Cloud processing-based reactive power regulation method and system for electric vehicle charging piles

Abstract

A cloud processing-based reactive power regulation method for electric vehicle charging piles, comprising: acquiring real-time electrical quantities and operation state data by means of a smart meter and charging piles; using historical data and a machine learning algorithm to predict a reactive power regulation range satisfying voltage safety constraints; on the basis of a target power factor or a power grid regulation instruction, establishing a reactive power optimization model, and calculating a reactive power allocation scheme for the charging piles; and issuing an optimization instruction to the charging piles for execution, and dynamically regulating the reactive power allocation scheme. The method can fully utilize the bidirectional reactive power regulation capability of charging piles, reduce equipment investment, and improve energy efficiency, has high efficiency and flexibility, and can adapt to the requirements of future power grids for reactive power regulation. In addition, the present invention also relates to a cloud processing-based reactive power regulation system for electric vehicle charging piles.

Description

A cloud-based reactive power regulation method and system for electric vehicle charging piles Technical Field

[0001] This invention belongs to the field of charging pile technology, and in particular to reactive power regulation technology for electric vehicle charging facilities. Background Technology

[0002] With the widespread application of distributed photovoltaic (PV) power generation and electric vehicle (EV) charging stations, the electricity consumption characteristics on the user side have changed significantly. The integration of distributed PV power generation has led to greater randomness and volatility in the power supply on the user side; simultaneously, EV charging loads are characterized by rapid instantaneous changes and high power demands. These factors result in rapid changes in user-side load and frequent voltage fluctuations, posing a significant challenge to the stable operation of power equipment.

[0003] Traditional voltage and reactive power regulation methods mainly rely on transformer tap adjustment and capacitor switching. However, these solutions typically suffer from slow response times, large size, and high costs, making them unsuitable for scenarios involving the uncertainty of photovoltaic power generation and rapid changes in electric vehicle charging loads. Furthermore, because users generally only have capacitors installed on the user side, they can only provide reactive power but cannot absorb it, thus failing to regulate overvoltages during periods of high photovoltaic power generation or low load in the distribution area.

[0004] In addition, when issuing electricity bills, the power company will adjust the electricity charges for users whose installed capacity exceeds a certain value based on the average power factor during the billing period; this is known as the power factor adjustment fee. If the power factor is lower than the assessment standard, a penalty of the power factor adjustment fee will be charged; otherwise, a portion of the electricity bill will be reduced as a reward for the power factor adjustment fee.

[0005] At the same time, as the power grid's demand for reactive power regulation increases, power users may gradually be required to participate in the power grid's reactive power regulation in the future. By responding to the power grid's reactive power regulation needs, power users can obtain regulation benefits.

[0006] Although electric vehicle charging stations possess bidirectional reactive power regulation potential due to their use of power electronic charging modules, there is currently a lack of effective methods to integrate and utilize these dispersed reactive power resources. Current technological limitations not only restrict the efficiency of grid management but also fail to fully realize the potential of electric vehicle charging facilities in reactive power regulation and voltage quality improvement. Therefore, there is an urgent need for a new reactive power regulation method that can fully integrate and leverage the reactive power regulation capabilities of electric vehicle charging stations to improve reactive power management capabilities on the electricity user side, directly reflecting in electricity cost savings and voltage quality improvements for users. Summary of the Invention

[0007] This invention relates to a cloud-based reactive power regulation method and system for electric vehicle charging piles, which aims to improve the power factor of power users, improve voltage quality, and respond to the reactive power regulation needs of the power grid.

[0008] This invention provides a cloud-based method for reactive power regulation of electric vehicle charging piles, comprising the following steps:

[0009] 1. Data Acquisition: Install smart meters at the power gateway to collect electrical quantities such as power factor, active power, reactive power, and voltage in real time; obtain the operating status and output power data of the charging pile.

[0010] 2. Reactive power regulation range prediction: Using collected historical data, establish a relationship model between active power, reactive power, voltage, voltage change and reactive power regulation to predict the reactive power regulation range that meets voltage safety constraints under the current condition.

[0011] 3. Reactive power optimization calculation: Based on the predicted reactive power adjustment range, combined with the power factor target of the power user or the reactive power adjustment demand of the power grid, the target reactive power is calculated; based on the real-time power and power circle characteristics of the charging pile, the upper and lower limits of reactive power adjustment for each pile are calculated, and the reactive power output of each charging pile is optimized to meet the overall reactive power adjustment target.

[0012] 4. Command Issuance and Execution: The optimized reactive power adjustment command is issued to each charging pile for execution, the execution effect is monitored, and the control strategy is dynamically adjusted based on real-time feedback.

[0013] The present invention also provides a cloud-based reactive power regulation system for electric vehicle charging piles, the system comprising:

[0014] • Data acquisition unit: Deployed at the power gateway port and charging pile, used to collect electrical quantities and operating status data.

[0015] ●Communication Unit: Deployed in the charging pile controller, responsible for data uploading and command reception.

[0016] ●Cloud processing unit: Includes data storage and preprocessing module, reactive power adjustment range prediction module and reactive power optimization module, responsible for data analysis and optimization calculation.

[0017] ●Control command issuing unit: responsible for generating reactive power adjustment commands and issuing them to charging piles for execution, while monitoring the execution results.

[0018] ●User Interface Unit: Provides a visual interface that supports system operation monitoring and parameter configuration.

[0019] Through the above methods and systems, this invention realizes centralized management and optimized utilization of the reactive power regulation capability of electric vehicle charging piles, improves the reactive power management capability of power users, improves voltage quality, reduces electricity costs caused by low power factor, and can respond to the reactive power regulation needs of the power grid, thus having good application prospects.

[0020] Useful Explanation

[0021] This invention utilizes cloud processing technology to uniformly manage the reactive power regulation capabilities of distributed charging piles. Through machine learning and advanced reactive power optimization algorithms, it effectively leverages the application value of electric vehicle charging piles in reactive power regulation. By adjusting reactive power, this invention can significantly improve the power factor of electricity users, enhance voltage quality, and strengthen the overall stability of the power grid. Compared to traditional reactive power compensation devices, this invention fully utilizes the inherent reactive power regulation potential of electric vehicle charging piles, reducing or replacing the need for conventional reactive power compensation equipment, thereby lowering equipment investment costs.

[0022] Furthermore, the cloud-based centralized management and optimization functions provided by this invention make reactive power regulation more flexible and efficient. Users can not only monitor the system's operating status in real time, but also flexibly adjust reactive power regulation strategies according to actual needs to cope with various complex power grid environments. This efficient and intelligent regulation method can not only help electricity users reduce electricity bill penalties caused by low power factor, but also increase the chances of electricity users obtaining reactive power regulation rewards, thereby significantly reducing electricity costs.

[0023] In scenarios where multiple charging stations operate collaboratively, this invention can coordinate the reactive power output of multiple charging stations through a cloud system, achieving overall optimization of the regional power grid. This not only improves the operational efficiency of the regional power grid but also provides an effective means of reactive power regulation, helping to stabilize grid operation and reduce the risk of voltage fluctuations.

[0024] With the increasing demand for reactive power regulation in future power grids, the system of this invention can also interface with the power grid dispatch center to respond to external reactive power regulation commands and provide the power grid with fast and accurate reactive power regulation services. This highly automated and intelligent regulation system will play an important role in the future electricity market, helping power users and grid operators achieve higher operational efficiency.

[0025] In summary, this invention not only significantly improves the reactive power regulation capability of electric vehicle charging stations, but also reduces equipment investment and operating costs through centralized cloud management and optimization, thereby improving the energy utilization efficiency of electricity users and the overall stability of the power grid. This invention has broad application prospects, and is particularly suitable for various power grid environments that require optimization of the power factor and improvement of energy efficiency. Attached Figure Description

[0026] Figure 1 is a flowchart of the reactive power regulation method for electric vehicle charging piles based on cloud processing proposed in this invention.

[0027] Figure 2 is a system architecture diagram of the cloud-based reactive power regulation system for electric vehicle charging piles proposed in this invention.

[0028] Figure 3 is a flowchart of Example 1. Detailed Implementation

[0029] The reactive power regulation method and system for electric vehicle charging piles based on cloud processing of the present invention will be described in detail below with reference to the accompanying drawings and embodiments.

[0030] Example 1: Cloud-based reactive power regulation method

[0031] This embodiment provides a cloud-based method for reactive power regulation of electric vehicle charging piles, with the following specific steps:

[0032] 1. Data Collection

[0033] Install a smart meter at the power gateway to collect the following electrical quantities in real time:

[0034] ○ Active power P: Represents the real-time active power consumption of electricity users.

[0035] ○Reactive power Q: Represents the real-time reactive power consumption of power users.

[0036] ○Voltage V: Real-time voltage value at the power gateway port.

[0037] ○ Power factor PF: Represents the power factor of an electricity user.

[0038] The following data was obtained from various electric vehicle charging stations:

[0039] ○ Operational status: Whether the charging station is in operation, idle, or faulty.

[0040] ○ Output power: The current active and reactive power output of the charging station.

[0041] 2. Reactive power regulation range prediction

[0042] A model relating power grid parameters to reactive power regulation is established using collected historical data. The specific implementation is as follows:

[0043] ○ Data preprocessing: Clean historical data, remove outliers and missing values ​​to ensure data quality.

[0044] ○Feature extraction: Select key features, such as active power P, reactive power Q, voltage V, voltage change ΔV (voltage difference from the previous time point), etc.

[0045] ○ Model Training: The prediction model is trained using machine learning algorithms (such as LightGBM) to establish the relationship between active power, reactive power, voltage, voltage change and reactive power regulation.

[0046] ○ Real-time prediction: Input current real-time data and use a trained model to predict the reactive power regulation range, i.e., the upper and lower limits Q of reactive power, under the condition of satisfying voltage safety constraints. min and Q max .

[0047] According to the set upper voltage limit V max and V min Calculate the voltage difference ΔV respectively. up =V max -V current ΔV down =V current -V min

[0048] The above data is used to construct a feature vector, which is then input into a trained machine learning model to predict the reactive power regulation limit ΔQ that satisfies voltage safety constraints under the current state. up,limit ,ΔQ down,limit Then, based on the current reactive power, calculate the upper and lower limits Q of the reactive power. max =Q current +ΔQ up,limit Q min =Q current -ΔQ down,limit

[0049] 3. Reactive power optimization calculation

[0050] Based on the predicted reactive power regulation range, perform reactive power optimization calculations:

[0051] ○ Determine the target reactive power Q target :

[0052] ■ Power Factor Control Mode: Based on the set power factor target PF target Given the current active power P, calculate the target reactive power: Q target =P×tan(arccos(PF) target ))

[0053] ■ Power Grid Reactive Power Regulation Mode: If a reactive power regulation command is received from the power grid, then Q will be... target Set as the command value.

[0054] ○ Range constraint: Ensure Q target Within the predicted reactive power regulation range: Q min ≤Q target ≤Qmax

[0055] If the value exceeds the range, the corresponding upper and lower limits will be used.

[0056] ○ Establish an optimization model to optimize the allocation of reactive power output for each charging station:

[0057] ■ Objective function: The difference between the total reactive power of the charging pile and the target reactive power should be minimized. Meanwhile, to prevent frequent adjustments due to unstable optimization results, the absolute value Z of the maximum reactive power adjustment is introduced:

[0058] Among them, Q target Q represents the total reactive power target value for the charging pile. i Z represents the reactive power output of the i-th charging pile, and Z is the absolute value of the maximum reactive power adjustment: Z = max(|ΔQ) i |)

[0059] ■Constraints:

[0060] ●Charging station capacity limitations:

[0061] According to the power circle characteristics of AC / DC: Q i,min =-Q i,max

[0062] Q i,min Q i,max These are the lower and upper limits of reactive power for charging piles, respectively. i,max P represents the maximum apparent power of the charging station. i This refers to the real-time power output of the charging station.

[0063] ■ Solution method: The above optimization problem is solved using the SCIP solver to obtain the optimal reactive power output allocation scheme for each charging pile.

[0064] 4. Instruction Issuance and Execution

[0065] ○ Instruction Generation: Based on the optimization calculation results, generate reactive power adjustment instructions, including the charging pile number and the corresponding reactive power setting value.

[0066] ○ Command issuance: Commands are issued to each charging station via the communication unit.

[0067] ○ Execution Monitoring: Monitor the execution status of the charging piles to ensure that instructions are executed correctly.

[0068] 5. Dynamic adjustment

[0069] Based on real-time monitoring results and new collected data, the above steps are repeated cyclically to dynamically adjust the reactive power regulation strategy and adapt to changes in the power grid and load.

[0070] Example 2: Cloud-based reactive power regulation system

[0071] This embodiment provides a cloud-based reactive power regulation system for electric vehicle charging piles, the structure of which is as follows:

[0072] 1. Data Acquisition Unit

[0073] ○ Smart meter at the power grid connection point: Installed at the connection point between the power user and the power grid, it collects electrical parameters in real time.

[0074] ○ Charging pile data acquisition module: Embedded inside the charging pile, it collects the charging pile's operating status and power data.

[0075] 2. Communication Unit

[0076] ○ Deployed on the charging pile controller, it uses wired or wireless communication to transmit data and send and receive commands with the cloud server.

[0077] 3. Cloud processing unit

[0078] ○ Data storage and preprocessing module: Stores historical data and performs data cleaning and preprocessing.

[0079] ○ Reactive power regulation range prediction module: Predicts the reactive power regulation range based on historical and real-time data.

[0080] ○Reactive power optimization module: Performs reactive power optimization calculations and generates the optimal adjustment scheme.

[0081] 4. Control command issuing unit

[0082] ○ Send the reactive power adjustment command calculated in the cloud to each charging pile to control its reactive power output.

[0083] 5. User Interface Unit

[0084] ○Web-based visual interface: Allows users to view system operating status, set power factor targets, monitor voltage quality, etc.

[0085] ○ Parameter configuration interface: Allows users to configure system parameters, such as target power factor value, voltage safety range, etc.

[0086] Example 3: Responding to the reactive power regulation needs of the power grid

[0087] When a reactive power deficit occurs in the power grid, the power grid dispatch center sends reactive power adjustment instructions to power users. Using the system of this invention, power users can respond to the power grid's reactive power adjustment needs. The specific implementation steps are as follows:

[0088] 1. Receive instructions

[0089] The system receives reactive power adjustment instructions from the power grid dispatch center through the communication unit, such as increasing reactive power by 100kVar.

[0090] 2. Adjust the target value

[0091] ○ Q target Set to the current reactive power plus the adjustment amount required by the power grid.

[0092] 3. Reactive power optimization calculation

[0093] ○Refer to the steps in Implementation Example 1 and recalculate the reactive power distribution scheme for each charging pile.

[0094] 4. Implementation and Feedback

[0095] ○ Issue adjustment instructions to the charging pile to adjust the reactive power output.

[0096] ○ Feed back the execution results and current reactive power to the power grid dispatch center.

Claims

1. A method for reactive power regulation of electric vehicle charging piles based on cloud processing, comprising the following steps:

1. Data acquisition steps: Electrical quantities, including power factor, active power, reactive power and voltage, are collected in real time through smart meters. At the same time, the operating status data of each charging pile is collected. The operating status data includes the working status of the charging pile, real-time active power and real-time reactive power. The electrical quantities and the operating status data are uploaded to the cloud processing unit for storage to form historical data.

2. Reactive power regulation range prediction step: Based on the historical data, a relationship model between active power, reactive power, voltage, voltage difference, and reactive power regulation is established using machine learning algorithms. The relationship model includes: Based on the preset upper and lower voltage limits, calculate the voltage difference between the current voltage and the upper and lower limits. The voltage difference, current active power, and current reactive power are input into the relationship model to predict the upper and lower limits of reactive power adjustment that meet voltage safety constraints.

3. Reactive power optimization calculation steps: Based on the user-defined power factor target value or the received power grid reactive power regulation command, determine the target reactive power. Based on the real-time power and maximum apparent power of each charging pile, calculate the upper and lower limits of reactive power regulation for each charging pile. Under the condition of satisfying the reactive power adjustment constraints of each charging pile, the reactive power output allocation scheme of each charging pile is calculated by an optimization algorithm.

4. Instruction execution steps: The reactive power output allocation scheme is converted into a reactive power adjustment command and sent to each charging pile. ο Monitor the operation of charging piles in real time and collect electrical quantities after reactive power adjustment; Based on the monitoring results, determine whether the target requirements are met. If not, return to the reactive power optimization calculation step to recalculate the allocation scheme.

2. The reactive power regulation method for electric vehicle charging piles based on cloud processing according to claim 1, characterized in that: Reactive power regulation range prediction uses machine learning algorithms to model historical data in order to accurately predict the reactive power regulation range under voltage safety constraints.

3. The reactive power regulation method for electric vehicle charging piles based on cloud processing according to claim 1, characterized in that, The objective function is: Among them, Q target Q represents the total reactive power target value for the charging pile. i Z represents the reactive power output of the i-th charging pile, and Z is the absolute value of the maximum reactive power adjustment of the charging pile.

4. A cloud-based reactive power regulation system for electric vehicle charging piles, comprising: 1) Data acquisition unit: used to collect electrical quantities and charging pile operating status data; 2) Communication unit: used for uploading data and receiving instructions; 3) Cloud processing unit: including data storage and preprocessing module, reactive power adjustment range prediction module and reactive power optimization module; 4) Control command issuing unit: used to send reactive power adjustment commands to the charging pile; 5) User interface unit: used to visually display the system's operating status and configuration parameters.

5. The cloud-based reactive power regulation system for electric vehicle charging piles according to claim 4, characterized in that: The cloud processing unit uses machine learning algorithms to predict the reactive power adjustment range and employs mathematical optimization methods to calculate the optimal reactive power allocation scheme.

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