CN114676731A - Energy storage resource flexibility analysis method, device, equipment and storage medium - Google Patents
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Abstract
The invention discloses a method, a device, equipment and a storage medium for analyzing the flexibility of energy storage resources, relates to the technical field of the flexibility of the energy storage resources, and solves the technical problem that the prior energy storage technology has poor effect on electric power with different powers, so that the utilization rate of the energy storage is not high enough; the method specifically comprises the steps of providing energy support for a power grid by using energy storage units with different characteristics, maintaining the balance of supply and demand of the power grid, and explaining the flexibility of an energy storage group based on an intuitive graphical method to meet different requirements. The method comprises the following steps that the power grid sends a signal every hour, and suppliers call the stored energy according to the sequence from large to small of the running time to meet the requirement of supply and demand balance.
Description
Technical Field
The invention relates to the technical field of energy storage resource flexibility, in particular to an energy storage resource flexibility analysis method, device, equipment and storage medium.
Background
In recent years, the application of energy storage is more and more extensive, and the energy storage technology can provide a series of valuable services for the system, adjust the output fluctuation of a power grid and support the real-time balance of the supply and demand of the power grid. Many system operators offer a service framework that facilitates transactions, and the U.S. PJM market offers a control framework: a system-wide regulation signal representing the mismatch between the power supply and demand is provided, which the supplier should track to provide a demand response that satisfies the conditions.
The existing energy storage technology has a poor effect when providing electric power with different powers, so that the utilization rate of energy storage is not high enough; therefore, an energy storage resource flexibility analysis method, an energy storage resource flexibility analysis device, energy storage equipment and a storage medium are provided, under the condition of uncertain requirements, the energy storage equipment is optimally scheduled to meet real-time supply and demand balance, and the time capable of meeting the requirements is maximized.
Disclosure of Invention
In order to solve the above mentioned drawbacks in the background art, the present invention provides a method, an apparatus, a device and a storage medium for analyzing flexibility of energy storage resources.
The purpose of the invention can be realized by the following technical scheme: an energy storage resource flexibility analysis method comprises the following steps:
the method comprises the following steps: the dispatching center sends a power adjusting signal representing unmatched power supply and demand every hour;
step two: the supplier tracks the power adjustment signal to provide a demand response that satisfies the condition;
step three: sequencing the running time of the stored energy under the maximum power from large to small, and aggregating the stored energy with the same running time into a whole;
step four: according to the sequence of the running time of the stored energy under the maximum power from big to small, calling the stored energy from big to small, and obtaining the power of the stored energy when calling;
step five: after the dispatching center sends the next power adjusting signal, the stored energy is reordered and called to meet the demand and supply requirements;
step six: and after all the stored energy is exhausted, generating a capacity curve according to the obtained power and the corresponding time period when the stored energy is called, wherein if the capacity curve is below the maximum capacity curve, the stored energy calling meets the flexibility requirement, and if part of the capacity curve is above the maximum capacity curve, the sorting is wrong.
Further, the process of sequencing the running times of the energy storages at the maximum power from large to small and aggregating the energy storages with the same running time into a whole comprises the following steps:
grid imbalance signal:
in the formula PrSending a signal every hour for a power grid unbalanced signal;
run time at maximum stored energy:
in the formula xi(t) maximum run time of the plant, ei(t) is the energy of the device,
is the maximum discharge power of the device;
run time and power set:
x(t)＝[x1(t)...xn(t)]T
sorting each device from large to small according to the running time:
the energy storage with the same running time is aggregated into a whole:
in the formula
And aggregating the stored energy for the same operation time.
Further, the process of calling the energy storage from large to small comprises the following steps:
setting received unbalanced signal of power grid to PrAnd are called in descending order to satisfy the signal value Pr：
In the formula riAs a percentage of the corresponding energy storage call,
power values for different run times; the stored energy is called in sequence, when the power is less than the signal value PrWhen the energy is stored, the whole energy storage is completely called; when the power of the finally called stored energy is larger than the signal value PrAnd in time, the stored energy is called according to the proportion, and the rest stored energy is kept unchanged.
Further, upon receiving the next PrAfter the signals are sent, the stored energy is sorted again, and the stored energy is called according to the stored energy sorting sequence to meet the power grid balance requirement.
Further, the process of verifying whether the capacity curve meets the maximum capacity curve requirement is as follows:
calculating a capacity curve, and converting an E-p formula:
in the formula, a reference signal PrP is the power of each stored energy, [0, + ∞ ];
sorting the stored energy according to the running time under the maximum power from large to small, and obtaining a maximum capacity curve according to an E-p conversion formula;
according to the obtained energy storage power and the corresponding time period, an actual capacity curve can be obtained through an E-p conversion formula;
the actual capacity curve is below the maximum capacity curve, i.e. the flexibility requirement is met.
Further, the energy storage resource flexibility analysis device is characterized by comprising a measured state parameter acquisition module and an energy storage power output module;
the measured state parameter acquisition module is used for acquiring measured state parameters of the measured energy storage, and the measured state parameters comprise power and energy in the measured energy storage;
the energy storage calling output module is used for inputting the measured energy storage state parameters into a graphical energy storage resource flexibility analysis model which is trained in advance, the output measured energy storage is matched with a target power grid imbalance signal, and the graphical energy storage resource flexibility analysis model is obtained based on machine learning model training.
Further, an apparatus for energy storage resource flexibility analysis includes a memory and one or more processors, the memory is used for storing one or more programs, and the one or more programs are executed by the one or more processors, so that the processors implement the energy storage resource flexibility analysis method.
Further, a storage medium for energy storage resource flexibility analysis, the storage medium containing computer executable instructions for performing a method of energy storage resource flexibility analysis as described above when executed by a computer processor.
The invention has the beneficial effects that:
in the using process of the invention, firstly, power regulating signals with unmatched power supply and demand are sent by a scheduling center every hour, a supplier correspondingly provides requirements meeting the conditions according to the power regulating signals after receiving the power regulating signals, then the running time of the stored energy under the maximum power is sequenced from large to small, the stored energy with the same running time is aggregated into a whole, the stored energy is called from large to small according to the sequencing, the power when the stored energy is called is obtained, after all the stored energy is exhausted, a capacity curve is generated according to the obtained power when the stored energy is called and the corresponding time period, if the capacity curve is below the maximum capacity curve, the stored energy calling meets the requirements, if part of the capacity curve is above the maximum capacity curve, the sequencing is wrong, thus, the method of sequencing from large to small can realize the function of supplying energy to the power with different powers, the utilization rate of stored energy is improved.
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In order to more clearly illustrate the embodiments or technical solutions in the prior art of the present invention, the drawings used in the description of the embodiments or prior art will be briefly described below, and it is obvious for those skilled in the art to obtain other drawings without creative efforts;
FIG. 1 is a flow chart of the present invention.
Detailed Description
The technical solutions in the embodiments of the present invention will be clearly and completely described below with reference to the drawings in the embodiments of the present invention, and it is obvious that the described embodiments are only a part of the embodiments of the present invention, and not all of the embodiments. All other embodiments, which can be derived by a person skilled in the art from the embodiments given herein without making any creative effort, shall fall within the protection scope of the present invention.
As shown in fig. 1, a method for analyzing flexibility of energy storage resources includes the following steps:
the method comprises the following steps: the dispatching center sends a power adjusting signal representing unmatched power supply and demand every hour;
step two: the supplier tracks the power adjustment signal to provide a demand response that satisfies the condition;
step three: sequencing the running time of the stored energy under the maximum power from large to small, and aggregating the stored energy with the same running time into a whole;
step four: according to the sequence of the running time of the stored energy under the maximum power from big to small, calling the stored energy from big to small, and obtaining the power of the stored energy when calling;
step five: after the dispatching center sends the next power adjusting signal, the stored energy is reordered and called to meet the demand and supply requirements;
step six: and after all the stored energy is exhausted, generating a capacity curve according to the obtained power and the corresponding time period during energy storage calling, wherein if the capacity curve is below the maximum capacity curve, the energy storage calling meets the flexibility requirement, and if part of the capacity curve is above the maximum capacity curve, the sorting error is shown.
It should be further noted that, in the implementation process, the process of sorting the operation times of the energy storages at the maximum power from large to small and aggregating the energy storages with the same operation time into a whole includes:
grid imbalance signal:
in the formula PrSending a signal every hour for a power grid unbalanced signal;
run time at maximum stored energy:
in the formula xi(t) maximum run time of the plant, ei(t) is the energy of the device,
is the maximum discharge power of the device;
run time and power set:
x(t)＝[x1(t)...xn(t)]T
sorting each device from large to small according to the running time:
the energy storage with the same running time is aggregated into a whole:
in the formula
And aggregating the stored energy for the same operation time.
It should be further noted that, in the implementation process, the process of calling the energy storage from large to small includes:
setting received unbalanced signal of power grid to PrAnd are called in descending order to satisfy the signal value Pr：
In the formula riAs a percentage of the corresponding energy storage call,
power values for different run times; the stored energy is called in sequence, when the power is less than the signal value PrWhen the energy is stored, the whole energy storage is completely called; when the power of the finally called stored energy is larger than the signal value PrAnd in time, the stored energy is called according to the proportion, and the rest stored energy is kept unchanged.
It should be further noted that, in the implementation, the next P is receivedrAfter the signals are sent, the stored energy is sorted again and called according to the stored energy sorting sequenceTo meet the power grid balance requirement.
It should be further noted that, in a specific implementation process, the process of verifying whether the capacity curve meets the requirement of the maximum capacity curve is as follows:
calculating a capacity curve, and converting an E-p formula:
in the formula, a reference signal PrP is the power of each stored energy, [0, + ∞ ];
sorting the stored energy according to the running time under the maximum power from large to small, and obtaining a maximum capacity curve according to an E-p conversion formula;
according to the obtained energy storage power and the corresponding time period, an actual capacity curve can be obtained through an E-p conversion formula;
the actual capacity curve is below the maximum capacity curve, i.e. the flexibility requirement is met.
It should be further explained that, in the specific implementation process, an energy storage resource flexibility analysis device is characterized by comprising a measured state parameter acquisition module and an energy storage power output module;
the measured state parameter acquisition module is used for acquiring measured state parameters of the measured energy storage, and the measured state parameters comprise power and energy in the measured energy storage;
the energy storage calling output module is used for inputting the measured energy storage state parameters into a graphical energy storage resource flexibility analysis model which is trained in advance, the output measured energy storage is matched with a target power grid imbalance signal, and the graphical energy storage resource flexibility analysis model is obtained based on machine learning model training.
It should be further noted that, in an implementation, an apparatus for energy storage resource flexibility analysis includes a memory and one or more processors, where the memory is used for storing one or more programs, and the one or more programs are executed by the one or more processors, so that the processors implement the energy storage resource flexibility analysis method described above.
Further, a storage medium for energy storage resource flexibility analysis, the storage medium containing computer executable instructions for performing a method of energy storage resource flexibility analysis as described above when executed by a computer processor.
It should be further appreciated that, in the context of this application, a computer storage medium may be any combination of one or more computer-readable media. The computer readable medium may be a computer readable signal medium or a computer readable storage medium. The computer readable storage medium may be, for example, but not limited to, an electronic, magnetic, optical, electrical, magnetic, infrared, or semiconductor system, apparatus, or device, or any combination of the foregoing. More specific examples (a non-exhaustive list) of the computer readable storage medium would include the following: an electrical connection having one or more wires, a portable computer diskette, 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 disc read-only memory (CD-ROM), an optical storage device, a magnetic storage device, or any suitable combination of the foregoing. In the context of this document, a computer readable storage medium may be any tangible medium that can contain, or store a program for use by or in connection with an instruction execution system, apparatus, or device.
The foregoing shows and describes the general principles, essential features, and advantages of the invention. It will be understood by those skilled in the art that the present invention is not limited to the embodiments described above, which are described in the specification and illustrated only to illustrate the principle of the present invention, but that various changes and modifications may be made therein without departing from the spirit and scope of the present invention, which fall within the scope of the invention as claimed.
Claims (8)
1. An energy storage resource flexibility analysis method is characterized by comprising the following steps:
the method comprises the following steps: the dispatching center sends a power adjusting signal representing unmatched power supply and demand every hour;
step two: the supplier tracks the power adjustment signal to provide a demand response that satisfies the condition;
step three: sequencing the running time of the stored energy under the maximum power from large to small, and aggregating the stored energy with the same running time into a whole;
step four: according to the sequence of the running time of the stored energy under the maximum power from big to small, calling the stored energy from big to small, and obtaining the power of the stored energy when in calling;
step five: after the dispatching center sends the next power adjusting signal, the stored energy is reordered and called to meet the demand and supply requirements;
step six: and after all the stored energy is exhausted, generating a capacity curve according to the obtained power during the energy storage calling and the corresponding time period, verifying whether the capacity curve meets the requirement of the maximum capacity curve, if the capacity curve is below the maximum capacity curve, indicating that the energy storage calling meets the flexibility requirement, wherein the flexibility requirement is that the called capacity curve meets the requirement of the maximum capacity curve, and if part of the capacity curve is above the maximum capacity curve, indicating that the sorting has errors.
2. The method for analyzing the flexibility of energy storage resources according to claim 1, wherein the process of sequencing the running times of the energy storage at the maximum power from large to small and aggregating the energy storage with the same running time into a whole comprises:
grid imbalance signal:
in the formula PrSending a signal every hour for a power grid unbalanced signal;
run time at maximum stored energy:
in the formula xi(t) maximum run time of the plant, ei(t) is the energy of the device,
is the maximum discharge power of the device;
run time and power set:
x(t)＝[x1(t)...xn(t)]T
sorting each device from large to small according to the running time:
energy storage with the same running time is aggregated into a whole:
in the formula
And aggregating the stored energy for the same operation time.
3. The method for analyzing the flexibility of the energy storage resources according to claim 1, wherein the process of calling the energy storage from large to small comprises the following steps:
setting received unbalanced signal of power grid to PrAnd are called in descending order to satisfy the signal value Pr：
In the formula riAs a percentage of the corresponding energy storage call,
power values for different run times; the stored energy is called in sequence, when the power is less than the signal value PrWhen the energy is stored, the whole energy storage is completely called; when the power of the finally called stored energy is larger than the signal value PrAnd in time, the stored energy is called according to the proportion, and the rest stored energy is kept unchanged.
4. A method for energy storage resource flexibility analysis according to claim 1, wherein a next P is receivedrAfter the signals are sent, the stored energy is sorted again, and the stored energy is called according to the stored energy sorting sequence to meet the power grid balance requirement.
5. The method for analyzing the flexibility of the energy storage resource according to claim 1, wherein the process of verifying whether the capacity curve meets the requirement of the maximum capacity curve is as follows:
calculating a capacity curve, and converting an E-p formula:
in the formula, a reference signal PrP is the power of each stored energy, [0, + ∞ ];
sorting the stored energy according to the running time under the maximum power from large to small, and obtaining a maximum capacity curve according to an E-p conversion formula;
according to the obtained energy storage power and the corresponding time period, an actual capacity curve can be obtained through an E-p conversion formula;
the actual capacity curve is below the maximum capacity curve, i.e. the flexibility requirement is met.
6. The energy storage resource flexibility analysis device is characterized by comprising a measured state parameter acquisition module and an energy storage power output module;
the measured state parameter acquisition module is used for acquiring measured state parameters of the measured energy storage, and the measured state parameters comprise power and energy in the measured energy storage;
the energy storage power output module is used for inputting the measured state parameters into a graphical energy storage resource flexibility analysis model which is trained in advance, the output measured energy storage is matched with a target power grid imbalance signal, and the graphical energy storage resource flexibility analysis model is obtained based on machine learning model training.
7. An energy storage resource flexibility analysis device, comprising a memory and one or more processors, the memory storing one or more programs, the one or more programs being executable by the one or more processors to cause the processors to implement an energy storage resource flexibility analysis method as claimed in any one of claims 1-5.
8. A storage medium for energy storage resource flexibility analysis, the storage medium containing computer-executable instructions which, when executed by a computer processor, are configured to perform an energy storage resource flexibility analysis method as claimed in any one of claims 1-5.
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