Electricity selling strategy optimization method based on market factors and resource configuration optimization

Abstract

The invention discloses an electricity selling strategy optimization method based on market factors and resource configuration optimization, and relates to the technical field of electric power analysis, and the method comprises the steps: building a relation model of electricity consumption and price; obtaining an electric quantity potential consumption model; calculating the potential increase amount of power consumption; calculating a growth coefficient of the potential lifting amount to form a critical value of the growth coefficient; calculating a power utilization resource load coefficient, and forming a preset value of the power utilization resource load coefficient; when the growth coefficient is greater than a critical value, performing electricity selling price reduction optimization; calculating to obtain a first adjustment electricity price; adjusting the floating electricity price; when the power utilization resource load coefficient is greater than a preset value, power sale price increase optimization is carried out; calculating to obtain a second adjustment electricity price; and adjusting the floating electricity price. The electric quantity potential consumption model is obtained by establishing the relation model of the electricity consumption and the price, so that the potential electricity consumption demand of the user can be stimulated, the electricity consumption satisfaction degree of the user is further improved, and line faults caused by overhigh load are avoided.

Description

Technical Field

[0001] The present invention relates to the technical field of power analysis, and in particular to a method for optimizing a power sales strategy based on market factors and resource allocation optimization. Background Art

[0002] Power sales companies improve their market competitiveness, meet user needs and enhance user satisfaction through flexible sales models, diversified products and pricing strategies. As the power market becomes increasingly open, how power sales companies can sell electricity efficiently and accurately has become a focus of attention within and outside the industry.

[0003] The existing technology generates power sales strategies for different power users by analyzing the power load characteristics of power users and combining them with the power sales revenue of power sales companies. However, the power load characteristics of users cannot reflect the potential power consumption capacity of users, resulting in the set electricity price being unable to stimulate potential power consumption, and thus the potential power demand of users cannot be met. There is room for improvement in user satisfaction. In addition, the existing technology does not have sufficient control over power load, which can easily cause power transmission failures. Summary of the invention

[0004] In order to solve the above technical problems, a method for optimizing electricity sales strategies based on market factors and resource allocation optimization is provided. This technical solution solves the problem that the existing technology proposed in the above background technology generates electricity sales strategies for different electricity users by analyzing the electricity load characteristics of electricity users and combining the electricity sales revenue of the power sales company. However, the user's electricity load characteristics cannot reflect the user's potential electricity consumption capacity, resulting in the set electricity price being unable to stimulate potential electricity consumption, and then the user's potential electricity demand cannot be met, and there is room for improvement in user satisfaction. In addition, the existing technology does not have sufficient control over the electricity load, which can easily cause power transmission failures.

[0005] In order to achieve the above purpose, the technical solution adopted by the present invention is:

[0006] A method for optimizing power sales strategy based on market factors and resource allocation optimization, comprising:

[0007] Obtaining the real-time power generation of the power plant and the real-time power consumption of at least one user, wherein the real-time power consumption is the total power consumption of all users within a time period less than a preset time from the current time;

[0008] According to the supply and demand relationship of electricity, establish the relationship model between electricity consumption and price;

[0009] The electricity price is divided into two parts: the basic electricity price and the floating electricity price. The basic electricity price is a fixed value, and the floating electricity price is a variable value. Based on historical data, the variable range of the floating electricity price is obtained.

[0010] Analyze the potential power consumption capacity of the market and obtain the potential power consumption model;

[0011] Calculate the potential increase in power consumption based on the power consumption potential model;

[0012] Calculate the growth coefficient of potential improvement and form the critical value of the growth coefficient;

[0013] Calculate the power resource load factor to form a preset value of the power resource load factor;

[0014] When the growth coefficient is greater than the critical value, the electricity price reduction optimization is carried out;

[0015] When optimizing the electricity price reduction, the first adjusted electricity price is calculated based on the relationship model between electricity consumption and price;

[0016] adjusting the floating electricity price based on the first adjusted electricity price;

[0017] When the load factor of electricity resources is greater than the preset value, the electricity price will be optimized;

[0018] When optimizing the electricity price increase, the second adjusted electricity price is calculated based on the relationship model between electricity consumption and price;

[0019] The floating electricity price is adjusted based on the second adjusted electricity price.

[0020] Preferably, the step of establishing a relationship model between electricity consumption and price based on the supply and demand relationship of electricity consumption comprises the following steps:

[0021] Obtain a value range of the electricity selling price, divide the value range of the real-time electricity consumption into equal intervals, and obtain at least one identification point;

[0022] Obtain the value range of the power price regulation range, divide the value range of the power price regulation range into equal intervals (-k, k), and obtain at least one test point, where k is the maximum value of the power price regulation range in the historical data. If the electricity price is increased, the power price regulation range is positive, and if the electricity price is reduced, the power price regulation range is negative;

[0023] Under the condition that the electricity selling price is equal to the value at the identification point, the first electricity consumption is obtained, and under the condition that the electricity selling price is equal to the sum of the value at the identification point and the value at the test point, the second electricity consumption is obtained;

[0024] Using the proportional formula, calculate the change ratio of the first power consumption;

[0025] Pairing the change ratio, the value at the identification point and the value at the test point, and fitting at least one set of the paired change ratio, the value at the identification point and the value at the test point to obtain a supply-demand fitting function, and using the supply-demand fitting function as a relationship model between electricity consumption and price, wherein the change ratio and the value at the identification point are independent variables, and the value at the test point is a dependent variable;

[0026] The ratio formula is as follows:

[0027]

[0028] Among them, A is the change ratio, a is the second power consumption, and b is the first power consumption.

[0029] Preferably, the step of analyzing the potential power consumption capacity of the market to obtain a potential power consumption model comprises the following steps:

[0030] Evenly divide the whole day time period to obtain at least one partition time period, and the length of the partition time period is equal to twice the preset time;

[0031] Obtaining the income of at least one user, dividing the users according to their income, and obtaining at least one user set, wherein the income difference of users in the user set is less than a preset amount;

[0032] Randomly select a user from the user set as a sample user;

[0033] Acquire at least one power-consuming device used by the sample user;

[0034] Based on big data, obtain the usage time of power-consuming devices;

[0035] When the usage time of the power-consuming device overlaps with the partition time period, the power-consuming device is paired with the partition time period;

[0036] Add the rated powers of the power consuming devices paired with the partition time periods to obtain the total rated power;

[0037] The total rated power is multiplied by the length of the partition period to obtain the potential upper limit of power consumption of the sample user in the partition period;

[0038] The potential power consumption upper limit of at least one sample user in at least one partition period is aggregated to obtain a potential power consumption model.

[0039] Preferably, the calculation of the potential increase in power consumption based on the power potential consumption model comprises the following steps:

[0040] Get the current actual time, and use the partition period where the current actual time is located as the target partition period;

[0041] Using the comprehensive electricity formula, calculate the overall electricity consumption limit of at least one user;

[0042] Subtract the real-time power consumption from the real-time power generation to obtain the power idle value;

[0043] Subtract the real-time power consumption from the total power consumption limit to get the power potential value;

[0044] The smaller value between the power idle value and the power potential value is used as the potential increase in power consumption;

[0045] The comprehensive formula for electricity is as follows:

[0046]

[0047] Where B is the total power consumption limit, i is the subscript, n is the total number of at least one user set, c i is the potential upper limit of electricity consumption of the sample users in the i-th user set during the target partition period, d i is the number of elements in the i-th user set.

[0048] Preferably, the step of calculating the growth coefficient of the potential improvement and forming a critical value of the growth coefficient comprises the following steps:

[0049] Take at least one time point within one hour before the current time, and obtain the potential improvement at the time point as the feature potential improvement;

[0050] Pair and fit the time points with the potential lift of the features to obtain the lift fitting function;

[0051] Derivative the lifting fitting function to obtain the growth fitting function;

[0052] Substitute the current time into the growth fitting function to obtain the growth coefficient of the potential improvement;

[0053] Obtain at least one sample time, substitute the sample time into the growth fitting function, and obtain the sample growth coefficient;

[0054] Using the minimum and maximum values ​​of at least one sample growth factor, a growth interval is formed;

[0055] Uniformly select at least one growth point in the growth interval, and obtain the increase in electricity consumption when the power selling price changes by the preset price range under the condition that the potential increase is equal to the value at the growth point;

[0056] When the increase in power consumption is greater than the preset power consumption, the growth point is taken as the target growth point;

[0057] The minimum value of at least one target growth point is used as the critical value of the growth coefficient.

[0058] Preferably, the calculating of the power resource load coefficient to form a preset value of the power resource load coefficient comprises the following steps:

[0059] The real-time power consumption is divided by the real-time power generation to obtain the power resource load factor;

[0060] Based on the historical data, obtaining at least one historical power resource load factor;

[0061] Obtain the failure rate of transmission lines under the condition of historical power resource load factor;

[0062] When the failure rate is greater than the preset ratio, the historical power resource load factor is used as the risk value;

[0063] The minimum value of at least one risk value is used as a preset value of the power resource load factor.

[0064] Preferably, the step of calculating the first adjusted electricity price based on the relationship model between electricity consumption and price comprises the following steps:

[0065] The potential increase in power consumption is divided by the real-time power consumption to obtain the actual ratio;

[0066] Substitute the actual proportion and electricity selling price into the supply and demand fitting function to obtain the first adjusted electricity price.

[0067] Preferably, the adjusting the floating electricity price based on the first adjusted electricity price comprises the following steps:

[0068] The first adjusted electricity price is added to the floating electricity price to obtain a first change value;

[0069] When the first change value belongs to the variable range, the floating electricity price is adjusted to the first change value; otherwise, the floating electricity price is adjusted to the maximum value in the variable range.

[0070] Preferably, the step of calculating the second adjusted electricity price based on the relationship model between electricity consumption and price comprises the following steps:

[0071] The real-time power generation is multiplied by the preset value to obtain the target power consumption;

[0072] The difference between the target power consumption and the real-time power consumption is divided by the real-time power consumption to obtain the target ratio;

[0073] Substitute the target ratio and electricity selling price into the supply and demand fitting function to obtain the second adjusted electricity price.

[0074] Preferably, the adjusting the floating electricity price based on the second adjusted electricity price comprises the following steps:

[0075] The second adjusted electricity price is added to the floating electricity price to obtain a second change value;

[0076] When the second change value belongs to the variable range, the floating electricity price is adjusted to the second change value; otherwise, the floating electricity price is adjusted to the maximum value in the variable range.

[0077] Compared with the prior art, the present invention has the following beneficial effects:

[0078] By establishing a relationship model between electricity consumption and price, obtaining a potential electricity consumption model, judging the growth coefficient and the load coefficient of electricity resources and making corresponding adjustments to the electricity price, we can estimate the user's potential electricity consumption, and then make reasonable adjustments to the electricity price to stimulate the user's potential electricity demand, thereby improving the user's electricity satisfaction. At the same time, the electricity load is calculated, and the price is adjusted in time according to the electricity load situation, thereby avoiding line failures caused by excessive load. BRIEF DESCRIPTION OF THE DRAWINGS

[0079] Figure 1 A flow chart of a method for optimizing a power sales strategy based on market factors and resource allocation optimization according to the present invention;

[0080] Figure 2 A flow chart of establishing a relationship model between electricity consumption and price according to the supply and demand relationship of electricity consumption according to the present invention;

[0081] Figure 3 A schematic diagram of a flow chart of analyzing the potential power consumption capacity of the market and obtaining a potential power consumption model of the present invention;

[0082] Figure 4 A schematic diagram of a flow chart of calculating a potential increase in power consumption based on a potential power consumption model of the present invention;

[0083] Figure 5 A schematic diagram of a process for calculating the growth coefficient of potential improvement and forming a critical value of the growth coefficient according to the present invention;

[0084] Figure 6 A schematic diagram of a flow chart of calculating the power resource load factor and forming a preset value of the power resource load factor according to the present invention;

[0085] Figure 7 A schematic diagram of a flow chart of calculating a first adjusted electricity price based on a relationship model between electricity consumption and price according to the present invention;

[0086] Figure 8 It is a schematic diagram of a process of adjusting the floating electricity price based on the first adjusted electricity price of the present invention;

[0087] Fig. 9 A schematic diagram of a flow chart of calculating a second adjusted electricity price based on a relationship model between electricity consumption and price according to the present invention;

[0088] Fig.10 It is a schematic diagram of a flow chart of adjusting the floating electricity price based on the second adjusted electricity price according to the present invention. DETAILED DESCRIPTION

[0089] The following description is used to disclose the present invention so that those skilled in the art can implement the present invention. The preferred embodiments described below are only examples, and those skilled in the art may think of other obvious variations.

[0090] Reference Figure 1 As shown, a method for optimizing a power sales strategy based on market factors and resource allocation optimization includes:

[0091] Obtaining the real-time power generation of the power plant and the real-time power consumption of at least one user, wherein the real-time power consumption is the total power consumption of all users within a time period less than a preset time from the current time;

[0092] According to the supply and demand relationship of electricity, establish the relationship model between electricity consumption and price;

[0093] The electricity price is divided into two parts: the basic electricity price and the floating electricity price. The basic electricity price is a fixed value, and the floating electricity price is a variable value. Based on historical data, the variable range of the floating electricity price is obtained.

[0094] Analyze the potential power consumption capacity of the market and obtain the potential power consumption model;

[0095] Calculate the potential increase in power consumption based on the power consumption potential model;

[0096] Calculate the growth coefficient of potential improvement and form the critical value of the growth coefficient;

[0097] Calculate the power resource load factor to form a preset value of the power resource load factor;

[0098] When the growth coefficient is greater than the critical value, the electricity price reduction optimization is carried out;

[0099] When optimizing the electricity price reduction, the first adjusted electricity price is calculated based on the relationship model between electricity consumption and price;

[0100] adjusting the floating electricity price based on the first adjusted electricity price;

[0101] When the load factor of electricity resources is greater than the preset value, the electricity price will be optimized;

[0102] When optimizing the electricity price increase, the second adjusted electricity price is calculated based on the relationship model between electricity consumption and price;

[0103] The floating electricity price is adjusted based on the second adjusted electricity price.

[0104] Electricity service is a public service. Therefore, when selling electricity, profit is not the main factor. However, costs will be controlled to prevent excessive losses. Therefore, in this plan, when adjusting prices, the electricity price is divided into two parts, namely the basic electricity price and the floating electricity price, and a variable range is set for the floating electricity price. The basic electricity price accounts for the main part of the electricity price, while the floating electricity price is the part used for adjustment. In this way, the adjustment can be controlled within a reasonable range to prevent extreme prices.

[0105] In this solution, the main purpose is to improve the user's electricity experience. Due to price factors, some users will reduce the use of some electrical appliances, but the actual situation is that the existing electricity can meet the current potential electricity demand, and users actually have the need to use it. If this electricity is not used, it will be wasted. Therefore, it is necessary to make reasonable adjustments to the price in order to increase user satisfaction.

[0106] The real-time power consumption is the total power consumption of all users within a period less than the preset time from the current time. When the preset time is small enough, the real-time power consumption can be approximately regarded as the instantaneous power consumption. According to the definition, it is easy to know that the real-time power consumption is the power consumed by twice the preset time length.

[0107] Reference Figure 2 As shown, according to the supply and demand relationship of electricity, establishing the relationship model between electricity consumption and price includes the following steps:

[0108] Obtain a value range of the electricity selling price, divide the value range of the real-time electricity consumption into equal intervals, and obtain at least one identification point;

[0109] Obtain the value range of the power price regulation range, divide the value range of the power price regulation range into equal intervals (-k, k), and obtain at least one test point, where k is the maximum value of the power price regulation range in the historical data. If the electricity price is increased, the power price regulation range is positive, and if the electricity price is reduced, the power price regulation range is negative;

[0110] Under the condition that the electricity selling price is equal to the value at the identification point, the first electricity consumption is obtained, and under the condition that the electricity selling price is equal to the sum of the value at the identification point and the value at the test point, the second electricity consumption is obtained;

[0111] Using the proportional formula, calculate the change ratio of the first power consumption;

[0112] Pairing the change ratio, the value at the identification point and the value at the test point, and fitting at least one set of the paired change ratio, the value at the identification point and the value at the test point to obtain a supply-demand fitting function, and using the supply-demand fitting function as a relationship model between electricity consumption and price, wherein the change ratio and the value at the identification point are independent variables, and the value at the test point is a dependent variable;

[0113] The ratio formula is as follows:

[0114]

[0115] Among them, A is the change ratio, a is the second power consumption, and b is the first power consumption.

[0116] There is a strong correlation between electricity demand and price, but it should be noted that electricity demand is not only related to the magnitude of price changes, but also to the price itself. Obviously, the change in electricity demand caused by a price difference of 1 yuan and 1.1 yuan is different from the change in electricity demand caused by a price difference of 0.5 yuan and 0.6 yuan. Therefore, these two factors are taken into account when constructing the model. At the same time, in order to facilitate subsequent calculations, the change ratio and the value at the identification point are used as independent variables when setting the supply and demand fitting function, because in actual calculations, the required price change value needs to be calculated.

[0117] Reference Figure 3 As shown, the potential power consumption capacity of the market is analyzed to obtain the potential power consumption model, which includes the following steps:

[0118] Evenly divide the whole day time period to obtain at least one partition time period, and the length of the partition time period is equal to twice the preset time;

[0119] Obtaining the income of at least one user, dividing the users according to their income, and obtaining at least one user set, wherein the income difference of users in the user set is less than a preset amount;

[0120] Randomly select a user from the user set as a sample user;

[0121] Acquire at least one power-consuming device used by the sample user;

[0122] Based on big data, obtain the usage time of power-consuming devices;

[0123] When the usage time of the power-consuming device overlaps with the partition time period, the power-consuming device is paired with the partition time period;

[0124] Add the rated powers of the power consuming devices paired with the partition time periods to obtain the total rated power;

[0125] The total rated power is multiplied by the length of the partition period to obtain the potential upper limit of power consumption of the sample user in the partition period;

[0126] The potential power consumption upper limit of at least one sample user in at least one partition period is aggregated to obtain a potential power consumption model.

[0127] The partition period is set to 2 times the preset time in order to keep the calculation method of the potential power consumption limit relatively consistent with the calculation method of the real-time power consumption, that is, their time lengths are consistent;

[0128] The reason for classifying users is that users with different incomes use different electrical appliances, so their power consumption is also different. By using the classification method, the power consumption of sample users in the user set can be used to represent all users in the user set. Therefore, it is not necessary to calculate for each user, thereby reducing the load of the algorithm.

[0129] When calculating the potential upper limit of electricity consumption, it is necessary to calculate according to the actual situation, because each power-consuming device has a relatively fixed usage time. For example, lights and air conditioners have basically the same usage time under big data statistics. Therefore, the power consumption can be calculated according to the partition time period in which they are used, thereby obtaining the potential upper limit of electricity consumption.

[0130] Reference Figure 4 As shown, based on the potential power consumption model, calculating the potential increase in power consumption includes the following steps:

[0131] Get the current actual time, and use the partition period where the current actual time is located as the target partition period;

[0132] Using the comprehensive electricity formula, calculate the overall electricity consumption limit of at least one user;

[0133] Subtract the real-time power consumption from the real-time power generation to obtain the power idle value;

[0134] Subtract the real-time power consumption from the total power consumption limit to get the power potential value;

[0135] The smaller value between the power idle value and the power potential value is used as the potential increase in power consumption;

[0136] The comprehensive formula for electricity is as follows:

[0137]

[0138] Where B is the total power consumption limit, i is the subscript, n is the total number of at least one user set, c i is the potential upper limit of electricity consumption of the sample users in the i-th user set during the target partition period, d i is the number of elements in the i-th user set.

[0139] Since there are users who should use certain power-consuming devices but do not use them due to price reasons, it is necessary to identify this situation and calculate the potential value of power consumption;

[0140] The reason for selecting the smaller value between the power idle value and the power potential value is that the power potential value cannot be greater than the power idle value, otherwise, it will cause excessive load and easily cause failure.

[0141] Reference Figure 5 As shown, calculating the growth coefficient of the potential improvement and forming the critical value of the growth coefficient includes the following steps:

[0142] Take at least one time point within one hour before the current time, and obtain the potential improvement at the time point as the feature potential improvement;

[0143] Pair and fit the time points with the potential lift of the features to obtain the lift fitting function;

[0144] Derivative the lifting fitting function to obtain the growth fitting function;

[0145] Substitute the current time into the growth fitting function to obtain the growth coefficient of the potential improvement;

[0146] Obtain at least one sample time, substitute the sample time into the growth fitting function, and obtain the sample growth coefficient;

[0147] Using the minimum and maximum values ​​of at least one sample growth factor, a growth interval is formed;

[0148] Uniformly select at least one growth point in the growth interval, and obtain the increase in electricity consumption when the power selling price changes by the preset price range under the condition that the potential increase is equal to the value at the growth point;

[0149] When the increase in power consumption is greater than the preset power consumption, the growth point is taken as the target growth point;

[0150] The minimum value of at least one target growth point is used as the critical value of the growth coefficient.

[0151] Since this program is carried out continuously, the potential improvement amount counted is actually the value that has been adjusted by this program. Therefore, there is no value in adjusting the potential improvement amount. Therefore, the growth coefficient of the potential improvement amount is calculated. The growth coefficient reflects the future changes in the potential improvement amount. Therefore, the subsequent potential improvement amount can be adjusted based on this.

[0152] The critical value of the growth coefficient is set according to the adjustment of electricity consumption. When the growth coefficient is small, the increase in electricity consumption caused by the preset price change is very small and can be ignored. Therefore, not adjusting such a growth coefficient can save computing power.

[0153] Reference Figure 6 As shown, calculating the power resource load factor and forming a preset value of the power resource load factor includes the following steps:

[0154] The real-time power consumption is divided by the real-time power generation to obtain the power resource load factor;

[0155] Based on the historical data, obtaining at least one historical power resource load factor;

[0156] Obtain the failure rate of transmission lines under the condition of historical power resource load factor;

[0157] When the failure rate is greater than the preset ratio, the historical power resource load factor is used as the risk value;

[0158] The minimum value of at least one risk value is used as a preset value of the power resource load factor.

[0159] The preset value of the power resource load factor is set according to the failure rate. When the failure cannot be ignored, the corresponding power resource load factor is used as the preset value.

[0160] Reference Figure 7 As shown, based on the relationship model between electricity consumption and price, calculating the first adjusted electricity price includes the following steps:

[0161] The potential increase in power consumption is divided by the real-time power consumption to obtain the actual ratio;

[0162] Substitute the actual proportion and electricity selling price into the supply and demand fitting function to obtain the first adjusted electricity price.

[0163] When making calculations, you need to know the proportion of electricity adjustment and the current price. The current price is the electricity selling price, and the actual proportion can be calculated in a manner consistent with the proportion formula.

[0164] Reference Figure 8 As shown, based on the first adjusted electricity price, adjusting the floating electricity price includes the following steps:

[0165] The first adjusted electricity price is added to the floating electricity price to obtain a first change value;

[0166] When the first change value belongs to the variable range, the floating electricity price is adjusted to the first change value; otherwise, the floating electricity price is adjusted to the maximum value in the variable range.

[0167] Here, the adjustment of the floating electricity price cannot exceed the variable range, otherwise it may cause excessive cost losses. The maximum value in the variable range is the value of the right endpoint of the variable range.

[0168] Reference Fig. 9 As shown, based on the relationship model between electricity consumption and price, calculating the second adjusted electricity price includes the following steps:

[0169] The real-time power generation is multiplied by the preset value to obtain the target power consumption;

[0170] The difference between the target power consumption and the real-time power consumption is divided by the real-time power consumption to obtain the target ratio;

[0171] Substitute the target ratio and electricity selling price into the supply and demand fitting function to obtain the second adjusted electricity price.

[0172] The target electricity consumption is the goal that the price adjustment hopes to achieve in real-time electricity consumption. According to the origin of the target electricity consumption, when the real-time electricity consumption becomes the target electricity consumption, the electricity resource load factor at this time is equal to the target electricity consumption divided by the real-time power generation, which is equal to the preset value and not greater than the preset value. Therefore, the load is normal.

[0173] When making calculations, you need to know the electricity adjustment ratio and the current price. The current price is the electricity selling price, and the target ratio can be calculated in a manner consistent with the ratio formula.

[0174] Reference Fig.10 As shown, based on the second adjusted electricity price, adjusting the floating electricity price includes the following steps:

[0175] The second adjusted electricity price is added to the floating electricity price to obtain a second change value;

[0176] When the second change value belongs to the variable range, the floating electricity price is adjusted to the second change value; otherwise, the floating electricity price is adjusted to the maximum value in the variable range.

[0177] Furthermore, the present solution also proposes a storage medium on which a computer-readable program is stored. When the computer-readable program is called, the above-mentioned power sales strategy optimization method based on market factors and resource allocation optimization is executed.

[0178] It is understandable that the storage medium may be a magnetic medium, such as a floppy disk, a hard disk, or a magnetic tape; an optical medium, such as a DVD; or a semiconductor medium, such as a solid state drive (SSD).

[0179] In summary, the advantages of the present invention are: by establishing a relationship model between electricity consumption and price, obtaining a potential electricity consumption model, judging the growth coefficient and the load coefficient of electricity resources and making corresponding adjustments to the electricity price based on this, the user's potential electricity consumption can be estimated, and then the electricity price can be reasonably adjusted to stimulate the user's potential electricity demand, thereby improving the user's electricity satisfaction. At the same time, the electricity load is also calculated, and the price is adjusted in time according to the electricity load situation, thereby avoiding line failures caused by excessive load.

[0180] The above shows and describes the basic principles, main features and advantages of the present invention. Those skilled in the art should understand that the present invention is not limited to the above embodiments. The above embodiments and descriptions only describe the principles of the present invention. The present invention may be subject to various changes and improvements without departing from the spirit and scope of the present invention. These changes and improvements fall within the scope of the present invention. The scope of protection claimed by the present invention is defined by the attached claims and their equivalents.

Claims

1. A method for optimizing electricity sales strategy based on market factors and resource allocation optimization, characterized in that: include: Obtaining the real-time power generation of the power plant and the real-time power consumption of at least one user, wherein the real-time power consumption is the total power consumption of all users within a time period less than a preset time from the current time; According to the supply and demand relationship of electricity, establish the relationship model between electricity consumption and price; The electricity price is divided into two parts: the basic electricity price and the floating electricity price. The basic electricity price is a fixed value, and the floating electricity price is a variable value. Based on historical data, the variable range of the floating electricity price is obtained. Analyze the potential power consumption capacity of the market and obtain the potential power consumption model; Calculate the potential increase in power consumption based on the power consumption potential model; Calculate the growth coefficient of potential improvement and form the critical value of the growth coefficient; Calculate the power resource load factor to form a preset value of the power resource load factor; When the growth coefficient is greater than the critical value, the electricity price reduction optimization is carried out; When optimizing the electricity price reduction, the first adjusted electricity price is calculated based on the relationship model between electricity consumption and price; adjusting the floating electricity price based on the first adjusted electricity price; When the load factor of electricity resources is greater than the preset value, the electricity price will be optimized; When optimizing the electricity price increase, the second adjusted electricity price is calculated based on the relationship model between electricity consumption and price; The floating electricity price is adjusted based on the second adjusted electricity price.

2. The method for optimizing power sales strategy based on market factors and resource allocation optimization according to claim 1, characterized in that: The establishment of a relationship model between electricity consumption and price according to the supply and demand relationship of electricity consumption includes the following steps: Obtain a value range of the electricity selling price, divide the value range of the real-time electricity consumption into equal intervals, and obtain at least one identification point; Obtain the value range of the power price regulation range, divide the value range of the power price regulation range into equal intervals (-k, k), and obtain at least one test point, where k is the maximum value of the power price regulation range in the historical data. If the electricity price is increased, the power price regulation range is positive, and if the electricity price is reduced, the power price regulation range is negative; Under the condition that the electricity selling price is equal to the value at the identification point, the first electricity consumption is obtained, and under the condition that the electricity selling price is equal to the sum of the value at the identification point and the value at the test point, the second electricity consumption is obtained; Using the proportional formula, calculate the change ratio of the first power consumption; Pairing the change ratio, the value at the identification point and the value at the test point, and fitting at least one set of the paired change ratio, the value at the identification point and the value at the test point to obtain a supply-demand fitting function, and using the supply-demand fitting function as a relationship model between electricity consumption and price, wherein the change ratio and the value at the identification point are independent variables, and the value at the test point is a dependent variable; The ratio formula is as follows: Among them, A is the change ratio, a is the second power consumption, and b is the first power consumption.

3. The method for optimizing electricity sales strategy based on market factors and resource allocation optimization according to claim 2, characterized in that: The analysis of the potential power consumption capacity of the market to obtain a potential power consumption model includes the following steps: Evenly divide the whole day time period to obtain at least one partition time period, and the length of the partition time period is equal to twice the preset time; Obtaining the income of at least one user, dividing the users according to their income, and obtaining at least one user set, wherein the income difference of users in the user set is less than a preset amount; Randomly select a user from the user set as a sample user; Acquire at least one power-consuming device used by the sample user; Based on big data, obtain the usage time of power-consuming devices; When the usage time of the power-consuming device overlaps with the partition time period, the power-consuming device is paired with the partition time period; Add the rated powers of the power consuming devices paired with the partition time periods to obtain the total rated power; The total rated power is multiplied by the length of the partition period to obtain the potential upper limit of power consumption of the sample user in the partition period; The potential power consumption upper limit of at least one sample user in at least one partition period is aggregated to obtain a potential power consumption model.

4. The method for optimizing power sales strategy based on market factors and resource allocation optimization according to claim 3 is characterized in that: The calculation of the potential increase in power consumption based on the power potential consumption model includes the following steps: Get the current actual time, and use the partition period where the current actual time is located as the target partition period; Using the comprehensive electricity formula, calculate the overall electricity consumption limit of at least one user; Subtract the real-time power consumption from the real-time power generation to obtain the power idle value; Subtract the real-time power consumption from the total power consumption limit to get the power potential value; The smaller value between the power idle value and the power potential value is used as the potential increase in power consumption; The comprehensive formula for electricity is as follows: Where B is the total power consumption limit, i is the subscript, n is the total number of at least one user set, c i is the potential upper limit of electricity consumption of the sample users in the i-th user set during the target partition period, d i is the number of elements in the i-th user set.

5. The method for optimizing power sales strategy based on market factors and resource allocation optimization according to claim 4, characterized in that: The step of calculating the growth coefficient of the potential improvement and forming a critical value of the growth coefficient comprises the following steps: Take at least one time point within one hour before the current time, and obtain the potential improvement at the time point as the feature potential improvement; Pair and fit the time points with the potential lift of the features to obtain the lift fitting function; Derivative the lifting fitting function to obtain the growth fitting function; Substitute the current time into the growth fitting function to obtain the growth coefficient of the potential improvement; Obtain at least one sample time, substitute the sample time into the growth fitting function, and obtain the sample growth coefficient; Using the minimum and maximum values ​​of at least one sample growth factor, a growth interval is formed; Uniformly select at least one growth point in the growth interval, and obtain the increase in electricity consumption when the power selling price changes by the preset price range under the condition that the potential increase is equal to the value at the growth point; When the increase in power consumption is greater than the preset power consumption, the growth point is taken as the target growth point; The minimum value of at least one target growth point is used as the critical value of the growth coefficient.

6. The method for optimizing electricity sales strategy based on market factors and resource allocation optimization according to claim 5, characterized in that: The step of calculating the power resource load factor and forming a preset value of the power resource load factor comprises the following steps: The real-time power consumption is divided by the real-time power generation to obtain the power resource load factor; Based on the historical data, obtaining at least one historical power resource load factor; Obtain the failure rate of transmission lines under the condition of historical power resource load factor; When the failure rate is greater than the preset ratio, the historical power resource load factor is used as the risk value; The minimum value of at least one risk value is used as a preset value of the power resource load factor.

7. The method for optimizing power selling strategy based on market factors and resource allocation optimization according to claim 6, characterized in that: The step of calculating the first adjusted electricity price based on the relationship model between electricity consumption and price comprises the following steps: The potential increase in power consumption is divided by the real-time power consumption to obtain the actual ratio; Substitute the actual proportion and electricity selling price into the supply and demand fitting function to obtain the first adjusted electricity price.

8. The method for optimizing power sales strategy based on market factors and resource allocation optimization according to claim 7, characterized in that: The adjusting of the floating electricity price based on the first adjusted electricity price comprises the following steps: The first adjusted electricity price is added to the floating electricity price to obtain a first change value; When the first change value belongs to the variable range, the floating electricity price is adjusted to the first change value; otherwise, the floating electricity price is adjusted to the maximum value in the variable range.

9. The method for optimizing power sales strategy based on market factors and resource allocation optimization according to claim 8, characterized in that: The calculation of the second adjusted electricity price based on the relationship model between electricity consumption and price comprises the following steps: The real-time power generation is multiplied by the preset value to obtain the target power consumption; The difference between the target power consumption and the real-time power consumption is divided by the real-time power consumption to obtain the target ratio; Substitute the target ratio and electricity selling price into the supply and demand fitting function to obtain the second adjusted electricity price.

10. The method for optimizing power selling strategy based on market factors and resource allocation optimization according to claim 9, characterized in that: The adjusting of the floating electricity price based on the second adjusted electricity price comprises the following steps: The second adjusted electricity price is added to the floating electricity price to obtain a second change value; When the second change value belongs to the variable range, the floating electricity price is adjusted to the second change value; otherwise, the floating electricity price is adjusted to the maximum value in the variable range.

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