CN114462676A - User side energy storage optimization method and system - Google Patents
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Abstract
The invention is suitable for the technical field of electric power, and provides a user side energy storage optimization method and a system, wherein the method comprises the following steps: acquiring electricity charge data of a user side and compensation electricity charge data of a demand side; establishing an energy storage optimization model of a user side according to the electric charge data and the compensation electric charge data; determining a predicted demand side response curve according to historical power consumption data of a user side; and determining the optimal response power according to the energy storage optimization model and the predicted demand side response curve, and optimizing the energy storage at the user side based on the optimal response power. The invention can solve the problem of unbalance between power supply and demand at present.
Description
Technical Field
The invention belongs to the technical field of electric power, and particularly relates to a user side energy storage optimization method and system.
Background
With the continuous development of society, users are making higher and higher requirements on the quality and reliability of electric energy, and today, the traditional power system is challenged seriously due to the more and more serious environmental deterioration and resource crisis.
In recent years, the electricity consumption demand of China keeps increasing rapidly, the electricity consumption peak-valley difference is increased year by year, and seasonal electricity shortage occurs at times. Although the order of power supply and utilization can be effectively guaranteed to be stable through the ordered power utilization management, the contradiction between supply and demand still can cause certain influence on industrial production, so that the difficulty of organization coordination implementation is continuously increased. How to relieve the contradiction between power supply and demand and promote the optimal configuration of resources becomes an urgent problem to be solved.
Disclosure of Invention
In view of this, embodiments of the present invention provide a method and a system for optimizing energy storage at a user side, so as to solve the problem of imbalance between power supply and demand in the prior art.
A first aspect of an embodiment of the present invention provides a user-side energy storage optimization method, including:
acquiring electricity charge data of a user side and compensation electricity charge data of a demand side;
establishing an energy storage optimization model of a user side according to the electric charge data and the compensation electric charge data;
determining a predicted demand side response curve according to historical power consumption data of a user side;
and determining the optimal response power according to the energy storage optimization model and the predicted demand side response curve, and optimizing the energy storage at the user side based on the optimal response power.
Optionally, the establishing of the energy storage optimization model at the user side includes:
establishing an objective function by taking the lowest monthly energy storage electricity charge of the user side as a target, and establishing a constraint condition of the objective function to obtain an energy storage optimization model of the user side; an objective function of
K＝minimize(S1)+S2-S3
In the formula, K is the current-month energy storage electricity fee of the user side, S1 is the current-month electricity quantity and electricity fee of the user side, S2 is the current-month demand electricity fee of the user side, and S3 is the current-month compensation electricity fee of the demand side.
Optionally, determining a predicted demand side response curve according to the historical power consumption data of the user side includes:
and determining a historical demand side response curve according to the historical power consumption data, and determining a predicted demand side response curve based on the historical demand side response curve.
Optionally, determining the optimal response power according to the energy storage optimization model and the predicted demand side response curve includes:
acquiring energy storage capacity, energy storage rated power and annual load peak clipping rate;
and calculating an energy storage optimal charging and discharging curve according to the parameters of the energy storage optimization model and the parameters of the predicted demand side response curve, and determining the optimal response power based on the energy storage optimal charging and discharging curve, the energy storage capacity, the energy storage rated power and the annual load peak clipping rate.
Optionally, the monthly electricity amount and the electricity charge of the user side are calculated in a time-sharing charging mode.
Optionally, the demand side is a power station, and the user side is an energy storage battery; or the demand side is an energy storage battery, and the user side is an electricity user.
Optionally, the energy storage optimization model is represented in a curve form; after optimizing the user-side energy storage, the method further comprises:
comparing the curve of the energy storage optimization model with the predicted demand side response curve;
and if the difference of the curvatures of the two curves exceeds a preset threshold and the duration time reaches a preset duration, performing abnormity warning, analyzing abnormity reasons and storing abnormity information.
A second aspect of an embodiment of the present invention provides a user-side energy storage optimization system, including:
the acquisition module is used for acquiring the electric charge data of the user side and the compensation electric charge data of the demand side;
the building module is used for building an energy storage optimization model of the user side according to the electric charge data and the compensation electric charge data;
the budget module is used for determining a predicted demand side response curve according to historical power consumption data of a user side;
and the optimization module is used for determining the optimal response power according to the energy storage optimization model and the predicted demand side response curve and optimizing the energy storage at the user side based on the optimal response power.
A third aspect of embodiments of the present invention provides an electronic device, including a memory, a processor, and a computer program stored in the memory and executable on the processor, where the processor implements the steps of the user-side energy storage optimization method according to the first aspect when executing the computer program.
A fourth aspect of embodiments of the present invention provides a computer-readable storage medium, which stores a computer program, and when the computer program is executed by a processor, the steps of the user-side energy storage optimization method according to the first aspect are implemented.
Compared with the prior art, the embodiment of the invention has the following beneficial effects:
the embodiment of the invention provides a user side energy storage optimization method considering incentive demand side response, namely, the optimal response power is calculated under a user side energy storage optimization model and a predicted demand side response curve, so that the optimization of user side energy storage is carried out, a long-acting mechanism of power demand response can be favorably established, the contradiction between power supply and demand is solved, and the economic benefit is improved.
Drawings
In order to more clearly illustrate the technical solutions in the embodiments of the present invention, the drawings needed to be used in the embodiments or the prior art descriptions will be briefly described below, and it is obvious that the drawings in the following description are only some embodiments of the present invention, and it is obvious for those skilled in the art to obtain other drawings based on these drawings without inventive exercise.
Fig. 1 is a schematic flow chart of a user-side energy storage optimization method according to an embodiment of the present invention;
fig. 2 is a schematic structural diagram of a user-side energy storage optimization system according to an embodiment of the present invention;
fig. 3 is a schematic structural diagram of an electronic device according to an embodiment of the present invention.
Detailed Description
In the following description, for purposes of explanation and not limitation, specific details are set forth, such as particular system structures, techniques, etc. in order to provide a thorough understanding of the embodiments of the invention. It will be apparent, however, to one skilled in the art that the present invention may be practiced in other embodiments that depart from these specific details. In other instances, detailed descriptions of well-known systems, devices, circuits, and methods are omitted so as not to obscure the description of the present invention with unnecessary detail.
In order to explain the technical means of the present invention, the following description will be given by way of specific examples.
Referring to fig. 1, an embodiment of the present invention provides a user-side energy storage optimization method, which specifically includes the following steps:
step S101, acquiring the electricity charge data of the user side and the compensation electricity charge data of the demand side.
In the embodiment of the invention, the electricity charge data of the user side comprises the electricity quantity and electricity charge of the current month and the electricity charge of the current month demand. Optionally, the total amount of the monthly electric quantity and the electric charge is charged in a time-sharing manner, the total amount of the monthly electric quantity and the electric charge can be acquired once every 60 minutes in the electricity consumption valley time period through the electricity price acquisition device, the electricity charge of the first 60 minutes is acquired every time, the electricity charge of the first 30 minutes is acquired every 30 minutes in the electricity consumption level time period and the electricity consumption peak time period, and the electricity charge acquired at each acquisition time point of the electricity consumption valley time period, the electricity consumption level time period and the electricity consumption peak time period is calculated to obtain the monthly electric quantity and the electric charge. The monthly demand electric charge can be calculated by monitoring the monthly maximum demand through an electric energy meter, and the maximum demand is the maximum active power value of the electric energy used at a certain moment.
Meanwhile, the electric energy meter can also be used for monitoring the approved demand, and when the maximum demand does not exceed the approved demand, the basic electric charge calculation formula is as follows: the basic electricity charge is the real maximum demand of reading and the basic electricity price of charging according to the demand, and when the maximum demand exceeds the approved fixed demand, the basic electricity charge calculation formula is as follows: the basic electricity fee is the rated demand × the basic electricity price charged by demand + (maximum demand-rated demand) × 2 × the basic electricity price charged by demand.
And S102, establishing an energy storage optimization model of the user side according to the electric charge data and the compensation electric charge data.
Optionally, the establishing of the energy storage optimization model at the user side includes:
establishing an objective function by taking the lowest monthly energy storage electricity charge of the user side as a target, and establishing a constraint condition of the objective function to obtain an energy storage optimization model of the user side; an objective function of
K＝minimize(S1)+S2-S3
In the formula, K is the current-month energy storage electricity fee of the user side, S1 is the current-month electricity quantity and electricity fee of the user side, S2 is the current-month demand electricity fee of the user side, and S3 is the current-month compensation electricity fee of the demand side.
In the embodiment of the invention, the energy storage optimization model aims at optimizing the economic efficiency of energy storage at the user side, wherein the calculation formulas of S1, S2 and S3 are as follows:
in the formula, CiIs time-of-use electricity price, n is the number of collected points in the month, LoadiIs the user load power at the i-th moment, Pc,iCharging power for the stored energy at the i-th moment, Pd,iIs the energy storage discharge power at the i-th moment, Pdemand,maxThe maximum demand value reported by the user side, b is the actual demand value, alphaiInterruptible load electricity rates for demand response, siFor adjustingElectricity price standard v corresponding to time control lengthiIn response to the speed coefficient, PDSM,iAnd m is the number of required responses.
The constraint conditions of the objective function comprise energy storage charge state constraint, energy storage charge-discharge power constraint and energy storage charge state continuity constraint.
And step S103, determining a predicted demand side response curve according to the historical electricity consumption data of the user side.
Optionally, determining a predicted demand side response curve according to the historical power consumption data of the user side includes:
and determining a historical demand side response curve according to the historical power consumption data, and determining a predicted demand side response curve based on the historical demand side response curve.
In the embodiment of the invention, the trend of the historical demand side response curve is analyzed, so that the predicted demand side response curve can be predicted more accurately.
And S104, determining the optimal response power according to the energy storage optimization model and the predicted demand side response curve, and optimizing the energy storage of the user side based on the optimal response power.
Optionally, determining the optimal response power according to the energy storage optimization model and the predicted demand side response curve includes:
acquiring energy storage capacity, energy storage rated power and annual load peak clipping rate;
and calculating an energy storage optimal charging and discharging curve according to the parameters of the energy storage optimization model and the parameters of the predicted demand side response curve, and determining the optimal response power based on the energy storage optimal charging and discharging curve, the energy storage capacity, the energy storage rated power and the annual load peak clipping rate.
In the embodiment of the invention, the simulation duration is read, the related parameters of the energy storage optimization model and the predicted demand side response curve are read, the energy storage capacity, the energy storage rated power and the annual load peak clipping rate information in the simulation time period are read, the optimized model and the related parameters of the predicted demand side response curve in the simulation time period are called to calculate the optimal energy storage and discharge curve, and the optimal response power can be calculated according to the optimal energy storage and discharge curve, the energy storage capacity, the energy storage rated power and the annual load peak clipping rate information in the simulation time period.
Therefore, the embodiment of the invention provides a user side energy storage optimization method considering incentive demand side response, namely, the optimal response power is calculated under a user side energy storage optimization model and a predicted demand side response curve, so that the user side energy storage is optimized, a long-term power demand response mechanism can be established, the contradiction between power supply and demand is solved, and the economic benefit is improved.
Optionally, the demand side is a power station, and the user side is an energy storage battery; or the demand side is an energy storage battery, and the user side is an electricity user.
In the embodiment of the invention, due to the problem of supply and demand contradiction caused by the current electric quantity shortage, the user side energy storage optimization can provide reliable technical support for power utilization management, and meanwhile, the point that the energy storage system can not be separated when the user side stores energy, namely, the energy storage type battery is arranged at the angle of the user side to form the energy storage system, so that the buffer effect of the electric quantity can be formed at the low-voltage side, a part of electric power of photovoltaic power generation and the like with large output is absorbed, the control of a power regulation and control department on a continuous tide method, saddle node bifurcation and the like is enhanced, and the operation stability of a power grid is further improved.
When the energy storage system is installed on the user side, the energy storage battery is generally used for storing electric power, and under the model that the power station serves as a demand side and the energy storage battery serves as a user side, the user side can be a primary user such as a large-scale charging station, a large-scale enterprise, a signal base station, a port and a remote island. The energy storage function at the user side is: the energy storage battery comprises a primary energy storage battery K (primary energy storage battery) S1 (primary energy storage battery) + S2 (primary energy storage battery) -S3 (primary energy storage battery), wherein the primary energy storage battery K (primary energy storage battery) is the energy storage electricity fee required by the energy storage battery, the primary energy storage battery S1 (primary energy storage battery) is the electricity and electricity fee required by the energy storage battery, the primary energy storage battery S2 is the demand electricity fee required by the energy storage battery, and the primary energy storage battery S3 is the compensation electricity fee required by the energy storage battery.
Under the model that the energy storage battery is used as a demand side and the electricity user is used as a user side, the user side can be a secondary user such as a small-sized charging station, a small-sized enterprise, a hospital, a market, a hotel, a garden and the like. The energy storage function at the user side is: k (secondary user) ═ minimize S1 (secondary user) + S2 (secondary user) -S3 (secondary user), where K (secondary user) is the energy storage electricity fee required by the secondary user, S1 (secondary user) is the electricity amount and electricity fee required by the secondary user, S2 (secondary user) is the required electricity fee required by the secondary user, and S3 (secondary user) is the compensation electricity fee required by the secondary user.
And, for stable transmission of electric quantity and balancing supply and demand of electric power, the sum of the total energy storage electric charge of the primary user and the energy storage electric charge of the secondary user should satisfy the following mutual balance:
wherein K (m) is the total energy storage electric charge of one-time user energy storage, KiThe energy storage electricity charge of the secondary user is m, the total amount of the secondary user is m, and the formula shows that the optimization is accurate when the error is within a certain range, so that the method can be used for detecting the optimized result, and meanwhile, the optimization detection can be real-time and staged.
Optionally, the energy storage optimization model is represented in a curve form. After optimizing the user-side energy storage, the method further comprises:
comparing the curve of the energy storage optimization model with the predicted demand side response curve;
and if the difference of the curvatures of the two curves exceeds a preset threshold and the duration time reaches a preset duration, performing abnormity warning, analyzing abnormity reasons and storing abnormity information.
In the embodiment of the invention, the abnormal information may include contents such as a warning time period, an error reason, a curve curvature presented by the energy storage optimization model, and a curvature of a predicted demand side response curve.
It should be understood that, the sequence numbers of the steps in the foregoing embodiments do not imply an execution sequence, and the execution sequence of each process should be determined by its function and inherent logic, and should not constitute any limitation to the implementation process of the embodiments of the present invention.
Referring to fig. 2, an embodiment of the present invention provides a user-side energy storage optimization system, where the system 20 includes:
and the obtaining module 21 is used for obtaining the electricity fee data of the user side and the compensation electricity fee data of the demand side.
And the establishing module 22 is used for establishing an energy storage optimization model of the user side according to the electric charge data and the compensation electric charge data.
And the budget module 23 is used for determining a predicted demand side response curve according to the historical power consumption data of the user side.
And the optimization module 24 is configured to determine an optimal response power according to the energy storage optimization model and the predicted demand side response curve, and optimize the user side energy storage based on the optimal response power.
Optionally, the establishing module 22 is specifically configured to:
establishing an objective function by taking the lowest monthly energy storage electricity charge of the user side as a target, and establishing a constraint condition of the objective function to obtain an energy storage optimization model of the user side; an objective function of
K＝minimize(S1)+S2-S3
In the formula, K is the current-month energy storage electricity fee of the user side, S1 is the current-month electricity quantity and electricity fee of the user side, S2 is the current-month demand electricity fee of the user side, and S3 is the current-month compensation electricity fee of the demand side.
Optionally, the budget module 23 is specifically configured to:
and determining a historical demand side response curve according to the historical power consumption data, and determining a predicted demand side response curve based on the historical demand side response curve.
Optionally, the optimization module 24 is specifically configured to:
acquiring energy storage capacity, energy storage rated power and annual load peak clipping rate;
and calculating an energy storage optimal charging and discharging curve according to the parameters of the energy storage optimization model and the parameters of the predicted demand side response curve, and determining the optimal response power based on the energy storage optimal charging and discharging curve, the energy storage capacity, the energy storage rated power and the annual load peak clipping rate.
Optionally, the monthly electricity amount and the electricity charge of the user side are calculated in a time-sharing charging mode.
Optionally, the demand side is a power station, and the user side is an energy storage battery; or the demand side is an energy storage battery, and the user side is an electricity user.
Optionally, the energy storage optimization model is represented in a curve form. The system 20 may further include an alert module for, after optimizing the user-side energy storage:
comparing the curve of the energy storage optimization model with the predicted demand side response curve;
and if the difference of the curvatures of the two curves exceeds a preset threshold and the duration time reaches a preset duration, performing abnormity warning, analyzing abnormity reasons and storing abnormity information.
Fig. 3 is a schematic diagram of an electronic device 30 according to an embodiment of the present invention. As shown in fig. 3, the electronic apparatus 30 of this embodiment includes: a processor 31, a memory 32, and a computer program 33, such as a user-side energy storage optimization program, stored in the memory 32 and executable on the processor 31. The processor 31, when executing the computer program 33, implements the steps in the above-described respective embodiments of the user-side energy storage optimization method, such as the steps S101 to S104 shown in fig. 1. Alternatively, the processor 31 implements the functions of the modules in the above-described device embodiments, such as the functions of the modules 21 to 24 shown in fig. 2, when executing the computer program 33.
Illustratively, the computer program 33 may be divided into one or more modules/units, which are stored in the memory 32 and executed by the processor 31 to carry out the invention. One or more modules/units may be a series of computer program instruction segments capable of performing specific functions, which are used to describe the execution of the computer program 33 in the electronic device 30. For example, the computer program 33 may be divided into an acquisition module 21, a setup module 22, a budget module 23, and an optimization module 24 (modules in the virtual device), each of which functions specifically as follows:
and the obtaining module 21 is used for obtaining the electricity fee data of the user side and the compensation electricity fee data of the demand side.
And the establishing module 22 is used for establishing an energy storage optimization model of the user side according to the electric charge data and the compensation electric charge data.
And the budget module 23 is used for determining a predicted demand side response curve according to the historical power consumption data of the user side.
And the optimization module 24 is configured to determine an optimal response power according to the energy storage optimization model and the predicted demand side response curve, and optimize the user side energy storage based on the optimal response power.
The electronic device 30 may be a desktop computer, a notebook, a palm top computer, a cloud server, or other computing devices. The electronic device 30 may include, but is not limited to, a processor 31, a memory 32. Those skilled in the art will appreciate that fig. 3 is merely an example of the electronic device 30, and does not constitute a limitation of the electronic device 30, and may include more or less components than those shown, or combine certain components, or different components, e.g., the electronic device 30 may also include input-output devices, network access devices, buses, etc.
The Processor 31 may be a Central Processing Unit (CPU), other general purpose Processor, a Digital Signal Processor (DSP), an Application Specific Integrated Circuit (ASIC), an off-the-shelf Programmable Gate Array (FPGA) or other Programmable logic device, discrete Gate or transistor logic, discrete hardware components, etc. A general purpose processor may be a microprocessor or the processor may be any conventional processor or the like.
The storage 32 may be an internal storage unit of the electronic device 30, such as a hard disk or a memory of the electronic device 30. The memory 32 may also be an external storage device of the electronic device 30, such as a plug-in hard disk, a Smart Media Card (SMC), a Secure Digital (SD) Card, a Flash memory Card (Flash Card), and the like provided on the electronic device 30. Further, the memory 32 may also include both internal storage units and external storage devices of the electronic device 30. The memory 32 is used for storing computer programs and other programs and data required by the electronic device 30. The memory 32 may also be used to temporarily store data that has been output or is to be output.
It will be apparent to those skilled in the art that, for convenience and brevity of description, only the above-mentioned division of the functional units and modules is illustrated, and in practical applications, the above-mentioned function distribution may be performed by different functional units and modules according to needs, that is, the internal structure of the apparatus is divided into different functional units or modules, so as to perform all or part of the functions described above. Each functional unit and module in the embodiments may be integrated in one processing unit, or each unit may exist alone physically, or two or more units are integrated in one unit, and the integrated unit may be implemented in a form of hardware, or in a form of software functional unit. In addition, specific names of the functional units and modules are only for convenience of distinguishing from each other, and are not used for limiting the protection scope of the present application. The specific working processes of the units and modules in the system may refer to the corresponding processes in the foregoing method embodiments, and are not described herein again.
In the above embodiments, the descriptions of the respective embodiments have respective emphasis, and reference may be made to the related descriptions of other embodiments for parts that are not described or illustrated in a certain embodiment.
Those of ordinary skill in the art will appreciate that the various illustrative elements and algorithm steps described in connection with the embodiments disclosed herein may be implemented as electronic hardware or combinations of computer software and electronic hardware. Whether such functionality is implemented as hardware or software depends upon the particular application and design constraints imposed on the implementation. Skilled artisans may implement the described functionality in varying ways for each particular application, but such implementation decisions should not be interpreted as causing a departure from the scope of the present invention.
In the embodiments provided in the present invention, it should be understood that the disclosed apparatus/electronic device and method may be implemented in other ways. For example, the above-described apparatus/electronic device embodiments are merely illustrative, and for example, a module or a unit may be divided into only one type of logic function, and another division may be implemented in practice, for example, a plurality of units or components may be combined or integrated into another system, or some features may be omitted, or not implemented. In addition, the shown or discussed mutual coupling or direct coupling or communication connection may be an indirect coupling or communication connection through some interfaces, devices or units, and may be in an electrical, mechanical or other form.
Units described as separate parts may or may not be physically separate, and parts displayed as units may or may not be physical units, may be located in one place, or may be distributed on a plurality of network units. Some or all of the units can be selected according to actual needs to achieve the purpose of the solution of the embodiment.
In addition, functional units in the embodiments of the present invention may be integrated into one processing unit, or each unit may exist alone physically, or two or more units are integrated into one unit. The integrated unit can be realized in a form of hardware, and can also be realized in a form of a software functional unit.
The integrated modules/units, if implemented in the form of software functional units and sold or used as separate products, may be stored in a computer readable storage medium. Based on such understanding, all or part of the flow in the method according to the embodiments of the present invention may also be implemented by a computer program to instruct related hardware, where the computer program may be stored in a computer readable storage medium, and when the computer program is executed by a processor, the computer program may implement the steps of the embodiments of the method. Wherein the computer program comprises computer program code, which may be in the form of source code, object code, an executable file or some intermediate form, etc. The computer readable medium may include: any entity or device capable of carrying computer program code, recording medium, U.S. disk, removable hard disk, magnetic diskette, optical disk, computer Memory, Read-Only Memory (ROM), Random Access Memory (RAM), electrical carrier wave signal, telecommunications signal, software distribution medium, etc. It should be noted that the computer readable medium may contain other components which may be suitably increased or decreased as required by legislation and patent practice in jurisdictions, for example, in some jurisdictions, in accordance with legislation and patent practice, the computer readable medium does not include electrical carrier signals and telecommunications signals.
The above examples are only intended to illustrate the technical solution of the present invention, but not to limit it; although the present invention has been described in detail with reference to the foregoing embodiments, it will be understood by those of ordinary skill in the art that: the technical solutions described in the foregoing embodiments may still be modified, or some technical features may be equivalently replaced; such modifications and substitutions do not substantially depart from the spirit and scope of the embodiments of the present invention, and are intended to be included within the scope of the present invention.
Claims (10)
1. A user side energy storage optimization method is characterized by comprising the following steps:
acquiring electricity charge data of a user side and compensation electricity charge data of a demand side;
establishing an energy storage optimization model of a user side according to the electric charge data and the compensation electric charge data;
determining a predicted demand side response curve according to historical power consumption data of a user side;
and determining the optimal response power according to the energy storage optimization model and the predicted demand side response curve, and optimizing the energy storage at the user side based on the optimal response power.
2. The method for optimizing energy storage at the user side according to claim 1, wherein the establishing of the energy storage optimization model at the user side comprises:
establishing an objective function by taking the lowest monthly energy storage electricity charge of the user side as a target, and establishing a constraint condition of the objective function to obtain an energy storage optimization model of the user side; the objective function is
K＝minimize(S1)+S2-S3
In the formula, K is the current-month energy storage electricity fee of the user side, S1 is the current-month electricity quantity and electricity fee of the user side, S2 is the current-month demand electricity fee of the user side, and S3 is the current-month compensation electricity fee of the demand side.
3. The method for optimizing energy storage at the customer side according to claim 1, wherein determining the predicted response curve at the demand side according to the historical power consumption data at the customer side comprises:
and determining a historical demand side response curve according to the historical power consumption data, and determining a predicted demand side response curve based on the historical demand side response curve.
4. The user-side energy storage optimization method according to claim 1, wherein determining an optimal response power according to the energy storage optimization model and the predicted demand-side response curve comprises:
acquiring energy storage capacity, energy storage rated power and annual load peak clipping rate;
and calculating an energy storage optimal charging and discharging curve according to the parameters of the energy storage optimization model and the parameters of the predicted demand side response curve, and determining optimal response power based on the energy storage optimal charging and discharging curve, the energy storage capacity, the energy storage rated power and the annual load peak clipping rate.
5. The method as claimed in claim 2, wherein the monthly electricity consumption and the electricity charge of the user side are calculated in a time-sharing charging manner.
6. The user-side energy storage optimization method according to claim 1, wherein the demand side is a power station, and the user side is an energy storage battery;
or the demand side is an energy storage battery, and the user side is an electricity user.
7. The user-side energy storage optimization method according to any one of claims 1 to 6, wherein the energy storage optimization model is represented in a curve form;
after optimizing the user-side energy storage, the method further comprises:
comparing the curve of the energy storage optimization model with the predicted demand side response curve;
and if the difference of the curvatures of the two curves exceeds a preset threshold and the duration time reaches a preset duration, performing abnormity warning, analyzing abnormity reasons and storing abnormity information.
8. A user-side energy storage optimization system, comprising:
the acquisition module is used for acquiring the electric charge data of the user side and the compensation electric charge data of the demand side;
the establishing module is used for establishing an energy storage optimization model of a user side according to the electric charge data and the compensation electric charge data;
the budget module is used for determining a predicted demand side response curve according to historical power consumption data of a user side;
and the optimization module is used for determining the optimal response power according to the energy storage optimization model and the predicted demand side response curve and optimizing the energy storage at the user side based on the optimal response power.
9. An electronic device comprising a memory, a processor and a computer program stored in the memory and executable on the processor, characterized in that the steps of the method according to any of claims 1 to 7 are implemented when the computer program is executed by the processor.
10. A computer-readable storage medium, in which a computer program is stored which, when being executed by a processor, carries out the steps of the method according to any one of claims 1 to 7.
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| Publication number | Priority date | Publication date | Assignee | Title |
|---|---|---|---|---|
| CN114971400A (en) * | 2022-06-24 | 2022-08-30 | 东南大学溧阳研究院 | User side energy storage polymerization method based on Dirichlet distribution-multinomial distribution conjugate prior |
Citations (2)
| Publication number | Priority date | Publication date | Assignee | Title |
|---|---|---|---|---|
| CN111969598A (en) * | 2020-08-04 | 2020-11-20 | 广西电网有限责任公司电力科学研究院 | User side energy storage optimization method and system considering incentive type demand side response |
| CN112085394A (en) * | 2020-09-11 | 2020-12-15 | 广西电网有限责任公司电力科学研究院 | User side energy storage assessment method and system considering demand side response |
-
2021
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Patent Citations (2)
| Publication number | Priority date | Publication date | Assignee | Title |
|---|---|---|---|---|
| CN111969598A (en) * | 2020-08-04 | 2020-11-20 | 广西电网有限责任公司电力科学研究院 | User side energy storage optimization method and system considering incentive type demand side response |
| CN112085394A (en) * | 2020-09-11 | 2020-12-15 | 广西电网有限责任公司电力科学研究院 | User side energy storage assessment method and system considering demand side response |
Cited By (2)
| Publication number | Priority date | Publication date | Assignee | Title |
|---|---|---|---|---|
| CN114971400A (en) * | 2022-06-24 | 2022-08-30 | 东南大学溧阳研究院 | User side energy storage polymerization method based on Dirichlet distribution-multinomial distribution conjugate prior |
| CN114971400B (en) * | 2022-06-24 | 2023-01-31 | 东南大学溧阳研究院 | User side energy storage polymerization method based on Dirichlet distribution-multinomial distribution conjugate prior |
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