A distributed intelligent measurement and control scheduling management system based on IPT communication mechanism

Abstract

The application relates to the technical field of distributed intelligent measurement and control scheduling management, and particularly discloses a distributed intelligent measurement and control scheduling management system based on an IPT communication mechanism, which comprises a power station cluster confirmation module, a power station cluster information extraction module, an IPT communication mechanism construction module, a power grid information extraction module, a power scheduling analysis module and a database; the application confirms each power station cluster in a region from three aspects of a power grid topology, power station distance and climate conditions, and realizes orderly monitoring of the power generation of each power station cluster through the IPT communication mechanism; scheduling adaptive analysis is carried out from two aspects of whether the power generation of the power station cluster is sufficient and energy loss of power transmission between the power station cluster and the power grid, the orderliness and the intelligence of distributed energy monitoring are improved, the rationality of power station cluster clustering is improved, the flexibility of subsequent power scheduling is avoided, and therefore the stability of power grid operation is improved.

Description

TECHNICAL FIELD

[0001] The present application relates to the technical field of distributed intelligent measurement and control scheduling management, in particular to a distributed intelligent measurement and control scheduling management system based on IPT communication mechanism. BACKGROUND

[0002] With the increasing proportion of renewable energy in power supply, such as the emergence of a large number of photovoltaic power station clusters, the demand for fine and intelligent management of power systems is increasingly urgent. Through distributed photovoltaic clustering to voltage coordinated regulation, the cluster autonomy and global power regulation and optimization between clusters are realized, the flexible resources are reasonably optimized, the power output is coordinated, the advantages are complementary, and the standardized management and unified scheduling of centralized and distributed resources are realized through integrated control of main and distribution, and the adjustable and controllable ability of power system is improved.

[0003] The prior art also has the following problems:

[0004] 1. For distributed photovoltaic power stations, in the photovoltaic power station monitoring system, the information end of each photovoltaic power station needs to be individually connected with multiple devices or nodes, resulting in complex wiring. At the same time, due to the different installation positions of sensors in photovoltaic power stations, if the intelligent monitoring nodes are accessed to the measurement and control network in the traditional way, it is difficult to guarantee the orderliness and regularity of the access, and there are problems such as poor distributed photovoltaic data transmission quality, poor data system sharing, relatively large wiring operation amount and high cost, and inability to control.

[0005] 2. For photovoltaic power station clusters, the comprehensive analysis of photovoltaic power station clusters is not carried out from the aspects of power grid topology structure, power station distance and similar climate conditions, which reduces the rationality of power station cluster clustering, limits the flexibility of subsequent power scheduling, and increases the operation and maintenance cost of subsequent power scheduling.

[0006] 3. In the power station cluster power generation prediction aspect, the influence of climate condition deviation on power generation prediction is not analyzed, which reduces the accuracy of power station cluster power generation prediction and cannot provide effective data support for subsequent power grid power scheduling.

[0007] 4. In the power grid power consumption scheduling aspect, the scheduling adaptation analysis is not carried out from the aspects of whether the power generation of power station cluster is sufficient and the energy loss of power transmission between power station cluster and power grid, which cannot guarantee the sufficiency of power supply required by power grid, thereby reducing the stability of power grid operation, causing a large amount of power to be wasted in the transmission process, reducing the energy utilization efficiency, and increasing energy waste. SUMMARY

[0008] In view of this, in order to solve the problems raised in the background art, a distributed intelligent measurement and control scheduling management system based on IPT communication mechanism is proposed.

[0009] The object of the present application can be achieved by the following technical solution: The present application provides a distributed intelligent measurement and control scheduling management system based on an IPT communication mechanism, comprising: a power station cluster confirmation module, configured to extract the substations accessed by each photovoltaic power station in a target area, obtain each preliminary power station cluster in the target area, extract the location and climate condition information of each photovoltaic power station in each preliminary power station cluster, and confirm each power station cluster in the target area.

[0010] A power station cluster information extraction module, configured to extract the light intensity and light duration corresponding to each photovoltaic power station in each power station cluster in the target area on the current monitoring day, and extract the installation position of each photovoltaic panel in each photovoltaic power station.

[0011] An IPT communication mechanism construction module, configured to connect the information terminals of each photovoltaic power station in each power station cluster in the target area together through a cable, form the intelligent sensing link corresponding to each power station cluster, and in the distributed communication network based on the intelligent sensing link corresponding to each power station cluster, each intelligent monitoring node of each photovoltaic power station in each power station cluster is unordered accessed to the measurement and control network of the corresponding power station cluster according to the installation position of the sensor, so that the power generation of each power station cluster in the target area on the current monitoring day is orderly monitored.

[0012] A power grid information extraction module, configured to extract the total load and total output power corresponding to each power grid in the target area on the current monitoring day, confirm each power scheduling grid in the target area on the current monitoring day, extract the location of the substation of each power scheduling grid, and extract the length of the power transmission line between each power scheduling grid and each power station cluster.

[0013] A power scheduling analysis module, configured to perform power scheduling on each power scheduling grid in the target area on the current monitoring day.

[0014] A database, configured to store the reference light intensity, reference light duration, and single-day reference power generation of the installation angle of each photovoltaic panel in each photovoltaic power station in each power station cluster, and store the loss power corresponding to the unit power transmission line length in the power transmission of each power grid in the target area.

[0015] Compared with the prior art, the embodiments of the present application have at least the following advantages or beneficial effects: (1) The present application confirms each power station cluster in the target area from three aspects of the power grid topology structure, the distance between power stations, and the similarity of climate conditions, improves the rationality of power station cluster clustering, avoids the limitation of the flexibility of subsequent power scheduling, and reduces the operation and maintenance cost of subsequent power scheduling.

[0016] (2) The application improves the accuracy of power generation prediction of the power station cluster by analyzing the influence of climate condition deviation on power generation prediction in the aspect of power generation prediction of the power station cluster, and provides effective data support for subsequent power grid power scheduling.

[0017] (3) The application confirms the adaptive power station cluster corresponding to the required power scheduling power grid by scheduling adaptive analysis from two aspects of whether the power generation of the power station cluster is sufficient and energy loss of power transmission between the power station cluster and the power grid, thereby guaranteeing the sufficiency of power supply required by the power grid, improving the stability of the power grid operation, avoiding the waste of a large amount of power in the transmission process, improving the energy utilization efficiency, and reducing energy waste. BRIEF DESCRIPTION OF DRAWINGS

[0018] In order to more clearly illustrate the technical solutions of the embodiments of the application, the following will briefly introduce the drawings needed to be used in the description of the embodiments. Obviously, the drawings in the following description are only some embodiments of the application, and other drawings can be obtained by those skilled in the art without creative labor.

[0019] Figure 1 It is a schematic diagram of the system module structure of the application.

[0020] Figure 2 It is a flow chart for confirming the adaptive power station cluster of the power scheduling power grid of the application.

[0021] Figure 3 It is a schematic diagram of the power station cluster in the target area of the application.

[0022] BRIEF DESCRIPTION OF DRAWINGS: 1, target area, 2, preliminary power station cluster, 3, power station cluster, 4, photovoltaic power station. DETAILED DESCRIPTION

[0023] The technical solutions in the embodiments of the application will be described clearly and completely below with reference to the drawings in the embodiments of the application. Obviously, the described embodiments are only some embodiments of the application, not all the embodiments. Based on the embodiments in the application, all other embodiments obtained by those skilled in the art without creative labor are within the protection scope of the application.

[0024] Please refer to Figure 1 The application provides a distributed intelligent measurement and control scheduling management system based on IPT communication mechanism, which comprises a power station cluster confirmation module, a power station cluster information extraction module, an IPT communication mechanism construction module, a power grid information extraction module, a power scheduling analysis module and a database.

[0025] The power station cluster confirmation module is connected with the power station cluster information extraction module, the power station cluster information extraction module is connected with the IPT communication mechanism construction module, both the IPT communication mechanism construction module and the power grid information extraction module are connected with the power dispatching analysis module, and both the IPT communication mechanism construction module and the power dispatching analysis module are connected with the database.

[0026] Please refer to Figure 3 As shown in the figure, the power station cluster confirmation module is used for extracting the transformer substations to which the photovoltaic power stations in the target region are connected, obtaining each preliminary power station cluster in the target region, extracting the location and climate condition information of each photovoltaic power station in each preliminary power station cluster, and confirming each power station cluster in the target region.

[0027] It should be noted that the transformer substations to which the photovoltaic power stations in the target region are connected are obtained from the photovoltaic power station construction manual of the target region, and the location of each photovoltaic power station in each preliminary power station cluster is obtained from the GPS system.

[0028] In the embodiment of the application, the manner of obtaining each preliminary power station cluster in the target region is that, based on the transformer substations to which the photovoltaic power stations in the target region are connected, the photovoltaic power stations connected to the same transformer substation are recorded as power stations with the same power grid topology, and each power station with the same power grid topology is clustered into a preliminary power station cluster, thereby obtaining each preliminary power station cluster in the target region.

[0029] It should be noted that the power grid topology is the most critical factor affecting the access and operation of distributed photovoltaic power stations. From the perspective of safe and stable operation of the power grid, clustering is first considered according to the power grid topology. This is because the operation mode, power flow distribution, and voltage regulation of the power grid are closely related to the physical connection of the power grid. For example, the photovoltaic power stations connected to the same transformer substation determine their common influence on the voltage, frequency, and other parameters of the power grid. If the power grid topology is not considered first, and different power stations are randomly clustered, it may cause chaos in the local power flow distribution of the power grid, affecting the safe and stable operation of the power grid.

[0030] In the embodiment of the application, the climate condition information includes daily average light intensity, time points of occurrence of light intensity peak and light intensity valley on each historical monitoring day, and daily average temperature, time points of occurrence of maximum temperature and minimum temperature on each historical monitoring day.

[0031] It should be noted that the daily average light intensity, the time points of occurrence of light intensity peak and light intensity valley on each historical monitoring day, and the daily average temperature, the time points of occurrence of maximum temperature and minimum temperature on each historical monitoring day are all obtained from the meteorological information platform.

[0032] In the embodiments of the present application, the specific way of confirming each power station cluster in the target region is: A1, randomly selecting a photovoltaic power station from each preliminary power station cluster as the target power station of each preliminary power station cluster.

[0033] A2, analyzing the comprehensive similarity θ of the target power station of each preliminary power station cluster and the remaining photovoltaic power stations ij , wherein i represents the number of the preliminary power station cluster, i = 1, 2,..., n, and j represents the number of the remaining photovoltaic power stations, j = 1, 2,..., m.

[0034] In the embodiments of the present application, the specific process of analyzing the comprehensive similarity of the target power station of each preliminary power station cluster and the remaining photovoltaic power stations is: B1, calculating the distance proximity β of the target power station of each preliminary power station cluster and the remaining photovoltaic power stations based on the positions of the photovoltaic power stations in each preliminary power station cluster ij .

[0035] It should be noted that the specific process of calculating the distance proximity of the target power station of each preliminary power station cluster and the remaining photovoltaic power stations is: obtaining the distance of the target power station of each preliminary power station cluster and the remaining photovoltaic power stations, and denoted as L ij .

[0036] It should be noted that the way of obtaining the distance of the target power station of each preliminary power station cluster and the remaining photovoltaic power stations is: marking the positions of the target power station and the remaining photovoltaic power stations in GIS, and then directly calculating the distance of the target power station and the remaining photovoltaic power stations through the measurement tool of GIS.

[0037] Obtaining the distance between each adjacent photovoltaic power station in each preliminary power station cluster, and performing mean calculation on the distance, taking the calculation result as the reference value of the power station distance of each preliminary power station cluster, and denoted as

[0038] It should be noted that the way of obtaining the distance between each adjacent photovoltaic power station in each preliminary power station cluster is: marking the positions of the photovoltaic power stations in each preliminary power station cluster in GIS, and then directly calculating the distance between each adjacent photovoltaic power station in each preliminary power station cluster through the measurement tool of GIS.

[0039] Calculating the distance proximity β of the target power station of each preliminary power station cluster and the remaining photovoltaic power stations ij ,

[0040] B2, extract the daily average light intensity, the time point of the light intensity peak and the light intensity valley of each historical monitoring day, and the daily average temperature, the time point of the highest temperature and the lowest temperature of each historical monitoring day from the climate condition information of each photovoltaic power station in each preliminary power station cluster, and calculate the climate similarity χ of the target power station of each preliminary power station cluster and the remaining photovoltaic power stations ij .

[0041] In specific embodiments of the present application, the specific process of calculating the climate similarity of the target power station of each preliminary power station cluster and the remaining photovoltaic power stations is: C1, calculating the climate similarity of the target power station of each preliminary power station cluster and the remaining photovoltaic power stations in the light intensity layer

[0042] It should be noted that the specific process of calculating the climate similarity of the target power station of each preliminary power station cluster and the remaining photovoltaic power stations in the light intensity layer is: subtracting the daily average light intensity of the target power station of each preliminary power station cluster and the remaining photovoltaic power stations to obtain the daily average light intensity deviation of the target power station of each preliminary power station cluster and the remaining photovoltaic power stations, and denoted as τ ij .

[0043] Comparing the time point of the light intensity peak of each historical monitoring day of the target power station of each preliminary power station cluster and the remaining photovoltaic power stations, obtaining the deviation length of the light intensity peak of each historical monitoring day of the target power station and the remaining photovoltaic power stations, and extracting the maximum value as the deviation length of the light intensity peak of each preliminary power station cluster and the remaining photovoltaic power stations, denoted as

[0044] Obtaining the deviation length of the light intensity valley of each preliminary power station cluster and the remaining photovoltaic power stations

[0045] It should be noted that the way of obtaining the deviation length of the light intensity valley of each preliminary power station cluster and the remaining photovoltaic power stations is: comparing the time point of the light intensity valley of each historical monitoring day of the target power station of each preliminary power station cluster and the remaining photovoltaic power stations, obtaining the deviation length of the light intensity valley of each historical monitoring day of the target power station and the remaining photovoltaic power stations, and extracting the maximum value as the deviation length of the light intensity valley of each preliminary power station cluster and the remaining photovoltaic power stations.

[0046] Calculating the climate similarity of the target power station of each preliminary power station cluster and the remaining photovoltaic power stations in the light intensity layer Wherein, τ', T 峰 and T 谷respectively represent the set reference day average light intensity deviation, the light intensity peak value appearing deviation time length and the light intensity valley appearing deviation time length.

[0047] It should be noted that the set reference day average light intensity deviation, the light intensity peak value appearing deviation time length and the light intensity valley appearing deviation time length are specified by the power station cluster industry.

[0048] C2, the climate similarity of the target power station of each preliminary power station cluster and the remaining photovoltaic power stations in the light intensity layer is calculated in the same way.

[0049] C3, the climate similarity χ of the target power station of each preliminary power station cluster and the remaining photovoltaic power stations is calculated. ij , Wherein, b1 and b2 respectively represent the set light intensity layer and temperature layer climate similarity corresponding climate similarity evaluation proportion weight, b1+b2=1.

[0050] In the specific embodiments of the present application, the set value of b1 is 0.6, and the set value of b2 is 0.4. Light intensity is the core driving factor of photovoltaic power generation, and the similarity of light intensity has a key influence on the power generation income and resource utilization efficiency of the power station. Therefore, when calculating the climate similarity of the target power station of each preliminary power station cluster and the remaining photovoltaic power stations, the climate similarity weight proportion in the light intensity layer is larger.

[0051] B3, the comprehensive similarity θ of the target power station of each preliminary power station cluster and the remaining photovoltaic power stations is calculated. ij , Wherein, a1 and a2 respectively represent the set distance proximity and climate similarity corresponding comprehensive similarity evaluation proportion weight, a1+a2=1.

[0052] In the specific embodiments of the present application, the set value of a1 is 0.5, and the set value of a2 is 0.5. When calculating the comprehensive similarity of the target power station of each preliminary power station cluster and the remaining photovoltaic power stations, the distance proximity and the climate similarity are equally important, complementary to each other, and mutually influenced, thus requiring comprehensive analysis.

[0053] A3, the comprehensive similarity of the target power station of each preliminary power station cluster and the remaining photovoltaic power stations is compared with the set reference comprehensive similarity. If the comprehensive similarity of the target power station and the remaining photovoltaic power station is greater than or equal to the set reference comprehensive similarity, the photovoltaic power station is taken as the clustering power station of the target power station. In this way, the clustering power stations of the target power station are obtained, and the target power station cluster is clustered to obtain the target power station cluster of each preliminary power station cluster.

[0054] A4, each photovoltaic power station in the target power station cluster of each preliminary power station cluster is removed, and a certain photovoltaic power station is randomly selected as a target power station, and the same analysis method is used to obtain each power station cluster in each preliminary power station cluster, so as to obtain each power station cluster in the target region.

[0055] It should be noted that when each power station cluster in each preliminary power station cluster is obtained, the power station cluster is taken as a unit, so that each power station cluster in the target region is obtained.

[0056] The embodiment of the application confirms each power station cluster in the target region from three aspects of power grid topology, distance between power stations and similar climate conditions, improves the rationality of power station cluster clustering, avoids the limitation of flexibility of subsequent electric energy scheduling, and reduces the operation and maintenance cost of subsequent electric energy scheduling.

[0057] The power station cluster information extraction module is configured to extract the illumination intensity and illumination duration of each photovoltaic power station in each power station cluster in the target region on the current monitoring day, and extract the installation position of each photovoltaic panel in each photovoltaic power station.

[0058] It should be noted that the illumination intensity and illumination duration of each photovoltaic power station in each power station cluster in the target region on the current monitoring day are collected from the meteorological information platform, and the installation position of each photovoltaic panel in each photovoltaic power station is extracted from the photovoltaic management system of the corresponding photovoltaic power station.

[0059] The IPT communication mechanism construction module is configured to connect the information terminals of each photovoltaic power station in each power station cluster in the target region through a cable, form an intelligent sensing link corresponding to each power station cluster, and in the distributed communication network based on the intelligent sensing link corresponding to each power station cluster, each intelligent monitoring node of each photovoltaic power station in each power station cluster is randomly accessed into the measurement and control network of the corresponding power station cluster according to the installation position of the sensor, so that the power generation of each power station cluster in the target region on the current monitoring day is sequentially monitored.

[0060] In the embodiment of the application, the specific process of sequentially monitoring the power generation of each power station cluster in the target region on the current monitoring day is as follows: D1, based on the illumination intensity and illumination duration of each photovoltaic power station in each power station cluster in the target region on the current monitoring day and the installation position of each photovoltaic panel in each photovoltaic power station, the power generation influence factor λ of each photovoltaic panel in each photovoltaic power station in each power station cluster corresponding to the meteorological layer is set. gpr Wherein, g represents the number of power station clusters, g = 1, 2,..., z, p represents the number of photovoltaic power stations, p = 1, 2,..., q, and r represents the number of photovoltaic panels, r = 1, 2,..., x.

[0061] In specific embodiments of the present application, the specific process of setting the meteorological level power generation influence factor of each photovoltaic power generation panel in each photovoltaic power station in each power station cluster is as follows: E1, according to the installation position of each photovoltaic power generation panel in each photovoltaic power station, the reference light intensity and the reference light duration of the installation angle to which each photovoltaic power generation panel in each photovoltaic power station in each power station cluster belongs are located from the database, and are respectively recorded as and

[0062] E2, the light intensity and light duration corresponding to the current monitoring day of each photovoltaic power station in each power station cluster in the target area are recorded as ε gp and T gp .

[0063] E3, the meteorological level power generation influence factor λ gpr of each photovoltaic power generation panel in each photovoltaic power station in each power station cluster is set , wherein e represents a natural constant.

[0064] D2, the single-day reference power generation amount of the installation angle to which each photovoltaic power generation panel in each photovoltaic power station in each power station cluster belongs is extracted from the database, and is recorded as

[0065] D3, the power generation amount Q g of each power station cluster in the target area in the current monitoring day is predicted , wherein x represents the number of photovoltaic power generation panels, and q represents the number of photovoltaic power stations.

[0066] The embodiments of the present application improve the accuracy of power station cluster power generation prediction by analyzing the influence of climate condition deviation on power generation prediction in the aspect of power station cluster power generation prediction, and provide effective data support for subsequent power grid energy scheduling.

[0067] The power grid information extraction module is configured to extract the total load and total output power of each power grid in the target area corresponding to the current monitoring day, identify each power scheduling power grid in the target area in the current monitoring day, extract the location of the transformer substation of each power scheduling power grid, and extract the length of the power transmission line between each power scheduling power grid and each power station cluster.

[0068] It should be noted that the total load of each power grid in the target area corresponding to the current monitoring day is collected by collecting the load of each node in each power grid through the smart meter arranged at each node in each power grid, and then adding the loads to obtain the total load of each power grid corresponding to the current monitoring day. The total output power of each power grid in the target area corresponding to the current monitoring day refers to the cumulative value of the output power of each power plant in each power grid.

[0069] It should be noted that the manner of the target region in the current monitoring day is that the total load and the total output power of each power grid in the target region in the current monitoring day are compared, and if the total load of a power grid in the current monitoring day is greater than the total output power, the power grid is recorded as a power scheduling power grid, thereby obtaining each power scheduling power grid of the target region in the current monitoring day.

[0070] It should be further noted that the positions of the transformer substations of each power scheduling power grid are extracted from the GPS system, and the lengths of the power transmission lines between each power scheduling power grid and each power station cluster are extracted from the power transmission management system of the target region.

[0071] The power scheduling analysis module is configured to perform power scheduling on each power scheduling power grid of the target region in the current monitoring day.

[0072] In specific embodiments of the present application, the specific process of performing power scheduling on each power scheduling power grid of the target region in the current monitoring day is as follows: F1, the total load and the total output power of each power scheduling power grid in the current monitoring day are extracted from the total load and the total output power of each power grid in the target region in the current monitoring day, and the difference is obtained to obtain the required supplementary power of each power scheduling power grid in the current monitoring day.

[0073] Please refer to Figure 2 F2, each to-be-adapted power station cluster corresponding to each power scheduling power grid in the current monitoring day is obtained.

[0074] It should be noted that the specific manner of obtaining each to-be-adapted power station cluster corresponding to each power scheduling power grid in the current monitoring day is that the required supplementary power of each power scheduling power grid in the current monitoring day is compared with the power generation of each power station cluster in the target region in the current monitoring day, and if the power generation of a power station cluster in the current monitoring day is greater than the required supplementary power of a power scheduling power grid in the current monitoring day, the power station cluster is regarded as a to-be-adapted power station cluster of the power scheduling power grid, otherwise, the power station cluster is regarded as a non-adapted power station cluster of the power scheduling power grid, thereby obtaining each to-be-adapted power station cluster corresponding to each power scheduling power grid in the current monitoring day.

[0075] F3, based on the positions of the transformer substations of each power scheduling power grid and the lengths of the power transmission lines between each power scheduling power grid and each power station cluster, the scheduling adaptation degree between each power scheduling power grid and each to-be-adapted power station cluster corresponding thereto is calculated Wherein, y represents the number of power scheduling power grid, y=1, 2,..., s, u represents the number of to-be-adapted power station cluster, u=1, 2,..., l.

[0076] In the embodiment of the present application, the specific process of calculating the scheduling adaptation degree between each required power scheduling power grid and each corresponding to-be-adapted power station cluster is: G1, obtaining the distance between each substation of each required power scheduling power grid and each photovoltaic power station in each corresponding to-be-adapted power station cluster, and performing mean value calculation to obtain the distance between each substation of each required power scheduling power grid and each corresponding to-be-adapted power station cluster, denoted as L y u .

[0077] It should be noted that the distance between each substation of each required power scheduling power grid and each photovoltaic power station in each corresponding to-be-adapted power station cluster is obtained in the following manner: marking the location of each substation of each required power scheduling power grid in GIS, and then directly calculating the distance between each substation of each required power scheduling power grid and each photovoltaic power station in each corresponding to-be-adapted power station cluster through the measurement tool of GIS.

[0078] G2, extracting the power transmission line length between each required power scheduling power grid and each corresponding to-be-adapted power station cluster from the power transmission line length between each required power scheduling power grid and each power station cluster, denoted as

[0079] G3, extracting the loss power corresponding to the unit power transmission line length in the power transmission of each power grid in the target region from the database, and then matching to obtain the loss power corresponding to the unit power transmission line length in the power transmission of each required power scheduling power grid, denoted as

[0080] G4, calculating the scheduling adaptation degree between each required power scheduling power grid and each corresponding to-be-adapted power station cluster Wherein, L' and Q 损 respectively represent the distance and loss power between the set reference power grid and power station cluster.

[0081] F4, extracting the to-be-adapted power station cluster corresponding to the maximum scheduling adaptation degree from the scheduling adaptation degree between each required power scheduling power grid and each corresponding to-be-adapted power station cluster, and taking it as the adapted power station cluster of each required power scheduling power grid, so that the adapted power station cluster of each required power scheduling power grid supplements the power of each required power scheduling power grid.

[0082] The embodiment of the present application analyzes the scheduling adaptation from two aspects of whether the power generation of the power station cluster is sufficient and the energy loss of the power transmission between the power station cluster and the power grid, so as to confirm the adapted power station cluster corresponding to the required power scheduling power grid, guarantee the sufficiency of the required power supplement of the power grid, improve the stability of the power grid operation, avoid the waste of a large amount of power in the transmission process, improve the energy utilization efficiency, and reduce the energy waste.

[0083] ​The database is used for storing the reference light intensity, the reference light duration and the single-day reference power generation of the installation angle of each photovoltaic power generation panel in each photovoltaic power station in each power station cluster, and storing the loss power corresponding to the unit length of the power transmission line in the power transmission of each power grid in the target area. The data source in the database of the embodiment is shown in Table 1.

[0084] Table 1 Data source in the database

[0085]

[0086]

[0087] The above is only an example and description of the concept of the present application. Those skilled in the art can make various modifications or supplements to the described specific embodiments or replace them with similar ways, as long as they do not deviate from the concept of the present application or exceed the scope defined by the present application, which shall belong to the protection scope of the present application.

Claims

1. A distributed intelligent measurement and control scheduling management system based on an IPT communication mechanism, characterized in that, The method comprises the following steps: A power station cluster confirmation module is used to extract the substations to which the photovoltaic power stations in a target region are connected, obtain each preliminary power station cluster in the target region, extract the location and climate condition information of each photovoltaic power station in each preliminary power station cluster, and confirm each power station cluster in the target region; The manner of obtaining each preliminary power station cluster in the target region is that, based on the substations to which the photovoltaic power stations in the target region are connected, the photovoltaic power stations connected to the same substation are recorded as power grid topology identical power stations, and each power grid topology identical power station is clustered into a preliminary power station cluster, thereby obtaining each preliminary power station cluster in the target region; The specific manner of confirming each power station cluster in the target region is that: A1, a certain photovoltaic power station is randomly selected from each preliminary power station cluster as a target power station of each preliminary power station cluster; A2, analyzing the comprehensive similarity of the target power station of each preliminary power station cluster and the rest of each photovoltaic power station wherein, denotes the number of the preliminary power station cluster, , denotes the number of the rest of each photovoltaic power station, ; A3, the comprehensive similarity between the target power station of each preliminary power station cluster and the remaining photovoltaic power stations is compared with the comprehensive similarity of a set reference, if the comprehensive similarity between the target power station and the certain photovoltaic power station is greater than or equal to the comprehensive similarity of the set reference, the photovoltaic power station is taken as a clustered power station of the target power station, and the clustered power stations of the target power station are obtained in the same way, and the target power station cluster is obtained by clustering, thereby obtaining the target power station cluster of each preliminary power station cluster; A4, each photovoltaic power station in the target power station cluster of each preliminary power station cluster is removed, a certain photovoltaic power station is randomly selected as a target power station, and the above analysis method is the same, thereby obtaining each power station cluster in each preliminary power station cluster, and obtaining each power station cluster in the target region; A power station cluster information extraction module is used to extract the light intensity and light duration corresponding to each photovoltaic power station in each power station cluster in the target region on a current monitoring day, and extract the installation position of each photovoltaic panel in each photovoltaic power station; An IPT communication mechanism construction module is used to connect the information terminals of each photovoltaic power station in each power station cluster in the target region through a cable, form an intelligent sensing link corresponding to each power station cluster, and orderly monitor and predict the power generation of each power station cluster in the target region on the current monitoring day based on the distributed communication network of the intelligent sensing link corresponding to each power station cluster. A power grid information extraction module is used to extract the total load and total output power of each power grid in the target region on the current monitoring day, confirm each power grid requiring energy scheduling in the target region on the current monitoring day, extract the location of the substation of each power grid requiring energy scheduling, and extract the length of the power transmission line between each power grid requiring energy scheduling and each power station cluster; An energy scheduling analysis module is used to perform energy scheduling on each power grid requiring energy scheduling in the target region on the current monitoring day; A database is used to store the reference light intensity, reference light duration and single-day reference power generation of each photovoltaic panel in each photovoltaic power station in each power station cluster, and store the loss power corresponding to the unit power transmission line length in the energy transmission of each power grid in the target region.

2. The distributed intelligent measurement and control scheduling management system based on the IPT communication mechanism according to claim 1, characterized in that: The climate condition information includes daily average light intensity, time points of light intensity peak and light intensity valley of each historical monitoring day, and daily average temperature, time points of maximum temperature and minimum temperature of each historical monitoring day.

3. The distributed intelligent measurement and control scheduling management system based on the IPT communication mechanism according to claim 1, characterized in that: The specific process of analyzing the comprehensive similarity of the target power station of each preliminary power station cluster and the rest of the photovoltaic power stations is as follows: B1. calculating the distance proximity of the target power station of each preliminary power station cluster to the rest of the photovoltaic power stations in each preliminary power station cluster based on the locations of the photovoltaic power stations in each preliminary power station cluster ; B2. Extracting the daily average light intensity, the time points of the light intensity peak and the light intensity valley of each historical monitoring day, and the daily average temperature, the time points of the highest temperature and the lowest temperature of each historical monitoring day from the climate condition information of each photovoltaic power station in each preliminary power station cluster, and calculating the climate similarity of the target power station of each preliminary power station cluster and the remaining photovoltaic power stations ; B3、calculating the comprehensive similarity of each target power station of each preliminary power station cluster with the rest of the photovoltaic power stations , wherein, and respectively represent the set distance proximity and climate similarity corresponding comprehensive similarity evaluation proportion weights, .

4. The distributed intelligent measurement and control scheduling management system based on the IPT communication mechanism according to claim 3, characterized in that: The specific process of calculating the climate similarity of the target power station of each preliminary power station cluster and the rest of the photovoltaic power stations is as follows: C1. Calculate the climate similarity of each target power station in each preliminary power station cluster with the rest of the photovoltaic power stations in terms of the intensity of light ; C2. The climate similarity of the target power station of each preliminary power station cluster with the rest of the photovoltaic power stations in the temperature level is calculated in the same way as the climate similarity of the target power station of each preliminary power station cluster with the rest of the photovoltaic power stations in the light intensity level ; C3, calculating the target power station of each preliminary power station cluster and the climate similarity of the remaining photovoltaic power stations , wherein, and respectively represent the climate similarity corresponding to the climate similarity evaluation proportion weight of the set light intensity level and temperature level, .

5. The distributed intelligent measurement and control scheduling management system based on the IPT communication mechanism according to claim 1, characterized in that: The specific process of sequentially monitoring and predicting the power generation of each power station cluster in the target region in the current monitoring day is as follows: D1, based on the installation position of each photovoltaic panel in each photovoltaic power station in each power station cluster in the target area, the light intensity and light duration corresponding to the current monitoring day of each photovoltaic power station, and the installation position of each photovoltaic panel in each photovoltaic power station, set the power generation influence factor of each photovoltaic panel in each photovoltaic power station in each power station cluster corresponding to the meteorological level wherein, represents the number of power station clusters, , represents the number of photovoltaic power stations, , represents the number of photovoltaic panels, ; D2, extracting the single-day reference power generation amount of each photovoltaic panel in each photovoltaic power station in each power station cluster from the database according to the installation angle, denoted as ; D3, predict the power generation of each power plant cluster in the target area in the current monitoring day , , wherein, represents the number of photovoltaic power generation panels, represents the number of photovoltaic power plants.

6. The distributed intelligent measurement and control scheduling management system based on the IPT communication mechanism according to claim 5, characterized in that: The specific process of setting the power generation influence factor of each photovoltaic power generation panel corresponding to the meteorological level in each photovoltaic power station in each power station cluster is as follows: E1. According to the installation positions of the photovoltaic panels in each photovoltaic power station, the reference light intensity and the reference light duration of the installation angle to which the photovoltaic panels in each photovoltaic power station in each power station cluster belong are located from the database, and are respectively recorded as and ; E2, the light intensity and the light duration of each photovoltaic power station in each power station cluster in the target area on the current monitoring day are respectively recorded as and ; E3. Set the meteorological level power generation influence factor of each photovoltaic power generation panel in each photovoltaic power station in each power station cluster , wherein, represents a natural constant.

7. The distributed intelligent measurement and control scheduling management system based on the IPT communication mechanism according to claim 6, characterized in that: The specific process of performing power scheduling on each power grid requiring power scheduling in the target region in the current monitoring day is as follows: F1, extracting the total load and total output power of each power grid requiring power scheduling in the target region corresponding to the current monitoring day from the total load and total output power of each power grid in the target region corresponding to the current monitoring day, and performing subtraction to obtain the required supplementary power of each power grid requiring power scheduling corresponding to the current monitoring day; F2, obtaining each to-be-adapted power station cluster corresponding to the current monitoring day of each power grid requiring power scheduling; F3、based on the location of the transformer substation of each power dispatching grid and the length of the transmission line between each power dispatching grid and each power station cluster, calculate the dispatching adaptation degree between each power dispatching grid and its corresponding each to-be-adapted power station cluster wherein, represents the power dispatching grid number, , represents the number of the to-be-adapted power station cluster, ; F4, extracting the to-be-adapted power station cluster corresponding to the maximum scheduling adaptation degree from the scheduling adaptation degrees between each power grid requiring power scheduling and its corresponding to-be-adapted power station cluster, and taking it as the adapted power station cluster of each power grid requiring power scheduling, so that the adapted power station cluster of each power grid requiring power scheduling supplements power to each power grid requiring power scheduling.

8. The distributed intelligent measurement and control scheduling management system based on the IPT communication mechanism according to claim 7, characterized in that: The specific process of calculating the scheduling adaptation degree between each power grid requiring power scheduling and its corresponding to-be-adapted power station cluster is as follows: G1, obtain the distance between each power scheduling substation and each photovoltaic power station in the corresponding each to-be-adapted power station cluster, and perform mean value calculation to obtain the distance between each power scheduling substation and the corresponding each to-be-adapted power station cluster, denoted as ; G2, extract the power transmission line length between each power demand dispatching grid and its corresponding each to-be-adapted power station cluster from the power transmission line length between each power demand dispatching grid and each power station cluster, denoted as ; G3, extracting the loss power corresponding to the unit length of the transmission line in the power transmission of each power grid in the target area from the database, and then matching to obtain the loss power corresponding to the unit length of the transmission line in the power transmission of each power grid requiring power scheduling, and denoted as ; G4, calculate the scheduling adaptation degree between each required power scheduling power grid and its corresponding each to-be-adapted power station cluster , wherein, and respectively represent the distance and the loss power between the set reference power grid and the power station cluster.

Images