CN114254558A - Comprehensive energy transformer substation planning method and device and terminal equipment - Google Patents

Comprehensive energy transformer substation planning method and device and terminal equipment Download PDF

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CN114254558A
CN114254558A CN202111439925.2A CN202111439925A CN114254558A CN 114254558 A CN114254558 A CN 114254558A CN 202111439925 A CN202111439925 A CN 202111439925A CN 114254558 A CN114254558 A CN 114254558A
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高明
舒建华
左红群
葛志峰
柏帆
裘森强
王永利
花之蕾
韩煦
王亚楠
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Ninghai Yancangshan Electric Power Construction Co ltd
State Grid Zhejiang Electric Power Co Ltd Ninghai County Power Supply Co
North China Electric Power University
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State Grid Zhejiang Electric Power Co Ltd Ninghai County Power Supply Co
North China Electric Power University
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Abstract

The application is suitable for the technical field of transformer substation planning, and provides a comprehensive energy transformer substation planning method and device terminal equipment, wherein the comprehensive energy transformer substation planning method comprises the following steps: establishing a comprehensive energy transformer substation planning model; the comprehensive energy transformer substation planning model comprises a target function and constraint conditions; the target function represents the total investment cost of the comprehensive energy transformer substation; the constraint condition comprises one or more of a power flow constraint, a logic gate constraint, a power supply range constraint and an operation capacity constraint; calculating an optimal planning scheme which enables the total investment cost to be lowest according to the comprehensive energy transformer substation planning model; and determining the site selection and the capacity of the comprehensive energy transformer substation according to the optimal planning scheme. The method aims at minimizing the cost without influencing the efficiency, plans a plurality of comprehensive energy substations in the area as a whole, and calculates an optimal planning scheme meeting constraint conditions, thereby realizing the maximum resource saving and improving the power supply efficiency of the comprehensive energy substations in the area.

Description

Comprehensive energy transformer substation planning method and device and terminal equipment
Technical Field
The application belongs to the technical field of transformer substation planning, and particularly relates to a comprehensive energy transformer substation planning method, a comprehensive energy transformer substation planning device and terminal equipment.
Background
On the background of reformation from a conventional transformer substation to a comprehensive energy transformer substation, how to plan site selection and power supply range of the comprehensive energy transformer substation becomes a core technical problem. Aiming at the demand target of most efficient planning and site selection of the comprehensive energy transformer substation in a specific environment, a planning network diagram with the maximum utilization efficiency and the lowest cost of the transformer substation is required to be constructed according to the mutual relation and the overall planning coordination among the transformer substations.
In recent years, some scholars research a planning method of an integrated energy transformer substation, the general process is to plan the scale and the capacity of the transformer substation according to the electricity demand of each local area, each transformer substation supports the electricity supply of the corresponding area, and the transformer substations are rarely linked. Such an integrated energy substation planning method is prone to waste of capital and resources and difficult to maximize the power supply efficiency of the integrated energy substation in the area.
Disclosure of Invention
In view of this, the embodiment of the invention provides a method and a device for planning an integrated energy substation and a terminal device, so as to improve the integrated power supply efficiency of multiple integrated energy substations in a region.
The application is realized by the following technical scheme:
in a first aspect, an embodiment of the present application provides a method for planning an integrated energy substation, including: establishing a comprehensive energy transformer substation planning model; the comprehensive energy transformer substation planning model comprises a target function and constraint conditions; the objective function represents the total investment cost of the comprehensive energy transformer substation; the constraint condition comprises one or more of a power flow constraint, a logic gate constraint, a power supply range constraint and an operation capacity constraint; calculating an optimal planning scheme which enables the total investment cost to be lowest according to the comprehensive energy transformer substation planning model; and determining the site selection and the capacity of the comprehensive energy transformer substation according to the optimal planning scheme.
In the embodiment of the application, the establishment of the comprehensive energy transformer substation planning model aims at minimizing the cost without influencing the efficiency, a plurality of comprehensive energy transformer substations in the area are planned as a whole, and the optimal planning scheme meeting the constraint condition is calculated, so that the resource saving is realized to the greatest extent, and the power supply efficiency of the comprehensive energy transformer substations in the area is improved.
Based on the first aspect, in some embodiments, the establishing an integrated energy substation planning model includes: determining the influence factors of the investment cost of the comprehensive energy transformer substation; constructing a target function of a planning model of the comprehensive energy transformer substation based on the influence factors of the investment cost of the comprehensive energy transformer substation; and constructing constraint conditions, and determining a comprehensive energy transformer substation planning model according to the objective function and the constraint conditions.
Based on the first aspect, in some embodiments, the objective function of the integrated energy substation planning model is:
Figure BDA0003382578040000021
wherein F is the total investment cost, i is the number of planning stages, i is 1,2, …, N, F1iFor the basic investment costs of the substation in stage i, F2iCost for constructing a line fair, F3iFor power network loss costs, F4iThe investment cost of the transformer is reduced.
Based on the first aspect, in some embodiments, the constraint is:
Figure BDA0003382578040000022
0≤T0,j≤T1,j≤…≤TN-1,j≤TN,j≤Tj-max
Dj,k≤Dj-max
Figure BDA0003382578040000023
Pi,j≤γTi,jPmax
wherein, when L is equal to 1,2, …, N, substation number j is equal to 1,2, …, M, load point number K is equal to 1,2, …, K, and L is equal toi,j,kWhen the power supply relation is equal to 1, the power supply relation exists, otherwise, the power supply is not supplied; t isi,jTransformer station already put into operation at i stage for j-th substationNumber, Tj_maxThe number of the transformers which can be accommodated by the jth substation at most; dj,kIs the linear distance between the jth substation and the kth load point, Dj_maxThe maximum power supply radius of the transformer substation is obtained; pi,j,kTransmitting power to the kth load for the jth substation in the ith stage; pmaxThe maximum power capacity that the transformer can bear under the current voltage level, and gamma is the load factor of the transformer.
Based on the first aspect, in some embodiments, the calculating an optimal planning scheme that minimizes the total investment cost according to the integrated energy substation planning model includes: initializing a population and parameters of a differential evolution algorithm, wherein individuals in the population represent the planning scheme of the comprehensive energy transformer substation; calculating the fitness value of the individual according to the total investment cost calculated by the individual bringing objective function; and carrying out iterative cycle of variation, intersection and selection operations on the population through the differential evolution algorithm on the basis of the fitness value, and outputting an optimal planning scheme when an iteration termination condition is met.
Based on the first aspect, in some embodiments, the performing variation operations on the population includes: xi,tRandomly generating three mutually different integers r for the ith individual in the t generation population1,r2,r3E {1,2, …, N }, and r1,r2,r3I four numbers are different from each other, and a variant individual V is generated according to random integersi,t(ii) a Wherein the content of the first and second substances,
Figure BDA0003382578040000031
f is a variation factor F epsilon [0,2](ii) a If Vi,tIs not in [ X ]min,Xmax]In then order Vi,t＝Xmin+rand(0,1)*(Xmax-Xmin) Wherein [ X ]min,Xmax]For a given search space range of variables, rand (0,1) is a random number uniformly distributed within (0, 1).
Based on the first aspect, in some embodiments, the selecting a population includes: generating a tth generation candidate individual U after mutation and cross operationi,tAnd the targetIndividual Xi,tCompetition is carried out to obtain t +1 generation individual Xi,t+1，Xi,t+1The calculation expression of (a) is:
Figure BDA0003382578040000032
where f is the fitness function, in Ui,tAnd Xi,tAnd selecting the one with the optimal fitness function value as the t +1 th generation individual to replace the t-th generation individual.
In a second aspect, an embodiment of the present application provides an integrated energy substation planning apparatus, the apparatus includes: the model building module is used for building a comprehensive energy transformer substation planning model; the comprehensive energy transformer substation planning model comprises a target function and constraint conditions; the objective function represents the total investment cost of the comprehensive energy transformer substation; the constraint condition comprises one or more of a power flow constraint, a logic gate constraint, a power supply range constraint and an operation capacity constraint; the calculation module is used for calculating an optimal planning scheme which enables the total investment cost to be lowest according to the comprehensive energy transformer substation planning model; and the planning module is used for determining the site selection and the capacity of the comprehensive energy transformer substation according to the optimal planning scheme.
In a third aspect, an embodiment of the present application provides a terminal device, which includes a memory, a processor, and a computer program stored in the memory and executable on the processor, where the processor, when executing the computer program, implements the steps of the method for planning an integrated energy substation according to any one of the first aspect.
In a fourth aspect, the present embodiments provide a computer-readable storage medium, which stores a computer program, and when the computer program is executed by a processor, the method for planning an integrated energy substation according to any one of the first aspect is implemented.
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 specification.
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In order to more clearly illustrate the technical solutions in the embodiments of the present application, the drawings needed to be used in the embodiments or the prior art descriptions will be briefly described below, and it is obvious that the drawings in the following description are only some embodiments of the present application, and it is obvious for those skilled in the art to obtain other drawings based on these drawings without inventive exercise.
Fig. 1 is a schematic flow chart of a method for planning an integrated energy substation provided in an embodiment of the present application;
fig. 2 is an algorithm flowchart of a method for planning an integrated energy substation according to an embodiment of the present application;
fig. 3 is a function convergence graph of the method for planning an integrated energy substation according to the embodiment of the present application;
fig. 4 is a schematic structural diagram of an integrated energy substation planning device provided in an embodiment of the present application;
fig. 5 is a schematic structural diagram of a terminal device according to an embodiment of the present application.
Detailed Description
In the following description, for purposes of explanation and not limitation, specific details are set forth, such as particular system structures, techniques, etc. in order to provide a thorough understanding of the embodiments of the present application. It will be apparent, however, to one skilled in the art that the present application may be practiced in other embodiments that depart from these specific details. In other instances, detailed descriptions of well-known systems, devices, circuits, and methods are omitted so as not to obscure the description of the present application with unnecessary detail.
It will be understood that the terms "comprises" and/or "comprising," when used in this specification and the appended claims, specify the presence of stated features, integers, steps, operations, elements, and/or components, but do not preclude the presence or addition of one or more other features, integers, steps, operations, elements, components, and/or groups thereof.
It should also be understood that the term "and/or" as used in this specification and the appended claims refers to and includes any and all possible combinations of one or more of the associated listed items.
As used in this specification and the appended claims, the term "if" may be interpreted contextually as "when", "upon" or "in response to" determining "or" in response to detecting ". Similarly, the phrase "if it is determined" or "if a [ described condition or event ] is detected" may be interpreted contextually to mean "upon determining" or "in response to determining" or "upon detecting [ described condition or event ]" or "in response to detecting [ described condition or event ]".
Furthermore, in the description of the present application and the appended claims, the terms "first," "second," "third," and the like are used for distinguishing between descriptions and not necessarily for describing or implying relative importance.
Reference throughout this specification to "one embodiment" or "some embodiments," or the like, means that a particular feature, structure, or characteristic described in connection with the embodiment is included in one or more embodiments of the present application. Thus, appearances of the phrases "in one embodiment," "in some embodiments," "in other embodiments," or the like, in various places throughout this specification are not necessarily all referring to the same embodiment, but rather "one or more but not all embodiments" unless specifically stated otherwise. The terms "comprising," "including," "having," and variations thereof mean "including, but not limited to," unless expressly specified otherwise.
Fig. 1 is a schematic flow chart of a method for planning an integrated energy substation according to an embodiment of the present application, and the method for planning an integrated energy substation according to the present application is described in detail below with reference to fig. 1:
step 101: and establishing a comprehensive energy transformer substation planning model.
The optimization target of the model is the total investment cost, but due to the fact that planning is performed in stages, the comprehensive energy transformer substation planning model is constructed based on the whole life cycle cost, the influence factors of the cost in each stage are comprehensively considered, and the comprehensive energy transformer substation planning model with the aim of minimizing the total investment cost without influencing the efficiency is established.
Firstly, determining influence factors of investment cost of the comprehensive energy transformer substation, and constructing an objective function of a planning model of the comprehensive energy transformer substation based on the influence factors of the investment cost of the comprehensive energy transformer substation, wherein the objective function represents the total investment cost of the comprehensive energy transformer substation. The influence factors to be considered include a plurality of schemes of the total electric load of the area to be planned in the target year, the number of the newly-built substations and the capacity combination of all the newly-built substations, and the expense of the initial station address of each newly-built substation and the construction line shared cost of different initial station addresses.
The objective function of the comprehensive energy transformer substation planning model considering the influence factors is as follows:
Figure BDA0003382578040000061
wherein F is the total investment cost, i is the number of planning stages, i is 1,2, …, N, F1iFor the basic investment costs of the substation in stage i, F2iCost for constructing a line fair, F3iFor power network loss costs, F4iThe investment cost of the transformer is reduced.
Figure BDA0003382578040000062
Figure BDA0003382578040000063
Figure BDA0003382578040000064
Figure BDA0003382578040000071
Figure BDA0003382578040000072
Wherein, the planning stage i is 1,2, …, N, the substation number j is 1,2, …, M, the load point number K is 1,2, …, K, Csi,jInitial investment (without transformer investment cost) us for building the jth substation under the ith stagei,jFor annual operation and maintenance of the jth substation in the ith planning phase, r0For discount rate, H is the number of years included in a stage, α is the unit line cost, Dj,kIs the straight-line distance between the jth substation and the kth load point, (x)j，yj) And (x)k，yk) Respectively as coordinates of the substation and the load point, Si,jAnd Li,j,kInteger variables (when S is 0 or 1) that are alli,jWhen 1, it indicates that the jth substation is put into operation, otherwise it indicates that it is not put into operation), when Li,j,kWhen 1, indicating that there is a power supply relationship, otherwise, indicating that no power supply exists), Pi,j,kThe power transmitted to the kth load in the ith stage for the jth substation, U is the current voltage level, beta1To the electricity price, beta2Is a line resistance per unit length, beta3Hours of annual power supply, CT0Initial investment required for adding a transformer, Ti,jAnd (4) putting the number of the transformers into operation in the ith stage of the jth transformer substation, wherein ut is the capital required by annual operation and maintenance of the transformers, and ms, mt and mg are the depreciation years of investment cost for building the transformer substation, the transformers and lines respectively.
And constructing constraint conditions, and determining a comprehensive energy transformer substation planning model according to the objective function and the constraint conditions. The constraint condition comprises one or more of a power flow constraint, a logic gate constraint, a power supply range constraint and an operation capacity constraint.
Specifically, the constraint conditions are:
Figure BDA0003382578040000073
wherein, when L is equal to 1,2, …, N, substation number j is equal to 1,2, …, M, load point number K is equal to 1,2, …, K, and L is equal toi,j,kWhen the power supply relation is equal to 1, the power supply relation exists, otherwise, the power supply is not supplied; t isi,jThe number of the transformers which have been put into operation in the ith stage, T, for the jth substationj_maxThe number of the transformers which can be accommodated by the jth substation at most; dj,kIs the linear distance between the jth substation and the kth load point, Dj_maxThe maximum power supply radius of the transformer substation is obtained; pi,j,kTransmitting power to the kth load for the jth substation in the ith stage; pmaxThe maximum power capacity that the transformer can bear under the current voltage level, and gamma is the load factor of the transformer.
The constraint conditions can constrain the optimization direction, so that the planning result meets the actual situation of transformer substation planning.
Step 102: and calculating the optimal plan which enables the total investment cost to be lowest according to the comprehensive energy transformer substation planning model.
And coding the planning scheme conforming to the comprehensive energy transformer substation planning model into an individual, and calculating an optimal solution through a differential evolution algorithm. The differential evolution algorithm involves five control parameters, namely a population size N, a mutation operator F, a cross probability factor CR, a maximum iteration number T and a termination condition. As shown in fig. 2, the overall process of the differential evolution algorithm includes the following steps: coding and initializing, individual evaluation, mutation operation, cross operation and selection operation.
A1, encoding and initialization
Let the optimization problem to be solved be
Figure BDA0003382578040000081
The differential evolution algorithm adopts real number coding, the population scale is N, the independent variable of the solved problem has D dimension, the maximum iteration time T is specified, and the variation factor F belongs to [0,2 ]]The cross probability factor CR ∈ [0,1 ]]The current evolutionary algebra is t. Then the ith individual X in the population of the t generationi,tComprises the following steps:
Figure BDA0003382578040000082
the specified search space range of the variable is [ X ]min,Xmax]Each parameter in the above formula
Figure BDA0003382578040000083
In a specified value range [ X ]min,Xmax]Internally randomly generated, whose value range is expressed as follows:
Figure BDA0003382578040000084
the initialization population is randomly generated within this range of values.
Let evolution algebra t be 0 at [ X [ ]min,Xmax]Randomly generating N individuals in the range to form an initial population
Figure BDA0003382578040000091
A2, evaluation of individuals
Calculating each individual Xi,tFitness function value f (X)i,t)。
A3, mutation operation
Xi,tRandomly generating three mutually different integers r for the ith individual in the t generation population1,r2,r3E {1,2, …, N }, and r1,r2,r3I four numbers are different from each other, and a variant individual V is generated according to random integersi,t. Wherein the content of the first and second substances,
Figure BDA0003382578040000092
f is a variation factor F epsilon [0,2]。
If Vi,tIs not in [ X ]min,Xmax]In then order Vi,t＝Xmin+rand(0,1)*(Xmax-Xmin) Wherein [ X ]min,Xmax]For a given search space range of variables, rand (0,1) is uniformly distributed within (0,1)The random number of (2).
The differential mutation operation is the most important operation in the differential evolution algorithm.
A4, crossover operation
Variant individuals V generated by the varianti,tWith the target individual Xi,tPerforming cross operation to generate test individuals Ui,t。
First, a random integer randn is generatediTo ensure evolution of the individuals, test individuals U were selected randomlyi,tAt least one bit consisting of Vi,tThe other bits are determined by the cross probability CR, which bit is specified by Xi,tWhich contributed from Vi,tA contribution. The test subject U was obtained according to the following formula (12)i,t，
Figure BDA0003382578040000093
Figure BDA0003382578040000094
Formula of middle randjIs located at [0,1 ]]Uniformly distributed random real numbers in between, and randniIs a randomly generated dimension index number within {1, 2., D }, which guarantees
Figure BDA0003382578040000095
At least one bit of the variance vector
Figure BDA0003382578040000096
A contribution. Where CR is the crossover probability factor, also located at [0,1 ]]Is constant. The differential evolution algorithm introduces crossover operations in order to increase the diversity of the population.
A5, selection operation
The selection operation adopts a greedy selection strategy, and the tth generation candidate individuals U generated after the mutation and cross operationi,tWith the target individual Xi,tCompetition is carried out to obtain t +1 generation individual Xi,t+1，Xi,t+1The calculation expression of (a) is:
Figure BDA0003382578040000101
where f is the fitness function, in Ui,tAnd Xi,tAnd selecting the optimum fitness function value as the t +1 th generation individual, replacing the t-th generation individual, and increasing the iteration counter t by 1.
And (3) performing an iterative cycle of variation, intersection and selection operations on the population by using the fitness value as a basis through a differential evolution algorithm as shown in fig. 2, and outputting an optimal solution when an iteration termination condition is met or the maximum iteration time T is reached, wherein the optimal solution is an optimal planning scheme.
Step 103: and determining the site selection and the capacity of the comprehensive energy transformer substation according to the optimal planning scheme.
In the case of the example 1, the following examples are given,
the comprehensive energy transformer substation planning method is applied to planning of 110kV transformer substations in a certain county, and a planning result is obtained and corresponding analysis is carried out.
The county is administered with 3 offices and 7 towns, which are divided into 10 load areas and numbered correspondingly in the calculation example. In order to simplify model calculation, regional loads are replaced by central load points, substation planning is conducted on the region for 6 years only, the current planning year is 2018, the planning target year is 2024, and the planning is conducted in 3 stages, wherein each stage is two years. The load requirements and coordinate locations of the various zones at different stages are shown in table 1.
TABLE 1 annual load demand and coordinates of each load zone at different planning stages
Figure BDA0003382578040000111
By the end of 2017, the county grid had 5 total 110kV substations, which were numbered, without consideration of the customer-specific substation (not included in the plan). And 8 spare substation sites are selected and numbered through geographic environment survey, and the optimal alternative site is selected for planning and constructing a new site under the condition of considering the existing substation. The power supply membership relationship between the existing 110kV transformer substation in the county and a power supply load area is shown in table 2, the site coordinates and the capacity of the existing transformer substation are shown in table 3, and the site coordinates of the standby transformer substation are shown in table 4.
Table 22017 administrative affiliation of 110kV power supply in county
Figure BDA0003382578040000112
TABLE 3 existing substation site and Capacity
Figure BDA0003382578040000121
TABLE 4 Standby substation site
Figure BDA0003382578040000122
And (5) simulating by adopting matlab to obtain a simulation result, and analyzing based on the simulation result. The mathematical model parameters were set as shown in table 5 by consulting the substation design specification manual and referring to the actual engineering case.
TABLE 5 model parameter Table
Figure BDA0003382578040000123
The initial investment cost of all transformer substations is set to be 5000 ten thousand yuan, and the annual operation and maintenance cost is set to be 20 ten thousand yuan. The capacity of the newly added transformer is 50MVA, the investment cost is 1100 ten thousand yuan, and the annual operation and maintenance cost is 10 ten thousand yuan. The maximum number of iterations is defined as 100 and the convergence curve of the economic investment optimization objective obtained with Matlab software is shown in fig. 3. It can be seen from fig. 3 that the objective function reaches steady state around 45 iterations, resulting in an optimized minimum, i.e., a total economic investment of l.613 billion dollars.
The substation layout planning schemes obtained according to the decision variable results obtained by the simulation solution are shown in tables 6 and 7. The specific embodiment is as follows:
planning stage 1: a new station 1 is built at an alternative station site 3, the power supply of a 10 th load area is changed from an existing station 2 to the new station 1, and the new station 1 is provided with 1 50MVA transformer
And 2, planning stage: a new station 2 is built at the alternative site 2 and the power supply of the 4 th load area is changed from the existing station 2 to the new station 2. The new building station 2 is equipped with 1 50MVA transformer. Meanwhile, 1 50MVA transformer is newly installed for the expansion of the existing station 1 and the existing station 5.
TABLE 6 planned Power supply membership
Figure BDA0003382578040000131
TABLE 7 planned substation Capacity
Figure BDA0003382578040000141
And 3, planning stage: a new build station 3 is built at an alternative site 6 and a new build station 4 is built at an alternative site 7. The power supply of the 6 th load area is changed from the existing station 3 to the new station 3, and the power supply of the 7 th load area is changed from the existing station 4 to the new station 4. The new building station 3 and the new building station 4 are both provided with 1 50MVA transformer. Meanwhile, the newly built station 1 is expanded, and 1 50MVA transformer is newly installed.
It should be understood that, the sequence numbers of the steps in the foregoing embodiments do not imply an execution sequence, and the execution sequence of each process should be determined by its function and inherent logic, and should not constitute any limitation to the implementation process of the embodiments of the present application.
Corresponding to the method for planning an integrated energy substation of the foregoing embodiment, fig. 4 shows a block diagram of a device for planning an integrated energy substation provided in the embodiment of the present application, and for convenience of description, only the parts related to the embodiment of the present application are shown.
Referring to fig. 4, the integrated energy substation planning apparatus in the embodiment of the present application may include: a model building module 310, a calculation module 320, and a planning module 330.
The model establishing module 310 is used for establishing a comprehensive energy transformer substation planning model; the comprehensive energy transformer substation planning model comprises a target function and constraint conditions; the objective function represents the total investment cost of the comprehensive energy transformer substation; the constraint condition comprises one or more of a power flow constraint, a logic gate constraint, a power supply range constraint and an operation capacity constraint.
And the calculating module 320 is used for calculating an optimal planning scheme which enables the total investment cost to be the lowest according to the comprehensive energy transformer substation planning model.
And the planning module 330 is used for determining the site selection and the capacity of the integrated energy transformer substation according to the optimal planning scheme.
It should be noted that, for the information interaction, execution process, and other contents between the above-mentioned devices/units, the specific functions and technical effects thereof are based on the same concept as those of the embodiment of the method of the present application, and specific reference may be made to the part of the embodiment of the method, which is not described herein again.
It will be apparent to those skilled in the art that, for convenience and brevity of description, only the above-mentioned division of the functional units and modules is illustrated, and in practical applications, the above-mentioned function distribution may be performed by different functional units and modules according to needs, that is, the internal structure of the apparatus is divided into different functional units or modules to perform all or part of the above-mentioned functions. Each functional unit and module in the embodiments may be integrated in one processing unit, or each unit may exist alone physically, or two or more units are integrated in one unit, and the integrated unit may be implemented in a form of hardware, or in a form of software functional unit. In addition, specific names of the functional units and modules are only for convenience of distinguishing from each other, and are not used for limiting the protection scope of the present application. The specific working processes of the units and modules in the system may refer to the corresponding processes in the foregoing method embodiments, and are not described herein again.
An embodiment of the present application further provides a terminal device, and referring to fig. 5, the terminal device 500 may include: at least one processor 510, a memory 520, and a computer program stored in the memory 520 and executable on the at least one processor 510, the processor 510, when executing the computer program, implementing the steps of any of the various method embodiments described above, such as the steps 101 to 103 in the embodiment shown in fig. 1. Alternatively, the processor 510, when executing the computer program, implements the functions of the modules/units in the above-described device embodiments, such as the functions of the modules 310 to 330 shown in fig. 4.
Illustratively, the computer program may be divided into one or more modules/units, which are stored in the memory 520 and executed by the processor 510 to accomplish the present application. The one or more modules/units may be a series of computer program segments capable of performing specific functions, which are used to describe the execution of the computer program in the terminal device 500.
Those skilled in the art will appreciate that fig. 5 is merely an example of a terminal device and is not limiting and may include more or fewer components than shown, or some components may be combined, or different components such as input output devices, network access devices, buses, etc.
The Processor 510 may be a Central Processing Unit (CPU), other general purpose Processor, a Digital Signal Processor (DSP), an Application Specific Integrated Circuit (ASIC), a Field-Programmable Gate Array (FPGA) or other Programmable logic device, discrete Gate or transistor logic, discrete hardware components, etc. A general purpose processor may be a microprocessor or the processor may be any conventional processor or the like.
The memory 520 may be an internal storage unit of the terminal device, or may be an external storage device of the terminal device, such as a plug-in hard disk, a Smart Media Card (SMC), a Secure Digital (SD) Card, a Flash memory Card (Flash Card), and the like. The memory 520 is used for storing the computer programs and other programs and data required by the terminal device. The memory 520 may also be used to temporarily store data that has been output or is to be output.
The bus may be an Industry Standard Architecture (ISA) bus, a Peripheral Component Interconnect (PCI) bus, an extended ISA (E integrated energy substation plan) bus, or the like. The bus may be divided into an address bus, a data bus, a control bus, etc. For ease of illustration, the buses in the figures of the present application are not limited to only one bus or one type of bus.
The method for planning the comprehensive energy transformer substation provided by the embodiment of the application can be applied to terminal devices such as computers, wearable devices, vehicle-mounted devices, tablet computers, notebook computers, netbooks, Personal Digital Assistants (PDAs), Augmented Reality (AR)/Virtual Reality (VR) devices and mobile phones, and the embodiment of the application does not limit the specific types of the terminal devices at all.
The embodiment of the application also provides a computer-readable storage medium, which stores a computer program, and when the computer program is executed by a processor, the computer program can implement the steps in the various embodiments of the integrated energy substation planning method.
The embodiment of the application provides a computer program product, and when the computer program product runs on a mobile terminal, the steps in each embodiment of the comprehensive energy substation planning method can be realized when the mobile terminal is executed.
The integrated unit, if implemented in the form of a software functional unit and sold or used as a stand-alone product, may be stored in a computer readable storage medium. Based on such understanding, all or part of the processes in the methods of the embodiments described above can be implemented by a computer program, which can be stored in a computer-readable storage medium and can implement the steps of the embodiments of the methods described above when the computer program is executed by a processor. Wherein the computer program comprises computer program code, which may be in the form of source code, object code, an executable file or some intermediate form, etc. The computer readable medium may include at least: any entity or device capable of carrying computer program code to a photographing apparatus/terminal apparatus, a recording medium, computer Memory, Read-Only Memory (ROM), Random Access Memory (RAM), an electrical carrier signal, a telecommunications signal, and a software distribution medium. Such as a usb-disk, a removable hard disk, a magnetic or optical disk, etc. In certain jurisdictions, computer-readable media may not be an electrical carrier signal or a telecommunications signal in accordance with legislative and patent practice.
In the above embodiments, the descriptions of the respective embodiments have respective emphasis, and reference may be made to the related descriptions of other embodiments for parts that are not described or illustrated in a certain embodiment.
Those of ordinary skill in the art will appreciate that the various illustrative elements and algorithm steps described in connection with the embodiments disclosed herein may be implemented as electronic hardware or combinations of computer software and electronic hardware. Whether such functionality is implemented as hardware or software depends upon the particular application and design constraints imposed on the implementation. Skilled artisans may implement the described functionality in varying ways for each particular application, but such implementation decisions should not be interpreted as causing a departure from the scope of the present application.
In the embodiments provided in the present application, it should be understood that the disclosed apparatus/network device and method may be implemented in other ways. For example, the above-described apparatus/network device embodiments are merely illustrative, and for example, the division of the modules or units is only one logical division, and there may be other divisions when actually implementing, for example, a plurality of units or components may be combined or integrated into another system, or some features may be omitted, or not implemented. In addition, the shown or discussed mutual coupling or direct coupling or communication connection may be an indirect coupling or communication connection through some interfaces, devices or units, and may be in an electrical, mechanical or other form.
The units described as separate parts may or may not be physically separate, and parts displayed as units may or may not be physical units, may be located in one place, or may be distributed on a plurality of network units. Some or all of the units can be selected according to actual needs to achieve the purpose of the solution of the embodiment.
The above-mentioned embodiments are only used for illustrating the technical solutions of the present application, and not for limiting the same; although the present application has been described in detail with reference to the foregoing embodiments, it should be understood by those of ordinary skill in the art that: the technical solutions described in the foregoing embodiments may still be modified, or some technical features may be equivalently replaced; such modifications and substitutions do not substantially depart from the spirit and scope of the embodiments of the present application and are intended to be included within the scope of the present application.

Claims (10)

1. A method for planning an integrated energy substation is characterized by comprising the following steps:
establishing a comprehensive energy transformer substation planning model; the comprehensive energy transformer substation planning model comprises a target function and constraint conditions; the objective function represents the total investment cost of the comprehensive energy transformer substation; the constraint condition comprises one or more of a power flow constraint, a logic gate constraint, a power supply range constraint and an operation capacity constraint;
calculating an optimal planning scheme which enables the total investment cost to be lowest according to the comprehensive energy transformer substation planning model;
and determining the site selection and the capacity of the comprehensive energy transformer substation according to the optimal planning scheme.
2. The integrated energy substation planning method of claim 1, wherein said building an integrated energy substation planning model comprises:
determining the influence factors of the investment cost of the comprehensive energy transformer substation;
constructing a target function of a planning model of the comprehensive energy transformer substation based on the influence factors of the investment cost of the comprehensive energy transformer substation;
and constructing constraint conditions, and determining a comprehensive energy transformer substation planning model according to the objective function and the constraint conditions.
3. The integrated energy substation planning method of claim 2, wherein the objective function of the integrated energy substation planning model is:
Figure FDA0003382578030000011
wherein F is the total investment cost, i is the number of planning stages, i is 1,2, …, N, F1iFor the basic investment costs of the substation in stage i, F2iCost for constructing a line fair, F3iFor power network loss costs, F4iThe investment cost of the transformer is reduced.
4. The integrated energy substation planning method according to claim 2, wherein the constraints are:
Figure FDA0003382578030000021
0≤T0,j≤T1,j≤…≤TN-1,j≤TN,j≤Tj-max
Dj,k≤Dj-max
Figure FDA0003382578030000022
Pi,j≤γTi,jPmax
wherein, the planning stage i is 1,2, …, N, the substation number j is 1,2,…, M, load point number K1, 2, …, K, when Li,j,kWhen the power supply relation is equal to 1, the power supply relation exists, otherwise, the power supply is not supplied; t isi,jThe number of the transformers which have been put into operation in the ith stage, T, for the jth substationj_maxThe number of the transformers which can be accommodated by the jth substation at most; dj,kIs the linear distance between the jth substation and the kth load point, Dj_maxThe maximum power supply radius of the transformer substation is obtained; pi,j,kTransmitting power to the kth load for the jth substation in the ith stage; pmaxThe maximum power capacity that the transformer can bear under the current voltage level, and gamma is the load factor of the transformer.
5. The integrated energy substation planning method of claim 1, wherein said calculating an optimal planning solution that minimizes total investment costs according to the integrated energy substation planning model comprises:
initializing a population and parameters of a differential evolution algorithm, wherein individuals in the population represent the planning scheme of the comprehensive energy transformer substation;
calculating the fitness value of the individual according to the total investment cost calculated by the individual bringing objective function;
and carrying out iterative cycle of variation, intersection and selection operations on the population through the differential evolution algorithm on the basis of the fitness value, and outputting an optimal planning scheme when an iteration termination condition is met.
6. The integrated energy substation planning method of claim 5, wherein said performing variation operations on the population comprises:
Xi,trandomly generating three mutually different integers r for the ith individual in the t generation population1,r2,r3E {1,2, …, N }, and r1,r2,r3I four numbers are different from each other, and a variant individual V is generated according to random integersi,t(ii) a Wherein the content of the first and second substances,
Figure FDA0003382578030000023
f isThe variation factor F is belonged to [0,2 ]]；
If Vi,tIs not in [ X ]min,Xmax]In then order Vi,t＝Xmin+rand(0,1)*(Xmax-Xmin) Wherein [ X ]min,Xmax]For a given search space range of variables, rand (0,1) is a random number uniformly distributed within (0, 1).
7. The integrated energy substation planning method of claim 5, wherein said selecting a population comprises:
generating a tth generation candidate individual U after mutation and cross operationi,tWith the target individual Xi,tCompetition is carried out to obtain t +1 generation individual Xi,t+1，Xi,t+1The calculation expression of (a) is:
Figure FDA0003382578030000031
where f is the fitness function, in Ui,tAnd Xi,tAnd selecting the one with the optimal fitness function value as the t +1 th generation individual to replace the t-th generation individual.
8. An integrated energy substation planning device, comprising:
the model building module is used for building a comprehensive energy transformer substation planning model; the comprehensive energy transformer substation planning model comprises a target function and constraint conditions; the objective function represents the total investment cost of the comprehensive energy transformer substation; the constraint condition comprises one or more of a power flow constraint, a logic gate constraint, a power supply range constraint and an operation capacity constraint;
the calculation module is used for calculating an optimal planning scheme which enables the total investment cost to be lowest according to the comprehensive energy transformer substation planning model;
and the planning module is used for determining the site selection and the capacity of the comprehensive energy transformer substation according to the optimal planning scheme.
9. A terminal device comprising a memory, a processor and a computer program stored in the memory and executable on the processor, characterized in that the processor, when executing the computer program, carries out the steps of the integrated energy substation planning method according to any one of claims 1 to 7.
10. A computer-readable storage medium storing a computer program, wherein the computer program, when executed by a processor, performs the steps of the method of planning an integrated energy substation according to any one of claims 1 to 7.
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Cited By (1)

* Cited by examiner, † Cited by third party
Publication number Priority date Publication date Assignee Title
CN115018151A (en) * 2022-06-02 2022-09-06 南京工程学院 Multi-station fusion site extension planning method

Cited By (1)

* Cited by examiner, † Cited by third party
Publication number Priority date Publication date Assignee Title
CN115018151A (en) * 2022-06-02 2022-09-06 南京工程学院 Multi-station fusion site extension planning method

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