CN113315173B - Distribution network planning method, equipment, system and storage medium based on big data analysis and supply and demand double-side collaborative optimization - Google Patents
Distribution network planning method, equipment, system and storage medium based on big data analysis and supply and demand double-side collaborative optimization Download PDFInfo
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- CN113315173B CN113315173B CN202110659401.8A CN202110659401A CN113315173B CN 113315173 B CN113315173 B CN 113315173B CN 202110659401 A CN202110659401 A CN 202110659401A CN 113315173 B CN113315173 B CN 113315173B
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- H—ELECTRICITY
- H02—GENERATION; CONVERSION OR DISTRIBUTION OF ELECTRIC POWER
- H02J—CIRCUIT ARRANGEMENTS OR SYSTEMS FOR SUPPLYING OR DISTRIBUTING ELECTRIC POWER; SYSTEMS FOR STORING ELECTRIC ENERGY
- H02J3/00—Circuit arrangements for ac mains or ac distribution networks
- H02J3/38—Arrangements for parallely feeding a single network by two or more generators, converters or transformers
- H02J3/46—Controlling of the sharing of output between the generators, converters, or transformers
- H02J3/466—Scheduling the operation of the generators, e.g. connecting or disconnecting generators to meet a given demand
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- H—ELECTRICITY
- H02—GENERATION; CONVERSION OR DISTRIBUTION OF ELECTRIC POWER
- H02J—CIRCUIT ARRANGEMENTS OR SYSTEMS FOR SUPPLYING OR DISTRIBUTING ELECTRIC POWER; SYSTEMS FOR STORING ELECTRIC ENERGY
- H02J3/00—Circuit arrangements for ac mains or ac distribution networks
- H02J3/003—Load forecast, e.g. methods or systems for forecasting future load demand
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- H—ELECTRICITY
- H02—GENERATION; CONVERSION OR DISTRIBUTION OF ELECTRIC POWER
- H02J—CIRCUIT ARRANGEMENTS OR SYSTEMS FOR SUPPLYING OR DISTRIBUTING ELECTRIC POWER; SYSTEMS FOR STORING ELECTRIC ENERGY
- H02J3/00—Circuit arrangements for ac mains or ac distribution networks
- H02J3/004—Generation forecast, e.g. methods or systems for forecasting future energy generation
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- H—ELECTRICITY
- H02—GENERATION; CONVERSION OR DISTRIBUTION OF ELECTRIC POWER
- H02J—CIRCUIT ARRANGEMENTS OR SYSTEMS FOR SUPPLYING OR DISTRIBUTING ELECTRIC POWER; SYSTEMS FOR STORING ELECTRIC ENERGY
- H02J2203/00—Indexing scheme relating to details of circuit arrangements for AC mains or AC distribution networks
- H02J2203/20—Simulating, e g planning, reliability check, modelling or computer assisted design [CAD]
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- Y04—INFORMATION OR COMMUNICATION TECHNOLOGIES HAVING AN IMPACT ON OTHER TECHNOLOGY AREAS
- Y04S—SYSTEMS INTEGRATING TECHNOLOGIES RELATED TO POWER NETWORK OPERATION, COMMUNICATION OR INFORMATION TECHNOLOGIES FOR IMPROVING THE ELECTRICAL POWER GENERATION, TRANSMISSION, DISTRIBUTION, MANAGEMENT OR USAGE, i.e. SMART GRIDS
- Y04S10/00—Systems supporting electrical power generation, transmission or distribution
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Abstract
The invention discloses a distribution network planning method, equipment, a system and a storage medium based on big data analysis and supply and demand double-side collaborative optimization, which are characterized in that by counting power stations existing in urban areas and determining distribution areas corresponding to the power stations, the required power generation capacity and the current month supply power generation capacity of the distribution areas corresponding to current months of the power stations are analyzed from the two aspects of power generation suppliers and power utilization demander, the current month required power generation capacity and the current month supply power generation capacity are compared, and unbalanced supply and demand power stations are screened out, so that the power generation capacity of the power stations with supply and demand from the power stations with supply and demand is allocated, the purpose of optimizing and planning the distribution network in the urban areas is achieved, the power utilization requirements of all current urban power users are really guaranteed, the power utilization experience of the urban power utilization users is improved, unnecessary power waste is avoided, and the power resources are reasonably utilized and configured.
Description
Technical Field
The invention belongs to the technical field of power distribution network planning, and particularly relates to a power distribution network planning method, equipment, a system and a storage medium based on big data analysis and supply and demand double-side collaborative optimization.
Background
With the large-scale development of cities, more and more people are rushed to the cities, so that urban population and industry are gradually increased, the number of urban electricity utilization users is increased, and the electricity utilization demands of people are greatly increased. However, the distribution network of the present city is laid according to the original population and industry distribution pattern of the city, and the population and industry of the present city are far broken through whether the population and industry of the present city are the number or the distribution status along with the development of the city, if the distribution network of the present city is used for distributing power to all the power utilization users in the present city according to the original distribution network of the city, the power utilization requirements of some power utilization users are likely to be unable to be guaranteed, and the power utilization requirements of some power utilization users are rich, so that the power waste is caused. Therefore, the original power distribution network of the city cannot meet the power consumption requirements of the current city power consumption users, on one hand, in order to practically guarantee the power consumption requirements of all the current city power consumption users, and on the other hand, in order to avoid unnecessary electric energy waste, the electric energy resources are reasonably utilized and configured, and the power distribution network of the city is required to be optimally planned.
Disclosure of Invention
In order to achieve the above purpose, the invention provides a distribution network planning method, equipment, a system and a storage medium based on big data analysis and supply and demand double-side collaborative optimization, which are characterized in that by counting power stations existing in urban areas and determining distribution areas corresponding to the power stations, the required power generation amount and the current month supply power generation amount of the distribution areas corresponding to the current month of each power station are analyzed from the two aspects of power generation suppliers and power utilization demander, the current month required power generation amount and the current month supply power generation amount are compared, and unbalanced supply and demand power stations are screened out, so that the power generation amount allocation of power stations with supply and demand is carried out from power stations with supply and demand nearby, and the power utilization demands of all power utilization users in the current city are practically ensured.
The aim of the invention can be achieved by the following technical scheme:
in a first aspect, the present invention provides a power distribution network planning method based on big data analysis and supply and demand double-sided collaborative optimization, comprising the steps of;
s1, carrying out statistics on power stations in urban areas: counting the number of power stations existing in the urban area according to a power station counting module in the urban area, numbering each power station according to a predefined sequence, and marking the power stations as 1,2, i, n, and simultaneously obtaining the geographic position of each power station and the current month supply generating capacity;
S2, determining a power distribution area of the power station and carrying out electricity user statistics: the method comprises the steps that a power station power distribution area determining module takes the geographical position of each power station as a circle center and takes a set distance length as a radius to form a circle, a power distribution range circle is obtained, the area in the power distribution range circle corresponding to each power station is the power distribution area corresponding to each power station, at the moment, the number of power utilization users in the power distribution area corresponding to each power station is counted, the geographical position of each power utilization user is obtained, and accordingly the power utilization users corresponding to each power station are numbered according to the sequence from near to far between the geographical position of the power utilization user and the geographical position of the power station, and the power utilization users are sequentially marked as 1, 2.
S3, counting total power consumption of the current month of the power station: predicting the average power consumption of the power stations corresponding to the current month of each power utilization user according to the current month power utilization statistics module of the power stations, so as to count the total power consumption of the power stations corresponding to the current month of all power utilization users;
s4, counting the total loss of power transmission of the power station: the power transmission loss statistics module of the power stations is adopted to acquire the length of the power transmission line of each power station corresponding to each power utilization user according to the geographic position of each power station and the geographic position of each power station corresponding to each power utilization user, and acquire the basic parameters of the power transmission line, so as to analyze the total loss of the power transmission corresponding to each power station;
S5, counting the current month demand power generation amount of the power station: adding the total power consumption of the power stations corresponding to the current month of all power utilization users and the total power transmission loss according to the current month demand power generation amount statistical module of the power stations to obtain the demand power generation amount corresponding to the current month of each power station;
s6, screening a supply and demand unbalanced power station: comparing the current month demand generating capacity corresponding to each power station with the current month supply generating capacity according to the analysis cloud platform, and screening power stations with unbalanced supply and demand from the power stations;
s7, planning and allocating the electric quantity of the unbalanced supply and demand power station: and judging the unbalanced supply and demand type of each unbalanced supply and demand power station according to the intelligent planning and allocation terminal, and further allocating the power generation amount of the power station with the unbalanced supply and demand type being the supply and demand power station from the unbalanced supply and demand type to the power station with the supply and demand type being the supply and demand nearby.
According to a preferred embodiment of the first aspect of the present invention, in the step S3, the average power consumption of each power station corresponding to the current month of each power consumer is predicted, and the specific prediction method performs the following steps:
a1, acquiring a current year, setting a plurality of historical years on the basis of the current year, numbering the set historical years according to the sequence from short time to long time of the set historical years, and marking the set historical years as 1,2, k, t, so as to acquire the electricity consumption of each power station corresponding to each electricity user in each historical year corresponding to the current month, and further forming a current month electricity consumption set Q of the historical years of the power station electricity users ij (q ij 1,q ij 2,...,q ij k,…,q ij t)，q ij k represents the electricity consumption of the jth electricity user corresponding to the kth historical year corresponding to the current month in the ith power station;
a2, calculating the average power consumption of each power station corresponding to the current month of each power utilization user according to the current month power consumption set of the historical years of the power utilization users of the power station, wherein the calculation formula is as follows
The average power consumption of the current month corresponding to the jth power utilization user is represented as the ith power station.
According to a preferred embodiment of the first aspect of the present invention, the statistical method of the total power consumption of each power station corresponding to the current month of all power users is to accumulate the average power consumption of each power station corresponding to the current month of each power user to obtain the total power consumption of each power station corresponding to the current month of all power users.
According to a preferred embodiment of the first aspect of the present invention, the step S4 of analyzing the total loss of power transmission corresponding to each power station, the specific analysis method thereof performs the following steps:
b1, comparing the transmission line material in the transmission line basic parameters with the transmission loss amount of unit length of various transmission line diameters subordinate to the transmission line material in various transmission line diameters in a distribution database to obtain the transmission loss amount of unit length of various transmission line diameters subordinate to the transmission line material;
B2, comparing the transmission line diameter in the transmission line basic parameters with the transmission loss quantity of unit length of the transmission line diameter of various transmission line subordinate to the transmission line material to obtain the transmission loss quantity of unit length of the transmission line corresponding to the transmission line diameter;
b3, calculating the power transmission loss quantity of each power station corresponding to each power user according to the power transmission line length of each power station corresponding to each power user and the power transmission loss quantity of each power transmission line corresponding to the power transmission line diameter, wherein the calculation formula is P ij ＝p*l ij ，P ij The transmission loss amount of the power transmission line corresponding to the power transmission line diameter is expressed as the transmission loss amount of the power transmission line corresponding to the power transmission line of the j power utilization user of the i power station, and p is expressed as the transmission loss amount of the power transmission line corresponding to the power transmission line diameter of the unit length, l ij The length of the transmission line corresponding to each power station to each power utilization user is expressed;
and B4, accumulating the transmission loss quantity of each power station corresponding to each power utilization user to obtain the total transmission loss quantity corresponding to each power station.
According to a preferred embodiment of the first aspect of the present invention, in the step S6, unbalanced supply and demand power plants are screened, wherein the specific screening process is to compare the current month demand power generation amount corresponding to each power plant with the current month supply power generation amount, if the current month demand power generation amount corresponding to a certain power plant is equal to the current month supply power generation amount, the power plant is marked as a balanced supply and demand power plant, and if the current month demand power generation amount corresponding to the certain power plant is unequal to the current month supply power generation amount, the power plant is marked as a balanced supply and demand power plant.
According to a preferred embodiment of the first aspect of the present invention, in the step S7, the intelligent planning and allocation terminal determines a supply and demand unbalance type of each unbalanced supply and demand power station, and further performs power generation allocation on the unbalanced supply and demand power station with the supply and demand unbalance type being the supply and demand unbalance type from the unbalanced supply and demand power station with the supply and demand unbalance type being the supply and demand unbalance type, which specifically includes the following steps:
comparing the current month required power generation amount corresponding to each unbalanced supply and demand power generation station with the current month supply power generation amount, if the current month required power generation amount corresponding to a certain unbalanced supply and demand power generation station is larger than the current month supply power generation amount, the type of supply and demand unbalance corresponding to the unbalanced supply and demand power generation station is supply and demand, and if the current month required power generation amount corresponding to the certain unbalanced supply and demand power generation station is smaller than the current month supply power generation amount, the type of supply and demand unbalance corresponding to the unbalanced supply and demand power generation station is supply and demand;
c2, comparing the supply and demand unbalanced types corresponding to the supply and demand unbalanced power stations with each other, classifying the power stations corresponding to the same supply and demand unbalanced type, and obtaining a plurality of supply and demand unbalanced power stations corresponding to supply and demand and a plurality of supply and demand unbalanced power stations corresponding to supply and demand, wherein the supply and demand unbalanced power stations corresponding to supply and demand are denoted as supply and demand power stations, and the supply and demand unbalanced power stations corresponding to supply and demand are denoted as supply and demand power stations;
The corresponding numbers of the supply and demand power stations and the supply and demand power stations are counted respectively, so that the geographic positions of the supply and demand power stations and the supply and demand power stations are obtained;
c4, comparing the geographical position of each supply and demand power station with the geographical position of all supply and demand power stations to obtain the route distance between each supply and demand power station and each supply and demand power station, so that each supply and demand power station corresponding to each supply and demand power station is ordered according to the sequence from the near to the far of the route distance between each supply and demand power station and each supply and demand power station to obtain the ordering result of the supply and demand power stations corresponding to each supply and demand power station;
c5, subtracting the current month supply generating capacity from the current month demand generating capacity corresponding to each supply-demand generating station to obtain supply shortage generating capacity corresponding to each supply-demand generating station, and subtracting the current month supply generating capacity from the current month supply generating capacity corresponding to each supply-demand generating station to obtain supply surplus generating capacity corresponding to each supply-demand generating station;
c6, carrying out generating capacity allocation on each supply and demand generating station in turn according to the corresponding number sequence of each supply and demand generating station, wherein the specific allocation process is to extract the supply and demand generating station arranged at the first position from the supply and demand generating station sequencing result corresponding to the current demand generating station, and compare the supply and demand generating station corresponding to the current demand generating station with the supply and demand generating station corresponding to the first position, if the supply and demand generating capacity is larger than the supply and demand generating capacity, the supply and demand generating station corresponding to the current demand generating station is indicated to be not met, at the moment, the supply and demand generating station arranged at the next position is continuously extracted from the supply and demand generating station sequencing result corresponding to the current demand generating station, the supply and demand generating station is processed according to the method of the step until the supply and demand generating station corresponding to the last position is extracted, if the supply and demand generating capacity is smaller than or equal to the supply and demand generating station corresponding to the current demand generating station is not met, and the supply and demand generating station corresponding to the current demand generating station is not met, the supply and the current generating station is not met, the current demand generating station is not met, and the supply and the power station is required and the current generating station is required to be met, and then, according to the new supply and demand power station sequencing result corresponding to the supply and demand power station allocated with the next required power generation amount, continuing to allocate the power generation amount of the supply and demand power station according to the allocation method of the step.
According to a preferred embodiment of the first aspect of the present invention, the step S7 further includes:
s8, optimizing and planning the number of power stations corresponding to various power generation types in the region: the method comprises the following steps of obtaining various power generation types in an urban area according to an intelligent planning and allocation terminal, and optimizing the number of power stations corresponding to the various power generation types, wherein the specific optimization process comprises the following steps:
s81, acquiring power generation types corresponding to all power generation stations in an urban area, comparing the power generation types corresponding to all the power generation stations with each other, analyzing whether the same power generation type exists, classifying the power generation stations corresponding to the same power generation type to obtain a power generation station set corresponding to various power generation types, numbering the various power generation types at the moment, and respectively marking the power generation types as 1,2, f, r, and acquiring the numbers of the power generation stations in the power generation station set corresponding to the various power generation types at the moment;
s82, converting the current month into each month, and further obtaining each supply and demand power station corresponding to each month and the corresponding number of each supply and demand power station in the urban area according to the steps S1-S7, so as to count the number of the supply and demand power stations corresponding to each month according to the numbers of each power station in the power station set corresponding to each power generation type;
S83, carrying out average processing on the number of the supply and demand power stations of each month corresponding to each power generation type to obtain the average number of the supply and demand power stations of each power generation type, and evaluating the supply and demand proportionality coefficient corresponding to each power generation type according to the average number of the supply and demand power stations and the total number of the power stations of each power generation type, wherein an evaluation calculation formula is that
Expressed as the supply-demand proportionality coefficient corresponding to the f-th power generation type, x f 、X f Respectively representing the average number of the supply and demand power stations and the total number of the power stations corresponding to the f power generation type, comparing the average number of the supply and demand power stations with the set maximum supply and demand proportionality coefficient, and if the supply and demand ratio corresponding to a certain power generation typeAnd if the example coefficient is larger than the maximum supply-demand proportional coefficient, the number of power stations corresponding to the power generation type needs to be planned to be increased in the later period.
The invention provides a distribution network planning system based on big data analysis and supply and demand double-side collaborative optimization, which comprises a urban area power station statistics module, a power station distribution area determination module, a power station current month power consumption statistics module, a power station transmission loss statistics module, a power station current month demand power generation amount statistics module, a distribution database, an analysis cloud platform and an intelligent planning allocation terminal, wherein the urban area power station statistics module is connected with the power station distribution area determination module, the power station distribution area determination module is respectively connected with the power station current month power consumption statistics module and the power station transmission loss statistics module, the power station current month power consumption statistics module and the power station transmission loss statistics module are both connected with the power station current month demand power generation amount statistics module, the urban area power station statistics module and the power station current month demand power generation amount statistics module are both connected with the analysis cloud platform, and the analysis cloud platform is connected with the intelligent planning allocation terminal.
In a third aspect, the invention provides an apparatus comprising a processor, and a memory and network interface coupled to the processor; the network interface is connected with a nonvolatile memory in the server; and the processor retrieves the computer program from the nonvolatile memory through the network interface when in operation, and runs the computer program through the memory to execute the distribution network planning method based on big data analysis and supply and demand double-side collaborative optimization.
In a fourth aspect, the present invention provides a storage medium, where a computer program is burned, and the computer program implements the distribution network planning method based on big data analysis and supply and demand double-sided collaborative optimization according to the present invention when running in a memory of a server.
Based on any one of the above aspects, the beneficial effects of the invention are as follows:
(1) According to the invention, by counting the power stations in the urban area and determining the power distribution area corresponding to each power station, the required power generation amount and the current month supply power generation amount of the power distribution area corresponding to each power station are analyzed from the two aspects of a power generation supplier and a power consumption demand side, the current month required power generation amount and the current month supply power generation amount are compared, and the power stations with unbalanced supply and demand are screened out, so that the power generation amount of the power stations with unbalanced supply and demand is allocated from the power stations with over supply and demand in a double-side cooperative optimization mode, the optimal planning purpose of the power distribution network in the urban area is realized, the power consumption demands of all power consumption users in the current city are practically ensured, the power consumption experience sense of the power consumption users in the city is improved, unnecessary electric energy waste is avoided, and the electric energy resources are reasonably utilized and configured.
(2) The invention adopts a nearby allocation principle in the allocation process of the generated energy of the power stations with the supply and demand from the power stations with the supply and demand, shortens the allocation distance, further improves the allocation rate of the generated energy, ensures that the allocated generated energy can be timely transmitted to the power distribution area corresponding to the power stations with the supply and demand as soon as possible, and avoids the influence on the power utilization timeliness of the power distribution area corresponding to the power stations with the supply and demand due to the excessive allocation distance.
(3) According to the invention, the power generation capacity allocation planning is carried out on the power generation stations in the urban area, the optimization planning is carried out on the number of the power generation stations corresponding to various power generation types in the urban area, and the purpose of meeting the power generation type to the application power demand is achieved by increasing the number of the power generation stations corresponding to the power generation type with the overlarge supply and demand proportion coefficient in the urban area, so that various power generation types existing in the urban area are uniformly developed, the planning range of the urban area power distribution network is expanded, the urban area power distribution network planning is more comprehensive, and the planning level of the urban area power distribution network is further improved.
Drawings
The invention will be further described with reference to the accompanying drawings, in which embodiments do not constitute any limitation of the invention, and other drawings can be obtained by one of ordinary skill in the art without inventive effort from the following drawings.
FIG. 1 is a flow chart of the steps of the method of the present invention.
Fig. 2 is a schematic diagram of system module connection according to the present invention.
Detailed Description
The following description of the embodiments of the present invention will be made clearly and completely with reference to the accompanying drawings, in which it is apparent that the embodiments described are only some embodiments of the present invention, but not all embodiments. All other embodiments, which can be made by those skilled in the art based on the embodiments of the invention without making any inventive effort, are intended to be within the scope of the invention.
Referring to fig. 1, in a first aspect, the present invention provides a power distribution network planning method based on big data analysis and supply and demand double-sided collaborative optimization, comprising the following steps;
s1, carrying out statistics on power stations in urban areas: counting the number of power stations existing in the urban area according to a power station counting module in the urban area, numbering each power station according to a predefined sequence, and marking the power stations as 1,2, i, n, and simultaneously obtaining the geographic position of each power station and the current month supply generating capacity;
s2, determining a power distribution area of the power station and carrying out electricity user statistics: the method comprises the steps that a power station power distribution area determining module takes the geographical position of each power station as a circle center and takes a set distance length as a radius to form a circle, a power distribution range circle is obtained, the area in the power distribution range circle corresponding to each power station is the power distribution area corresponding to each power station, at the moment, the number of power utilization users in the power distribution area corresponding to each power station is counted, the geographical position of each power utilization user is obtained, and accordingly the power utilization users corresponding to each power station are numbered according to the sequence from near to far between the geographical position of the power utilization user and the geographical position of the power station, and the power utilization users are sequentially marked as 1, 2.
S3, counting total power consumption of the current month of the power station: according to the current month electricity consumption statistics module of the power station, predicting the current month average electricity consumption of each power station corresponding to each electricity user, wherein the specific prediction method comprises the following steps:
a1, obtaining the timeThe method comprises the steps of setting a plurality of historical years based on the current years, numbering the set historical years according to the sequence from short time to long time of the set historical years to the current years, and marking the set historical years as 1,2, k, t, and the t in sequence, so as to obtain the electricity consumption of each power station corresponding to each electricity user in each historical year corresponding to the current month, and further forming a current month electricity consumption set Q of the historical years of the power station electricity users ij (q ij 1,q ij 2,...,q ij k,...,q ij t)，q ij k represents the electricity consumption of the jth electricity user corresponding to the kth historical year corresponding to the current month in the ith power station;
a2, calculating the average power consumption of each power station corresponding to the current month of each power utilization user according to the current month power consumption set of the historical years of the power utilization users of the power station, wherein the calculation formula is as follows
Represented as the current month average power usage of the ith power plant for the jth power consumer,
the number of the plurality of historical years set by the embodiment is at least not less than three, so that the problem that the accuracy of the current month average electricity consumption prediction results of the corresponding electricity utilization users of all power stations is not high due to the fact that the number of the set historical years is too small is avoided;
At the moment, accumulating average power consumption of the power stations corresponding to the current month of each power utilization user to obtain total power consumption of the power stations corresponding to the current month of all power utilization users;
s4, counting the total loss of power transmission of the power station: the method comprises the following steps that a power transmission loss statistics module of a power station is adopted, according to the geographic position of each power station and the geographic position of each power station corresponding to each power utilization user, the distance between the geographic position of each power station and the geographic position of each power station corresponding to each power utilization user is counted, so that the length of a power transmission line of each power station corresponding to each power utilization user is obtained, and basic parameters of the power transmission line are obtained, wherein the basic parameters of the power transmission line comprise the material of the power transmission line and the diameter of the power transmission line, and further the total loss of the power transmission corresponding to each power station is analyzed according to the basic parameters, and the specific analysis method comprises the following steps:
b1, comparing the transmission line material in the transmission line basic parameters with the transmission loss amount of unit length of various transmission line diameters subordinate to the transmission line material in various transmission line diameters in a distribution database to obtain the transmission loss amount of unit length of various transmission line diameters subordinate to the transmission line material;
b2, comparing the transmission line diameter in the transmission line basic parameters with the transmission loss quantity of unit length of the transmission line diameter of various transmission line subordinate to the transmission line material to obtain the transmission loss quantity of unit length of the transmission line corresponding to the transmission line diameter;
B3, calculating the power transmission loss quantity of each power station corresponding to each power user according to the power transmission line length of each power station corresponding to each power user and the power transmission loss quantity of each power transmission line corresponding to the power transmission line diameter, wherein the calculation formula is P ij ＝p*l ij ，P ij The transmission loss amount of the power transmission line corresponding to the power transmission line diameter is expressed as the transmission loss amount of the power transmission line corresponding to the power transmission line of the j power utilization user of the i power station, and p is expressed as the transmission loss amount of the power transmission line corresponding to the power transmission line diameter of the unit length, l ij The length of the transmission line corresponding to each power station to each power utilization user is expressed;
b4, accumulating the transmission loss quantity of each power station corresponding to each power utilization user to obtain the total transmission loss quantity corresponding to each power station;
s5, counting the current month demand power generation amount of the power station: adding the total power consumption of the power stations corresponding to the current month of all power utilization users and the total power transmission loss according to the current month demand power generation amount statistical module of the power stations to obtain the demand power generation amount corresponding to the current month of each power station;
in the embodiment, the total power consumption and the total power transmission loss of all power stations corresponding to the current month of all power utilization users are comprehensively considered in the process of counting the required power generation amount corresponding to the current month of each power station, so that the problem that the reliability of a counting result is affected due to the fact that the total power consumption of the power utilization users is used as the required power generation amount is solved;
S6, screening a supply and demand unbalanced power station: comparing the current month required power generation amount corresponding to each power station with the current month supply power generation amount according to the analysis cloud platform, and screening out power stations with unbalanced supply and demand from the current month required power generation amount;
s7, planning and allocating the electric quantity of the unbalanced supply and demand power station: judging the unbalanced supply and demand type of each unbalanced supply and demand power station according to the intelligent planning and allocation terminal, and further allocating the power generation amount of the power station with the unbalanced supply and demand type being the supply and demand power station from the unbalanced supply and demand type to the power station with the supply and demand type being the supply and demand nearby, wherein the specific operation steps are as follows:
comparing the current month required power generation amount corresponding to each unbalanced supply and demand power generation station with the current month supply power generation amount, if the current month required power generation amount corresponding to a certain unbalanced supply and demand power generation station is larger than the current month supply power generation amount, the type of supply and demand unbalance corresponding to the unbalanced supply and demand power generation station is supply and demand, and if the current month required power generation amount corresponding to the certain unbalanced supply and demand power generation station is smaller than the current month supply power generation amount, the type of supply and demand unbalance corresponding to the unbalanced supply and demand power generation station is supply and demand;
C2, comparing the supply and demand unbalanced types corresponding to the supply and demand unbalanced power stations with each other, classifying the power stations corresponding to the same supply and demand unbalanced type, and obtaining a plurality of supply and demand unbalanced power stations corresponding to supply and demand and a plurality of supply and demand unbalanced power stations corresponding to supply and demand, wherein the supply and demand unbalanced power stations corresponding to supply and demand are denoted as supply and demand power stations, and the supply and demand unbalanced power stations corresponding to supply and demand are denoted as supply and demand power stations;
the corresponding numbers of the supply and demand power stations and the supply and demand power stations are counted respectively, so that the geographic positions of the supply and demand power stations and the supply and demand power stations are obtained;
c4, comparing the geographical position of each supply and demand power station with the geographical position of all supply and demand power stations to obtain the route distance between each supply and demand power station and each supply and demand power station, so that each supply and demand power station corresponding to each supply and demand power station is ordered according to the sequence from the near to the far of the route distance between each supply and demand power station and each supply and demand power station to obtain the ordering result of the supply and demand power stations corresponding to each supply and demand power station;
c5, subtracting the current month supply generating capacity from the current month demand generating capacity corresponding to each supply-demand generating station to obtain supply shortage generating capacity corresponding to each supply-demand generating station, and subtracting the current month supply generating capacity from the current month supply generating capacity corresponding to each supply-demand generating station to obtain supply surplus generating capacity corresponding to each supply-demand generating station;
C6, carrying out generating capacity allocation on each supply and demand generating station in turn according to the corresponding number sequence of each supply and demand generating station, wherein the specific allocation process is to extract the supply and demand generating station arranged at the first position from the supply and demand generating station sequencing result corresponding to the current demand generating station, and compare the supply and demand generating station corresponding to the current demand generating station with the supply and demand generating station corresponding to the first position, if the supply and demand generating capacity is larger than the supply and demand generating capacity, the supply and demand generating station corresponding to the current demand generating station is indicated to be not met, at the moment, the supply and demand generating station arranged at the next position is continuously extracted from the supply and demand generating station sequencing result corresponding to the current demand generating station, the supply and demand generating station is processed according to the method of the step until the supply and demand generating station corresponding to the last position is extracted, if the supply and demand generating capacity is smaller than or equal to the supply and demand generating station corresponding to the current demand generating station is not met, and the supply and demand generating station corresponding to the current demand generating station is not met, the supply and the current generating station is not met, the current demand generating station is not met, and the supply and the power station is required and the current generating station is required to be met, and then, according to the new supply and demand power station sequencing result corresponding to the supply and demand power station allocated with the next required power generation amount, continuing to allocate the power generation amount of the supply and demand power station according to the allocation method of the step.
According to the method, the power generation stations in the urban area are counted, the distribution areas corresponding to the power generation stations are determined, and then the required power generation amount and the current month supply power generation amount of the distribution areas corresponding to the current months of the power generation stations are analyzed from the two aspects of power generation suppliers and power utilization demand parties, so that the current month required power generation amount and the current month supply power generation amount are compared, unbalanced supply and demand power generation stations are screened out, the supply and demand power generation stations are subjected to power generation amount allocation from the supply and demand power generation stations in a supply and demand power supply and demand cooperative optimization mode, the purpose of optimizing and planning a power distribution network in the urban area is achieved, the power utilization demands of all power utilization users in the city are practically guaranteed, the power utilization experience of the power utilization users in the city is improved, unnecessary power waste is avoided, and the power resources are reasonably utilized and configured.
According to the method, the device and the system, the nearby allocation principle is adopted in the allocation process of the generated energy of the power stations of the supply and demand from the power stations of the supply and demand, so that the allocation distance is shortened, the allocation rate of the generated energy is further improved, the allocated generated energy can be timely transmitted to the power distribution area corresponding to the power stations of the supply and demand as soon as possible, and the influence on the power utilization timeliness of the power distribution area corresponding to the power stations of the supply and demand due to the fact that the allocation distance is too far is avoided.
S8, optimizing and planning the number of power stations corresponding to various power generation types in the region: various power generation types existing in the urban area are obtained according to the intelligent planning and allocation terminal, wherein the power generation types comprise wind power generation, thermal power generation, hydroelectric power generation, photovoltaic power generation, other types of power generation and the like, the number of power stations corresponding to the various power generation types is optimized, and the specific optimization process comprises the following steps:
s81, acquiring power generation types corresponding to all power generation stations in an urban area, comparing the power generation types corresponding to all the power generation stations with each other, analyzing whether the same power generation type exists, classifying the power generation stations corresponding to the same power generation type to obtain a power generation station set corresponding to various power generation types, numbering the various power generation types at the moment, and respectively marking the power generation types as 1,2, f, r, and acquiring the numbers of the power generation stations in the power generation station set corresponding to the various power generation types at the moment;
s82, converting the current month into each month, and further obtaining each supply and demand power station corresponding to each month and the corresponding number of each supply and demand power station in the urban area according to the steps S1-S7, so as to count the number of the supply and demand power stations corresponding to each month according to the numbers of each power station in the power station set corresponding to each power generation type;
S83, carrying out average processing on the number of the supply and demand power stations of each month corresponding to each power generation type to obtain the average number of the supply and demand power stations of each power generation type, and evaluating the supply and demand proportionality coefficient corresponding to each power generation type according to the average number of the supply and demand power stations and the total number of the power stations of each power generation type, wherein an evaluation calculation formula is that
Expressed as the supply-demand proportionality coefficient corresponding to the f-th power generation type, x f 、X f Respectively representing the average number of supply and demand power stations and the total number of power stations corresponding to the f-th power generation type, comparing the average number of supply and demand power stations with the set maximum supply and demand proportionality coefficient, and if the supply and demand proportionality coefficient corresponding to a certain power generation type is larger than the maximum supply and demand proportionality coefficient, increasing the number of power stations corresponding to the power generation type at the later stageAnd (5) scribing.
According to the embodiment, the power generation types existing in the urban area are counted, the supply and demand proportion coefficients corresponding to the various power generation types are counted, so that the number of power stations corresponding to the power generation types with overlarge supply and demand proportion coefficients in the urban area is increased, the purpose of meeting the power demand of the power generation types on the application power is achieved, the optimization planning of the number of the power stations corresponding to the various power generation types in the urban area is achieved, the various power generation types existing in the urban area are uniformly developed, the planning range of the urban area power distribution network is expanded, the urban area power distribution network is planned more comprehensively, and the planning level of the urban area power distribution network is improved.
Referring to fig. 2, in a second aspect, the invention provides a distribution network planning system based on big data analysis and supply and demand double-sided collaborative optimization, which comprises a urban area power station statistics module, a power station distribution area determination module, a power station current month power consumption statistics module, a power station transmission loss statistics module, a power station current month demand power generation amount statistics module, a distribution database, an analysis cloud platform and an intelligent planning allocation terminal, wherein the distribution database is used for storing the power transmission loss amount of various power transmission wires corresponding to the unit length of various power transmission line diameters of the power transmission line material, the urban area power station statistics module is connected with the power station distribution area determination module, the power station distribution area determination module is respectively connected with the power station current month power consumption statistics module and the power station transmission loss statistics module, the power station current month power consumption statistics module and the power station current month demand power generation amount statistics module are connected with the analysis cloud platform, and the analysis cloud platform is connected with the intelligent planning allocation terminal.
In a third aspect, the invention provides an apparatus comprising a processor, and a memory and network interface coupled to the processor; the network interface is connected with a nonvolatile memory in the server; and the processor retrieves the computer program from the nonvolatile memory through the network interface when in operation, and runs the computer program through the memory to execute the distribution network planning method based on big data analysis and supply and demand double-side collaborative optimization.
In a fourth aspect, the present invention provides a storage medium, where a computer program is burned, and the computer program implements the distribution network planning method based on big data analysis and supply and demand double-sided collaborative optimization according to the present invention when running in a memory of a server.
The foregoing is merely illustrative of the structures of this invention and various modifications, additions and substitutions for those skilled in the art can be made to the described embodiments without departing from the scope of the invention or from the scope of the invention as defined in the accompanying claims.
Claims (9)
1. The power distribution network planning method based on big data analysis and supply and demand double-side collaborative optimization is characterized by comprising the following steps of:
S1, carrying out statistics on power stations in urban areas: counting the number of power stations existing in the urban area according to a power station counting module in the urban area, numbering each power station according to a predefined sequence, and marking the power stations as 1,2, i, n, and simultaneously obtaining the geographic position of each power station and the current month supply generating capacity;
s2, determining a power distribution area of the power station and carrying out electricity user statistics: the method comprises the steps that a power station power distribution area determining module takes the geographical position of each power station as a circle center and takes a set distance length as a radius to form a circle, a power distribution range circle is obtained, the area in the power distribution range circle corresponding to each power station is the power distribution area corresponding to each power station, at the moment, the number of power utilization users in the power distribution area corresponding to each power station is counted, the geographical position of each power utilization user is obtained, and accordingly the power utilization users corresponding to each power station are numbered according to the sequence from near to far between the geographical position of the power utilization user and the geographical position of the power station, and the power utilization users are sequentially marked as 1, 2.
S3, counting total power consumption of the current month of the power station: predicting the average power consumption of the power stations corresponding to the current month of each power utilization user according to the current month power utilization statistics module of the power stations, so as to count the total power consumption of the power stations corresponding to the current month of all power utilization users;
S4, counting the total loss of power transmission of the power station: the power transmission loss statistics module of the power stations is adopted to acquire the length of the power transmission line of each power station corresponding to each power utilization user according to the geographic position of each power station and the geographic position of each power station corresponding to each power utilization user, and acquire the basic parameters of the power transmission line, so as to analyze the total loss of the power transmission corresponding to each power station;
s5, counting the current month demand power generation amount of the power station: adding the total power consumption of the power stations corresponding to the current month of all power utilization users and the total power transmission loss according to the current month demand power generation amount statistical module of the power stations to obtain the demand power generation amount corresponding to the current month of each power station;
s6, screening a supply and demand unbalanced power station: comparing the current month demand generating capacity corresponding to each power station with the current month supply generating capacity according to the analysis cloud platform, and screening power stations with unbalanced supply and demand from the power stations;
s7, planning and allocating the electric quantity of the unbalanced supply and demand power station: judging the unbalanced supply and demand type of each unbalanced supply and demand power station according to the intelligent planning and allocation terminal, and further allocating the power generation amount of the power station with the unbalanced supply and demand type being the supply and demand power station from the unbalanced supply and demand type to the power station with the supply and demand type being the supply and demand power station nearby;
The step S7 further comprises:
s8, optimizing and planning the number of power stations corresponding to various power generation types in the region: the method comprises the following steps of obtaining various power generation types in an urban area according to an intelligent planning and allocation terminal, and optimizing the number of power stations corresponding to the various power generation types, wherein the specific optimization process comprises the following steps:
s81, acquiring power generation types corresponding to all power generation stations in an urban area, comparing the power generation types corresponding to all the power generation stations with each other, analyzing whether the same power generation type exists, classifying the power generation stations corresponding to the same power generation type to obtain a power generation station set corresponding to various power generation types, numbering the various power generation types at the moment, and respectively marking the power generation types as 1,2, f, r, and acquiring the numbers of the power generation stations in the power generation station set corresponding to the various power generation types at the moment;
s82, converting the current month into each month, and further obtaining each supply and demand power station corresponding to each month and the corresponding number of each supply and demand power station in the urban area according to the steps S1-S7, so as to count the number of the supply and demand power stations corresponding to each month according to the numbers of each power station in the power station set corresponding to each power generation type;
S83, carrying out average processing on the number of the supply and demand power stations of each month corresponding to each power generation type to obtain the average number of the supply and demand power stations of each power generation type, and evaluating the supply and demand proportionality coefficient corresponding to each power generation type according to the average number of the supply and demand power stations and the total number of the power stations of each power generation type, wherein an evaluation calculation formula is that
Expressed as the supply-demand proportionality coefficient corresponding to the f-th power generation type, x f 、X f The average number of the supply and demand power stations and the total number of the power stations corresponding to the f-th power generation type are respectively expressed, the average number of the supply and demand power stations and the total number of the power stations are compared with the set maximum supply and demand proportionality coefficient, and if the supply and demand proportionality coefficient corresponding to a certain power generation type is larger than the maximum supply and demand proportionality coefficient, the number of the power stations corresponding to the power generation type needs to be planned in an increasing mode in the later period.
2. The distribution network planning method based on big data analysis and supply and demand double-sided collaborative optimization according to claim 1, wherein the method comprises the following steps: in the step S3, the average power consumption of each power station corresponding to the current month of each power utilization user is predicted, and the specific prediction method comprises the following steps:
a1, obtaining the current years, setting a plurality of historical years based on the current years, and setting each time The historical years are numbered in order of time from the current year from short to long, labeled sequentially 1, 2. The electricity consumption of each power station corresponding to each electricity user in each historical period corresponding to the current month is obtained, and then the electricity consumption is formed into a power station electricity user historical period current month electricity consumption set Q ij (q ij 1,q ij 2,...,q ij k,...,q ij t)，q ij k represents the electricity consumption of the jth electricity user corresponding to the kth historical year corresponding to the current month in the ith power station;
a2, calculating the average power consumption of each power station corresponding to the current month of each power utilization user according to the current month power consumption set of the historical years of the power utilization users of the power station, wherein the calculation formula is as follows
The average power consumption of the current month corresponding to the jth power utilization user is represented as the ith power station.
3. The distribution network planning method based on big data analysis and supply and demand double-sided collaborative optimization according to claim 1, wherein the method comprises the following steps: the statistical method of the total power consumption of the power stations corresponding to the current month of all the power utilization users is to accumulate the average power consumption of the power stations corresponding to the current month of all the power utilization users, so as to obtain the total power consumption of the power stations corresponding to the current month of all the power utilization users.
4. The distribution network planning method based on big data analysis and supply and demand double-sided collaborative optimization according to claim 1, wherein the method comprises the following steps: and S4, analyzing the total loss of power transmission corresponding to each power station, wherein the specific analysis method comprises the following steps of:
B1, comparing the transmission line material in the transmission line basic parameters with the transmission loss amount of unit length of various transmission line diameters subordinate to the transmission line material in various transmission line diameters in a distribution database to obtain the transmission loss amount of unit length of various transmission line diameters subordinate to the transmission line material;
b2, comparing the transmission line diameter in the transmission line basic parameters with the transmission loss quantity of unit length of the transmission line diameter of various transmission line subordinate to the transmission line material to obtain the transmission loss quantity of unit length of the transmission line corresponding to the transmission line diameter;
b3, calculating the power transmission loss quantity of each power station corresponding to each power user according to the power transmission line length of each power station corresponding to each power user and the power transmission loss quantity of each power transmission line corresponding to the power transmission line diameter, wherein the calculation formula is P ij ＝p*l ij ，P ij The transmission loss amount of the power transmission line corresponding to the power transmission line diameter is expressed as the transmission loss amount of the power transmission line corresponding to the power transmission line of the j power utilization user of the i power station, and p is expressed as the transmission loss amount of the power transmission line corresponding to the power transmission line diameter of the unit length, l ij The length of the transmission line corresponding to each power station to each power utilization user is expressed;
and B4, accumulating the transmission loss quantity of each power station corresponding to each power utilization user to obtain the total transmission loss quantity corresponding to each power station.
5. The distribution network planning method based on big data analysis and supply and demand double-sided collaborative optimization according to claim 1, wherein the method comprises the following steps: and S6, screening out power stations with unbalanced supply and demand, wherein the specific screening process is to compare the current month required power generation amount corresponding to each power station with the current month supply power generation amount, if the current month required power generation amount corresponding to a certain power station is equal to the current month supply power generation amount, the power station is marked as the power station with unbalanced supply and demand, and if the current month required power generation amount corresponding to the certain power station is unequal to the current month supply power generation amount, the power station is marked as the power station with unbalanced supply and demand.
6. The distribution network planning method based on big data analysis and supply and demand double-sided collaborative optimization according to claim 1, wherein the method comprises the following steps: in the step S7, the supply-demand unbalanced type judgment is performed on each supply-demand unbalanced power station according to the intelligent planning and allocation terminal, and then the power generation capacity allocation is performed on the supply-demand unbalanced power station with the supply-demand unbalanced type being the supply-demand unbalanced power station from the supply-demand unbalanced type nearby, which comprises the following specific operation steps:
comparing the current month required power generation amount corresponding to each unbalanced supply and demand power generation station with the current month supply power generation amount, if the current month required power generation amount corresponding to a certain unbalanced supply and demand power generation station is larger than the current month supply power generation amount, the type of supply and demand unbalance corresponding to the unbalanced supply and demand power generation station is supply and demand, and if the current month required power generation amount corresponding to the certain unbalanced supply and demand power generation station is smaller than the current month supply power generation amount, the type of supply and demand unbalance corresponding to the unbalanced supply and demand power generation station is supply and demand;
C2, comparing the supply and demand unbalanced types corresponding to the supply and demand unbalanced power stations with each other, classifying the power stations corresponding to the same supply and demand unbalanced type, and obtaining a plurality of supply and demand unbalanced power stations corresponding to supply and demand and a plurality of supply and demand unbalanced power stations corresponding to supply and demand, wherein the supply and demand unbalanced power stations corresponding to supply and demand are denoted as supply and demand power stations, and the supply and demand unbalanced power stations corresponding to supply and demand are denoted as supply and demand power stations;
the corresponding numbers of the supply and demand power stations and the supply and demand power stations are counted respectively, so that the geographic positions of the supply and demand power stations and the supply and demand power stations are obtained;
c4, comparing the geographical position of each supply and demand power station with the geographical position of all supply and demand power stations to obtain the route distance between each supply and demand power station and each supply and demand power station, so that each supply and demand power station corresponding to each supply and demand power station is ordered according to the sequence from the near to the far of the route distance between each supply and demand power station and each supply and demand power station to obtain the ordering result of the supply and demand power stations corresponding to each supply and demand power station;
c5, subtracting the current month supply generating capacity from the current month demand generating capacity corresponding to each supply-demand generating station to obtain supply shortage generating capacity corresponding to each supply-demand generating station, and subtracting the current month supply generating capacity from the current month supply generating capacity corresponding to each supply-demand generating station to obtain supply surplus generating capacity corresponding to each supply-demand generating station;
C6, carrying out generating capacity allocation on each supply and demand generating station in turn according to the corresponding number sequence of each supply and demand generating station, wherein the specific allocation process is to extract the supply and demand generating station arranged at the first position from the supply and demand generating station sequencing result corresponding to the current demand generating station, and compare the supply and demand generating station corresponding to the current demand generating station with the supply and demand generating station corresponding to the first position, if the supply and demand generating capacity is larger than the supply and demand generating capacity, the supply and demand generating station corresponding to the current demand generating station is indicated to be not met, at the moment, the supply and demand generating station arranged at the next position is continuously extracted from the supply and demand generating station sequencing result corresponding to the current demand generating station, the supply and demand generating station is processed according to the method of the step until the supply and demand generating station corresponding to the last position is extracted, if the supply and demand generating capacity is smaller than or equal to the supply and demand generating station corresponding to the current demand generating station is not met, and the supply and demand generating station corresponding to the current demand generating station is not met, the supply and the current generating station is not met, the current demand generating station is not met, and the supply and the power station is required and the current generating station is required to be met, and then, according to the new supply and demand power station sequencing result corresponding to the supply and demand power station allocated with the next required power generation amount, continuing to allocate the power generation amount of the supply and demand power station according to the allocation method of the step.
7. A distribution network planning system based on big data analysis and supply and demand double-sided collaborative optimization for performing the method of any of the preceding claims 1-6, characterized by: the system comprises a urban area power station statistics module, a power station distribution area determination module, a power station current month power consumption statistics module, a power station transmission loss statistics module, a power station current month demand power generation amount statistics module, a power distribution database, an analysis cloud platform and an intelligent planning and allocation terminal, wherein the urban area power station statistics module is connected with the power station distribution area determination module, the power station distribution area determination module is respectively connected with the power station current month power consumption statistics module and the power station transmission loss statistics module, the power station current month power consumption statistics module and the power station transmission loss statistics module are both connected with the power station current month demand power generation amount statistics module, the urban area power station statistics module and the power station current month demand power generation amount statistics module are both connected with the analysis cloud platform, and the analysis cloud platform is connected with the intelligent planning and allocation terminal.
8. The utility model provides a distribution network planning equipment based on big data analysis and supply and demand double-sided collaborative optimization which characterized in that: the system comprises a processor, and a memory and a network interface which are connected with the processor; the network interface is connected with a nonvolatile memory in the server; the processor, when running, retrieving a computer program from the non-volatile memory via the network interface and running the computer program via the memory to perform the method of any of the preceding claims 1-6.
9. A storage medium, characterized by: the storage medium has a computer program recorded thereon, which when run in the memory of a server implements the method of any of the preceding claims 1-6.
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