CN112257945A - Power clearing automatic optimization method and system based on energy storage users - Google Patents
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Abstract
The invention relates to an automatic optimization method and system for power clearing based on energy storage users. The invention does not need a large amount of manual work, has higher automation degree, and improves the efficiency of electric power clearing and the operation and maintenance controllability of energy storage users on energy storage equipment.
Description
Technical Field
The invention belongs to the field of power system automation, and particularly relates to an automatic power clearing optimization method and system based on energy storage users.
Background
The energy storage has a positive influence on stabilizing the output fluctuation of clean energy and improving the operation efficiency of a power grid due to the advantage that the translation transfer of the power load can be quickly realized. Always, the main profit mode of the energy storage equipment participating in the operation of the power grid is peak clipping and valley filling, the profit mode is single, and the investment return rate is low. The release of the market on the demand side enables energy storage users to participate in electric power market competition as market main bodies and directly obtain market dividends. On the other hand, with the gradual advance of the spot market, the time attribute of the electric energy is reflected, and the energy storage user can obtain profits from the electricity price difference at different times. Because the investment cost of energy storage construction is high, the operating characteristics are different from the traditional users and power supplies, a flexible quotation mode which is beneficial to cost recovery and gives consideration to market clearing convenience is required to be designed, and the interaction with clean energy is smoothly realized.
In the prior art, the electric power based on the energy storage user is clear, a large amount of manual work is needed, the automation degree is low, the efficiency is not high, and the operation and maintenance controllability of the energy storage user on the energy storage device is also poor.
Disclosure of Invention
The invention mainly aims to overcome the defects and shortcomings of the prior art and provides an automatic power clearing optimization method and system based on energy storage users. The invention does not need a large amount of manual work, has higher automation degree, and improves the efficiency of electric power clearing and the operation and maintenance controllability of energy storage users on energy storage equipment.
According to one aspect of the invention, the invention provides an automatic optimization method for power clearing based on energy storage users, which comprises the following steps:
s1, receiving a power output optimization request;
s2, responding to the optimization request, determining the life cycle cost information of the energy storage user and the life cycle cost information in a single transaction period;
s3, determining expected income information based on the life cycle cost information, and determining the electric quantity information of the flexible electric quantity block based on the expected income information, the parameter information in a preset declaration model and a first constraint condition;
s4, acquiring declaration information of an energy storage user, wherein the declaration information comprises electric quantity information of the flexible electric quantity block; performing power clearing optimization based on the declaration information and a second constraint condition to obtain a clearing optimization result;
s5: and returning and displaying the clearing optimization result.
Preferably, the life cycle cost C of the energy storage user comprises investment cost C1, operation and maintenance cost C2 and loss cost C3; wherein the content of the first and second substances,
C＝C1+C2+C3，C1＝αeEmax+αpp，
the life cycle cost within a single transaction cycle j of the energy storage user is:
in the formula, alphae、αp、αmAnd alphawRespectively representing the unit capacity cost, unit charging and discharging power cost, unit operation and maintenance cost and unit capacity loss cost of energy storage; emaxAnd p is the rated capacity and rated charge-discharge power of the stored energy respectively; i.e. ir、drRespectively showing the inflation rate and the discount rate of the currency; y is the energy storage service life; y is the expected cost recovery life of the stored energy, and N is the maximum charging and discharging times of the stored energy; b isjIs the number of charging and discharging times in the transaction period.
Preferably, the predetermined declaration model is:
in the formula (I), the compound is shown in the specification,
and
the energy storage user i reports the power price pair gamma respectively in charging and dischargingi、ViRespectively a declaration time interval set and a declaration energy block of an energy storage user i,
and
the states of charge at the initial and end time of user participation, respectively;
Vi＝[Va，Vb，Vc…]and satisfy
And
the corresponding relationship of (1).
Preferably, the first constraint condition is:
the second constraint includes: market declaration constraints, energy storage operation constraints, and energy storage cost constraints.
According to another aspect of the present invention, the present invention further provides an energy storage user-based power output automatic optimization system, including:
the request receiving module is used for receiving a power output and clearing optimization request;
the first determining module is used for responding to the optimization request, and determining the life cycle cost information of the energy storage user and the life cycle cost information in a single transaction period;
the second determining module is used for determining expected income information based on the life cycle cost information and determining the electric quantity information of the flexible electric quantity block based on the expected income information, the parameter information in a preset reporting model and the first constraint condition;
the clearing optimization module is used for acquiring declaration information of an energy storage user, wherein the declaration information comprises electric quantity information of the flexible electric quantity block; performing power clearing optimization based on the declaration information and a second constraint condition to obtain a clearing optimization result;
and returning to the display module, and returning and displaying the clearing optimization result.
Preferably, the life cycle cost C of the energy storage user comprises investment cost C1, operation and maintenance cost C2 and loss cost C3; wherein the content of the first and second substances,
C＝C1+C2+C3，C1＝αeEmax+αpp，
the life cycle cost within a single transaction cycle j of the energy storage user is:
in the formula, alphae、αp、αmAnd alphawRespectively representing the unit capacity cost, unit charging and discharging power cost, unit operation and maintenance cost and unit capacity loss cost of energy storage; emaxAnd p is the rated capacity and rated charge-discharge power of the stored energy respectively; i.e. ir、drRespectively showing the inflation rate and the discount rate of the currency; y is the energy storage service life; y is the expected cost recovery age of stored energyN is the maximum energy storage charging and discharging times; b isjIs the number of charging and discharging times in the transaction period.
Preferably, the predetermined declaration model is:
in the formula (I), the compound is shown in the specification,
and
the energy storage user i reports the power price pair gamma respectively in charging and dischargingi、ViRespectively a declaration time interval set and a declaration energy block of an energy storage user i,
and
the states of charge at the initial and end time of user participation, respectively;
Vi＝[Va，Vb，Vc…]and satisfy
And
the corresponding relationship of (1).
Preferably, the first constraint condition is:
the second constraint includes: market declaration constraints, energy storage operation constraints, and energy storage cost constraints.
According to another aspect of the present invention, the present invention further provides an energy storage user-based power output automatic optimization system, including: a processor, a memory, said memory storing computer executable instructions which, when executed by the processor, implement the above-mentioned method steps.
According to another aspect of the present invention, there is also provided a computer-readable storage medium, characterized in that the computer-readable storage medium stores computer-executable instructions which, when executed by a processor, implement the above-mentioned method steps.
Has the advantages that: the invention does not need a large amount of manual work, has higher automation degree, and improves the efficiency of electric power clearing and the operation and maintenance controllability of energy storage users on energy storage equipment.
The features and advantages of the present invention will become apparent by reference to the following drawings and detailed description of specific embodiments of the invention.
Drawings
The accompanying drawings, which are incorporated in and constitute a part of this application, illustrate embodiments of the invention and, together with the description, serve to explain the invention and not to limit the invention. In the drawings:
FIG. 1 is a flow chart of a method for automatically optimizing power output based on energy storage users according to the present invention;
FIG. 2 is a schematic diagram of an energy storage consumer-based automatic power output optimization system of the present invention;
fig. 3 is a schematic diagram of another energy storage user-based automatic power output optimization system according to the present invention.
Detailed Description
The technical solutions in the embodiments of the present invention are 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 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.
Unless defined otherwise, all technical and scientific terms used herein have the same meaning as commonly understood by one of ordinary skill in the art to which this invention belongs. The terminology used in the description of the invention herein is for the purpose of describing particular embodiments only and is not intended to be limiting of the invention. As used herein, the term "and/or" includes any and all combinations of one or more of the associated listed items.
Example 1
Fig. 1 is a flow chart of an automatic power clearing optimization method based on energy storage users according to the invention. As shown in fig. 1, the present invention provides an automatic optimization method for power clearing based on energy storage users, which comprises the following steps:
s1, receiving a power output optimization request;
in this step, a user may input a request through a user interface in the system to request the system to perform power clearing optimization.
S2, responding to the optimization request, determining the life cycle cost information of the energy storage user and the life cycle cost information in a single transaction period;
in the step, the energy storage user calculates the cost expenditure in a single transaction period according to the investment cost, the operation and maintenance cost and the loss cost.
The user side energy storage life cycle cost comprises three factors, wherein the life cycle cost C of the energy storage user comprises investment cost C1, operation and maintenance cost C2 and loss cost C3; wherein the content of the first and second substances,
C＝C1+C2+C3，C1＝αeEmax+αpp，
in the formula, alphae、αp、αmAnd alphawRespectively the unit capacity cost, unit charging and discharging power cost, unit operation and maintenance cost andloss cost per unit capacity; emaxAnd p is the rated capacity and rated charge-discharge power of the stored energy respectively; i.e. ir、drRespectively showing the inflation rate and the discount rate of the currency; y is the energy storage service life; y is the expected cost recovery life of the stored energy, and N is the maximum charging and discharging times of the stored energy; b isjIs the number of charging and discharging times in the transaction period.
When parameters such as cost coefficient, currency expansion rate, current rate, expected life cycle of energy storage and the like are determined, the conversion of the total life cycle cost of an energy storage user to a single transaction cycle j can be expressed as:
s3, determining expected income information based on the life cycle cost information, and determining the electric quantity information of the flexible electric quantity block based on the expected income information, the parameter information in a preset declaration model and a first constraint condition;
in the step, the single charge-discharge cycle income and the final investment recovery period of the energy storage user participating in the market transaction are determined, and the lowest expected income in one transaction period should cover the cost.
And reporting transaction information such as charging and discharging power, electricity price, charge state, flexible reporting time period, flexible electric energy block and the like according to the requirements of the reporting model. The reporting model is as follows:
preferably, the predetermined declaration model is:
in the formula (I), the compound is shown in the specification,
and
the energy storage user i reports the power price pair gamma respectively in charging and dischargingi、ViRespectively a declaration time interval set and a declaration energy block of an energy storage user i,
and
the states of charge at the initial and end time of user participation, respectively;
Vi＝[Va，Vb，Vc…]and satisfy
And
the corresponding relationship of (1).
For example, the information about participation of a certain energy storage user in the market declaration at the day-ahead time is as follows:
{(20，500)，(20，200)，(t3-t7，t8-t13，t20-t22)，0.2，0.2，(-80，220，-40)}
the formula shows that the energy storage user declares that the discharge power and the charge power are both 20MW, the discharge price is not lower than 500 yuan/MWh, the charge price is not higher than 200 yuan/MWh, and the charge states of the energy storage at the starting time and the ending time of the transaction period are both 0.2; the flexible operation time periods are three and are respectively t3-t7、t8-t13And t20-t22And the electric quantity of the energy block is reported to be 80MWh for charging, 220MWh for discharging and 40MWh for charging in three time intervals.
And calculating the electric quantity of the flexible power block according to the calculated expected income and by combining with the energy storage operation characteristic.
Preferably, the first constraint is:
s4: acquiring declaration information of an energy storage user, wherein the declaration information comprises electric quantity information of a flexible electric quantity block; performing power clearing optimization based on the declaration information and a second constraint condition to obtain a clearing optimization result;
in this step, the second constraint condition includes: market declaration constraints, energy storage operation constraints, and energy storage cost constraints.
Specifically, the system performs market clearing by taking social welfare as a maximum target and taking clean energy market declaration constraints, energy storage operation constraints and energy storage cost constraints as constraint conditions according to declaration information submitted by an energy storage user and clean energy declaration information. In each transaction period gamma _ i, the transaction can be completed as long as the transaction power is ensured to be higher than the corresponding V _ i.
S5: and returning and displaying the clearing optimization result.
In this step, the optimization result can be output and displayed to the dispatcher through a display of the user interface.
In this embodiment, in response to a request, the life cycle cost information and the expected revenue information of an energy storage user are determined, the electric quantity information of the flexible electric quantity block is determined based on the parameter information in the declaration model and the first constraint condition, and electric power clearing optimization is performed based on the declaration information including the electric quantity information of the flexible electric quantity block and the second constraint condition, so that a clearing optimization result is obtained. The invention does not need a large amount of manual work, has higher automation degree, and improves the efficiency of electric power clearing and the operation and maintenance controllability of energy storage users on energy storage equipment.
Example 2
Fig. 2 is a schematic diagram of the automatic power output and cleaning optimization system based on the energy storage users. As shown in fig. 2, the present invention further provides an energy storage user-based power output automatic optimization system, which includes:
the request receiving module is used for receiving a power output and clearing optimization request;
the first determining module is used for responding to the optimization request, and determining the life cycle cost information of the energy storage user and the life cycle cost information in a single transaction period;
the second determining module is used for determining expected income information based on the life cycle cost information and determining the electric quantity information of the flexible electric quantity block based on the expected income information, the parameter information in a preset reporting model and the first constraint condition;
the clearing optimization module is used for acquiring declaration information of an energy storage user, wherein the declaration information comprises electric quantity information of the flexible electric quantity block; performing power clearing optimization based on the declaration information and a second constraint condition to obtain a clearing optimization result;
and returning to the display module, and returning and displaying the clearing optimization result.
Preferably, the life cycle cost C of the energy storage user comprises investment cost C1, operation and maintenance cost C2 and loss cost C3; wherein the content of the first and second substances,
C＝C1+C2+C3，C1＝αeEmax+αpp，
the life cycle cost within a single transaction cycle j of the energy storage user is:
in the formula, alphae、αp、αmAnd alphawRespectively representing the unit capacity cost, unit charging and discharging power cost, unit operation and maintenance cost and unit capacity loss cost of energy storage; emaxAnd p is the rated capacity and rated charge-discharge power of the stored energy respectively; i.e. ir、drRespectively showing the inflation rate and the discount rate of the currency; y is the energy storage service life; y is the expected cost recovery life of the stored energy, and N is the maximum charging and discharging times of the stored energy; b isjIs the number of charging and discharging times in the transaction period.
Preferably, the predetermined declaration model is:
in the formula (I), the compound is shown in the specification,
and
the energy storage user i reports the power price pair gamma respectively in charging and dischargingi、ViRespectively a declaration time interval set and a declaration energy block of an energy storage user i,
and
the states of charge at the initial and end time of user participation, respectively;
Vi＝[Va，Vb，Vc…]and satisfy
And
the corresponding relationship of (1).
Preferably, the first constraint condition is:
the second constraint includes: market declaration constraints, energy storage operation constraints, and energy storage cost constraints.
The specific implementation process of the method steps executed by each module in embodiment 2 of the present invention is the same as the implementation process of each step in embodiment 1, and is not described herein again.
Example 3
Fig. 3 is a schematic diagram of another energy storage user-based automatic power output optimization system according to the present invention. As shown in fig. 3, the present invention further provides an energy storage user-based power output automatic optimization system, which includes: the processor and the memory, where the memory stores computer-executable instructions, and the computer-executable instructions are executed by the processor to implement the method steps in embodiment 1, and a specific implementation process may refer to an implementation process of the method steps in embodiment 1, which is not described herein again.
Example 4
According to another aspect of the present invention, the present invention further provides a computer-readable storage medium, where the computer-readable storage medium stores computer-executable instructions, and the computer-executable instructions, when executed by a processor, implement the method steps in embodiment 1, and for a specific implementation process, reference may be made to an implementation process of the method steps in embodiment 1, which is not described herein again.
As will be appreciated by one skilled in the art, embodiments of the present application may be provided as a method, system, or computer program product. Accordingly, the present application may take the form of an entirely hardware embodiment, an entirely software embodiment or an embodiment combining software and hardware aspects. Furthermore, the present application may take the form of a computer program product embodied on one or more computer-usable storage media (including, but not limited to, disk storage, CD-ROM, optical storage, and the like) having computer-usable program code embodied therein.
The present application is described with reference to flowchart illustrations and/or block diagrams of methods, apparatus (systems), and computer program products according to embodiments of the application. It will be understood that each flow and/or block of the flow diagrams and/or block diagrams, and combinations of flows and/or blocks in the flow diagrams and/or block diagrams, can be implemented by computer program instructions. These computer program instructions may be provided to a processor of a general purpose computer, special purpose computer, embedded processor, or other programmable data processing apparatus to produce a machine, such that the instructions, which execute via the processor of the computer or other programmable data processing apparatus, create means for implementing the functions specified in the flowchart flow or flows and/or block diagram block or blocks.
These computer program instructions may also be stored in a computer-readable memory that can direct a computer or other programmable data processing apparatus to function in a particular manner, such that the instructions stored in the computer-readable memory produce an article of manufacture including instruction means which implement the function specified in the flowchart flow or flows and/or block diagram block or blocks.
These computer program instructions may also be loaded onto a computer or other programmable data processing apparatus to cause a series of operational steps to be performed on the computer or other programmable apparatus to produce a computer implemented process such that the instructions which execute on the computer or other programmable apparatus provide steps for implementing the functions specified in the flowchart flow or flows and/or block diagram block or blocks.
Finally, it should be noted that: the above embodiments are only for illustrating the technical solutions of the present invention and not for limiting the same, and although the present invention is described in detail with reference to the above embodiments, those of ordinary skill in the art should understand that: modifications and equivalents may be made to the embodiments of the invention without departing from the spirit and scope of the invention, which is to be covered by the claims.
Claims (10)
1. An automatic optimization method for power clearing based on energy storage users is characterized by comprising the following steps:
s1: receiving a power clearing optimization request;
s2: responding to the optimization request, and determining the life cycle cost information of the energy storage user and the life cycle cost information in a single transaction period;
s3: determining expected revenue information based on the life cycle cost information, and determining electric quantity information of the flexible electric quantity block based on the expected revenue information, parameter information in a preset declaration model and a first constraint condition;
s4: acquiring declaration information of an energy storage user, wherein the declaration information comprises electric quantity information of a flexible electric quantity block; performing power clearing optimization based on the declaration information and a second constraint condition to obtain a clearing optimization result;
s5: and returning and displaying the clearing optimization result.
2. The method of claim 1, wherein the energy storage user's life cycle cost C comprises investment cost C1, operation and maintenance cost C2, loss cost C3; wherein the content of the first and second substances,
C＝C1+C2+C3，C1＝αeEmax+αpp，
the life cycle cost within a single transaction cycle j of the energy storage user is:
in the formula, alphae、αp、αmAnd alphawRespectively representing the unit capacity cost, unit charging and discharging power cost, unit operation and maintenance cost and unit capacity loss cost of energy storage; emaxAnd p is the rated capacity and rated charge-discharge power of the stored energy respectively; i.e. ir、drRespectively showing the inflation rate and the discount rate of the currency; y is the energy storage service life; y is the expected cost recovery life of the stored energy, and N is the maximum charging and discharging times of the stored energy; b isjIs the number of charging and discharging times in the transaction period.
3. The method of claim 2, wherein the predetermined declaration model is: bidi：
In the formula (I), the compound is shown in the specification,
and
the energy storage user i reports the power price pair gamma respectively in charging and dischargingi、ViRespectively a declaration time interval set and a declaration energy block of an energy storage user i,
and
the states of charge at the initial and end time of user participation, respectively;
Vi＝[Va，Vb，Vc…]and satisfy
And
the corresponding relationship of (1).
4. The method of claim 3, wherein the first constraint is:
the second constraint includes: market declaration constraints, energy storage operation constraints, and energy storage cost constraints.
5. An energy storage user-based automatic power output optimization system, comprising:
the request receiving module is used for receiving a power output and clearing optimization request;
the first determining module is used for responding to the optimization request, and determining the life cycle cost information of the energy storage user and the life cycle cost information in a single transaction period;
the second determining module is used for determining expected income information based on the life cycle cost information and determining the electric quantity information of the flexible electric quantity block based on the expected income information, the parameter information in a preset reporting model and the first constraint condition;
the clearing optimization module is used for acquiring declaration information of an energy storage user, wherein the declaration information comprises electric quantity information of the flexible electric quantity block; performing power clearing optimization based on the declaration information and a second constraint condition to obtain a clearing optimization result;
and returning to the display module, and returning and displaying the clearing optimization result.
6. The system of claim 5, wherein the energy storage user's full life cycle cost C comprises an investment cost C1, an operation and maintenance cost C2, a loss cost C3; wherein the content of the first and second substances,
C＝C1+C2+C3，C1＝αeEmax+αpp，
the life cycle cost within a single transaction cycle j of the energy storage user is:
in the formula, alphae、αp、αmAnd alphawRespectively unit capacity cost and unit charge-discharge power of stored energyCost, unit operation and maintenance cost and unit capacity loss cost; emaxAnd p is the rated capacity and rated charge-discharge power of the stored energy respectively; i.e. ir、drRespectively showing the inflation rate and the discount rate of the currency; y is the energy storage service life; y is the expected cost recovery life of the stored energy, and N is the maximum charging and discharging times of the stored energy; b isjIs the number of charging and discharging times in the transaction period.
7. The system of claim 6, wherein the predetermined declaration model is: bidi：
In the formula (I), the compound is shown in the specification,
and
the energy storage user i reports the power price pair gamma respectively in charging and dischargingi、ViRespectively a declaration time interval set and a declaration energy block of an energy storage user i,
and
the states of charge at the initial and end time of user participation, respectively;
Vi＝[Va，Vb，Vc…]and satisfy
And
the corresponding relationship of (1).
8. The system of claim 7, wherein the first constraint is:
the second constraint includes: market declaration constraints, energy storage operation constraints, and energy storage cost constraints.
9. An energy storage user-based automatic power output optimization system, comprising: a processor, a memory storing computer-executable instructions that, when executed by the processor, implement the method of any one of claims 1-4.
10. A computer-readable storage medium having computer-executable instructions stored thereon which, when executed by a processor, implement the method of any one of claims 1-4.
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| CN113270896A (en) * | 2021-07-20 | 2021-08-17 | 中国电力科学研究院有限公司 | Electric energy and auxiliary service joint optimization method, system, equipment and storage medium |
| CN116976531A (en) * | 2023-09-25 | 2023-10-31 | 华夏天信智能物联股份有限公司 | Integrated management method and system for underground electric control equipment |
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