CN113516306B - Power configuration method, device, medium and electronic equipment of flywheel energy storage system - Google Patents
Power configuration method, device, medium and electronic equipment of flywheel energy storage system Download PDFInfo
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Abstract
The present disclosure relates to a power configuration method, apparatus, medium and electronic device for a flywheel energy storage system, comprising: acquiring wind measurement data of a target area applied by an energy storage system in a current time period and wind power data of an upwind area corresponding to the target area; acquiring a wind power predicted value and an electric load predicted value of the target area in a future time period according to the wind measurement data and the wind power data; determining an economic resource consumption value corresponding to the energy storage system through a preset economic model according to the wind power predicted value and the power load predicted value; determining a power distribution coefficient of the energy storage system according to the economic resource consumption value, and performing power configuration on the energy storage system according to the power distribution coefficient; therefore, under the condition of effectively solving the problem that the wind power stably supplies the load power, the economic cost is greatly saved, and the popularization and the application are facilitated.
Description
Technical Field
The present disclosure relates to the field of flywheel energy storage system configuration, and in particular, to a power configuration method, device, medium, and electronic device for a flywheel energy storage system.
Background
The wind power generation is an important direction for developing and utilizing green energy by virtue of the advantages of environmental protection, abundant resources, short development period and the like, fully utilizes the wind power generation and improves the stability of the wind power generation, is a problem faced all the time, combines an energy storage system with a wind power plant to establish a wind power plant energy storage combined power generation system, and is a promising solution for improving the reliability of integrated wind power.
The flywheel energy storage is a pure physical energy storage technology, and has the advantages of high energy storage density, high conversion efficiency, large instantaneous power, high response speed, long service life, environmental protection, no pollution, no geographic environment limitation and the like.
Disclosure of Invention
In order to solve the above problems, an object of the present disclosure is to provide a power configuration method, device, medium, and electronic apparatus for a flywheel energy storage system.
In a first aspect, a power configuration method of a flywheel energy storage system is provided, including: acquiring wind measurement data of a target area applied by an energy storage system in a current time period and wind power data of an upwind area corresponding to the target area; acquiring a wind power predicted value and an electric load predicted value of the target area in a future time period according to the wind measurement data and the wind power data; determining an economic resource consumption value corresponding to the energy storage system through a preset economic model according to the wind power predicted value and the power load predicted value; and determining a power distribution coefficient of the energy storage system according to the economic resource consumption value, and performing power configuration on the energy storage system according to the power distribution coefficient.
Optionally, the wind measurement data includes wind speed and wind direction of the current time period and historical wind power data of a target area; the step of obtaining a wind power predicted value and an electricity load predicted value of the target area in a future time period according to the wind measurement data and the wind power data comprises the following steps: taking the wind speed, the wind direction, the historical wind power data and the wind power data of the upwind area as the input of a pre-trained wind power prediction model to obtain the wind power prediction value; acquiring a plurality of historical load data of a target area in a historical time period corresponding to the future time period; and taking the average value of the plurality of historical load data as the predicted value of the electric load.
Optionally, the determining, by a preset economic model, an economic resource consumption value corresponding to the energy storage system according to the predicted wind power value and the predicted power load value includes: carrying out wavelet decomposition on the wind power predicted value to obtain high-frequency wind power and low-frequency wind power; the high-frequency wind power is wind power larger than or equal to a preset frequency threshold value, and the low-frequency wind power is wind power smaller than the preset frequency threshold value; determining a first economic resource consumption value of the power type flywheel energy storage subsystem for finishing unit energy storage and release according to the high-frequency wind power and the predicted value of the power load through the preset economic model; determining a second economic resource consumption value of the energy type flywheel energy storage subsystem for finishing unit energy storage and release through the preset economic model according to the low-frequency wind power and the predicted value of the power load; determining a third economic resource consumption value of the lithium battery energy storage subsystem for completing unit energy storage and release through the preset economic model according to the low-frequency wind power and the predicted value of the electric load; the determining the power distribution coefficient of the energy storage system according to the economic resource consumption value comprises: and determining the distribution coefficient of the power type flywheel energy storage subsystem as a first power distribution coefficient, the distribution coefficient of the energy type flywheel energy storage subsystem as a second power distribution coefficient, and the distribution coefficient of the lithium battery energy storage subsystem as a third power distribution coefficient, so that the sum of a first product of the first power distribution coefficient and the first economic resource consumption value, a second product of the second power distribution coefficient and the second economic resource consumption value, and a third product of the third power distribution coefficient and the third economic resource consumption value is a minimum value.
Optionally, the preset economic model is configured to calculate an economic resource consumption value of the target energy storage subsystem for completing unit energy storage and release according to the wind power predicted value, the power load predicted value, and depreciation economic resources and investment economic resources of preset unit energy of the target energy storage subsystem, where the target energy storage subsystem includes a power type flywheel energy storage subsystem, an energy type flywheel energy storage subsystem, or a lithium battery energy storage subsystem.
Optionally, the power configuring the energy storage system according to the power distribution coefficient includes: calculating a maximum instantaneous power difference value of the power load predicted value and the wind power predicted value, and taking the maximum instantaneous power difference value as a total power value of the energy storage system; calculating the product of the total power value and the first power distribution coefficient to obtain the energy storage power corresponding to the power type flywheel energy storage subsystem; calculating the product of the total power value and the second power distribution coefficient to obtain the energy storage power corresponding to the energy type flywheel energy storage subsystem; and calculating the product of the total power value and the third power distribution coefficient to obtain the energy storage power corresponding to the lithium battery energy storage subsystem.
Optionally, the method further comprises: and controlling the energy storage system to charge and discharge according to the wind power predicted value and the power load predicted value. Optionally, the controlling the energy storage system to perform charging and discharging according to the wind power predicted value and the electrical load predicted value includes: under the condition that the wind power predicted value is larger than the electricity load predicted value, controlling the energy storage system to charge so that the output power of the energy storage system is equal to the electricity load predicted value; under the condition that the wind power predicted value is smaller than the electric load predicted value, controlling the energy storage system to discharge so that the output power of the energy storage system is equal to the electric load predicted value; and controlling the energy storage system to stop charging and discharging under the condition that the wind power predicted value is equal to the power load predicted value.
In a second aspect, a power configuration apparatus for a flywheel energy storage system is provided, including: the system comprises an acquisition module, a judgment module and a control module, wherein the acquisition module is used for acquiring wind measurement data in a current time period of a target area applied by an energy storage system and wind power data of an upwind area corresponding to the target area; the prediction module is used for acquiring a wind power prediction value and an electric load prediction value of the target area in a future time period according to the wind measurement data and the wind power data; the calculation module is used for determining an economic resource consumption value corresponding to the energy storage system through a preset economic model according to the wind power predicted value and the power load predicted value; and the distribution module is used for determining the power distribution coefficient of the energy storage system according to the economic resource consumption value and carrying out power configuration on the energy storage system according to the power distribution coefficient.
Optionally, the wind measurement data includes wind speed and wind direction of the current time period and historical wind power data of a target area; the acquisition module is used for acquiring a plurality of historical load data of a target area in a historical time period corresponding to the future time period; the prediction module is used for taking the wind speed, the wind direction, the historical wind power data and the wind power data of the upwind area as the input of a pre-trained wind power prediction model to obtain the wind power prediction value; and taking the average value of the plurality of historical load data as the predicted value of the electric load.
Optionally, the energy storage system includes a power type flywheel energy storage subsystem, an energy type flywheel energy storage subsystem, and a lithium battery energy storage subsystem; the calculation module is used for performing wavelet decomposition on the wind power predicted value to obtain high-frequency wind power and low-frequency wind power; the high-frequency wind power is wind power larger than or equal to a preset frequency threshold value, and the low-frequency wind power is wind power smaller than the preset frequency threshold value; determining a first economic resource consumption value of the power type flywheel energy storage subsystem for finishing unit energy storage and release according to the high-frequency wind power and the predicted value of the power load through the preset economic model; determining a second economic resource consumption value of the energy type flywheel energy storage subsystem for finishing unit energy storage and release through the preset economic model according to the low-frequency wind power and the predicted value of the power load; and determining a third economic resource consumption value of the lithium battery energy storage subsystem for finishing unit energy storage and release through the preset economic model according to the low-frequency wind power and the predicted value of the power load.
Optionally, the calculation module is further configured to determine that a distribution coefficient of the power flywheel energy storage subsystem is a first power distribution coefficient, a distribution coefficient of the energy flywheel energy storage subsystem is a second power distribution coefficient, and a distribution coefficient of the lithium battery energy storage subsystem is a third power distribution coefficient, so that a sum of a first product of the first power distribution coefficient and the first economic resource consumption value, a second product of the second power distribution coefficient and the second economic resource consumption value, and a third product of the third power distribution coefficient and the third economic resource consumption value is a minimum value; and the preset economic model is used for calculating the economic resource consumption value of the target energy storage subsystem for finishing unit energy storage and release according to the wind power predicted value, the power load predicted value and the depreciation economic resources and investment economic resources of preset unit energy of the target energy storage subsystem, and the target energy storage subsystem comprises a power type flywheel energy storage subsystem, an energy type flywheel energy storage subsystem or a lithium battery energy storage subsystem.
Optionally, the distribution module is configured to calculate a maximum instantaneous power difference between the electrical load predicted value and the wind power predicted value, and use the maximum instantaneous power difference as a total power value of the energy storage system; calculating the product of the total power value and the first power distribution coefficient to obtain the energy storage power corresponding to the power type flywheel energy storage subsystem; calculating the product of the total power value and the second power distribution coefficient to obtain the energy storage power corresponding to the energy type flywheel energy storage subsystem; and calculating the product of the total power value and the third power distribution coefficient to obtain the energy storage power corresponding to the lithium battery energy storage subsystem.
Optionally, the apparatus further comprises: and the control module is used for controlling the energy storage system to charge and discharge according to the wind power predicted value and the power load predicted value.
Optionally, the control module is configured to control the energy storage system to charge when the predicted wind power value is greater than the predicted power consumption load value, so that the output power of the energy storage system is equal to the predicted power consumption load value; under the condition that the wind power predicted value is smaller than the electric load predicted value, controlling the energy storage system to discharge so that the output power of the energy storage system is equal to the electric load predicted value; and controlling the energy storage system to stop charging and discharging under the condition that the wind power predicted value is equal to the power load predicted value.
In a third aspect, a non-transitory computer readable storage medium is provided, on which a computer program is stored, which program, when being executed by a processor, is adapted to carry out the steps of the method of any one of the above-mentioned methods of power configuration of a flywheel energy storage system.
In a fourth aspect, an electronic device is provided, comprising: a memory having a computer program stored thereon; a processor for executing the computer program in the memory to implement the steps of any of the above-described methods of power configuration of a flywheel energy storage system.
By adopting the technical scheme, the required energy storage power can be determined by predicting the wind power and the load power, the power distribution of different energy storage systems can be determined by economic resource consumption values, and the energy storage system configuration is made in advance, so that the problem that the wind power cannot stably supply the load power is effectively solved, and the economic cost is saved.
Additional features and advantages of the disclosure will be set forth in the detailed description which follows.
Drawings
The accompanying drawings, which are included to provide a further understanding of the disclosure and are incorporated in and constitute a part of this specification, illustrate embodiments of the disclosure and together with the description serve to explain the disclosure without limiting the disclosure. In the drawings:
FIG. 1 is a schematic flow diagram illustrating a power configuration method for a flywheel energy storage system in accordance with an exemplary embodiment;
FIG. 2 is a schematic flow diagram illustrating another method for configuring power for a flywheel energy storage system in accordance with an exemplary embodiment;
FIG. 3 is a block diagram of a power configuration arrangement for a flywheel energy storage system, according to an exemplary embodiment;
FIG. 4 is a block diagram of a power configuration arrangement for another flywheel energy storage system in accordance with an exemplary embodiment;
FIG. 5 is a block diagram illustrating an electronic device in accordance with an example embodiment.
Detailed Description
The following detailed description of specific embodiments of the present disclosure is provided in connection with the accompanying drawings. It should be understood that the detailed description and specific examples, while indicating the present disclosure, are given by way of illustration and explanation only, not limitation.
Firstly, an application scenario of the present disclosure is explained, and the present disclosure may be applied to a scenario in which an energy storage system is combined with a wind farm to establish a wind farm energy storage combined power generation system, where wind power depends on anemometry data, and the fluctuation is large, and is not suitable for directly supplying power to a load power grid.
In the prior art, different energy storage systems have different response times and different action times, so that a unified energy storage system is difficult to form, and various energy storage systems have different characteristics, different energy storage system configuration methods and different required cost input and expected effects, so that the aim of supplying power for a load power grid by stabilizing wind power with the lowest economic cost is difficult to achieve.
In order to solve the problems, the method can determine the required energy storage power by predicting the wind power and the load power, determine the power distribution of different energy storage systems by economic resource consumption values, and make the energy storage system configuration in advance, so that the problem that the wind power cannot stably supply the load power is effectively solved, the economic cost is saved, and the popularization and the application are facilitated.
The disclosure is described below with reference to specific examples.
Fig. 1 is a power configuration method of a flywheel energy storage system according to an embodiment of the present disclosure, as shown in fig. 1, the method includes:
s101, acquiring wind measurement data of a target area applied by an energy storage system in a current time period and wind power data of an upwind area corresponding to the target area.
The target area to which the energy storage system is applied may be a wind power generation farm to which the energy storage system is applied, the anemometry data includes wind speed, wind direction and historical wind power data of the target area for the current time period, the current time period may be a time period from the next time to one minute before the current time, or a time period from the next time to one hour before the current time, which is not specifically limited, and the historical wind power includes wind power of a historical time period corresponding to the current time period, for example, the current time period may be from two to three months in three months, the historical time period corresponding to the current time period may be from two to three months in three months before one year, or the current time period may be from two to three months in two months before two years, the historical time period corresponding to the current time period may be from two to three days in two afternoon before one day, the next to three hours before two to three hours before one day, the wind power data of the upwind area may be 10 upwind power data of the target area, or the historical wind power data may be a kilometer of the target area, and the historical wind power data may be a kilometer data of the target area, and the target wind power data may be illustrated by way of the target area.
And S102, acquiring a wind power predicted value and an electric load predicted value of the target area in a future time period according to the wind measurement data and the wind power data.
In this step, the wind power predicted value and the electrical load predicted value may be obtained by: the wind speed, the wind direction, the historical wind power data and the wind power data of the upwind area can be used as the input of a wind power prediction model trained in advance to obtain the wind power prediction value, a plurality of historical load data of the target area in a historical time period corresponding to the future time period are obtained, and the average value of the plurality of historical load data is used as the electricity load prediction value.
The wind power prediction model can be a BP neural network, and can be trained in advance in the following modes: acquiring a wind power training sample, wherein the wind power training sample comprises historical wind speed, wind direction, historical wind power data, wind power data of an upwind area and second day wind power data of a target area corresponding to the wind power training sample; and training a target training model according to the wind power training sample and the next day wind power data of the target area corresponding to the wind power training sample to obtain a wind power prediction model.
And S103, determining an economic resource consumption value corresponding to the energy storage system through a preset economic model according to the wind power predicted value and the power load predicted value.
Wherein, this energy storage system includes power type flywheel energy storage subsystem, energy type flywheel energy storage subsystem and lithium battery energy storage subsystem, this power type flywheel energy storage subsystem can carry out the charge-discharge response of high frequency low energy, this energy type flywheel energy storage subsystem and lithium battery energy storage subsystem can carry out the charge-discharge response of low frequency large capacity, multiple energy storage subsystem arranges like this, the response effect that can full play energy storage system, be arranged in throwing into wind power generation system, improve wind power generation system's reliability and stability, this economic resources consumption value can be the consumption of cost, like the consumption of money etc..
In this step, as shown in fig. 2, the economic resource consumption value corresponding to the energy storage system may be determined by the following steps:
and S1031, performing wavelet decomposition on the wind power predicted value to obtain high-frequency wind power and low-frequency wind power.
The high-frequency wind power is wind power larger than or equal to a preset frequency threshold value, and the low-frequency wind power is wind power smaller than the preset frequency threshold value.
For example, the preset frequency threshold may be a division frequency value of a low frequency band and a middle and low frequency band defined by the international electrotechnical commission IEC581 standard, the low frequency wind power may be a wind power less than the division frequency value defined by the international electrotechnical commission IEC581 standard, and the high frequency wind power may be greater than or equal to the wind power of the division frequency value defined by the international electrotechnical commission IEC581 standard; or the preset frequency threshold value can be the dividing frequency values of the low frequency band and the medium and low frequency band specified by the national standard GB/T14277-93 of China, the low frequency wind power can be the wind power which is less than the dividing frequency value specified by the national standard GB/T14277-93, and the high frequency wind power can be the wind power which is greater than or equal to the dividing frequency value specified by the national standard GB/T14277-93. It should be noted that, for the specific implementation manner of the classification method, reference may be made to an implementation manner in the related art, which is not described herein again, and the classification method is only an example, and is not limited in this disclosure.
S1032, determining a first economic resource consumption value of the power type flywheel energy storage subsystem for finishing unit energy storage and release according to the high-frequency wind power and the predicted value of the electrical load through the preset economic model.
The economic resource consumption value can be consumption of economic cost, such as consumption of money, the preset economic model is used for calculating the economic resource consumption value of finishing energy storage and energy release in unit time of the target energy storage subsystem according to the wind power predicted value, the electricity load predicted value and depreciation economic resources and investment economic resources of preset unit energy of the target energy storage subsystem by the following formula, and the target energy storage subsystem comprises a power type flywheel energy storage subsystem, an energy type flywheel energy storage subsystem or a lithium battery energy storage subsystem.
For example, the economic cost formula for the energy storage subsystem to complete the storage and release of energy per unit time is:
among them, cost P For the total investment cost per unit energy of the target energy storage subsystem,
cost per unit energy depreciation, P, for the target energy storage subsystem SOC As energy storage system energy per unit timeVolume storage and release of the total volume.
Total investment cost per unit energy:
cost per energy depreciation:
energy generated by charging and discharging of the energy storage system:
where E is the preset total rated energy of the target energy storage subsystem, eta is the preset efficiency of the target energy storage subsystem, and C total For the preset total investment Cost, corresponding to the target energy storage subsystem J And the total depreciation cost corresponding to the preset target energy storage subsystem is obtained.
Total amount of energy stored and released by the energy storage system per unit time:
wherein, P wt Is the predicted value of the wind power, the corresponding P of the power type flywheel energy storage subsystem wt The high-frequency wind power of the wind power predicted value, the energy type flywheel energy storage subsystem and the lithium battery energy storage subsystem correspond to P wt Low frequency wind power, P, for the predicted value of the wind power load Is the predicted value of the electrical load.
Through the formula, according to the preset rated total energy, the preset energy storage efficiency, the preset total investment cost and the preset total depreciation cost of the power type flywheel energy storage subsystem, the economic cost of the power type flywheel energy storage subsystem for finishing energy storage and energy release in unit time can be obtained, and the economic cost is a first economic resource consumption value corresponding to the energy stored and released in unit time of the power type flywheel energy storage subsystem.
And S1033, determining a second economic resource consumption value of the energy type flywheel energy storage subsystem for finishing unit energy storage and release through the preset economic model according to the low-frequency wind power and the predicted value of the electric load.
Illustratively, by using the above economic cost formula for completing energy storage and energy release in unit time by the energy storage subsystem, according to the preset rated total energy, the preset energy storage efficiency, the preset total investment cost and the preset total depreciation cost of the energy type flywheel energy storage subsystem, the economic cost for completing energy storage and energy release in unit time by the energy type flywheel energy storage subsystem can be obtained, and the economic cost is a second economic resource consumption value corresponding to the completion of energy storage and energy release in unit time by the energy type flywheel energy storage subsystem.
S1034, determining a third economic resource consumption value of the lithium battery energy storage subsystem for completing unit energy storage and release according to the low-frequency wind power and the predicted value of the electrical load through the preset economic model.
Illustratively, by using the above economic cost formula for completing energy storage and energy release in unit time by the energy storage subsystem, according to a preset rated total energy, a preset energy storage efficiency, a preset total investment cost and a preset total depreciation cost of the lithium battery energy storage subsystem, the economic cost for completing energy storage and energy release in unit time by the lithium battery energy storage subsystem can be obtained, and the economic cost is a third economic resource consumption value corresponding to the completion of energy storage and energy release in unit time by the lithium battery energy storage subsystem.
And S104, determining a power distribution coefficient of the energy storage system according to the economic resource consumption value, and performing power configuration on the energy storage system according to the power distribution coefficient.
In one possible implementation, the power allocation coefficient may be determined by: the distribution coefficient of the power flywheel energy storage subsystem can be determined to be a first power distribution coefficient, the distribution coefficient of the energy flywheel energy storage subsystem is determined to be a second power distribution coefficient, the distribution coefficient of the lithium battery energy storage subsystem is determined to be a third power distribution coefficient, and therefore the sum of a first product of the first power distribution coefficient and the first economic resource consumption value, a second product of the second power distribution coefficient and the second economic resource consumption value, and a third product of the third power distribution coefficient and the third economic resource consumption value is the minimum value.
The step of determining the power distribution coefficient may be expressed by the following equation: minJ = aF fess +bF' fess +cF bess Wherein minJ is the minimum economic resource consumption value, a is the first power distribution coefficient, b is the second power distribution coefficient, c is the third power distribution coefficient, F fess Is a first economic resource cost value, F' fess For the second economic resource consumption value, F bess A third economic resource cost value.
After obtaining the power distribution coefficient, the energy storage system may be configured in the following manner:
calculating the maximum instantaneous power difference value of the power load predicted value and the wind power predicted value, and taking the maximum instantaneous power difference value as the total power value of the energy storage system; calculating the product of the total power value and the first power distribution coefficient to obtain the energy storage power corresponding to the power type flywheel energy storage subsystem; calculating the product of the total power value and the second power distribution coefficient to obtain the energy storage power corresponding to the energy type flywheel energy storage subsystem; and calculating the product of the total power value and the third power distribution coefficient to obtain the energy storage power corresponding to the lithium battery energy storage subsystem.
By adopting the method, the intelligent energy storage configuration mode of hybrid flywheel energy storage and lithium battery is adopted on the basis of wind power prediction, so that the power configuration of the energy storage system can be effectively completed, the cost can be effectively saved, and the economic benefit of the whole wind power system and the stability of the wind power generation system are improved by fully utilizing the intelligent algorithm of a computer.
After the energy storage system is configured with power, the energy storage system can be controlled to be charged and discharged according to the wind power predicted value and the power load predicted value:
under the condition that the wind power predicted value is larger than the electricity load predicted value, controlling the energy storage system to charge so that the output power of the energy storage system is equal to the electricity load predicted value; under the condition that the wind power predicted value is smaller than the power load predicted value, controlling the energy storage system to discharge so that the output power of the energy storage system is equal to the power load predicted value; and controlling the energy storage system to stop charging and discharging under the condition that the wind power predicted value is equal to the power load predicted value. Therefore, the energy storage system plays a role in smoothing wind power, the stability of the wind power generation system is guaranteed, the wind power can be connected into a load power grid, and the economic benefit of the wind power system is improved.
Fig. 3 is a power configuration method of a flywheel energy storage system according to an embodiment of the present disclosure, and as shown in fig. 3, the apparatus includes:
the acquiring module 301 is configured to acquire wind measurement data in a current time period of a target area where the energy storage system is applied and wind power data of an upwind area corresponding to the target area;
the prediction module 302 is configured to obtain a wind power prediction value and an electrical load prediction value of the target area in a future time period according to the wind measurement data and the wind power data;
the calculating module 303 is configured to determine, according to the wind power predicted value and the power load predicted value, an economic resource consumption value corresponding to the energy storage system through a preset economic model;
and the allocating module 304 is configured to determine a power allocation coefficient of the energy storage system according to the economic resource consumption value, and perform power allocation on the energy storage system according to the power allocation coefficient.
Illustratively, the obtaining module 301 is configured to obtain wind measurement data of a wind power generation farm applied by an energy storage system in a current time period and wind power data of an upwind area corresponding to the wind power generation farm; the anemometry data comprises wind speed and wind direction of the current time period and historical wind power data of the region.
Optionally, the obtaining module 301 is further configured to obtain a plurality of historical load data of the target area in a historical time period corresponding to the future time period.
Optionally, the prediction module 302 is further configured to use the wind speed, the wind direction, the historical wind power data, and the wind power data of the upwind region as inputs of a pre-trained wind power prediction model to obtain the wind power prediction value; the average value of the plurality of historical load data is used as the predicted value of the electric load.
Optionally, the calculating module 303 is further configured to perform wavelet decomposition on the wind power predicted value to obtain a high-frequency wind power and a low-frequency wind power; the high-frequency wind power is wind power larger than or equal to a preset frequency threshold, and the low-frequency wind power is wind power smaller than the preset frequency threshold; determining a first economic resource consumption value of the power type flywheel energy storage subsystem for completing unit energy storage and release according to the high-frequency wind power and the electric load predicted value through the preset economic model; determining a second economic resource consumption value of the energy type flywheel energy storage subsystem for finishing unit energy storage and release through the preset economic model according to the low-frequency wind power and the predicted value of the power load; and determining a third economic resource consumption value of the lithium battery energy storage subsystem for finishing unit energy storage and release through the preset economic model according to the low-frequency wind power and the predicted value of the power load.
In addition, the calculating module 303 is further configured to determine that the distribution coefficient of the power flywheel energy storage subsystem is a first power distribution coefficient, the distribution coefficient of the energy flywheel energy storage subsystem is a second power distribution coefficient, and the distribution coefficient of the lithium battery energy storage subsystem is a third power distribution coefficient, so that a sum of a first product of the first power distribution coefficient and the first economic resource consumption value, a second product of the second power distribution coefficient and the second economic resource consumption value, and a third product of the third power distribution coefficient and the third economic resource consumption value is a minimum value; the preset economic model is used for calculating the economic resource consumption value of the target energy storage subsystem for completing unit energy storage and release according to the wind power predicted value, the power load predicted value and depreciation economic resources and investment economic resources of preset unit energy of the target energy storage subsystem, and the target energy storage subsystem comprises a power type flywheel energy storage subsystem, an energy type flywheel energy storage subsystem or a lithium battery energy storage subsystem.
Optionally, the allocating module 304 is further configured to calculate a maximum instantaneous power difference between the electrical load predicted value and the wind power predicted value, and use the maximum instantaneous power difference as a total power value of the energy storage system; calculating the product of the total power value and the first power distribution coefficient to obtain the energy storage power corresponding to the power type flywheel energy storage subsystem; calculating the product of the total power value and the second power distribution coefficient to obtain the energy storage power corresponding to the energy type flywheel energy storage subsystem; and calculating the product of the total power value and the third power distribution coefficient to obtain the energy storage power corresponding to the lithium battery energy storage subsystem.
After the energy storage system is configured with power, the energy storage system may be controlled to be charged and discharged according to the wind power predicted value and the electrical load predicted value, and therefore, as shown in fig. 4, the apparatus further includes: and a control module 305, configured to control the energy storage system to perform charging and discharging according to the wind power predicted value and the electrical load predicted value.
Optionally, the control module 305 is configured to, when the predicted wind power value is greater than the predicted power consumption load value, control the energy storage system to charge so that the output power of the energy storage system is equal to the predicted power consumption load value; under the condition that the wind power predicted value is smaller than the power load predicted value, controlling the energy storage system to discharge so that the output power of the energy storage system is equal to the power load predicted value; and controlling the energy storage system to stop charging and discharging under the condition that the wind power predicted value is equal to the power load predicted value.
With regard to the apparatus in the above-described embodiment, the specific manner in which each module performs the operation has been described in detail in the embodiment related to the method, and will not be elaborated here.
By adopting the device, the required energy storage power can be determined by predicting the wind power and the load power, the power distribution of different energy storage systems can be determined by the economic resource consumption value, and the energy storage system configuration is made in advance, so that the problem that the wind power cannot stably supply the load power is effectively solved, the economic cost is saved, and the popularization and the application are facilitated.
Fig. 5 is a block diagram of an electronic device 500 shown in accordance with an example embodiment. As shown in fig. 5, the electronic device 500 may include: a processor 501 and a memory 502. The electronic device 500 may also include one or more of a multimedia component 503, an input/output (I/O) interface 504, and a communication component 505.
The processor 501 is configured to control the overall operation of the electronic device 500, so as to complete all or part of the steps in the power configuration method of the flywheel energy storage system. The memory 502 is used to store various types of data to support operation at the electronic device 500, such as instructions for any application or method operating on the electronic device 500 and application-related data, such as contact data, messaging, pictures, audio, video, and so forth. The Memory 502 may be implemented by any type of volatile or non-volatile Memory device or combination thereof, such as Static Random Access Memory (SRAM), electrically Erasable Programmable Read-Only Memory (EEPROM), erasable Programmable Read-Only Memory (EPROM), programmable Read-Only Memory (PROM), read-Only Memory (ROM), magnetic Memory, flash Memory, magnetic disk or optical disk. The multimedia component 503 may include a screen and an audio component. Wherein the screen may be, for example, a touch screen and the audio component is used for outputting and/or inputting audio signals. For example, the audio component may include a microphone for receiving external audio signals. The received audio signal may further be stored in the memory 502 or transmitted through the communication component 505. The audio assembly also includes at least one speaker for outputting audio signals. The I/O interface 504 provides an interface between the processor 501 and other interface modules, such as a keyboard, mouse, buttons, and the like. These buttons may be virtual buttons or physical buttons. The communication component 505 is used for wired or wireless communication between the electronic device 500 and other devices. Wireless Communication, such as Wi-Fi, bluetooth, near Field Communication (NFC for short), 2G, 3G, 4G, NB-IOT, eMTC, or other 5G, etc., or a combination of one or more of them, which is not limited herein. The corresponding communication component 505 may thus comprise: wi-Fi modules, bluetooth modules, NFC modules, and the like.
In an exemplary embodiment, the electronic Device 500 may be implemented by one or more Application Specific Integrated Circuits (ASICs), digital Signal Processors (DSPs), digital Signal Processing Devices (DSPDs), programmable Logic Devices (PLDs), field Programmable Gate Arrays (FPGAs), controllers, microcontrollers, microprocessors, or other electronic components, and is used for executing the above-mentioned power configuration method of the flywheel energy storage system.
In another exemplary embodiment, a computer readable storage medium comprising program instructions is also provided, which when executed by a processor, implement the steps of the power configuration method of the flywheel energy storage system described above. For example, the computer readable storage medium may be the memory 502 described above that includes program instructions executable by the processor 501 of the electronic device 500 to perform the method for power configuration of a flywheel energy storage system described above.
In another exemplary embodiment, a computer program product is also provided, which comprises a computer program executable by a programmable apparatus, the computer program having code portions for performing the above-mentioned method of power configuration of a flywheel energy storage system when executed by the programmable apparatus.
The preferred embodiments of the present disclosure are described in detail with reference to the accompanying drawings, however, the present disclosure is not limited to the specific details of the above embodiments, and various simple modifications may be made to the technical solution of the present disclosure within the technical idea of the present disclosure, and these simple modifications all belong to the protection scope of the present disclosure.
It should be noted that, in the foregoing embodiments, various features described in the above embodiments may be combined in any suitable manner, and in order to avoid unnecessary repetition, various combinations that are possible in the present disclosure are not described again.
In addition, any combination of various embodiments of the present disclosure may be made, and the same should be considered as the disclosure of the present disclosure, as long as it does not depart from the spirit of the present disclosure.
Claims (9)
1. A method of power configuration for a flywheel energy storage system, comprising:
acquiring wind measurement data of a target area applied by an energy storage system in a current time period and wind power data of an upwind area corresponding to the target area;
acquiring a wind power predicted value and an electric load predicted value of the target area in a future time period according to the wind measurement data and the wind power data;
determining an economic resource consumption value corresponding to the energy storage system through a preset economic model according to the wind power predicted value and the power load predicted value;
determining a power distribution coefficient of the energy storage system according to the economic resource consumption value, and performing power configuration on the energy storage system according to the power distribution coefficient;
and the preset economic model is used for calculating the economic resource consumption value of the target energy storage subsystem for storing and releasing energy in unit time through a preset formula according to the wind power predicted value, the electricity load predicted value and the depreciation economic resources and investment economic resources of preset unit energy of the target energy storage subsystem, and the target energy storage subsystem comprises a power type flywheel energy storage subsystem, an energy type flywheel energy storage subsystem or a lithium battery energy storage subsystem.
2. The method of claim 1, wherein the anemometry data comprises wind speed, wind direction, and historical wind power data for a target region for the current time period; the step of obtaining the wind power predicted value and the power load predicted value of the target area in the future time period according to the wind measurement data and the wind power data comprises the following steps:
taking the wind speed, the wind direction, the historical wind power data and the wind power data of the upwind area as the input of a pre-trained wind power prediction model to obtain the wind power prediction value;
acquiring a plurality of historical load data of a target area in a historical time period corresponding to the future time period;
and taking the average value of the plurality of historical load data as the predicted value of the electric load.
3. The method according to claim 1, wherein the energy storage system comprises a power type flywheel energy storage subsystem, an energy type flywheel energy storage subsystem and a lithium battery energy storage subsystem, and the determining the economic resource consumption value corresponding to the energy storage system through a preset economic model according to the wind power predicted value and the power load predicted value comprises:
carrying out wavelet decomposition on the wind power predicted value to obtain high-frequency wind power and low-frequency wind power; the high-frequency wind power is wind power larger than or equal to a preset frequency threshold value, and the low-frequency wind power is wind power smaller than the preset frequency threshold value;
determining a first economic resource consumption value of the power type flywheel energy storage subsystem for completing unit energy storage and release according to the high-frequency wind power and the electric load predicted value through the preset economic model;
determining a second economic resource consumption value of the energy type flywheel energy storage subsystem for finishing unit energy storage and release through the preset economic model according to the low-frequency wind power and the predicted value of the power load;
determining a third economic resource consumption value of the lithium battery energy storage subsystem for finishing unit energy storage and release through the preset economic model according to the low-frequency wind power and the predicted value of the power load;
the determining the power distribution coefficient of the energy storage system according to the economic resource consumption value comprises:
and determining the distribution coefficient of the power type flywheel energy storage subsystem as a first power distribution coefficient, the distribution coefficient of the energy type flywheel energy storage subsystem as a second power distribution coefficient, and the distribution coefficient of the lithium battery energy storage subsystem as a third power distribution coefficient, so that the sum of a first product of the first power distribution coefficient and the first economic resource consumption value, a second product of the second power distribution coefficient and the second economic resource consumption value, and a third product of the third power distribution coefficient and the third economic resource consumption value is a minimum value.
4. The method of claim 3, wherein the power configuring the energy storage system according to the power distribution coefficients comprises:
calculating a maximum instantaneous power difference value of the electric load predicted value and the wind power predicted value, and taking the maximum instantaneous power difference value as a total power value of the energy storage system;
calculating the product of the total power value and the first power distribution coefficient to obtain the energy storage power corresponding to the power type flywheel energy storage subsystem;
calculating the product of the total power value and the second power distribution coefficient to obtain the energy storage power corresponding to the energy type flywheel energy storage subsystem;
and calculating the product of the total power value and the third power distribution coefficient to obtain the energy storage power corresponding to the lithium battery energy storage subsystem.
5. The method according to any one of claims 1 to 4, further comprising:
and controlling the energy storage system to charge and discharge according to the wind power predicted value and the power load predicted value.
6. The method of claim 5, wherein the controlling the energy storage system to charge and discharge according to the wind power predicted value and the electrical load predicted value comprises:
controlling the energy storage system to charge under the condition that the wind power predicted value is larger than the electricity load predicted value, so that the output power of the energy storage system is equal to the electricity load predicted value;
under the condition that the wind power predicted value is smaller than the power load predicted value, controlling the energy storage system to discharge so that the output power of the energy storage system is equal to the power load predicted value;
and controlling the energy storage system to stop charging and discharging under the condition that the wind power predicted value is equal to the electric load predicted value.
7. A power arrangement for a flywheel energy storage system, comprising:
the system comprises an acquisition module, a judgment module and a control module, wherein the acquisition module is used for acquiring wind measurement data in a current time period of a target area applied by an energy storage system and wind power data of an upwind area corresponding to the target area;
the prediction module is used for acquiring a wind power prediction value and an electric load prediction value of the target area in a future time period according to the wind measurement data and the wind power data;
the calculation module is used for determining an economic resource consumption value corresponding to the energy storage system through a preset economic model according to the wind power predicted value and the power load predicted value;
the distribution module is used for determining a power distribution coefficient of the energy storage system according to the economic resource consumption value and performing power configuration on the energy storage system according to the power distribution coefficient;
and the preset economic model is used for calculating the economic resource consumption value of the target energy storage subsystem for storing and releasing energy in unit time through a preset formula according to the wind power predicted value, the electricity load predicted value and the depreciation economic resources and investment economic resources of preset unit energy of the target energy storage subsystem, and the target energy storage subsystem comprises a power type flywheel energy storage subsystem, an energy type flywheel energy storage subsystem or a lithium battery energy storage subsystem.
8. A non-transitory computer-readable storage medium, on which a computer program is stored, which program, when executed by a processor, performs the steps of the method of any one of claims 1 to 6.
9. An electronic device, comprising:
a memory having a computer program stored thereon;
a processor for executing the computer program in the memory to implement the steps of the method of any one of claims 1-6.
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