New energy spot transaction price optimization method of full life cycle carbon emission

Abstract

The invention relates to the technical field of new energy transaction, and discloses a new energy spot transaction price optimization method for full life cycle carbon emission, which comprises the following steps: performing random cycle detection on carbon emission based on a carbon emission data detection cycle, and determining multiple carbon emission cycle detection data; determining a carbon emission fitting curve according to the carbon emission cycle detection data, performing curve segmentation, and calculating a first transaction price influence coefficient and a second transaction price influence coefficient; determining a carbon emission transaction price influence coefficient based on the first transaction price influence coefficient and the second transaction price influence coefficient; according to the method, the current new energy spot transaction price is obtained, the current new energy spot transaction price is optimized based on the carbon emission transaction price influence coefficient, the optimized energy spot transaction price is obtained, dynamic analysis of carbon emission can be realized, the more scientific and reasonable new energy spot transaction price is formulated, the goal of carbon emission reduction can be realized, and the energy consumption is reduced. And green development of the new energy industry can be promoted.

Description

Technical Field

[0001] The present invention relates to the field of new energy trading technology, and in particular to a method for optimizing the spot trading price of new energy with full life cycle carbon emissions. Background Art

[0002] New energy spot trading refers to the trading of electricity (electric energy) that is expected to be supplied to users by power plants that have been built and connected to the power grid and have the conditions for power generation in the electricity market. This trading method allows market participants to determine the trading price and quantity of electricity through centralized bidding or other trading methods based on real-time or short-term supply and demand conditions.

[0003] In the context of the current energy transformation and low-carbon economic development, the new energy spot trading market is developing rapidly. However, the existing new energy spot trading price optimization methods mainly rely on short-term supply and demand relationships and real-time data of the power market, ignoring the impact of carbon emissions throughout the life cycle. Although this method has promoted the consumption of new energy and the optimal scheduling of the power system to a certain extent, it has significant shortcomings in achieving carbon emission reduction goals. In addition, traditional power system optimization models usually only focus on the cost-effectiveness of power supply and fail to fully consider the impact of carbon emissions on the environment. Although some studies have attempted to take carbon emissions into consideration, most of them are still in the static evaluation stage and lack the ability to dynamically analyze and optimize carbon emissions throughout the life cycle. Summary of the invention

[0004] An embodiment of the present invention provides a method for optimizing the spot trading price of new energy with full life cycle carbon emissions, so as to solve the problem that the prior art lacks dynamic analysis and real-time optimization capabilities for full life cycle carbon emissions, resulting in a lack of rationality in the spot trading price of new energy, which is not conducive to achieving carbon emission reduction targets.

[0005] In order to achieve the above object, the present invention provides a method for optimizing the spot transaction price of new energy with full life cycle carbon emissions, comprising:

[0006] Preset multiple carbon emission data detection cycles, perform random periodic detection of carbon emissions based on the carbon emission data detection cycles, and determine multiple carbon emission periodic detection data;

[0007] Determine a carbon emission fitting curve according to the carbon emission cycle detection data, segment the carbon emission fitting curve, and calculate a first transaction price impact coefficient and a second transaction price impact coefficient based on the curve segmentation result;

[0008] Determine a first transaction price impact coefficient and a second transaction price impact coefficient corresponding to all carbon emission data detection periods, and determine a carbon emission transaction price impact coefficient based on the first transaction price impact coefficient and the second transaction price impact coefficient;

[0009] The current new energy spot transaction price is obtained, and the current new energy spot transaction price is optimized based on the carbon emission transaction price influence coefficient to obtain an optimized energy spot transaction price.

[0010] Furthermore, when the carbon emission fitting curve is segmented, and the first transaction price impact coefficient and the second transaction price impact coefficient are calculated based on the curve segmentation result, the method includes:

[0011] Calculate the carbon emission data mean of all carbon emission period detection data, and determine the data position point of the emission data mean on the carbon emission fitting curve;

[0012] Determine the carbon emission period detection data corresponding to the initial moment in the carbon emission data detection period, and use the curve segment between the carbon emission period detection data and the data position point as the first segmentation fitting curve;

[0013] Determine the carbon emission period detection data corresponding to the end time of the carbon emission data detection period, and use the curve segment between the carbon emission period detection data and the data position point as the second segmentation fitting curve;

[0014] Calculating a first transaction price impact coefficient corresponding to the carbon emission data detection period based on the first segmentation fitting curve;

[0015] A second transaction price impact coefficient corresponding to the carbon emission data detection period is calculated based on the second segmentation fitting curve.

[0016] Further, when calculating the first transaction price impact coefficient corresponding to the carbon emission data detection period based on the first segmentation fitting curve, it includes:

[0017] Randomly matching the carbon emission period detection data on the first segmentation fitting curve in pairs to obtain multiple carbon emission data sets;

[0018] Determine whether two carbon emission period detection data in the carbon emission data set are equal, and if so, delete the corresponding carbon emission data set;

[0019] Extract the remaining carbon emission data set, calculate the carbon emission data and value of the two carbon emission cycle detection data in the carbon emission data set, and select the maximum carbon emission data and value;

[0020] Determine a data variance of all carbon emission data and values, and generate a first carbon emission mark for all carbon emission data and values ​​greater than the data variance;

[0021] generating a second carbon emission mark for all carbon emission data and values ​​that are less than or equal to the data variance;

[0022] A first transaction price impact coefficient corresponding to the carbon emission data detection period is calculated according to the maximum carbon emission data and value, the first carbon emission mark and the second carbon emission mark.

[0023] Further, when calculating the first transaction price impact coefficient corresponding to the carbon emission data detection period according to the maximum carbon emission data and value, the first carbon emission mark and the second carbon emission mark, it includes:

[0024] The first transaction price impact coefficient corresponding to the carbon emission data detection period is calculated according to the following formula:

[0025]

[0026] Where q is the first transaction price impact coefficient corresponding to the carbon emission data detection period, e is the number of remaining carbon emission data sets, y1 is the first calculation coefficient, y2 is the second calculation coefficient, y1+y2=1, y1>y2, r i is the carbon emission data and value corresponding to the i-th carbon emission data set, r max is the maximum carbon emission data and value, t1 i is the first data moment corresponding to the carbon emission period detection data in the i-th carbon emission data set, t2 i is the second data moment corresponding to the carbon emission period detection data in the i-th carbon emission data set, w1 is the number of first carbon emission marks, and w2 is the number of second carbon emission marks.

[0027] Further, when calculating the second transaction price impact coefficient corresponding to the carbon emission data detection period based on the second segmentation fitting curve, it includes:

[0028] Extracting all carbon emission period detection data on the second segmentation fitting curve, and extracting the same carbon emission period detection data, to obtain multiple carbon emission period detection data sets;

[0029] Counting the first set number of carbon emission period detection data sets;

[0030] Extracting one carbon emission cycle detection data from all carbon emission cycle detection data sets respectively, and calculating the first carbon emission cycle detection data and value;

[0031] Acquire preset carbon emission cycle detection data, remove all carbon emission cycle detection data sets that are smaller than the preset carbon emission cycle detection data, and count the number of second sets of remaining carbon emission cycle detection data sets;

[0032] Extracting one carbon emission period detection data from the remaining carbon emission period detection data set respectively, and calculating the second carbon emission period detection data and value;

[0033] The second transaction price impact coefficient corresponding to the carbon emission data detection period is calculated according to the first set quantity, the second set quantity, the first carbon emission period detection data and value, and the second carbon emission period detection data and value.

[0034] Further, when calculating the second transaction price impact coefficient corresponding to the carbon emission data detection period according to the first set quantity, the second set quantity, the first carbon emission period detection data and value, and the second carbon emission period detection data and value, it includes:

[0035] The second transaction price impact coefficient corresponding to the carbon emission data detection period is calculated according to the following formula:

[0036]

[0037] Among them, u is the second transaction price impact coefficient corresponding to the carbon emission data detection period, s1 is the first set quantity, s2 is the second set quantity, d1=s1 / s1+s2, d2=s2 / s1+s2, f1 is the first carbon emission cycle detection data and value, f2 is the second carbon emission cycle detection data and value, g1=f1 / f1+f2, g2=f2 / f1+f2.

[0038] Furthermore, when determining the first transaction price impact coefficient and the second transaction price impact coefficient corresponding to all carbon emission data detection periods, and determining the carbon emission transaction price impact coefficient based on the first transaction price impact coefficient and the second transaction price impact coefficient, it includes:

[0039] The first transaction price impact coefficient is used as the horizontal coordinate, the second transaction price impact coefficient is used as the vertical coordinate, and all carbon emission data detection periods are mapped in the rectangular coordinate system;

[0040] Determine the transaction price impact coefficient curve based on the mapping results;

[0041] Select any carbon emission data detection period, and use the second transaction price impact coefficient of the selected carbon emission data detection period as the cluster center, determine the distance from the second transaction price impact coefficient of each remaining carbon emission data detection period to the cluster center, sort all distances from small to large, and extract the carbon emission data detection periods corresponding to the first h distances as processable carbon emission data detection periods;

[0042] Respectively connecting the processable carbon emission data detection period with the selected carbon emission data detection period to determine a plurality of connection lines;

[0043] Determine whether there is an intersection between the connection line and the transaction price impact coefficient curve, if not, remove the corresponding connection line;

[0044] If yes, the corresponding connecting line is retained, and the tangent line at the intersection of the connecting line and the transaction price impact coefficient curve is determined;

[0045] determining a cosine value between a tangent line and the connecting line;

[0046] Integrate all cosine values ​​and determine the carbon emission trading price impact coefficient based on all cosine values.

[0047] Furthermore, when integrating all cosine values ​​and determining the carbon emission trading price impact coefficient based on all cosine values, it includes:

[0048] Determine a first partitioned cosine value and a second partitioned cosine value, wherein the first partitioned cosine value is less than the second partitioned cosine value;

[0049] Generate a first cosine value set according to all cosine values ​​less than the first divided cosine value;

[0050] Generate a second cosine value set according to all cosine values ​​that are greater than or equal to the first partitioned cosine value and less than the second partitioned cosine value;

[0051] generating a third cosine value set according to all cosine values ​​greater than or equal to the second divided cosine value;

[0052] A carbon emission trading price impact coefficient is determined based on the first cosine value set, the second cosine value set and the third cosine value set.

[0053] Furthermore, when determining the carbon emission trading price impact coefficient based on the first cosine value set, the second cosine value set and the third cosine value set, it includes:

[0054] Calculate the carbon emission trading price impact coefficient according to the following formula:

[0055]

[0056] Among them, k is the carbon emission trading price impact coefficient, c1 is the number corresponding to the first cosine value set, c2 is the number corresponding to the second cosine value set, and c3 is the number corresponding to the third cosine value set.

[0057] Further, when optimizing the current new energy spot transaction price based on the carbon emission transaction price impact coefficient to obtain the optimized energy spot transaction price, it includes:

[0058] Setting a first preset carbon emission trading price impact coefficient and a second preset carbon emission trading price impact coefficient;

[0059] Setting a first price optimization coefficient, a second price optimization coefficient, and a third price optimization coefficient;

[0060] When the carbon emission trading price impact coefficient is less than the first preset carbon emission trading price impact coefficient, the product value of the first price optimization coefficient and the current new energy spot trading price is calculated and used as the optimized energy spot trading price;

[0061] When the carbon emission trading price impact coefficient is greater than or equal to the first preset carbon emission trading price impact coefficient, and less than the second preset carbon emission trading price impact coefficient, the product value of the second price optimization coefficient and the current new energy spot trading price is calculated and used as the optimized energy spot trading price;

[0062] When the carbon emission trading price impact coefficient is greater than or equal to the second preset carbon emission trading price impact coefficient, the product value of the third price optimization coefficient and the current new energy spot trading price is calculated and used as the optimized energy spot trading price.

[0063] Compared with the prior art, the present invention has the following beneficial effects:

[0064] The present invention discloses a method for optimizing the spot transaction price of new energy for full life cycle carbon emissions. The method comprises the following steps: performing random periodic detection on carbon emissions based on the carbon emission data detection period, and determining a plurality of carbon emission periodic detection data; determining a carbon emission fitting curve based on the carbon emission periodic detection data, performing curve segmentation, and calculating a first transaction price influence coefficient and a second transaction price influence coefficient; determining a carbon emission transaction price influence coefficient based on the first transaction price influence coefficient and the second transaction price influence coefficient; obtaining a current new energy spot transaction price, and optimizing the current new energy spot transaction price based on the carbon emission transaction price influence coefficient to obtain an optimized energy spot transaction price. The method can realize dynamic analysis of carbon emissions, thereby formulating a more scientific and reasonable new energy spot transaction price, which is helpful to achieve carbon emission reduction targets, and can also promote the green development of the new energy industry. BRIEF DESCRIPTION OF THE DRAWINGS

[0065] Various other advantages and benefits will become apparent to those of ordinary skill in the art by reading the detailed description of the preferred embodiments below. The accompanying drawings are only for the purpose of illustrating the preferred embodiments and are not to be considered as limiting the present invention. Moreover, the same reference symbols are used throughout the accompanying drawings to represent the same components. In the accompanying drawings:

[0066] Figure 1 A flow chart of a method for optimizing the spot transaction price of new energy for full life cycle carbon emissions in an embodiment of the present invention is shown. DETAILED DESCRIPTION

[0067] The specific implementation of the present invention is further described in detail below in conjunction with the accompanying drawings and examples. The following examples are used to illustrate the present invention, but are not intended to limit the scope of the present invention.

[0068] In the description of the present application, it should be understood that the terms "center", "up", "down", "front", "back", "left", "right", "vertical", "horizontal", "top", "bottom", "inside", "outside", etc., indicating orientations or positional relationships, are based on the orientations or positional relationships shown in the accompanying drawings, and are only for the convenience of describing the present application and simplifying the description, and do not indicate or imply that the device or element referred to must have a specific orientation, be constructed and operated in a specific orientation, and therefore should not be understood as a limitation on the present application.

[0069] The terms "first" and "second" are used for descriptive purposes only and should not be understood as indicating or implying relative importance or implicitly indicating the number of the indicated technical features. Thus, a feature defined as "first" or "second" may explicitly or implicitly include one or more of the features. In the description of this application, unless otherwise specified, "plurality" means two or more.

[0070] In the description of this application, it should be noted that, unless otherwise clearly specified and limited, the terms "installed", "connected", and "connected" should be understood in a broad sense, for example, it can be a fixed connection, a detachable connection, or an integral connection; it can be a mechanical connection or an electrical connection; it can be a direct connection, or it can be indirectly connected through an intermediate medium, or it can be the internal communication of two components. For ordinary technicians in this field, the specific meanings of the above terms in this application can be understood according to specific circumstances.

[0071] The following is a description of preferred embodiments of the present invention with reference to the accompanying drawings.

[0072] like Figure 1 As shown, an embodiment of the present invention discloses a method for optimizing the spot transaction price of new energy for full life cycle carbon emissions, including:

[0073] S110: Preset multiple carbon emission data detection cycles, perform random periodic detection on carbon emissions based on the carbon emission data detection cycles, and determine multiple carbon emission periodic detection data;

[0074] In this embodiment, if a carbon emission data detection cycle is constructed every 10 minutes, the carbon emission data detection cycle performs random periodic detection on carbon emissions, that is, carbon emission detection is performed in the first minute, carbon emission detection is performed in the third minute, and carbon emission detection is performed in the fifth minute. The carbon emission data detection cycle is preferably 8 here, and can be adjusted according to actual conditions. Multiple carbon emission cycle detection data are obtained in each carbon emission data detection cycle.

[0075] S120: determining a carbon emission fitting curve according to the carbon emission cycle detection data, performing curve segmentation on the carbon emission fitting curve, and calculating a first transaction price impact coefficient and a second transaction price impact coefficient based on the curve segmentation result;

[0076] In some embodiments of the present application, when the carbon emission fitting curve is segmented, and the first transaction price impact coefficient and the second transaction price impact coefficient are calculated based on the curve segmentation result, the method includes:

[0077] Calculate the carbon emission data mean of all carbon emission period detection data, and determine the data position point of the emission data mean on the carbon emission fitting curve;

[0078] Determine the carbon emission period detection data corresponding to the initial moment in the carbon emission data detection period, and use the curve segment between the carbon emission period detection data and the data position point as the first segmentation fitting curve;

[0079] Determine the carbon emission period detection data corresponding to the end time of the carbon emission data detection period, and use the curve segment between the carbon emission period detection data and the data position point as the second segmentation fitting curve;

[0080] Calculating a first transaction price impact coefficient corresponding to the carbon emission data detection period based on the first segmentation fitting curve;

[0081] A second transaction price impact coefficient corresponding to the carbon emission data detection period is calculated based on the second segmentation fitting curve.

[0082] In this embodiment, the mean carbon emission data may or may not exist on the carbon emission fitting curve. If the mean carbon emission data already exists, the existing mean carbon emission data will be determined to the first segmentation fitting curve. If it does not exist, the curve segment between the carbon emission period detection data and the data position point will be used as the first segmentation fitting curve, and the curve segment between the carbon emission period detection data and the data position point will be used as the second segmentation fitting curve.

[0083] The beneficial effect of the above technical solution is that the present invention can realize the accurate segmentation of the carbon emission fitting curve, laying a foundation for calculating the first transaction price impact coefficient and the second transaction price impact coefficient.

[0084] In some embodiments of the present application, when calculating the first transaction price impact coefficient corresponding to the carbon emission data detection period based on the first segmentation fitting curve, it includes:

[0085] Randomly matching the carbon emission period detection data on the first segmentation fitting curve in pairs to obtain multiple carbon emission data sets;

[0086] Determine whether two carbon emission period detection data in the carbon emission data set are equal, and if so, delete the corresponding carbon emission data set;

[0087] Extract the remaining carbon emission data set, calculate the carbon emission data and value of the two carbon emission cycle detection data in the carbon emission data set, and select the maximum carbon emission data and value;

[0088] Determine a data variance of all carbon emission data and values, and generate a first carbon emission mark for all carbon emission data and values ​​greater than the data variance;

[0089] generating a second carbon emission mark for all carbon emission data and values ​​that are less than or equal to the data variance;

[0090] A first transaction price impact coefficient corresponding to the carbon emission data detection period is calculated according to the maximum carbon emission data and value, the first carbon emission mark and the second carbon emission mark.

[0091] In this embodiment, the carbon emission data set includes two carbon emission period detection data, and the two carbon emission period detection data are summed to obtain a plurality of carbon emission data and values.

[0092] The beneficial effect of the above technical solution is: the present invention calculates the first transaction price impact coefficient corresponding to the carbon emission data detection period according to the maximum carbon emission data and value, the first carbon emission mark and the second carbon emission mark, which not only ensures the calculation accuracy of the first transaction price impact coefficient, but also lays the foundation for the optimization of the spot transaction price of new energy.

[0093] In some embodiments of the present application, when calculating the first transaction price impact coefficient corresponding to the carbon emission data detection period according to the maximum carbon emission data and value, the first carbon emission mark and the second carbon emission mark, it includes:

[0094] The first transaction price impact coefficient corresponding to the carbon emission data detection period is calculated according to the following formula:

[0095]

[0096] Where q is the first transaction price impact coefficient corresponding to the carbon emission data detection period, e is the number of remaining carbon emission data sets, y1 is the first calculation coefficient, y2 is the second calculation coefficient, y1+y2=1, y1>y2, r i is the carbon emission data and value corresponding to the i-th carbon emission data set, r max is the maximum carbon emission data and value, t1 i is the first data moment corresponding to the carbon emission period detection data in the i-th carbon emission data set, t2i is the second data moment corresponding to the carbon emission period detection data in the i-th carbon emission data set, w1 is the number of first carbon emission marks, and w2 is the number of second carbon emission marks.

[0097] In some embodiments of the present application, when calculating the second transaction price impact coefficient corresponding to the carbon emission data detection period based on the second segmentation fitting curve, it includes:

[0098] Extracting all carbon emission period detection data on the second segmentation fitting curve, and extracting the same carbon emission period detection data, to obtain multiple carbon emission period detection data sets;

[0099] Counting the first set number of carbon emission period detection data sets;

[0100] Extracting one carbon emission cycle detection data from all carbon emission cycle detection data sets respectively, and calculating the first carbon emission cycle detection data and value;

[0101] Acquire preset carbon emission cycle detection data, remove all carbon emission cycle detection data sets that are smaller than the preset carbon emission cycle detection data, and count the number of second sets of remaining carbon emission cycle detection data sets;

[0102] Extracting one carbon emission period detection data from the remaining carbon emission period detection data set respectively, and calculating the second carbon emission period detection data and value;

[0103] The second transaction price impact coefficient corresponding to the carbon emission data detection period is calculated according to the first set quantity, the second set quantity, the first carbon emission period detection data and value, and the second carbon emission period detection data and value.

[0104] In this embodiment, the carbon emission period detection data in the carbon emission period detection data set are all the same.

[0105] In this embodiment, the preset carbon emission period detection data is the variance of all carbon emission period detection data on the second segmentation fitting curve.

[0106] The beneficial effect of the above technical solution is: the present invention calculates the second transaction price impact coefficient corresponding to the carbon emission data detection period according to the first set quantity, the second set quantity, the first carbon emission cycle detection data and value, and the second carbon emission cycle detection data and value, and also provides a basis for optimizing the spot transaction price of new energy, ensuring the accuracy of price optimization and avoiding errors.

[0107] In some embodiments of the present application, when calculating the second transaction price impact coefficient corresponding to the carbon emission data detection period according to the first set quantity, the second set quantity, the first carbon emission period detection data and value, and the second carbon emission period detection data and value, it includes:

[0108] The second transaction price impact coefficient corresponding to the carbon emission data detection period is calculated according to the following formula:

[0109]

[0110] Among them, u is the second transaction price impact coefficient corresponding to the carbon emission data detection period, s1 is the first set quantity, s2 is the second set quantity, d1=s1 / s1+s2, d2=s2 / s1+s2, f1 is the first carbon emission cycle detection data and value, f2 is the second carbon emission cycle detection data and value, g1=f1 / f1+f2, g2=f2 / f1+f2.

[0111] S130: Determine a first transaction price impact coefficient and a second transaction price impact coefficient corresponding to all carbon emission data detection periods, and determine a carbon emission transaction price impact coefficient based on the first transaction price impact coefficient and the second transaction price impact coefficient;

[0112] In this embodiment, each carbon emission data detection period corresponds to a first transaction price impact coefficient and a second transaction price impact coefficient.

[0113] In some embodiments of the present application, when determining the first transaction price impact coefficient and the second transaction price impact coefficient corresponding to all carbon emission data detection periods, and determining the carbon emission transaction price impact coefficient based on the first transaction price impact coefficient and the second transaction price impact coefficient, it includes:

[0114] The first transaction price impact coefficient is used as the horizontal coordinate, the second transaction price impact coefficient is used as the vertical coordinate, and all carbon emission data detection periods are mapped in the rectangular coordinate system;

[0115] Determine the transaction price impact coefficient curve based on the mapping results;

[0116] Select any carbon emission data detection period, and use the second transaction price impact coefficient of the selected carbon emission data detection period as the cluster center, determine the distance from the second transaction price impact coefficient of each remaining carbon emission data detection period to the cluster center, sort all distances from small to large, and extract the carbon emission data detection periods corresponding to the first h distances as processable carbon emission data detection periods;

[0117] Respectively connecting the processable carbon emission data detection period with the selected carbon emission data detection period to determine a plurality of connection lines;

[0118] Determine whether there is an intersection between the connection line and the transaction price impact coefficient curve, if not, remove the corresponding connection line;

[0119] If yes, the corresponding connecting line is retained, and the tangent line at the intersection of the connecting line and the transaction price impact coefficient curve is determined;

[0120] determining a cosine value between a tangent line and the connecting line;

[0121] Integrate all cosine values ​​and determine the carbon emission trading price impact coefficient based on all cosine values.

[0122] In this embodiment, the determination of the clustering distance will not be further described here.

[0123] In this embodiment, h is 4, and can be adjusted according to actual conditions.

[0124] In this example, tangent: The tangent of a given curve at a point is the line that is tangent to the curve at that point. Cosine: In a triangle, the law of cosines can be used to find the relationship between any two sides and their angle. For two lines (here, the tangent and the connecting line), we determine the cosine of the angle θ between the tangent and the connecting line.

[0125] In this embodiment, the cosine value corresponding to the remaining carbon emission data detection period is determined according to the above method.

[0126] In some embodiments of the present application, when integrating all cosine values ​​and determining the carbon emission trading price impact coefficient according to all cosine values, it includes:

[0127] Determine a first partitioned cosine value and a second partitioned cosine value, wherein the first partitioned cosine value is less than the second partitioned cosine value;

[0128] Generate a first cosine value set according to all cosine values ​​less than the first divided cosine value;

[0129] Generate a second cosine value set according to all cosine values ​​that are greater than or equal to the first partitioned cosine value and less than the second partitioned cosine value;

[0130] generating a third cosine value set according to all cosine values ​​greater than or equal to the second divided cosine value;

[0131] A carbon emission trading price impact coefficient is determined based on the first cosine value set, the second cosine value set and the third cosine value set.

[0132] The beneficial effect of the above technical solution is: the present invention calculates the cosine value corresponding to each carbon emission data detection period, which can provide a premise for calculating the carbon emission trading price impact coefficient, and determines the carbon emission trading price impact coefficient based on the first cosine value set, the second cosine value set and the third cosine value set, thereby ensuring the calculation accuracy of the carbon emission trading price impact coefficient and further ensuring the optimization accuracy of the new energy spot trading price.

[0133] In some embodiments of the present application, when determining the carbon emission trading price impact coefficient based on the first cosine value set, the second cosine value set and the third cosine value set, it includes:

[0134] Calculate the carbon emission trading price impact coefficient according to the following formula:

[0135]

[0136] Among them, k is the carbon emission trading price impact coefficient, c1 is the number corresponding to the first cosine value set, c2 is the number corresponding to the second cosine value set, and c3 is the number corresponding to the third cosine value set.

[0137] S140: Obtain the current new energy spot transaction price, and optimize the current new energy spot transaction price based on the carbon emission transaction price impact coefficient to obtain an optimized energy spot transaction price.

[0138] In some embodiments of the present application, when optimizing the current new energy spot transaction price based on the carbon emission transaction price impact coefficient to obtain the optimized energy spot transaction price, it includes:

[0139] Setting a first preset carbon emission trading price impact coefficient and a second preset carbon emission trading price impact coefficient;

[0140] Setting a first price optimization coefficient, a second price optimization coefficient, and a third price optimization coefficient;

[0141] When the carbon emission trading price impact coefficient is less than the first preset carbon emission trading price impact coefficient, the product value of the first price optimization coefficient and the current new energy spot trading price is calculated and used as the optimized energy spot trading price;

[0142] When the carbon emission trading price impact coefficient is greater than or equal to the first preset carbon emission trading price impact coefficient, and less than the second preset carbon emission trading price impact coefficient, the product value of the second price optimization coefficient and the current new energy spot trading price is calculated and used as the optimized energy spot trading price;

[0143] When the carbon emission trading price impact coefficient is greater than or equal to the second preset carbon emission trading price impact coefficient, the product value of the third price optimization coefficient and the current new energy spot trading price is calculated and used as the optimized energy spot trading price.

[0144] In this embodiment, the first preset carbon emission trading price impact coefficient is preferably 4, and the second preset carbon emission trading price impact coefficient is preferably 8.

[0145] In this embodiment, the first price optimization coefficient is preferably 0.85, the second price optimization coefficient is preferably 1.15, and the third price optimization coefficient is preferably 1.25.

[0146] The beneficial effect of the above technical solution is: the present invention selects a price optimization coefficient according to the carbon emission trading price impact coefficient, the first preset carbon emission trading price impact coefficient and the second preset carbon emission trading price impact coefficient, and optimizes the current new energy spot trading price, which not only ensures the optimization intelligence, but also can formulate a more scientific and reasonable new energy spot trading price, which is helpful to achieve carbon emission reduction goals and promote the green development of the new energy industry.

[0147] In the description of the above embodiments, specific features, structures, materials or characteristics may be combined in a suitable manner in any one or more embodiments or examples.

[0148] Although the present invention has been described above with reference to the embodiments, various modifications may be made thereto and parts thereof may be replaced with equivalents without departing from the scope of the present invention. In particular, as long as there is no structural conflict, the various features in the embodiments disclosed by the present invention may be used in combination with each other in any manner, and the fact that these combinations are not fully described in this specification is only for the sake of omitting space and saving resources.

[0149] Those skilled in the art can understand that the above are only preferred embodiments of the present invention and are not intended to limit the present invention. Although the present invention has been described in detail with reference to the aforementioned embodiments, those skilled in the art can still modify the technical solutions recorded in the aforementioned embodiments or replace some of the technical features therein by equivalents. Any modification, equivalent replacement, improvement, etc. made within the spirit and principle of the present invention shall be included in the protection scope of the present invention.

Claims

1. A method for optimizing the spot transaction price of new energy with full life cycle carbon emissions, characterized in that: include: Preset multiple carbon emission data detection cycles, perform random periodic detection of carbon emissions based on the carbon emission data detection cycles, and determine multiple carbon emission periodic detection data; Determine a carbon emission fitting curve according to the carbon emission cycle detection data, segment the carbon emission fitting curve, and calculate a first transaction price impact coefficient and a second transaction price impact coefficient based on the curve segmentation result; Determine a first transaction price impact coefficient and a second transaction price impact coefficient corresponding to all carbon emission data detection periods, and determine a carbon emission transaction price impact coefficient based on the first transaction price impact coefficient and the second transaction price impact coefficient; The current new energy spot transaction price is obtained, and the current new energy spot transaction price is optimized based on the carbon emission transaction price influence coefficient to obtain an optimized energy spot transaction price.

2. The method for optimizing the spot transaction price of new energy for full life cycle carbon emissions according to claim 1 is characterized in that: When the carbon emission fitting curve is segmented, and the first transaction price impact coefficient and the second transaction price impact coefficient are calculated based on the curve segmentation result, the following steps are included: Calculate the carbon emission data mean of all carbon emission period detection data, and determine the data position point of the emission data mean on the carbon emission fitting curve; Determine the carbon emission period detection data corresponding to the initial moment in the carbon emission data detection period, and use the curve segment between the carbon emission period detection data and the data position point as the first segmentation fitting curve; Determine the carbon emission period detection data corresponding to the end time of the carbon emission data detection period, and use the curve segment between the carbon emission period detection data and the data position point as the second segmentation fitting curve; Calculating a first transaction price impact coefficient corresponding to the carbon emission data detection period based on the first segmentation fitting curve; A second transaction price impact coefficient corresponding to the carbon emission data detection period is calculated based on the second segmentation fitting curve.

3. The method for optimizing the spot transaction price of new energy for full life cycle carbon emissions according to claim 2 is characterized in that: When calculating the first transaction price impact coefficient corresponding to the carbon emission data detection period based on the first segmentation fitting curve, it includes: Randomly matching the carbon emission period detection data on the first segmentation fitting curve in pairs to obtain multiple carbon emission data sets; Determine whether two carbon emission period detection data in the carbon emission data set are equal, and if so, delete the corresponding carbon emission data set; Extract the remaining carbon emission data set, calculate the carbon emission data and value of the two carbon emission cycle detection data in the carbon emission data set, and select the maximum carbon emission data and value; Determine a data variance of all carbon emission data and values, and generate a first carbon emission mark for all carbon emission data and values ​​greater than the data variance; generating a second carbon emission mark for all carbon emission data and values ​​that are less than or equal to the data variance; A first transaction price impact coefficient corresponding to the carbon emission data detection period is calculated according to the maximum carbon emission data and value, the first carbon emission mark and the second carbon emission mark.

4. The method for optimizing the spot transaction price of new energy for full life cycle carbon emissions according to claim 3 is characterized in that: When calculating the first transaction price impact coefficient corresponding to the carbon emission data detection period according to the maximum carbon emission data and value, the first carbon emission mark and the second carbon emission mark, it includes: The first transaction price impact coefficient corresponding to the carbon emission data detection period is calculated according to the following formula: Where q is the first transaction price impact coefficient corresponding to the carbon emission data detection period, e is the number of remaining carbon emission data sets, y1 is the first calculation coefficient, y2 is the second calculation coefficient, y1+y2=1, y1>y2, r i is the carbon emission data and value corresponding to the i-th carbon emission data set, r max is the maximum carbon emission data and value, t1 i is the first data moment corresponding to the carbon emission period detection data in the i-th carbon emission data set, t2 i is the second data moment corresponding to the carbon emission period detection data in the i-th carbon emission data set, w1 is the number of first carbon emission marks, and w2 is the number of second carbon emission marks.

5. The method for optimizing the spot transaction price of new energy for full life cycle carbon emissions according to claim 4 is characterized in that: When calculating the second transaction price impact coefficient corresponding to the carbon emission data detection period based on the second segmentation fitting curve, it includes: Extracting all carbon emission period detection data on the second segmentation fitting curve, and extracting the same carbon emission period detection data, to obtain multiple carbon emission period detection data sets; Counting the first set number of carbon emission period detection data sets; Extracting one carbon emission cycle detection data from all carbon emission cycle detection data sets respectively, and calculating the first carbon emission cycle detection data and value; Acquire preset carbon emission cycle detection data, remove all carbon emission cycle detection data sets that are smaller than the preset carbon emission cycle detection data, and count the number of second sets of remaining carbon emission cycle detection data sets; Extracting one carbon emission period detection data from the remaining carbon emission period detection data set respectively, and calculating the second carbon emission period detection data and value; The second transaction price impact coefficient corresponding to the carbon emission data detection period is calculated according to the first set quantity, the second set quantity, the first carbon emission period detection data and value, and the second carbon emission period detection data and value.

6. The method for optimizing the spot transaction price of new energy for full life cycle carbon emissions according to claim 5 is characterized in that: When calculating the second transaction price impact coefficient corresponding to the carbon emission data detection period according to the first set quantity, the second set quantity, the first carbon emission period detection data and value, and the second carbon emission period detection data and value, it includes: The second transaction price impact coefficient corresponding to the carbon emission data detection period is calculated according to the following formula: Among them, u is the second transaction price impact coefficient corresponding to the carbon emission data detection period, s1 is the first set quantity, s2 is the second set quantity, d1=s1 / s1+s2, d2=s2 / s1+s2, f1 is the first carbon emission cycle detection data and value, f2 is the second carbon emission cycle detection data and value, g1=f1 / f1+f2, g2=f2 / f1+f2.

7. The method for optimizing the spot transaction price of new energy for full life cycle carbon emissions according to claim 1 is characterized in that: When determining the first transaction price impact coefficient and the second transaction price impact coefficient corresponding to all carbon emission data detection periods, and determining the carbon emission transaction price impact coefficient based on the first transaction price impact coefficient and the second transaction price impact coefficient, it includes: The first transaction price impact coefficient is used as the horizontal coordinate, the second transaction price impact coefficient is used as the vertical coordinate, and all carbon emission data detection periods are mapped in the rectangular coordinate system; Determine the transaction price impact coefficient curve based on the mapping results; Select any carbon emission data detection period, and use the second transaction price impact coefficient of the selected carbon emission data detection period as the cluster center, determine the distance from the second transaction price impact coefficient of each remaining carbon emission data detection period to the cluster center, sort all distances from small to large, and extract the carbon emission data detection periods corresponding to the first h distances as processable carbon emission data detection periods; Respectively connecting the processable carbon emission data detection period with the selected carbon emission data detection period to determine a plurality of connection lines; Determine whether there is an intersection between the connection line and the transaction price impact coefficient curve, if not, remove the corresponding connection line; If yes, the corresponding connecting line is retained, and the tangent line at the intersection of the connecting line and the transaction price impact coefficient curve is determined; determining a cosine value between a tangent line and the connecting line; Integrate all cosine values ​​and determine the carbon emission trading price impact coefficient based on all cosine values.

8. The method for optimizing the spot transaction price of new energy for full life cycle carbon emissions according to claim 7 is characterized in that: When integrating all cosine values ​​and determining the carbon emission trading price impact coefficient based on all cosine values, it includes: Determine a first partitioned cosine value and a second partitioned cosine value, wherein the first partitioned cosine value is less than the second partitioned cosine value; Generate a first cosine value set according to all cosine values ​​less than the first divided cosine value; Generate a second cosine value set according to all cosine values ​​that are greater than or equal to the first partitioned cosine value and less than the second partitioned cosine value; generating a third cosine value set according to all cosine values ​​greater than or equal to the second divided cosine value; A carbon emission trading price impact coefficient is determined based on the first cosine value set, the second cosine value set and the third cosine value set.

9. The method for optimizing the spot transaction price of new energy for full life cycle carbon emissions according to claim 8 is characterized in that: When determining the carbon emission trading price impact coefficient based on the first cosine value set, the second cosine value set and the third cosine value set, it includes: Calculate the carbon emission trading price impact coefficient according to the following formula: Among them, k is the carbon emission trading price impact coefficient, c1 is the number corresponding to the first cosine value set, c2 is the number corresponding to the second cosine value set, and c3 is the number corresponding to the third cosine value set.

10. The method for optimizing the spot transaction price of new energy for full life cycle carbon emissions according to claim 1 is characterized in that: When the current new energy spot transaction price is optimized based on the carbon emission transaction price impact coefficient to obtain the optimized energy spot transaction price, it includes: Setting a first preset carbon emission trading price impact coefficient and a second preset carbon emission trading price impact coefficient; Setting a first price optimization coefficient, a second price optimization coefficient, and a third price optimization coefficient; When the carbon emission trading price impact coefficient is less than the first preset carbon emission trading price impact coefficient, the product value of the first price optimization coefficient and the current new energy spot trading price is calculated and used as the optimized energy spot trading price; When the carbon emission trading price impact coefficient is greater than or equal to the first preset carbon emission trading price impact coefficient, and less than the second preset carbon emission trading price impact coefficient, the product value of the second price optimization coefficient and the current new energy spot trading price is calculated and used as the optimized energy spot trading price; When the carbon emission trading price impact coefficient is greater than or equal to the second preset carbon emission trading price impact coefficient, the product value of the third price optimization coefficient and the current new energy spot trading price is calculated and used as the optimized energy spot trading price.

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