Electric power transaction method and system of long-distance transmission pipe network based on energy storage device

Abstract

The invention provides a power transaction method and system for a long-distance transmission pipe network based on an energy storage device, and belongs to the technical field of long-distance transmission pipe networks, and the method specifically comprises the steps: obtaining the distribution data of reliable adjustment dates in a future preset time period, and combining the adjustment reliable demand coefficients of different reliable adjustment dates, when it is determined that the demand reliability degree of electric energy supply in the future preset time period meets the requirement, power utilization data of electric equipment of the long-distance transmission pipe network at different dates are obtained, and a power transaction processing strategy at the current date is determined according to the power utilization data, the residual electric energy of the energy storage device and the demand reliability degree; therefore, on the basis of ensuring the power utilization reliability of the power utilization equipment, the power utilization cost is reduced.

Description

Technical Field

[0001] The present invention belongs to the technical field of long-distance pipeline networks, and particularly relates to a power trading method and system for a long-distance pipeline network based on an energy storage device. Background Art

[0002] A long-distance pipeline network is used to transport remote heat sources at the edge of a city to heat users in the city. On the basis of meeting the heat demand of the city, it also further reduces environmental pollution in the city. However, at the same time, various types of water pumps and electric regulating valves are often installed in the long-distance pipeline network. Therefore, how to use an energy storage device to reduce the electricity consumption cost of the electrical equipment in the long-distance pipeline network has become a technical problem to be solved urgently.

[0003] In view of the above technical problems, specifically, the present application provides a power trading method and system for a long-distance pipeline network based on an energy storage device. Summary of the Invention

[0004] To achieve the purpose of the present invention, the present invention adopts the following technical solutions: In a first aspect, the present application provides a power trading method for a long-distance pipeline network based on an energy storage device, specifically including: S1 Analyze the weather data of different dates within a preset future time period to determine the change situation of the electricity price quotation data of similar historical dates corresponding to different dates. When it is determined that there are historical electricity prices that meet the requirements for a certain date, proceed to the next step; S2 Based on the historical adjustment data of the long-distance pipeline network corresponding to similar historical dates of different dates, determine the change situation of the adjustment instructions of the electrical equipment of the long-distance pipeline network corresponding to the similar historical dates of the dates, and combine the historical adjustment data of the electrical equipment of the long-distance pipeline network corresponding to the similar historical dates to determine the adjustment reliability demand coefficient and the reliable adjustment date for different dates; S3 Obtain the distribution data of reliable adjustment dates within a preset future time period, and combine the adjustment reliability demand coefficients of different reliable adjustment dates. When the demand reliability degree of the electric energy supply within the preset future time period meets the requirements, proceed to the next step; S4 Obtain the electricity consumption data of the electrical equipment of the long-distance pipeline network for different dates, and determine the power trading processing strategy for the current date based on the electricity consumption data, the remaining electric energy of the energy storage device, and the demand reliability degree.

[0005] The beneficial effects of the present invention are as follows: Based on the distribution data of reliable adjustment dates within a preset future period and the adjustment reliability demand coefficients for different reliable adjustment dates, determine whether the demand reliability degree of power supply within the preset future period meets the requirements, fully considering the reliability demand degree of power supply in the long-distance transmission pipeline network within the preset future period, avoiding the technical problem of excessive electricity costs caused by the remaining power of the energy storage device being unable to meet the electricity demand of the electrical equipment in the long-distance transmission pipeline network, and at the same time improving the energy supply reliability of the long-distance transmission pipeline network.

[0006] Determine the power trading processing strategy for the current date based on electricity consumption data, the remaining power of the energy storage device, and the demand reliability degree. This not only considers the deviation between the remaining power of the energy storage device and the electricity consumption data within the preset future period, but also takes into account the reliability degree of the demand for power supply within the preset future period, achieving the determination of the power trading processing strategy for the current date from multiple dimensions, further ensuring the energy supply reliability of the electrical equipment in the long-distance transmission pipeline network, and at the same time further reducing the electricity cost.

[0007] A further technical solution is that before determining the date when the historical power price meets the requirements, it is also necessary to determine whether there is a period on the current date when the trading electricity price is within the preset electricity price range. When there is a period when the trading electricity price is within the preset electricity price range, the power trading is processed using the period with the lowest price quotation of the energy storage device on the current date.

[0008] A further technical solution is that the preset period is determined according to the energy storage capacity of the energy storage device, where the larger the energy storage capacity of the energy storage device, the longer the preset period.

[0009] A further technical solution is that the similar historical date is a historical date with a deviation amount of weather data from the date within a preset deviation range.

[0010] A further technical solution is that the change situation of the power price quotation data includes the change amount of the power price quotation in the corresponding period on different similar historical dates.

[0011] A further technical solution is that the method for determining the date when the historical power price meets the requirements is as follows: Based on the change situation, determine the change amount of the power price quotation in different periods of different similar historical dates of the date, and use the change amount to determine the stable quotation period in the period; Based on the power price quotations of different similar historical dates in the stable quotation period, determine the proportion of the number of similar historical dates with a power price lower than the preset electricity price in different stable quotation periods, and use the proportion to determine the low electricity price proportion of different stable quotation periods; Determine whether the date is a date that meets the requirements of historical electricity quotes according to the proportion of low electricity prices during different stable quote periods.

[0012] A further technical solution is that the stable quote period is a period during which the change amounts of electricity quotes on different similar historical dates are all within a preset change amount range.

[0013] A further technical solution is to determine that the demand reliability degree of power supply within a preset future period meets the requirements, specifically including: Based on the distribution data of reliable regulation dates within a preset future period, determine the proportion of the number of reliable regulation dates within a preset future period and use it as the proportion of the number of reliable dates; Based on the regulation reliability demand coefficients of different reliable regulation dates, determine the average value of the regulation reliability demand coefficients of different reliable regulation dates and use it as the average reliability coefficient; Determine the demand reliability degree of power supply within a preset future period through the product of the average reliability coefficient and the proportion of the number of reliable dates, and combine it with a preset reliability degree threshold to determine whether the demand reliability degree meets the requirements.

[0014] A further technical solution is that when the demand reliability degree of power supply within a preset future period is less than the preset reliability degree threshold, it is determined that the demand reliability degree does not meet the requirements.

[0015] A further technical solution is that when the demand reliability degree does not meet the requirements, use the energy storage device to conduct power trading processing during the period with the lowest quote on the current date.

[0016] A further technical solution is that the electricity consumption data of the power consumption equipment of the long-distance transmission pipeline network on different dates is determined according to the average value of the historical electricity consumption of the power consumption equipment of the long-distance transmission pipeline network on the historical similar dates corresponding to different dates.

[0017] A further technical solution is that the method for determining the power trading processing strategy on the current date is: Based on the electricity consumption data of the power consumption equipment of the long-distance transmission pipeline network on different dates, determine the total electricity consumption of the power consumption equipment of the long-distance transmission pipeline network on different dates; Determine the energy storage electricity ratio based on the ratio of the remaining electric energy of the energy storage device to the total electricity consumption; Determine the trading demand coefficient on the current date based on the energy storage electricity ratio and the demand reliability degree, and use the trading demand coefficient to determine the power trading processing strategy on the current date.

[0018] A further technical solution is that using the trading demand coefficient to determine the power trading processing strategy on the current date specifically includes: When the transaction demand coefficient is greater than a preset demand coefficient threshold, power trading processing is performed using the energy storage device during the period with the lowest quotation on the current date; When the transaction demand coefficient is not greater than the preset demand coefficient threshold, there is no need to perform power trading processing using the energy storage device on the current date.

[0019] On the other hand, an embodiment of the present application provides a computer system on which a computer program is stored. When the computer program is executed on a computer, the computer is made to execute the above-mentioned power trading method for a long-distance pipeline network based on an energy storage device.

[0020] On the other hand, an embodiment of the present application provides a computer program product, characterized in that the computer program product stores instructions, and when the instructions are executed by a computer, the computer is made to implement the above-mentioned power trading method for a long-distance pipeline network based on an energy storage device. Description of the Drawings

[0021] By referring to the accompanying drawings and describing its exemplary embodiments in detail, the above and other features and advantages of the present invention will become more apparent.

[0022] Figure 1 is a flowchart of a power trading method for a long-distance pipeline network based on an energy storage device according to Embodiment 1.

[0023] Figure 2 is a flowchart of a method for determining a date when historical power quotations meet requirements.

[0024] Figure 3 is a flowchart of a method for determining a power trading processing strategy for the current date. Detailed Embodiments

[0025] Example embodiments will now be described more fully with reference to the accompanying drawings. However, the example embodiments can be implemented in various ways and should not be construed as limited to the embodiments set forth herein; rather, these embodiments are provided so that this invention will be thorough and complete, and will fully convey the concept of the example embodiments to those skilled in the art. Like reference numerals in the figures denote the same or similar structures, and thus their detailed descriptions will be omitted.

[0026] The terms "a", "an", "the", and "said" are used to denote the presence of one or more elements / components / etc.; the terms "comprising" and "having" are used to denote an open inclusion meaning and mean that in addition to the listed elements / components / etc., there may be additional elements / components / etc.

[0027] Embodiment 1 To solve the above problems, according to one aspect of the present invention, as Figure 1 shown, a first aspect is provided. The present application provides a power trading method for a long-distance pipeline network based on an energy storage device, specifically including: S1 Analyze the weather data of different dates within a future preset time period to determine the change situation of the electricity price quotation data of similar historical dates corresponding to different dates. When it is determined that there is a historical electricity price quotation that meets the requirements for a certain date, proceed to the next step; Furthermore, before determining that there is a historical electricity price quotation that meets the requirements for a certain date, it is also necessary to determine whether there is a time period during which the transaction electricity price is within a preset electricity price range on the current date. When there is a time period during which the transaction electricity price is within the preset electricity price range, the energy storage device is used to perform power trading processing during the time period with the lowest quotation on the current date.

[0028] Specifically, the preset time period is determined according to the energy storage capacity of the energy storage device. The larger the energy storage capacity of the energy storage device, the longer the preset time period.

[0029] It should be noted that the similar historical date is a historical date whose deviation from the weather data of the date is within a preset deviation range.

[0030] It can be understood that the change situation of the electricity price quotation data includes the change amount of the electricity price quotation in the corresponding time periods of different similar historical dates.

[0031] Specifically, as Figure 2 shown, the method for determining the date with a historical electricity price quotation that meets the requirements is as follows: Based on the change situation, determine the change amount of the electricity price quotation of different similar historical dates of the date in different time periods, and use the change amount to determine the stable quotation time period in the time period; Based on the electricity price quotations of different similar historical dates during the stable quotation time period, determine the proportion of the number of similar historical dates with electricity price quotations lower than the preset electricity price in different stable quotation time periods, and use the proportion to determine the low electricity price proportion of different stable quotation time periods; Determine whether the date is a date with a historical electricity price quotation that meets the requirements according to the low electricity price proportion of different stable quotation time periods.

[0032] Furthermore, the stable quotation time period is a time period during which the change amounts of the electricity price quotations of different similar historical dates are all within a preset change amount range.

[0033] It should be noted that when there is a stable quotation time period on the date with a low electricity price proportion greater than the preset date proportion, it is determined that the date is a date with a historical electricity price quotation that meets the requirements.

[0034] It is understandable that when there is no date with historical electricity quotes meeting the requirements, electricity trading is processed during the period with the lowest quote of the energy storage device on the current date.

[0035] In another possible embodiment, the method for determining the date when the historical electricity quotes meet the requirements is as follows: Obtain the electricity quote data of similar historical dates for the date. When there is no period with an electricity quote lower than the preset electricity price for different similar historical dates, it is determined that the date does not belong to the date when the historical electricity quotes meet the requirements; When there are similar historical dates with periods having electricity quotes lower than the preset electricity price: Obtain the proportion of the number of similar historical dates with periods having electricity quotes lower than the preset electricity price. When the proportion of the number of similar historical dates with periods having electricity quotes lower than the preset electricity price is less than the preset proportion threshold, it is determined that the date does not belong to the date when the historical electricity quotes meet the requirements; When the proportion of the number of similar historical dates with periods having electricity quotes lower than the preset electricity price is not less than the preset proportion threshold, obtain the proportion of the number of similar historical dates with periods having electricity quotes lower than the preset electricity price in different periods. When there is no period where the proportion of the number of similar historical dates with periods having electricity quotes lower than the preset electricity price meets the requirements, it is determined that the date does not belong to the date when the historical electricity quotes meet the requirements; When there is a period where the proportion of the number of similar historical dates with periods having electricity quotes lower than the preset electricity price meets the requirements: Based on the change situation, determine the change amount of the electricity quotes of different similar historical dates of the date in different periods, and use the change amount to determine that there is no stable quote period in the period, then it is determined that the date does not belong to the date when the historical electricity quotes meet the requirements; When there is a stable quote period in the period: Based on the electricity quotes of different similar historical dates in the stable quote period, determine the proportion of the number of similar historical dates with electricity quotes lower than the preset electricity price in different stable quote periods, and use the proportion to determine the low electricity price proportion of different stable quote periods; Determine whether the date is a date when the historical electricity quotes meet the requirements according to the low electricity price proportion of different stable quote periods.

[0036] S2 Based on the historical adjustment data of the long-distance pipeline network corresponding to different dates for similar historical dates, determine the change situation of the adjustment instructions of the electrical equipment of the long-distance pipeline network corresponding to the similar historical dates of the date, and combine the historical adjustment data of the electrical equipment of the long-distance pipeline network of the similar historical dates to determine the adjustment reliability demand coefficient and the reliable adjustment date for different dates; Furthermore, the historical regulation data of the long-distance pipeline network includes the number of adjustments and the duration of the adjustments of the electrical equipment in the long-distance pipeline network on different similar historical dates.

[0037] It should be noted that the change of the adjustment instruction of the electric device is determined according to the change of the number of adjustments of the electric device and the adjustment usage time on different similar historical dates.

[0038] Specifically, the method for determining the adjustment reliability demand coefficient of the date is: Using similar historical dates corresponding to the date as matching historical dates, determining the number of adjustments of the long-distance pipeline network's electrical equipment on different matching historical dates and the duration of adjustments for different adjustment times based on historical adjustment data of the electrical equipment on the long-distance pipeline network on different matching historical dates, and determining frequently used electrical equipment among the electrical equipment using the number of adjustments and the duration of adjustments for different adjustment times; Determining adjustment-changed devices among the electric devices based on changes in the number of adjustments of electric devices in the long-distance pipeline network on different matching historical dates; The regulation reliability demand coefficient for the date is determined according to an average value of the proportion of the number of the regulation-variable equipment and the proportion of the number of frequently-used electrical equipment.

[0039] Furthermore, the frequently used electrical equipment is an electrical equipment for which the proportion of the number of matching historical dates with adjustment durations of different adjustment times and greater than a preset duration threshold is within a preset proportion range.

[0040] It is understood that the method for determining the adjustment change device is: Based on the number of times the electric equipment of the long-distance pipeline network is adjusted on different matching historical dates, an average value of the number of times the electric equipment of the long-distance pipeline network is adjusted on different matching historical dates is determined, and the average value is used as a reference number of times; The matching historical date whose deviation from the reference adjustment number does not meet the requirement is used as the change date; According to the number of the change dates, it is determined whether the electric device is a regulation-changed device.

[0041] Furthermore, the adjustment reliability demand coefficient of the date ranges from 0 to 1, wherein when the adjustment reliability demand coefficient of the date is greater than a preset demand coefficient threshold, the date is determined to be a reliable adjustment date.

[0042] In another possible embodiment, the method for determining the adjustment reliability demand coefficient of the date is: Use the similar historical date corresponding to the said date as the matching historical date, and based on the historical adjustment data of the power-consuming equipment of the long-distance pipeline network on different matching historical dates, determine the adjustment times of the power-consuming equipment of the long-distance pipeline network on different matching historical dates and the adjustment durations of different adjustment times, and use the adjustment times and the adjustment durations of different adjustment times to determine that there is no frequently used power-consuming equipment in the said power-consuming equipment: Then determine that the said date does not belong to the reliable adjustment date; When there is frequently used power-consuming equipment in the said power-consuming equipment: Use the adjustment times of the power-consuming equipment of the long-distance pipeline network on different matching historical dates and the adjustment durations of different adjustment times to determine the adjustment frequency coefficients on different historical matching dates. When the adjustment frequency coefficients on different historical matching dates are all less than the preset frequency coefficient threshold, then determine that the said date does not belong to the reliable adjustment date; When there is a historical matching date with an adjustment frequency coefficient not less than the preset frequency coefficient threshold: Based on the adjustment frequency coefficients on different matching historical dates, determine the adjustment frequency evaluation amount of the said date. When the adjustment frequency evaluation amount of the said date is within the preset evaluation amount interval: Based on the change situation of the adjustment times of the power-consuming equipment of the long-distance pipeline network on different matching historical dates, determine that there is no adjustment change equipment in the said power-consuming equipment: Then determine that the said date does not belong to the reliable adjustment date; When there is adjustment change equipment in the said power-consuming equipment: Based on the change situation of the adjustment times of the adjustment change equipment of the long-distance pipeline network on different matching historical dates, determine the adjustment change coefficient of the said date. When the adjustment change coefficient of the said date is less than the preset change coefficient threshold, then determine that the said date does not belong to the reliable adjustment date; When the adjustment frequency evaluation amount of the said date is not within the preset evaluation amount interval or the adjustment change coefficient is not less than the preset change coefficient threshold: Based on the adjustment frequency evaluation amount and the adjustment change coefficient of the said date, determine the adjustment reliable demand coefficient of the said date.

[0043] S3 Obtain the distribution data of reliable adjustment dates within a future preset time period, and combine the adjustment reliable demand coefficients of different reliable adjustment dates. When the demand reliable degree of power supply within the future preset time period meets the requirements, proceed to the next step; Further, determining that the demand reliable degree of power supply within a future preset time period meets the requirements specifically includes: Based on the distribution data of reliable adjustment dates within a preset future period, determine the proportion of the number of reliable adjustment dates within the preset future period, and use it as the proportion of the number of reliable dates. Based on the adjustment reliability demand coefficients of different reliable adjustment dates, determine the average value of the adjustment reliability demand coefficients of different reliable adjustment dates, and use it as the average reliability coefficient. Determine the demand reliability degree of power supply within a preset future period through the product of the average reliability coefficient and the proportion of the number of reliable dates, and combine it with a preset reliability degree threshold to determine whether the demand reliability degree meets the requirements.

[0044] Specifically, when the demand reliability degree of power supply within a preset future period is less than the preset reliability degree threshold, it is determined that the demand reliability degree does not meet the requirements.

[0045] It should be noted that when the demand reliability degree does not meet the requirements, power trading processing is carried out using the energy storage device during the period with the lowest quotation on the current date.

[0046] S4 Obtain the power consumption data of the power consumption equipment of the long-distance transmission pipeline network on different dates, and determine the power trading processing strategy for the current date based on the power consumption data, the remaining electric energy of the energy storage device, and the demand reliability degree.

[0047] Furthermore, the power consumption data of the power consumption equipment of the long-distance transmission pipeline network on different dates is determined according to the average value of the historical power consumption of the power consumption equipment of the long-distance transmission pipeline network on the historical similar dates corresponding to different dates.

[0048] Specifically, as Figure 3 shown, the method for determining the power trading processing strategy for the current date is as follows: Based on the power consumption data of the power consumption equipment of the long-distance transmission pipeline network on different dates, determine the total power consumption of the power consumption equipment of the long-distance transmission pipeline network on different dates; Determine the energy storage power ratio based on the ratio of the remaining electric energy of the energy storage device to the total power consumption; Determine the trading demand coefficient for the current date based on the energy storage power ratio and the demand reliability degree, and use the trading demand coefficient to determine the power trading processing strategy for the current date.

[0049] Furthermore, using the trading demand coefficient to determine the power trading processing strategy for the current date specifically includes: When the trading demand coefficient is greater than the preset demand coefficient threshold, power trading processing is carried out using the energy storage device during the period with the lowest quotation on the current date; When the trading demand coefficient is not greater than the preset demand coefficient threshold, there is no need to carry out power trading processing using the energy storage device on the current date.

[0050] Example 2 On the other hand, an embodiment of the present application provides a computer system, on which a computer program is stored. When the computer program is executed on a computer, the computer is made to execute the above-mentioned power trading method for a long-distance pipeline network based on an energy storage device.

[0051] Example 3 On the other hand, an embodiment of the present application provides a computer program product, characterized in that the computer program product stores instructions, and when the instructions are executed by a computer, the computer is made to implement the above-mentioned power trading method for a long-distance pipeline network based on an energy storage device.

[0052] In the embodiments of the present invention, the term "plurality" refers to two or more, unless otherwise clearly defined. Terms such as "installation", "connection", "fixation" and the like should be understood in a broad sense. For example, "connection" can be a fixed connection, a detachable connection, or an integral connection. For those of ordinary skill in the art, the specific meanings of the above terms in the embodiments of the present invention can be understood according to specific situations.

[0053] In the description of the embodiments of the present invention, it should be understood that the orientation or positional relationship indicated by terms such as "upper", "lower", etc. is based on the orientation or positional relationship shown in the drawings, and is only for the convenience of describing the embodiments of the present invention and simplifying the description, rather than indicating or implying that the device or unit referred to must have a specific direction, be constructed and operated in a specific orientation, and therefore, should not be construed as a limitation to the embodiments of the present invention.

[0054] In the description of this specification, the description of terms such as "one embodiment", "one preferred embodiment", etc. means that the specific features, structures, materials or characteristics described in connection with the embodiment or example are included in at least one embodiment or example of the embodiments of the present invention. In this specification, the schematic representations of the above terms do not necessarily refer to the same embodiment or example. Moreover, the specific features, structures, materials or characteristics described can be combined in a suitable manner in any one or more embodiments or examples.

[0055] The above are only the preferred embodiments of the embodiments of the present invention, and are not used to limit the embodiments of the present invention. For those skilled in the art, the embodiments of the present invention can have various changes and modifications. Any modification, equivalent replacement, improvement, etc. made within the spirit and principle of the embodiments of the present invention shall be included in the protection scope of the embodiments of the present invention.

Claims

1. A power trading method for a long-distance pipeline network based on an energy storage device, characterized in that Specifically, it includes: S1 Analyze the weather data of different dates within a preset future time period, determine the changes in the electricity price quotation data of similar historical dates corresponding to different dates, and when it is determined that there is a date with historical electricity price quotations meeting the requirements based on the changes, proceed to the next step; S2 Determine the changes in the adjustment instructions of the power-consuming equipment of the long-distance transmission pipeline network corresponding to similar historical dates of different dates based on the historical adjustment data of the long-distance transmission pipeline network corresponding to similar historical dates of different dates, and combine the historical adjustment data of the power-consuming equipment of the long-distance transmission pipeline network of similar historical dates to determine the adjustment reliability demand coefficient and reliable adjustment dates of different dates; S3 Obtain the distribution data of reliable adjustment dates within a preset future time period, and when it is determined that the demand reliability degree of power supply within the preset future time period meets the requirements in combination with the adjustment reliability demand coefficients of different reliable adjustment dates, proceed to the next step; S4 Obtain the power consumption data of the power-consuming equipment of the long-distance transmission pipeline network of different dates, and determine the power trading processing strategy for the current date based on the power consumption data, the remaining power of the energy storage device, and the demand reliability degree.

2. The power trading method for a long-distance transmission pipeline network based on an energy storage device according to claim 1, wherein, Before determining that there is a date with historical electricity price quotations meeting the requirements, it is also necessary to determine whether there is a time period during the current date when the trading electricity price is within the preset electricity price range. When there is a time period during the current date when the trading electricity price is within the preset electricity price range, then use the time period with the lowest quotation of the energy storage device on the current date for power trading processing.

3. The power trading method for a long-distance pipeline network based on an energy storage device according to claim 1, characterized in that, The preset time period is determined according to the energy storage capacity of the energy storage device, and the larger the energy storage capacity of the energy storage device, the longer the preset time period.

4. The power trading method for long-distance transmission pipeline networks based on energy storage devices according to claim 1, wherein, The similar historical date is a historical date with a deviation amount of weather data from the date within a preset deviation range.

5. The power trading method for long-distance transmission pipe networks based on energy storage devices according to claim 1, characterized in that, The method for determining the date with historical electricity price quotations meeting the requirements is as follows: Based on the changes, determine the change amounts of the electricity price quotations of different similar historical dates of the date at different time periods, and use the change amounts to determine the quotation stable time periods during the time periods; Based on the electricity price quotations of different similar historical dates during the quotation stable time periods, determine the proportion of the number of similar historical dates with electricity price quotations lower than the preset electricity price in different quotation stable time periods, and use the proportion to determine the low electricity price proportion of different quotation stable time periods; Determine whether the date is a date with historical electricity price quotations meeting the requirements according to the low electricity price proportion of different quotation stable time periods.

6. The power trading method for long-distance transmission pipe networks based on energy storage devices according to claim 5, characterized in that The quotation stable time period is a time period during which the change amounts of the electricity price quotations of different similar historical dates are all within a preset change amount range.

7. The power trading method for long-distance transmission pipe networks based on energy storage devices according to claim 5, wherein When there is no date with historical electricity price quotations meeting the requirements, then use the time period with the lowest quotation of the energy storage device on the current date for power trading processing.

8. The power trading method for long-distance transmission pipe networks based on energy storage devices according to claim 1, wherein, The method for determining the power trading processing strategy for the current date is as follows: Based on the power consumption data of the power-consuming equipment of the long-distance transmission pipeline network of different dates, determine the total power consumption of the power-consuming equipment of the long-distance transmission pipeline network of different dates; Determine the energy storage power ratio based on the ratio of the remaining power of the energy storage device to the total power consumption. Determine the trading demand coefficient for the current date based on the ratio of the stored energy quantity to the demand reliability, and use the trading demand coefficient to determine the power trading processing strategy for the current date.

9. The power trading method for a long-distance pipeline network based on an energy storage device according to claim 8, wherein, Using the trading demand coefficient to determine the power trading processing strategy for the current date specifically includes: When the trading demand coefficient is greater than the preset demand coefficient threshold, power trading processing is performed using the time period with the lowest quote of the energy storage device on the current date; When the trading demand coefficient is not greater than the preset demand coefficient threshold, there is no need to perform power trading processing using the energy storage device on the current date.

10. A computer system on which a computer program is stored, and when the computer program is executed in a computer, it is characterized in that, Let a computer execute a power trading method for a long-distance pipeline network based on an energy storage device according to any one of claims 1-9.

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