A method and system for smoothing tie-line power fluctuations based on electric vehicles

Abstract

The application provides a tie line power fluctuation flattening method and system based on an electric vehicle, comprising the following steps: determining a target change value of total output power of a plurality of electric vehicle clusters based on a real-time fluctuation rate of a tie line and real-time power of the tie line; determining a target change value of output power of each electric vehicle cluster based on the target change value of total output power of the plurality of electric vehicle clusters, total capacity of batteries of the electric vehicle cluster and output power of the batteries of the electric vehicle cluster; determining a target value of output power of each electric vehicle in each electric vehicle cluster based on the target change value of output power of each electric vehicle cluster and an SOC state of each electric vehicle; and calculating actual power of the tie line after flattening based on the target value of output power of each electric vehicle in each cluster. The application comprehensively considers information such as a battery state of charge of an electric vehicle and output power of the electric vehicle, optimizes charging and discharging behaviors of users on the basis of guaranteeing demands of the users for energy and travel.

Description

Technical Field

[0001] This invention relates to the field of V2G charging and discharging control for electric vehicles, and specifically to a method and system for smoothing power fluctuations in the tie line of an electric vehicle. Background Technology

[0002] With the large-scale integration of distributed renewable energy into the power grid, its random and intermittent nature will profoundly impact the safe and stable operation of the grid. The power output of distributed renewable energy is highly volatile, and traditional generators, limited by ramp-up rates, struggle to track these rapid changes. This has become a major obstacle to the large-scale grid integration of distributed renewable energy. To promote the absorption and utilization of distributed renewable energy in the grid, an effective approach is to utilize energy storage devices to mitigate the impact of power fluctuations.

[0003] In recent years, with the rapid development of demand-side response technology, demand-side resources, represented by electric vehicles, can serve as energy storage units after being connected to the power grid. By changing the amount of power exchanged with the grid (charging or discharging), they can provide various types of ancillary services to the grid. Therefore, how to optimize the charging and discharging behavior of electric vehicle users while ensuring their energy and travel needs, and how to provide ancillary services to the grid through electric vehicles to achieve the smoothing of tie-line power fluctuations, is a key issue that needs to be addressed by those skilled in the art. Summary of the Invention

[0004] To address the challenge of optimizing charging and discharging behavior for electric vehicle (EV) users while ensuring their energy and travel needs, and to mitigate tie-line power fluctuations by enabling EVs to provide ancillary services to the power grid, this invention proposes a tie-line power fluctuation mitigation method based on EVs, comprising:

[0005] The target change value of the total output power of multiple electric vehicle clusters is determined based on the real-time volatility and real-time power of the tie line.

[0006] The target change value of the output power of each electric vehicle cluster is determined based on the target change value of the total output power of the multiple electric vehicle clusters, the total battery capacity of the electric vehicle clusters, and the output power of the electric vehicle clusters.

[0007] Based on the target change value of the output power of each electric vehicle cluster and the SOC state of each electric vehicle, the target value of the output power of each electric vehicle in each electric vehicle cluster is determined.

[0008] The actual power of the tie line after smoothing is calculated based on the target value of the output power of each electric vehicle in each cluster.

[0009] Optionally, determining the target change value of the total output power of multiple electric vehicle clusters based on the real-time volatility and real-time power of the tie line includes:

[0010] The tie-line power mitigation target value is determined based on the tie-line real-time volatility and its upper and lower limits.

[0011] Alternatively, the target value for tie-line power suppression can be determined based on the discharge power of electric vehicles in the electric vehicle cluster;

[0012] The target change value of the total output power of the electric vehicle cluster is obtained by subtracting the real-time power of the tie line from the target value of the tie line power suppression.

[0013] Optionally, determining the tie-line power smoothing target value based on the tie-line's real-time volatility and its upper and lower limits includes:

[0014] When the real-time volatility of the tie line is less than the lower limit of the real-time volatility, the tie line power stabilization target value is determined by the tie line real-time power, the lower limit of the real-time volatility power, and the rated power of the tie line at the previous moment.

[0015] When the real-time volatility of the tie line is less than the lower limit and upper limit of the real-time volatility, the real-time power of the tie line is used as the tie line power smoothing target value.

[0016] When the real-time volatility of the tie line is greater than the upper limit of the real-time volatility, the tie line power suppression target value is determined by the tie line real-time power, the upper limit of the real-time volatility power, and the rated power of the tie line at the previous moment.

[0017] Optionally, the target value for power suppression of the tie line is calculated using the following formula:

[0018] P DE* (t)=P DE (t-Δt)+br min ·P DE,rated

[0019] In the formula, To suppress the target value of tie line power; P DE (t-Δt) represents the real-time power of the tie line at time t-Δt; min P represents the lower bound of real-time volatility. DE,rated This refers to the rated power of the connecting line.

[0020] Optionally, determining the total discharge power of the electric vehicle cluster based on the discharge power of the electric vehicles in the cluster includes:

[0021] The total discharge power of the electric vehicle cluster is the sum of the discharge power of the electric vehicles in the cluster.

[0022] The difference is obtained by subtracting the total discharge power of the electric vehicle cluster from the real-time power of the connecting line, and the difference is used as the total discharge power of the electric vehicle cluster.

[0023] Optionally, determining the target change value of the output power of each electric vehicle cluster based on the target change value of the total output power of the multiple electric vehicle clusters, the total battery capacity of the electric vehicle clusters, and the battery capacity of the electric vehicle clusters includes:

[0024] When the target change value of the total output power of the multiple electric vehicle clusters is greater than zero and less than the difference between the maximum output power and the output power of the electric vehicle cluster, the first objective function is constructed by providing more target power for the cluster with larger energy storage capacity, and the target change value of the output power of each electric vehicle cluster is determined by combining the target change value constraint of the electric vehicle output power.

[0025] When the target change value of the total output power of the multiple electric vehicle clusters is less than zero and greater than the difference between the minimum output power and the output power of the electric vehicle cluster, a second objective function is constructed with the cluster with the smallest energy storage capacity providing more target power. The target change value of the output power of each electric vehicle cluster is determined by combining the target change value constraint of the electric vehicle output power.

[0026] When the target change value of the total output power of the multiple electric vehicle clusters is greater than the difference between the maximum output power of the electric vehicle cluster and the output power of the electric vehicle cluster, the difference between the maximum output power of the electric vehicle cluster and the output power of the electric vehicle cluster shall be used as the target change value of the output power of each electric vehicle cluster.

[0027] When the target change value of the total output power of the multiple electric vehicle clusters is less than the difference between the maximum output power of the electric vehicle cluster and the output power of the electric vehicle cluster, the difference between the maximum output power of the electric vehicle cluster and the output power of the electric vehicle cluster shall be used as the target change value of the output power of each electric vehicle cluster.

[0028] Optionally, determining the target value of the output power of each electric vehicle in each electric vehicle cluster based on the target change value of the output power of each electric vehicle cluster and the SOC state of each electric vehicle includes:

[0029] When the target change value of the output power of each electric vehicle cluster is greater than zero, the target value of the output power of each electric vehicle in the electric vehicle cluster is obtained based on the target change value of the output power of each electric vehicle cluster, the real-time power of the electric vehicles in the electric vehicle cluster, the SOC, the lower limit of SOC during discharge, and the discharge formula.

[0030] When the target change value of the output power of each electric vehicle cluster is less than zero, the target value of the output power of each electric vehicle in the electric vehicle cluster is obtained by combining the target change value of the output power of each electric vehicle cluster, the real-time power of the electric vehicles in the electric vehicle cluster, the SOC, the lower limit of SOC during discharge, and the charging formula.

[0031] Optionally, the discharge formula is as follows:

[0032]

[0033] In the formula, P represents the target output power of the j-th electric vehicle in the k-th electric vehicle cluster. k,j (t) represents the real-time power of the j-th electric vehicle in the k-th electric vehicle cluster; S k,j (t) represents the real-time SOC of the j-th electric vehicle in the k-th electric vehicle cluster; Let SOC be the lower limit of the j-th electric vehicle in the k-th electric vehicle cluster during discharge. Let be the number of electric vehicles in the k-th electric vehicle cluster; The target change value for the output power of the electric vehicle cluster.

[0034] Optionally, the charging formula is as follows:

[0035]

[0036] In the formula, P represents the target output power of the j-th electric vehicle in the k-th electric vehicle cluster. k,j (t) represents the real-time power of the j-th electric vehicle in the k-th electric vehicle cluster; S k,j (t) represents the real-time SOC of the j-th electric vehicle in the k-th electric vehicle cluster; The upper limit of SOC when charging the j-th electric vehicle in the k-th electric vehicle cluster; Let be the number of electric vehicles in the k-th electric vehicle cluster; The target change value for the output power of the electric vehicle cluster.

[0037] Furthermore, this application also provides a tie-line power fluctuation mitigation system based on electric vehicles, comprising:

[0038] Global control module: Determines the target change value of the total output power of multiple electric vehicle clusters based on the real-time volatility and real-time power of the tie line;

[0039] Local control module: used to determine the target change value of the output power of each electric vehicle cluster based on the target change value of the total output power of the multiple electric vehicle clusters, the total battery capacity of the electric vehicle clusters, and the battery of the electric vehicle clusters;

[0040] The individual control module is used to determine the target value of the output power of each electric vehicle in each electric vehicle cluster based on the target change value of the output power of each electric vehicle cluster and the SOC state of each electric vehicle.

[0041] The terminal control module calculates the smoothed actual power of the tie line based on the target value of the output power of each electric vehicle in each cluster.

[0042] Optionally, the local area control module includes:

[0043] The power mitigation target calculation submodule is used to determine the power mitigation target value of the tie line based on the real-time volatility of the tie line and its upper and lower limits; or to determine the power mitigation target value of the tie line based on the discharge power of electric vehicles in the electric vehicle cluster.

[0044] The total target calculation submodule is used to obtain the target change value of the total output power of the electric vehicle cluster by subtracting the real-time power of the tie line from the tie line power suppression target value. Optionally, the suppression target calculation submodule is specifically used to: determine the tie line power suppression target value by using the tie line real-time power, the lower limit of real-time fluctuation power, and the rated power of the tie line at the previous moment when the real-time fluctuation rate of the tie line is less than the lower limit of the real-time fluctuation rate.

[0045] When the real-time volatility of the tie line is less than the lower limit and upper limit of the real-time volatility, the real-time power of the tie line is used as the tie line power smoothing target value.

[0046] When the real-time volatility of the tie line is greater than the upper limit of the real-time volatility, the tie line power suppression target value is determined by the tie line real-time power, the upper limit of the real-time volatility power, and the rated power of the tie line at the previous moment.

[0047] Alternatively, the total discharge power of the electric vehicle cluster can be obtained by summing the discharge power of the electric vehicles in the cluster; the difference between the real-time power of the tie line and the total discharge power of the electric vehicle cluster can be used as the tie line power stabilization target value.

[0048] Optionally, the local control module is specifically used for:

[0049] When the target change value of the total output power of the multiple electric vehicle clusters is greater than zero and less than the difference between the maximum output power and the output power of the electric vehicle cluster, the first objective function is constructed by providing more target power for the cluster with larger energy storage capacity, and the target change value of the output power of each electric vehicle cluster is determined by combining the target change value constraint of the electric vehicle output power.

[0050] When the target change value of the total output power of the multiple electric vehicle clusters is less than zero and greater than the difference between the minimum output power and the output power of the electric vehicle cluster, a second objective function is constructed with the cluster with the smallest energy storage capacity providing more target power. The target change value of the output power of each electric vehicle cluster is determined by combining the target change value constraint of the electric vehicle output power.

[0051] When the target change value of the total output power of the multiple electric vehicle clusters is greater than the difference between the maximum output power of the electric vehicle cluster and the output power of the electric vehicle cluster, the difference between the maximum output power of the electric vehicle cluster and the output power of the electric vehicle cluster shall be used as the target change value of the output power of each electric vehicle cluster.

[0052] When the target change value of the total output power of the multiple electric vehicle clusters is less than the difference between the maximum output power of the electric vehicle cluster and the output power of the electric vehicle cluster, the difference between the maximum output power of the electric vehicle cluster and the output power of the electric vehicle cluster shall be used as the target change value of the output power of each electric vehicle cluster.

[0053] Optional, individual control module, specifically used for:

[0054] When the target change value of the output power of each electric vehicle cluster is greater than zero, the target value of the output power of each electric vehicle in the electric vehicle cluster is obtained based on the target change value of the output power of each electric vehicle cluster, the real-time power of the electric vehicles in the electric vehicle cluster, the SOC, the lower limit of SOC during discharge, and the discharge formula.

[0055] When the target change value of the output power of each electric vehicle cluster is less than zero, the target value of the output power of each electric vehicle in the electric vehicle cluster is obtained by combining the target change value of the output power of each electric vehicle cluster, the real-time power of the electric vehicles in the electric vehicle cluster, the SOC, the lower limit of SOC during discharge, and the charging formula.

[0056] Optionally, the discharge formula is as follows:

[0057]

[0058] In the formula, P represents the target output power of the j-th electric vehicle in the k-th electric vehicle cluster. k,j(t) represents the real-time power of the j-th electric vehicle in the k-th electric vehicle cluster; S k,j (t) represents the real-time SOC of the j-th electric vehicle in the k-th electric vehicle cluster; Let SOC be the lower limit of the j-th electric vehicle in the k-th electric vehicle cluster during discharge. Let be the number of electric vehicles in the k-th electric vehicle cluster; The target change value for the output power of the electric vehicle cluster.

[0059] Optionally, the charging formula is as follows:

[0060]

[0061] In the formula, P represents the target output power of the j-th electric vehicle in the k-th electric vehicle cluster. k,j (t) represents the real-time power of the j-th electric vehicle in the k-th electric vehicle cluster; S k,j (t) represents the real-time SOC of the j-th electric vehicle in the k-th electric vehicle cluster; The upper limit of SOC when charging the j-th electric vehicle in the k-th electric vehicle cluster; The target change value for the output power of the electric vehicle cluster.

[0062] Furthermore, this application also provides a computing device, comprising: one or more processors;

[0063] A processor is used to execute one or more programs;

[0064] When the one or more programs are executed by the one or more processors, a tie-line power fluctuation smoothing method based on electric vehicles as described above is implemented.

[0065] In another aspect, this application also provides a computer-readable storage medium having a computer program stored thereon, which, when executed, implements the above-described method for smoothing power fluctuations in tie lines based on electric vehicles.

[0066] Compared with the prior art, the beneficial effects of the present invention are as follows:

[0067] This invention provides a method for mitigating power fluctuations in electric vehicle (EV) tie lines, comprising: determining a target change value for the total output power of multiple EV clusters based on the real-time volatility and real-time power of the tie lines; determining a target change value for the output power of each EV cluster based on the target change value of the total output power of the multiple EV clusters, the total battery capacity of the EV clusters, and the output power of the EV clusters; determining a target value for the output power of each EV cluster based on the target change value of the output power of each EV cluster and the state of charge (SOC) of each EV; and calculating the mitigated actual power of the tie lines based on the target values ​​of the output power of each EV cluster. This invention comprehensively considers information such as the state of charge of EV batteries and the output power of EVs, optimizing user charging and discharging behavior while ensuring the energy and travel needs of EV users. Attached Figure Description

[0068] Figure 1 This is a flowchart of a tie-line power fluctuation mitigation method based on electric vehicles according to the present invention.

[0069] Figure 2 This is a schematic diagram illustrating the specific process of the electric vehicle-based tie-line power fluctuation mitigation method of the present invention. Detailed Implementation

[0070] To leverage the mobile energy storage capabilities of electric vehicles and provide ancillary services to the power grid, thereby mitigating tie-line power fluctuations, this invention proposes a tie-line power fluctuation mitigation method based on electric vehicles. This method comprehensively considers information such as the state of charge of the electric vehicle battery and the output power of the electric vehicle to provide a tie-line power fluctuation mitigation method for the power grid.

[0071] Example 1:

[0072] A tie-line power fluctuation mitigation method based on electric vehicles, such as Figure 1 As shown, it includes:

[0073] Step S1: Determine the target change value of the total output power of multiple electric vehicle clusters based on the real-time volatility and real-time power of the tie line;

[0074] Step S2: Based on the target change value of the total output power of the multiple electric vehicle clusters, the total battery capacity of the electric vehicle clusters, and the output power of the electric vehicle clusters, determine the target change value of the output power of each electric vehicle cluster.

[0075] Step S3: Based on the target change value of the output power of each electric vehicle cluster and the SOC state of each electric vehicle, determine the target value of the output power of each electric vehicle in each electric vehicle cluster;

[0076] Step S4: Calculate the smoothed actual power of the tie line based on the target value of the output power of each electric vehicle in each cluster.

[0077] The following is combined Figure 2 The present invention further describes a tie-line power fluctuation mitigation method based on electric vehicles.

[0078] The steps preceding step S1 also include:

[0079] The objective of this strategy is to ensure that the tie-line power fluctuation does not exceed a set threshold within time period T. This fluctuation threshold is an adjustable value, which can be adjusted based on factors such as generator ramp-up rates and grid connection requirements in the actual power grid.

[0080]

[0081]

[0082] Among them, br T P represents the volatility of the tie-line power. DE,rated The rated power of the connecting line; Maximum power of the tie line; Minimum power of the tie line; The set volatility adjustment rate threshold.

[0083]

[0084] P D (t)=P DE (t)-P E (t)

[0085] T = n T ·Δt

[0086] Among them, P E (t) represents the total output power of multiple electric vehicle clusters; P D (t) represents the difference between the real-time power of the tie line and the total output power of the multiple electric vehicle clusters; P represents the output power of the k-th electric vehicle cluster. DE (t) represents the real-time power of the tie line; M represents the total number of electric vehicle clusters; Δt represents the time interval; n T This represents the number of time intervals within time period T.

[0087] In volatility br T Based on this, the real-time volatility br(t) of the tie-line power and the upper limit of the real-time volatility br are defined simultaneously. max Lower bound of real-time volatility min :

[0088]

[0089]

[0090] In the formula, P DE (t-Δt) represents the real-time power of the tie line at time t-Δt.

[0091] To mitigate the impact of tie-line power fluctuations on the power grid by leveraging the energy storage capacity of electric vehicle clusters, constraints need to be considered, including upper and lower limits on electric vehicle output power and electric vehicle state of charge (SOC) constraints. The implementation process of this smoothing control strategy is as follows:

[0092] Step S1: Determine the target change value of the total output power of multiple electric vehicle clusters based on the real-time volatility and real-time power of the tie line. Specific steps include:

[0093] Determine the target change value of the total output power of multiple electric vehicle clusters.

[0094] Step 1.1: Calculate the target value for tie-line power suppression In this step, two different methods, Method 1 and Method 2, are proposed to calculate the tie-line power suppression target value.

[0095] Method 1:

[0096] (a) If the real-time volatility br(t) of the connection line is less than the lower limit of the real-time volatility br min That is, br(t) < br min Then we have:

[0097] P DE* (t)=P DE (t-Δt)+br min ·P DE,rated

[0098] In the formula, To suppress the target value of tie line power; P DE (t-Δt) represents the real-time power of the tie line at time t-Δt; min P represents the lower bound of real-time volatility. DE,rated This refers to the rated power of the connecting line.

[0099] (b) If the real-time volatility br(t) of the connection line is at the lower bound of the real-time volatility br min and upper limit value br max Between, i.e., br min ≤br(t)≤br max Then we have:

[0100] PDE* (t)=P DE (t)

[0101] In the formula, P DE (t) represents the real-time power of the tie line.

[0102] (c) If the real-time volatility br(t) of the connection line is greater than the upper limit of real-time volatility br max That is, br(t) > br max Then we have:

[0103] P DE* (t)=P DE (t-Δt)+br max ·P DE,rated

[0104] In the formula, br max The upper limit of real-time volatility.

[0105] Method 2:

[0106] Because the cost of discharging electric vehicles is high, the discharge process of electric vehicles should be minimized during control. A parameter-based approach is proposed. This indicates the magnitude of the discharge power of each electric vehicle cluster. Therefore, the corrected tie-line power P DE '(t) is shown in the following formula. In this method, the target value for power suppression of the tie line is calculated. When, P is needed DE '(t) replaces P DE (t) is used to perform the calculations of processes (a) to (c) in Method 1.

[0107]

[0108] in, Discharge power for each electric vehicle cluster; Let k be the set of indices of electric vehicles in the discharge state, satisfying For electric vehicle clusters k; P k,j (t) represents the discharge power of the j-th electric vehicle in the electric vehicle cluster k.

[0109]

[0110] Among them, P DE (t) represents the real-time power of the tie line; P DE '(t) represents the corrected tie-line power; Discharge power for each electric vehicle cluster.

[0111] Step 1.2: Determine the target change value ΔP of the total output power of multiple electric vehicle clusters.E* (t)

[0112] In obtaining P DE* Based on (t), ΔP E* The expression for (t) is shown below:

[0113] ΔP E* (t)=P DE* (t)-P DE (t)

[0114] Wherein, ΔP E* (t) represents the target change in the total output power of multiple electric vehicle clusters; To suppress the target value of tie line power; P DE (t) represents the real-time power of the tie line.

[0115] Step S2: Based on the target change value of the total output power of the multiple electric vehicle clusters, the total battery capacity of the electric vehicle clusters, and the output power of the electric vehicle clusters, determine the target change value of the output power of each electric vehicle cluster. Specific steps include:

[0116] Determine the target change value of the output power of each electric vehicle cluster. (Discharging is positive, charging is negative).

[0117] To obtain the target change value ΔP of the total output power of multiple electric vehicle clusters E* Based on (t), and taking into account the differences in energy storage capacity among different electric vehicle clusters, the target change value of the output power of each electric vehicle cluster is determined using the following processes (a) to (d).

[0118] (a) If That is, it is necessary to leverage the discharge capacity of the electric vehicle cluster to provide a sufficient target power for the cluster with a large energy storage capacity, which leads to:

[0119]

[0120] st

[0121]

[0122] in, The target change value for the total output power of multiple electric vehicle clusters; The maximum output power of the k-th electric vehicle cluster; Let be the total battery capacity of the k-th electric vehicle cluster; Let SOC be the battery SOC of the k-th electric vehicle cluster; The target change value for the output power of each electric vehicle cluster; Let M be the output power of the k-th electric vehicle cluster, M be the total number of electric vehicle clusters, and k be the cluster number.

[0123] (b) If That is, it is necessary to leverage the charging capacity of the electric vehicle cluster to provide a larger target power for the cluster with smaller energy storage capacity, which leads to:

[0124]

[0125] st

[0126]

[0127] in, Let be the minimum output power of the k-th electric vehicle cluster; Let SOC be the battery SOC of the k-th electric vehicle cluster; Let ΔP be the total battery capacity of the k-th electric vehicle cluster; E* (t) represents the target change in the total output power of multiple electric vehicle clusters; Target change values ​​for the output power of each electric vehicle cluster.

[0128] (c) If If the cluster can only respond to a portion of the target power, then:

[0129]

[0130] Wherein, ΔP E* (t) represents the target change in the total output power of multiple electric vehicle clusters; The maximum output power of the k-th electric vehicle cluster; Target variation values ​​of output power for each electric vehicle cluster; Let be the output power of the k-th electric vehicle cluster.

[0131] (d) If If the cluster can only respond to a portion of the target power, then:

[0132]

[0133] in, Let be the minimum output power of the k-th electric vehicle cluster; Let M be the output power of the k-th electric vehicle cluster, M be the total number of electric vehicle clusters, and k be the cluster number.

[0134] In processes (c) and (d) above, the electric vehicle cluster cannot achieve the target output power requirement, that is, it cannot completely suppress power fluctuations. The unsuppressed portion needs to be provided by other energy storage batteries or adjustable resources.

[0135] Step S3: Based on the target change value of the output power of each electric vehicle cluster and the SOC state of each electric vehicle, determine the target value of the output power of each electric vehicle in each electric vehicle cluster. The specific steps include:

[0136] Considering the SOC state of each electric vehicle, determine the target value of the output power of each electric vehicle in each cluster.

[0137] Based on the target change value of the output power of each electric vehicle cluster obtained in step S2 Considering the SOC state and capacity constraints of each electric vehicle, determine the target value of the output power of each electric vehicle.

[0138] (a) If Since electric vehicles need to discharge, and electric vehicles with higher SOC provide more target power, then:

[0139]

[0140] in, P represents the target output power of the j-th electric vehicle in the k-th electric vehicle cluster. k,j (t) represents the real-time power of the j-th electric vehicle in the k-th electric vehicle cluster; S k,j (t) represents the real-time SOC of the j-th electric vehicle in the k-th electric vehicle cluster; Let SOC be the lower limit of the j-th electric vehicle in the k-th electric vehicle cluster during discharge. Let be the number of electric vehicles in the k-th electric vehicle cluster; The target change value for output power for each electric vehicle cluster.

[0141] (b) If Since electric vehicles need to be charged, and electric vehicles with lower SOC provide more target power, then:

[0142]

[0143] in, The upper limit of SOC when charging the j-th electric vehicle in the k-th electric vehicle cluster.

[0144] Step S4: Calculate the smoothed actual power of the tie line based on the target output power of each electric vehicle in each cluster. Specific steps include:

[0145] Correction using upper and lower limits of output power constraints for each electric vehicle

[0146] Step S3 is in obtaining During the process, the upper and lower limits of the output power of each electric vehicle were not considered. Therefore, it is necessary to modify the data obtained in step S3. Corrections are made. For an electric vehicle cluster k, if the output power of the electric vehicles in the cluster violates its upper and lower bound constraints, i.e., satisfies... or The set of electric vehicle subscripts is then defined as The complement of this set is defined as Then it satisfies as well as in, Let k be the kth electric vehicle cluster.

[0147] (1) If it exists Then there is a correction for:

[0148]

[0149]

[0150]

[0151] in, For set The total output power that needs to be corrected for all electric vehicles in the system; for The corrected value; Let j be the target value of the output power of the j-th electric vehicle in the k-th electric vehicle cluster. This represents the maximum output power of the electric vehicles in the cluster. S represents the lower limit of the State of Charge (SOC) when the j-th electric vehicle in the k-th electric vehicle cluster is discharging; k,j (t) represents the real-time SOC of the j-th electric vehicle in the k-th electric vehicle cluster; The set consisting of subscripts for electric vehicles.

[0152] (2) If it exists Then there is a correction

[0153]

[0154]

[0155]

[0156] in, This represents the maximum output power of the electric vehicles in the cluster. The upper limit of SOC when charging the j-th electric vehicle in the k-th electric vehicle cluster.

[0157] Recalculate the set if If it is still not an empty set, then repeat step 4 until the result is obtained. Until it becomes an empty set.

[0158] Based on the results obtained in steps S1 to S4 Calculate the total output power P of multiple electric vehicle clusters after smoothing. E,r (t); Based on this, calculate the smoothed tie-line power:

[0159]

[0160] P DE,r (t)=P D (t)+P E,r (t)

[0161] In the formula, P E,r (t) represents the total output power of the multiple electric vehicle clusters after smoothing; P DE,r (t) represents the actual power of the tie line after smoothing, P D (t) represents the difference between the real-time power of the tie line and . Let J be the target value of the output power of the j-th electric vehicle in the k-th electric vehicle cluster. M represents the number of electric vehicles in the k-th electric vehicle cluster; M represents the total number of electric vehicle clusters; and k represents the cluster number.

[0162] Compared with current tie-line power fluctuation mitigation methods, the tie-line power fluctuation mitigation method based on electric vehicles proposed in this invention can fully utilize the energy storage characteristics of electric vehicles and take into account the SOC and power constraints of electric vehicles, thereby improving the feasibility of the fluctuation mitigation method while ensuring the needs of electric vehicle users.

[0163] Example 2:

[0164] Based on the same inventive concept, the present invention also provides a tie-line power fluctuation mitigation system for electric vehicles, comprising:

[0165] Global control module: Determines the target change value of the total output power of multiple electric vehicle clusters based on the real-time volatility and real-time power of the tie line;

[0166] Local control module: used to determine the target change value of the output power of each electric vehicle cluster based on the target change value of the total output power of the multiple electric vehicle clusters, the total battery capacity of the electric vehicle clusters, and the output power of the electric vehicle clusters;

[0167] The individual control module is used to determine the target value of the output power of each electric vehicle in each electric vehicle cluster based on the target change value of the output power of each electric vehicle cluster and the SOC state of each electric vehicle.

[0168] The terminal control module calculates the smoothed actual power of the tie line based on the target value of the output power of each electric vehicle in each cluster.

[0169] Optional, the local control module includes

[0170] The power mitigation target calculation submodule is used to determine the power mitigation target value of the tie line based on the real-time volatility of the tie line and its upper and lower limits; or to determine the power mitigation target value of the tie line based on the discharge power of electric vehicles in the electric vehicle cluster.

[0171] The total target calculation submodule is used to obtain the target change value of the total output power of the electric vehicle cluster by subtracting the real-time power of the tie line from the tie line power suppression target value. Optionally, the suppression target calculation submodule is specifically used to: determine the tie line power suppression target value by using the tie line real-time power, the lower limit of real-time fluctuation power, and the rated power of the tie line at the previous moment when the real-time fluctuation rate of the tie line is less than the lower limit of the real-time fluctuation rate.

[0172] When the real-time volatility of the tie line is less than the lower limit and upper limit of the real-time volatility, the real-time power of the tie line is used as the tie line power smoothing target value.

[0173] When the real-time volatility of the tie line is greater than the upper limit of the real-time volatility, the tie line power suppression target value is determined by the tie line real-time power, the upper limit of the real-time volatility power, and the rated power of the tie line at the previous moment.

[0174] Alternatively, the total discharge power of the electric vehicle cluster can be obtained by summing the discharge power of the electric vehicles in the cluster; the difference between the real-time power of the tie line and the total discharge power of the electric vehicle cluster can be used as the tie line power stabilization target value.

[0175] Optionally, the local control module is specifically used for:

[0176] When the target change value of the total output power of the multiple electric vehicle clusters is greater than zero and less than the difference between the maximum output power and the output power of the electric vehicle cluster, the first objective function is constructed by providing more target power for the cluster with larger energy storage capacity, and the target change value of the output power of each electric vehicle cluster is determined by combining the target change value constraint of the electric vehicle output power.

[0177] When the target change value of the total output power of the multiple electric vehicle clusters is less than zero and greater than the difference between the minimum output power and the output power of the electric vehicle cluster, a second objective function is constructed with the cluster with the smallest energy storage capacity providing more target power. The target change value of the output power of each electric vehicle cluster is determined by combining the target change value constraint of the electric vehicle output power.

[0178] When the target change value of the total output power of the multiple electric vehicle clusters is greater than the difference between the maximum output power of the electric vehicle cluster and the output power of the electric vehicle cluster, the difference between the maximum output power of the electric vehicle cluster and the output power of the electric vehicle cluster shall be used as the target change value of the output power of each electric vehicle cluster.

[0179] When the target change value of the total output power of the multiple electric vehicle clusters is less than the difference between the maximum output power of the electric vehicle cluster and the output power of the electric vehicle cluster, the difference between the maximum output power of the electric vehicle cluster and the output power of the electric vehicle cluster shall be used as the target change value of the output power of each electric vehicle cluster.

[0180] Optional, individual control module, specifically used for:

[0181] When the target change value of the output power of each electric vehicle cluster is greater than zero, the target value of the output power of each electric vehicle in the electric vehicle cluster is obtained based on the target change value of the output power of each electric vehicle cluster, the real-time power of the electric vehicles in the electric vehicle cluster, the SOC, the lower limit of SOC during discharge, and the discharge formula.

[0182] When the target change value of the output power of each electric vehicle cluster is less than zero, the target value of the output power of each electric vehicle in the electric vehicle cluster is obtained by combining the target change value of the output power of each electric vehicle cluster, the real-time power of the electric vehicles in the electric vehicle cluster, the SOC, the lower limit of SOC during discharge, and the charging formula.

[0183] Optionally, the discharge formula is as follows:

[0184]

[0185] In the formula, P represents the target output power of the j-th electric vehicle in the k-th electric vehicle cluster. k,j (t) represents the real-time power of the j-th electric vehicle in the k-th electric vehicle cluster; S k,j (t) represents the real-time SOC of the j-th electric vehicle in the k-th electric vehicle cluster; Let SOC be the lower limit of the j-th electric vehicle in the k-th electric vehicle cluster during discharge. Let be the number of electric vehicles in the k-th electric vehicle cluster; The target change value for the output power of the electric vehicle cluster.

[0186] Optionally, the charging formula is as follows:

[0187]

[0188] In the formula, P represents the target output power of the j-th electric vehicle in the k-th electric vehicle cluster. k,j (t) represents the real-time power of the j-th electric vehicle in the k-th electric vehicle cluster; S k,j (t) represents the real-time SOC of the j-th electric vehicle in the k-th electric vehicle cluster; The upper limit of SOC when charging the j-th electric vehicle in the k-th electric vehicle cluster; The target change value for the output power of the electric vehicle cluster.

[0189] The present invention can also achieve power fluctuation smoothing of tie lines in the following ways, the details of which are as follows:

[0190] Global control layer: Collects tie-line power, receives response capability parameters of each electric vehicle cluster, generates scheduling control signals based on tie-line power fluctuations and response capability parameters of each electric vehicle cluster, and sends scheduling control signals to the local control layer.

[0191] The local control layer is used to collect the output power and SOC of each electric vehicle in the corresponding electric vehicle cluster, and evaluate the response capability parameters of the corresponding electric vehicle cluster in real time based on the energy consumption and travel offline data of electric vehicles, and then upload them to the global control layer; at the same time, it receives scheduling control signals, calculates the target output power of each electric vehicle based on the SOC state constraints and output power constraints of electric vehicles, and sends the corresponding control signals to the terminal control layer.

[0192] The terminal control layer adjusts the output power of the electric vehicle in real time according to the corresponding control signals.

[0193] Furthermore, the global control layer is specifically used to: collect real-time tie-line power and response capability parameters of each electric vehicle cluster, and send scheduling control signals to the local control layer based on tie-line power fluctuations and the response capability of each electric vehicle cluster.

[0194] Furthermore, the local control layer includes multiple electric vehicle cluster control centers. Each electric vehicle cluster control center can collect the output power and SOC of each individual electric vehicle within its corresponding electric vehicle cluster in real time. It can also evaluate the response capability parameters of the corresponding electric vehicle cluster in real time based on offline data such as electric vehicle energy consumption and travel, and then upload them to the global control layer. At the same time, the electric vehicle cluster control center can receive scheduling control signals from the upper layer, consider the electric vehicle SOC state constraints and output power constraints, calculate the target output power of each electric vehicle, and send the corresponding control signals to the lower layer.

[0195] Furthermore, the terminal control layer is specifically used to: adjust the output power of electric vehicles in real time according to the control signals of the local control layer; before electric vehicles are connected, a charging plan needs to be formulated on the terminal device, and the plan will be uploaded to the local control layer to ensure that the charging needs of electric vehicle users are met.

[0196] In practice, the tie-line power fluctuation smoothing process can be divided into three layers. The top layer is the global control layer, which is crucial for power smoothing. It can collect tie-line power and the response capability parameters of each electric vehicle cluster in real time, and send scheduling control signals to the lower layers based on tie-line power fluctuations and the response capability of each electric vehicle cluster. The middle layer is the local control layer, which contains multiple electric vehicle cluster control centers. Each electric vehicle cluster control center can collect the output power and SOC of each electric vehicle in its corresponding electric vehicle cluster in real time, and can evaluate the response capability parameters of the corresponding electric vehicle cluster in real time based on offline data such as electric vehicle energy consumption and travel, and then upload them to the global control layer. At the same time, the electric vehicle cluster control center can receive scheduling control signals from the upper layer, consider the electric vehicle SOC state constraints and output power constraints, calculate the target output power of each electric vehicle, and send corresponding control signals to the lower layers. The bottom layer is the terminal control layer. The terminal devices at this layer can adjust the output power of electric vehicles in real time according to the control signals from the upper layer. Before electric vehicles connect, they need to formulate a charging plan on the terminal device, and this plan will be uploaded to the local control layer to ensure that the charging needs of electric vehicle users are met.

[0197] Tie lines are used to connect load areas to the power grid. Load areas include conventional loads, EV loads, and distributed renewable energy sources. Power fluctuations in tie lines directly affect the stable operation of the power grid.

[0198] Example 3:

[0199] Based on the same inventive concept, this invention also provides a computer device, which includes a processor and a memory. The memory stores a computer program, which includes program instructions. The processor executes the program instructions stored in the computer storage medium. The processor may be a Central Processing Unit (CPU), or other general-purpose processors, digital signal processors (DSPs), application-specific integrated circuits (ASICs), field-programmable gate arrays (FPGAs), or other programmable logic devices, discrete gate or transistor logic devices, discrete hardware components, etc. It is the computing and control core of the terminal, and is suitable for implementing one or more instructions. Specifically, it is suitable for loading and executing one or more instructions from the computer storage medium to implement corresponding method flows or corresponding functions, thereby realizing the steps of the above-described method for smoothing power fluctuations in electric vehicle tie lines.

[0200] Example 4:

[0201] Based on the same inventive concept, this invention also provides a storage medium, specifically a computer-readable storage medium (Memory), which is a memory device in a computer device used to store programs and data. It is understood that the computer-readable storage medium here can include both the built-in storage medium in the computer device and extended storage media supported by the computer device. The computer-readable storage medium provides storage space that stores the terminal's operating system. Furthermore, this storage space also stores one or more instructions suitable for loading and execution by a processor. These instructions can be one or more computer programs (including program code). It should be noted that the computer-readable storage medium here can be high-speed RAM or non-volatile memory, such as at least one disk storage device. The processor can load and execute one or more instructions stored in the computer-readable storage medium to implement the steps of the tie-line power fluctuation smoothing method for electric vehicles in the above embodiments.

[0202] Those skilled in the art will understand that embodiments of the present invention can be provided as methods, systems, or computer program products. Therefore, the present invention can take the form of a completely hardware embodiment, a completely software embodiment, or an embodiment combining software and hardware aspects. Furthermore, the present invention can take the form of a computer program product embodied on one or more computer-usable storage media (including, but not limited to, disk storage, CD-ROM, optical storage, etc.) containing computer-usable program code.

[0203] This invention is described with reference to flowchart illustrations and / or block diagrams of methods, apparatus (systems), and computer program products according to embodiments of the invention. It will be understood that each block of the flowchart illustrations and / or block diagrams, and combinations of blocks in the flowchart illustrations and / or block diagrams, can be implemented by computer program instructions. These computer program instructions can be provided to a processor of a general-purpose computer, special-purpose computer, embedded processor, or other programmable data processing apparatus to produce a machine, such that the instructions, which execute via the processor of the computer or other programmable data processing apparatus, generate instructions for implementing the flowchart illustrations and / or block diagrams. Figure 1 One or more processes and / or boxes Figure 1 A device that provides the functions specified in one or more boxes.

[0204] These computer program instructions may also be stored in a computer-readable storage medium that can direct a computer or other programmable data processing device to function in a particular manner, such that the instructions stored in the computer-readable storage medium produce an article of manufacture including instruction means, which are implemented in a process Figure 1 One or more processes and / or boxes Figure 1 The function specified in one or more boxes.

[0205] These computer program instructions may also be loaded onto a computer or other programmable data processing equipment to cause a series of operational steps to be performed on the computer or other programmable equipment to produce a computer-implemented process, thereby providing instructions that execute on the computer or other programmable equipment for implementing the process. Figure 1 One or more processes and / or boxes Figure 1 The steps of the function specified in one or more boxes.

[0206] The above are merely embodiments of the present invention and are not intended to limit the present invention. Any modifications, equivalent substitutions, improvements, etc., made within the spirit and principles of the present invention are included within the scope of the claims of the present invention pending approval.

Claims

1. A tie-line power fluctuation mitigation method based on electric vehicles, characterized in that, include: The target change value of the total output power of multiple electric vehicle clusters is determined based on the real-time volatility and real-time power of the tie line. Based on the target change value of the total output power of the multiple electric vehicle clusters, the total battery capacity of the electric vehicle clusters, and the output power of the electric vehicle clusters, the target change value of the output power of each electric vehicle cluster is determined. Based on the target change value of the output power of each electric vehicle cluster and the SOC state of each electric vehicle, the target value of the output power of each electric vehicle in each electric vehicle cluster is determined. Calculate the smoothed actual power of the tie line based on the target value of the output power of each electric vehicle in each cluster. The determination of the target output power of each electric vehicle in each electric vehicle cluster based on the target change value of the output power of each electric vehicle cluster and the SOC state of each electric vehicle includes: When the target change value of the output power of each electric vehicle cluster is greater than zero, the target value of the output power of each electric vehicle in the electric vehicle cluster is obtained based on the target change value of the output power of each electric vehicle cluster, the real-time power of the electric vehicles in the electric vehicle cluster, the SOC, the lower limit of SOC during discharge, and the discharge formula. When the target change value of the output power of each electric vehicle cluster is less than zero, the target value of the output power of each electric vehicle cluster is obtained by combining the target change value of the output power of each electric vehicle cluster, the real-time power of the electric vehicles in the electric vehicle cluster, the SOC, the lower limit of the SOC during discharge, and the charging formula. The discharge formula is shown below: In the formula, Let J be the target value of the output power of the j-th electric vehicle in the k-th electric vehicle cluster. Let be the real-time power of the j-th electric vehicle in the k-th electric vehicle cluster; Let SOC be the real-time SOC of the j-th electric vehicle in the k-th electric vehicle cluster; Let SOC be the lower limit of the j-th electric vehicle in the k-th electric vehicle cluster during discharge. Let be the number of electric vehicles in the k-th electric vehicle cluster; The target change value for the output power of the electric vehicle cluster.

2. The method as described in claim 1, characterized in that, The determination of the target change value of the total output power of multiple electric vehicle clusters based on the real-time volatility and real-time power of the tie line includes: The tie-line power mitigation target value is determined based on the tie-line real-time volatility and its upper and lower limits. Alternatively, the target value for tie-line power suppression can be determined based on the discharge power of electric vehicles in the electric vehicle cluster; The target change value of the total output power of the electric vehicle cluster is obtained by subtracting the real-time power of the tie line from the target value of the tie line power suppression.

3. The method as described in claim 2, characterized in that, The determination of the tie-line power mitigation target value based on the tie-line real-time volatility and its upper and lower limits includes: When the real-time volatility of the tie line is less than the lower limit of the real-time volatility, the tie line power stabilization target value is determined by the tie line real-time power, the lower limit of the real-time volatility power, and the rated power of the tie line at the previous moment. When the real-time volatility of the tie line is less than the lower limit and upper limit of the real-time volatility, the real-time power of the tie line is used as the tie line power smoothing target value. When the real-time volatility of the tie line exceeds the upper limit of the real-time volatility, the tie line power stabilization target value is determined by the tie line real-time power, the upper limit of the real-time volatility power, and the tie line rated power at the previous moment.

4. The method as described in claim 3, characterized in that, The target value for power suppression of the tie line is calculated using the following formula: In the formula, To suppress the target value of tie line power; For the connecting line in Real-time power at that time; This represents the lower limit of real-time volatility. This refers to the rated power of the connecting line.

5. The method as described in claim 2, characterized in that, The determination of the tie-line power smoothing target value based on the discharge power of electric vehicles in the electric vehicle cluster includes: The total discharge power of the electric vehicle cluster is the sum of the discharge power of the electric vehicles in the cluster. The difference is obtained by subtracting the total discharge power of the electric vehicle cluster from the real-time power of the tie line, and the difference is used as the tie line power stabilization target value.

6. The method as described in claim 1, characterized in that, The determination of the target change value of the output power of each electric vehicle cluster based on the target change value of the total output power of the multiple electric vehicle clusters, the total battery capacity of the electric vehicle clusters, and the output power of the electric vehicle clusters includes: When the target change value of the total output power of the multiple electric vehicle clusters is greater than zero and less than the difference between the maximum output power and the output power of the electric vehicle cluster, the first objective function is constructed by providing more target power for the electric vehicle cluster with larger energy storage capacity, and the target change value of the output power of each electric vehicle cluster is determined by combining the target change value constraint of the electric vehicle output power. When the target change value of the total output power of the multiple electric vehicle clusters is less than zero and greater than the difference between the minimum output power and the output power of the electric vehicle cluster, a second objective function is constructed with the cluster with the smallest energy storage capacity providing more target power. The target change value of the output power of each electric vehicle cluster is determined by combining the target change value constraint of the electric vehicle output power. When the target change value of the total output power of the multiple electric vehicle clusters is greater than the difference between the maximum output power of the electric vehicle cluster and the output power of the electric vehicle cluster, the difference between the maximum output power of the electric vehicle cluster and the output power of the electric vehicle cluster shall be used as the target change value of the output power of each electric vehicle cluster. When the target change value of the total output power of the multiple electric vehicle clusters is less than the difference between the maximum output power of the electric vehicle cluster and the output power of the electric vehicle cluster, the difference between the maximum output power of the electric vehicle cluster and the output power of the electric vehicle cluster shall be used as the target change value of the output power of each electric vehicle cluster.

7. The method as described in claim 1, characterized in that, The charging formula is shown below: In the formula, Let J be the target value of the output power of the j-th electric vehicle in the k-th electric vehicle cluster. Let be the real-time power of the j-th electric vehicle in the k-th electric vehicle cluster; Let SOC be the real-time SOC of the j-th electric vehicle in the k-th electric vehicle cluster; The upper limit of SOC (State of Charge) when charging the j-th electric vehicle in the k-th electric vehicle cluster; Let be the number of electric vehicles in the k-th electric vehicle cluster; The target change value for the output power of the electric vehicle cluster.

8. A system for implementing the electric vehicle-based tie-line power fluctuation smoothing method as described in any one of claims 1-7, characterized in that, include: Global control module: Determines the target change value of the total output power of multiple electric vehicle clusters based on the real-time volatility and real-time power of the tie line; Local control module: used to determine the target change value of the output power of the electric vehicle cluster based on the target change value of the total output power of the multiple electric vehicle clusters, the total battery capacity of the electric vehicle clusters, and the output power of the electric vehicle clusters; The individual control module is used to determine the target value of the output power of each electric vehicle in each electric vehicle cluster based on the target change value of the output power of each electric vehicle cluster and the SOC state of each electric vehicle. The terminal control module calculates the smoothed actual power of the tie line based on the target value of the output power of each electric vehicle in each cluster.

9. The system as described in claim 8, characterized in that, The global control module includes: The power mitigation target calculation submodule is used to determine the power mitigation target value of the tie line based on the real-time volatility of the tie line and its upper and lower limits; or to determine the power mitigation target value of the tie line based on the discharge power of electric vehicles in the electric vehicle cluster. The total target calculation submodule is used to obtain the target change value of the total output power of the electric vehicle cluster by subtracting the real-time power of the tie line from the target value of the tie line power smoothing.

10. The system as described in claim 9, characterized in that, The specific function of the smoothing target calculation submodule is to: when the real-time volatility of the tie line is less than the lower limit of the real-time volatility, determine the tie line power smoothing target value based on the tie line real-time power, the lower limit of the real-time volatility power, and the rated power of the tie line at the previous moment. When the real-time volatility of the tie line is less than the lower limit and upper limit of the real-time volatility, the real-time power of the tie line is used as the tie line power smoothing target value. When the real-time volatility of the tie line is greater than the upper limit of the real-time volatility, the tie line power suppression target value is determined by the tie line real-time power, the upper limit of the real-time volatility power, and the rated power of the tie line at the previous moment. Alternatively, the total discharge power of the electric vehicle cluster can be obtained by summing the discharge power of the electric vehicles in the cluster; the difference between the real-time power of the tie line and the total discharge power of the electric vehicle cluster can be used as the tie line power stabilization target value.

11. The system as described in claim 8, characterized in that, The local control module is specifically used for: When the target change value of the total output power of the multiple electric vehicle clusters is greater than zero and less than the difference between the maximum output power and the output power of the electric vehicle cluster, the first objective function is constructed by providing more target power for the cluster with larger energy storage capacity, and the target change value of the output power of each electric vehicle cluster is determined by combining the target change value constraint of the electric vehicle output power. When the target change value of the total output power of the multiple electric vehicle clusters is less than zero and greater than the difference between the minimum output power and the output power of the electric vehicle cluster, a second objective function is constructed with the cluster with the smallest energy storage capacity providing more target power. The target change value of the output power of each electric vehicle cluster is determined by combining the target change value constraint of the electric vehicle output power. When the target change value of the total output power of the multiple electric vehicle clusters is greater than the difference between the maximum output power of the electric vehicle cluster and the output power of the electric vehicle cluster, the difference between the maximum output power of the electric vehicle cluster and the output power of the electric vehicle cluster shall be used as the target change value of the output power of each electric vehicle cluster. When the target change value of the total output power of the multiple electric vehicle clusters is less than the difference between the maximum output power of the electric vehicle cluster and the output power of the electric vehicle cluster, the difference between the maximum output power of the electric vehicle cluster and the output power of the electric vehicle cluster shall be used as the target change value of the output power of each electric vehicle cluster.

12. A computer device, characterized in that, include: One or more processors; The processor is used to store one or more programs; When the one or more programs are executed by the one or more processors, a tie-line power fluctuation smoothing method based on electric vehicles as described in any one of claims 1 to 7 is implemented.

13. A computer-readable storage medium, characterized in that, It contains a computer program, which, when executed, implements a tie-line power fluctuation smoothing method based on electric vehicles as described in any one of claims 1 to 7.

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