Installation method, device, electronic equipment and medium of pure hydrogen gas turbine energy storage system

Abstract

The embodiments of the present disclosure disclose a method, device, electronic device and medium for installing a pure hydrogen gas turbine energy storage system. A specific implementation method of the method includes: obtaining the historical annual available power generation information and the historical annual online power sequence of the target wind and solar power station; generating the estimated annual abandoned power information based on the historical annual available power generation information and the historical annual online power sequence; generating the daily hydrogen production of abandoned power based on the estimated annual abandoned power information; generating the number of electrolyzers, the number of hydrogen storage spherical tanks and the daily operating time of gas turbines based on the daily hydrogen production of abandoned power; generating the number of gas turbines based on the daily operating time of gas turbines; generating the value information of energy storage system collection based on the daily operating time of gas turbines; controlling the associated installation equipment to perform the installation operations of each equipment based on the number of electrolyzers, the number of hydrogen storage spherical tanks, the number of gas turbines and the value information of energy storage system collection. This implementation method can save installation resources and energy.

Description

Technical Field

[0001] The embodiments of the present disclosure relate to the technical field of energy storage systems, and specifically to installation methods, devices, electronic equipment, and media for pure hydrogen gas turbine energy storage systems. Background Art

[0002] As a large-scale, long-cycle energy storage technology, the pure hydrogen gas turbine energy storage system has the characteristics of zero carbon emissions, fast start and stop, and strong frequency and voltage regulation support, which can smooth or reduce the impact of unstable wind and photovoltaic power generation output. At present, when installing the various energy storage devices included in the pure hydrogen gas turbine energy storage system, the usual method is: based on the historical annual power abandonment of wind and solar power stations, the annual power abandonment in the future time period is estimated through a time series prediction model, and then, based on the estimated annual power abandonment, the equipment quantity and value information (such as investment cost) of each energy storage device required to configure the pure hydrogen gas turbine energy storage system are determined. When it is determined that the pure hydrogen gas turbine energy storage system can be configured, the various energy storage devices included in the pure hydrogen gas turbine energy storage system are installed.

[0003] However, when the above-mentioned method is used to install the various energy storage devices included in the pure hydrogen gas turbine energy storage system, the following technical problems often occur: the change in annual power abandonment is directly affected by the annual power generation and the annual grid-connected power. The annual power abandonment in future time periods is estimated only based on the historical annual power abandonment, resulting in low accuracy in the estimated annual power abandonment, and low accuracy in the number of each energy storage device determined. When the estimated number of equipment is higher than the actual number of equipment required, it causes a waste of installation resources. When the estimated number of equipment is lower than the actual number of equipment required, it causes a waste of energy.

[0004] When adopting a technical solution to solve the technical problem 1 in the background technology, it is often accompanied by the following problem: how to determine the value information (such as investment cost) required for configuring a pure hydrogen gas turbine energy storage system according to the number of each device required for each energy storage device to determine whether to configure a pure hydrogen gas turbine energy storage system, thereby saving energy or installation resources. In response to these problems, the conventional solution is generally: for each energy storage device, the equipment value information required for the energy storage device is generated by determining the number of devices and the pre-set value information required for transporting and installing a single device, and then, for each energy storage device, the value information of each device is summed to obtain the total equipment value information required for investment. However, the above solution has the following technical problem 2: the installation difficulty of wind and solar power stations in different locations when transporting and installing different energy storage devices is also different. Only by determining the number of equipment and the pre-set value information required for installing and operating and maintaining a single device, the influence of the location of the wind and solar power station on transportation and installation is not considered, resulting in a low accuracy of the generated total equipment value information, which leads to a low accuracy of the verification result used to determine whether to configure a pure hydrogen gas turbine energy storage system, thereby causing a waste of installation resources and transportation resources.

[0005] The above information disclosed in this Background section is only for enhancement of understanding of the background of the present disclosure concept and therefore it may contain information that does not form the prior art that is already known in this country to a person of ordinary skill in the art. Summary of the invention

[0006] The content of this disclosure is used to introduce concepts in a brief form, which will be described in detail in the detailed implementation section below. The content of this disclosure is not intended to identify the key features or essential features of the technical solution claimed for protection, nor is it intended to limit the scope of the technical solution claimed for protection.

[0007] Some embodiments of the present disclosure propose a pure hydrogen gas turbine energy storage system installation method, device, electronic device and computer-readable medium to solve one or more of the technical problems mentioned in the above background technology section.

[0008] In a first aspect, some embodiments of the present disclosure provide a method for installing a pure hydrogen gas turbine energy storage system, the method comprising: obtaining historical annual available power generation information and historical annual grid-connected power sequence of a target wind and solar power station; generating estimated annual power abandonment information based on the above historical annual available power generation information and the above historical annual grid-connected power sequence; generating daily hydrogen production based on the above estimated annual power abandonment information; generating the number of electrolyzers, the number of hydrogen storage spherical tanks and the daily operating time of gas turbines corresponding to the pure hydrogen gas turbine energy storage system to be configured based on the above abandoned power daily hydrogen production; generating the number of gas turbines based on the above gas turbine daily operating time; generating energy storage system collection value information based on the above gas turbine daily operating time; controlling each associated installation device to perform each device installation operation based on the above electrolyzer number, the above hydrogen storage spherical tank number, the above gas turbine number and the above energy storage system collection value information.

[0009] In a second aspect, some embodiments of the present disclosure provide a pure hydrogen gas turbine energy storage system installation device, the device comprising: an acquisition unit, configured to acquire historical annual available power generation information and historical annual grid-connected power sequence of a target wind and solar power station; a first generation unit, configured to generate estimated annual power abandonment information based on the above historical annual available power generation information and the above historical annual grid-connected power sequence; a second generation unit, configured to generate daily hydrogen production based on the above estimated annual power abandonment information; a third generation unit, configured to generate the number of electrolyzers, the number of hydrogen storage spherical tanks and the daily operating time of gas turbines corresponding to the pure hydrogen gas turbine energy storage system to be configured based on the above abandoned daily hydrogen production; a fourth generation unit, configured to generate the number of gas turbines based on the above daily operating time of the gas turbines; a fifth generation unit, configured to generate value information collected by the energy storage system based on the above daily operating time of the gas turbines; a control unit, configured to control each associated installation device to perform each device installation operation based on the above number of electrolyzers, the above number of hydrogen storage spherical tanks, the above number of gas turbines and the above energy storage system collection value information.

[0010] In a third aspect, some embodiments of the present disclosure provide an electronic device comprising: one or more processors; a storage device on which one or more programs are stored, and when the one or more programs are executed by the one or more processors, the one or more processors implement the method described in any implementation manner of the above-mentioned first aspect.

[0011] In a fourth aspect, some embodiments of the present disclosure provide a computer-readable medium having a computer program stored thereon, wherein when the program is executed by a processor, the method described in any implementation manner of the above-mentioned first aspect is implemented.

[0012] The above-mentioned embodiments of the present disclosure have the following beneficial effects: the installation resources and energy can be saved by the installation method of the pure hydrogen gas turbine energy storage system of some embodiments of the present disclosure. Specifically, the reason for the waste of configuration resources and installation resources or energy waste is that the change of annual abandoned power is directly affected by the annual power generation and the annual online power. The annual abandoned power in the future time period is estimated only based on the historical annual abandoned power, resulting in the low accuracy of the estimated annual abandoned power, resulting in the low accuracy of the number of each device of each energy storage device determined. When the estimated number of devices is higher than the actual number of devices required, it causes a waste of installation resources. When the estimated number of devices is lower than the actual number of devices required, it causes energy waste. Based on this, the installation method of the pure hydrogen gas turbine energy storage system of some embodiments of the present disclosure, first, obtain the historical annual power generation information and the historical annual online power sequence of the target wind and solar power station. Thus, the power generation information and online power information of the wind and solar power station to be configured in the historical time period can be obtained, so as to estimate the abandoned power information of the wind and solar power station to be configured. Secondly, according to the above-mentioned historical annual power generation information and the above-mentioned historical annual online power sequence, the estimated annual abandoned power information is generated. Thus, the annual power generation and annual power abandonment of the wind and solar power station can be comprehensively considered to estimate the information of the annual power abandonment of the wind and solar power station to be configured, so as to improve the accuracy of the estimated annual power abandonment. Then, based on the above-mentioned estimated annual power abandonment information, the daily hydrogen production of abandoned power is generated. Thus, the amount of hydrogen that can be produced by the daily abandoned power can be obtained, which can be used to determine the number of various devices included in the pure hydrogen gas turbine energy storage system to be configured. Afterwards, based on the above-mentioned daily hydrogen production of abandoned power, the number of electrolyzers, the number of hydrogen storage spherical tanks and the daily operating time of the gas turbine corresponding to the pure hydrogen gas turbine energy storage system to be configured are generated. Based on the above-mentioned daily operating time of the gas turbine, the number of gas turbines is generated. Thus, the number of various energy storage devices included in the pure hydrogen gas turbine energy storage system to be configured can be obtained, so as to determine whether to install the various energy storage devices included in the pure hydrogen gas turbine energy storage system to be configured. Then, based on the above-mentioned daily operating time of the gas turbine, the value information collected by the energy storage system is generated. Thus, the value information that can be obtained by configuring the pure hydrogen gas turbine energy storage system can be obtained, and thus the value information required for configuring the pure hydrogen gas turbine energy storage system can be obtained, which can be used to determine whether to install the various energy storage devices included in the pure hydrogen gas turbine energy storage system to be configured. Finally, according to the value information collected based on the number of electrolyzers, the number of hydrogen storage tanks, the number of gas turbines, and the energy storage system, the associated installation devices are controlled to perform various equipment installation operations. Thus, the various energy storage devices included in the pure hydrogen gas turbine energy storage system can be installed, so that they can be used to store energy.Also, when installing the various energy storage devices included in the pure hydrogen gas turbine energy storage system, the annual power abandonment is estimated by the power generation and grid-connected capacity of the wind and solar power stations in historical time periods, thereby improving the accuracy of the estimated annual power abandonment. Then, the value recovery time is estimated based on actual conditions, thereby improving the accuracy of the number of various energy storage devices included in the pure hydrogen gas turbine energy storage system, thereby saving installation resources and energy. BRIEF DESCRIPTION OF THE DRAWINGS

[0013] The above and other features, advantages and aspects of the embodiments of the present disclosure will become more apparent with reference to the following detailed description in conjunction with the accompanying drawings. Throughout the accompanying drawings, the same or similar reference numerals represent the same or similar elements. It should be understood that the drawings are schematic and that components and elements are not necessarily drawn to scale.

[0014] Figure 1 is a flow chart of some embodiments of a method for installing a pure hydrogen gas turbine energy storage system according to the present disclosure;

[0015] Figure 2 It is a structural schematic diagram of some embodiments of the installation device of the pure hydrogen gas turbine energy storage system according to the present disclosure;

[0016] Figure 3 It is a schematic diagram of the structure of an electronic device suitable for implementing some embodiments of the present disclosure. DETAILED DESCRIPTION

[0017] Embodiments of the present disclosure will be described in more detail below with reference to the accompanying drawings. Although certain embodiments of the present disclosure are shown in the accompanying drawings, it should be understood that the present disclosure can be implemented in various forms and should not be construed as being limited to the embodiments set forth herein. On the contrary, these embodiments are provided to provide a more thorough and complete understanding of the present disclosure. It should be understood that the drawings and embodiments of the present disclosure are only for exemplary purposes and are not intended to limit the scope of protection of the present disclosure.

[0018] It should also be noted that, for ease of description, only the parts related to the invention are shown in the drawings. In the absence of conflict, the embodiments and features in the embodiments of the present disclosure can be combined with each other.

[0019] It should be noted that the concepts such as "first" and "second" mentioned in the present disclosure are only used to distinguish different devices, modules or units, and are not used to limit the order or interdependence of the functions performed by these devices, modules or units.

[0020] It should be noted that the modifications of "one" and "plurality" mentioned in the present disclosure are illustrative rather than restrictive, and those skilled in the art should understand that unless otherwise clearly indicated in the context, it should be understood as "one or more".

[0021] The names of the messages or information exchanged between multiple devices in the embodiments of the present disclosure are only used for illustrative purposes and are not used to limit the scope of these messages or information.

[0022] The present disclosure will be described in detail below with reference to the accompanying drawings and in conjunction with embodiments.

[0023] Figure 1 A process 100 of some embodiments of a pure hydrogen gas turbine energy storage system installation method according to the present disclosure is shown. The pure hydrogen gas turbine energy storage system installation method comprises the following steps:

[0024] Step 101, obtaining the historical annual available power generation information and historical annual grid-connected power sequence of the target wind and solar power station.

[0025] In some embodiments, the execution subject (e.g., a computing device) of the pure hydrogen gas turbine energy storage system installation method may obtain the historical annual available power generation information and the historical annual online power generation sequence of the target wind and solar power station. Among them, the above-mentioned target wind and solar power station may be a wind and solar power station selected by the user that has been put into operation and is waiting to be configured with a pure hydrogen gas turbine energy storage system. The above-mentioned wind and solar power station may be a power station that generates electricity through wind power and photovoltaics. The above-mentioned pure hydrogen gas turbine energy storage system may be a system that stores electrical energy through a pure hydrogen gas turbine. The above-mentioned pure hydrogen gas turbine may be a gas turbine whose fuel is 100% hydrogen. The above-mentioned historical annual available power generation information may characterize the amount of power that can be generated by the above-mentioned target wind and solar power station each year in a historical time period. The above-mentioned historical annual online power generation sequence may be a sequence in which the online power generation of each historical year is arranged in ascending order of time. The historical annual online power generation may be the total power generation of the power grid in the corresponding year. In practice, the above-mentioned execution subject may obtain the historical annual available power generation information and the historical annual online power generation sequence of the target wind and solar power station from the database by wired connection or wireless connection.

[0026] Step 102, based on the historical annual available power generation information and the historical annual grid-connected power sequence, generate the estimated annual abandoned power information.

[0027] In some embodiments, the execution subject may generate estimated annual power abandonment information based on the historical annual power generation information and the historical annual grid-connected power sequence. The estimated annual power abandonment information may represent the estimated power abandonment of the target wind and solar power station in one year.

[0028] Optionally, the above-mentioned historical annual available power generation information may include each historical monthly available power generation information sequence and a historical annual available power generation data sequence. The historical monthly available power generation information sequence in each historical monthly available power generation information sequence corresponds to a historical year. The historical monthly available power generation information sequence may be a sequence in which each historical monthly available power generation information is arranged in ascending order of time. Each historical monthly available power generation information corresponds to a month. The historical monthly available power generation information may characterize the power generation that can be generated by the above-mentioned target wind and solar power station in the corresponding month. The historical monthly available power generation information in each historical monthly available power generation information sequence may include the historical monthly available power generation. The above-mentioned historical monthly available power generation may be the power generation of the above-mentioned target wind and solar power station in the corresponding month. The historical annual available power generation information in the above-mentioned historical annual available power generation data sequence corresponds to a historical year. The historical monthly available power generation information may also include monthly weather information. The above-mentioned monthly weather information may characterize the weather information of the corresponding month of the above-mentioned target wind and solar power station. The above-mentioned monthly weather information may include but is not limited to the monthly average wind speed, the monthly average sunshine duration and the monthly average temperature. The above-mentioned monthly average wind speed may be the average value of the wind speed of the corresponding month. The monthly average sunshine duration may be the average of the sunshine durations of each day included in the corresponding month. The sunshine duration may be the sunshine duration of the corresponding date. The monthly average temperature may be the average of the temperature of the corresponding month. The historical annual power generation data sequence may be a sequence in which each historical annual power generation data is arranged in ascending order of time. The historical annual power generation information in the historical annual power generation data sequence may include the historical annual power generation and may also include annual weather information. The historical annual power generation may be the power generation of the target wind and solar power station in the corresponding year. The annual weather information may include but is not limited to the annual average wind speed, the annual average sunshine duration and the annual average temperature. The annual average wind speed may be the average of the wind speed in the corresponding year. The annual average sunshine duration may be the average of the sunshine durations of each day included in the corresponding year. The annual average temperature may be the average of the temperature in the corresponding year.

[0029] In some optional implementations of some embodiments, the execution subject may generate the estimated annual power abandonment information according to the historical annual available power generation information and the historical annual online power sequence through the following steps:

[0030] In the first step, each historical monthly available power generation information included in the above-mentioned each historical monthly available power generation information sequence is grouped to obtain each historical monthly available power generation information group. In practice, the above-mentioned execution subject can determine each historical monthly available power generation information corresponding to the same month in each historical monthly available power generation information included in the above-mentioned each historical monthly available power generation information sequence as a historical monthly available power generation information group to obtain each historical monthly available power generation information group.

[0031] In the second step, for each historical monthly power generation information group obtained, perform the following sub-steps:

[0032] The first sub-step is to sort the above historical monthly power generation information group to obtain a target historical monthly power generation information sequence. In practice, the above execution entity can sort the above historical monthly power generation information group in ascending order of each historical year corresponding to each historical monthly power generation information included in the above historical monthly power generation information group to obtain a target historical monthly power generation information sequence.

[0033] The second sub-step is to input the target historical monthly electricity generation information sequence into the pre-trained estimated monthly electricity generation model to obtain the estimated monthly electricity generation. The estimated monthly electricity generation model may be a neural network that takes the target historical monthly electricity generation information sequence as input and the estimated monthly electricity generation as output. The estimated monthly electricity generation may be the predicted electricity generation of the target month. The target month may be the month corresponding to the target historical monthly electricity generation information sequence. The estimated monthly electricity generation model may include a first feature extraction layer, a second feature extraction layer, a feature merging layer, and an output layer. The first feature extraction layer may be used to extract the spatial features of the target historical monthly electricity generation information sequence. For example, the first feature extraction layer may be a convolutional neural network layer. The second feature extraction layer may be used to extract the temporal features of the target historical monthly electricity generation information sequence. For example, the second feature extraction layer may be a long short-term memory neural network layer. The feature merging layer may be used to concatenate the first feature vector output by the first feature extraction layer and the second feature vector output by the second feature extraction layer to obtain a merged feature vector. The output layer may be a neural network that outputs the estimated monthly power generation according to the merged feature vector. The first feature extraction layer, the second feature extraction layer and the feature merging layer are network-connected. The feature merging layer is network-connected to the output layer.

[0034] In the third step, the sum of the estimated monthly power generation amounts is determined as the first estimated annual power generation amount.

[0035] In the fourth step, the historical annual available power generation data sequence is input into the pre-trained estimated annual available power generation model to obtain the second estimated annual available power generation. In practice, the execution subject can be a neural network that takes the historical annual available power generation data sequence as input and the estimated annual available power generation as output. The neural network can be a gated recurrent neural network. The estimated annual available power generation can be the total power generation predicted for one year.

[0036] The fifth step is to determine the variance of the available power in each historical month included in the above-mentioned available power information sequence as the variance of the available power in the first month for each historical month included in the above-mentioned available power information sequence.

[0037] In the sixth step, for each historical monthly available power generation information group included in the above-mentioned historical monthly available power generation information group, the variance of the available power generation of each historical month included in the above-mentioned historical monthly available power generation information group is determined as the variance of the available power generation of the second month.

[0038] The seventh step is to determine the power generation weight set corresponding to the first estimated annual power generation and the second estimated annual power generation according to the variance of the first monthly power generation and the variance of the second monthly power generation. The power generation weight set includes the first power generation weight and the second power generation weight. The first power generation weight may be the weight corresponding to the first estimated annual power generation. The second power generation weight may be the weight corresponding to the second estimated annual power generation. In practice, the execution subject may determine the first preset power generation weight as the power generation weight corresponding to the first estimated annual power generation in response to determining that the variance of the first monthly power generation and the variance of the second monthly power generation are both less than the preset monthly power generation variance, and determine the second preset power generation weight as the power generation weight corresponding to the second estimated annual power generation. The preset monthly power generation variance may be a preset monthly power generation variance that characterizes the large fluctuation of the monthly power generation. Both the first preset power generation weight and the second preset power generation weight may be preset power generation weights. It should be noted that the first preset power generation weight may be smaller than the second preset power generation weight. For example, the first preset power generation weight may be 0.4, and the second preset power generation weight may be 0.6. Then, in response to determining that the variance of the first month's available power generation and the variance of the second month's available power generation are both greater than the preset monthly available power generation variance, the third preset power generation weight is determined as the power generation weight corresponding to the first estimated annual available power generation, and the fourth preset power generation weight is determined as the power generation weight corresponding to the second estimated annual available power generation. The third preset power generation weight and the fourth preset power generation weight may both be pre-set power generation weights. It should be noted that the third preset power generation weight may be greater than the fourth preset power generation weight. For example, the third preset power generation weight may be 0.6, and the fourth preset power generation weight may be 0.4. Finally, in response to determining that the variance of the first month's available power generation is greater than the preset monthly available power generation variance, and the variance of the second month's available power generation is less than the preset monthly available power generation variance, or determining that the variance of the first month's available power generation is less than the preset monthly available power generation variance, and the variance of the second month's available power generation is greater than the preset monthly available power generation variance, the fifth preset power generation weight is determined as the power generation weight corresponding to the first estimated annual available power generation, and the sixth preset power generation weight is determined as the power generation weight corresponding to the second estimated annual available power generation. The fifth preset power generation weight and the sixth preset power generation weight can both be pre-set power generation weights. It should be noted that the fifth preset power generation weight can be equal to the sixth preset power generation weight. For example, the fifth preset power generation and the sixth preset power generation weight can be 0.5.

[0039] In the eighth step, the estimated annual available power generation is generated according to the first estimated annual available power generation, the second estimated annual available power generation and the power generation weight set. In practice, the execution entity may determine the sum of the product of the first estimated annual available power generation and the first power generation weight included in the power generation weight set, and the product of the second estimated annual available power generation and the second power generation weight included in the power generation weight set as the estimated annual available power generation.

[0040] In the ninth step, the above historical annual online power sequence is input into the pre-trained estimated annual online power generation model to obtain the estimated annual online power. The estimated annual online power generation model can be a neural network that takes the historical annual online power sequence as input and the estimated annual online power as output. The neural network can be a long short-term memory neural network. The estimated annual online power can be the estimated total online power for one year.

[0041] The tenth step is to determine the difference between the estimated annual power generation and the estimated annual grid-connected power as the estimated annual power abandonment information.

[0042] Therefore, when estimating the annual available power, it is possible not only to estimate based on the annual available power, but also to consider the impact of seasonal changes on the power generation of wind and solar power stations, estimate the monthly available power each year, and then sum up the estimated annual available power. In addition, the annual available power estimated by the two methods is combined according to the fluctuation of the monthly available power, and the final estimated annual available power is determined, thereby improving the accuracy of the estimated annual available power, and further improving the accuracy of the number of each device of each energy storage device. Thus, resources or energy can be installed.

[0043] Step 103, generating the daily hydrogen production amount of the abandoned electricity according to the estimated annual abandoned electricity information.

[0044] In some embodiments, the above-mentioned execution entity may generate the amount of hydrogen produced on a daily basis due to the abandoned power according to the above-mentioned estimated annual amount of abandoned power information. The above-mentioned amount of hydrogen produced on a daily basis due to the abandoned power may be the amount of hydrogen produced on average per day due to the abandoned power. In practice, first, the above-mentioned execution entity may determine the ratio of the above-mentioned estimated annual amount of abandoned power information to the preset number of days in a year as the estimated daily amount of abandoned power. The above-mentioned preset number of days in a year may be the preset number of days in a year. Then, the ratio of the above-mentioned estimated daily amount of abandoned power to the preset unit power consumption of hydrogen production by electrolysis is determined as the amount of hydrogen produced on a daily basis due to the abandoned power. The above-mentioned preset unit power consumption of hydrogen production by electrolysis may be the preset unit power consumption of hydrogen production by electrolysis. The above-mentioned unit power consumption of hydrogen production by electrolysis may be the electric energy required to produce 1 cubic meter of hydrogen by electrolyzing water. For example, the value range of the above-mentioned preset unit power consumption of hydrogen production by electrolysis may be [4, 5], in kilowatt-hours.

[0045] Step 104, based on the daily hydrogen production of abandoned electricity, generate the number of electrolyzers, the number of hydrogen storage spherical tanks and the daily operating time of the gas turbine corresponding to the pure hydrogen gas turbine energy storage system to be configured.

[0046] In some embodiments, the above-mentioned execution subject may generate the number of electrolyzers, the number of hydrogen storage spherical tanks and the daily operation time of the gas turbine corresponding to the pure hydrogen gas turbine energy storage system to be configured according to the above-mentioned daily hydrogen production of abandoned electricity. Among them, the above-mentioned pure hydrogen gas turbine energy storage system to be configured may include various energy storage devices. The energy storage device may be a device for storing energy. The above-mentioned various energy storage devices may include an electrolyzer, a hydrogen storage spherical tank and a pure hydrogen gas turbine. The above-mentioned hydrogen storage spherical tank may be a spherical hydrogen storage tank. The above-mentioned number of electrolyzers may be the number of electrolyzers. The above-mentioned number of hydrogen storage spherical tanks may be the number of hydrogen storage spherical tanks. The above-mentioned daily operation time of the gas turbine may be the daily operation time required for each pure hydrogen gas turbine included in the above-mentioned pure hydrogen gas turbine energy storage system to be configured. The pure hydrogen gas turbine may be a gas turbine whose fuel is 100% hydrogen. In practice, the above-mentioned execution subject may generate the number of electrolyzers, the number of hydrogen storage spherical tanks and the daily operation time of the gas turbine corresponding to the pure hydrogen gas turbine energy storage system to be configured according to the above-mentioned daily hydrogen production of abandoned electricity in various ways.

[0047] In some optional implementations of some embodiments, the execution subject may generate the number of electrolyzers, the number of hydrogen storage spherical tanks and the daily operation time of the gas turbine corresponding to the pure hydrogen gas turbine energy storage system to be configured according to the daily hydrogen production of the abandoned electricity through the following steps:

[0048] The first step is to obtain the electrolyzer attribute information corresponding to the electrolyzer identification. The electrolyzer attribute information may characterize the attributes of the electrolyzer. The electrolyzer attribute information may include but is not limited to the electrolyzer identification and the unit rated hydrogen production of the electrolyzer. The unit rated hydrogen production of the electrolyzer may be the rated hydrogen production per hour of a single electrolyzer. The unit rated hydrogen production of the electrolyzer may be in cubic meters. The electrolyzer identification may be the unique identification of the electrolyzer. For example, the electrolyzer identification may be the model of the electrolyzer. In practice, the execution entity may obtain the electrolyzer attribute information corresponding to the electrolyzer identification from the database via a wired connection or a wireless connection.

[0049] The second step is to generate the number of electrolyzers according to the above-mentioned abandoned power daily hydrogen production and the above-mentioned electrolyzer attribute information. In practice, first, the above-mentioned execution entity can determine the product of the unit rated hydrogen production of the electrolyzer included in the above-mentioned electrolyzer attribute information and the above-mentioned preset unit power consumption of electrolysis hydrogen production as the electrolyzer power. Among them, the unit of the above-mentioned electrolyzer power can be kilowatts. Secondly, the percentage of the ratio of the above-mentioned estimated annual abandoned power information to the above-mentioned estimated annual power generation is determined as the annual abandoned power rate. Then, the product of the preset wind and solar installed capacity and the above-mentioned annual abandoned power rate is determined as the annual abandoned power capacity. Among them, the above-mentioned preset wind and solar installed capacity can be the total capacity of the wind and solar installed capacity of the target wind and solar power station. The above-mentioned preset wind and solar installed capacity can be kilowatts. Finally, the ratio of the above-mentioned preset wind and solar installed capacity to the above-mentioned electrolyzer power is determined as the number of electrolyzers. It should be noted that when the ratio is a non-integer, it needs to be rounded up as the number of electrolyzers.

[0050] The third step is to obtain the hydrogen storage tank attribute information corresponding to the hydrogen storage tank identification. The above hydrogen storage tank identification may be a unique identification of the hydrogen storage tank. The above hydrogen storage tank attribute information may characterize the attributes of the hydrogen storage tank. The above hydrogen storage tank attribute information may include but is not limited to the hydrogen storage tank identification and the tank hydrogen storage capacity. The tank hydrogen storage capacity may be the hydrogen that each hydrogen storage tank can store. The unit of the tank hydrogen storage capacity may be cubic meters. In practice, the above execution entity may obtain the hydrogen storage tank attribute information corresponding to the hydrogen storage tank identification from the database through a wired connection or a wireless connection.

[0051] The fourth step is to generate the number of hydrogen storage tanks according to the above-mentioned daily hydrogen production of abandoned electricity and the above-mentioned hydrogen storage tank attribute information. In practice, the above-mentioned execution entity can determine the ratio of the above-mentioned daily hydrogen production of abandoned electricity to the spherical tank hydrogen storage capacity included in the above-mentioned hydrogen storage tank attribute information as the number of hydrogen storage tanks. It should be noted that when the ratio is a non-integer, it needs to be rounded up as the number of electrolyzers.

[0052] The fifth step is to obtain the gas turbine attribute information corresponding to the pure hydrogen gas turbine identifier. Among them, the pure hydrogen gas turbine identifier can be a unique identifier of the pure hydrogen gas turbine. The above-mentioned gas turbine attribute information can characterize the attributes of the pure hydrogen gas turbine. The above-mentioned gas turbine attribute information may include but is not limited to the gas turbine power and the pure hydrogen gas turbine heat rate. The above-mentioned gas turbine power may be the power of the pure hydrogen gas turbine. The above-mentioned pure hydrogen gas turbine heat rate may be the heat consumed by the pure hydrogen gas turbine for every kilowatt-hour of electricity generated. In practice, the above-mentioned execution entity can obtain the gas turbine attribute information corresponding to the pure hydrogen gas turbine identifier from the database through a wired connection or a wireless connection.

[0053] The sixth step is to generate the daily operating time of the gas turbine according to the above-mentioned daily hydrogen production due to abandoned power and the above-mentioned gas turbine attribute information. In practice, first, the above-mentioned execution entity may determine the product of the ratio of the heat consumption rate of the pure hydrogen gas turbine included in the above-mentioned gas turbine attribute information to the preset hydrogen volume calorific value and the gas turbine power included in the above-mentioned gas turbine attribute information as the hydrogen consumption per unit time of the gas turbine. Among them, the above-mentioned preset hydrogen volume calorific value may be a preset hydrogen volume calorific value. The above-mentioned hydrogen consumption per unit time of the gas turbine may be the amount of hydrogen consumed per hour by the pure hydrogen gas turbine. Then, the ratio of the above-mentioned daily hydrogen production due to abandoned power to the above-mentioned hydrogen consumption per unit time of the gas turbine is determined as the daily operating time of the gas turbine.

[0054] Step 105: Generate the number of gas turbines according to the daily operation time of the gas turbines.

[0055] In some embodiments, the execution subject may generate the number of gas turbines according to the daily operation time of the gas turbines. The number of gas turbines may be the number of pure hydrogen gas turbines included in the pure hydrogen gas turbine energy storage system to be configured. In practice, the execution subject may generate the number of gas turbines according to the daily operation time of the gas turbines in various ways.

[0056] In some optional implementations of some embodiments, the execution subject may generate the number of gas turbines according to the daily operation time of the gas turbines through the following steps:

[0057] The first step is to determine the target daily peak-shaving duration corresponding to the target wind and solar power station. The target daily peak-shaving duration may be the peak-shaving duration of the target wind and solar power station every day. In practice, the execution entity may determine the target daily peak-shaving duration corresponding to the target wind and solar power station in various ways.

[0058] The second step is to determine the ratio of the daily operating time of the gas turbine to the target daily peak load shaving time as the number of gas turbines. It should be noted that when the ratio is not an integer, it needs to be rounded up as the number of gas turbines.

[0059] In some optional implementations of some embodiments, the execution subject may determine the daily peak load duration corresponding to the target wind and solar power station through the following steps:

[0060] The first step is to obtain the set of historical daily peak-shaving durations corresponding to the above-mentioned target wind and solar power stations. The historical daily adjustment duration included in the above-mentioned historical daily peak-shaving duration set can be the peak-shaving duration of the target wind and solar power station on the historical date. In practice, the above-mentioned execution entity can obtain the set of historical daily peak-shaving durations corresponding to the above-mentioned target wind and solar power stations from the database through a wired connection or a wireless connection.

[0061] In the second step, the average value of the peak-shaving durations of each historical day included in the above-mentioned historical daily peak-shaving duration set is determined as the average peak-shaving duration.

[0062] In the third step, each historical daily peak-shaving duration in the above historical daily peak-shaving duration set that is greater than the above average peak-shaving duration is determined as a target historical daily peak-shaving duration group.

[0063] In the fourth step, the average value of the target historical daily peak-shaving durations included in the above target historical daily peak-shaving duration group is determined as the target daily peak-shaving duration.

[0064] Step 106: Generate energy storage system charging value information based on the daily operating time of the gas turbine.

[0065] In some embodiments, the execution entity may generate the energy storage system collection value information based on the daily operation time of the gas turbine. The energy storage system collection value information may be the collection value information (e.g., revenue) obtained during the operation of the pure hydrogen gas turbine energy storage system. In practice, the execution entity may generate the energy storage system collection value information based on the daily operation time of the gas turbine in various ways.

[0066] In some optional implementations of some embodiments, the execution subject may generate the energy storage system charging value information according to the daily operation time of the gas turbine through the following steps:

[0067] In the first step, the product of the daily operation time of the gas turbine and the preset annual peak-shaving days is determined as the annual peak-shaving time. The preset annual peak-shaving days can be the preset number of days in a year for the target wind and solar power station to perform peak-shaving. For example, the preset annual peak-shaving days can be 365 days.

[0068] The second step is to obtain the gas turbine power corresponding to the pure hydrogen gas turbine identification. In practice, the above execution subject can obtain the gas turbine power corresponding to the pure hydrogen gas turbine identification from the database through a wired connection or a wireless connection.

[0069] The third step is to determine the annual gas turbine peak-shaving power as the product of the annual peak-shaving time, the gas turbine power and the number of gas turbines.

[0070] The fourth step is to obtain the historical peak-shaving electricity value information set. The historical peak-shaving electricity value information included in the historical peak-shaving electricity value information set may be the peak-shaving electricity value information at a historical time point (e.g., peak-shaving electricity price). The peak-shaving electricity value information may be the electricity value information (e.g., electricity price) during the peak-shaving period. In practice, the execution entity may obtain the historical peak-shaving electricity value information set from the database via a wired connection or a wireless connection.

[0071] The fifth step is to generate average peak-shaving electricity value information based on the historical peak-shaving electricity value information set. In practice, the execution entity may determine the average value of each historical peak-shaving electricity value information included in the historical peak-shaving electricity value information set as the average peak-shaving electricity value information.

[0072] Step 6: Generate the gas turbine peak-shaving value information based on the annual gas turbine peak-shaving power and the average peak-shaving power value information. In practice, the execution entity may determine the gas turbine peak-shaving value information as the product of the annual gas turbine peak-shaving power and the average peak-shaving power value information.

[0073] The seventh step is to generate carbon dioxide collection value information based on the above-mentioned annual gas turbine peak-shaving power, the preset average carbon dioxide emission factor of electricity and the preset carbon dioxide unit value information. Among them, the above-mentioned preset average carbon dioxide emission factor of electricity can be the preset carbon dioxide emissions per unit power generation of the target wind and solar power station. The above-mentioned preset carbon dioxide unit value information can be the preset value information (such as price) of carbon dioxide per ton. In practice, the above-mentioned execution entity can determine the product of the above-mentioned annual gas turbine peak-shaving power, the preset average carbon dioxide emission factor of electricity and the preset carbon dioxide unit value information as the carbon dioxide collection value information.

[0074] Step 8: Generate capacity compensation value information based on the gas turbine power and the preset unit capacity compensation value information. The preset unit capacity compensation value information may be the preset capacity electricity value information (capacity electricity price) per kilowatt per year. In practice, the execution entity may determine the product of the gas turbine power and the preset unit capacity compensation value information as the capacity compensation value information.

[0075] The ninth step is to generate the energy storage system charging value information based on the gas turbine peak-shaving charging value information, the carbon dioxide charging value information and the capacity compensation charging value information. In practice, the execution entity may determine the sum of the gas turbine peak-shaving charging value information, the carbon dioxide charging value information and the capacity compensation charging value information as the energy storage system charging value information.

[0076] Step 107, collecting value information based on the number of electrolyzers, the number of hydrogen storage tanks, the number of gas turbines and the energy storage system, and controlling each associated installation device to perform each equipment installation operation.

[0077] In some embodiments, the execution subject may control the associated installation devices to perform the installation operations of the devices according to the value information collected by the number of electrolyzers, the number of hydrogen storage tanks, the number of gas turbines, and the energy storage system. Among them, the installation devices in the installation devices may correspond to the energy storage devices included in the energy storage devices. The installation device may be a device for installing the corresponding energy storage device. For example, the installation device may be an industrial robot. The installation device may also be an automated installation device or a semi-automated installation device that requires manual operation by the installer. As an example, when the installation device is a semi-automated installation device that requires manual operation by the installer, the control of the associated installation devices to perform the installation operations of the devices may be instruction control. That is, the execution subject may determine the installation operation corresponding to the installation information in response to the installation information corresponding to the installation device identification sent by the installation user terminal. Among them, the installation user terminal may be the terminal of the installer. The installation device identification may be a unique identification of the installation device. The installation information may include, but is not limited to, the installation component identification and the installation location information. The installation component identification may be a unique identification of the installation component. The installation component may be a component included in the corresponding energy storage device. For example, when the energy storage device corresponding to the installation device is a hydrogen storage spherical tank, the installation component may be a "hydrogen storage spherical tank body". The above-mentioned hydrogen storage spherical tank body may be the tank body of the hydrogen storage spherical tank. The above-mentioned installation location information represents the location where the corresponding installation component needs to be installed. The above-mentioned installation location information may include but is not limited to installation coordinates. The above-mentioned installation coordinates may be the coordinates of the first installation point of the above-mentioned installation component in the installation coordinate system. The above-mentioned installation coordinate system may be a three-dimensional space coordinate system with the installation device as the origin. Then, the installation device corresponding to the above-mentioned installation device identification is controlled to perform the installation operation corresponding to the above-mentioned installation information. Among them, the above-mentioned installation operation corresponding to the above-mentioned installation information may be: the installation device performs the operation corresponding to the pre-set instruction of the component corresponding to the installation component identification included in the above-mentioned installation information. The above-mentioned equipment installation operation may be the operation of installing the corresponding energy storage device in the above-mentioned target wind and solar power station. In practice, the above-mentioned execution subject can collect value information according to the number of the above-mentioned electrolyzers, the number of the above-mentioned hydrogen storage spherical tanks, the number of the above-mentioned gas turbines and the above-mentioned energy storage system in various ways, and control the associated various installation devices to perform various equipment installation operations.

[0078] For the second technical problem in the background technology, the following solution can be adopted:

[0079] In some optional implementations of some embodiments, the execution subject may collect value information according to the number of electrolyzers, the number of hydrogen storage spherical tanks, the number of gas turbines, and the energy storage system, and control the associated installation equipment to perform various equipment installation operations through the following steps:

[0080] The first step is to generate equipment investment value information based on the number of electrolytic cells, the number of hydrogen storage spherical tanks and the number of gas turbines. The equipment investment value information may be the value information (e.g., price) required to obtain (e.g., purchase) each energy storage device. In practice, the execution entity may determine the sum of the product of the number of electrolytic cells and the preset electrolytic cell unit acquisition value information (e.g., electrolytic cell purchase price), the product of the number of hydrogen storage spherical tanks and the preset hydrogen storage spherical tank unit acquisition value information (e.g., hydrogen storage spherical tank purchase price), and the product of the number of gas turbines and the preset gas turbine unit acquisition value information (e.g., gas turbine purchase price) as the equipment investment value information.

[0081] The second step is to obtain the power station location information of the target wind and solar power station. The power station location information can represent the location of the target wind and solar power station. The power station location information can include but is not limited to altitude and terrain type. The terrain type can be but is not limited to one of the following: plain, mountainous area, plateau, sea area. In practice, the execution entity can obtain the power station location information of the target wind and solar power station from the database through a wired connection or a wireless connection.

[0082] The third step is to input the power station location information into the pre-trained electrolytic cell unit installation investment value growth information generation model to obtain the electrolytic cell unit installation investment value growth information. The electrolytic cell unit installation investment value growth information generation model may be a neural network with the power station location information as input and the electrolytic cell unit installation investment value growth information as output. The neural network may be a convolutional neural network. The electrolytic cell unit installation investment value growth information may be the additional investment value information (e.g., investment amount) required to transport and install each electrolytic cell.

[0083] The fourth step is to input the power station location information into the pre-trained hydrogen storage tank unit installation investment value growth information generation model to obtain the hydrogen storage tank unit installation investment value growth information. The hydrogen storage tank unit installation investment value growth information generation model can be a neural network with the power station location information as input and the hydrogen storage tank unit installation investment value growth information as output. The neural network can be a recurrent neural network. The hydrogen storage tank unit installation investment value growth information can be the additional investment value information (such as the investment amount) required to transport and install each hydrogen storage tank.

[0084] In the fifth step, the power station location information is input into the pre-trained gas turbine unit installation investment value growth information generation model to obtain the gas turbine unit installation investment value growth information. The gas turbine unit installation investment value growth information generation model may be a neural network that takes the power station location information as input and the gas turbine unit installation investment value growth information as output. The neural network may be a convolutional neural network. The gas turbine unit installation investment value growth information may be the additional investment value information (e.g., investment amount) required to transport and install each gas turbine.

[0085] The sixth step is to determine the number of each type of transport equipment corresponding to each type of equipment to be transported according to the number of electrolyzers, the number of hydrogen storage spherical tanks and the number of gas turbines. Among them, the type of equipment to be transported in the above-mentioned types of equipment to be transported can be the type of equipment waiting to be transported. The above-mentioned types of equipment to be transported can include but are not limited to electrolyzers, hydrogen storage spherical tanks, gas turbines, and installation equipment. Each type of equipment to be transported corresponds to a number of transport equipment. The number of transport equipment can be the number of transport equipment required for transporting the equipment corresponding to the type of equipment to be transported. The above-mentioned transport equipment can be a vehicle for transportation. In practice, the above-mentioned execution subject can determine the number of transport equipment corresponding to the electrolyzer by multiplying the preset number of transport equipment per unit of the electrolyzer and the number of the above-mentioned electrolyzers in response to determining that the type of equipment to be transported is an electrolyzer. Among them, the above-mentioned preset number of transport equipment per unit of the electrolyzer can be the number of transport equipment required for each transport of an electrolyzer set in advance. The above-mentioned execution subject can determine the number of transport equipment corresponding to the hydrogen storage spherical tank by multiplying the preset number of transport equipment per unit of the hydrogen storage spherical tank and the number of the above-mentioned hydrogen storage spherical tanks in response to determining that the type of equipment to be transported is a hydrogen storage spherical tank. Wherein, the preset number of unit transport equipment for hydrogen storage spherical tanks may be the preset number of transport equipment required for each transport of hydrogen storage spherical tank. The above-mentioned execution subject may, in response to determining that the type of the above-mentioned equipment to be transported is a gas turbine, determine the product of the preset number of unit transport equipment for gas turbines and the number of gas turbines as the number of transport equipment corresponding to the gas turbine. Wherein, the preset number of unit transport equipment for gas turbines may be the preset number of transport equipment required for each transport of gas turbines. The above-mentioned execution subject may, in response to determining that the type of the above-mentioned equipment to be transported is an installation device, determine the sum of the number of electrolyzers, the number of hydrogen storage spherical tanks and the number of gas turbines as the number of energy storage equipment. Then, the product of the preset number of unit transport equipment corresponding to the installation equipment and the number of energy storage equipment is determined as the number of transport equipment corresponding to the installation equipment. Wherein, the preset number of unit transport equipment corresponding to the installation equipment may be: the preset number of transport equipment required for each transport of the installation equipment.

[0086] The seventh step is to input the number of each of the above-mentioned transportation equipment, the number of the above-mentioned electrolyzers, the number of the above-mentioned hydrogen storage tanks, and the number of the above-mentioned gas turbines into the preset energy storage system configuration basic investment value information generation model to obtain the energy storage system configuration basic investment value information. Among them, the preset energy storage system configuration basic investment value information generation model can be a pre-set linear function with the number of each of the above-mentioned transportation equipment, the number of the above-mentioned electrolyzers, the number of the above-mentioned hydrogen storage tanks, and the number of the above-mentioned gas turbines as inputs and the energy storage system configuration basic investment value information as output. The above-mentioned energy storage system configuration basic investment value information can be the investment value information (such as the investment amount) required to configure a pure hydrogen gas turbine energy storage system on a plain. It should be noted that the above-mentioned configuration may include actions such as transportation, installation, and maintenance.

[0087] In the eighth step, the product of the above-mentioned electrolytic cell unit installation investment value growth information and the above-mentioned number of electrolytic cells is determined as the electrolytic cell installation investment value growth information.

[0088] The ninth step is to determine the hydrogen storage spherical tank installation investment value growth information as the hydrogen storage spherical tank installation investment value growth information by multiplying the above-mentioned hydrogen storage spherical tank quantity.

[0089] The tenth step is to determine the gas turbine installation investment value growth information as the product of the above-mentioned gas turbine unit installation investment value growth information and the above-mentioned gas turbine quantity.

[0090] The eleventh step is to generate the energy storage system investment value information based on the above equipment investment value information, the above energy storage system configuration basic investment value information, the above electrolyzer installation investment value growth information, the above hydrogen storage spherical tank installation investment value growth information and the above gas turbine installation investment value growth information. In practice, the above execution entity may determine the sum of the above equipment investment value information, the above energy storage system configuration basic investment value information, the above electrolyzer installation investment value growth information, the above hydrogen storage spherical tank installation investment value growth information and the above gas turbine installation investment value growth information as the energy storage system investment value information. Among them, the above energy storage system investment value information may be the investment value information (such as investment cost) required to install and operate a pure hydrogen gas turbine energy storage system.

[0091] Step 12: Generate a value recovery period based on the energy storage system input value information and the energy storage system collection value information. The value recovery period may be the time required for the pure hydrogen gas turbine energy storage system to collect net value information (such as net profit). The value recovery period may be expressed in years. In practice, the execution entity may determine the value recovery period as the ratio of the energy storage system input value information to the energy storage system collection value information.

[0092] Step 13, generate installation verification information based on the above-mentioned value recovery time. In practice, the above-mentioned execution entity can determine the preset verification pass information as the installation verification information in response to determining that the above-mentioned value recovery time is greater than or equal to the preset value recovery time. Among them, the above-mentioned preset value recovery time can be a preset value recovery time that characterizes the configuration of a pure hydrogen gas turbine energy storage system that is feasible. The above-mentioned preset verification pass information can be preset information that characterizes that a pure hydrogen gas turbine energy storage system can be configured. For example, the above-mentioned preset verification pass information can be "1".

[0093] In the fourteenth step, in response to determining that the above-mentioned installation verification information satisfies the preset verification conditions, according to the above-mentioned number of each transportation equipment, the transportation equipment scheduling operation and the equipment transportation operation are executed. Among them, the above-mentioned preset verification condition may be: the above-mentioned preset verification passes the information characterization that the pure hydrogen gas turbine energy storage system can be configured. The above-mentioned computing equipment scheduling operation may be an operation of scheduling transportation equipment. The above-mentioned equipment transportation operation may be an operation of transporting each energy storage equipment and installation equipment from the corresponding warehouse to the above-mentioned target wind and solar power station. In practice, for each type of equipment to be transported, the above-mentioned execution subject may dispatch the corresponding number of transportation equipment to the warehouse where the equipment corresponding to the above-mentioned type of equipment to be transported is located, and control the number of transportation equipment to transport the equipment corresponding to the above-mentioned type of equipment to be transported to the above-mentioned target wind and solar power station.

[0094] Step 15: In response to detecting the transport completion information, control the associated installation equipment to perform various equipment installation operations. The transport completion information may represent the information that the transport of the electrolyzer, hydrogen storage spherical tank, gas turbine and installation equipment is completed. For example, the transport completion information may be: "finish".

[0095] The above technical solution and its related contents, as an inventive point of an embodiment of the present disclosure, solve the second technical problem mentioned in the background technology: "Wind and solar power stations in different locations have different installation difficulties when transporting and installing different energy storage devices. Only by determining the number of equipment and the pre-set value information required for installing and operating and maintaining a single device, the influence of the location of the wind and solar power station on transportation and installation is not considered, resulting in low accuracy of the generated total equipment value information, which leads to low accuracy of the verification result used to determine whether to configure a pure hydrogen gas turbine energy storage system, and further causes a waste of installation resources and transportation resources. If the above factors are solved, the effect of saving installation resources and transportation resources can be achieved. In order to To achieve this effect, the pure hydrogen gas turbine energy storage system installation method disclosed in the present invention takes into account the impact of the location of the wind and solar power stations on the transportation and installation value information (such as investment cost) when determining the value information required for transporting and installing each energy storage device. For different energy storage devices, by training corresponding models, according to the location of the target wind and solar power stations, the value information required to increase the transportation and installation value information (such as investment cost) compared to the plain location is determined, and then the final required value information is determined, thereby improving the accuracy of the generated energy storage system investment value information, and then improving the accuracy of the verification results for determining whether to configure a pure hydrogen gas turbine energy storage system, thereby saving installation resources and energy.

[0096] When adopting a technical solution to solve the second technical problem in the background technology, the following problem often arises: how to determine the value information (such as operation and maintenance costs) required for the subsequent operation and maintenance of each energy storage device. In response to these problems, the conventional solution is generally: to determine according to the number of each energy storage device and in accordance with past historical experience. However, the above solution has the following technical problem three: wind and solar power stations in different locations encounter different phenomena and frequencies of natural disasters in actual scenarios. Each energy storage device installed in different locations uses the value information required for operation and maintenance of the same corresponding number of devices, resulting in a lower accuracy of the total value information required to generate the configuration of the pure hydrogen gas turbine energy storage system, resulting in a lower accuracy of the verification result used to determine whether to configure the pure hydrogen gas turbine energy storage system, which in turn leads to a waste of installation resources or transportation resources.

[0097] For technical problem three, the following solutions can be adopted:

[0098] Optionally, the power station location information may further include power station location coordinates. The power station location coordinates may be coordinates of the target wind and solar power station in the earth coordinate system. For example, the power station coordinates may be the longitude and latitude coordinates of the target wind and solar power station.

[0099] In some optional implementations of some embodiments, the execution subject may generate installation verification information according to the value recovery period through the following steps:

[0100] The first step is to obtain a historical natural disaster information set corresponding to the position coordinates of the power station in the target historical time period. The target historical time period may be a time period corresponding to the target historical time point to the current time. The target historical time point may be a historical time point whose interval with the current time is the value recovery time. The historical natural disaster information set corresponds to each preset natural disaster type. The historical natural disaster information set in the historical natural disaster information set may correspond to the preset natural disaster type in each preset natural disaster type. The preset natural disaster type in each preset natural disaster type may be a pre-set natural disaster type. The natural disaster type may be, but not limited to, one of the following: sandstorm, earthquake, mountain torrent, tsunami. The historical natural disaster information in the historical natural disaster information set may be information on the occurrence of the corresponding preset natural disaster type at the location of the target power station at the corresponding historical time point. The historical natural disaster information may include, but not limited to, the time of the natural disaster, the type of natural disaster, and the disaster level. The natural disaster time may be the time when the natural disaster occurs. The disaster level may characterize the severity of the natural disaster. The disaster level may be, but not limited to, one of the following: a first-level disaster, a second-level disaster, or a third-level disaster. It should be noted that the higher the disaster level, the more serious the disaster. In practice, the execution subject may obtain the historical natural disaster information set corresponding to the power station location information in the target historical time period from the database through a wired connection or a wireless connection.

[0101] In the second step, for each historical natural disaster information group included in the above historical natural disaster information group set, the following sub-steps are performed:

[0102] The first sub-step is to determine the number of each historical natural disaster information included in the above historical natural disaster information group as the number of natural disasters.

[0103] In the second sub-step, the preset natural disaster type corresponding to the historical natural disaster information group among the preset natural disaster types is determined as the target natural disaster type.

[0104] In the third sub-step, the preset risk score corresponding to the above-mentioned target natural disaster type in the preset risk score set is determined as the target risk score. Among them, the preset risk score in the above-mentioned preset risk score set corresponds to a preset natural disaster type. The preset risk score can represent the degree of harm to the pure hydrogen gas turbine energy storage system caused by a natural disaster of a preset natural disaster type. It should be noted that the more serious the degree of harm, the higher the preset risk score.

[0105] The fourth sub-step is to determine the preset risk coefficient corresponding to the above-mentioned number of natural disasters in the preset risk coefficient set as the target risk coefficient. Each preset risk coefficient in the above-mentioned preset risk coefficient set corresponds to a preset range of natural disaster numbers. The preset risk coefficient corresponding to the above-mentioned number of natural disasters may be: the corresponding preset range of natural disaster numbers includes the above-mentioned number of natural disasters. The range of the above-mentioned preset number of natural disasters may be a preset range of natural disaster numbers. The preset risk coefficient may be a preset coefficient that characterizes the degree of harm of natural disasters to the pure hydrogen gas turbine energy storage system. The larger the number of natural disasters, the larger the preset risk coefficient.

[0106] The fifth sub-step is to determine the product of the target risk score and the target risk coefficient as the risk score.

[0107] The third step is to determine the sum of the determined risk scores as the natural disaster risk score.

[0108] The fourth step is to determine the preset recovery time risk score corresponding to the above value recovery time in the preset recovery time risk score set as the value risk score. The preset recovery time risk score in the above preset recovery time risk score set can represent the degree of value risk existing in the corresponding preset value recovery time.

[0109] The fifth step is to determine the total risk score as the sum of the above natural disaster risk score and the above value risk score.

[0110] In step 6, in response to determining that the total risk score satisfies the preset value safety condition, the preset verification pass information is determined as the installation verification information. The preset value safety condition may be that the total risk is less than or equal to the preset risk score. The preset risk score may be a pre-set risk score indicating that the installation of each energy storage device included in the pure hydrogen gas turbine energy storage system is not feasible.

[0111] The above technical solution and its related contents, as an inventive point of the embodiment of the present disclosure, solve the technical problem three mentioned in the background technology: "Wind and solar power stations at different locations encounter different phenomena and frequencies of natural disasters in actual scenarios. The various energy storage devices installed at different locations use the value information required for operation and maintenance of the same number of corresponding devices, resulting in a low accuracy of the total value information generated for configuring the pure hydrogen gas turbine energy storage system, which results in a low accuracy of the verification result used to determine whether to configure the pure hydrogen gas turbine energy storage system, and further leads to a waste of installation resources or transportation resources. If the above factors are solved, the effect of saving installation resources and transportation resources can be achieved. In order to achieve this effect, the pure hydrogen gas turbine energy storage system installation method disclosed in the present disclosure estimates the possibility of various natural disasters occurring at the location of the target wind and solar power station within the estimated future value recovery time, and determines the verification result of whether to configure the pure hydrogen gas turbine energy storage system in combination with the estimated value recovery time, thereby improving the accuracy of the verification result of whether to configure the pure hydrogen gas turbine energy storage system, thereby saving installation resources and transportation resources.

[0112] The above-mentioned embodiments of the present disclosure have the following beneficial effects: the installation resources and energy can be saved by the installation method of the pure hydrogen gas turbine energy storage system of some embodiments of the present disclosure. Specifically, the reason for the waste of configuration resources and installation resources or energy waste is that the change of annual abandoned power is directly affected by the annual power generation and the annual online power. The annual abandoned power in the future time period is estimated only based on the historical annual abandoned power, resulting in the low accuracy of the estimated annual abandoned power, resulting in the low accuracy of the number of each device of each energy storage device determined. When the estimated number of devices is higher than the actual number of devices required, it causes a waste of installation resources. When the estimated number of devices is lower than the actual number of devices required, it causes energy waste. Based on this, the installation method of the pure hydrogen gas turbine energy storage system of some embodiments of the present disclosure, first, obtain the historical annual power generation information and the historical annual online power sequence of the target wind and solar power station. Thus, the power generation information and online power information of the wind and solar power station to be configured in the historical time period can be obtained, so as to estimate the abandoned power information of the wind and solar power station to be configured. Secondly, according to the above-mentioned historical annual power generation information and the above-mentioned historical annual online power sequence, the estimated annual abandoned power information is generated. Therefore, the annual power generation and annual power abandonment of the wind and solar power station can be comprehensively considered to estimate the information of the annual power abandonment of the wind and solar power station to be configured, so as to improve the accuracy of the estimated annual power abandonment. Then, based on the above-mentioned estimated annual power abandonment information, the daily hydrogen production of abandoned power is generated. Thus, the amount of hydrogen that can be produced by the daily abandoned power can be obtained, which can be used to determine the number of each device included in the pure hydrogen gas turbine energy storage system to be configured. Afterwards, based on the above-mentioned daily hydrogen production of abandoned power, the number of electrolyzers, the number of hydrogen storage spherical tanks and the daily operating time of the gas turbine corresponding to the pure hydrogen gas turbine energy storage system to be configured are generated. Thus, the number of each energy storage device included in the pure hydrogen gas turbine energy storage system to be configured can be obtained, which can be used to determine whether to install each energy storage device included in the pure hydrogen gas turbine energy storage system to be configured. Then, based on the above-mentioned daily operating time of the gas turbine, the value information collected by the energy storage system is generated. Thus, the value information that can be obtained by configuring the pure hydrogen gas turbine energy storage system can be obtained, and thus the value information required for configuring the pure hydrogen gas turbine energy storage system can be obtained, which can be used to determine whether to install the various energy storage devices included in the pure hydrogen gas turbine energy storage system to be configured. Finally, according to the value information collected based on the number of electrolyzers, the number of hydrogen storage tanks, the number of gas turbines, and the energy storage system, the associated installation devices are controlled to perform various equipment installation operations. Thus, the various energy storage devices included in the pure hydrogen gas turbine energy storage system can be installed, so that they can be used to store energy.Also, when installing the various energy storage devices included in the pure hydrogen gas turbine energy storage system, the annual power abandonment is estimated by the power generation and grid-connected capacity of the wind and solar power stations in historical time periods, thereby improving the accuracy of the estimated annual power abandonment. Then, the value recovery time is estimated based on actual conditions, thereby improving the accuracy of the number of various energy storage devices included in the pure hydrogen gas turbine energy storage system, thereby saving installation resources and energy.

[0113] Further references Figure 2 As an implementation of the methods shown in the above figures, the present disclosure provides some embodiments of a pure hydrogen gas turbine energy storage system installation device. These device embodiments are similar to Figure 1 Corresponding to the method embodiments shown, the device can be specifically applied to various electronic devices.

[0114] like Figure 2 As shown, a pure hydrogen gas turbine energy storage system installation device 200 of some embodiments includes: an acquisition unit 201 , a first generation unit 202 , a second generation unit 203 , a third generation unit 204 , a fourth generation unit 205 , a fifth generation unit 206 and a control unit 207 . Among them, the acquisition unit 201 is configured to acquire the historical annual available power generation information and the historical annual grid-connected power sequence of the target wind and solar power station; the first generation unit 202 is configured to generate the estimated annual abandoned power information based on the above-mentioned historical annual available power generation information and the above-mentioned historical annual grid-connected power sequence; the second generation unit 203 is configured to generate the daily hydrogen production of abandoned power based on the above-mentioned estimated annual abandoned power information; the third generation unit 204 is configured to generate the number of electrolyzers, the number of hydrogen storage spherical tanks and the daily operating time of the gas turbine corresponding to the pure hydrogen gas turbine energy storage system to be configured according to the above-mentioned daily hydrogen production of abandoned power; the fourth generation unit 205 is configured to generate the number of gas turbines according to the daily operating time of the above-mentioned gas turbine; the fifth generation unit 206 is configured to generate the value information collected by the energy storage system according to the daily operating time of the above-mentioned gas turbine; the control unit 209 is configured to control the associated installation equipment to perform various equipment installation operations based on the above-mentioned number of electrolyzers, the above-mentioned number of hydrogen storage spherical tanks, the above-mentioned number of gas turbines and the above-mentioned energy storage system collection value information.

[0115] It is understood that the units described in the device 200 are similar to those described in the reference Figure 1 Therefore, the operations, features and beneficial effects described above for the method are also applicable to the device 200 and the units included therein, and will not be described in detail here.

[0116] Reference below Figure 3, which shows a schematic diagram of the structure of an electronic device 300 suitable for implementing some embodiments of the present disclosure. The electronic devices in some embodiments of the present disclosure may include but are not limited to mobile terminals such as mobile phones, laptop computers, digital broadcast receivers, PDAs (personal digital assistants), PADs (tablet computers), PMPs (portable multimedia players), vehicle terminals (such as vehicle navigation terminals), etc., and fixed terminals such as digital TVs, desktop computers, etc. Figure 3 The electronic device shown is only an example and should not bring any limitation to the functions and scope of use of the embodiments of the present disclosure.

[0117] like Figure 3 As shown, the electronic device 300 may include a processing device (e.g., a central processing unit, a graphics processing unit, etc.) 301, which can perform various appropriate actions and processes according to a program stored in a read-only memory (ROM) 302 or a program loaded from a storage device 308 into a random access memory (RAM) 303. In the RAM 303, various programs and data required for the operation of the electronic device 300 are also stored. The processing device 301, the ROM 302, and the RAM 303 are connected to each other via a bus 304. An input / output (I / O) interface 305 is also connected to the bus 304.

[0118] Typically, the following devices may be connected to the I / O interface 305: input devices 306 including, for example, a touch screen, a touch pad, a keyboard, a mouse, a camera, a microphone, an accelerometer, a gyroscope, etc.; output devices 307 including, for example, a liquid crystal display (LCD), a speaker, a vibrator, etc.; storage devices 308 including, for example, a magnetic tape, a hard disk, etc.; and communication devices 309. The communication devices 309 may allow the electronic device 300 to communicate with other devices wirelessly or by wire to exchange data. Although Figure 3 The electronic device 300 is shown with various devices, but it should be understood that it is not required to implement or possess all the devices shown. More or fewer devices may be implemented or possessed instead. Figure 3 Each block shown in the figure may represent one device, or may represent multiple devices as required.

[0119] In particular, according to some embodiments of the present disclosure, the process described above with reference to the flowchart can be implemented as a computer software program. For example, some embodiments of the present disclosure include a computer program product, which includes a computer program carried on a computer-readable medium, and the computer program includes a program code for executing the method shown in the flowchart. In some such embodiments, the computer program can be downloaded and installed from the network through the communication device 309, or installed from the storage device 308, or installed from the ROM 302. When the computer program is executed by the processing device 301, the above-mentioned functions defined in the method of some embodiments of the present disclosure are executed.

[0120] It should be noted that the computer-readable medium recorded in some embodiments of the present disclosure may be a computer-readable signal medium or a computer-readable storage medium or any combination of the above two. The computer-readable storage medium may be, for example, but not limited to, an electrical, magnetic, optical, electromagnetic, infrared, or semiconductor system, device or device, or any combination of the above. More specific examples of computer-readable storage media may include, but are not limited to: an electrical connection with one or more wires, a portable computer disk, a hard disk, a random access memory (RAM), a read-only memory (ROM), an erasable programmable read-only memory (EPROM or flash memory), an optical fiber, a portable compact disk read-only memory (CD-ROM), an optical storage device, a magnetic storage device, or any suitable combination of the above. In some embodiments of the present disclosure, a computer-readable storage medium may be any tangible medium containing or storing a program that can be used by or in combination with an instruction execution system, device or device. In some embodiments of the present disclosure, a computer-readable signal medium may include a data signal propagated in a baseband or as part of a carrier wave, which carries a computer-readable program code. This propagated data signal may take a variety of forms, including but not limited to electromagnetic signals, optical signals, or any suitable combination of the above. The computer readable signal medium may also be any computer readable medium other than a computer readable storage medium, which may send, propagate or transmit a program for use by or in conjunction with an instruction execution system, apparatus or device. The program code contained on the computer readable medium may be transmitted using any suitable medium, including but not limited to: wires, optical cables, RF (radio frequency), etc., or any suitable combination of the above.

[0121] In some embodiments, the client and the server may communicate using any currently known or future developed network protocol such as HTTP (Hyper Text Transfer Protocol), and may be interconnected with any form or medium of digital data communication (e.g., a communication network). Examples of communication networks include a local area network ("LAN"), a wide area network ("WAN"), an internet (e.g., the Internet), and a peer-to-peer network (e.g., an ad hoc peer-to-peer network), as well as any currently known or future developed network.

[0122] The computer-readable medium may be included in the electronic device; or it may exist independently without being installed in the electronic device. The computer-readable medium carries one or more programs. When the one or more programs are executed by the electronic device, the electronic device: obtains the historical annual available power generation information and the historical annual online power sequence of the target wind and solar power station; generates the estimated annual abandoned power information based on the historical annual available power generation information and the historical annual online power sequence; generates the abandoned power daily hydrogen production based on the estimated annual abandoned power information; generates the number of electrolyzers, the number of hydrogen storage spherical tanks and the daily operating time of the gas turbine corresponding to the pure hydrogen gas turbine energy storage system to be configured based on the abandoned power daily hydrogen production; generates the number of gas turbines based on the daily operating time of the gas turbine; generates the energy storage system collection value information based on the daily operating time of the gas turbine; controls the associated installation equipment to perform the installation operations of each equipment based on the number of electrolyzers, the number of hydrogen storage spherical tanks, the number of gas turbines and the energy storage system collection value information.

[0123] Computer program code for performing the operations of some embodiments of the present disclosure may be written in one or more programming languages ​​or a combination thereof, including object-oriented programming languages ​​such as Java, Smalltalk, C++, and conventional procedural programming languages ​​such as "C" or similar programming languages. The program code may be executed entirely on the user's computer, partially on the user's computer, as a separate software package, partially on the user's computer and partially on a remote computer, or entirely on a remote computer or server. In cases involving a remote computer, the remote computer may be connected to the user's computer via any type of network, including a local area network (LAN) or a wide area network (WAN), or may be connected to an external computer (e.g., via the Internet using an Internet service provider).

[0124] The flow chart and block diagram in the accompanying drawings illustrate the possible architecture, function and operation of the system, method and computer program product according to various embodiments of the present disclosure. In this regard, each square box in the flow chart or block diagram can represent a module, a program segment or a part of a code, and the module, the program segment or a part of the code contains one or more executable instructions for realizing the specified logical function. It should also be noted that in some implementations as replacements, the functions marked in the square box can also occur in a sequence different from that marked in the accompanying drawings. For example, two square boxes represented in succession can actually be executed substantially in parallel, and they can sometimes be executed in the opposite order, depending on the functions involved. It should also be noted that each square box in the block diagram and / or flow chart, and the combination of the square boxes in the block diagram and / or flow chart can be implemented with a dedicated hardware-based system that performs a specified function or operation, or can be implemented with a combination of dedicated hardware and computer instructions.

[0125] The units described in some embodiments of the present disclosure may be implemented by software or by hardware. The described units may also be provided in a processor, for example, may be described as: a processor including an acquisition unit, a first generation unit, a second generation unit, a third generation unit, a fourth generation unit, a fifth generation unit and a control unit. Among them, the names of these units do not constitute a limitation on the unit itself under certain circumstances. For example, the acquisition unit may also be described as "a unit for acquiring the historical annual available power generation information and the historical annual online power generation sequence of the target wind and solar power station".

[0126] The functions described above herein may be performed at least in part by one or more hardware logic components. For example, without limitation, exemplary types of hardware logic components that may be used include: field programmable gate arrays (FPGAs), application specific integrated circuits (ASICs), application specific standard products (ASSPs), systems on chips (SOCs), complex programmable logic devices (CPLDs), and the like.

[0127] The above descriptions are only some preferred embodiments of the present disclosure and an explanation of the technical principles used. Those skilled in the art should understand that the scope of the invention involved in the embodiments of the present disclosure is not limited to the technical solutions formed by a specific combination of the above-mentioned technical features, but should also cover other technical solutions formed by any combination of the above-mentioned technical features or their equivalent features without departing from the above-mentioned inventive concept. For example, the above-mentioned features are replaced with the technical features with similar functions disclosed in the embodiments of the present disclosure (but not limited to) and the technical solutions formed.

Claims

1. A method for installing a pure hydrogen gas turbine energy storage system, comprising: Obtain the historical annual power generation information and historical annual grid-connected power generation sequence of the target wind and solar power station; Generate estimated annual power abandonment information based on the historical annual available power generation information and the historical annual on-grid power sequence; According to the estimated annual power abandonment information, generate the daily hydrogen production of abandoned power; According to the daily hydrogen production of abandoned electricity, the number of electrolyzers, the number of hydrogen storage spherical tanks and the daily operating time of the gas turbine corresponding to the pure hydrogen gas turbine energy storage system to be configured are generated; Generating the number of gas turbines according to the daily operating time of the gas turbines, wherein generating the number of gas turbines according to the daily operating time of the gas turbines includes: Determine a target daily peak-shaving duration corresponding to the target wind-solar power station, wherein determining the target daily peak-shaving duration corresponding to the target wind-solar power station comprises: Obtain a set of historical daily peak-shaving durations corresponding to the target wind and solar power station; Determine the average value of the peak-shaving durations of each historical day included in the historical daily peak-shaving duration set as the average peak-shaving duration; Determine each historical daily peak-shaving duration in the historical daily peak-shaving duration set that is greater than the average peak-shaving duration as a target historical daily peak-shaving duration group; Determine the average value of each target historical daily peak-shaving duration included in the target historical daily peak-shaving duration group as the target daily peak-shaving duration; The ratio of the daily operating time of the gas turbine to the target daily peak load regulation time is determined as the number of gas turbines; Generating information on the value of energy storage system collection according to the daily operation time of the gas turbine; According to the number of electrolyzers, the number of hydrogen storage tanks, the number of gas turbines and the value information collected by the energy storage system, each associated installation device is controlled to perform each equipment installation operation.

2. The method according to claim 1, wherein: The historical annual available power generation information includes each historical monthly available power generation information sequence and a historical annual available power generation data sequence, wherein the historical monthly available power generation information in each historical monthly available power generation information sequence includes the historical monthly available power generation, and the historical annual available power generation data in the historical annual available power generation data sequence includes the historical annual available power generation; And generating the estimated annual power abandonment information according to the historical annual power generation information and the historical annual grid-connected power sequence includes: Grouping the available power generation information for each historical month included in the available power generation information sequence for each historical month to obtain the available power generation information groups for each historical month; For each historical monthly power generation information group obtained, perform the following steps: Sorting the historical monthly power generation information group to obtain a target historical monthly power generation information sequence; Inputting the target historical monthly power generation information sequence into a pre-trained estimated monthly power generation model to obtain the estimated monthly power generation; The sum of the obtained estimated monthly power generation amounts is determined as the first estimated annual power generation amount; Inputting the historical annual available power generation data sequence into a pre-trained estimated annual available power generation model to obtain a second estimated annual available power generation; For each historical monthly power generation information sequence included in the historical monthly power generation information sequence, the variance of the power generation amount of each historical month included in the historical monthly power generation information sequence is determined as the variance of the power generation amount of the first month; For each historical monthly available power generation information group included in each historical monthly available power generation information group, the variance of the available power generation of each historical month included in the historical monthly available power generation information group is determined as the variance of the available power generation of the second month; Determining a power generation weight set corresponding to the first estimated annual power generation and the second estimated annual power generation according to the first monthly power generation variance and the second monthly power generation variance; Generate an estimated annual power generation according to the first estimated annual power generation, the second estimated annual power generation and the power generation weight set; Inputting the historical annual grid-connected power sequence into a pre-trained estimated annual grid-connected power generation model to obtain the estimated annual grid-connected power; The difference between the estimated annual power generation amount and the estimated annual grid-connected power amount is determined as the estimated annual power abandonment information.

3. The method according to claim 1, wherein: The method of generating the number of electrolyzers, the number of hydrogen storage spherical tanks and the daily operation time of the gas turbine corresponding to the pure hydrogen gas turbine energy storage system to be configured according to the daily hydrogen production amount of the abandoned electricity includes: Obtaining electrolytic cell attribute information corresponding to the electrolytic cell identifier; Generate the number of electrolytic cells according to the daily hydrogen production of abandoned electricity and the electrolytic cell attribute information; Obtain the attribute information of the hydrogen storage spherical tank corresponding to the hydrogen storage spherical tank identification; Generate the number of hydrogen storage spherical tanks according to the daily hydrogen production of abandoned electricity and the attribute information of the hydrogen storage spherical tanks; Obtaining gas turbine attribute information corresponding to a pure hydrogen gas turbine identifier; The daily operating time of the gas turbine is generated according to the daily hydrogen production amount due to abandoned electricity and the property information of the gas turbine.

4. The method according to claim 1, wherein: The generating of the energy storage system charging value information according to the daily operation time of the gas turbine includes: The product of the daily operation time of the gas turbine and the preset annual peak-shaving days is determined as the annual peak-shaving time; Obtain the gas turbine power corresponding to the pure hydrogen gas turbine identification; The product of the annual peak-shaving duration, the gas turbine power and the number of gas turbines is determined as the annual gas turbine peak-shaving electricity; Obtain the historical peak-shaving power value information set; Generate average peak-shaving electricity value information according to the historical peak-shaving electricity value information set; Generate gas turbine peak-shaving charge value information based on the annual gas turbine peak-shaving power and the average peak-shaving power value information; Generate carbon dioxide collection value information based on the annual gas turbine peak load electricity, the preset average carbon dioxide emission factor of electricity and the preset carbon dioxide unit value information; generating capacity compensation collection value information according to the gas turbine power and preset unit capacity compensation value information; The energy storage system collection value information is generated according to the gas turbine peak load shaving collection value information, the carbon dioxide collection value information and the capacity compensation collection value information.

5. A pure hydrogen gas turbine energy storage system installation device, comprising: An acquisition unit is configured to acquire historical annual available power generation information and historical annual online power generation sequence of a target wind and solar power station; A first generating unit is configured to generate estimated annual power abandonment information based on the historical annual available power generation information and the historical annual online power generation sequence; The second generating unit is configured to generate a daily hydrogen production amount of abandoned electricity according to the estimated annual abandoned electricity information; The third generating unit is configured to generate the number of electrolyzers, the number of hydrogen storage spherical tanks and the daily operating time of the gas turbine corresponding to the pure hydrogen gas turbine energy storage system to be configured according to the daily hydrogen production amount of the abandoned electricity; The fourth generating unit is configured to generate the number of gas turbines according to the daily operating time of the gas turbine, wherein the generating the number of gas turbines according to the daily operating time of the gas turbine comprises: Determine a target daily peak-shaving duration corresponding to the target wind-solar power station, wherein determining the target daily peak-shaving duration corresponding to the target wind-solar power station comprises: Obtain a set of historical daily peak-shaving durations corresponding to the target wind and solar power station; Determine the average value of the peak-shaving durations of each historical day included in the historical daily peak-shaving duration set as the average peak-shaving duration; Determine each historical daily peak-shaving duration in the historical daily peak-shaving duration set that is greater than the average peak-shaving duration as a target historical daily peak-shaving duration group; Determine the average value of each target historical daily peak-shaving duration included in the target historical daily peak-shaving duration group as the target daily peak-shaving duration; The ratio of the daily operating time of the gas turbine to the target daily peak load regulation time is determined as the number of gas turbines; A fifth generating unit is configured to generate energy storage system charging value information according to the daily operation time of the gas turbine; The control unit is configured to control each associated installation device to perform each equipment installation operation according to the number of the electrolyzers, the number of the hydrogen storage tanks, the number of the gas turbines and the value information collected by the energy storage system.

6. An electronic device comprising: one or more processors; a storage device having one or more programs stored thereon; When the one or more programs are executed by the one or more processors, the one or more processors implement the method according to any one of claims 1 to 4.

7. A computer readable medium having a computer program stored thereon, wherein: When the program is executed by a processor, the method according to any one of claims 1 to 4 is implemented.

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