A smart city power distribution method and system

Abstract

The present invention relates to the field of intelligent power distribution technology, specifically to an intelligent city power distribution method and system, including the following steps: counting the instantaneous power output values ​​and current power flow directions of all regional power supply units in the urban power grid, calculating the power increments within adjacent time intervals, judging the power increment change trend, and screening the power supply nodes to obtain the periodic power increment trend analysis results. In the present invention, by counting the instantaneous power output values ​​and power flow directions of the power supply units, an accurate judgment of the power change trend is achieved, the impact of sudden load fluctuations is reduced, and the problems of load overload or redundant scheduling in the traditional mode are avoided according to the calculated load growth rate. By analyzing the power flow direction to adjust the path, the load units are sorted according to the real-time demand, power factor and load change rate, and the power redundancy of non-critical areas is reduced in combination with the optimization calculation of the power supply scheduling path, and the responsiveness of the power grid in emergency situations is improved.

Description

Technical Field

[0001] The present invention relates to the technical field of intelligent power distribution, and in particular to a method and system for intelligent city power distribution. Background Art

[0002] The field of intelligent power distribution technology includes power load management, power grid dispatching, optimal allocation of power resources and other aspects, involving the automated control of power systems, distributed energy management and intelligent dispatching strategies. The core content includes the realization of a dynamic balance between power supply and demand through intelligent perception, data analysis and dispatching strategy optimization to improve power grid stability and energy efficiency. Intelligent power distribution systems usually use distributed computing, real-time monitoring and predictive control to analyze power load changes, and adjust power distribution strategies based on the operating status of the power grid to ensure the safety and economy of power supply. In addition, the field of intelligent power distribution also involves the construction of an energy Internet architecture, which enables distributed power generation, energy storage equipment and power users to interact collaboratively and improve the flexibility and reliability of the overall energy system.

[0003] Among them, the smart city power distribution method refers to a method for optimizing the allocation of power resources through data collection, power flow analysis and dynamic scheduling mechanism based on the power supply and consumption in the urban area. It covers technical matters such as power grid monitoring, load forecasting, and power flow optimization. Specifically, a load forecasting model based on real-time data is used to predict power demand, and power supply and demand are matched through power flow scheduling strategies. By establishing a regional power grid operation status model and combining the topological relationship of the power transmission network, the optimal power scheduling plan is calculated, and the power distribution path is adjusted in combination with the availability of distributed power generation units. At the same time, this method uses time series data analysis to identify the trend of power grid load changes, and adjusts the power allocation plan based on rule-based scheduling strategies or machine learning algorithms, so that urban power resources can be reasonably allocated among different regions to cope with the dynamic changes in urban electricity demand.

[0004] In terms of power flow regulation, the existing technology lacks dynamic tracking of the power increment of the power supply node, making it difficult to timely reflect the load changes in a short period, resulting in delayed grid adjustment and affecting the balance of power supply and demand. The load assessment method usually uses a static load benchmark for comparison, but fails to make dynamic adjustments based on the load change trend, resulting in a delayed response to high-growth areas during resource allocation, affecting the rationality of power supply. The selection of power flow adjustment paths relies more on empirical settings rather than on real-time calculated power adjustment efficiency, which can easily lead to a lack of flexibility in the scheduling scheme and uneven power flow distribution. The priority determination of load units relies on fixed parameters, and fails to sort the criticality index according to the real-time changes in power demand, resulting in some critical load units not receiving sufficient support in the case of power shortage. In the process of emergency power dispatch, power allocation is usually carried out according to established rules, and the power supply strategy is not optimized in combination with the real-time power grid status, making it difficult to meet the stability requirements of the power grid due to sudden load changes. Summary of the invention

[0005] The purpose of the present invention is to solve the shortcomings of the prior art and to propose a smart city power distribution method.

[0006] In order to achieve the above object, the present invention adopts the following technical solution: a smart city power distribution method, comprising the following steps: S1: Count the instantaneous power output values ​​and current power flow directions of all regional power supply units in the urban power grid, calculate the power increments in adjacent time intervals, determine the power increment change trend, and screen the power supply nodes to obtain the periodic power increment trend analysis results; S2: Based on the cycle power increment trend analysis result, calculate the regional load growth rate, screen the grid load area that exceeds the load threshold, calculate the current power flow direction change rate, determine the power flow direction adjustment demand, and obtain the power flow change analysis result; S3: Based on the power flow change analysis results, calculate the load carrying capacity of the adjacent power grid load regulation zone, screen the power flow direction adjustment path, select the path with the highest adjustment efficiency, and obtain the optimal power allocation path; S4: obtaining the real-time load demand, load change rate, and power factor of the load units of the urban power grid, determining the availability of backup power supply, calculating the criticality index and ranking them, and obtaining the load criticality ranking result; S5: Based on the load criticality ranking result, critical load units are screened and allocable power resources are calculated, and emergency power distribution is performed according to the optimal power allocation path to obtain an urban power emergency distribution plan.

[0007] As a further solution of the present invention, the periodic power increment trend analysis results include the power increment value of the power supply node, the power increment change direction, and the increment threshold over-limit status; the power flow change analysis results include the load growth rate of the power grid load area, the power grid load area over-limit status, and the power margin of the backup power area; the optimal power allocation path includes the power flow direction adjustment path, power adjustment efficiency, and power carrying capacity status; the load criticality ranking results include the real-time load demand of the load unit, the load change rate of the load unit, and the criticality index ranking results; the urban power emergency allocation plan includes the power supply matching status of the key load units, the allocatable power resources, and the power margin status of the power adjustment center.

[0008] As a further solution of the present invention, the instantaneous power output values ​​and current power flow directions of all regional power supply units in the urban power grid are counted, the power increments in adjacent time intervals are calculated, the power increment change trend is determined, and the power supply nodes are screened to obtain the specific steps of the periodic power increment trend analysis results: S111: Based on the instantaneous power output values ​​of power supply units in all regions of the urban power grid, the current power flow direction of each power supply unit is detected, the power increment in adjacent time intervals is calculated, and the power change of each power supply unit between the current moment and the previous moment is recorded to obtain a power increment data set; S112: Analyze the power increment change trend of adjacent time intervals for the power increment values ​​of all power supply units according to the power increment data set, using the formula: ; Calculation of power supply unit The power increment change rate , filter the power supply nodes whose power increment exceeds the set increment threshold, and obtain the super-threshold power increment nodes, where, Represents the power supply unit At the moment The power output value, Represents the power supply unit At the moment The power output value, represents a time interval; S113: According to the super-threshold power increment nodes, statistics are collected on the power increment change trends of each node in multiple time intervals, the change patterns of the power increments at different time points are analyzed, and power increment trend analysis is performed to obtain periodic power increment trend analysis results.

[0009] As a further solution of the present invention, based on the periodic power increment trend analysis result, the regional load growth rate is calculated, the power grid load area exceeding the load threshold is screened, the current power flow direction change rate is calculated, and the power flow direction adjustment demand is determined. The specific steps of obtaining the power flow change analysis result are: S211: Based on the cycle power increment trend analysis result, calculate the load growth rate of the power supply unit in each area, obtain the load change amount of each area in adjacent time intervals, filter out the power grid load area whose growth rate exceeds the load threshold, and obtain the over-threshold load growth area; S212: According to the over-threshold load growth area, power margin data of adjacent backup power areas are counted using the formula: ; Calculating the backup power area Available power , obtain the backup power availability data, where, Stands for Reserve Power Area The maximum power supply capacity, Stands for Reserve Power Area The current power used, Stands for Reserve Power Area With load growth area The transmission distance between represents the number of all available backup power areas; S213: Based on the backup power availability data, calculate the current power flow direction change rate, analyze the power dispatching capability of the power supply unit, determine the power flow direction adjustment demand, and obtain the power flow change analysis result.

[0010] As a further solution of the present invention, based on the power flow change analysis results, the load carrying capacity of the adjacent power grid load regulation zone is calculated, the power flow direction adjustment path is screened, and the path with the highest adjustment efficiency is selected to obtain the optimal power allocation path. The specific steps are: S311: Based on the power flow change analysis result, calculate the load carrying capacity of the adjacent power grid load regulation zone, obtain the maximum adjustable power and current load situation of each regulation zone, determine whether the regulation zone has power adjustment capability, and obtain the adjustable load adjustment zone; S312: Based on the adjustable load adjustment area, screen the power flow direction adjustment path, using the formula: ; Calculate adjustment path Power regulation efficiency , obtain the power adjustment efficiency distribution record, where, Represents the grid node in the path The transmission power, Represents the grid node in the path The power loss, Represents the grid node in the path The transmission distance to the starting point of the path, represents the number of grid nodes in the path; S313: According to the power adjustment efficiency distribution record, the power adjustment efficiency of each path is compared, and the path with the highest adjustment efficiency is selected to obtain the optimal power adjustment path.

[0011] As a further solution of the present invention, the specific steps of obtaining the real-time load demand, load change rate, and power factor of the load unit of the urban power grid, determining the availability of the backup power supply, calculating the criticality index and ranking, and obtaining the load criticality ranking result are: S411: obtaining the real-time load demand, load change rate and power factor of the load unit of the urban power grid, calculating the available power of the backup power supply unit in combination with the power demand change of the load unit, determining the backup power supply availability of each load unit, and obtaining the backup power supply availability data; S412: According to the backup power supply availability data, the criticality index of each load unit is calculated according to the load power stability, fluctuation and adaptability of the backup power supply, using the formula: ; Calculation load unit Criticality Index , obtain the load criticality index distribution results, where, Representative load unit The historical load level, Representative load unit Load stability, Representative load unit Load fluctuations, Represents the average load fluctuation value of all load units, Stands for backup power The available power, Representative load unit The current power demand, Represents the number of all load units; S413: Based on the load criticality index distribution result, all load units are sorted according to the criticality index to obtain a load criticality sorting result.

[0012] As a further solution of the present invention, based on the load criticality ranking result, critical load units are screened and allocable power resources are calculated, and emergency power allocation is performed according to the optimal power allocation path to obtain the specific steps of the urban power emergency allocation plan: S511: Based on the load criticality ranking result, critical load units are screened, and the available power supply of each dispatching center is calculated in combination with the power margin data of the power dispatching center in the adjacent area to obtain the adjustable power resource data; S512: According to the adjustable power resource data, the power supply demand of the key load unit is matched, using the formula: ; Calculate critical load units Emergency power distribution , get the emergency power supply matching result, where, Representing the Electricity Dispatch Center of available electricity, Represents key load units With the Adjustment Center The transmission distance between Representative load unit The load criticality, Representative Transfer Center The load criticality, Represents the number of available power dispatch centers; S513: Based on the emergency power supply matching result and in accordance with the optimal power allocation path, emergency power distribution is performed to obtain an urban power emergency distribution plan.

[0013] A smart city power distribution system, comprising: The power increment trend analysis module obtains the instantaneous power output value and current power flow direction of all regional power supply units in the urban power grid, calculates the power increment in adjacent time intervals, determines the change trend and screens the power supply nodes, and generates the periodic power increment trend analysis results; The load growth assessment module calculates the regional load growth rate based on the periodic power increment trend analysis result, screens the power grid load area and calculates the current power flow direction change rate, determines the power flow direction adjustment demand, and generates the power flow change analysis result; The power flow control module calculates the load carrying capacity of the adjacent power grid load adjustment zone based on the power flow change analysis result, selects the power flow direction adjustment path and calculates the power adjustment efficiency, selects the path with the highest adjustment efficiency, and generates the optimal power allocation path; The load criticality ranking module obtains the real-time load demand, load change rate, and power factor of the load unit of the urban power grid, determines the availability of backup power supply, and simultaneously calculates the criticality index and sorts to obtain the load criticality ranking result; The emergency power distribution module screens the key load units and calculates the allocatable power resources based on the load criticality ranking results, matches the power supply requirements of the key load units, distributes emergency power according to the optimal power allocation path, and generates an urban power emergency distribution plan.

[0014] Compared with the prior art, the advantages and positive effects of the present invention are: In the present invention, by statistics of instantaneous power output values ​​and power flow directions of power supply units, combined with power increment calculations within adjacent time intervals, accurate judgment of power change trends is achieved, the impact of sudden load fluctuations is reduced, and the load growth rate is calculated and the load overlimit area is screened to avoid the problems of load overload or redundant scheduling in the traditional mode. The path is adjusted by analyzing the power flow direction, and the optimal path is screened based on the power adjustment efficiency to reduce unnecessary energy loss and improve the utilization rate of power supply resources. The load units are sorted according to their real-time demands, power factors and load change rates, so that key load units are given priority in resource allocation, thereby improving the safety and reliability of power grid operation. Combined with the optimized calculation of the power supply scheduling path, the allocable power resources are matched to make emergency power allocation more accurate, reduce power redundancy in non-critical areas, and improve the response capability of the power grid in emergency situations. BRIEF DESCRIPTION OF THE DRAWINGS

[0015] Figure 1 It is a main step flow chart of the present invention; Figure 2 This is a flow chart of step S1 of the present invention; Figure 3 This is a flow chart of step S2 of the present invention; Figure 4 This is a flow chart of step S3 of the present invention; Figure 5 This is a flow chart of step S4 of the present invention; Figure 6 This is a flow chart of step S5 of the present invention. DETAILED DESCRIPTION

[0016] In order to make the purpose, technical solution and advantages of the present invention more clearly understood, the present invention is further described in detail below in conjunction with the accompanying drawings and embodiments. It should be understood that the specific embodiments described herein are only used to explain the present invention and are not intended to limit the present invention.

[0017] In the description of the present invention, it should be understood that the terms "length", "width", "up", "down", "front", "back", "left", "right", "vertical", "horizontal", "top", "bottom", "inside", "outside" and the like indicate positions or positional relationships based on the positions or positional relationships shown in the drawings, and are only for the convenience of describing the present invention and simplifying the description, rather than indicating or implying that the device or element referred to must have a specific orientation, be constructed and operated in a specific orientation, and therefore cannot be understood as limiting the present invention. In addition, in the description of the present invention, "multiple" means two or more, unless otherwise clearly and specifically defined.

[0018] See also Figure 1 , a smart city power distribution method, comprising the following steps: S1: Count the instantaneous power output values ​​and current power flow directions of all regional power supply units in the urban power grid, calculate the power increments in adjacent time intervals, determine the power increment change trend, screen the power supply nodes whose power increments exceed the set increment threshold, and obtain the periodic power increment trend analysis results; S2: Based on the results of the periodic power increment trend analysis, calculate the regional load growth rate, screen the grid load area whose growth rate exceeds the load threshold, count the power margin data of the adjacent backup power area, calculate the current power flow direction change rate, determine the power flow direction adjustment demand, and obtain the power flow change analysis results; S3: Based on the power flow change analysis results, calculate the load carrying capacity of the adjacent power grid load regulation area, determine whether the regulation area has the power adjustment capacity, select the power flow direction adjustment path, and calculate the power adjustment efficiency of each adjustment path, select the path with the highest adjustment efficiency, and obtain the optimal power allocation path; S4: Obtain the real-time load demand, load change rate, and power factor of the load unit of the urban power grid, determine the availability of backup power supply, calculate the criticality index and sort it according to the load power stability, fluctuation, and adaptability of the backup power supply, and obtain the load criticality sorting result; S5: Based on the load criticality ranking results, critical load units are screened, and the allocatable power resources are calculated based on the power margin data of the power dispatch center in the adjacent area to match the power supply demand of critical load units. Emergency power distribution is carried out according to the optimal power dispatch path to obtain the city power emergency distribution plan.

[0019] The results of the periodic power increment trend analysis include the power increment value of the power supply node, the direction of power increment change, and the increment threshold over-limit status; the power flow change analysis results include the load growth rate of the power grid load area, the over-limit status of the power grid load area, and the power margin of the backup power area; the optimal power allocation path includes the power flow direction adjustment path, power adjustment efficiency, and power carrying capacity status; the load criticality ranking results include the real-time load demand of the load unit, the load change rate of the load unit, and the criticality index ranking results; the urban power emergency allocation plan includes the power supply matching situation of the key load units, the allocatable power resources, and the power margin status of the power adjustment center.

[0020] See also Figure 2 , the S1 step is: S111: Based on the instantaneous power output values ​​of power supply units in all regions of the urban power grid, the current power flow direction of each power supply unit is detected, the power increment in adjacent time intervals is calculated, and the power change of each power supply unit between the current moment and the previous moment is recorded to obtain a power increment data set; Based on the instantaneous power output values ​​of all regional power supply units in the urban power grid, the current power flow direction of each power supply unit is obtained, and its changes in a specific time interval are counted. For example, for five power supply units in a certain area, at time The instantaneous power output values ​​are , , , , , and at the time (interval of 5 minutes) the instantaneous power output values ​​are , , , , , calculate the power increment of each power supply unit, that is, , the power increments of the five power supply units are , , , , In the process of statistics, the power flow direction is recorded at the same time. Assuming that the power flow direction of three power supply units remains unchanged, while the power flow direction of the other two power supply units is reversed, the change in the power flow direction needs to be specially marked. Based on the statistical incremental data, the power incremental data set is obtained.

[0021] S112: Analyze the power increment change trend of adjacent time intervals for the power increment values ​​of all power supply units according to the power increment data set, using the formula: ; Calculation of power supply unit The power increment change rate , filter the power supply nodes whose power increment exceeds the set increment threshold, and obtain the super-threshold power increment nodes, where, Represents the power supply unit At the moment The power output value, Represents the power supply unit At the moment The power output value, represents a time interval; Based on the power increment data set, the power increment change trend of adjacent time intervals is analyzed for the power increment values ​​of all power supply units. Taking a power supply unit as an example, assuming that the power increments of its five historical measurement data are , the power increment change rate is calculated using the formula.

[0022] For example, for the two most recent measurements: Indicates that the power increment is decreasing, and the increment threshold is set to The value is set based on the short-term fluctuation of the power supply unit under different load conditions. The threshold is usually determined by the historical load curve characteristics of the power grid, the rated power of the power supply unit, and the standard deviation of short-term load changes. Specifically, the calculation formula for the threshold setting is: in, represents the power increment threshold, is the average value of the power increment of all power supply units within the statistical period, is the standard deviation of the power increment, is the adjustment factor, usually set at arrive to adapt to different load fluctuation conditions. Assume that during the statistical period, the average power increment of the power supply unit is , the standard deviation is , then when When , the threshold is calculated as follows: It can ensure that the set threshold can effectively screen out power supply nodes with large power increment fluctuations, while not over-amplifying the impact of normal load fluctuations, and the value varies with load characteristics and adjustment factors. As well as the fluctuations in the statistical period range, it can be flexibly adjusted to adapt to different power grid operating environments.

[0023] When filtering, power supply nodes with a value less than the threshold are excluded, and only power supply nodes with a value exceeding the set threshold are retained. For example, in this example, All exceeded The set threshold value, therefore the power supply node meets the super-threshold screening condition, and the super-threshold power increment node is obtained.

[0024] Table 1.1 Power supply unit power increment change rate table As shown in Table 1.1, for all power supply units, calculate their power increment change rate, and filter out those with a change rate greater than or equal to The power supply nodes whose power increment exceeds the set threshold are finally determined as the nodes with over-threshold power increment.

[0025] S113: according to the power increment nodes exceeding the threshold value, counting the power increment change trend of each node in multiple time intervals, analyzing the change mode of the power increment at different time points, performing power increment trend analysis, and obtaining a periodic power increment trend analysis result; According to the nodes with power increment exceeding the threshold, the power increment change trend of each node in multiple time intervals is counted, and the change pattern of power increment at different time points is analyzed. Taking five power supply nodes exceeding the threshold as an example, the power increment data of the past six measurement time points are as follows: Table 1.2 Trend table of power increment of super-threshold power supply nodes Refer to Table 1.2 to analyze the power increment trend of the power supply node in each time period. For example, power supply node 3 The power increment within the minute range varies greatly, reflecting the load fluctuation, while the increment of power supply node 5 is relatively stable, indicating that the load is relatively stable. The statistical results of all nodes are combined to finally obtain the periodic power increment trend analysis results.

[0026] See also Figure 3 , the S2 step is: S211: Based on the results of the periodic power increment trend analysis, the load growth rate of the power supply unit in each area is calculated, the load change amount of each area in adjacent time intervals is obtained, and the power grid load area whose growth rate exceeds the load threshold is screened out to obtain the over-threshold load growth area; Based on the results of the cycle power increment trend analysis, the load growth rate of each area is calculated for the power supply units in different areas of the urban power grid. First, the historical load data of each power supply unit is obtained, and the load value of each time interval is recorded. For example, for a certain area, at time The load is 150MW. The load increases to 165MW, so the load increment in this time period is 15MW. This data is collated and the load growth rate is calculated. Assuming that the time interval in this area is 1 hour, the load growth rate in this area is Similarly, the load growth rate of other areas is calculated in the same way. Then, the load growth rate of all areas is compared with the set load threshold. The load threshold is set based on the load bearing capacity of the power supply equipment, the grid dispatch response rate, and the allowable range of short-term power fluctuations. Usually, this value is affected by the maximum loadable power change rate of the substation and is calculated in combination with historical load data. For example, the rated load of a substation in a certain area is 200MW, and the short-term load increment shall not exceed 5%. Then its maximum loadable power growth rate is Therefore, 10MW / h is selected as the load threshold for screening, and the area exceeding the threshold is identified as the super-threshold load growth area. For example, if the growth rate of a certain area is 12MW / h, it is marked as a high-growth area, and if the growth rate of a certain area is only 8MW / h, it is not marked. Finally, the set of all super-threshold load growth areas is obtained as an important basis for subsequent power scheduling, and the super-threshold load growth area is obtained.

[0027] S212: According to the over-threshold load growth area, the power margin data of the adjacent backup power area is counted, using the formula: ; Calculating the backup power area Available power , obtain the backup power availability data, where, Stands for Reserve Power Area The maximum power supply capacity, Stands for Reserve Power Area The current power used, Stands for Reserve Power Area With load growth area The transmission distance between represents the number of all available backup power areas; Based on the over-threshold load growth area, the power margin data of adjacent backup power areas are counted, and the remaining power available in each backup power area is calculated. First, the maximum available power of the backup power area is obtained, and the currently used power is deducted from it to form a backup power data set. For example, the maximum available power of a certain area is 200MW, and 140MW is currently used, then the backup power of the area is 60MW. Similarly, the data of other backup areas are calculated in the same way. ,and Assuming it is 3km, then: The calculation results show that the power supply capacity of the backup area to the area with super-threshold load growth is 20MW, indicating that the current backup power area still has some available power, but attention should be paid to transmission losses during the scheduling process to finally obtain the availability of backup power.

[0028] Table 2.1: As shown in Table 2.1, there are differences in the availability of backup power in different backup power areas. The calculation results will serve as the key parameter for subsequent adjustments to the power flow direction.

[0029] S213: Based on the backup power availability data, calculate the current power flow direction change rate, analyze the power dispatching capability of the power supply unit, determine the power flow direction adjustment demand, and obtain the power flow change analysis result; Based on the availability of backup power, the current power flow direction change rate is calculated to analyze the power dispatching capability of the power supply unit. First, the actual power flow direction of each power supply unit is monitored. Assuming that the current power flow direction of a certain area is 150MW pointing to the north, after 1 hour, the power in this direction increases to 180MW, then the change rate is calculated as: Similarly, the power flow change rate calculation method for other areas is the same. The change rate data of all areas are archived, and the areas where the change rate exceeds the set adjustment threshold are marked. The power flow change adjustment threshold is set based on the grid power flow stability requirements and load distribution balance. This value is usually related to the grid instantaneous load change allowable range and the line allowable load power change rate. Assuming that the maximum allowable power of a transmission line is 500MW and its instantaneous power change allowable range is 5%, the power flow change allowable threshold can be calculated as Therefore, the power flow change adjustment threshold is set to 25MW / h. If the power flow change rate of a certain area exceeds this value, it is marked as an area that needs adjustment. For example, if the threshold is set to 25MW / h, the area with a calculated power flow of 30MW / h is identified as an area that needs to adjust the power flow direction. If the power flow change rate of a certain area is 20MW / h, it is not within the adjustment range. Finally, the data of each area is combined to determine the overall power flow direction adjustment needs of the power grid and obtain the power flow change analysis results.

[0030] Table 2.2: As shown in Table 2.2, the power flow change rate in some areas has exceeded the set adjustment threshold, and corresponding measures need to be taken for scheduling to ensure the stability of the power flow in the power grid.

[0031] See also Figure 4 , the S3 step is: S311: Based on the power flow change analysis results, calculate the load carrying capacity of the adjacent power grid load regulation zone, obtain the maximum adjustable power and current load conditions of each regulation zone, determine whether the regulation zone has power adjustment capability, and obtain the adjustable load regulation zone; Based on the results of power flow change analysis, the load carrying capacity of adjacent power grid load regulation zones is calculated. For the maximum loadable power and current load conditions of each load regulation zone, the current power demand data of each zone is first obtained. This data can be collected in real time through the load monitoring module in the power grid dispatching system. For example, at a certain moment, the load demand of zone A is 320MW, the load demand of zone B is 275MW, and the load demand of zone C is 400MW. At the same time, the historical power change trend of each zone is recorded to determine its load stability. If the load fluctuation of a certain zone is large in multiple time periods, there may be a supply shortage. For example, the load fluctuation range of area A in the past hour is ±30MW, while the fluctuation range of area B is only ±10MW. In this case, area B is relatively more stable. Then the maximum loadable power of each regulation area is calculated. This data can be determined by the transformer capacity of the power grid substation and the rated transmission capacity of the line. For example, the maximum loadable power of area A is 400MW, that of area B is 350MW, and that of area C is 420MW. The remaining power is further calculated, which is the difference between the loadable power and the current load. For example, the remaining power of area A is 400MW-320MW=80MW, and that of area B is 400MW-320MW=80MW. The surplus power of the area is 350MW-275MW=75MW, and the surplus power of area C is 420MW-400MW=20MW. For areas where the surplus power is greater than a certain threshold, the adjustment capacity threshold is set to 50MW. This threshold is formulated according to the requirements of power grid security dispatch, mainly referring to the load growth rate of each area, the load limit of power supply equipment and the historical load adjustment capacity. Assuming that the average load growth rate of a power grid system is 15MW / h, and the conventional load adjustment cycle is 3 hours, the power adjustment demand per unit time is approximately 15MW / h×3h=45MW. Taking into account the redundancy demand for power dispatching, an appropriate increase of 5MW is made. Therefore, the final adjustment capacity threshold is set at 50MW. This value may be adjusted in different regions, which is usually related to factors such as the power supply radius of the substation and the line loss rate. For example, in areas with high line loss rates (such as above 10%), the threshold can be appropriately increased to 60MW to ensure the adjustment efficiency. In areas with low loss rates (such as below 5%), the threshold can be maintained at around 50MW. In this way, areas A and B have the ability to adjust, while area C does not have the ability to adjust because its margin is less than 50MW, and finally an adjustable load adjustment zone is obtained.

[0032] S312: Based on the adjustable load regulation area, screen the power flow direction adjustment path, using the formula: ; Calculate adjustment path Power regulation efficiency , obtain the power adjustment efficiency distribution record, where, Represents the grid node in the path The transmission power, Represents the grid node in the path The power loss, Represents the grid node in the path The transmission distance to the starting point of the path, represents the number of grid nodes in the path; Based on the adjustable load regulation area, the power flow direction adjustment path is screened, and the power adjustment efficiency of each path is calculated. First, the grid connection between each regulation area and the load growth area is analyzed to obtain the transmission capacity of each power transmission line. For example, the maximum transmission capacity of line X is 120MW, line Y is 150MW, and line Z is 200MW. Then, the current transmission load of each line is obtained. For example, line X currently transmits 80MW, line Y transmits 130MW, and line Z transmits 190MW. The remaining transmission capacity of each line is calculated. For example, the remaining capacity of line X is 120MW-80MW=40MW, line Y is 150MW-130MW=20MW, and line Z is 200MW-190MW=10MW. Only the remaining capacity of line X is greater than the 50MW threshold, and it has a strong adjustment capacity. Then the power adjustment efficiency of each path is calculated.

[0033] In path X, the transmission power of node 1 is 60MW, node 2 is 50MW, node 3 is 30MW, and the total transmission power is 140MW. Represents the grid node in the path For example, node 1 loses 5MW, node 2 loses 3MW, node 3 loses 2MW, and the total loss is 10MW. Represents the grid node in the path Transmission distance to the starting point of the path. For example, the distance from node 1 to the starting point is 10 km, node 2 is 20 km, and node 3 is 30 km. Then: Calculate the power regulation efficiency of path X: The power regulation efficiency of paths Y and Z is calculated similarly, and the power regulation efficiency distribution record is summarized, as shown in Table 3.1: Table 3.1 Power adjustment efficiency distribution table As shown in Table 3.1, path X has the highest power allocation efficiency, so path X will be given priority for power allocation in the next step.

[0034] S313: comparing the power adjustment efficiency of each path according to the power adjustment efficiency distribution record, selecting the path with the highest adjustment efficiency, and obtaining the optimal power allocation path; According to the power adjustment efficiency distribution record, the power adjustment efficiency of each path is compared, and the path with the highest adjustment efficiency is selected. First, the power adjustment efficiency of all paths is sorted. For example, the efficiency of path X is the highest, which is 0.0944, followed by path Y with 0.0876, and finally path Z with 0.0815. Then, the reliability of each path is further considered, its line status is analyzed, and the operating status of the current line of each path is checked. For example, if the load rate of the main transformer of path Y has reached 95% and there is an overload risk, the path is eliminated, and finally path X is selected as the optimal power adjustment path to obtain the optimal power adjustment path.

[0035] See also Figure 5 , step S4 is: S411: obtaining the real-time load demand, load change rate and power factor of the load unit of the urban power grid, calculating the available power of the backup power supply unit in combination with the power demand change of the load unit, determining the backup power supply availability of each load unit, and obtaining the backup power supply availability data; To obtain the real-time load demand, load change rate and power factor of the urban power grid load unit, it is necessary to collect the power consumption in different areas of the city in real time. For example, monitoring devices are deployed in industrial areas, commercial areas and residential areas respectively. The monitoring equipment can record the instantaneous load conditions of each area and store its historical load change data. Assuming that the real-time load demand of the industrial area is 120MW during peak hours and 80MW during off-peak hours, the commercial area is 60MW during peak hours and 40MW during off-peak hours, and the residential area reaches 100MW during peak hours and drops to 50MW during off-peak hours, the load change rate of each area can be calculated through these data. The calculation method is: in represents the peak load value, Represents the valley load value, Represents the time span. For example, for an industrial area, the peak period lasts 4 hours and the trough period lasts 6 hours. The load change rate is calculated as In addition, the power factor needs to be calculated in combination with the active power and reactive power of each area. Assuming that the reactive power of industrial area, commercial area and residential area is 40MVar, 25MVar and 30MVar respectively, the power factor is calculated as follows: in is the active power, is the reactive power, calculated as follows: Based on these calculated values, the load characteristics of each area can be obtained, and combined with the data of the backup power supply unit, the backup power supply availability can be calculated. Assuming that the total capacity of the backup power supply is 200MW and the current power usage is 150MW, the available capacity is calculated as follows: Finally, the backup power supply availability data is obtained.

[0036] S412: Based on the backup power supply availability data, load power stability, fluctuations and backup power adaptability, calculate the criticality index of each load unit using the formula: ; Calculation load unit Criticality Index , obtain the load criticality index distribution results, where, Representative load unit The historical load level, Representative load unit Load stability, Representative load unit Load fluctuations, Represents the average load fluctuation value of all load units, Stands for backup power The available power, Representative load unit The current power demand, Represents the number of all load units; Based on the backup power supply availability data, the criticality index of each load unit is calculated according to the load power stability, fluctuation and adaptability of the backup power supply. The load power stability can be measured by the standard deviation of historical data, and the fluctuation can be calculated based on the maximum fluctuation amplitude in the past week. Assume that the historical load fluctuation data of the industrial zone is as follows (unit: MW): Its standard deviation is calculated as follows: in is the average value: Similarly, the standard deviation of loads for commercial and residential areas can be calculated.

[0037] For the adaptability of backup power supply, the geographical distance between the backup power supply and the load unit and the power transmission loss can be considered. Assuming that the backup power supply distances for industrial areas, commercial areas, and residential areas are 5km, 10km, and 8km respectively, and the transmission loss is calculated at 0.1% / km, the loss is calculated as follows: Finally, calculate according to the formula, for example, by inserting the industrial zone data: The criticality indexes of commercial areas and residential areas are calculated similarly, and finally the load criticality index distribution results are obtained.

[0038] S413: Based on the load criticality index distribution result, all load units are sorted according to the criticality index to obtain the load criticality sorting result; According to the load criticality index distribution results, all load units are sorted according to the criticality index to obtain the load criticality ranking results. Assuming that the criticality indexes calculated for commercial areas, industrial areas, and residential areas are 1.35, 1.59, and 1.28 respectively, the criticality ranking is as follows: Table 4.1: As shown in Table 4.1, the industrial area has the highest criticality index, which means that its load occupies a relatively important position in the overall power grid and needs to give priority to the backup power supply, and finally obtain the load criticality ranking results.

[0039] See also Figure 6 , step S5 is: S511: Based on the load criticality ranking results, critical load units are screened, and the available power supply of each dispatching center is calculated in combination with the power margin data of the power dispatching center in the adjacent area to obtain the adjustable power resource data; Based on the load criticality ranking results, when screening critical load units, all load units need to be screened according to their criticality index. The standard for selecting critical load units is usually set at a criticality index greater than a certain critical value, such as 0.75 (set between 0 and 1). The standard is determined by the distribution of historical load data. Specifically, if the criticality index of a load unit meets the screening conditions, it will be included in the list of critical load units. For example, if there are 10 load units in a city power grid, and their criticality indexes are 0.8, 0.72, 0.85, 0.6, 0.9, 0.88, 0.74, 0.77, 0.83, and 0.79, respectively, then the screened critical load units are: 0.8, 0.85, 0.9, 0.88, 0.77, 0.83, and 0.79. For the screened critical load units, it is necessary to further obtain the power margin data of the power dispatching center in the adjacent area. The data is usually obtained in real time by power monitoring. The power margin can be obtained through real-time data collection of the power grid dispatching center, as shown in Table 5.1: Table 5.1 Power margin table of power dispatch center As shown in Table 5.1, the power margins of different power dispatch centers are different, among which the power margin of dispatch center D is the largest, while the power margin of C is the smallest. Based on the power margin data, the adjustable power resources are obtained.

[0040] S512: According to the adjustable power resource data, match the power supply demand of key load units, using the formula: ; Calculate critical load units Emergency power distribution , get the emergency power supply matching result, where, Representing the Electricity Dispatch Center of available electricity, Represents key load units With the Adjustment Center The transmission distance between Representative load unit The load criticality, Representative Transfer Center The load criticality, Represents the number of available power dispatch centers; According to the adjustable power resource data, to match the power supply demand of key load units, it is necessary to calculate the emergency power that can be allocated to each key load unit. Taking key load unit 1 as an example, its criticality index is 0.85, and the transmission distances from the adjustment centers A, B, C, and D are 5km, 10km, 12km, and 8km respectively. The emergency power allocation calculation is as follows: That is, the allocable power of the critical load unit 1 is about 2.215MW, and the emergency power supply matching result is finally obtained.

[0041] S513: Based on the emergency power supply matching result and the optimal power allocation path, emergency power allocation is performed to obtain an urban power emergency allocation plan; The emergency power supply matching result is called, and emergency power distribution is performed according to the optimal power allocation path. The optimal power allocation path is usually determined by the path with the smallest power loss. For example, if power allocation centers A, B, C, and D are connected to key load units 1, 2, 3, and 4 respectively, the loss of each path needs to be calculated, as shown in Table 2: Table 5.2 Power allocation path loss table As shown in Table 5.2, different paths have different power losses. The path with the smaller loss rate is more optimal. For example, the loss rate of power supply from dispatch center A to key load unit 1 is the smallest, and finally the city power emergency distribution plan is obtained.

[0042] A smart city power distribution system, comprising: The power increment trend analysis module obtains the instantaneous power output value and current power flow direction of all regional power supply units in the urban power grid, calculates the power increment in adjacent time intervals, determines the change trend and screens the power supply nodes, and generates the periodic power increment trend analysis results; The load growth assessment module calculates the regional load growth rate based on the periodic power increment trend analysis results, screens the grid load area and calculates the current power flow direction change rate, determines the power flow direction adjustment demand, and generates the power flow change analysis results; The power flow control module calculates the load carrying capacity of the adjacent power grid load adjustment zone based on the power flow change analysis results, selects the power flow direction adjustment path and calculates the power adjustment efficiency, selects the path with the highest adjustment efficiency, and generates the optimal power allocation path; The load criticality ranking module obtains the real-time load demand, load change rate, and power factor of the load unit of the urban power grid, determines the availability of backup power supply, and simultaneously calculates the criticality index and sorts to obtain the load criticality ranking result; The emergency power distribution module selects key load units and calculates the allocatable power resources based on the load criticality sorting results, matches the power supply requirements of key load units, distributes emergency power according to the optimal power allocation path, and generates an urban power emergency distribution plan.

[0043] The above are only preferred embodiments of the present invention and are not intended to limit the present invention in other forms. Any technician familiar with the profession may use the technical contents disclosed above to change or modify them into equivalent embodiments with equivalent changes and apply them to other fields. However, any simple modification, equivalent change and modification made to the above embodiments based on the technical essence of the present invention without departing from the technical solution of the present invention still falls within the protection scope of the technical solution of the present invention.

Claims

1. A smart city power distribution method, characterized in that: The following steps are involved: S1: Count the instantaneous power output values ​​and current power flow directions of all regional power supply units in the urban power grid, calculate the power increments in adjacent time intervals, determine the power increment change trend, and screen the power supply nodes to obtain the periodic power increment trend analysis results; S2: Based on the cycle power increment trend analysis result, calculate the regional load growth rate, screen the grid load area that exceeds the load threshold, calculate the current power flow direction change rate, determine the power flow direction adjustment demand, and obtain the power flow change analysis result; S3: Based on the power flow change analysis results, calculate the load carrying capacity of the adjacent power grid load regulation zone, screen the power flow direction adjustment path, select the path with the highest adjustment efficiency, and obtain the optimal power allocation path; S4: obtaining the real-time load demand, load change rate, and power factor of the load units of the urban power grid, determining the availability of backup power supply, calculating the criticality index and ranking them, and obtaining the load criticality ranking result; S5: Based on the load criticality ranking result, critical load units are screened and allocable power resources are calculated, and emergency power distribution is performed according to the optimal power allocation path to obtain an urban power emergency distribution plan.

2. The smart city power distribution method according to claim 1, characterized in that: The periodic power increment trend analysis results include the power increment value of the power supply node, the power increment change direction, and the increment threshold over-limit status; the power flow change analysis results include the load growth rate of the power grid load area, the power grid load area over-limit status, and the power margin of the backup power area; the optimal power allocation path includes the power flow direction adjustment path, power adjustment efficiency, and power carrying capacity status; the load criticality ranking results include the real-time load demand of the load unit, the load change rate of the load unit, and the criticality index ranking results; the urban power emergency allocation plan includes the power supply matching status of the key load units, the allocatable power resources, and the power margin status of the power adjustment center.

3. The smart city power distribution method according to claim 1, characterized in that: The specific steps to count the instantaneous power output values ​​and current power flow directions of all regional power supply units in the urban power grid, calculate the power increments in adjacent time intervals, determine the power increment change trend, and screen the power supply nodes to obtain the periodic power increment trend analysis results are as follows: S111: Based on the instantaneous power output values ​​of power supply units in all regions of the urban power grid, the current power flow direction of each power supply unit is detected, the power increment within adjacent time intervals is calculated, and the power change of each power supply unit between the current moment and the previous moment is recorded to obtain a power increment data set; S112: Analyze the power increment change trend of adjacent time intervals for the power increment values ​​of all power supply units according to the power increment data set, using the formula: ； Calculation of power supply unit The power increment change rate , filter the power supply nodes whose power increment exceeds the set increment threshold, and obtain the super-threshold power increment nodes, where, Represents the power supply unit At the moment The power output value, Represents the power supply unit At the moment The power output value, represents a time interval; S113: According to the super-threshold power increment nodes, statistics are collected on the power increment change trends of each node in multiple time intervals, the change patterns of the power increments at different time points are analyzed, and power increment trend analysis is performed to obtain periodic power increment trend analysis results.

4. The smart city power distribution method according to claim 1, characterized in that: Based on the cycle power increment trend analysis results, the regional load growth rate is calculated, the grid load area exceeding the load threshold is screened, the current power flow direction change rate is calculated, and the power flow direction adjustment demand is determined. The specific steps of obtaining the power flow change analysis results are as follows: S211: Based on the cycle power increment trend analysis result, the load growth rate of the power supply unit in each area is calculated, the load change amount of each area in the adjacent time interval is obtained, and the power grid load area whose growth rate exceeds the load threshold is screened out to obtain the over-threshold load growth area; S212: According to the over-threshold load growth area, power margin data of adjacent backup power areas are counted using the formula: ； Calculating the backup power area Available power , obtain the backup power availability data, where, Stands for Reserve Power Area The maximum power supply capacity, Stands for Reserve Power Area The current power used, Stands for Reserve Power Area With load growth area The transmission distance between represents the number of all available backup power areas; S213: Based on the backup power availability data, calculate the current power flow direction change rate, analyze the power dispatching capability of the power supply unit, determine the power flow direction adjustment demand, and obtain the power flow change analysis result.

5. The smart city power distribution method according to claim 1, characterized in that: Based on the power flow change analysis results, the load carrying capacity of the adjacent power grid load regulation zone is calculated, the power flow direction adjustment path is screened, and the path with the highest adjustment efficiency is selected. The specific steps to obtain the optimal power allocation path are: S311: Based on the power flow change analysis result, calculate the load carrying capacity of the adjacent power grid load regulation zone, obtain the maximum adjustable power and current load situation of each regulation zone, determine whether the regulation zone has power adjustment capability, and obtain the adjustable load adjustment zone; S312: Based on the adjustable load adjustment area, screen the power flow direction adjustment path, using the formula: ； Calculate adjustment path Power regulation efficiency , obtain the power adjustment efficiency distribution record, where, Represents the grid node in the path The transmission power, Represents the grid node in the path The power loss, Represents the grid node in the path The transmission distance to the starting point of the path, represents the number of grid nodes in the path; S313: According to the power adjustment efficiency distribution record, the power adjustment efficiency of each path is compared, and the path with the highest adjustment efficiency is selected to obtain the optimal power adjustment path.

6. The smart city power distribution method according to claim 1, characterized in that: The specific steps of obtaining the real-time load demand, load change rate, and power factor of the load units of the urban power grid, determining the availability of backup power supply, calculating the criticality index and sorting them, and obtaining the load criticality sorting results are as follows: S411: obtaining the real-time load demand, load change rate and power factor of the load unit of the urban power grid, calculating the available power of the backup power supply unit in combination with the power demand change of the load unit, determining the backup power supply availability of each load unit, and obtaining the backup power supply availability data; S412: According to the backup power supply availability data, the criticality index of each load unit is calculated according to the load power stability, fluctuation and adaptability of the backup power supply, using the formula: ； Calculation load unit Criticality Index , obtain the load criticality index distribution results, where, Representative load unit The historical load level, Representative load unit Load stability, Representative load unit Load fluctuations, Represents the average load fluctuation value of all load units, Stands for backup power The available power, Representative load unit The current power demand, Represents the number of all load units; S413: Based on the load criticality index distribution result, all load units are sorted according to the criticality index to obtain a load criticality sorting result.

7. The smart city power distribution method according to claim 1, characterized in that: Based on the load criticality ranking results, critical load units are screened and allocable power resources are calculated, and emergency power distribution is performed according to the optimal power allocation path to obtain the specific steps of the urban power emergency distribution plan: S511: Based on the load criticality ranking result, critical load units are screened, and the available power supply of each dispatching center is calculated in combination with the power margin data of the power dispatching center in the adjacent area to obtain the adjustable power resource data; S512: According to the adjustable power resource data, the power supply demand of the key load unit is matched, using the formula: ； Calculate critical load units Emergency power distribution , get the emergency power supply matching result, where, Representing the Electricity Dispatch Center of available electricity, Represents key load units With the Adjustment Center The transmission distance between Representative load unit The load criticality, Representative Transfer Center The load criticality, Represents the number of available power dispatch centers; S513: Based on the emergency power supply matching result and in accordance with the optimal power allocation path, emergency power distribution is performed to obtain an urban power emergency distribution plan.

8. A smart city power distribution system, characterized in that: The system is used to execute the method according to any one of claims 1 to 7, comprising: The power increment trend analysis module obtains the instantaneous power output value and current power flow direction of all regional power supply units in the urban power grid, calculates the power increment in adjacent time intervals, determines the change trend and screens the power supply nodes, and generates the periodic power increment trend analysis results; The load growth assessment module calculates the regional load growth rate based on the periodic power increment trend analysis result, screens the power grid load area and calculates the current power flow direction change rate, determines the power flow direction adjustment demand, and generates the power flow change analysis result; The power flow control module calculates the load carrying capacity of the adjacent power grid load adjustment zone based on the power flow change analysis result, selects the power flow direction adjustment path and calculates the power adjustment efficiency, selects the path with the highest adjustment efficiency, and generates the optimal power allocation path; The load criticality ranking module obtains the real-time load demand, load change rate, and power factor of the load unit of the urban power grid, determines the availability of backup power supply, and simultaneously calculates the criticality index and sorts to obtain the load criticality ranking result; The emergency power distribution module screens the key load units and calculates the allocatable power resources based on the load criticality ranking results, matches the power supply requirements of the key load units, distributes emergency power according to the optimal power allocation path, and generates an urban power emergency distribution plan.

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