Power distribution load adaptive scheduling method and device, computer equipment and storage medium

Abstract

The invention discloses a power distribution load adaptive scheduling method and device, computer equipment and a storage medium, relates to the field of electric power, and solves the problem of poor scheduling effect of an existing power distribution load adaptive scheduling method. S2, carrying out historical power supply analysis on the target dispatching area, carrying out power supply index value prediction on the target dispatching time period according to the analysis result to obtain a load supply index value, and carrying out power supply index value prediction on the target dispatching time period according to the analysis result to obtain a load supply index value; and S3, performing power distribution load scheduling on the target power supply unit in the target scheduling time period according to the load demand index value and the load supply index value. The method can improve the accuracy and timeliness of a power distribution load adaptive scheduling result.

Description

Technical Field

[0001] This invention belongs to the field of power and relates to load dispatching technology, specifically a method, device, computer equipment, and storage medium for adaptive dispatching of power distribution loads. Background Technology

[0002] The existing power system has the following shortcomings when dispatching power distribution loads in power consumption areas:

[0003] 1. When the power system needs to perform distribution load scheduling in the power consumption area, it can only perform distribution load scheduling based on the real-time deviation between the real-time power supply status and the circuit demand status of the power consumption area. It cannot combine the temperature status of the target scheduling period and the historical power supply and demand index deviation of the power consumption area to make scheduling predictions, which leads to the lag in the distribution load scheduling process.

[0004] 2. When the power system needs to conduct distribution load dispatch for the power consumption area, it can only make power supply and demand forecasts based on the historical power consumption indicators of the target power consumption area. It does not select matching power consumption areas for the target power consumption area based on the historical power consumption trend and the historical power generation trend of the target power consumption area, and does not combine the historical power supply and demand of the matching power consumption area with the historical power supply and demand of the target power consumption area to jointly predict the power supply and demand deviation of the target dispatch, thus resulting in the lack of accuracy of the distribution load dispatch results.

[0005] To this end, we propose a method, device, computer equipment, and storage medium for adaptive power distribution load scheduling. Summary of the Invention

[0006] In view of the shortcomings of the existing technology, the purpose of this invention is to provide a method, device, computer equipment and storage medium for adaptive scheduling of power distribution load, and to improve the accuracy of adaptive scheduling of power distribution load.

[0007] To achieve the above objectives, the present invention adopts the following technical solution: a power distribution load adaptive scheduling method, characterized in that it includes:

[0008] Step S1: Perform historical electricity demand analysis on the target scheduling area, and predict the electricity demand index value for the target scheduling period based on the analysis results to obtain the load demand index value;

[0009] Step S2: Perform historical power supply analysis on the target scheduling area, and predict the power supply index value for the target scheduling period based on the analysis results to obtain the load supply index value.

[0010] Step S3: Distribute load scheduling is performed on the target power supply unit during the target scheduling period based on the load demand index value and the load supply index value.

[0011] Furthermore, step S1 also includes the following steps:

[0012] Step S11: Obtain the power consumption areas that need to be adaptively scheduled for power distribution load, obtain multiple power consumption areas, and arbitrarily select one target power consumption area from the multiple obtained power consumption areas;

[0013] Step S12: Set the previous natural date of the current time as the regional electricity consumption characteristic date, obtain the electricity consumption period covered by the regional electricity consumption characteristic date to obtain multiple electricity consumption periods, and obtain the actual electricity consumption of the target electricity consumption area in each electricity consumption period to obtain the actual electricity consumption of multiple regional periods.

[0014] Step S13: Obtain the average ambient temperature of the target power consumption area during each power consumption period to obtain the average temperature of multiple areas during different time periods;

[0015] Step S14: Select any characteristic electricity consumption temperature from the multiple regional time period temperatures obtained, perform historical electricity consumption analysis on the characteristic electricity consumption temperature, and obtain the characteristic electricity demand corresponding to the characteristic electricity consumption temperature based on the analysis results.

[0016] Furthermore, step S1 also includes the following steps:

[0017] Step S15: Obtain the characteristic electricity demand corresponding to the temperature of each region during each time period;

[0018] Step S16: In the existing Cartesian coordinate system, connect the coordinate points with the abscissa being the temperature of the area during the time period and the ordinate being the characteristic electricity demand in sequence to obtain the electricity consumption fitting polygonal line corresponding to the target electricity consumption area, and name it the target electricity consumption fitting polygonal line.

[0019] Step S17: Obtain the power consumption fitting polyline corresponding to each power consumption area. Set the coordinate system for drawing the power consumption fitting polyline as the power consumption fitting coordinate system. In the power consumption fitting coordinate system, draw the first power consumption reference polyline above the target power consumption fitting polyline and the second power consumption reference polyline above the target power consumption fitting polyline. Draw a straight line perpendicular to the x-axis through the left endpoint of the first power consumption reference polyline to obtain the first power consumption feature line. Draw a straight line perpendicular to the x-axis through the left endpoint of the second power consumption reference polyline to obtain the second power consumption feature line. Set the closed area in the first power consumption reference polyline, the second power consumption reference polyline, the first power consumption feature line, and the second power consumption feature line as the target power consumption drawing area.

[0020] Step S18: Set the power consumption area where the power consumption fitting line is completely within the target power consumption drawing area as the power consumption matching area, obtain the power consumption period that needs to be dispatched for power distribution load, obtain the target dispatch period, obtain the ambient average temperature of the target power consumption area during the target dispatch period through weather forecast, and obtain the predicted ambient average temperature.

[0021] Step S19: Obtain the demand temperature matching range corresponding to the predicted ambient average temperature, obtain the historical average electricity consumption of each electricity matching area within the demand temperature matching range, and take the median of the multiple historical average electricity consumptions to obtain the load demand index value.

[0022] Furthermore, step S14 also includes the following steps:

[0023] Set a required temperature preset ratio, and calculate the upper limit value of the required temperature corresponding to the characteristic power consumption temperature by combining the characteristic power consumption temperature and the required temperature preset ratio.

[0024] The lower limit of the required temperature corresponding to the characteristic power consumption temperature is calculated by the ratio of the characteristic power consumption temperature to the preset temperature of the required temperature.

[0025] The numerical range formed by the upper limit of the demand temperature and the lower limit of the demand temperature is set as the demand temperature matching range corresponding to the characteristic electricity consumption temperature. The historical average temperature of the target electricity consumption area is obtained, and the historical electricity consumption periods in which the historical average temperature is within the demand temperature matching range are obtained. The electricity consumption of each historical electricity consumption period in the target electricity consumption area is obtained respectively.

[0026] The electricity consumption data from multiple time periods is sorted in descending order of numerical value. The electricity consumption data from each time period is named from Y1 to Ya according to the sorting order. The median of the electricity consumption data from Y1 to Ya is obtained to obtain the median of the characteristic electricity consumption. The electricity consumption data from Y1 to Ya is summed to obtain the cumulative value of the electricity consumption data for each time period.

[0027] Calculate the ratio of electricity consumption in period Y1 to the cumulative electricity consumption of period Y1 to obtain the cumulative electricity consumption percentage of Y1. Calculate the ratio of the sum of electricity consumption from period Y1 to period Y1 to the cumulative electricity consumption of period Y2 to obtain the cumulative electricity consumption percentage of Y2. Calculate the ratio of the sum of electricity consumption from period Y1 to period Y3 to the cumulative electricity consumption of period Y3 to obtain the cumulative electricity consumption percentage of Y3. And so on, calculate the ratio of the sum of electricity consumption from period Y1 to period Ya to the cumulative electricity consumption of period Ya to obtain the cumulative electricity consumption percentage of Ya.

[0028] Calculate the difference between each cumulative electricity consumption percentage and half, and set the last accumulated value corresponding to the minimum difference as the characteristic electricity demand corresponding to the characteristic electricity consumption temperature.

[0029] Furthermore, step S2 also includes the following steps:

[0030] Step S21: Set the previous natural date of the current time as the regional power supply characteristic date, obtain the power supply period covered by the regional power supply characteristic date to obtain multiple power supply periods, and obtain the actual power supply of the target power supply area in each power supply period to obtain the actual power supply of multiple regional periods.

[0031] Step S22: Obtain the average ambient temperature of the target power supply area during each power supply period to obtain the average temperature of multiple areas during the same period;

[0032] Step S23: Select any characteristic power supply temperature from the multiple regional time period temperatures obtained, perform historical power supply analysis on the characteristic power supply temperature, and obtain the characteristic power supply volume based on the analysis results;

[0033] Step S24: Obtain the characteristic power supply corresponding to the temperature of each region during a given time period;

[0034] Step S25: In the existing Cartesian coordinate system, connect the coordinate points with the abscissa being the temperature of the area during the time period and the ordinate being the characteristic power supply quantity in sequence to obtain the power supply fitting polyline corresponding to the target power supply area, and name it the target power supply fitting polyline.

[0035] Step S26: Obtain the power supply fitting polyline corresponding to each power supply area, set the coordinate system with the power supply fitting polyline as the power supply fitting coordinate system, draw the first power supply reference polyline above the target power supply fitting polyline in the power supply fitting coordinate system, draw the second power supply reference polyline above the target power supply fitting polyline, draw a straight line perpendicular to the X-axis through the left endpoint of the first power supply reference polyline to obtain the first power supply feature line, draw a straight line perpendicular to the X-axis through the left endpoint of the second power supply reference polyline to obtain the second power supply feature line, and set the closed area in the first power supply reference polyline, the second power supply reference polyline, the first power supply feature line and the second power supply feature line as the target power supply drawing area;

[0036] Step S27: Set the power supply area where the power supply fitting polyline is completely within the target power supply drawing area as the power supply matching area;

[0037] Step S28: Obtain the power supply period for which power distribution load scheduling is required, obtain the target scheduling period, obtain the average ambient temperature of the target power supply area during the target scheduling period through weather forecast, and obtain the predicted average ambient temperature.

[0038] Step S29: Obtain the supply temperature matching interval corresponding to the predicted ambient temperature, obtain the historical average power supply of each power supply matching area within the supply temperature matching interval, and take the median of the multiple historical average power supply to obtain the load supply index value.

[0039] Furthermore, step S23 also includes the following steps:

[0040] A supply temperature preset ratio is set, and the upper limit value of the supply temperature corresponding to the characteristic power supply temperature is calculated by combining the characteristic power supply temperature and the supply temperature preset ratio.

[0041] The lower limit of the supply temperature corresponding to the characteristic power supply temperature is calculated by using the characteristic power supply temperature and the preset ratio of the supply temperature.

[0042] The numerical range formed by the upper limit of the supply temperature and the lower limit of the supply temperature is set as the supply temperature matching range corresponding to the characteristic power supply temperature. The historical average temperature of the target power supply area is obtained, and the historical power supply periods in which the historical average temperature is within the supply temperature matching range are obtained. The power supply amount of each historical power supply period in the target power supply area is obtained respectively.

[0043] The power supply data obtained from multiple time periods is sorted in descending order of numerical value. The power supply data for each time period is named from X1 to Xb according to the sorting order. The median of the power supply data from X1 to Xb is obtained to obtain the median of the characteristic power supply. The power supply data from X1 to Xb is summed to obtain the cumulative value of the power supply data for each time period.

[0044] Calculate the ratio of power supply in time period X1 to the cumulative power supply in time period X1 to obtain the cumulative power supply percentage of X1. Calculate the ratio of the sum of power supply from time period X1 to X1 to the cumulative power supply in time period X2 to obtain the cumulative power supply percentage of X2. Calculate the ratio of the sum of power supply from time period X1 to X3 to the cumulative power supply in time period X3 to obtain the cumulative power supply percentage of X3. And so on, calculate the ratio of the sum of power supply from time period X1 to Xb to the cumulative power supply in time period Xb to obtain the cumulative power supply percentage of Xb.

[0045] Calculate the difference between each cumulative power supply percentage and half, and set the final cumulative value corresponding to the minimum difference as the characteristic power supply quantity corresponding to the characteristic power supply temperature.

[0046] Furthermore, step S3 also includes the following steps:

[0047] Obtain the load demand index value and the load supply index value respectively, calculate the difference between the load demand index value and the load supply index value, and take the absolute value of the obtained difference to obtain the distribution load supply deviation.

[0048] Set a preset range for power distribution supply deviation. If the power distribution load supply deviation is greater than the upper limit of the preset range, the power distribution load will be increased. If the power distribution load supply deviation is less than the upper limit of the preset range, the power distribution load will be decreased. If the power distribution load supply deviation is within the preset range, no power distribution load adjustment is required.

[0049] The power distribution load adaptive dispatching method, wherein the dispatching device includes:

[0050] Demand forecasting module: Performs historical electricity demand analysis on the target scheduling area, and forecasts electricity demand index values ​​for the target scheduling period based on the analysis results, thereby obtaining load demand index values;

[0051] Supply forecasting module: Performs historical power supply analysis on the target scheduling area, and predicts power supply index values ​​for the target scheduling period based on the analysis results, thereby obtaining load supply index values;

[0052] Load dispatching module: Dispatches power distribution loads of target power supply units within the target dispatching period based on load demand index values ​​and load supply index values.

[0053] A computer device includes: a memory for storing a computer program; and a processor for executing the computer program to perform an adaptive scheduling method for power distribution loads.

[0054] A storage medium for storing a computer program that, when executed by a processor, implements an adaptive scheduling method for power distribution loads.

[0055] In summary, due to the adoption of the above technical solution, the beneficial effects of the present invention are:

[0056] 1. This invention combines the temperature conditions during the target scheduling period with the historical power supply and demand deviations of the power consumption area to make scheduling predictions, thereby ensuring that there is a lag in the power distribution load scheduling process.

[0057] 2. This invention does not select matching power consumption areas for the target power consumption area based on the historical power consumption trend and historical power generation trend of the target power consumption area, but combines the historical power supply and demand of the matching power consumption area with the historical power supply and demand of the target power consumption area to jointly predict the power supply and demand deviation of the target dispatch, which can effectively ensure the accuracy of the power distribution load dispatch results. Attached Figure Description

[0058] To facilitate understanding by those skilled in the art, the present invention will be further described below with reference to the accompanying drawings.

[0059] Figure 1 This is a diagram illustrating the implementation steps of the present invention;

[0060] Figure 2 This is an overall system block diagram of the present invention. Detailed Implementation

[0061] The technical solution of the present invention will be clearly and completely described below with reference to the embodiments. Obviously, the described embodiments are only some embodiments of the present invention, and not all embodiments. Based on the embodiments of the present invention, all other embodiments obtained by those of ordinary skill in the art without creative effort are within the scope of protection of the present invention.

[0062] First aspect

[0063] Please see Figure 1 This invention provides a technical solution: an adaptive scheduling method for power distribution load, comprising the following steps:

[0064] Step S1: Perform historical electricity demand analysis on the target scheduling area, and predict the electricity demand index value for the target scheduling period based on the analysis results to obtain the load demand index value;

[0065] Step S1 further includes the following steps:

[0066] Step S11: Obtain the power consumption areas that need to be adaptively scheduled for power distribution load, obtain multiple power consumption areas, and arbitrarily select one target power consumption area from the multiple obtained power consumption areas;

[0067] Step S12: Set the previous natural date of the current time as the regional electricity consumption characteristic date, obtain the electricity consumption period covered by the regional electricity consumption characteristic date to obtain multiple electricity consumption periods, and obtain the actual electricity consumption of the target electricity consumption area in each electricity consumption period to obtain the actual electricity consumption of multiple regional periods.

[0068] Step S13: Obtain the average ambient temperature of the target power consumption area during each power consumption period to obtain the average temperature of multiple areas during different time periods;

[0069] Step S14: Randomly select a characteristic electricity consumption temperature from the multiple regional time period temperatures obtained, perform historical electricity consumption analysis on the characteristic electricity consumption temperature, and obtain the characteristic electricity demand corresponding to the characteristic electricity consumption temperature based on the analysis results.

[0070] Step S14 further includes the following steps:

[0071] Set a required temperature preset ratio, and calculate the upper limit value of the required temperature corresponding to the characteristic power consumption temperature by combining the characteristic power consumption temperature and the required temperature preset ratio.

[0072] The lower limit of the required temperature corresponding to the characteristic power consumption temperature is calculated by the ratio of the characteristic power consumption temperature to the preset temperature of the required temperature.

[0073] The numerical range formed by the upper limit of the demand temperature and the lower limit of the demand temperature is set as the demand temperature matching range corresponding to the characteristic electricity consumption temperature. The historical average temperature of the target electricity consumption area is obtained, and the historical electricity consumption periods in which the historical average temperature is within the demand temperature matching range are obtained. The electricity consumption of each historical electricity consumption period in the target electricity consumption area is obtained respectively.

[0074] The electricity consumption data from multiple time periods is sorted in descending order of numerical value. The electricity consumption data from each time period is named from Y1 to Ya according to the sorting order. The median of the electricity consumption data from Y1 to Ya is obtained to obtain the median of the characteristic electricity consumption. The electricity consumption data from Y1 to Ya is summed to obtain the cumulative value of the electricity consumption data for each time period.

[0075] Calculate the ratio of electricity consumption in period Y1 to the cumulative electricity consumption of period Y1 to obtain the cumulative electricity consumption percentage of Y1. Calculate the ratio of the sum of electricity consumption from period Y1 to period Y1 to the cumulative electricity consumption of period Y2 to obtain the cumulative electricity consumption percentage of Y2. Calculate the ratio of the sum of electricity consumption from period Y1 to period Y3 to the cumulative electricity consumption of period Y3 to obtain the cumulative electricity consumption percentage of Y3. And so on, calculate the ratio of the sum of electricity consumption from period Y1 to period Ya to the cumulative electricity consumption of period Ya to obtain the cumulative electricity consumption percentage of Ya.

[0076] Calculate the difference between each cumulative electricity consumption percentage and half, and set the last cumulative value corresponding to the minimum difference as the characteristic electricity demand corresponding to the characteristic electricity consumption temperature;

[0077] Step S15: Obtain the characteristic electricity demand corresponding to the temperature of each region during each time period;

[0078] Step S16: In the existing Cartesian coordinate system, connect the coordinate points with the abscissa being the temperature of the area during the time period and the ordinate being the characteristic electricity demand in sequence to obtain the electricity consumption fitting polygonal line corresponding to the target electricity consumption area, and name it the target electricity consumption fitting polygonal line.

[0079] Step S17: Obtain the power consumption fitting polyline corresponding to each power consumption area. Set the coordinate system for drawing the power consumption fitting polyline as the power consumption fitting coordinate system. In the power consumption fitting coordinate system, draw the first power consumption reference polyline above the target power consumption fitting polyline and the second power consumption reference polyline above the target power consumption fitting polyline. Draw a straight line perpendicular to the x-axis through the left endpoint of the first power consumption reference polyline to obtain the first power consumption feature line. Draw a straight line perpendicular to the x-axis through the left endpoint of the second power consumption reference polyline to obtain the second power consumption feature line. Set the closed area in the first power consumption reference polyline, the second power consumption reference polyline, the first power consumption feature line, and the second power consumption feature line as the target power consumption drawing area.

[0080] Step S18: Set the power consumption area where the power consumption fitting line is completely within the target power consumption drawing area as the power consumption matching area, obtain the power consumption period that needs to be dispatched for power distribution load, obtain the target dispatch period, obtain the ambient average temperature of the target power consumption area during the target dispatch period through weather forecast, and obtain the predicted ambient average temperature.

[0081] Step S19: Obtain the demand temperature matching range corresponding to the predicted ambient average temperature, obtain the historical average electricity consumption of each electricity matching area within the demand temperature matching range, and take the median of the multiple historical average electricity consumptions to obtain the load demand index value.

[0082] Step S2: Perform historical power supply analysis on the target scheduling area, and predict the power supply index value for the target scheduling period based on the analysis results to obtain the load supply index value.

[0083] Step S2 further includes the following steps:

[0084] Step S21: Set the previous natural date of the current time as the regional power supply characteristic date, obtain the power supply period covered by the regional power supply characteristic date to obtain multiple power supply periods, and obtain the actual power supply of the target power supply area in each power supply period to obtain the actual power supply of multiple regional periods.

[0085] Step S22: Obtain the average ambient temperature of the target power supply area during each power supply period to obtain the average temperature of multiple areas during the same period;

[0086] Step S23: Select any characteristic power supply temperature from the multiple regional time period temperatures obtained, perform historical power supply analysis on the characteristic power supply temperature, and obtain the characteristic power supply volume based on the analysis results;

[0087] Step S23 further includes the following steps:

[0088] A supply temperature preset ratio is set, and the upper limit value of the supply temperature corresponding to the characteristic power supply temperature is calculated by combining the characteristic power supply temperature and the supply temperature preset ratio.

[0089] The lower limit of the supply temperature corresponding to the characteristic power supply temperature is calculated by using the characteristic power supply temperature and the preset ratio of the supply temperature.

[0090] The numerical range formed by the upper limit of the supply temperature and the lower limit of the supply temperature is set as the supply temperature matching range corresponding to the characteristic power supply temperature. The historical average temperature of the target power supply area is obtained, and the historical power supply periods in which the historical average temperature is within the supply temperature matching range are obtained. The power supply amount of each historical power supply period in the target power supply area is obtained respectively.

[0091] The power supply data obtained from multiple time periods is sorted in descending order of numerical value. The power supply data for each time period is named from X1 to Xb according to the sorting order. The median of the power supply data from X1 to Xb is obtained to obtain the median of the characteristic power supply. The power supply data from X1 to Xb is summed to obtain the cumulative value of the power supply data for each time period.

[0092] Calculate the ratio of power supply in time period X1 to the cumulative power supply in time period X1 to obtain the cumulative power supply percentage of X1. Calculate the ratio of the sum of power supply from time period X1 to X1 to the cumulative power supply in time period X2 to obtain the cumulative power supply percentage of X2. Calculate the ratio of the sum of power supply from time period X1 to X3 to the cumulative power supply in time period X3 to obtain the cumulative power supply percentage of X3. And so on, calculate the ratio of the sum of power supply from time period X1 to Xb to the cumulative power supply in time period Xb to obtain the cumulative power supply percentage of Xb.

[0093] Calculate the difference between each cumulative power supply percentage and half, and set the last cumulative value corresponding to the minimum difference as the characteristic power supply quantity corresponding to the characteristic power supply temperature;

[0094] Step S24: Obtain the characteristic power supply corresponding to the temperature of each region during a given time period;

[0095] Step S25: In the existing Cartesian coordinate system, connect the coordinate points with the abscissa being the temperature of the area during the time period and the ordinate being the characteristic power supply quantity in sequence to obtain the power supply fitting polyline corresponding to the target power supply area, and name it the target power supply fitting polyline.

[0096] Step S26: Obtain the power supply fitting polyline corresponding to each power supply area, set the coordinate system with the power supply fitting polyline as the power supply fitting coordinate system, draw the first power supply reference polyline above the target power supply fitting polyline in the power supply fitting coordinate system, draw the second power supply reference polyline above the target power supply fitting polyline, draw a straight line perpendicular to the X-axis through the left endpoint of the first power supply reference polyline to obtain the first power supply feature line, draw a straight line perpendicular to the X-axis through the left endpoint of the second power supply reference polyline to obtain the second power supply feature line, and set the closed area in the first power supply reference polyline, the second power supply reference polyline, the first power supply feature line and the second power supply feature line as the target power supply drawing area;

[0097] Step S27: Set the power supply area where the power supply fitting polyline is completely within the target power supply drawing area as the power supply matching area;

[0098] Step S28: Obtain the power supply period for which power distribution load scheduling is required, obtain the target scheduling period, obtain the average ambient temperature of the target power supply area during the target scheduling period through weather forecast, and obtain the predicted average ambient temperature.

[0099] Step S29: Obtain the supply temperature matching interval corresponding to the predicted ambient temperature, obtain the historical average power supply of each power supply matching area within the supply temperature matching interval, and take the median of the multiple historical average power supply to obtain the load supply index value.

[0100] Step S3: Perform power distribution load scheduling for the target power supply unit during the target scheduling period based on the load demand index value and the load supply index value;

[0101] Step S3 further includes the following steps:

[0102] Obtain the load demand index value and the load supply index value respectively, calculate the difference between the load demand index value and the load supply index value, and take the absolute value of the obtained difference to obtain the distribution load supply deviation.

[0103] Set a preset range for power distribution supply deviation. If the power distribution load supply deviation is greater than the upper limit of the preset range, the power distribution load will be increased. If the power distribution load supply deviation is less than the upper limit of the preset range, the power distribution load will be decreased. If the power distribution load supply deviation is within the preset range, no power distribution load adjustment is required.

[0104] Second aspect

[0105] Please see Figure 2Based on another concept of the same invention, a power distribution load adaptive dispatching device is proposed, including a demand forecasting module, a supply forecasting module, a load dispatching module and a server. The demand forecasting module, the supply forecasting module and the load dispatching module are respectively connected to the server, and the server controls the demand forecasting module, the supply forecasting module and the load dispatching module respectively.

[0106] The demand forecasting module performs historical electricity demand analysis on the target scheduling area, and predicts the electricity demand index value for the target scheduling period based on the analysis results, thereby obtaining the load demand index value.

[0107] Specifically as follows:

[0108] The power consumption areas that require adaptive scheduling of power distribution load are obtained, resulting in multiple power consumption areas. Then, a target power consumption area is arbitrarily selected from the multiple obtained power consumption areas.

[0109] It should be noted here that:

[0110] In this application, the electricity consumption areas referred to herein are all electricity consumption areas where adaptive load dispatching devices for power distribution are deployed;

[0111] In this application, the electricity-consuming areas referred to herein are all areas where clean energy power generation devices are deployed, and the clean energy referred to herein is specifically solar energy.

[0112] Set the previous natural date of the current moment as the regional electricity consumption characteristic date, obtain the electricity consumption period covered by the regional electricity consumption characteristic date to obtain multiple electricity consumption periods, and obtain the actual electricity consumption of the target electricity consumption area in each electricity consumption period to obtain the actual electricity consumption of multiple regional periods.

[0113] The average ambient temperature of the target power consumption area during each power consumption period is obtained to obtain the average temperature of multiple areas during different time periods.

[0114] Select any characteristic power consumption temperature from the multiple regional time periods obtained, and set a demand temperature preset ratio. Calculate the upper limit value of the demand temperature corresponding to the characteristic power consumption temperature by combining the characteristic power consumption temperature and the demand temperature preset ratio.

[0115] The formula for calculating the upper limit of the required temperature is as follows:

[0116] ;

[0117] Where Xws is the upper limit of the required temperature, Tyd is the characteristic power consumption temperature, and Ygb is the preset ratio of the required temperature;

[0118] The lower limit of the required temperature corresponding to the characteristic power consumption temperature is calculated by the ratio of the characteristic power consumption temperature to the preset temperature of the required temperature.

[0119] The formula for calculating the lower limit of the required temperature is as follows:

[0120] ;

[0121] Where Xwx is the lower limit of the demand temperature, Tyd is the characteristic power consumption temperature, and Ygb is the preset ratio of the demand temperature;

[0122] It should be noted here that:

[0123] In this application, the required temperature preset ratio is 0.05.

[0124] The numerical range formed by the upper limit of the demand temperature and the lower limit of the demand temperature is set as the demand temperature matching range corresponding to the characteristic electricity consumption temperature. The historical average temperature of the target electricity consumption area is obtained, and the historical electricity consumption periods in which the historical average temperature is within the demand temperature matching range are obtained. The electricity consumption of each historical electricity consumption period in the target electricity consumption area is obtained respectively.

[0125] The electricity consumption data from multiple time periods is sorted in descending order of numerical value. The electricity consumption data from each time period is named from Y1 to Ya according to the sorting order. The median of the electricity consumption data from Y1 to Ya is obtained to obtain the median of the characteristic electricity consumption. The electricity consumption data from Y1 to Ya is summed to obtain the cumulative value of the electricity consumption data for each time period.

[0126] It should be noted here that:

[0127] In this application, Y1, Y2...Yb in the electricity consumption of time period Y1 to time period Ya are the serial numbers corresponding to the electricity consumption of each time period;

[0128] Calculate the ratio of electricity consumption in period Y1 to the cumulative electricity consumption of period Y1 to obtain the cumulative electricity consumption percentage of Y1. Calculate the ratio of the sum of electricity consumption from period Y1 to period Y1 to the cumulative electricity consumption of period Y2 to obtain the cumulative electricity consumption percentage of Y2. Calculate the ratio of the sum of electricity consumption from period Y1 to period Y3 to the cumulative electricity consumption of period Y3 to obtain the cumulative electricity consumption percentage of Y3. And so on, calculate the ratio of the sum of electricity consumption from period Y1 to period Ya to the cumulative electricity consumption of period Ya to obtain the cumulative electricity consumption percentage of Ya.

[0129] Calculate the difference between each cumulative electricity consumption percentage and half, and set the last cumulative value corresponding to the minimum difference as the characteristic electricity demand corresponding to the characteristic electricity consumption temperature;

[0130] It should be noted here that:

[0131] In this application, if the difference between the cumulative proportion of electricity consumption of Yi and half is the smallest, then the electricity consumption of Yi during the period is set as the characteristic electricity demand corresponding to the characteristic electricity consumption temperature.

[0132] Repeat the process of determining the characteristic electricity demand corresponding to the characteristic electricity demand corresponding to the characteristic electricity temperature, and obtain the characteristic electricity demand corresponding to the temperature of each region and time period.

[0133] In the existing Cartesian coordinate system, the coordinate points with the horizontal axis representing the temperature of the area during a time period and the vertical axis representing the characteristic electricity demand are connected sequentially to obtain the electricity consumption fitting polygonal line corresponding to the target electricity consumption area, and this polygonal line is named the target electricity consumption fitting polygonal line.

[0134] Repeat the process of obtaining the power consumption fitting polyline corresponding to the target power consumption area, obtain the power consumption fitting polyline corresponding to each power consumption area, and set the coordinate system with the power consumption fitting polyline as the power consumption fitting coordinate system.

[0135] In the power consumption fitting coordinate system, a first power consumption reference polyline is drawn above the target power consumption fitting polyline, and a second power consumption reference polyline is drawn above the target power consumption fitting polyline. A straight line perpendicular to the x-axis is drawn through the left endpoint of the first power consumption reference polyline to obtain the first power consumption characteristic line. A straight line perpendicular to the x-axis is drawn through the left endpoint of the second power consumption reference polyline to obtain the second power consumption characteristic line. The closed area in the first power consumption reference polyline, the second power consumption reference polyline, the first power consumption characteristic line, and the second power consumption characteristic line is set as the target power consumption drawing area.

[0136] The electricity consumption area whose fitted polyline is completely within the target electricity consumption drawing area is set as the electricity consumption matching area corresponding to the target electricity consumption unit;

[0137] The electricity consumption periods that require power distribution load scheduling are obtained to get the target scheduling period. The average ambient temperature of the target electricity consumption area during the target scheduling period is obtained through weather forecast to get the predicted average ambient temperature.

[0138] Repeatedly obtain the demand temperature matching interval corresponding to the characteristic electricity consumption temperature, and obtain the demand temperature matching interval corresponding to the predicted average ambient temperature. Obtain the historical average electricity consumption of each electricity consumption matching area within the demand temperature matching interval, and take the median of the multiple historical average electricity consumptions to obtain the load demand index value.

[0139] The supply forecasting module performs historical power supply analysis on the target scheduling area, and predicts the power supply index value for the target scheduling period based on the analysis results, thereby obtaining the load supply index value.

[0140] Specifically as follows:

[0141] Set the previous natural date of the current time as the regional power supply characteristic date, obtain the power supply period covered by the regional power supply characteristic date to obtain multiple power supply periods, and obtain the actual power supply of the target power supply area in each power supply period to obtain the actual power supply of multiple regional periods.

[0142] The average ambient temperature of the target power supply area during each power supply period is obtained to obtain the average temperature of multiple areas during different time periods.

[0143] Select a characteristic power supply temperature from the multiple regional time periods obtained, and set a preset supply temperature ratio. Calculate the upper limit of the supply temperature corresponding to the characteristic power supply temperature using the characteristic power supply temperature and the preset supply temperature ratio.

[0144] The formula for calculating the upper limit of the supply temperature is as follows:

[0145] ;

[0146] Wherein, Gws is the upper limit of the supply temperature, Gxd is the characteristic supply temperature, and Ggb is the preset ratio of the supply temperature;

[0147] The lower limit of the supply temperature corresponding to the characteristic power supply temperature is calculated by using the characteristic power supply temperature and the preset ratio of the supply temperature.

[0148] The lower limit of the supply temperature is calculated using the following formula:

[0149] ;

[0150] Where Xgx is the lower limit of the supply temperature, Gyd is the characteristic supply temperature, and Ggb is the preset supply temperature ratio;

[0151] It should be noted here that:

[0152] In this application, the preset supply temperature ratio is 0.05.

[0153] The numerical range formed by the upper limit of the supply temperature and the lower limit of the supply temperature is set as the supply temperature matching range corresponding to the characteristic power supply temperature. The historical average temperature of the target power supply area is obtained, and the historical power supply periods in which the historical average temperature is within the supply temperature matching range are obtained. The power supply amount of each historical power supply period in the target power supply area is obtained respectively.

[0154] The power supply data obtained from multiple time periods is sorted in descending order of numerical value. The power supply data for each time period is named from X1 to Xb according to the sorting order. The median of the power supply data from X1 to Xb is obtained to obtain the median of the characteristic power supply. The power supply data from X1 to Xb is summed to obtain the cumulative value of the power supply data for each time period.

[0155] It should be noted here that:

[0156] In this application, X1, X2...Xb in the power supply of time period X1 to Xb are the serial numbers corresponding to the power supply of time periods;

[0157] Calculate the ratio of power supply in time period X1 to the cumulative power supply in time period X1 to obtain the cumulative power supply percentage of X1. Calculate the ratio of the sum of power supply from time period X1 to X1 to the cumulative power supply in time period X2 to obtain the cumulative power supply percentage of X2. Calculate the ratio of the sum of power supply from time period X1 to X3 to the cumulative power supply in time period X3 to obtain the cumulative power supply percentage of X3. And so on, calculate the ratio of the sum of power supply from time period X1 to Xb to the cumulative power supply in time period Xb to obtain the cumulative power supply percentage of Xb.

[0158] Calculate the difference between each cumulative power supply percentage and half, and set the last cumulative value corresponding to the minimum difference as the characteristic power supply quantity corresponding to the characteristic power supply temperature;

[0159] It should be noted here that:

[0160] In this application, if the difference between the cumulative proportion of power supply in Xi and the difference between half is the smallest, then the power supply amount in the Xi period is set as the characteristic power supply amount corresponding to the characteristic power supply temperature.

[0161] Repeat the process of determining the characteristic power supply quantity corresponding to the characteristic power supply temperature, and obtain the characteristic power supply quantity corresponding to the temperature of each region and time period.

[0162] In the existing Cartesian coordinate system, the coordinate points with the abscissa representing the temperature of the region during the time period and the ordinate representing the characteristic power supply quantity are connected sequentially to obtain the power supply fitting polyline corresponding to the target power supply area, and this polyline is named the target power supply fitting polyline.

[0163] Repeat the process of obtaining the power supply fitting polyline corresponding to the target power supply area, obtain the power supply fitting polyline corresponding to each power supply area, and set the coordinate system with the power supply fitting polyline as the power supply fitting coordinate system.

[0164] In the power supply fitting coordinate system, a first power supply reference polyline is drawn above the target power supply fitting polyline, and a second power supply reference polyline is drawn above the target power supply fitting polyline. A straight line perpendicular to the X-axis is drawn through the left endpoint of the first power supply reference polyline to obtain the first power supply characteristic line. A straight line perpendicular to the X-axis is drawn through the left endpoint of the second power supply reference polyline to obtain the second power supply characteristic line. The closed area in the first power supply reference polyline, the second power supply reference polyline, the first power supply characteristic line, and the second power supply characteristic line is set as the target power supply drawing area.

[0165] The power supply region whose power supply fitting polyline is completely within the target power supply drawing area is set as the power supply matching region;

[0166] The power supply period that requires power distribution load scheduling is obtained to get the target scheduling period. The average ambient temperature of the target power supply area during the target scheduling period is obtained through weather forecast to get the predicted average ambient temperature.

[0167] Repeatedly obtain the supply temperature matching interval corresponding to the characteristic power supply temperature and the supply temperature matching interval corresponding to the predicted ambient average temperature. Obtain the historical average power supply of each power supply matching area within the supply temperature matching interval. Take the median of the multiple historical average power supply values ​​to obtain the load supply index value.

[0168] The load dispatching module performs power distribution load dispatching for the target power supply unit during the target dispatching period based on the load demand index value and the load supply index value.

[0169] Specifically as follows:

[0170] Obtain the load demand index value and the load supply index value respectively, calculate the difference between the load demand index value and the load supply index value, and take the absolute value of the obtained difference to obtain the distribution load supply deviation.

[0171] Set a preset range for power supply deviation. If the power supply deviation is greater than the upper limit of the preset range, the power load will be increased. If the power supply deviation is less than the upper limit of the preset range, the power load will be decreased. If the power supply deviation is within the preset range, no power load adjustment is required.

[0172] It should be noted here that:

[0173] Historical electricity consumption periods during which the target power supply unit is in a state of supply balance are obtained. The distribution load supply deviation corresponding to each historical electricity consumption period is obtained, and the obtained distribution load supply deviations are compared in magnitude. The distribution load supply deviation with the largest value is set as the upper limit of the preset range of distribution load deviation, and the distribution load supply deviation with the smallest value is set as the lower limit of the preset range of distribution load deviation.

[0174] Third aspect

[0175] A computer device includes: a memory for storing a computer program; and a processor for executing the computer program to perform an adaptive scheduling method for power distribution loads.

[0176] Fourth aspect

[0177] A storage medium for storing a computer program that, when executed by a processor, implements an adaptive scheduling method for power distribution loads.

[0178] The preferred embodiments of the present invention disclosed above are merely illustrative of the invention. These preferred embodiments do not exhaustively describe all details, nor do they limit the invention to any specific implementation. Clearly, many modifications and variations can be made based on the content of this specification. This specification selects and specifically describes these embodiments to better explain the principles and practical applications of the invention, thereby enabling those skilled in the art to better understand and utilize the invention. The invention is limited only by the claims and their full scope and equivalents.

Claims

1. A power distribution load adaptive dispatching method, characterized in that, include: Step S1: Perform historical electricity demand analysis on the target scheduling area, and predict the electricity demand index value for the target scheduling period based on the analysis results to obtain the load demand index value. Step S2: Perform historical power supply analysis on the target scheduling area, and predict the power supply index value for the target scheduling period based on the analysis results to obtain the load supply index value. Step S3: Perform power distribution load scheduling for the target power supply unit during the target scheduling period based on the load demand index value and the load supply index value.

2. The adaptive power distribution load scheduling method according to claim 1, characterized in that, Step S1 further includes the following steps: Step S11: Obtain the power consumption areas that need to be adaptively scheduled for power distribution load, obtain multiple power consumption areas, and arbitrarily select one target power consumption area from the multiple obtained power consumption areas; Step S12: Set the previous natural date of the current time as the regional electricity consumption characteristic date, obtain the electricity consumption period covered by the regional electricity consumption characteristic date to obtain multiple electricity consumption periods, and obtain the actual electricity consumption of the target electricity consumption area in each electricity consumption period to obtain the actual electricity consumption of multiple regional periods. Step S13: Obtain the average ambient temperature of the target power consumption area during each power consumption period to obtain the average temperature of multiple areas during different time periods; Step S14: Select any characteristic electricity consumption temperature from the multiple regional time period temperatures obtained, perform historical electricity consumption analysis on the characteristic electricity consumption temperature, and obtain the characteristic electricity demand corresponding to the characteristic electricity consumption temperature based on the analysis results.

3. The adaptive power distribution load scheduling method according to claim 2, characterized in that, Step S1 further includes the following steps: Step S15: Obtain the characteristic electricity demand corresponding to the temperature of each region during each time period; Step S16: In the existing Cartesian coordinate system, connect the coordinate points with the abscissa being the temperature of the area during the time period and the ordinate being the characteristic electricity demand in sequence to obtain the electricity consumption fitting polygonal line corresponding to the target electricity consumption area, and name it the target electricity consumption fitting polygonal line. Step S17: Obtain the power consumption fitting polyline corresponding to each power consumption area. Set the coordinate system for drawing the power consumption fitting polyline as the power consumption fitting coordinate system. In the power consumption fitting coordinate system, draw the first power consumption reference polyline above the target power consumption fitting polyline and the second power consumption reference polyline above the target power consumption fitting polyline. Draw a straight line perpendicular to the x-axis through the left endpoint of the first power consumption reference polyline to obtain the first power consumption feature line. Draw a straight line perpendicular to the x-axis through the left endpoint of the second power consumption reference polyline to obtain the second power consumption feature line. Set the closed area in the first power consumption reference polyline, the second power consumption reference polyline, the first power consumption feature line, and the second power consumption feature line as the target power consumption drawing area. Step S18: Set the power consumption area where the power consumption fitting line is completely within the target power consumption drawing area as the power consumption matching area, obtain the power consumption period that needs to be dispatched for power distribution load, obtain the target dispatch period, obtain the ambient average temperature of the target power consumption area during the target dispatch period, and obtain the predicted ambient average temperature. Step S19: Obtain the demand temperature matching range corresponding to the predicted ambient average temperature, obtain the historical average electricity consumption of each electricity matching area within the demand temperature matching range, and take the median of the multiple historical average electricity consumptions to obtain the load demand index value.

4. The adaptive dispatching method for power distribution load according to claim 2, characterized in that, Step S14 further includes the following steps: Obtain the upper limit and lower limit of the required temperature; set the numerical range formed by the upper limit and lower limit of the required temperature as the required temperature matching range corresponding to the characteristic electricity consumption temperature; obtain the historical average temperature of the target electricity consumption area; obtain the historical electricity consumption periods when the historical average temperature is within the required temperature matching range; obtain the electricity consumption of each historical electricity consumption period in the target electricity consumption area. The electricity consumption data from multiple time periods is sorted in descending order to obtain the electricity consumption data from time period Y1 to time period Ya. The median of the electricity consumption data for each time period is obtained to obtain the median of the characteristic electricity consumption data. The electricity consumption data from time period Y1 to time period Ya is summed to obtain the cumulative electricity consumption data for each time period. Calculate the ratio of electricity consumption in period Y1 to the cumulative electricity consumption of period Y1 to obtain the cumulative electricity consumption percentage of Y1. Calculate the ratio of the sum of electricity consumption from period Y1 to period Y1 to the cumulative electricity consumption of period Y2 to obtain the cumulative electricity consumption percentage of Y2. Calculate the ratio of the sum of electricity consumption from period Y1 to period Ya to the cumulative electricity consumption of period Ya to obtain the cumulative electricity consumption percentage of Ya. Calculate the difference between each cumulative electricity consumption percentage and half, and set the final cumulative value corresponding to the minimum difference as the characteristic electricity demand corresponding to the characteristic electricity consumption temperature.

5. The adaptive power distribution load scheduling method according to claim 1, characterized in that, Step S2 further includes the following steps: Step S21: Set the regional power supply characteristic date, obtain the power supply period covered by the regional power supply characteristic date, and obtain the actual power supply of the target power supply area in each power supply period to obtain the actual power supply of multiple regional periods. Step S22: Obtain the average ambient temperature of the target power supply area during each power supply period to obtain the average temperature of multiple areas during the same period; Step S23: Select a characteristic power supply temperature from the multiple regional time period temperatures, perform historical power supply analysis, and obtain the characteristic power supply volume based on the analysis results; Step S24: Obtain the characteristic power supply corresponding to the temperature of each region during a given time period; Step S25: In the existing Cartesian coordinate system, connect the coordinate points with the abscissa being the temperature of the area during the time period and the ordinate being the characteristic power supply quantity in sequence to obtain the power supply fitting polyline corresponding to the target power supply area, and name it the target power supply fitting polyline. Step S26: Obtain the power supply fitting polyline corresponding to each power supply area, set the coordinate system with the power supply fitting polyline as the power supply fitting coordinate system, draw the first power supply reference polyline above the target power supply fitting polyline in the power supply fitting coordinate system, draw the second power supply reference polyline above the target power supply fitting polyline, draw a straight line perpendicular to the X-axis through the left endpoint of the first power supply reference polyline to obtain the first power supply feature line, draw a straight line perpendicular to the X-axis through the left endpoint of the second power supply reference polyline to obtain the second power supply feature line, and set the closed area in the first power supply reference polyline, the second power supply reference polyline, the first power supply feature line and the second power supply feature line as the target power supply drawing area; Step S27: Set the power supply area where the power supply fitting polyline is completely within the target power supply drawing area as the power supply matching area; Step S28: Obtain the power supply period for which power distribution load scheduling is required, obtain the target scheduling period, obtain the average ambient temperature of the target power supply area during the target scheduling period, and obtain the predicted average ambient temperature. Step S29: Obtain the supply temperature matching interval corresponding to the predicted ambient average temperature, obtain the historical average power supply of each power supply matching area within the supply temperature matching interval, and take the median of multiple historical average power supply to obtain the load supply index value.

6. The adaptive dispatching method for power distribution load according to claim 5, characterized in that, Step S23 further includes the following steps: Obtain the upper limit and lower limit of the supply temperature; set the numerical range formed by the upper limit and lower limit of the supply temperature as the supply temperature matching range corresponding to the characteristic power supply temperature; obtain the historical average temperature of the target power supply area; obtain the historical power supply periods that are in the supply temperature matching range; and obtain the power supply amount corresponding to each historical power supply period of the target power supply area. The power supply data for multiple time periods is sorted in descending order. Based on the sorting order, the power supply data for each time period is named from X1 power supply data to Xb power supply data. The median of the power supply data for each time period is obtained to get the median of the characteristic power supply data. The power supply data for each time period is summed to get the cumulative value of the power supply data for each time period. Calculate the ratio of power supply in time period X1 to the cumulative power supply in time period X1 to obtain the cumulative power supply percentage of X1. Calculate the ratio of the sum of power supply from time period X1 to X2 to the cumulative power supply in time period X2 to obtain the cumulative power supply percentage of X2. Calculate the ratio of the sum of power supply from time period X1 to Xb to the cumulative power supply in time period Xb to obtain the cumulative power supply percentage of Xb. Calculate the difference between each cumulative power supply percentage and half, and set the final cumulative value corresponding to the minimum difference as the characteristic power supply quantity corresponding to the characteristic power supply temperature.

7. The adaptive power distribution load scheduling method according to claim 1, characterized in that, Step S3 further includes the following steps: Obtain the load demand index value and the load supply index value respectively, calculate the difference between the load demand index value and the load supply index value, and take the absolute value of the obtained difference to obtain the distribution load supply deviation. Set a preset range for power distribution supply deviation. If the power distribution load supply deviation is greater than the upper limit of the preset range, the power distribution load will be increased; if it is less than the upper limit, the power distribution load will be decreased. If the power distribution load supply deviation is within the preset range, no power distribution load adjustment is required.

8. A power distribution load adaptive dispatching device, applicable to the power distribution load adaptive dispatching method according to any one of claims 1-7, the dispatching device comprising: Demand forecasting module: Performs historical electricity demand analysis on the target scheduling area, and forecasts electricity demand index values ​​for the target scheduling period based on the analysis results, thereby obtaining load demand index values; Supply forecasting module: Performs historical power supply analysis on the target scheduling area, and predicts power supply index values ​​for the target scheduling period based on the analysis results to obtain load supply index values; Load dispatching module: Dispatches power distribution loads of target power supply units within the target dispatching period based on load demand index values ​​and load supply index values.

9. A computer device, comprising: Memory, used to store computer programs; And a processor for executing the computer program to perform the power distribution load adaptive scheduling method according to any one of claims 1-7.

10. A storage medium for storing a computer program, which, when executed by a processor, implements the adaptive power distribution load scheduling method according to any one of claims 1-7.

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