Power Allocation Method, Device, Equipment and Medium Based on Transmission Channel Allocation

Abstract

The present invention belongs to the field of electric power automation technology and discloses a method, device, equipment, and medium for allocating power based on transmission channel allocation. The method comprises: allocating transmission channel capacity for each month based on monthly average historical power generation data and monthly power generation forecast data; invoking a constraint condition group to solve a pre-established monthly objective function to obtain a monthly power curve; combining daily average historical power generation data and daily power generation forecast data within the month to allocate corresponding transmission channel capacity for each day; invoking a constraint condition group to solve a pre-established multi-day objective function within the month to obtain a multi-day power curve within the month; and invoking a constraint condition group to solve a pre-established multi-time period objective function within the day to obtain a multi-time period power curve within the day when allocating transmission channel capacity based on power generation output forecast. The present invention fully considers historical data and forecast data, and combines a flexible allocation mechanism for transmission channels at different time scales to improve the utilization rate of transmission channels.

Description

Technical Field

[0001] The present invention belongs to the technical field of electric power automation, and in particular relates to a method, device, equipment and medium for distributing electric power based on power transmission channel distribution. Background Art

[0002] Currently, medium- and long-term electricity markets are primarily based on electricity volume. Buyers and sellers typically sign contracts for volume, not electricity, and these contracts require physical execution during actual operations. The spot market, on the other hand, operates on electricity volume. Consequently, there are challenges in effectively integrating medium- and long-term electricity contracts with spot market transactions in terms of transaction types and settlement methods.

[0003] In order to achieve a good connection between medium- and long-term electricity transactions and spot market electricity transactions, it is necessary to gradually decompose medium- and long-term electricity contracts into electricity contracts to achieve consistency with the spot market in terms of subject matter, thereby facilitating the calculation of the spot market and medium- and long-term contracts.

[0004] However, the decomposition of power curves in existing medium- and long-term electricity contracts mostly adopts methods based on electricity proportions or typical curves. This makes the decomposition results of the power curve unable to take into account the characteristics of the power generation and consumption sides at the same time, and the feasibility is low. In addition, since it is difficult to accurately predict the output of the power generation side over long periods such as years and months, temporary adjustments to the decomposed power curve often encounter channel constraints, resulting in low utilization of transmission channels. Summary of the Invention

[0005] The present invention aims to provide a method, apparatus, device, and medium for allocating electricity based on transmission channel allocation, thereby improving transmission channel utilization. The present invention can decompose annual electricity consumption into power curves, thereby achieving a smooth connection between electricity contracts reached in the medium- and long-term electricity markets and electricity transactions in the spot market. Furthermore, the decomposed power curves can be effectively executed, thereby improving transmission channel utilization.

[0006] In order to achieve the above object, the present invention adopts the following technical solutions:

[0007] In a first aspect, the present invention provides a method for allocating power based on power transmission channel allocation, comprising:

[0008] Obtain monthly average historical power generation data; classify the 12 months of the year based on the monthly average historical power generation data and monthly power generation forecast data, and assign corresponding transmission channel capacity to each month based on the classification results to obtain monthly transmission channel capacity;

[0009] On an annual time scale, the monthly constraint condition group is called to solve a pre-established monthly objective function to obtain a monthly electricity curve; the monthly objective function considers maximizing the utilization rate of the allocated monthly transmission channel capacity;

[0010] Obtain the monthly daily average historical power generation data and daily power generation forecast data; combine the monthly daily average historical power generation data and daily power generation forecast data to classify each day of the month, and assign corresponding transmission channel capacity to each day based on the classification results to obtain the daily transmission channel capacity;

[0011] On a monthly scale, a multi-day constraint condition group is called to solve a pre-established multi-day objective function to obtain a multi-day electricity consumption curve; the multi-day objective function considers maximizing the utilization rate of the allocated daily transmission channel capacity;

[0012] On a multi-day scale within a month, the transmission channel capacity is allocated every hour based on the power generation output forecast to obtain the hourly transmission channel capacity; the intra-day multi-period constraint condition group is called to solve the pre-established intra-day multi-period objective function to obtain the intra-day multi-period power curve; wherein, the intra-day multi-period objective function considers maximizing the utilization rate of the allocated hourly transmission channel capacity.

[0013] A further improvement of the present invention is that the step of obtaining monthly average historical power generation data; classifying the 12 months of the year according to the monthly average historical power generation data and the monthly power generation forecast data, and allocating corresponding transmission channel capacity to each month according to the classification results to obtain the monthly transmission channel capacity specifically includes:

[0014] Obtain historical power generation data for X years, sum the historical power generation data for the corresponding month in the X years and divide it by X to obtain the monthly average historical power generation data; X is a positive integer greater than or equal to 3;

[0015] Based on the monthly average historical power generation data and the monthly power generation forecast data, the 12 months of the year are classified into: high-power months, average-power months, and low-power months; a high-power month is a month in which the monthly forecast power generation is greater than the F1% quantile of the monthly average historical power generation data; a average-power month is a month in which the monthly forecast power generation is between the F2% quantile and the F1% quantile of the monthly average historical power generation data; a low-power month is a month in which the monthly forecast power generation is less than the F2% quantile of the monthly average historical power generation data; wherein F1 and F2 are positive integers, 1>F1>F2;

[0016] For high-power months, the transmission channel capacity is allocated according to the installed capacity of the power generation side; for average power months, the transmission channel capacity is allocated according to M1% of the installed capacity of the power generation side; for low-power months, the transmission channel capacity is allocated according to M2% of the installed capacity of the power generation side; where M1 and M2 are positive integers, 0<M2<M1<100;

[0017] The steps of obtaining the monthly daily average historical power generation data and the daily power generation forecast data; classifying each day of the month based on the monthly average historical power generation data and the daily power generation forecast data, and allocating corresponding transmission channel capacity to each day based on the classification results to obtain the daily transmission channel capacity specifically include:

[0018] Combining the daily average historical power generation data and the daily power generation forecast data within the month, each day within the month is classified into: high power generation day, average power generation day and low power generation day; a high power generation day is a calendar day on which the daily power generation forecast data is greater than the F1 quantile of the daily average historical power generation data; a average power generation day is a calendar day on which the daily power generation forecast data is between the F2 quantile and the F1 quantile of the daily average historical power generation data; a low power generation day is a calendar day on which the daily power generation forecast data is less than the F2 quantile of the daily average historical power generation data;

[0019] For days with high power generation, the transmission channel capacity is allocated according to the installed capacity of the power generation side; for days with normal power generation, the transmission channel capacity is allocated according to M1% of the installed capacity of the power generation side; for days with low power generation, the transmission channel capacity is allocated according to M2% of the installed capacity of the power generation side.

[0020] A further improvement of the present invention is that: F1=65, F2=35; M1=80; M2=50.

[0021] A further improvement of the present invention is that: in the step of calling the monthly constraint condition group to solve the pre-established monthly objective function on the annual time scale to obtain the monthly electricity curve, the monthly objective function is:

[0022]

[0023] Among them, q m is the decomposed electricity in the mth month in the decomposed monthly electricity curve; is the typical electricity quantity in the mth month in the typical power generation curve; Q is the total annual electricity quantity to be decomposed; is the typical electricity consumption in the mth month in the monthly typical electricity consumption curve; β m and β′ m are the positive and negative slack variables of the channel vacancy capacity in the mth month, respectively, m is the penalty coefficient of the channel vacancy objective function in the mth month; F m is the transmission channel capacity allocated for the mth month according to the classification results, P m,t is the power generation output in period t in the mth month after decomposition; δ m is the penalty coefficient for the channel vacancy capacity in the mth month; α m,1 , α m,2 , α m,3 , α m,4is the weight coefficient of the monthly objective function;

[0024] The monthly constraint condition group includes:

[0025]

[0026] P m,t ≤F m

[0027] q m =p m,t ·T m

[0028]

[0029] Among them, T m is the total number of time periods in the mth month, is the utilization rate of the transmission channel in the mth month in the historical data; is the idle rate of the transmission channel in the mth month.

[0030] A further improvement of the present invention is that, on a monthly scale, in the step of calling a multi-day constraint condition group within a month to solve a pre-established multi-day objective function within a month to obtain a multi-day electricity curve within a month, the multi-day objective function within a month is:

[0031]

[0032] Among them, D m is the number of calendar days in a month; q d is the decomposed electricity quantity on the dth calendar day in the decomposed multi-day electricity quantity curve; is the typical power generation on the dth calendar day in the multi-day typical power generation curve; is the total monthly electricity consumption of the mth natural month to be decomposed; is the typical electricity consumption on the dth calendar day in the multi-day typical electricity consumption curve; β d and β′ d are the positive and negative slack variables of the channel vacancy capacity on the dth calendar day, respectively, λ d is the penalty coefficient of the channel vacancy objective function on the dth calendar day; F d is the transmission channel capacity allocated for the dth calendar day according to the classification results, P d,t is the power generation output in the tth period on the dth calendar day after decomposition; δ d is the penalty coefficient for the vacant capacity of the channel on the dth calendar day; α d,1 , α d,2 , α d,3 , α d,4 is the weight coefficient;

[0033] The multi-day constraint group within a month includes:

[0034]

[0035] P d,t ≤F d

[0036] P d,t =q d / twenty four

[0037]

[0038] in, is the utilization rate of the transmission channel on the dth calendar day in the historical data; ) is the idle rate of the transmission channel on the dth calendar day.

[0039] A further improvement of the present invention is that: on a multi-day scale within a month, the transmission channel capacity is allocated hourly based on the power generation output forecast to obtain the hourly transmission channel capacity; in the step of calling the multi-period constraint condition group within a day to solve the pre-established multi-period objective function within a day to obtain the power curve within a day, the multi-period objective function within a day is:

[0040]

[0041] Among them, p t is the output of the tth period in the decomposed intraday power curve; is the typical power output of the tth period in the typical power generation curve within the day; is the total daily electricity consumption on the dth calendar day to be decomposed; is the typical power load of the tth period in the typical power curve of the day; F t is the capacity of the transmission channel allocated during period t; δ t is the penalty coefficient of the channel vacancy capacity during period t; α t,1 , α t,2 , α t,3 is the weight coefficient;

[0042] The intraday multi-period constraint condition group includes:

[0043]

[0044] P t ≤F t .

[0045] A further improvement of the present invention is that it includes: classifying the 12 months of the year according to the size of power generation based on the monthly average historical power generation data and the monthly power generation forecast data, and allocating the corresponding monthly power transmission channel capacity to each month according to the classification results:

[0046] On an annual time scale, the transmission channel capacity allocated monthly The monthly objective function and monthly constraint condition group are established to maximize the utilization rate of the monthly transmission channel capacity and the annual total electricity Q; the monthly constraint condition group is called to solve the pre-established monthly objective function through the linear programming algorithm to obtain the monthly electricity curve

[0047] Combine the daily average historical power generation data and daily power generation forecast data within the month, classify each day within the month, and allocate the corresponding transmission channel capacity for each day based on the classification results D m is the number of calendar days in the month;

[0048] On a monthly scale, the daily transmission channel capacity allocated and monthly decomposition power consumption Establish a multi-day objective function and a multi-day constraint condition group within the month to maximize the utilization rate of the daily transmission channel capacity, and solve them to obtain the multi-day electricity curve within the month.

[0049] On a multi-day scale within a month, the hourly transmission channel capacity for each period of 24 hours within a day is allocated in combination with power generation output forecasts. Establish a multi-period objective function and a multi-period constraint condition group for maximizing the capacity utilization of the transmission channel considering the allocation, and solve them to obtain the power curve for each period of the day

[0050] In a second aspect, the present invention provides an electricity distribution device based on transmission channel distribution, comprising:

[0051] The monthly transmission channel capacity allocation module is used to obtain monthly average historical power generation data. Based on the monthly average historical power generation data and monthly power generation forecast data, the 12 months of the year are classified and the corresponding transmission channel capacity is allocated to each month based on the classification results to obtain the monthly transmission channel capacity.

[0052] A monthly electricity curve acquisition module is used to call the monthly constraint condition group to solve the pre-established monthly objective function on an annual time scale to obtain the monthly electricity curve; the monthly objective function considers maximizing the utilization rate of the allocated monthly transmission channel capacity;

[0053] The daily transmission channel capacity allocation module is used to obtain the monthly daily average historical power generation data and daily power generation forecast data; combining the monthly daily average historical power generation data and daily power generation forecast data, each day of the month is classified, and the corresponding transmission channel capacity is allocated to each day based on the classification results to obtain the daily transmission channel capacity;

[0054] The daily electricity curve acquisition module is used to call the multi-day constraint condition group within the month to solve the pre-established multi-day objective function on a monthly scale to obtain the multi-day electricity curve within the month; the multi-day objective function within the month considers maximizing the utilization rate of the allocated daily transmission channel capacity;

[0055] The time period electricity curve acquisition module is used to allocate transmission channel capacity for each hour based on the power generation output forecast on a multi-day scale within a month to obtain the hourly transmission channel capacity; call the intra-day multi-period constraint condition group to solve the pre-established intra-day multi-period objective function to obtain the intra-day multi-period electricity curve; wherein the intra-day multi-period objective function considers maximizing the utilization rate of the allocated hourly transmission channel capacity.

[0056] The present invention is further improved in that:

[0057] The monthly transmission channel capacity allocation module is used to classify the 12 months of the year by power generation size based on the monthly average historical power generation data and the monthly power generation forecast data, and allocate the corresponding monthly transmission channel capacity to each month based on the classification results:

[0058] The monthly electricity curve acquisition module is used to obtain the monthly electricity transmission channel capacity on an annual time scale. The monthly objective function and monthly constraint condition group are established to maximize the utilization rate of the monthly transmission channel capacity and the annual total electricity Q; the monthly constraint condition group is called to solve the pre-established monthly objective function through the linear programming algorithm to obtain the monthly electricity curve

[0059] The daily transmission channel capacity allocation module is used to classify each day of the month based on the daily average historical power generation data and daily power generation forecast data, and allocate the corresponding transmission channel capacity for each day according to the classification results. D m is the number of calendar days in the month;

[0060] The daily electricity curve acquisition module is used to obtain the daily transmission channel capacity allocated on a monthly basis. and monthly decomposition power consumption Establish a multi-day objective function and a multi-day constraint condition group within the month to maximize the utilization rate of the daily transmission channel capacity, and solve them to obtain the multi-day electricity curve within the month.

[0061] The time period electricity curve acquisition module is used to allocate the hourly transmission channel capacity of each period within 24 hours in a day in combination with the power generation output forecast on a multi-day scale within a month. Establish a multi-period objective function and a multi-period constraint condition group for maximizing the capacity utilization of the transmission channel considering the allocation, and solve them to obtain the power curve for each period of the day

[0062] In a third aspect, the present invention provides an electronic device comprising a processor and a memory, wherein the processor is configured to execute a computer program stored in the memory to implement the power distribution method based on power transmission channel allocation.

[0063] In a fourth aspect, the present invention provides a computer-readable storage medium, wherein the computer-readable storage medium stores at least one instruction, and when the at least one instruction is executed by a processor, the power distribution method based on transmission channel distribution is implemented.

[0064] Compared with the prior art, the present invention has the following beneficial effects:

[0065] The present invention provides an electricity distribution method, device, equipment and medium based on transmission channel allocation; historical data of recent years is obtained, and corresponding transmission channel capacity is allocated for each month according to the historical data to obtain monthly transmission channel capacity; each day of the month is classified in combination with daily average historical power generation data and daily power generation forecast data within the month, and corresponding transmission channel capacity is allocated for each day according to the classification result to obtain daily transmission channel capacity; transmission channel capacity is allocated for each hour according to power generation output forecast to obtain hourly transmission channel capacity; the present invention fully considers historical data and forecast data when decomposing the power curve, and combines the transmission channel capacity allocated at different time scales to consider maximizing the utilization rate of the transmission channel capacity, thereby ensuring the executability of the decomposed power curve and improving the utilization rate of the transmission channel.

[0066] Furthermore, the present invention adopts an optimized decomposition method, taking into account the factors of transmission channel utilization and power generation and consumption matching, and combining historical power generation and consumption data and forecast data, it can realize the decomposition of annual electricity contracts from year to month, from month to multiple days within a month, and from multiple days within a month to multiple time periods within a day. The present invention can decompose annual electricity consumption into a power curve, ultimately allocating hourly transmission channel capacity based on power generation output forecasts to obtain hourly transmission channel capacity. A pre-established intraday multi-period objective function is solved by calling a daily multi-period constraint group to obtain an intraday multi-period power curve. The present invention can utilize more accurate daily power generation output forecasts to obtain an intraday multi-period power curve that maximizes transmission channel capacity utilization, thereby achieving a smooth connection between electricity contracts reached in the medium- and long-term power market and power transactions in the spot market. Furthermore, the intraday multi-period power curve of the present invention maximizes the utilization of the transmission channel capacity allocated each hour, ensuring that the decomposed power curve is well executed and improving transmission channel utilization. This overcomes the problem in existing technologies where it is difficult to accurately predict power generation output over long periods such as years and months, resulting in temporary adjustments to the decomposed power curve often encountering channel constraints and low transmission channel utilization. The present invention is applicable to various medium- and long-term physical contracts, such as inter-provincial priority power generation plans. BRIEF DESCRIPTION OF THE DRAWINGS

[0067] The accompanying drawings, which constitute part of the present invention, are intended to provide a further understanding of the present invention. The exemplary embodiments of the present invention and their descriptions are intended to explain the present invention and do not constitute an undue limitation of the present invention. In the accompanying drawings:

[0068] Figure 1 This is a flow chart of a method for allocating power based on power transmission channel allocation according to the present invention;

[0069] Figure 2 This is a structural block diagram of an electric power distribution device based on power transmission channel distribution according to the present invention;

[0070] Figure 3 This is a structural block diagram of an electronic device of the present invention. DETAILED DESCRIPTION

[0071] The present invention will be described in detail below with reference to the accompanying drawings and in combination with embodiments. It should be noted that, in the absence of conflict, the embodiments and features of the embodiments of the present invention can be combined with each other.

[0072] The following detailed description is an exemplary description and is intended to provide further detailed description of the present invention. Unless otherwise indicated, all technical terms used in the present invention have the same meaning as those generally understood by those skilled in the art to which the present invention belongs. The terms used in the present invention are only for describing specific embodiments and are not intended to limit the exemplary embodiments according to the present invention.

[0073] Example 1

[0074] See also Figure 1 As shown, the present invention provides a method for allocating power based on power transmission channel allocation, comprising the following steps:

[0075] S101. Obtain monthly average historical power generation data; classify the 12 months of the year based on the monthly average historical power generation data and the monthly power generation forecast data, and assign corresponding transmission channel capacity to each month based on the classification results to obtain the monthly transmission channel capacity;

[0076] In the embodiment of the present invention, historical power generation data for X years (for example, X is equal to 3) is first obtained, and monthly average historical power generation data is calculated based on the historical power generation data of the previous three years.

[0077] In an embodiment of the present invention, three years of data are obtained, which may be historical power generation data from three years prior to the current power allocation time. Monthly average historical power generation data is calculated based on the three years of historical power generation data. The 12 months of the year are classified based on the monthly average historical power generation data and the monthly power generation forecast data. The corresponding transmission channel capacity is allocated to each month based on the classification results to obtain the monthly transmission channel capacity.

[0078] S102. On an annual time scale, call the monthly constraint condition group to solve a pre-established monthly objective function to obtain a monthly electricity curve; the monthly objective function considers maximizing the utilization rate of the allocated monthly transmission channel capacity;

[0079] In an embodiment of the present invention, a monthly objective function is established with the goal of maximizing channel utilization and generation-consumption matching, as well as multiple monthly constraints including transmission channel capacity. The monthly constraint group is called to solve the pre-established monthly objective function to obtain a monthly electricity curve.

[0080] S103. Obtain daily average historical power generation data and daily power generation forecast data within the month; classify each day within the month based on the daily average historical power generation data and the daily power generation forecast data, and assign corresponding transmission channel capacity to each day based on the classification results to obtain daily transmission channel capacity;

[0081] In an embodiment of the present invention, first obtain historical power generation data for X years (for example, X is equal to 3), and calculate the average daily historical power generation data within the month based on the historical power generation data of the previous three years. According to the relationship between the predicted daily power generation and the average daily historical power generation data within the month, calendar days are divided into three categories: "big power generation day", "average power generation day" and "low power generation day". The big power generation day is a calendar day on which the daily power generation forecast data is greater than the F1% quantile of the daily average historical power generation data; the average power generation day is a calendar day on which the daily power generation forecast data is between the F2% quantile and the F1% quantile of the daily average historical power generation data; the low power generation day is a calendar day on which the daily power generation forecast data is less than the F2% quantile of the daily average historical power generation data; wherein F1% and F2% are positive integers, 1>F1>F2;

[0082] For days with high power generation, the transmission channel capacity is allocated according to the installed capacity of the power generation side; for days with average power generation, the transmission channel capacity is allocated according to M1% of the installed capacity of the power generation side; for days with low power generation, the transmission channel capacity is allocated according to M2% of the installed capacity of the power generation side; M1 and M2 are positive integers, 0<M2<M1<100.

[0083] S104. On a monthly scale, a multi-day constraint condition group is called to solve a pre-established multi-day objective function to obtain a multi-day electricity consumption curve; the multi-day objective function considers maximizing the utilization rate of the allocated daily transmission channel capacity;

[0084] In this embodiment of the present invention, on a monthly scale, a multi-day monthly objective function is established with the goal of maximizing channel utilization and generation-consumption matching, as well as multiple multi-day monthly constraints including transmission channel capacity. The multi-day monthly constraint group is called to solve the pre-established multi-day monthly objective function to obtain a multi-day monthly electricity curve.

[0085] S105. On a multi-day scale within a month, allocating transmission channel capacity to each hour based on the daily power generation output forecast to obtain hourly transmission channel capacity; invoking a pre-established intraday multi-period constraint condition group to solve an intraday multi-period objective function to obtain an intraday multi-period power curve; wherein the intraday multi-period objective function considers maximizing the utilization rate of the allocated hourly transmission channel capacity;

[0086] In an embodiment of the present invention, on a multi-day scale within a month, the transmission channel capacity is allocated every hour in combination with the power generation output forecast to obtain the hourly transmission channel capacity; an intra-day multi-period objective function and its constraints are established with the goals of maximizing channel utilization, power generation and utilization matching, and power generation revenue of the power generator, and the intra-day multi-period constraint condition group is called to solve the pre-established intra-day multi-period objective function to obtain the intra-day multi-period power curve.

[0087] Example 2

[0088] The present invention provides a method for allocating power based on power transmission channel allocation, comprising the following steps:

[0089] S201. Obtain historical power generation data for X years, sum the historical power generation data for corresponding months in the X years and divide the sum by X to obtain monthly average historical power generation data; X is a positive integer greater than or equal to 3;

[0090] In an embodiment of the present invention, the 12 months of a year are classified into high-power months, average-power months, and low-power months based on the monthly average historical power generation data and the monthly power generation forecast data. The high-power months are months in which the monthly forecast power generation is greater than the F1% quantile of the monthly average historical power generation data; the average-power months are months in which the monthly forecast power generation is between the F2% quantile and the F1% quantile of the monthly average historical power generation data; and the low-power months are months in which the monthly forecast power generation is less than the F2% quantile of the monthly average historical power generation data. Wherein, F1 and F2 are positive integers, and 1>F1>F2.

[0091] In the embodiment of the present invention, F1=65, F=35, and the natural month is divided into three categories: "high-generation month", "average-generation month" and "low-generation month" in combination with the historical monthly electricity data and monthly power generation forecast data on the power generation side. Among them, "high-generation month" is defined as the month when the monthly forecast power generation is greater than the 65% percentile of the historical monthly power generation; "average-generation month" is defined as the month when the monthly forecast power generation is between the 35% percentile and the 65% percentile of the historical monthly power generation; "low-generation month" is defined as the month when the monthly forecast power generation is less than the 35% percentile of the historical monthly power generation. For "high-generation month", the transmission channel capacity is allocated according to the installed capacity of the power generation side (i.e., the maximum possible power generation output); for "average-generation month", the transmission channel capacity is reserved according to 80% of the installed capacity of the power generation side; for "low-generation month", the transmission channel capacity is reserved according to 50% of the installed capacity of the power generation side.

[0092] The 65% quantile (0.65 quantile) means that the probability of a value below this quantile in all historical data is 65%. For example, if there are 100 historical data points sorted from smallest to largest, the number ranked 65th is the 65% quantile.

[0093] S202. On an annual time scale, call the monthly constraint condition group to solve a pre-established monthly objective function to obtain a monthly electricity consumption curve; the monthly objective function considers maximizing the utilization rate of the allocated monthly transmission channel capacity;

[0094] In this embodiment of the present invention, a monthly objective function is established based on the goals of maximizing the matching degree between the monthly decomposed electricity and the monthly typical generation and consumption curve, maximizing the utilization rate of the allocated transmission channel capacity, and decomposing the monthly electricity consumption into months with idle transmission channels as much as possible:

[0095]

[0096] Among them, q m is the decomposed electricity in the mth month in the decomposed monthly electricity curve; is the typical electricity quantity in the mth month in the typical power generation curve; Q is the total annual electricity quantity to be decomposed; is the typical electricity consumption in the mth month in the monthly typical electricity consumption curve; β m and β′ m are the positive and negative slack variables of the channel vacancy capacity in the mth month, respectively, m is the penalty coefficient of the channel vacancy objective function in the mth month; F m is the monthly transmission channel capacity of the mth month allocated according to step S1, P m,t is the power generation output in period t in the mth month after decomposition. m is the penalty coefficient for the vacant capacity of the channel in the mth month. m,1 , α m,2 , α m,3 , α m,4 are the weight coefficients of each target, and the different weight coefficients reflect the priority of each target. Linear programming is used to solve the decomposed monthly electricity curve.

[0097] And establish the following monthly constraints:

[0098]

[0099] This constraint is an annual power balance constraint, which ensures that the annual total power can be executed when decomposed into monthly periods; M = 12, indicating 12 months.

[0100] P m,t ≤F m

[0101] This constraint is the transmission channel capacity constraint, which ensures that the power generation output in each period is less than the allocated transmission channel capacity.

[0102] q m =p m,t ·T m

[0103] This constraint is the connection constraint between the monthly electricity consumption and the output in each period of the month.

[0104]

[0105] This constraint ensures that the annual electricity consumption is decomposed into the months when the transmission channel is idle as much as possible. m is the decomposed electricity in the mth month in the decomposed monthly electricity curve; is the utilization rate of the transmission channel in the mth month in the historical data, then is the idle rate of the channel. m and β′ m are the positive and negative slack variables for month m, respectively;

[0106] On an annual time scale, the monthly constraint condition group is called to solve the pre-established monthly objective function to obtain the monthly electricity curve.

[0107] S203. Obtain daily average historical power generation data and daily power generation forecast data within the month; classify each day within the month based on the daily average historical power generation data and the daily power generation forecast data, and assign corresponding transmission channel capacity to each day based on the classification results to obtain daily transmission channel capacity;

[0108] In an embodiment of the present invention, calendar days are divided into three categories: "high-power days", "average-power days" and "low-power days" by combining the historical multi-day electricity data and multi-day power generation forecast data on the power generation side. Among them, "high-power days" are defined as calendar days on which the multi-day predicted power generation is greater than the 65% percentile of the historical daily power generation; "average-power days" are defined as calendar days on which the multi-day predicted power generation is between the 35% percentile and the 65% percentile of the historical daily power generation; and "low-power days" are defined as calendar days on which the multi-day predicted power generation is less than the 35% percentile of the historical daily power generation. For "high-power days", the transmission channel capacity is allocated according to the installed capacity of the power generation side (i.e., the maximum possible power generation output); for "average-power days", the transmission channel capacity is reserved according to 80% of the installed capacity of the power generation side; and for "low-power days", the transmission channel capacity is reserved according to 50% of the installed capacity of the power generation side.

[0109] S204. On a monthly scale, a multi-day constraint condition group is called to solve a pre-established multi-day objective function to obtain a multi-day electricity consumption curve; the multi-day objective function considers maximizing the utilization rate of the allocated daily transmission channel capacity;

[0110] In this embodiment of the present invention, a multi-day objective function is established based on the goals of maximizing the matching degree between the monthly decomposed electricity and the monthly typical generation and consumption curve, maximizing the utilization rate of the allocated transmission channel capacity, and decomposing the monthly electricity into months with idle transmission channels as much as possible:

[0111]

[0112] Among them, D m is the number of calendar days in a month; q d is the decomposed electricity quantity on the dth calendar day in the decomposed multi-day electricity quantity curve; is the typical power generation on the dth calendar day in the multi-day typical power generation curve; is the total monthly electricity consumption of the mth natural month to be decomposed; is the typical electricity consumption on the dth calendar day in the multi-day typical electricity consumption curve; β d and β′ d are the positive and negative slack variables of the channel vacancy capacity on the dth calendar day, respectively, λ d is the penalty coefficient of the channel vacancy objective function on the dth calendar day; F d is the transmission channel capacity for the dth calendar day allocated according to step S3, P d,t is the power generation output in the tth period on the dth calendar day after decomposition. d is the penalty coefficient for the vacant capacity of the channel on the dth calendar day. d,1 , α d,2 , α d,3 , α d,4 are the weight coefficients of each target, which reflect the priority of different targets according to the different weight coefficients. Linear programming is used to solve and obtain the multi-day electricity curve within the month after decomposition.

[0113] And establish the following multi-day constraints within a month:

[0114]

[0115] This constraint is a monthly power balance constraint, which ensures that the monthly total power can be executed when the power is decomposed over multiple days.

[0116] P d,t ≤F d

[0117] This constraint is the transmission channel capacity constraint, which ensures that the power generation output in each period is less than the allocated transmission channel capacity.

[0118] P d,t =q d / twenty four

[0119] This constraint is the connection between the total daily electricity consumption and the output in each period of the day.

[0120]

[0121] This constraint ensures that the monthly electricity consumption is decomposed into calendar days when the transmission channel is idle as much as possible. is the utilization rate of the transmission channel on the dth calendar day in the historical data, then is the idle rate of the channel. d and β′ d are the positive and negative slack variables for the dth calendar day, respectively;

[0122] On a monthly scale, the multi-day constraint condition group within a month is called to solve the pre-established multi-day objective function within a month to obtain the multi-day electricity curve within a month.

[0123] S205. On a multi-day scale within a month, allocate transmission channel capacity for each hour based on the daily power generation output forecast to obtain the hourly transmission channel capacity; call the intra-day multi-period constraint condition group to solve the pre-established intra-day multi-period objective function to obtain the intra-day multi-period power curve; wherein the intra-day multi-period objective function considers maximizing the utilization rate of the allocated hourly transmission channel capacity.

[0124] In this embodiment of the present invention, based on the goals of maximizing the matching degree between the daily decomposed power curve and the daily typical generation and consumption curve, maximizing the utilization rate of the allocated transmission channel capacity, and decomposing the daily power consumption into periods when the transmission channels are idle as much as possible, a daily multi-period objective function is established:

[0125]

[0126] Among them, p t is the output of the tth period in the decomposed intraday power curve; is the typical power output of the tth period in the typical power generation curve within the day; is the total daily electricity consumption on the dth calendar day to be decomposed; is the typical power load of the tth period in the typical power curve of the day; F t is the capacity of the transmission channel allocated during period t; δ t is the penalty coefficient for the vacant capacity of the channel during period t. t,1 , α t,2 , α t,3 are the weight coefficients of each target, which reflect the priority of different targets according to the different weight coefficients. Linear programming is used to solve the decomposed daily multi-period power curve.

[0127] And establish the following intraday multi-period constraints:

[0128]

[0129] This constraint is a daily power balance constraint, which ensures that the total daily power can be executed when the intraday power curve is decomposed.

[0130] P t ≤F t

[0131] This constraint is the transmission channel capacity constraint, which ensures that the power generation output in each period is less than the allocated transmission channel capacity;

[0132] The intraday multi-period constraint condition group is called to solve the pre-established intraday multi-period objective function to obtain the intraday multi-period power curve.

[0133] Example 3

[0134] The present invention provides a method for allocating power based on power transmission channel allocation, comprising the following steps:

[0135] S301. Obtain monthly average historical power generation data; classify the 12 months of the year based on the monthly average historical power generation data and the monthly power generation forecast data, and assign corresponding transmission channel capacity to each month based on the classification results to obtain the monthly transmission channel capacity;

[0136] In this embodiment of the present invention, the 12 months of the year are classified according to the power generation amount based on the monthly power generation data of the previous three years, and the corresponding transmission channel capacity is allocated to each month: Natural months are divided into three categories: "high-generation months," "average-generation months," and "low-generation months." A "high-generation month" is defined as a month in which the monthly forecasted power generation exceeds the 65th percentile of historical monthly power generation; a "average-generation month" is defined as a month in which the monthly forecasted power generation falls between the 35th and 65th percentiles of historical monthly power generation; and a "low-generation month" is defined as a month in which the monthly forecasted power generation falls below the 35th percentile of historical monthly power generation. For "high-generation months," transmission channel capacity is allocated based on the installed capacity (maximum potential power output) of the generator side. For "average-generation months," transmission channel capacity is allocated with a reserve of 80% of the generator side's installed capacity; and for "low-generation months," transmission channel capacity is allocated with a reserve of 50% of the generator side's installed capacity. The 65th percentile (0.65th percentile) means that within all historical data, there is a 65% probability that a value below this percentile will occur. For example, if there are 100 historical data points sorted from smallest to largest, the number ranked 65th would be the 65th percentile.

[0137] S302. On an annual time scale, call the monthly constraint condition group to solve a pre-established monthly objective function to obtain a monthly electricity curve; the monthly objective function considers maximizing the utilization rate of the allocated monthly transmission channel capacity;

[0138] In the embodiment of the present invention, on an annual time scale, the transmission channel capacity allocated monthly is used. The monthly objective function is established with the channel utilization rate and the maximization of the generation-use matching degree as the annual total power Q, as well as multiple monthly constraints including the transmission channel capacity. The monthly power curve is obtained by solving the linear programming algorithm.

[0139] S303. Obtain daily average historical power generation data and daily power generation forecast data within the month; classify each day of the month based on the daily average historical power generation data and the daily power generation forecast data, and assign corresponding transmission channel capacity to each day based on the classification results to obtain daily transmission channel capacity;

[0140] In the embodiment of the present invention, the historical power generation data of each day in the month is combined to classify each day in the month according to the daily power generation size and the predicted daily power generation size, and the corresponding transmission channel capacity is allocated to each day. (A month is calculated as 30 days); calendar days are divided into three categories: "high-generation days," "normal-generation days," and "low-generation days." A "high-generation day" is defined as a calendar day on which the predicted power generation for multiple days is greater than the 65th percentile of the historical daily power generation; a "normal-generation day" is defined as a calendar day on which the predicted power generation for multiple days is between the 35th and 65th percentiles of the historical daily power generation; and a "low-generation day" is defined as a calendar day on which the predicted power generation for multiple days is less than the 35th percentile of the historical daily power generation. For "high-generation days," the transmission channel capacity is allocated according to the installed capacity of the power generation side (i.e., the maximum possible power generation output); for "normal-generation days," the transmission channel capacity is allocated according to 80% of the installed capacity of the power generation side; and for "low-generation days," the transmission channel capacity is allocated according to 50% of the installed capacity of the power generation side.

[0141] S304. On a monthly scale, a multi-day constraint condition group is called to solve a pre-established multi-day objective function to obtain a multi-day electricity consumption curve; the multi-day objective function considers maximizing the utilization rate of the allocated daily transmission channel capacity;

[0142] In the embodiment of the present invention, on a monthly basis, according to the daily allocated transmission channel capacity and monthly decomposition power consumption Establish a multi-day objective function with the objectives of channel utilization and maximizing the matching degree of generation and use, as well as multiple multi-day constraints including transmission channel capacity, and solve them to obtain the multi-day electricity curve within the month.

[0143] S5. On a multi-day scale within a month, allocating transmission channel capacity to each hour based on the daily power generation output forecast to obtain hourly transmission channel capacity; calling the intra-day multi-period constraint condition group to solve a pre-established intra-day multi-period objective function to obtain an intra-day multi-period power curve; wherein the intra-day multi-period objective function considers maximizing the utilization rate of the allocated hourly transmission channel capacity;

[0144] In the embodiment of the present invention, the hourly transmission channel capacity is allocated on a multi-day scale within a month in combination with the power generation output forecast. Establish a multi-period objective function and its multi-period constraint conditions based on channel utilization, power generation and use matching, and maximize the power generation revenue of power generators, and solve them to obtain the multi-period power curve

[0145] Example 4

[0146] See also Figure 2 As shown, the present invention provides an electricity distribution device based on transmission channel distribution, comprising:

[0147] The monthly transmission channel capacity allocation module is used to obtain monthly average historical power generation data. Based on the monthly average historical power generation data and monthly power generation forecast data, the 12 months of the year are classified and the corresponding transmission channel capacity is allocated to each month based on the classification results to obtain the monthly transmission channel capacity.

[0148] A monthly electricity curve acquisition module is used to call the monthly constraint condition group to solve the pre-established monthly objective function on an annual time scale to obtain the monthly electricity curve; the monthly objective function considers maximizing the utilization rate of the allocated monthly transmission channel capacity;

[0149] The daily transmission channel capacity allocation module is used to obtain the monthly daily average historical power generation data and daily power generation forecast data; combining the monthly daily average historical power generation data and daily power generation forecast data, each day of the month is classified, and the corresponding transmission channel capacity is allocated to each day based on the classification results to obtain the daily transmission channel capacity;

[0150] The daily electricity curve acquisition module is used to call the multi-day constraint condition group within the month to solve the pre-established multi-day objective function on a monthly scale to obtain the multi-day electricity curve within the month; the multi-day objective function within the month considers maximizing the utilization rate of the allocated daily transmission channel capacity;

[0151] The time period electricity curve acquisition module is used to allocate transmission channel capacity for each hour based on the power generation output forecast on a multi-day scale within a month to obtain the hourly transmission channel capacity; call the intra-day multi-period constraint condition group to solve the pre-established intra-day multi-period objective function to obtain the intra-day multi-period electricity curve; wherein the intra-day multi-period objective function considers maximizing the utilization rate of the allocated hourly transmission channel capacity.

[0152] In the monthly transmission channel capacity allocation module: combining the historical monthly electricity data and monthly power generation forecast data on the power generation side, natural months are divided into three categories: "high-generation months", "normal-generation months", and "low-generation months". Among them, "high-generation months" are defined as months in which the monthly predicted power generation is greater than the 65th percentile of the historical monthly power generation; "normal-generation months" are defined as months in which the monthly predicted power generation is between the 35th and 65th percentiles of the historical monthly power generation; and "low-generation months" are defined as months in which the monthly predicted power generation is less than the 35th percentile of the historical monthly power generation. For "high-generation months", the transmission channel capacity is allocated according to the installed capacity of the power generation side (i.e., the maximum possible power generation output); for "normal-generation months", the transmission channel capacity is allocated according to 80% of the installed capacity of the power generation side; and for "low-generation months", the transmission channel capacity is allocated according to 50% of the installed capacity of the power generation side.

[0153] In the monthly electricity curve acquisition module, a monthly objective function is established based on the goals of maximizing the matching degree between the monthly decomposed electricity and the monthly typical generation and consumption curve, maximizing the utilization rate of the allocated transmission channel capacity, and decomposing the monthly electricity into months with idle transmission channels as much as possible:

[0154]

[0155] Among them, q m is the decomposed electricity in the mth month in the decomposed monthly electricity curve; is the typical electricity quantity in the mth month in the typical power generation curve; Q is the total annual electricity quantity to be decomposed; is the typical electricity consumption in the mth month in the monthly typical electricity consumption curve; β m and β′ m are the positive and negative slack variables of the channel vacancy capacity in the mth month, respectively, m is the penalty coefficient of the channel vacancy objective function in the mth month; F m is the monthly transmission channel capacity allocated in the mth month, P m,t is the power generation output in period t in the mth month after decomposition. m is the penalty coefficient for the vacant capacity of the channel in the mth month. m,1 , α m,2 , α m,3 , α m,4 are the weight coefficients of each target, and the different weight coefficients reflect the priority of each target. Linear programming is used to solve the decomposed monthly electricity curve.

[0156] And establish the following monthly constraints:

[0157]

[0158] This constraint is an annual power balance constraint, which ensures that the annual total power can be executed when decomposed into monthly periods; M = 12, indicating 12 months.

[0159] P m,t ≤F m

[0160] This constraint is the transmission channel capacity constraint, which ensures that the power generation output in each period is less than the allocated transmission channel capacity.

[0161] q m =p m,t ·T m

[0162] This constraint is the connection constraint between the monthly electricity consumption and the output in each period of the month.

[0163]

[0164] This constraint ensures that the annual electricity consumption is decomposed into the months when the transmission channel is idle as much as possible. m is the decomposed electricity in the mth month in the decomposed monthly electricity curve; is the utilization rate of the transmission channel in the mth month in the historical data, then is the idle rate of the channel. m and β′ m are the positive and negative slack variables for the mth month, respectively.

[0165] In the daily transmission channel capacity allocation module, calendar days are divided into three categories: "high-generation days," "average-generation days," and "low-generation days" by combining the generation-side's historical multi-day electricity data and multi-day power generation forecast data. A "high-generation day" is defined as a calendar day when the multi-day forecast power generation exceeds the 65th percentile of the historical daily power generation; a "average-generation day" is defined as a calendar day when the multi-day forecast power generation falls between the 35th and 65th percentiles of the historical daily power generation; and a "low-generation day" is defined as a calendar day when the multi-day forecast power generation falls below the 35th percentile of the historical daily power generation. For "high-generation days," transmission channel capacity is allocated based on the generation-side's installed capacity (i.e., maximum possible power output); for "average-generation days," transmission channel capacity is reserved based on 80% of the generation-side's installed capacity; and for "low-generation days," transmission channel capacity is reserved based on 50% of the generation-side's installed capacity.

[0166] In the daily electricity curve acquisition module, a multi-day objective function is established based on the goals of maximizing the matching degree between the monthly decomposed electricity and the monthly typical generation and consumption curve, maximizing the utilization rate of the allocated transmission channel capacity, and decomposing the monthly electricity into months with idle transmission channels as much as possible:

[0167]

[0168] Among them, D m is the number of calendar days in a month; q d is the decomposed electricity quantity on the dth calendar day in the decomposed multi-day electricity quantity curve; is the typical power generation on the dth calendar day in the multi-day typical power generation curve; is the total monthly electricity consumption of the mth natural month to be decomposed; is the typical electricity consumption on the dth calendar day in the multi-day typical electricity consumption curve; β d and β′ d are the positive and negative slack variables of the channel vacancy capacity on the dth calendar day, respectively, λ d is the penalty coefficient of the channel vacancy objective function on the dth calendar day; F d is the transmission channel capacity for the dth calendar day allocated according to step S3, P d,t is the power generation output in the tth period on the dth calendar day after decomposition. d is the penalty coefficient for the vacant capacity of the channel on the dth calendar day. d,1 , α d,2 , α d,3 , α d,4 are the weight coefficients of each target, which reflect the priority of different targets according to the different weight coefficients. Linear programming is used to solve and obtain the multi-day electricity curve within the month after decomposition.

[0169] And establish the following multi-day constraints within a month:

[0170]

[0171] This constraint is a monthly power balance constraint, which ensures that the monthly total power can be executed when the power is decomposed over multiple days.

[0172] P d,t ≤F d

[0173] This constraint is the transmission channel capacity constraint, which ensures that the power generation output in each period is less than the allocated transmission channel capacity.

[0174] P d,t =q d / twenty four

[0175] This constraint is the connection between the total daily electricity consumption and the output in each period of the day.

[0176]

[0177] This constraint ensures that the monthly electricity consumption is decomposed into calendar days when the transmission channel is idle as much as possible. is the utilization rate of the transmission channel on the dth calendar day in the historical data, then is the idle rate of the channel. d and β′ d are the positive and negative slack variables for the dth calendar day, respectively.

[0178] In the time period electricity curve acquisition module: Based on the goals of maximizing the matching degree between the daily decomposed power curve and the daily typical generation and consumption curve, maximizing the utilization rate of the allocated transmission channel capacity, and decomposing the daily electricity into periods when the transmission channels are idle as much as possible, a multi-period objective function is established within the day:

[0179]

[0180] Among them, p t is the output of the tth period in the decomposed intraday power curve; is the typical power output of the tth period in the typical power generation curve within the day; is the total daily electricity consumption on the dth calendar day to be decomposed; is the typical power load of the tth period in the typical power curve of the day; F t is the capacity of the transmission channel allocated during period t; δ t is the penalty coefficient for the vacant capacity of the channel during period t. t,1 , α t,2 , α t,3 are the weight coefficients of each target, which reflect the priority of different targets according to the different weight coefficients. Linear programming is used to solve the decomposed daily multi-period power curve.

[0181] And establish the following intraday multi-period constraints:

[0182]

[0183] This constraint is a daily power balance constraint, which ensures that the total daily power can be executed when the intraday power curve is decomposed.

[0184] P t ≤F t

[0185] This constraint is the transmission channel capacity constraint, which ensures that the power generation output in each period is less than the allocated transmission channel capacity.

[0186] Example 5

[0187] See also Figure 3 As shown, the present invention also provides an electronic device 100 for an electricity distribution method based on transmission channel allocation; the electronic device 100 includes a memory 101, at least one processor 102, a computer program 103 stored in the memory 101 and executable on the at least one processor 102, and at least one communication bus 104.

[0188] The memory 101 can be used to store the computer program 103. The processor 102 implements the method steps of the power distribution method based on power transmission channel allocation described in any one of Embodiments 1 to 2 by running or executing the computer program stored in the memory 101 and calling the data stored in the memory 101. The memory 101 can mainly include a program storage area and a data storage area. The program storage area can store an operating system and at least one application required for a function (such as a sound playback function, an image playback function, etc.); the data storage area can store data (such as audio data) generated based on the use of the electronic device 100. In addition, the memory 101 can include non-volatile memory, such as a hard disk, a memory, a plug-in hard disk, a smart media card (SMC), a secure digital (SD) card, a flash card, at least one disk storage device, a flash memory device, or other non-volatile solid-state storage device.

[0189] The at least one processor 102 may be a central processing unit (CPU), or other general-purpose processors, digital signal processors (DSP), application-specific integrated circuits (ASIC), field-programmable gate arrays (FPGA), or other programmable logic devices, discrete gate or transistor logic devices, discrete hardware components, etc. The processor 102 may be a microprocessor or any conventional processor, etc. The processor 102 is the control center of the electronic device 100 and connects various parts of the entire electronic device 100 using various interfaces and lines.

[0190] The memory 101 in the electronic device 100 stores a plurality of instructions to implement a power distribution method based on power transmission channel distribution. The processor 102 can execute the plurality of instructions to implement:

[0191] Obtain monthly average historical power generation data; classify the 12 months of the year based on the monthly average historical power generation data and monthly power generation forecast data, and assign corresponding transmission channel capacity to each month based on the classification results to obtain monthly transmission channel capacity;

[0192] On an annual time scale, the monthly constraint condition group is called to solve a pre-established monthly objective function to obtain a monthly electricity curve; the monthly objective function considers maximizing the utilization rate of the allocated monthly transmission channel capacity;

[0193] Obtain the monthly daily average historical power generation data and daily power generation forecast data; combine the monthly daily average historical power generation data and daily power generation forecast data to classify each day of the month, and assign corresponding transmission channel capacity to each day based on the classification results to obtain the daily transmission channel capacity;

[0194] On a monthly scale, a multi-day constraint condition group is called to solve a pre-established multi-day objective function to obtain a multi-day electricity consumption curve; the multi-day objective function considers maximizing the utilization rate of the allocated daily transmission channel capacity;

[0195] On a multi-day scale within a month, the transmission channel capacity is allocated every hour based on the power generation output forecast to obtain the hourly transmission channel capacity; the intra-day multi-period constraint condition group is called to solve the pre-established intra-day multi-period objective function to obtain the intra-day multi-period power curve; wherein, the intra-day multi-period objective function considers maximizing the utilization rate of the allocated hourly transmission channel capacity.

[0196] The specific implementation process of each step is detailed in Examples 1-3 and will not be repeated here.

[0197] Example 6

[0198] If the module / unit integrated in the electronic device 100 is implemented in the form of a software functional unit and sold or used as an independent product, it can be stored in a computer-readable storage medium. Based on this understanding, the present invention implements all or part of the processes in the above-mentioned embodiment method, and can also be completed by instructing the relevant hardware through a computer program. The computer program can be stored in a computer-readable storage medium, and the computer program can implement the above-mentioned various method embodiments when executed by the processor. Among them, the computer program includes computer program code, and the computer program code can be in source code form, object code form, executable file or some intermediate form, etc. The computer-readable medium may include: any entity or device that can carry the computer program code, recording medium, U disk, mobile hard disk, magnetic disk, optical disk, computer memory and read-only memory (ROM, Read-Only Memory).

[0199] It will be understood by those skilled in the art that embodiments of the present invention may be provided as methods, systems, or computer program products. Thus, the present invention may take the form of an entirely hardware embodiment, an entirely software embodiment, or an embodiment combining software and hardware. Furthermore, the present invention may take the form of a computer program product implemented on one or more computer-usable storage media (including but not limited to magnetic disk storage, CD-ROM, optical storage, etc.) containing computer-usable program code.

[0200] The present invention is described with reference to flowcharts and / or block diagrams of methods, devices (systems), and computer program products according to embodiments of the present invention. It should be understood that each process and / or block in the flowcharts and / or block diagrams, as well as combinations of processes and / or blocks in the flowcharts and / or block diagrams, can be implemented by computer program instructions. These computer program instructions can be provided to a processor of a general-purpose computer, a special-purpose computer, an embedded processor, or other programmable data processing device to produce a machine, so that the instructions executed by the processor of the computer or other programmable data processing device generate instructions for implementing the processes in the flowcharts and / or block diagrams. Figure 1 a process or multiple processes and / or boxes Figure 1 A device that provides the functions specified in a block or multiple blocks.

[0201] These computer program instructions may also be stored in a computer readable memory that can direct a computer or other programmable data processing device to work in a specific manner, so that the instructions stored in the computer readable memory produce an article of manufacture comprising an instruction device, which implements the process Figure 1 a process or multiple processes and / or boxes Figure 1 The function specified in one or more boxes.

[0202] These computer program instructions can also be loaded onto a computer or other programmable data processing device so that a series of operating steps are executed on the computer or other programmable device to produce a computer-implemented process, thereby providing the instructions executed on the computer or other programmable device for implementing the process. Figure 1 a process or multiple processes and / or boxes Figure 1 A step that specifies a function in one or more boxes.

[0203] Finally, it should be noted that the above embodiments are only used to illustrate the technical solutions of the present invention and not to limit it. Although the present invention has been described in detail with reference to the above embodiments, ordinary technicians in the field should understand that the specific implementation methods of the present invention can still be modified or replaced by equivalents. Any modification or equivalent replacement that does not depart from the spirit and scope of the present invention should be covered by the scope of protection of the claims of the present invention.

Claims

1. The power distribution method based on transmission channel allocation is characterized by: include: Obtain monthly average historical power generation data; classify the 12 months of the year based on the monthly average historical power generation data and monthly power generation forecast data, and assign corresponding transmission channel capacity to each month based on the classification results to obtain monthly transmission channel capacity; On an annual time scale, the monthly constraint condition group is called to solve a pre-established monthly objective function to obtain a monthly electricity curve; the monthly objective function considers maximizing the utilization rate of the allocated monthly transmission channel capacity; Obtain the monthly daily average historical power generation data and daily power generation forecast data; combine the monthly daily average historical power generation data and daily power generation forecast data to classify each day of the month, and assign corresponding transmission channel capacity to each day based on the classification results to obtain the daily transmission channel capacity; On a monthly scale, a multi-day constraint condition group is called to solve a pre-established multi-day objective function to obtain a multi-day electricity consumption curve; the multi-day objective function considers maximizing the utilization rate of the allocated daily transmission channel capacity; On a multi-day scale within a month, the transmission channel capacity is allocated for each hour based on the daily power generation output forecast to obtain the hourly transmission channel capacity; The intraday multi-period constraint condition group is called to solve the pre-established intraday multi-period objective function to obtain the intraday multi-period power curve; wherein the intraday multi-period objective function considers the maximization of the capacity utilization of the allocated transmission channel.

2. The power distribution method based on transmission channel allocation according to claim 1, characterized in that: The steps of obtaining monthly average historical power generation data; classifying the 12 months of the year according to the monthly average historical power generation data and the monthly power generation forecast data, and allocating corresponding transmission channel capacity to each month according to the classification results to obtain the monthly transmission channel capacity specifically include: Obtain historical power generation data for X years, sum the historical power generation data for the corresponding month in the X years and divide it by X to obtain the monthly average historical power generation data; X is a positive integer greater than or equal to 3; Based on the monthly average historical power generation data and the monthly power generation forecast data, the 12 months of the year are classified into: high-power months, average-power months, and low-power months; a high-power month is a month in which the monthly forecast power generation is greater than the F1% percentile of the monthly average historical power generation data; a average-power month is a month in which the monthly forecast power generation is between the F2% percentile and the F1 percentile of the monthly average historical power generation data; a low-power month is a month in which the monthly forecast power generation is less than the F2 percentile of the monthly average historical power generation data; where F1 and F2 are positive integers, 1>F1>F2; For high-power months, the transmission channel capacity is allocated according to the installed capacity of the power generation side; for average power months, the transmission channel capacity is allocated according to M1% of the installed capacity of the power generation side; for low-power months, the transmission channel capacity is allocated according to M2% of the installed capacity of the power generation side; where M1 and M2 are positive integers, 0<M2<M1<100; The steps of obtaining the monthly daily average historical power generation data and the daily power generation forecast data; classifying each day of the month based on the monthly average historical power generation data and the daily power generation forecast data, and allocating corresponding transmission channel capacity to each day based on the classification results to obtain the daily transmission channel capacity specifically include: Combining the daily average historical power generation data and the daily power generation forecast data within the month, each day within the month is classified into: a high power generation day, a normal power generation day, and a low power generation day; a high power generation day is a calendar day on which the daily power generation forecast data is greater than the F1% quantile of the daily average historical power generation data; a normal power generation day is a calendar day on which the daily power generation forecast data is between the F2% quantile and the F1% quantile of the daily average historical power generation data; and a low power generation day is a calendar day on which the daily power generation forecast data is less than the F2% quantile of the daily average historical power generation data. For days with high power generation, the transmission channel capacity is allocated according to the installed capacity of the power generation side; for days with normal power generation, the transmission channel capacity is allocated according to M1% of the installed capacity of the power generation side; for days with low power generation, the transmission channel capacity is allocated according to M2% of the installed capacity of the power generation side.

3. The power distribution method based on power transmission channel allocation according to claim 1, characterized in that: In the step of calling the monthly constraint condition group to solve the pre-established monthly objective function on the annual time scale to obtain the monthly electricity curve, the monthly objective function is: Among them, q m is the decomposed electricity in the mth month in the decomposed monthly electricity curve; is the typical electricity quantity in the mth month in the typical power generation curve; Q is the total annual electricity quantity to be decomposed; is the typical electricity consumption in the mth month in the monthly typical electricity consumption curve; β m and β′ m are the positive and negative slack variables of the channel vacancy capacity in the mth month, respectively, m is the penalty coefficient of the channel vacancy objective function in the mth month; F m is the transmission channel capacity allocated for the mth month according to the classification results, P m,t is the power generation output in period t in the mth month after decomposition; δ m is the penalty coefficient for the channel vacancy capacity in the mth month; α m,1 , α m,2 , α m,3 , α m,4 is the weight coefficient of the monthly objective function; The monthly constraint condition group includes: P m,t ≤F m q m =p m,t ·T m Among them, T m is the total number of time periods in the mth month, is the utilization rate of the transmission channel in the mth month in the historical data; is the idle rate of the transmission channel in the mth month.

4. The method for allocating power based on power transmission channel allocation according to claim 1, characterized in that: In the step of calling the multi-day constraint condition group within a month to solve the pre-established multi-day objective function within a month and obtaining the multi-day electricity curve within a month on a monthly scale, the multi-day objective function within a month is: Among them, D m is the number of calendar days in a month; q d is the decomposed electricity quantity on the dth calendar day in the decomposed multi-day electricity quantity curve; is the typical power generation on the dth calendar day in the multi-day typical power generation curve; is the total monthly electricity consumption of the mth natural month to be decomposed; is the typical electricity consumption on the dth calendar day in the multi-day typical electricity consumption curve; β d and β′ d are the positive and negative slack variables of the channel vacancy capacity on the dth calendar day, respectively, λ d is the penalty coefficient of the channel vacancy objective function on the dth calendar day; F d is the transmission channel capacity allocated for the dth calendar day according to the classification results, P d,t is the power generation output in the tth period on the dth calendar day after decomposition; δ d is the penalty coefficient for the vacant capacity of the channel on the dth calendar day; α d,1 , α d,2 , α d,3 , α d,4 is the weight coefficient; The multi-day constraint group within a month includes: P d,t ≤F d P d,t =q d / 24 in, is the utilization rate of the transmission channel on the dth calendar day in the historical data; is the idle rate of the transmission channel on the dth calendar day.

5. The method for distributing electricity based on transmission channel allocation according to claim 1, characterized in that: The transmission channel capacity is allocated every hour based on the daily power generation output forecast on a multi-day scale within a month to obtain the transmission channel capacity at that time; In the step of calling the intraday multi-period constraint condition group to solve the pre-established intraday multi-period objective function and obtaining the intraday multi-period power curve, the intraday multi-period objective function is: Among them, p t is the output of the tth period in the intraday power curve after decomposition; is the typical power output of the tth period in the typical power generation curve within the day; is the total daily electricity consumption on the dth calendar day to be decomposed; is the typical power load of the tth period in the typical power curve of the day; F t is the capacity of the transmission channel allocated during period t; δ t is the penalty coefficient of the channel vacancy capacity during period t; α t,1 , α t,2 , α t,3 is the weight coefficient; The intraday multi-period constraint condition group includes: P t ≤F t 。 6. The method for allocating power based on power transmission channel allocation according to claim 1, characterized in that: include: Based on the monthly average historical power generation data and monthly power generation forecast data, the 12 months of the year are classified according to power generation size, and the corresponding monthly transmission channel capacity is allocated to each month according to the classification results: On an annual time scale, the transmission channel capacity allocated monthly The monthly objective function and monthly constraint condition group are established to maximize the utilization rate of the monthly transmission channel capacity and the annual total electricity Q; the monthly constraint condition group is called to solve the pre-established monthly objective function through the linear programming algorithm to obtain the monthly electricity curve Combine the daily average historical power generation data and daily power generation forecast data within the month, classify each day within the month, and allocate the corresponding transmission channel capacity for each day based on the classification results D m is the number of calendar days in the month; On a monthly scale, the daily transmission channel capacity allocated and monthly decomposition power consumption Establish a multi-day objective function and a multi-day constraint condition group within the month to maximize the utilization rate of the daily transmission channel capacity, and solve them to obtain the multi-day electricity curve within the month. On a multi-day scale within a month, the hourly transmission channel capacity for each period of 24 hours within a day is allocated in combination with power generation output forecasts. Establish a multi-period objective function and a multi-period constraint condition group for maximizing the capacity utilization of the transmission channel considering the allocation, and solve them to obtain the power curve for each period of the day 7. The power distribution device based on power transmission channel distribution is characterized in that: include: Monthly transmission channel capacity allocation module, used to obtain monthly average historical power generation data; Based on the monthly average historical power generation data and monthly power generation forecast data, the 12 months of the year are classified and the corresponding transmission channel capacity is allocated to each month according to the classification results to obtain the monthly transmission channel capacity; A monthly electricity curve acquisition module is used to call the monthly constraint condition group to solve the pre-established monthly objective function on an annual time scale to obtain the monthly electricity curve; the monthly objective function considers maximizing the utilization rate of the allocated monthly transmission channel capacity; The daily transmission channel capacity allocation module is used to obtain the monthly daily average historical power generation data and daily power generation forecast data; combining the monthly daily average historical power generation data and daily power generation forecast data, each day of the month is classified, and the corresponding transmission channel capacity is allocated to each day based on the classification results to obtain the daily transmission channel capacity; The daily electricity curve acquisition module is used to call the multi-day constraint condition group within the month to solve the pre-established multi-day objective function on a monthly scale to obtain the multi-day electricity curve within the month; the multi-day objective function within the month considers maximizing the utilization rate of the allocated daily transmission channel capacity; The time period power curve acquisition module is used to allocate transmission channel capacity for each hour based on the daily power generation output forecast on a multi-day scale within a month, and obtain the transmission channel capacity at that time; The intraday multi-period constraint condition group is called to solve the pre-established intraday multi-period objective function to obtain the intraday multi-period power curve; wherein the intraday multi-period objective function considers the maximization of the capacity utilization of the allocated transmission channel.

8. The power distribution device based on power transmission channel allocation according to claim 7, characterized in that: The monthly transmission channel capacity allocation module is used to classify the 12 months of the year by power generation size based on the monthly average historical power generation data and the monthly power generation forecast data, and allocate the corresponding monthly transmission channel capacity to each month based on the classification results: The monthly electricity curve acquisition module is used to obtain the monthly electricity transmission channel capacity on an annual time scale. and the annual total electricity Q to establish the monthly objective function and the monthly constraint condition group that considers the maximum utilization rate of the monthly transmission channel capacity; Call the monthly constraint group to solve the pre-established monthly objective function through the linear programming algorithm to obtain the monthly power curve The daily transmission channel capacity allocation module is used to classify each day of the month based on the daily average historical power generation data and daily power generation forecast data, and allocate the corresponding transmission channel capacity for each day according to the classification results. D m is the number of calendar days in the month; The daily electricity curve acquisition module is used to obtain the daily transmission channel capacity allocated on a monthly basis. and monthly decomposition power consumption Establish a multi-day objective function and a multi-day constraint condition group within the month to maximize the utilization rate of the daily transmission channel capacity, and solve them to obtain the multi-day electricity curve within the month. The time period electricity curve acquisition module is used to allocate the hourly transmission channel capacity of each period within 24 hours in a day in combination with the power generation output forecast on a multi-day scale within a month. Establish a multi-period objective function and a multi-period constraint condition group for maximizing the capacity utilization of the transmission channel considering the allocation, and solve them to obtain the power curve for each period of the day 9. An electronic device, characterized in that: The electronic device includes a processor and a memory, and the processor is used to execute a computer program stored in the memory to implement the power distribution method based on power transmission channel distribution according to any one of claims 1 to 6.

10. A computer-readable storage medium, characterized in that The computer-readable storage medium stores at least one instruction, and when the at least one instruction is executed by a processor, the power distribution method based on power transmission channel distribution according to any one of claims 1 to 6 is implemented.

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