribution area topology optimization model includes: taking the number of disconnecting switches in the power distribution area topology optimization model as a national solution dimension, taking the positions of the disconnecting switches in the power distribution area topology optimization model as national positions, and initializing the country; calculating the fitness function of each initialized country according to the model fitness function of the power distribution station area topology optimization model; sorting the fitness functions of the initialized countries, dividing the initialized countries into empire nations and colonial countries according to sorting results, and batching colonial countries corresponding to the potential of the empire nations to form initial empire nations; carrying out assimilation and revolution operations on each empire state in each initial empire state group, and calculating the strength of the empire state group after the assimilation and revolution operations; according to the strength of each empire country group, carrying out mutual competition among the empire country groups, and dividing the water into the weakest empire countries; and judging whether the iteration termination condition is reached, and taking the iterated empire country group as an optimal power distribution area topology optimization model under the condition that the iteration termination condition is reached.
In specific application, the steps can be as follows: ,
1) National solutionDimension is equivalent to the number of open switches, from the sequential ring matrix O BRM One switch in each row is randomly selected to be turned off.
a country ＝[a 1 ,a 2 ,…,a n ]
Wherein, a n For selecting the switch to open in the nth loop, a country Is the location of the country.
2) Calculating the fitness function (momentum) of each initialized country and sequencing, dividing the countries into empire country or colonial land countries according to the sequence, and randomly distributing a certain number of colonial lands (matching the momentum of the empire) for the empire to form an initial empire group.
Wherein p is i And P i Respectively, the forces and relative forces of the ith empire, NC i For the number of colonists, N, divided into the ith empire COL Number of colonial sites.
3) The colonial land assimilates movements to the empire; the method is convenient for the empire to better control the colonial land, and essentially represents the process that the colonial land with a poor fitness function draws close to the empire with a good fitness function and changes the self fitness function of the colonial land.
a col ＝a col +[λ×δ.*(a imp -a col )]
Wherein, a col ,a imp Is the location of the colonial and empire regions, λ is the coefficient of assimilation, and δ is a number [0, 1%]N-dimensional vector of (1) [ ·]Indicating rounding.
4) Imperial reform; and disturbing the position of the empire by adopting a Cauchy variation method so as to generate a better fitness function value. The process considered as a reform of the empire itself, the perturbation process is as follows.
a imp,new ＝a imp +[a imp ·Cauchy(0,1))]
Wherein, a imp,new For the new position after the empire transformation, cauchy (0, 1) represents a random variable following a standard Cauchy distribution, [. Cndot.]Indicating rounding.
And calculating the fitness function of the reformed empire, comparing the fitness function with that before reformation, if the fitness function after the empire is reformed is better than that before the reformation, judging that the reformation succeeds, replacing the original position with the new position after the empire is reformed, and otherwise, judging that the reformation fails and maintaining the original position of the empire unchanged.
5) Empire group internal competition; the breeding place with strong potential replaces the original empire with an internal competition mode to become a new empire, namely, the breeding place assimilated and moved to the empire is compared with the application degree function of the empire.
6) Competition among empire nations; the process of self-tendency is expanded by simulating the process that an empire with stronger tendency in the real society occupies and controls the breeding land of the empire with weaker tendency.
The strength of forces of the empire nations group is calculated and sorted according to the following formula.
Wherein, P total,i Is the momentum of the ith empire group, p col,j The dynamism of the jth colonial place of the ith empire, and sigma is a colonial place dynamism influence factor, and depends on the influence degree of the colonial place on the empire group.
And competition among empire nationalities is carried out, so that a strong empire nationality group occupies the weakest colonial place in the weakest empire nationality group. The standardized forces of the empire nations and the probability of each empire nations occupying the colonial area are calculated according to the following formula, and the empire nations are determined by using a roulette method.
Wherein the content of the first and second substances,
is the standardized momentum of the empire group, occopy i The probability that each empire state occupies the weakest colonial area of the weakest empire state group; i is the ith empire.
7) Death of empire group; when an empire group loses all colonists, the empire group dies.
8) And (4) judging whether a termination condition, namely the maximum iteration number is reached, if so, outputting an optimal solution, otherwise, returning to the step (3).
Fig. 2 illustrates one embodiment of a power distribution grid topology optimization system of the present invention.
In this optional embodiment, the power distribution grid topology optimization system includes:
the optimization model building module 201 is configured to perform coding processing on a basic loop in a power distribution area by using a real number coding mode based on a sequential loop matrix to obtain a power distribution area topology optimization model;
the optimization model solving module 203 is used for solving the power distribution area topology optimization model according to an improved top-over-ambiguity competition algorithm to obtain an optimal power distribution area topology optimization model;
and the model optimization processing module 205 is configured to perform optimization processing on each operating parameter in the power distribution area by using the optimal power distribution area topology optimization model.
Correspondingly, in one embodiment, the operating parameters include at least one of: the distribution network node load level parameter comprises a distribution network area topology connection information parameter, a distribution network line model parameter, a distribution network resistance reactance parameter, a distribution network node load level parameter, a distribution network distributed photovoltaic access node parameter and a distribution network distributed photovoltaic node output level parameter.
Correspondingly, in one embodiment, the optimization model building module 201 includes: the system comprises a variable determination submodule (not shown in the figure), a function determination submodule (not shown in the figure) and a model construction submodule (not shown in the figure), wherein the variable determination submodule is used for reordering basic loop circuits in a power distribution area according to the connection sequence of each row of branches in a topological structure of the power distribution area to obtain a sequential basic loop matrix, and the sequential basic loop matrix is used as a model decision variable; the function determination submodule is used for determining a voltage safety margin and a current safety margin according to the evaluation index of the safe operation margin of the power distribution area, and establishing a model fitness function according to the voltage safety margin and the current safety margin; and the model construction submodule is used for constructing a power distribution station topology optimization model according to the model decision variable, the model fitness function and the constraint conditions of the power distribution station.
Correspondingly, in an embodiment, the variable determination submodule (not shown in the figure) is further configured to, before the sequential basic loop matrix is used as the model decision variable, perform elimination processing on repeated branches of each matrix row in the sequential basic loop matrix, so that each branch in the sequential basic loop matrix corresponds to only one matrix row, and the section switch of the sequential basic loop matrix is located in the matrix row with the smallest power distance.
Correspondingly, in one embodiment, the constraint condition includes: the power balance constraint condition, the voltage operation constraint condition, the current operation constraint condition, the distributed photovoltaic output constraint condition, the topological connectivity constraint condition of the distribution transformer area and the switch action times constraint condition.
Correspondingly, in one embodiment, the optimization model solving module 203 includes: the system comprises a country initialization submodule (not shown in the figure), a function calculation submodule (not shown in the figure), an imperial group initialization submodule (not shown in the figure), an imperial strength calculation submodule (not shown in the figure), an imperial competition submodule (not shown in the figure) and an iteration judgment submodule (not shown in the figure), wherein the country initialization submodule is used for initializing the country by taking the number of disconnecting switches in a power distribution area topology optimization model as a country solution dimension and taking the positions of the disconnecting switches in the power distribution area topology optimization model as country positions; the function calculation submodule is used for calculating the fitness function of each initialized country according to the model fitness function of the distribution area topology optimization model; the empire group initialization submodule is used for sequencing the fitness function of each initialization country, dividing each initialization country into an empire main country and a colonial country according to a sequencing result, and batching colonial countries corresponding to the momentum of the empire main country to form an initial empire group; the empire country potential force calculation submodule is used for carrying out assimilation and revolution operations on each empire country in each initial empire country group and calculating the potential force of the empire country group after the assimilation and revolution operations; the empire country competition submodule is used for carrying out mutual competition among empire country groups according to the strength of each empire country group, and the empire countries are the weakest empire countries; and the iteration judgment submodule is used for judging whether an iteration termination condition is met or not, and taking the iterated empire group as an optimal power distribution station area topology optimization model under the condition that the judgment result is that the iteration termination condition is met.
In one embodiment, a computer device is provided, which may be a server, the internal structure of which may be as shown in fig. 3. The computer device includes a processor, a memory, and a network interface connected by a system bus. Wherein the processor of the computer device is configured to provide computing and control capabilities. The memory of the computer device comprises a nonvolatile storage medium and an internal memory. The non-volatile storage medium stores an operating system, a computer program, and a database. The internal memory provides an environment for the operation of an operating system and computer programs in the non-volatile storage medium. The database of the computer device is used for storing static information and dynamic information data. The network interface of the computer device is used for communicating with an external terminal through a network connection. Which computer program is executed by a processor to carry out the steps in the above-described method embodiments.
It will be appreciated by those skilled in the art that the configuration shown in fig. 3 is a block diagram of only a portion of the configuration associated with the inventive arrangements and is not intended to limit the computing devices to which the inventive arrangements may be applied, and that a particular computing device may include more or less components than those shown, or may combine certain components, or have a different arrangement of components.
In an embodiment, there is also provided a computer device comprising a memory and a processor, the memory having stored therein a computer program, the processor implementing the steps of the above method embodiments when executing the computer program.
In an embodiment, a computer-readable storage medium is provided, on which a computer program is stored which, when being executed by a processor, carries out the steps of the above-mentioned method embodiments.
It will be understood by those skilled in the art that all or part of the processes of the methods of the embodiments described above can be implemented by hardware instructions of a computer program, which can be stored in a non-volatile computer-readable storage medium, and when executed, can include the processes of the embodiments of the methods described above. Any reference to memory, storage, database or other medium used in embodiments provided herein may include at least one of non-volatile and volatile memory. Non-volatile Memory may include Read-Only Memory (ROM), magnetic tape, floppy disk, flash Memory, optical storage, or the like. Volatile Memory can include Random Access Memory (RAM) or external cache Memory. By way of illustration and not limitation, RAM can take many forms, such as Static Random Access Memory (SRAM) or Dynamic Random Access Memory (DRAM), for example.
The present invention is not limited to the structures that have been described above and shown in the drawings, and various modifications and changes can be made without departing from the scope thereof. The scope of the invention is limited only by the appended claims.
Claims (16)
1. A topology optimization method for a power distribution area is characterized by comprising the following steps:
coding a basic loop in a power distribution area by adopting a real number coding mode based on a sequential loop matrix to obtain a power distribution area topology optimization model;
solving the power distribution area topology optimization model according to an improved top-over-ambiguity competition algorithm to obtain an optimal power distribution area topology optimization model;
and optimizing each operation parameter in the power distribution area by using the optimal power distribution area topology optimization model.
2. The power distribution grid topology optimization method of claim 1, wherein the operating parameters comprise at least one of:
the system comprises a power distribution network area topology connection information parameter, a power distribution network line model parameter, a power distribution network resistance reactance parameter, a power distribution network node load level parameter, a power distribution network distributed photovoltaic access node parameter and a power distribution network distributed photovoltaic node output level parameter.
3. The power distribution area topology optimization method according to claim 1, wherein coding a basic loop in the power distribution network by using a real number coding mode based on a sequential loop matrix to obtain a power distribution area topology optimization model comprises:
reordering basic ring loops in a power distribution area according to the connection sequence of each row of branch circuits in the topological structure of the power distribution area to obtain a sequence basic ring matrix, and taking the sequence basic ring matrix as a model decision variable;
determining a voltage safety margin and a current safety margin according to the evaluation index of the safe operation margin of the power distribution area, and establishing a model fitness function according to the voltage safety margin and the current safety margin;
and constructing a topological optimization model of the power distribution area according to the model decision variable, the model fitness function and the constraint condition of the power distribution area.
4. The distribution network topology optimization method according to claim 3, wherein a sequential loop matrix real number coding based coding mode is adopted to code a basic loop in the distribution network, and the obtaining of the distribution network topology optimization model further comprises:
before the sequence basic ring matrix is used as a model decision variable, repeated branches of each matrix row in the sequence basic ring matrix are removed, each branch in the sequence basic ring matrix is enabled to correspond to only one matrix row, and the section switch of the sequence basic ring matrix is located in the matrix row with the minimum power distance.
5. The power distribution grid topology optimization method of claim 3, wherein a calculation formula for establishing a model fitness function according to the voltage safety margin and the current safety margin is as follows:
max f(x)＝α·U margin +(1-α)·I margin
in the formula, N b The number of nodes and the number of branches of the power distribution area are U i For the actual operating voltage of node i, U max At the maximum allowed voltage, I i For the actual operating current of branch I, I max To ensure the maximum value of current allowed by safety, alpha is weight, and alpha is equal to 0,1]，U margin Is the voltage safety margin; I.C. A margin For current safety margin, f (x) is the model fitness function.
6. The power distribution grid topology optimization method according to claim 3, wherein the constraints comprise: the power balance constraint condition, the voltage operation constraint condition, the current operation constraint condition, the distributed photovoltaic output constraint condition, the power distribution area topological connectivity constraint condition and the switch action frequency constraint condition.
7. The power distribution grid topology optimization method according to claim 3, wherein solving the power distribution grid topology optimization model according to an improved top-over-sense competition algorithm to obtain an optimal power distribution grid topology optimization model comprises:
taking the number of disconnecting switches in the power distribution area topology optimization model as a national solution dimension, taking the positions of the disconnecting switches in the power distribution area topology optimization model as national positions, and initializing the country;
calculating a fitness function of each initialized country according to the model fitness function of the power distribution station area topology optimization model;
sorting the fitness functions of the initialized countries, dividing the initialized countries into empire nations and colonial countries according to sorting results, and batching colonial countries corresponding to the potential of the empire nations to form initial empire nations;
carrying out assimilation and revolution operations on each empire state in each initial empire state group, and calculating the strength of the empire state group after the assimilation and revolution operations;
according to the strength of each empire group, carrying out mutual competition among the empire groups, and dividing the weak empire;
and judging whether an iteration termination condition is reached or not, and taking the iterated empire group as an optimal power distribution station topology optimization model under the condition that the iteration termination condition is reached according to the judgment result.
8. A power distribution block topology optimization system, comprising:
the optimization model building module is used for coding a basic loop in the power distribution area by adopting a real number coding mode based on a sequential loop matrix to obtain a topology optimization model of the power distribution area;
the optimization model solving module is used for solving the power distribution area topology optimization model according to an improved top-over-ambiguity competition algorithm to obtain an optimal power distribution area topology optimization model;
and the model optimization processing module is used for optimizing each operation parameter in the power distribution area by using the optimal power distribution area topology optimization model.
9. The power distribution grid topology optimization system of claim 8, wherein the operating parameters comprise at least one of:
the distribution network node load level parameter comprises a distribution network area topology connection information parameter, a distribution network line model parameter, a distribution network resistance reactance parameter, a distribution network node load level parameter, a distribution network distributed photovoltaic access node parameter and a distribution network distributed photovoltaic node output level parameter.
10. The power distribution substation topology optimization system of claim 8, wherein the optimization model building module comprises: a variable determination submodule, a function determination submodule, and a model construction submodule, wherein,
the variable determination submodule is used for reordering the basic loop circuits in the power distribution area according to the connection sequence of each row of branch circuits in the topological structure of the power distribution area to obtain a sequential basic loop matrix, and the sequential basic loop matrix is used as a model decision variable;
the function determination submodule is used for determining a voltage safety margin and a current safety margin according to the evaluation index of the safe operation margin of the power distribution area, and establishing a model fitness function according to the voltage safety margin and the current safety margin;
and the model construction submodule is used for constructing a power distribution station topology optimization model according to the model decision variable, the model fitness function and the constraint conditions of the power distribution station.
11. The power distribution substation topology optimization system according to claim 10, wherein the variable determination submodule is further configured to remove repeated branches in each matrix row of the sequential basic loop matrix before using the sequential basic loop matrix as the model decision variable, so that each branch of the sequential basic loop matrix corresponds to only one matrix row, and the section switch of the sequential basic loop matrix is located in the matrix row with the smallest power distance.
12. The power distribution grid topology optimization system of claim 10, wherein the function determination sub-module establishes a model fitness function based on the voltage safety margin and the current safety margin according to the calculation formula:
max f(x)＝α·U margin +(1-α)·I margin
in the formula, N b The number of nodes and branches of the distribution area, U i For the actual operating voltage of node i, U max At the maximum allowed voltage, I i For the actual operating current of branch I, I max To ensure the maximum value of current allowed by safety, alpha is weight, and alpha is equal to 0,1]，U margin Is the voltage safety margin; i is margin For current safety margin, f (x) is the model fitness function.
13. The power distribution grid topology optimization system of claim 10, wherein the constraints comprise: the power balance constraint condition, the voltage operation constraint condition, the current operation constraint condition, the distributed photovoltaic output constraint condition, the power distribution area topological connectivity constraint condition and the switch action frequency constraint condition.
14. The power distribution grid topology optimization system of claim 10, wherein the optimization model solving module comprises: a country initialization submodule, a function calculation submodule, an empire group initialization submodule, an empire momentum calculation submodule, an empire competition submodule and an iteration judgment submodule, wherein,
the country initialization submodule is used for initializing a country by taking the number of disconnecting switches in the distribution area topology optimization model as a country solution dimension and taking the positions of the disconnecting switches in the distribution area topology optimization model as country positions;
the function calculation submodule is used for calculating the fitness function of each initialized country according to the model fitness function of the power distribution area topology optimization model;
the empire country group initialization submodule is used for sequencing the fitness function of each initialization country, dividing each initialization country into an empire country and a colonial country according to a sequencing result, and batching colonial countries corresponding to the momentum of the empire country to form an initial empire country group;
the empire country potential force calculation submodule is used for carrying out assimilation and revolution operations on each empire country in each initial empire country group and calculating the potential force of the empire country group after the assimilation and revolution operations;
the empire country competition submodule is used for carrying out mutual competition among empire country groups according to the strength of each empire country group, and the empire countries are the weakest empire countries;
and the iteration judgment submodule is used for judging whether an iteration termination condition is met or not, and taking the iterated empire group as an optimal power distribution station area topology optimization model under the condition that the judgment result is that the iteration termination condition is met.
15. A computer device comprising a memory and a processor, the memory storing a computer program, characterized in that the processor, when executing the computer program, implements the steps of the method of any of claims 1 to 7.
16. A computer-readable storage medium, on which a computer program is stored, which, when being executed by a processor, carries out the steps of the method of any one of claims 1 to 7.
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