CN115009065A - Charging processing method and device, electronic equipment and computer readable storage medium - Google Patents
Charging processing method and device, electronic equipment and computer readable storage medium Download PDFInfo
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Abstract
The invention discloses a charging processing method and device, electronic equipment and a computer readable storage medium. Wherein, the method comprises the following steps: constructing an objective function for determining a power curve of a target charging pile, wherein the objective function is obtained according to a charging target strategy of the target charging pile; determining a charging demand constraint and a load constraint of an objective function; and solving an objective function based on the charging demand constraint and the load constraint to obtain a power curve of the target charging pile. The invention solves the technical problem that the obtained charging power is not in accordance with the actual expectation because the constraint condition of the charging power is difficult to be considered comprehensively when the charging power of the charging pile is determined in the related technology.
Description
Technical Field
The invention relates to the field of computers, in particular to a charging processing method and device, electronic equipment and a computer readable storage medium.
Background
Traffic electrification is one of the main means for remarkably reducing carbon emission, and has recently been widely regarded by countries all over the world, so that the preservation amount of global electric automobiles continues to increase greatly. Along with the increase of electric automobile holding capacity, fill infrastructure such as electric pile, charging station also in the continuous construction. From the perspective of the power grid, the charging load of the electric vehicle belongs to a high-power load, if the charging load is not reasonably regulated, the safe operation of the power grid is affected, and the most common situation is that the transformer capacity of the charging station is overloaded. However, the electric vehicle can be used as a flexible load, and for a charging facility in a typical area such as a residential area or a commercial area, the electric vehicle is usually parked for a time far exceeding the time actually required for charging, which makes it possible for the charging station to regulate the charging load of the electric vehicle. Through the orderly charging control of the charging station level, the power overload of the charging station is avoided, the charging load is smoothed, and the operating cost of the charging station can be saved in the area with the time-of-use electricity price. Therefore, a reasonable in-station ordered charge operation strategy is needed.
In view of the above problems, no effective solution has been proposed.
Disclosure of Invention
The embodiment of the invention provides a charging processing method, a charging processing device, electronic equipment and a computer readable storage medium, which are used for solving the technical problem that when the charging power of a charging pile is determined in the related art, the constraint condition of the charging power is difficult to be considered comprehensively, so that the obtained charging power is not in line with the actual expectation.
According to an aspect of an embodiment of the present invention, there is provided a charging processing method including: constructing an objective function for determining a power curve of a target charging pile, wherein the objective function is obtained according to a charging objective strategy of the target charging pile; determining a charging demand constraint and a load constraint of the objective function; and solving the objective function based on the charging demand constraint and the load constraint to obtain a power curve of the target charging pile.
Optionally, the determining the charging demand constraint of the objective function includes: determining historical charging energy data and historical charging power data of the target charging pile within a preset time period; constructing a charging power constraint and a charging energy constraint of the target charging pile based on the historical charging energy data and the historical charging power data; determining the charging demand constraint according to the charging power constraint and the charging energy constraint.
Optionally, the determining the historical charging energy data and the historical charging power data of the target charging pile within the predetermined time period includes: acquiring target charging pile data of the target charging pile and target electric vehicle charging data of a target electric vehicle accessed by the target charging pile in the preset time period; and determining historical charging energy data and historical charging power data of the target charging pile within a preset time period according to the target charging pile data and the target electric vehicle charging data.
Optionally, the determining the charging demand constraint according to the charging power constraint and the charging energy constraint includes: determining a unified constraint expression of the charging power constraint and the charging energy constraint according to the charging power constraint and the charging energy constraint; converting the unified constraint expression into conditional risk value CVaR constraint corresponding to the target charging pile; determining the charging demand constraint based on the CVaR constraint.
Optionally, the determining the charging demand constraint based on the CVaR constraint includes: and determining the charging demand constraint under a preset conservative parameter based on the CVaR constraint, wherein the preset conservative parameter is used for controlling the conservative degree of the obtained power curve of the target charging pile.
Optionally, the determining a load constraint of the objective function includes: acquiring capacity data of a target distribution transformer corresponding to the target charging pile in the preset time period and load curves of other equipment accessed by the target distribution transformer; and determining the load constraint of the target function according to the capacity data of the target distribution transformer and the load curves of the other devices.
According to an aspect of an embodiment of the present invention, there is provided a charge processing apparatus including: the system comprises a construction module, a power control module and a charging module, wherein the construction module is used for constructing an objective function for determining a power curve of a target charging pile, and the objective function is obtained according to a charging objective strategy of the target charging pile; the determining module is used for determining the charging demand constraint and the load constraint of the objective function; and the solving module is used for solving the objective function based on the charging demand constraint and the load constraint to obtain a power curve of the target charging pile.
According to an aspect of an embodiment of the present invention, there is provided an electronic apparatus including: a processor; a memory for storing the processor-executable instructions; wherein the processor is configured to execute the instructions to implement any one of the above charging processing methods.
According to an aspect of the embodiments of the present invention, there is provided a computer-readable storage medium, wherein instructions of the computer-readable storage medium, when executed by a processor of an electronic device, enable the electronic device to perform any one of the charging processing methods described above.
According to an aspect of an embodiment of the present invention, there is provided a computer program product including a computer program, wherein the computer program is configured to implement any one of the charging processing methods described above when executed by a processor.
In the embodiment of the invention, an objective function for determining the power curve of the target charging pile is constructed, wherein the objective function is obtained according to a charging objective strategy of the objective charging pile, the charging demand constraint and the load constraint of the objective function are determined, further, the objective function can be solved based on the charging demand constraint and the load constraint to obtain the power curve of the target charging pile, because the objective function is obtained according to the charging objective strategy, the objective function is in accordance with the actual expectation, and because the charging requirement constraint and the conforming constraint are determined, so that the comprehensive consideration is carried out when determining the power curve, the obtained power curve is in accordance with the actual expectation, and furthermore, the technical problem that when the charging power of the charging pile is determined in the related technology, the constraint condition of the charging power is difficult to be considered comprehensively, so that the obtained charging power is not in line with actual expectation is solved.
Drawings
The accompanying drawings, which are included to provide a further understanding of the invention and are incorporated in and constitute a part of this application, illustrate embodiment(s) of the invention and together with the description serve to explain the invention and do not constitute a limitation of the invention. In the drawings:
fig. 1 is a flowchart of a charging processing method according to an embodiment of the present invention;
fig. 2 is a block diagram of the structure of a charge processing device according to an embodiment of the present invention.
Detailed Description
In order to make the technical solutions of the present invention better understood, 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 obtained by a person skilled in the art without making any creative effort based on the embodiments in the present invention, shall fall within the protection scope of the present invention.
It should be noted that the terms "first," "second," and the like in the description and claims of the present invention and in the drawings described above are used for distinguishing between similar elements and not necessarily for describing a particular sequential or chronological order. It is to be understood that the data so used is interchangeable under appropriate circumstances such that the embodiments of the invention described herein are capable of operation in sequences other than those illustrated or described herein. Furthermore, the terms "comprises," "comprising," and "having," and any variations thereof, are intended to cover a non-exclusive inclusion, such that a process, method, system, article, or apparatus that comprises a list of steps or elements is not necessarily limited to those steps or elements expressly listed, but may include other steps or elements not expressly listed or inherent to such process, method, article, or apparatus.
First, some terms or terms appearing in the description of the embodiments of the present application are applicable to the following explanations:
cvar: conditional risk value is an investment risk measurement method developed on the basis of VaR (risk value). Compared with VaR, CVaR satisfies the conditions of sub-additivity, homogeneity, monotonicity and transmission invariance, so CVaR is a consistent risk metering method.
Example 1
In accordance with an embodiment of the present invention, there is provided an embodiment of a charging processing method, it is noted that the steps illustrated in the flowchart of the drawings may be performed in a computer system such as a set of computer executable instructions, and that while a logical order is illustrated in the flowchart, in some cases the steps illustrated or described may be performed in an order different than here.
Fig. 1 is a flowchart of a charging processing method according to an embodiment of the present invention, as shown in fig. 1, the method including the steps of:
step S102, constructing an objective function for determining a power curve of the target charging pile, wherein the objective function is obtained according to a charging objective strategy of the target charging pile;
step S104, determining charging demand constraint and load constraint of the objective function;
and S106, solving an objective function based on the charging demand constraint and the load constraint to obtain a power curve of the target charging pile.
Through the steps, an objective function for determining the power curve of the target charging pile is constructed, wherein the objective function is obtained according to a charging objective strategy of the objective charging pile, the charging demand constraint and the load constraint of the objective function are determined, further solving the objective function based on the charging demand constraint and the load constraint to obtain a power curve of the target charging pile, because the objective function is obtained according to the charging objective strategy, the objective function is in accordance with the actual expectation, and because the charging requirement constraint and the conforming constraint are determined, so that the comprehensive consideration is carried out when determining the power curve, the obtained power curve is in accordance with the actual expectation, and furthermore, the technical problem that when the charging power of the charging pile is determined in the related technology, the constraint condition of the charging power is difficult to be considered comprehensively, so that the obtained charging power is not in line with actual expectation is solved.
As an alternative embodiment, an objective function for determining a power curve of a target charging pile is constructed, where the objective function is obtained according to a charging objective policy of the target charging pile. The charging objective policy may be determined by different identities, for example, when the charging station operator is identified, the charging objective policy may be an objective function that minimizes the operating cost and also maximizes the profit. The self-defined setting can be carried out according to the actual application and the scene. And obtaining an objective function which accords with the charging objective strategy, and solving the objective function to obtain an optimal power curve under the charging objective strategy. The power curve is made to conform to the charging target strategy, as expected by the user.
As an alternative embodiment, a charging demand constraint and a load constraint of the objective function are determined, where the charging demand constraint is a constraint set based on a demand of charging, and the load constraint is a constraint according to a load carrying capacity. The charging demand constraint and the load constraint of the objective function are determined and comprehensively considered, so that the charging demand and the load capacity are considered, and the obtained power curve is effective, reasonable and comprehensive.
As an alternative embodiment, determining the charging demand constraint of the objective function may include various ways, for example, historical charging energy data and historical charging power data of the target charging pile within a predetermined time period may be determined, a charging power constraint and a charging energy constraint of the target charging pile are constructed based on the historical charging energy data and the historical charging power data, and the charging demand constraint is determined to obtain the historical charging energy record and the historical charging power record according to the charging power constraint and the charging energy constraint, because the historical records often reflect the charging rules of the charging demand, for example, an electric vehicle in a residential area is parked in the next morning in the evening, an electric vehicle in a business area or an office area is parked in the evening in the morning in the daytime in the evening, and the like, which makes it possible to predict the future charging demand by using the data. Therefore, the historical charging energy data and the historical charging power data of the target charging pile in the preset time period are adopted for processing, and the obtained charging power constraint and charging energy constraint are more reasonable. Optionally, when the charging power constraint and the charging energy constraint of the target charging pile are constructed based on the historical charging energy data and the historical charging power data, the construction of the charging power constraint and the charging energy constraint of the target charging pile may be performed with reference to the power-energy boundary model.
As an optional embodiment, when determining the historical charging energy data and the historical charging power data of the target charging pile within the predetermined time period, it is known that the historical charging energy data and the historical charging power data of the target charging pile are generally not directly obtainable, and therefore, the target charging pile data of the target charging pile and the target electric vehicle charging data of the target electric vehicle connected to the target charging pile within the predetermined time period may be obtained, and the historical charging energy data and the historical charging power data of the target charging pile within the predetermined time period may be determined according to the target charging pile data and the target electric vehicle charging dataAnd (4) data. For example, the arrival time slot number t of the target electric vehicle connected to each target charging pile a Away period number t d Initial electric quantity E a Expected electric quantity E d Equal information, and the maximum battery capacity E max And charging power P of charging pile chg The charging demand of the target electric automobile can be calculated, and then the charging demand of the target charging pile is determined.
As an optional embodiment, when determining the charging demand constraint according to the charging power constraint and the charging energy constraint, a unified constraint expression of the charging power constraint and the charging energy constraint may be determined according to the charging power constraint and the charging energy constraint; converting the unified constraint expression into conditional risk value CVaR constraint corresponding to the target charging pile; based on the CVaR constraints, charging demand constraints are determined. So that the resulting charging demand constraints can be more reasonable.
Optionally, in order to make the conservative degree of the charging demand constraint adjustable, the charging demand constraint under a predetermined conservative parameter may be further determined based on the CVaR constraint, where the predetermined conservative parameter is used to control the conservative degree of the obtained power curve of the target charging pile.
As an optional embodiment, the load constraint of the target function is determined, the capacity data of the target distribution transformer corresponding to the target charging pile in a predetermined time period and the load curve of other devices connected to the target distribution transformer are obtained, and the load constraint of the target function is determined according to the capacity data of the target distribution transformer and the load curve of other devices. Guarantee promptly in the aspect of the load, guarantee the reasonable operation of target charging pile.
Based on the above embodiments and alternative embodiments, an alternative implementation is provided, which is described in detail below.
In the optional embodiment of the invention, a distributed robust opportunity constraint-based control scheme for orderly charging operation of electric vehicles in a charging station is provided, under the condition that historical operation data of the charging station are known, including arrival time, departure time, initial electric quantity, expected electric quantity and other data of historical charging requirements, the distributed robust opportunity constraint is used for establishing the charging requirements for each charging pile in the station, the regularity and uncertainty of the charging requirements can be considered, a reasonable power curve is formulated for the charging station, and safe and economic operation of the charging station is realized. The following is a detailed description of alternative embodiments of the invention:
s1, determining an objective function of the target charging pile;
the method provided by the optional embodiment of the invention is to design the ordered charging operation strategy of the electric vehicle from the perspective of a charging station operator, so the goal should be to maximize the income of the charging station operator or minimize the operation cost, and a specific mathematical expression is given below by taking the minimized operation cost as an example. The operation optimization objective function of each target charging pile in the charging station taking the minimum operation cost as the target is as follows:
wherein c (t) is the price of time-sharing electricity in time period t, P j (T) is the power of charging post J at time period T,. DELTA.T refers to the time interval, and J is the set of all charging posts in the station.
S2, constructing constraint conditions of an objective function of the target charging pile, wherein the constraint conditions comprise charging demand constraint and load constraint;
(one) constraint on charging demand:
1) the time is discretized and the time window considered for optimization (as with the predetermined time segments described above) is divided into a total of T time segments at time intervals of Δ T. Then historical data is obtained, and the arrival time period number t of the single electric automobile is known in the historical data a Away period number t d Initial electric quantity E a Expected electric quantity E d Equal information, and the maximum battery capacity E max And charging power P of charging pile chg The power-energy boundary can be calculatedp(t),
e(t),
Namely, the lower power bound, the upper power bound, the lower energy bound and the upper energy bound characterize the charging requirements of a single electric vehicle. The power boundary represents a power range of the electric automobile allowed to be charged in each time interval, and under the condition that the electric automobile discharges to a power grid, if the electric automobile is connected to the charging pile, the power range in the time interval is 0 to rated power, and if the electric automobile is not connected to the charging pile, the power can only be 0. The energy boundary represents a possible charging schedule for the electric vehicle, the basic principle being that the charging process is to reach the desired charge before leaving without exceeding the battery capacity. The power-energy boundaries of all electric vehicles which are successively connected to one charging pile are respectively superposed, so that the demand function of the single charging pile can be obtained, namely:
wherein, I j Is a set of electric vehicles connected to the charging pile j,P j (t),
E j (t),
is the power and energy boundary for charging pile j at time t.
And then can obtain all charging pile's in the charging station charging power restraint and charging energy restraint do:
2) the charging power constraint and the charging energy constraint constructed in the step 1) are constructed under the condition that the charging requirement of the electric automobile is known, so that a certain rule can be obtained according to historical data. Generally, the charging demand of electric vehicles at destinations such as residential areas, business areas and the like has a certain rule, for example, electric vehicles in residential areas generally stop to the next morning in the evening, electric vehicles in business areas or office areas generally stop to the evening in the morning in the daytime, and the like, which makes it possible to predict the future charging demand by using data. In the real-time control phase, step 1), power and energy boundary parametersP j (t),
E j (t),
Can be considered as a random variable. For a charging station, if it stores historical accessed electric vehicle charging demand data, a charging power constraint and a charging energy constraint can be constructed for each historical operating day. Accordingly, the charging pile power-energy boundary thus generated is a sample of the corresponding random variable. Considering that the power and energy boundaries are random variables, the charging pile power and energy boundary constraint should be described by an opportunity constraint, that is:
where 1- η represents the confidence level of the above constraints.
It should be noted that for convenience, the confidence level of all the above constraints may be taken to be the same. Uniformly, a vector formed by all random variables is represented by xi, and x represents a decision variable P j (t), then the expressions within all of the opportunity constraints described above are linear inequalities with respect to the random variable ξ. Without loss of generality, it can be rewritten as the following unified constraint expression:
where K is the number of all opportunity constraints. When K is 1, a is exemplified k (x) Represents the k dimension ofP j (t) other column vectors of 0, transposed to form row vectors, b k (x)＝-P j (t), ξ are k-dimensional.
3) The above-mentioned opportunity constraint is used for the calculation and also the distribution of the random variable ξ needs to be determined, for which a distribution robust opportunity constraint can be used, whose principle is to find out, among a set of possible distributions, the one that maximizes the probability of constraint violation. After a historical sample of ξ is known, a distributed robust opportunity constraint based on Wasserstein distance is used. For this reason, the opportunity constraint is first rewritten to a Conditional Risk Value (CVaR) constraint, namely:
the expression in expectation is rewritten as the maximum combination of two linear functions, namely:
wherein a is k,1 (x)＝a k (x),a k,2 (x)＝0,b k,1 (x,β k )＝b(x)-(1-η)β k ,b k,2 (x,β k )＝ηβ k 。
Distributed robust opportunity constraint based on Wasserstein distance requires roughly setting a set of random variables, and a multi-face set is taken in the patent
The CVAR constraint is then transformed into the expression of the distributed robust opportunity constraint as follows:
||C T γ k,dh -a k,h (x)|| ∞ ≤λ k
γ k,dh ≥0
it should be noted that, where D is the number of random variable samples,
the d-th sample representing ξ, ε represents the radius of the Wasserstein sphere. Lambda [ alpha ] k ,s k ,γ k,dh Are dual variables generated in the conversion process and are added into the optimization model as decision variables. It should be noted that the multi-surface set, i.e. the polyhedron, is a set in which a random variable ξ is preset, which is usually rough, for exampleS ═ xi | xi ≧ 0 }. And C and d are also only coefficients among the polyhedrons. C is a coefficient matrix and d is a right-hand-end vector, with no specific physical meaning, e.g., for the above example C-I (negative identity matrix) and d-0 (full 0 vector).
(ii) constraints on load, i.e. at the charging station level, which ensure that the overall load is not overloaded;
where, Cap is the capacity of the distribution transformer where the charging station is located, and l (t) is the load curve of the base load (residential load, industrial load, commercial load, etc.) to which the transformer is simultaneously connected.
S3, solving an objective function according to the constraints to obtain a power curve P which should be distributed on each charging pile j (t)。
s.t.
Through the above alternative embodiment, at least the following advantages can be achieved:
(1) historical charging demand data can be collected by a charging operator, and the calculated charging pile power curve can adapt to the uncertainty of the charging demand;
(2) the uncertainty of the charging requirement is described by using the distributed robust opportunity constraint, and the method has the advantage of adjustable conservative degree, namely a charging station operator can control the conservative degree of decision by setting different conservative parameters, so that different control effects are obtained, and the method has flexibility;
(3) the method can be applied to ordered charging of the charging station, and the power curve result obtained by the method provided by the optional embodiment of the invention can ensure safe operation of the charging station and the power grid and simultaneously maximize the income of a charging station operator.
It should be noted that, for simplicity of description, the above-mentioned method embodiments are described as a series of acts or combination of acts, but those skilled in the art will recognize that the present invention is not limited by the order of acts, as some steps may occur in other orders or concurrently in accordance with the invention. Further, those skilled in the art will appreciate that the embodiments described in this specification are presently preferred and that no acts or modules are required by the invention.
Through the above description of the embodiments, those skilled in the art can clearly understand that the method according to the above embodiments can be implemented by software plus a necessary general hardware platform, and certainly can also be implemented by hardware, but the former is a better implementation mode in many cases. Based on such understanding, the technical solutions of the present invention may be embodied in the form of a software product, which is stored in a storage medium (such as ROM/RAM, magnetic disk, optical disk) and includes instructions for enabling a terminal device (such as a mobile phone, a computer, a server, or a network device) to execute the method according to the embodiments of the present invention.
Example 2
According to an embodiment of the present invention, there is also provided an apparatus for implementing the charging processing method, and fig. 2 is a block diagram of a structure of the charging processing apparatus according to an embodiment of the present invention, as shown in fig. 2, the apparatus includes: a construction module 202, a determination module 204, and a solution module 206, which are described in detail below.
The building module 202 is configured to build an objective function for determining a power curve of a target charging pile, where the objective function is obtained according to a charging objective policy of the target charging pile; a determining module 204, connected to the constructing module 202, for determining the charging demand constraint and the load constraint of the objective function; and a solving module 206, connected to the determining module 204, for solving the objective function based on the charging demand constraint and the load constraint to obtain a power curve of the target charging pile.
It should be noted here that the building module 202, the determining module 204 and the solving module 206 correspond to steps S102 to S106 in the implementation of the charging processing method, and the modules are the same as the corresponding steps in the implementation example and the application scenario, but are not limited to the disclosure of the above embodiment 1.
Example 3
According to another aspect of the embodiments of the present invention, there is also provided an electronic device, including: a processor; a memory for storing processor-executable instructions, wherein the processor is configured to execute the instructions to implement the charging processing method of any of the above.
Example 4
According to another aspect of the embodiments of the present invention, there is also provided a computer-readable storage medium, where instructions of the computer-readable storage medium, when executed by a processor of an electronic device, enable the electronic device to perform any one of the above charging processing methods.
Example 5
According to another aspect of the embodiment of the present invention, there is also provided a computer program product including a computer program, wherein the computer program realizes the charging processing method described in any one of the above when executed by a processor.
The above-mentioned serial numbers of the embodiments of the present invention are merely for description and do not represent the merits of the embodiments.
In the above embodiments of the present invention, the descriptions of the respective embodiments have respective emphasis, and for parts that are not described in detail in a certain embodiment, reference may be made to related descriptions of other embodiments.
In the embodiments provided in the present application, it should be understood that the disclosed technology can be implemented in other ways. The above-described embodiments of the apparatus are merely illustrative, and for example, the division of the units may be a logical division, and in actual implementation, there may be another division, for example, multiple units or components may be combined or integrated into another system, or some features may be omitted, or not executed. 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, units or modules, and may be in an electrical or other form.
The 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 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 unit, if implemented in the form of a software functional unit and sold or used as a stand-alone product, may be stored in a computer readable storage medium. Based on such understanding, the technical solution of the present invention, which is substantially or partly contributed by the prior art, or all or part of the technical solution may be embodied in a software product, which is stored in a storage medium and includes instructions for causing a computer device (which may be a personal computer, a server, or a network device) to perform all or part of the steps of the method according to the embodiments of the present invention. And the aforementioned storage medium includes: a U-disk, a Read-Only Memory (ROM), a Random Access Memory (RAM), a removable hard disk, a magnetic or optical disk, and other various media capable of storing program codes.
The foregoing is only a preferred embodiment of the present invention, and it should be noted that, for those skilled in the art, various modifications and decorations can be made without departing from the principle of the present invention, and these modifications and decorations should also be regarded as the protection scope of the present invention.
Claims (10)
1. A charging processing method, comprising:
constructing an objective function for determining a power curve of a target charging pile, wherein the objective function is obtained according to a charging objective strategy of the target charging pile;
determining a charging demand constraint and a load constraint of the objective function;
and solving the objective function based on the charging demand constraint and the load constraint to obtain a power curve of the target charging pile.
2. The method of claim 1, wherein the determining the charge demand constraint of the objective function comprises:
determining historical charging energy data and historical charging power data of the target charging pile within a preset time period;
constructing a charging power constraint and a charging energy constraint of the target charging pile based on the historical charging energy data and the historical charging power data;
determining the charging demand constraint according to the charging power constraint and the charging energy constraint.
3. The method of claim 2, wherein the determining historical charging energy data and historical charging power data for the target charging post within a predetermined time period comprises:
acquiring target charging pile data of the target charging pile and target electric vehicle charging data of a target electric vehicle accessed by the target charging pile in the preset time period;
and determining historical charging energy data and historical charging power data of the target charging pile within a preset time period according to the target charging pile data and the target electric vehicle charging data.
4. The method of claim 2, wherein the determining the charging demand constraint as a function of the charging power constraint and the charging energy constraint comprises:
determining a unified constraint expression of the charging power constraint and the charging energy constraint according to the charging power constraint and the charging energy constraint;
converting the unified constraint expression into conditional risk value CVaR constraint corresponding to the target charging pile;
determining the charge demand constraint based on the CVaR constraint.
5. The method of claim 4, wherein the determining the charging demand constraint based on the CVaR constraint comprises:
and determining the charging demand constraint under a preset conservative parameter based on the CVaR constraint, wherein the preset conservative parameter is used for controlling the conservative degree of the obtained power curve of the target charging pile.
6. The method of any of claims 1-5, wherein determining the load constraint of the objective function comprises:
acquiring capacity data of a target distribution transformer corresponding to the target charging pile within a preset time period and load curves of other equipment accessed by the target distribution transformer;
and determining the load constraint of the target function according to the capacity data of the target distribution transformer and the load curves of the other devices.
7. A charge processing device characterized by comprising:
the system comprises a construction module, a power control module and a charging module, wherein the construction module is used for constructing an objective function for determining a power curve of a target charging pile, and the objective function is obtained according to a charging objective strategy of the target charging pile;
the determining module is used for determining a charging demand constraint and a load constraint of the objective function;
and the solving module is used for solving the objective function based on the charging demand constraint and the load constraint to obtain a power curve of the target charging pile.
8. An electronic device, comprising:
a processor;
a memory for storing the processor-executable instructions;
wherein the processor is configured to execute the instructions to implement the charging processing method of any one of claims 1 to 6.
9. A computer-readable storage medium, wherein instructions in the computer-readable storage medium, when executed by a processor of an electronic device, enable the electronic device to perform the charging processing method of any one of claims 1 to 6.
10. A computer program product comprising a computer program, characterized in that the computer program realizes the charging processing method of any one of claims 1 to 6 when executed by a processor.
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