Charging Pile Management Method and Device Based on Distributed Photovoltaic Power Generation

Abstract

This invention provides a method and device for managing charging piles based on distributed photovoltaic (PV) power generation, belonging to the field of electricity management technology. The method includes: acquiring the amount of electricity that is difficult to absorb during a period of high grid connection at least one PV power generation node within a target area; acquiring the topology between the PV power generation node and each charging pile within the target area; determining the allocated charging power for each charging pile during the period of high grid connection based on the topology and the amount of electricity that is difficult to absorb; acquiring the charging request from the user and the location information of each charging pile, the charging request including the location information of the user; determining the candidate charging piles based on the user's charging request, the location information of each charging pile, and the allocated charging power for each charging pile, and sending the period of high grid connection and the location information of the candidate charging piles to the user. This invention can more fully utilize PV energy and avoid energy waste.

Description

Technical Field

[0001] This invention relates to the field of electricity management technology, and in particular to a method and device for managing charging piles based on distributed photovoltaic power generation. Background Technology

[0002] With increasing global focus on low-carbon development and environmental protection, the utilization of renewable energy has become a crucial pathway to achieving sustainable energy supply. Photovoltaic power generation, as a widely used form of clean energy, has been connected to the grid on a large scale in many regions, making significant contributions to energy structure transformation and carbon emission reduction. The construction of a new power system primarily based on new energy power generation is underway. Among these, distributed photovoltaic power generation has been rapidly promoted in many areas due to its advantages such as flexible construction and clean, low-carbon operation.

[0003] Electric vehicles, as a low-carbon and green new mode of transportation, can reduce exhaust emissions from gasoline-powered vehicles and promote green development in the transportation sector. However, there is a mismatch between the charging time of electric vehicles and the surplus time of distributed photovoltaic power generation, which leads to energy waste and grid imbalance.

[0004] Patent application CN202011374239.7 proposes a charging management method that determines the maximum charging load value by predicting photovoltaic power generation and grid power supply, thereby generating a charging management strategy for charging piles. This method can improve management efficiency and avoid burdening the grid. However, this method mainly addresses the situation where charging piles over-output during peak electricity consumption periods and does not fully utilize photovoltaic power generation, still resulting in energy waste. Summary of the Invention

[0005] This invention provides a charging pile management method and device based on distributed photovoltaic power generation, so as to make fuller use of photovoltaic energy and avoid energy waste.

[0006] In a first aspect, embodiments of the present invention provide a charging pile management method based on distributed photovoltaic power generation, comprising:

[0007] Obtain the amount of electricity that is difficult to absorb during the period of difficult absorption of photovoltaic power generation nodes in the target area, and obtain the topology between photovoltaic power generation nodes and various charging piles in the target area;

[0008] Based on the topology and the difficulty in absorbing the electricity, determine the allocated charging power for each charging pile during the difficult period of electricity absorption;

[0009] Obtain the charging request of the charging object and the location information of each charging pile. The charging request includes the location information of the charging object.

[0010] Based on the charging request from the user, the location information of each charging pile, and the allocated charging power of each charging pile, the candidate charging piles are determined, and the difficult charging periods and the location information of the candidate charging piles are sent to the user.

[0011] In one possible implementation, obtaining the amount of electricity that is difficult to absorb from at least one photovoltaic power generation node within the target area during a period of difficult grid connection includes:

[0012] Obtain the photovoltaic power generation of at least one photovoltaic power generation node in the target area during each time period of a preset duration, and the amount of electricity that the regional power grid can absorb during each time period of the preset duration;

[0013] Based on the photovoltaic power generation and the amount of electricity that can be absorbed in each time period, determine the periods when photovoltaic power generation nodes face difficulties in absorbing electricity.

[0014] Based on the photovoltaic power generation and the amount of electricity that can be absorbed during the period of difficult absorption, calculate the amount of electricity that is difficult to absorb during the period of difficult absorption.

[0015] In one possible implementation, the charging request also includes the charging object's required power level;

[0016] Based on the charging request, the location information of each charging station, and the allocated charging power, the candidate charging stations are determined, including:

[0017] Obtain confirmation information for all confirmed charging requests, including the reserved charging station, the required electricity amount, and the reserved time period;

[0018] Based on the confirmation information that the reserved time period is a period of difficult charging and the allocated charging power of each charging pile, determine the remaining charging power of each charging pile during the period of difficult charging.

[0019] All charging stations with remaining charging capacity greater than the required charging capacity are identified as optional charging stations.

[0020] Based on the location information of each optional charging station and the location information of the charging object, the distance between each optional charging station and the charging object is determined, and the optional charging station with the smallest distance is selected as the candidate charging station.

[0021] In one possible implementation, the allocated charging power for each charging pile during periods of difficult power absorption is determined based on the topology and the amount of electricity that is difficult to absorb, including:

[0022] Based on the topology and the difficulty in absorbing the electricity, an objective function is established with the goal of minimizing the line loss between photovoltaic power generation nodes and charging piles within the target area, and constraints on the objective function are also established.

[0023] The objective function is solved based on the constraints to obtain the allocated charging power for each charging pile.

[0024] In one possible implementation, the objective function is:

[0025] f = min∑ i,j |I ij | 2 ·Re(Z ij );

[0026] In the formula, f represents the objective function, I ij Re(Z) represents the current in line ij. ij ) represents the real part of the impedance of line ij, i represents the photovoltaic power generation node, and j represents the charging pile node.

[0027] In one possible implementation, after determining the allocated charging power for each charging pile during periods of difficult power absorption based on the topology and the amount of electricity that is difficult to absorb, the method further includes:

[0028] The marginal charging price for each charging station is determined based on the allocated charging capacity of each charging station.

[0029] Accordingly, the method also includes:

[0030] The marginal charging price of the selected charging pile is sent to the charging target.

[0031] In one possible implementation, after identifying all charging stations with remaining charging capacity greater than the required charging capacity as optional charging stations, the following is also included:

[0032] The charging station with the lowest marginal charging price is selected as the candidate charging station.

[0033] In one possible implementation, the marginal charging price for each charging station is determined based on the allocated charging capacity for each station, including:

[0034] Obtain the first initial charging amount corresponding to each pre-determined charging pile during the period of difficult consumption;

[0035] For each charging pile, the total charging capacity of the charging pile is calculated based on the allocated charging capacity of the charging pile in the difficult-to-consume electricity and the initial charging capacity of the charging pile.

[0036] The total charging capacity of each charging pile is input into the pre-trained model for calculating the first marginal charging price of the charging pile, and the first marginal charging price of each charging pile is obtained.

[0037] In one possible implementation, the marginal charging price for each charging station is determined based on the allocated charging capacity for each station, including:

[0038] Obtain the second initial charging capacity corresponding to the period of difficult consumption of all charging piles in the predetermined target area. The second initial charging capacity is the sum of the initial charging capacity of all charging piles in the target area.

[0039] Calculate the total charging capacity of all charging piles in the target area based on the amount of electricity that is difficult to absorb and the second initial charging capacity;

[0040] The total charging capacity of all charging piles in the target area is input into the pre-trained second marginal charging price calculation model of the target area to obtain the second marginal charging price of each charging pile.

[0041] Secondly, embodiments of the present invention provide a charging pile management device based on distributed photovoltaic power generation, comprising:

[0042] The first acquisition module is used to acquire the amount of electricity that is difficult to absorb during the period of difficult absorption of photovoltaic power generation nodes in the target area, and to acquire the topology between photovoltaic power generation nodes and various charging piles in the target area.

[0043] The first determining module is used to determine the allocated charging power for each charging pile during the period of difficult power absorption based on the topology and the power absorption difficulties.

[0044] The second acquisition module is used to acquire the charging request of the charging object and the location information of each charging pile. The charging request includes the location information of the charging object.

[0045] The second determining module is used to determine the candidate charging piles based on the charging request of the charging object, the location information of each charging pile, and the allocated charging power of each charging pile, and to send the difficult charging period and the location information of the candidate charging piles to the charging object.

[0046] The beneficial effects of the embodiments of the present invention compared with the prior art are as follows:

[0047] This invention utilizes the topology between photovoltaic (PV) power generation nodes and various charging piles within a target area to allocate the difficult-to-absorb electricity generated by PV power generation nodes to each charging pile during periods of grid connection difficulties. This allows the charging piles to absorb the difficult-to-absorb electricity generated by PV power generation that cannot be connected to the grid. By acquiring the charging requests of charging users, the invention matches charging users with suitable locations and sufficient charging power, guiding them to the charging piles during periods of grid connection difficulties. This enables each charging pile to fully utilize the allocated charging power, thereby maximizing the utilization of PV energy generated by PV power generation, avoiding curtailment of solar power, and reducing energy waste. Attached Figure Description

[0048] To more clearly illustrate the technical solutions in the embodiments of the present invention, the drawings used in the description of the embodiments or the prior art will be briefly introduced below. Obviously, the drawings described below are only some embodiments of the present invention. For those skilled in the art, other drawings can be obtained based on these drawings without creative effort.

[0049] Figure 1 This is an application scenario diagram of the charging pile management method based on distributed photovoltaic power generation provided in the embodiments of the present invention;

[0050] Figure 2 This is a flowchart illustrating the implementation of the charging pile management method based on distributed photovoltaic power generation provided in this embodiment of the invention.

[0051] Figure 3 This is a schematic diagram illustrating the relationship between the charging capacity and the charging price of the charging pile provided in this embodiment of the invention;

[0052] Figure 4 This is a schematic diagram of the structure of a charging pile management device based on distributed photovoltaic power generation provided in an embodiment of the present invention. Detailed Implementation

[0053] In the following description, specific details such as particular system architectures and techniques are set forth for illustrative purposes and not for limitation, in order to provide a thorough understanding of the embodiments of the invention. However, those skilled in the art will understand that the invention can be implemented in other embodiments without these specific details. In other instances, detailed descriptions of well-known systems, apparatuses, circuits, and methods are omitted so as not to obscure the description of the invention with unnecessary detail.

[0054] To make the objectives, technical solutions, and advantages of the present invention clearer, specific embodiments will be described below in conjunction with the accompanying drawings.

[0055] The output of distributed photovoltaic (PV) power generation is primarily influenced by sunlight conditions, exhibiting strong regularity, especially during midday and afternoon when sunlight is strongest. Distributed PV power generation often exceeds the grid's absorption capacity, leading to grid instability, energy waste, and the implementation of power curtailment measures. Therefore, this application aims to improve the absorption capacity of PV power generation and reduce energy waste by guiding electric vehicle charging to absorb excess power during peak PV generation periods.

[0056] Figure 1 This diagram illustrates an application scenario of the charging pile management method based on distributed photovoltaic power generation provided in this invention, showing a simplified topology of photovoltaic nodes and charging piles within the target area. Figure 1The photovoltaic (PV) power generation nodes and charging pile nodes shown are equivalent to a 5-node micro-distribution network, comprising two PV power generation nodes, three charging pile nodes, and one distribution room node. The PV power generation nodes are designated as nodes 1 and 4, the charging pile nodes as nodes 2, 3, and 5, and the distribution room node as node 5'. Since nodes 5' and 5 are very close, there is no impedance between them, and they can be considered as the same node. Through the wiring connections between the PV power generation nodes and the charging piles, the electricity generated by the PV power generation can be supplied to the charging piles for their use. The distribution room provides power from the upstream power grid, ensuring the connection between the micro-distribution network and the upstream power grid.

[0057] Figure 2 The implementation flowchart of the charging pile management method based on distributed photovoltaic power generation provided in the embodiments of the present invention is described in detail below:

[0058] Step S201: Obtain the amount of electricity that is difficult to absorb during the difficult period of photovoltaic power generation node in the target area, and obtain the topology between photovoltaic power generation node and each charging pile in the target area.

[0059] In this embodiment, the amount of electricity that photovoltaic power generation nodes in the target area cannot consume during periods of grid connection difficulties is the amount of electricity that photovoltaic power generation nodes cannot connect to the grid. This portion of electricity needs to be consumed by the photovoltaic power generation companies themselves.

[0060] The topology between photovoltaic power generation nodes and various charging piles within the target area includes information such as the connection relationships and line distances between photovoltaic power generation nodes and various charging piles. The power generated by the photovoltaic power generation nodes can be supplied to the charging piles through the connection lines between the photovoltaic nodes and the charging piles.

[0061] Step S202: Based on the topology and the difficulty in absorbing the electricity, determine the allocated charging power for each charging pile during the difficult period of electricity absorption.

[0062] In this embodiment, there are multiple charging piles in the target area. Each charging pile is at a different distance from the photovoltaic power generation node, and each charging pile also has a different output power. Therefore, a corresponding amount of electricity is allocated to each charging pile so that the electricity that is difficult to consume can be fully utilized through the charging pile.

[0063] Step S203: Obtain the charging request of the charging object and the location information of each charging pile. The charging request includes the location information of the charging object.

[0064] In this embodiment, the location information of the charging object can be the current location of the charging object or other locations provided by the charging object. For example, if the charging object requests charging during a preset time period in the future, the corresponding charging location can be the location that the charging object may be in during the preset time period provided by the charging object.

[0065] Step S204: Based on the charging request of the charging object, the location information of each charging pile and the allocated charging power of each charging pile, determine the candidate charging pile, and send the difficult charging period and the location information of the candidate charging pile to the charging object.

[0066] In this embodiment, based on the charging request of the charging object, a charging pile with a suitable location and sufficient charging power is matched as a candidate charging pile to meet the charging object's charging needs. By sending the location information of the difficult period of photovoltaic power generation and the candidate charging pile to the charging object, the charging object can be guided to go to the charging pile for charging during the difficult period of photovoltaic power generation, thereby making full use of the difficult power generation during the difficult period of photovoltaic power generation and reducing energy waste.

[0067] This invention utilizes the topology between photovoltaic (PV) power generation nodes and various charging piles within a target area to allocate the difficult-to-absorb electricity generated by PV power generation nodes to each charging pile during periods of grid connection difficulties. This allows the charging piles to absorb the difficult-to-absorb electricity generated by PV power generation that cannot be connected to the grid. By acquiring the charging requests of charging users, the invention matches charging users with suitable locations and sufficient charging power, guiding them to the charging piles during periods of grid connection difficulties. This enables each charging pile to fully utilize the allocated charging power, thereby maximizing the utilization of PV energy generated by PV power generation, avoiding curtailment of solar power, and reducing energy waste.

[0068] In one possible implementation, step S201, obtaining the amount of electricity that is difficult to absorb from at least one photovoltaic power generation node in the target area during the period of difficult absorption, can be detailed as follows:

[0069] Obtain the photovoltaic power generation of at least one photovoltaic power generation node in the target area during each time period of a preset duration, and the amount of electricity that the regional power grid can absorb during each time period of the preset duration;

[0070] Based on the photovoltaic power generation and the amount of electricity that can be absorbed in each time period, determine the periods when photovoltaic power generation nodes face difficulties in absorbing electricity.

[0071] Based on the photovoltaic power generation and the amount of electricity that can be absorbed during the period of difficult absorption, calculate the amount of electricity that is difficult to absorb during the period of difficult absorption.

[0072] In this embodiment, the photovoltaic power generation of the photovoltaic power generation node can be predicted through meteorological data such as sunshine. For example, if the preset duration is one day and each time period is one hour, the photovoltaic output of each photovoltaic node in the target area can be predicted for each hour on the second day, thus obtaining the photovoltaic power generation of each photovoltaic node for each hour on the second day.

[0073] The amount of electricity that a regional power grid can absorb in each time period of a preset duration can be determined based on data released by the regional power grid dispatching agency. Specifically, the regional power grid dispatching agency will release the amount of photovoltaic power generation that each photovoltaic power generator can connect to the grid for absorption in each time period, or the proportion of the rated installed capacity that photovoltaic power generators can connect to the grid for absorption in each time period. Based on this proportion, the amount of electricity that the regional power grid can absorb in each time period of a preset duration can be determined.

[0074] For example, according to the forecast results of the regional power grid dispatching agency, the period from 14:00 to 16:00 on the second day is a difficult period for photovoltaic power generation to be absorbed in the region. During the period from 14:00 to 16:00, only 70% of the rated installed capacity of photovoltaic power generation can be uniformly connected to the grid for absorption. At other times, 100% of the rated installed capacity can be connected to the grid for absorption. Thus, the amount of electricity that the regional power grid can absorb in each period of the preset duration can be determined.

[0075] Based on the photovoltaic power generation and absorbable electricity corresponding to each time period of the photovoltaic power generation node, it is possible to accurately determine the difficult-to-absorb electricity during the difficult-to-absorb period of the photovoltaic node.

[0076] In one possible implementation, the charging request also includes the charging object's required power level;

[0077] Step S204 determines the candidate charging stations based on the charging request, the location information of each charging station, and the allocated charging power. This can be described in detail as follows:

[0078] Step S2041: Obtain confirmation information for all confirmed charging requests. The confirmation information includes the reserved charging station, the required electricity amount, and the reserved time period.

[0079] Step S2042: Based on the confirmation information that the reserved time period is a difficult period for charging and the allocated charging power of each charging pile, determine the remaining charging power of each charging pile during the difficult period for charging.

[0080] Step S2043: Determine all charging piles with remaining charging capacity greater than the required charging capacity as optional charging piles;

[0081] Step S2044: Based on the location information of each optional charging pile and the location information of the charging object, determine the distance between each optional charging pile and the charging object, and determine the optional charging pile with the smallest distance as the candidate charging pile.

[0082] In this embodiment, the charging request includes the location information of the object to be charged and the required amount of electricity. The charging piles are initially screened based on the required amount of electricity of the object to be charged, and charging piles with sufficient power can be selected as optional charging piles.

[0083] Optionally, since the charging requests of each charging object have a sequential order, in order to ensure that the charging pile can meet the current charging object's charging request, the portion of the reserved demanded power in the allocated charging power of each charging pile can be removed to determine the remaining charging power of each charging pile; the remaining charging power of the charging pile can be filtered according to the charging object's demanded power to ensure that the charging pile has sufficient charging power.

[0084] By using the location information of available charging stations and the location information of the object being charged, the nearest charging station can be found, so as to guide the object to charge and realize the utilization of electricity that is difficult to consume.

[0085] In one possible implementation, step S202 determines the allocated charging power for each charging pile during the difficult charging period based on the topology and the difficulty in absorbing the electricity. This can be detailed as follows:

[0086] Based on the topology and the difficulty in absorbing the electricity, an objective function is established with the goal of minimizing the line loss between photovoltaic power generation nodes and charging piles within the target area, and constraints on the objective function are also established.

[0087] The objective function is solved based on the constraints to obtain the allocated charging power for each charging pile.

[0088] In this embodiment, the allocation of power that is difficult to absorb is carried out with the goal of minimizing the line loss between the photovoltaic power generation nodes and each charging pile in the target area. This can provide a reasonable allocation of charging power to each charging pile, while reducing the loss of power that is difficult to absorb during transmission, and ensuring the full utilization of photovoltaic energy.

[0089] Optionally, the structure between photovoltaic power generation nodes and charging piles within the target area may include photovoltaic power generation nodes and charging pile nodes, and may also include other nodes.

[0090] The objective function is:

[0091] f = min∑ i,j |I ij | 2 ·Re(Z ij );

[0092] In the formula, f represents the objective function, I ij Re(Z) represents the current in line ij. ij) represents the real part of the impedance of line ij, i represents the i-th photovoltaic power generation node, and j represents the j-th charging pile node.

[0093] Optional constraints include power balance constraints, inter-node voltage constraints, and charging pile output power constraints.

[0094] Among them, power balance constraints include power balance constraints of photovoltaic nodes, power balance constraints of charging pile nodes, and power balance constraints of other nodes.

[0095] The power balance constraints of photovoltaic nodes are:

[0096]

[0097] The power balance constraints for charging pile nodes are:

[0098]

[0099] The power balance constraints for other nodes are:

[0100]

[0101] The inter-node voltage constraint is:

[0102] V i -V j =Z ij ·I ij .

[0103] The output power constraint of the charging pile is:

[0104] 0≤Pe j ≤Pe J .

[0105] In the formula, P i V represents the output power of the i-th photovoltaic power generation node. i Let represent the voltage of the i-th photovoltaic power generation node, and k represent the k-th node that is connected to the i-th photovoltaic power generation node by a line. V represents the conjugate of the current in line ik between photovoltaic power generation node i and node k, p represents the node p connected to the j-th charging pile by a line, and V j This represents the voltage of the j-th charging pile node. Pe represents the conjugate of the currents at node j and line pj at node p of the charging pile. j V represents the actual charging power of the j-th charging pile node, q represents the node that is connected to the h-th other node by a line, and V represents the actual charging power of the j-th charging pile node. q This represents the voltage at node q. Z represents the conjugate of the current in line qh at node h and node q. ijPe represents the impedance of line ij. J This represents the rated power of the j-th charging pile node.

[0106] Solving for the optimal solution to the above objective function and constraints will achieve the optimal power allocation among the charging piles while minimizing line loss, thereby obtaining the allocated charging power for each charging pile.

[0107] In one possible implementation, after determining the allocated charging power for each charging pile during the difficult charging period based on the topology and the difficult charging capacity in step S202, the method further includes:

[0108] The marginal charging price for each charging station is determined based on the allocated charging capacity of each charging station.

[0109] Accordingly, the method also includes:

[0110] The marginal charging price of the selected charging pile is sent to the charging target.

[0111] In this embodiment, the marginal charging price of each charging pile is re-determined based on the allocated charging power of each charging pile. By sending the marginal charging price to the charging object, the charging object is guided to charge during periods of difficult photovoltaic power consumption, thereby improving the photovoltaic power consumption capacity and avoiding curtailment.

[0112] In one possible implementation, after determining all charging stations with remaining charging capacity greater than the required charging capacity as selectable charging stations in step S2042, the method further includes:

[0113] The charging station with the lowest marginal charging price is selected as the candidate charging station.

[0114] In this embodiment, the optional charging pile with the lowest marginal charging price is also identified as the candidate charging pile. By leveraging the advantage of charging prices during periods of difficult photovoltaic power absorption, the charging target is guided to charge during these periods.

[0115] In one possible implementation, the marginal charging price for each charging station is determined based on the allocated charging capacity for each station, including:

[0116] Obtain the first initial charging amount corresponding to each pre-determined charging pile during the period of difficult consumption;

[0117] For each charging pile, the total charging capacity of the charging pile is calculated based on the allocated charging capacity of the charging pile in the difficult-to-consume electricity and the initial charging capacity of the charging pile.

[0118] The total charging capacity of each charging pile is input into the pre-trained model for calculating the first marginal charging price of the charging pile, and the first marginal charging price of each charging pile is obtained.

[0119] In this embodiment, each charging pile can also have an initial charging capacity to meet the normal charging needs of the users. The initial charging capacity of each charging pile is different, and the corresponding charging price is also different. After allocating the difficult-to-absorb electricity, the total charging capacity of each charging pile is different. Therefore, the marginal charging price of each charging pile is determined according to the pre-trained first marginal charging price calculation model to ensure that the marginal charging price of the charging pile matches the total charging capacity. This guides users to charge at charging piles with a larger total charging capacity, fully absorbing the charging capacity of the charging piles, thereby improving the photovoltaic absorption capacity.

[0120] In one possible implementation, the marginal charging price for each charging station is determined based on the allocated charging capacity for each station, including:

[0121] Obtain the second initial charging capacity corresponding to the period of difficult consumption of all charging piles in the predetermined target area. The second initial charging capacity is the sum of the initial charging capacity of all charging piles in the target area.

[0122] Calculate the total charging capacity of all charging piles in the target area based on the amount of electricity that is difficult to absorb and the second initial charging capacity;

[0123] The total charging capacity of all charging piles in the target area is input into the pre-trained second marginal charging price calculation model of the target area to obtain the second marginal charging price of each charging pile.

[0124] In this embodiment, all charging piles within the target area belong to the same photovoltaic operator, allowing the charging price to be determined as a whole. The total charging capacity of all charging piles within the target area is determined by summing the initial charging capacity of each pile and the amount of electricity subject to grid connection difficulties. Then, the marginal charging price of the charging piles within the target area is determined based on this total charging capacity. By adjusting the charging price of charging piles during periods of grid connection difficulties, the system guides users to charge during these periods, fully utilizing photovoltaic power generation and avoiding curtailment.

[0125] Optionally, the marginal charging price calculation model can be obtained by training a Support Vector Machine (SVM). The basic idea of ​​an SVM is to construct an optimal hyperplane in the feature space to separate sample points of different categories as much as possible. The optimal hyperplane can maximize the margin between the sample points and the hyperplane, thereby achieving accurate classification of unknown data.

[0126] When dealing with nonlinear problems, SVM uses kernel functions to map data to a high-dimensional feature space, making the nonlinear problem linearly separable in the high-dimensional space. Commonly used kernel functions include linear kernels, polynomial kernels, and radial basis function (RBF) kernels.

[0127] The regression function of SVM can be expressed as:

[0128]

[0129] In the formula, f(x) represents the regression function, x i Let x represent the i-th sample, l represent the total number of samples in the set, and ω represent the input vector. i Let K(x) represent the i-th weight vector, b represent the bias, and K(x) represent the bias. i (x) represents the kernel function, used to compute the input vector x and the sample x. i The similarity or correlation between them.

[0130] In a specific embodiment, a linear function is chosen to construct the kernel function of the SVM. The linear kernel function can be specifically represented as:

[0131] K(x i ,x)=x i ×x T +b

[0132] In the formula, K(x) i (x) represents the kernel function, i.e., the linear kernel function, x i Let x represent the i-th sample. T This expression represents the transpose of the input vector, and b represents the bias. The meaning of this expression is: a linear combination of the input vector and the sample, with an added bias.

[0133] To improve the speed of SVM without reducing the accuracy of the solution, the least squares method (LS) can be used for optimization, thereby forming the least squares support vector machine (LSSVM).

[0134] The optimal decision function of LSSVM in the high-dimensional feature space is:

[0135]

[0136] In the formula, y represents the optimal decision function, and ω represents the weight vector. Let X represent the decision function, X represent the vector formed by the sample set, and b represent the intercept, which is the offset corresponding to the decision function.

[0137] When solving regression problems, the above equation can be transformed into the following optimization problem:

[0138]

[0139] st

[0140]

[0141] In the formula, It is a function of the square of the error, used to represent the deviation between the predicted and actual values; e i Let y represent the i-th error quantity, γ represent the penalty coefficient, and y represent the error quantity. i Let x represent the i-th optimal decision function. i Let represent the i-th sample, and b represent the degree of paranoia.

[0142] The values ​​of the penalty coefficient γ and the kernel parameter λ are crucial, directly affecting the accuracy of marginal charging price prediction. An excessively large γ can lead to overlearning in the prediction model, while a small γ can result in underlearning. The value of the kernel parameter, in turn, affects the generalization performance of the SVM model.

[0143] If we take the accuracy of marginal charging price calculation as the objective function for optimizing parameters γ and λ, then we have:

[0144]

[0145] In the formula, G(M) represents the calculation accuracy of the marginal charging price, M represents the sample set containing all n samples, and γ min γ represents the minimum value of the penalty coefficient. max λ represents the maximum value of the penalty coefficient. min λ represents the minimum value of the kernel parameter. max This represents the maximum value of the kernel parameter.

[0146] In one specific embodiment, the target area is a high-tech industrial park. Figure 1 The topology of photovoltaic power generation nodes and charging pile nodes in a high-tech industrial park is shown, and simulation calculations are performed using the charging pile management method based on distributed photovoltaic power generation provided by this invention.

[0147] Figure 1The system includes two photovoltaic (PV) power generation nodes, three charging pile nodes, and a power distribution room node. The PV power generation nodes are designated as nodes 1 and 4, the charging pile nodes as nodes 2, 3, and 5, and the power distribution room node as node 5'. Since node 5' and node 5 are very close, there is no impedance between them, and they can be considered the same node. The voltage level is 220V. The PV power output of nodes 1 and 4 is 100kW each. The charging piles at nodes 2, 3, and 5 are of the same model, with a maximum charging power of 150kW each. The power distribution room includes a metering station and a step-up transformer with a transformer ratio of 220V / 10kV.

[0148] The structure contains a total of 4 lines, namely:

[0149] The impedance of the line between node 1 and node 2 is (0.02 + j0.2) Ω;

[0150] The impedance of the line between node 2 and node 3 is (0.01 + j0.1) Ω;

[0151] The impedance of the line between node 2 and node 4 is (0.04 + j0.4) Ω;

[0152] The impedance of the line between node 4 and node 5 is (0.02 + j0.2) Ω;

[0153] Where j represents the imaginary unit.

[0154] The period of difficulty in absorbing the load is from 2:00 PM to 3:00 PM, during which time the photovoltaic power generation nodes can achieve full power generation.

[0155] Without adopting the charging pile management method based on distributed photovoltaic power generation proposed in this invention, the charging price during this period is 0.5641 yuan / kWh, the total charging capacity of the charging piles is 358.71kWh, and the distributed photovoltaic power generation can only consume 70% of the electricity, i.e., 140kWh, resulting in 60kWh of wasted power. At this time, the output power of each charging pile is the same, and the charging capacity of each charging pile is expressed by power, as shown in Table 1.

[0156] Table 1. Charging Power Allocation for Charging Piles When Photovoltaic Power Generation is Not Consumed Locally

[0157] Output power of charging pile 1 119.57kW Output power of charging pile 2 119.57kW Output power of charging pile 3 119.57kW Distributed photovoltaic power curtailment 60kW

[0158] To reduce solar power curtailment, the distributed photovoltaic power generation-based charging pile management method proposed in this invention is adopted. This method allocates 30% of the curtailed solar power (60 kWh) to charging piles within the target area and guides electric vehicles to charge at these piles, thus absorbing the curtailed solar power locally. Using a marginal charging price calculation model, the marginal charging price for this period is calculated to be 0.3232 yuan / kWh. At this price level, the total charging capacity of charging piles within the target area increases from 358.71 kWh to 418.71 kWh, which can fully absorb the curtailed solar power that cannot be connected to the grid.

[0159] With the goal of minimizing line loss between photovoltaic power generation nodes and each charging pile, the ungridable electricity generated by the two photovoltaic power generation nodes (i.e., 60kWh of curtailed power, of which 30kWh is generated by each of the two photovoltaic power generation nodes, totaling 60kWh) is optimally allocated to determine the allocated charging power for each charging pile. The allocated charging power is still expressed as power, as shown in Table 2.

[0160] Table 2. Charging Power Allocation Table for Charging Stations

[0161]

[0162]

[0163] As shown in Table 2, during the peak photovoltaic power generation period from 14:00 to 15:00 in the afternoon, 60 kWh of the difficult-to-consume electricity generated by photovoltaic power generation can be consumed locally, with a total power loss of 0.461 kWh.

[0164] Based on the data in Tables 1 and 2, it can be seen that by adopting the charging pile management method based on distributed photovoltaic power generation provided by this invention, 60kWh of ungridable photovoltaic power can be locally absorbed by three charging piles in the target area, reducing power loss from 60kWh to 0.461kWh, greatly reducing the waste of energy resources and realizing the full utilization of photovoltaic power generation energy. At the same time, electric vehicle owners can enjoy electricity price discounts during this period, with the charging price for this portion of electricity being only 0.3232 yuan / kWh, which is 42.71% lower than the normal electricity price of 0.5641 yuan / kWh during this period, thus reducing charging costs.

[0165] In addition, in this embodiment, the charging volume of electric vehicles under different charging prices during the afternoon of weekdays (14:00-16:00) in the high-tech industrial park is selected as the basic dataset for training the marginal charging price calculation model. Partial data of the basic dataset is shown in Table 3.

[0166] Table 3. Charging Price and Charging Amount of Charging Stations in the Park

[0167]

[0168]

[0169] Based on the characteristics of the SVM model, the proportion of the training set is set to 80% and the proportion of the test set is set to 20%. If the number of samples is not large enough, a lower random state seed value can be used to avoid model generalization.

[0170] The function prediction error was tested using linear kernel function, polynomial kernel function, Gaussian kernel function, and Sigmoid kernel function respectively. The test results are shown in Table 4 below:

[0171] Table 4. Prediction Errors for Different Kernel Functions

[0172] SVM kernel function type Root Mean Square Error (RMSE) Linear kernel function 0.109279 Polynomial kernel function (quadratic) 0.129963 Polynomial kernel function (degree 3) 0.155614 Polynomial kernel function (degree 4) 0.176344 Gaussian kernel function 0.132268 Sigmoid kernel function 0.291942

[0173] As shown in Table 4, the linear kernel function has the best fitting effect on the basic data, with the smallest root mean square error of 0.109279. Therefore, the linear kernel function is selected for function fitting.

[0174] Within the park's microgrid, the total installed capacity of distributed photovoltaic (PV) power generation is 200kW. According to forecast data from the grid dispatching agency, the grid will absorb 70% of the PV power generation between 2:00 PM and 3:00 PM the following day. This means that 70kWh of PV power generation exceeding 70% of its rated capacity cannot be absorbed through grid connection, resulting in 60kWh of electricity needing to be absorbed within the park. The normal charging price during this period is 0.5641 yuan / kWh, and the initial charging capacity of the charging pile is 358.71kWh.

[0175] By allocating the difficult-to-consume electricity to various charging piles within the park, the total charging capacity of all charging piles in the park increased from 358.71kWh to 418.71kWh (that is, the 60kWh of difficult-to-consume electricity that cannot be connected to the grid is used as charging capacity to consume excess photovoltaic power). Using a trained marginal charging price calculation model, the marginal charging price for this period was calculated to be 0.3232 yuan / kWh, meaning that the charging price of the charging piles decreased from 0.5641 yuan / kWh to 0.3232 yuan / kWh. This reduction in charging price can motivate users within the park to charge their devices and facilitate the consumption of photovoltaic power generation.

[0176] This invention, through its embodiments, identifies the periods and quantities of photovoltaic (PV) power generation that are difficult to absorb by PV nodes, based on the PV power generation and the regional grid's absorbable power for each time period. This accurately determines the non-grid-connected power generation generated by PV nodes within the target area, facilitating the full absorption of this power. By utilizing the topology between PV nodes and charging piles within the target area, the non-grid-connected power generation from PV nodes is allocated to each charging pile during these difficult periods, allowing the charging piles to absorb the non-grid-connected power generated by PV power generation. Specifically, by establishing an objective function that minimizes line loss between PV nodes and charging piles, the allocated charging power for each charging pile is determined, reducing transmission losses and ensuring the full absorption of PV energy. By acquiring charging requests from users, the system matches users with suitable charging piles and sufficient charging capacity, guiding them to charge during periods of low solar power consumption. This ensures that each charging pile fully utilizes its allocated charging capacity, thereby maximizing the utilization of photovoltaic energy and preventing curtailment, thus reducing energy waste. Furthermore, by allocating charging capacity and determining the marginal charging price of each charging pile, which is then sent to users, the system guides them to charge during periods of low solar power consumption, maximizing the utilization of surplus photovoltaic power. Finally, by identifying the charging pile with the lowest marginal charging price as a candidate charging pile, users are guided to charge at the charging pile with the highest total charging capacity, improving the photovoltaic power absorption capacity.

[0177] It should be understood that the sequence number of each step in the above embodiments does not imply the order of execution. The execution order of each process should be determined by its function and internal logic, and should not constitute any limitation on the implementation process of the embodiments of the present invention.

[0178] The following are device embodiments of the present invention. For details not described in detail, please refer to the corresponding method embodiments described above.

[0179] Figure 4 A schematic diagram of a charging pile management device based on distributed photovoltaic power generation provided in an embodiment of the present invention is shown. For ease of explanation, only the parts related to the embodiment of the present invention are shown, and are described in detail below:

[0180] like Figure 4 As shown, the charging pile management device 40 based on distributed photovoltaic power generation includes:

[0181] The first acquisition module 41 is used to acquire the amount of electricity that is difficult to absorb during the difficult period of absorption of at least one photovoltaic power generation node in the target area, and to acquire the topology between the photovoltaic power generation node and each charging pile in the target area.

[0182] The first determining module 42 is used to determine the allocated charging power of each charging pile during the difficult period of power consumption based on the topology and the power consumption difficulties.

[0183] The second acquisition module 43 is used to acquire the charging request of the charging object and the location information of each charging pile. The charging request includes the location information of the charging object.

[0184] The second determining module 44 is used to determine the candidate charging piles based on the charging request of the charging object, the location information of each charging pile and the allocated charging power of each charging pile, and send the difficult charging period and the location information of the candidate charging piles to the charging object.

[0185] In one possible implementation, the first acquisition module 41 is specifically used for:

[0186] Obtain the photovoltaic power generation of at least one photovoltaic power generation node in the target area during each time period of a preset duration, and the amount of electricity that the regional power grid can absorb during each time period of the preset duration;

[0187] Based on the photovoltaic power generation and the amount of electricity that can be absorbed in each time period, determine the periods when photovoltaic power generation nodes face difficulties in absorbing electricity.

[0188] Based on the photovoltaic power generation and the amount of electricity that can be absorbed during the period of difficult absorption, calculate the amount of electricity that is difficult to absorb during the period of difficult absorption.

[0189] In one possible implementation, the charging request also includes the charging object's required power level;

[0190] The second determining module 44 is specifically used for:

[0191] Obtain confirmation information for all confirmed charging requests, including the reserved charging station, the required electricity amount, and the reserved time period;

[0192] Based on the confirmation information that the reserved time period is a period of difficult charging and the allocated charging power of each charging pile, determine the remaining charging power of each charging pile during the period of difficult charging.

[0193] All charging stations with remaining charging capacity greater than the required charging capacity are identified as optional charging stations.

[0194] Based on the location information of each optional charging station and the location information of the charging object, the distance between each optional charging station and the charging object is determined, and the optional charging station with the smallest distance is selected as the candidate charging station.

[0195] In one possible implementation, the first determining module 42 is specifically used for:

[0196] Based on the topology and the difficulty in absorbing the electricity, an objective function is established with the goal of minimizing the line loss between photovoltaic power generation nodes and charging piles within the target area, and constraints on the objective function are also established.

[0197] The objective function is solved based on the constraints to obtain the allocated charging power for each charging pile.

[0198] In one possible implementation, the objective function is:

[0199] f = min∑ i,j |I ij | 2 ·Re(Z ij );

[0200] In the formula, f represents the objective function, I ij Re(Z) represents the current in line ij. ij ) represents the real part of the impedance of line ij, i represents the photovoltaic power generation node, and j represents the charging pile node.

[0201] In one possible implementation, the first determining module 42 is further configured to:

[0202] The marginal charging price for each charging station is determined based on the allocated charging capacity of each charging station.

[0203] Correspondingly, the second determining module 44 is also used for:

[0204] The marginal charging price of the selected charging pile is sent to the charging target.

[0205] In one possible implementation, the second determining module 44 is further configured to:

[0206] The charging station with the lowest marginal charging price is selected as the candidate charging station.

[0207] In one possible implementation, the first determining module 42 is specifically used for:

[0208] Obtain the first initial charging amount corresponding to each pre-determined charging pile during the period of difficult consumption;

[0209] For each charging pile, the total charging capacity of the charging pile is calculated based on the allocated charging capacity of the charging pile in the difficult-to-consume electricity and the initial charging capacity of the charging pile.

[0210] The total charging capacity of each charging pile is input into the pre-trained model for calculating the first marginal charging price of the charging pile, and the first marginal charging price of each charging pile is obtained.

[0211] In one possible implementation, the first determining module 42 is specifically used for:

[0212] Obtain the second initial charging capacity corresponding to the period of difficult consumption of all charging piles in the predetermined target area. The second initial charging capacity is the sum of the initial charging capacity of all charging piles in the target area.

[0213] Calculate the total charging capacity of all charging piles in the target area based on the amount of electricity that is difficult to absorb and the second initial charging capacity;

[0214] The total charging capacity of all charging piles in the target area is input into the pre-trained second marginal charging price calculation model of the target area to obtain the second marginal charging price of each charging pile.

[0215] In the above embodiments, the descriptions of each embodiment have different focuses. For parts that are not described in detail or recorded in a certain embodiment, please refer to the relevant descriptions of other embodiments.

[0216] Those skilled in the art will recognize that the templates, units, and algorithm steps of the various examples described in conjunction with the embodiments disclosed herein can be implemented in electronic hardware, or a combination of computer software and electronic hardware. Whether these functions are implemented in hardware or software depends on the specific application and design constraints of the technical solution. Those skilled in the art can use different methods to implement the described functions for each specific application, but such implementations should not be considered beyond the scope of this invention.

[0217] If a module / unit is implemented as a software functional unit and sold or used as an independent product, it can be stored in a computer-readable storage medium. Based on this understanding, all or part of the processes in the methods of the above embodiments of the present invention can also be implemented by a computer program instructing related hardware. The computer program can be stored in a computer-readable storage medium, and when executed by a processor, it can implement the steps of the various method embodiments described above. The computer program includes computer program code, which can be in the form of source code, object code, executable files, or certain intermediate forms. The computer-readable medium can include: any entity or device capable of carrying computer program code, recording media, USB flash drives, portable hard drives, magnetic disks, optical disks, computer memory, read-only memory, random access memory, electrical carrier signals, telecommunication signals, and software distribution media, etc.

[0218] The above embodiments are only used to illustrate the technical solutions of the present invention, and are not intended to limit it. Although the present invention has been described in detail with reference to the foregoing embodiments, those skilled in the art should understand that modifications can still be made to the technical solutions described in the foregoing embodiments, or equivalent substitutions can be made to some of the technical features. Such modifications or substitutions do not cause the essence of the corresponding technical solutions to deviate from the spirit and scope of the technical solutions of the embodiments of the present invention, and should all be included within the protection scope of the present invention.

Claims

1. A charging pile management method based on distributed photovoltaic power generation, characterized in that, include: The system obtains the amount of electricity that is difficult to absorb during the period of difficult absorption of photovoltaic power generation at least one photovoltaic power generation node in the target area, and obtains the topology between the photovoltaic power generation node and each charging pile in the target area. Based on the topology and the amount of electricity that is difficult to absorb, determine the allocated charging power for each charging pile during the period of difficulty in absorbing electricity. Obtain the charging request of the charging object and the location information of each charging pile, wherein the charging request includes the location information of the charging object; Based on the charging request of the charging object, the location information of each charging pile, and the allocated charging power of each charging pile, the candidate charging pile is determined, and the difficult period of charging and the location information of the candidate charging pile are sent to the charging object. The acquisition of the difficult-to-absorb electricity volume of at least one photovoltaic power generation node in the target area during the difficult-to-absorb period includes: Obtain the photovoltaic power generation of at least one photovoltaic power generation node in the target area during each time period of a preset duration, and the amount of electricity that the regional power grid can absorb during each time period of the preset duration; Based on the photovoltaic power generation and the amount of electricity that can be absorbed for each time period, the difficult periods for the photovoltaic power generation nodes to absorb electricity are determined; Based on the photovoltaic power generation and absorbable electricity corresponding to the difficult period of grid connection, calculate the difficult electricity to be absorbed during the difficult period of grid connection. The charging request also includes the power requirement of the object to be charged; The step of determining the candidate charging piles based on the charging request, the location information of each charging pile, and the allocated charging power includes: Obtain confirmation information for all confirmed charging requests, including the reserved charging station, the required electricity amount, and the reserved time period; Based on the confirmation information that the reserved time period is the period of difficult consumption and the allocated charging power of each charging pile, the remaining charging power of each charging pile is determined during the period of difficult consumption. All charging stations with remaining charging capacity greater than the required charging capacity are identified as optional charging stations. Based on the location information of each optional charging pile and the location information of the charging object, the distance between each optional charging pile and the charging object is determined, and the optional charging pile with the smallest distance is determined as the candidate charging pile.

2. The charging pile management method based on distributed photovoltaic power generation according to claim 1, characterized in that, The step of determining the allocated charging power for each charging pile during periods of difficult power absorption based on the topology and the amount of electricity that is difficult to absorb includes: Based on the topology and the difficult-to-absorb electricity, an objective function is established with the goal of minimizing the line loss between the photovoltaic power generation nodes and each charging pile within the target area, and constraints on the objective function are established. The objective function is solved based on the constraints to obtain the allocated charging power for each charging pile.

3. The charging pile management method based on distributed photovoltaic power generation according to claim 2, characterized in that, The objective function is: ； In the formula, Denotes the objective function, Indicates the line The current, Indicates the line The real part of the impedance, This refers to the photovoltaic power generation node. This indicates the node of the charging pile.

4. The charging pile management method based on distributed photovoltaic power generation according to claim 1, characterized in that, After determining the allocated charging power for each charging pile during the difficult charging period based on the topology and the difficult charging power, the method further includes: The marginal charging price for each charging station is determined based on the allocated charging capacity of each charging station. Accordingly, the method further includes: The marginal charging price of the selected charging pile is sent to the charging target.

5. The charging pile management method based on distributed photovoltaic power generation according to claim 4, characterized in that, After identifying all charging stations with remaining charging capacity greater than the required charging capacity as selectable charging stations, the process further includes: The charging station with the lowest marginal charging price is selected as the candidate charging station.

6. The charging pile management method based on distributed photovoltaic power generation according to claim 5, characterized in that, The step of determining the marginal charging price for each charging pile based on its allocated charging capacity includes: Obtain the first initial charging amount corresponding to each pre-determined charging pile during the period of difficult consumption; For each charging pile, the total charging capacity of the charging pile is calculated based on the allocated charging capacity of the charging pile in the difficult-to-absorb electricity and the initial charging capacity of the charging pile. The total charging capacity of each charging pile is input into the pre-trained model for calculating the first marginal charging price of the charging pile, and the first marginal charging price of each charging pile is obtained.

7. The charging pile management method based on distributed photovoltaic power generation according to claim 4, characterized in that, The step of determining the marginal charging price for each charging pile based on its allocated charging capacity includes: Obtain the second initial charging capacity corresponding to the difficult period of consumption for all charging piles in the target area, where the second initial charging capacity is the sum of the initial charging capacity of all charging piles in the target area; Based on the difficult-to-absorb electricity and the second initial charging electricity, calculate the total charging electricity of all charging piles in the target area; The total charging capacity of all charging piles in the target area is input into the pre-trained second marginal charging price calculation model of the target area to obtain the second marginal charging price of each charging pile.

8. A charging pile management device based on distributed photovoltaic power generation, characterized in that, include: The first acquisition module is used to acquire the amount of electricity that is difficult to absorb during the period of difficult absorption of photovoltaic power generation nodes in the target area, and to acquire the topology between the photovoltaic power generation nodes and each charging pile in the target area. The first determining module is used to determine the allocated charging power of each charging pile during the difficult period of power absorption based on the topology and the power absorption difficulties. The second acquisition module is used to acquire the charging request of the charging object and the location information of each charging pile, wherein the charging request includes the location information of the charging object; The second determining module is used to determine the candidate charging piles based on the charging request of the charging object, the location information of each charging pile and the allocated charging power of each charging pile, and send the difficult period of charging and the location information of the candidate charging piles to the charging object. The first acquisition module is specifically used for: Obtain the photovoltaic power generation of at least one photovoltaic power generation node in the target area during each time period of a preset duration, and the amount of electricity that the regional power grid can absorb during each time period of the preset duration; Based on the photovoltaic power generation and the amount of electricity that can be absorbed for each time period, the difficult periods for the photovoltaic power generation nodes to absorb electricity are determined; Based on the photovoltaic power generation and absorbable electricity corresponding to the difficult period of grid connection, calculate the difficult electricity to be absorbed during the difficult period of grid connection. The charging request also includes the power requirement of the object to be charged; The second determining module is specifically used for: Obtain confirmation information for all confirmed charging requests, including the reserved charging station, the required electricity amount, and the reserved time period; Based on the confirmation information that the reserved time period is the period of difficult consumption and the allocated charging power of each charging pile, the remaining charging power of each charging pile is determined during the period of difficult consumption. All charging stations with remaining charging capacity greater than the required charging capacity are identified as optional charging stations. Based on the location information of each optional charging pile and the location information of the charging object, the distance between each optional charging pile and the charging object is determined, and the optional charging pile with the smallest distance is determined as the candidate charging pile.

Images