Grid-connected control method of bidirectional energy storage inverter

Abstract

The invention provides a grid-connected control method for a bidirectional energy storage inverter, which is applied to the technical field of energy storage inverters and comprises the following steps: acquiring current and voltage state information of a main power grid and a micro-grid and an external target load demand quantity; compensating an output load or being charged based on the preset micro-grid current threshold value; calculating electric energy loss of alternating current and direct current switching according to the target load; current is obtained based on the power supply sustainability of the micro-grid, and subsequent output power is judged; the technical problems that at present, unnecessary electric energy consumption is generated due to switching between a main power grid and a micro power grid, it is difficult to stabilize the voltage in the process of continuously outputting electric appliances to enable the current to be continuously output, and consequently the stable voltage and a smoother compensation mechanism are needed under the condition of unstable voltage and current are solved.

Description

Technical Field

[0001] The present application relates to the technical field of energy storage inverters, and in particular to a grid-connected control method for a bidirectional energy storage inverter. Background Art

[0002] Energy storage inverter is a device that converts direct current (DC) into alternating current (AC). It is mainly used in energy storage systems. It plays an important role in renewable energy (such as solar and wind) power generation, energy storage battery charging and discharging, and power dispatching.

[0003] The energy storage inverter includes bidirectional conversion current, charge and discharge energy management, grid-connected frequency and phase functions, support for renewable energy, power quality improvement, current and voltage fault protection, and intelligent control algorithms;

[0004] The current energy storage inverter will generate unnecessary energy consumption due to the switching between the main grid and the microgrid during the process of controlling current switching. It is also difficult to stabilize the voltage to ensure continuous current output during the continuous output of electrical appliances. Therefore, under unstable voltage and current conditions, stable voltage and smoother compensation mechanisms are required to achieve stable voltage and current and better match the user's energy-saving needs. Summary of the invention

[0005] The present application aims to solve the technical problem that unnecessary power consumption is generated due to switching between the main power grid and the microgrid, and it is difficult to stabilize the voltage so as to ensure continuous current output during the continuous output of electrical appliances, so that stable voltage and smoother compensation mechanism are required under unstable voltage and current conditions, and provide a grid-connected control method for a bidirectional energy storage inverter.

[0006] This application adopts the following technical means to solve the technical problem: a grid-connected control method for a bidirectional energy storage inverter,

[0007] A grid-connected control method for a bidirectional energy storage inverter, the method comprising:

[0008] Obtain the current and voltage status information of the main grid and microgrid as well as the external target load demand;

[0009] Compensating output load or being charged based on a preset microgrid current threshold;

[0010] Calculating the power loss of switching between AC and DC according to the target load;

[0011] The subsequent output power is determined based on the power supply sustainability of the microgrid by acquiring the current.

[0012] Furthermore, in the step of obtaining the current and voltage status information of the main grid and the microgrid and the external target load demand,

[0013] Obtain the target area data and labels of the user's main power grid;

[0014] Determine the current output frequency of the main power grid according to the target area data and tags;

[0015] The time stability interval of the user's main power grid is determined by training and learning big data models.

[0016] Further, after the step of determining the time stability interval of the user's main power grid by training and learning the big data model,

[0017] The time compensation interval that the microgrid needs to compensate is calculated through the time stability interval of the main power grid.

[0018] Further, in the step of compensating the output load or being charged based on the preset microgrid current threshold,

[0019] Determine the preset microgrid output current;

[0020] If the microgrid output storage energy is lower than a first percentage, the microgrid shuts down the output;

[0021] If the microgrid outputs stored energy higher than the second percentage, the microgrid directly outputs;

[0022] If the microgrid output stored energy is lower than the second percentage and lower than the first percentage, the microgrid compensates the main grid output.

[0023] Further, in the step of shutting down the output of the microgrid when the microgrid output energy storage is lower than the first percentage,

[0024] The microgrid is also charged with energy storage through the main grid via the inverter.

[0025] Furthermore, in the step of calculating the power loss of switching between AC and DC according to the target load,

[0026] Determine the target load and use the formula:

[0027] [P_{\text{load}}=V_{\text{load}}\times I_{\text{load}}\times\text{PF}]

[0028] Where (V_{\text{load}}) is the load voltage, (I_{\text{load}}) is the load current, and PF is the power factor (for AC loads).

[0029] Further, after the step of obtaining current based on the power supply sustainability of the microgrid to determine the subsequent output power,

[0030] Obtain external energy factors and integrate big data content to determine the available time and intensity of the microgrid.

[0031] The present application provides a grid-connected control method for a bidirectional energy storage inverter, which has the following beneficial effects: by obtaining the current and voltage status information of the main grid and the microgrid and the external target load demand; compensating the output load or being charged based on the preset current threshold of the microgrid; calculating the energy loss of switching between AC and DC according to the target load; obtaining the current based on the power sustainability of the microgrid to determine the subsequent output power; and having the ability to solve the current technical problem that unnecessary energy consumption is generated due to switching between the main grid and the microgrid, and it is difficult to stabilize the voltage so that the current is continuously output during the continuous output of electrical appliances, so that under the condition of unstable voltage and current, a stable voltage and a smoother compensation mechanism are required. BRIEF DESCRIPTION OF THE DRAWINGS

[0032] Figure 1 The present invention is a flowchart of an embodiment of a grid-connected control method for a bidirectional energy storage inverter.

[0033] The implementation, functional features and advantages of the present application will be further described in conjunction with embodiments and with reference to the accompanying drawings. DETAILED DESCRIPTION

[0034] It should be understood that the specific embodiments described herein are only used to explain the present application and are not used to limit the present application.

[0035] The following will be combined with the drawings in the embodiments of the present application to clearly and completely describe the technical solutions in the embodiments of the present application. Obviously, the described embodiments are only part of the embodiments of the present application, not all of the embodiments. Based on the embodiments in the present application, all other embodiments obtained by ordinary technicians in this field without creative work are within the scope of protection of this application.

[0036] It should be noted that the terms "include", "comprises" and "have" and any variations thereof in the specification and claims of the present application and the above-mentioned drawings are intended to cover non-exclusive inclusions. For example, a process, method, system, product or device that includes a series of steps or units is not limited to the listed steps or units, but may optionally include steps or units that are not listed, or may optionally include other steps or units that are inherent to these processes, methods, products or devices. In the claims, specification and drawings of the present application, relational terms such as "first" and "second" are merely used to distinguish one entity / operation / object from another entity / operation / object, and do not necessarily require or imply any such actual relationship or order between these entities / operations / objects.

[0037] Reference to "embodiments" herein means that a particular feature, structure, or characteristic described in conjunction with the embodiments may be included in at least one embodiment of the present application. The appearance of the phrase in various locations in the specification does not necessarily refer to the same embodiment, nor is it an independent or alternative embodiment that is mutually exclusive with other embodiments. It is explicitly and implicitly understood by those skilled in the art that the embodiments described herein may be combined with other embodiments.

[0038] Reference Figure 1 , is a flow chart of a grid-connected control method of a bidirectional energy storage inverter in an embodiment of the present application;

[0039] Embodiment 1

[0040] A grid-connected control method for a bidirectional energy storage inverter, the method comprising:

[0041] Obtain the current and voltage status information of the main grid and microgrid as well as the external target load demand;

[0042] Compensating output load or being charged based on a preset microgrid current threshold;

[0043] Calculating the power loss of switching between AC and DC according to the target load;

[0044] The subsequent output power is determined based on the power supply sustainability of the microgrid by acquiring the current.

[0045] In the step of obtaining the current and voltage status information of the main grid and the microgrid and the external target load demand,

[0046] Obtain the target area data and labels of the user's main power grid;

[0047] Determine the current output frequency of the main power grid according to the target area data and tags;

[0048] The time stability interval of the user's main power grid is determined by training and learning big data models.

[0049] Specifically,

[0050] The current, voltage, frequency, load, weather and other data of the main power grid are collected in real time through external devices such as sensors and smart meters. The collected data is pre-processed and cleaned in the cloud or local server, features are extracted from the processed data, and historical data is used to train machine learning models to identify current stability.

[0051] For example, real-time current and voltage waveform data of power grid operation, historical load data, user electricity usage habits, electricity price fluctuation data, energy storage equipment status, and model training data;

[0052] Get the data as follows:

[0053]

[0054]

[0055] Before model training, data needs to be preprocessed, including:

[0056] Missing value handling: filling or deleting missing data;

[0057] Standardization: Standardize the feature data so that it has a distribution with a mean of 0 and a variance of 1;

[0058] Label encoding: converting labels (such as "stable" and "unstable") into digital form (such as 0 and 1);

[0059] Select the support vector machine classification algorithm;

[0060] The following is an example code for model training using Python's scikit-learn library:

[0061] import pandas as pd

[0062] from sklearn.model_selection import train_test_split

[0063] from sklearn.preprocessing import StandardScaler

[0064] from sklearn.svm import SVC

[0065] from sklearn.metrics import classification_report,confusion_matrix

[0066] #Sample data

[0067] data = {

[0068] 'Current':[150,160,155,170,150],

[0069] 'Voltage':[220,220,219,221,220],

[0070] 'Frequency':[50.0,49.5,50.1,49.2,50.0],

[0071] 'Load':[500,600,550,680,500],

[0072] 'Electricity Price':[0.5,0.6,0.55,0.7,0.5],

[0073] 'Energy storage status':[50,48,49,45,50],

[0074] 'label':['stable','unstable','stable','unstable','stable']}

[0075] df = pd.DataFrame(data)

[0076] #Tag encoding

[0077] df['label'] = df['label'].map({'stable': 0, 'unstable': 1})

[0078] #Features and Tags

[0079] X = df.drop('label',axis=1)

[0080] y = df['label']

[0081] #Data segmentation

[0082] X_train,X_test,y_train,y_test=train_test_split(X,y,test_size=0.2,random_state=42)

[0083] #Data Standardization

[0084] scaler = StandardScaler()

[0085] X_train=scaler.fit_transform(X_train)

[0086] X_test=scaler.transform(X_test)

[0087] #SVM model training

[0088] model=SVC(kernel='linear')

[0089] model.fit(X_train,y_train)

[0090] #predict

[0091] y_pred=model.predict(X_test)

[0092] #Evaluate the model

[0093] print(confusion_matrix(y_test,y_pred))

[0094] print(classification_report(y_test,y_pred))

[0095] The vector machine algorithm trained through the above steps builds a model using characteristic data such as current, voltage, frequency, load, and meteorology, which can effectively distinguish the stability and instability of current at what time.

[0096] In this embodiment, after the step of determining the time stability interval of the user's main power grid by training and learning the big data model,

[0097] The time compensation interval that the microgrid needs to compensate is calculated through the time stability interval of the main power grid.

[0098] In the step of compensating the output load or being charged based on the preset microgrid current threshold,

[0099] Determine the preset microgrid output current;

[0100] If the microgrid output storage energy is lower than a first percentage, the microgrid shuts down the output;

[0101] If the microgrid outputs stored energy higher than the second percentage, the microgrid directly outputs;

[0102] If the microgrid output stored energy is lower than the second percentage and lower than the first percentage, the microgrid compensates the main grid output.

[0103] Specifically, it is judged in the energy storage of the microgrid whether the energy storage reaches the value of the first percentage of the region. If it is lower than the first percentage, the microgrid shuts down the output.

[0104] It can be understood that when the microgrid is below 30% of its power, it does not participate in compensating the main grid’s power, nor does it serve as the main output power source;

[0105] Similarly, when the microgrid has more than 80% power reserve, it directly participates and serves as the main output power energy source;

[0106] When the power reserve of the microgrid is between 30% and 80%, it will indirectly participate and serve as an auxiliary output to compensate the main grid's electric energy.

[0107] In this embodiment, when the microgrid output energy storage is lower than the first percentage, the microgrid shuts down the output.

[0108] The microgrid is also charged with energy storage through the main grid via the inverter.

[0109] Specifically, in other situations, when the microgrid cannot be replenished from external energy and the energy is less than 30%, the microgrid can be charged through the main grid so that the microgrid can always maintain a 30% energy storage state;

[0110] In another case, it can be adapted to different environments. For example, at night, when it is impossible to generate electricity through solar energy, the microgrid can be adjusted to store 80% or more energy at night to meet the conditions for the use of small energy storage devices.

[0111] In the step of calculating the power loss of switching between AC and DC according to the target load,

[0112] Determine the target load and use the formula:

[0113] [P_{\text{load}}=V_{\text{load}}\times I_{\text{load}}\times\text{PF}]

[0114] Where (V_{\text{load}}) is the load voltage, (I_{\text{load}}) is the load current, and PF is the power factor (for AC loads).

[0115] After the step of obtaining current based on the power supply sustainability of the microgrid to determine the subsequent output power,

[0116] Obtain external energy factors and integrate big data content to determine the available time and intensity of the microgrid.

[0117] Embodiment 2

[0118] A grid-connected control method for a bidirectional energy storage inverter, the method comprising:

[0119] Obtain the current and voltage status information of the main grid and microgrid as well as the external target load demand;

[0120] Compensating output load or being charged based on a preset microgrid current threshold;

[0121] Calculating the power loss of switching between AC and DC according to the target load;

[0122] The subsequent output power is determined based on the power supply sustainability of the microgrid by acquiring the current.

[0123] In this embodiment, in the step of obtaining the current and voltage status information of the main grid and the microgrid and the external target load demand,

[0124] Obtain the target area data and labels of the user's main power grid;

[0125] Determine the current output frequency of the main power grid according to the target area data and tags;

[0126] The time stability interval of the user's main power grid is determined by training and learning big data models.

[0127] After the step of determining the time stability interval of the user's main power grid by training and learning the big data model,

[0128] The time compensation interval that the microgrid needs to compensate is calculated through the time stability interval of the main power grid.

[0129] In the step of compensating the output load or being charged based on the preset microgrid current threshold,

[0130] Determine the preset microgrid output current;

[0131] If the microgrid output storage energy is lower than a first percentage, the microgrid shuts down the output;

[0132] If the microgrid outputs stored energy higher than the second percentage, the microgrid directly outputs;

[0133] If the microgrid output stored energy is lower than the second percentage and lower than the first percentage, the microgrid compensates the main grid output.

[0134] In this embodiment,

[0135] When it is determined that the electric energy of the microgrid is too low and is lower than the first percentage, the inverter determines that there is no microgrid output, and the main grid is fully used to output the load, and the microgrid is charged by the main grid through the inverter;

[0136] If it is determined that the energy storage is higher than 80% when the microgrid is outputting, the external energy cannot provide continuous and stable energy when the microgrid is collecting energy from the outside world. Therefore, the energy exceeding 80% in the energy storage is used first, and the power supply of the main grid is shut down to make perfect use of clean energy.

[0137] If it is determined that the energy storage during microgrid output is higher than 30% and lower than 80%, the main grid will be compensated for the auxiliary output.

[0138] When the microgrid output energy storage is lower than the first percentage, the microgrid shuts down the output.

[0139] The microgrid is also charged with energy storage through the main grid via the inverter.

[0140] In the step of calculating the power loss of switching between AC and DC according to the target load,

[0141] Determine the target load and use the formula:

[0142] [P_{\text{load}}=V_{\text{load}}\times I_{\text{load}}\times\text{PF}]

[0143] Where (V_{\text{load}}) is the load voltage, (I_{\text{load}}) is the load current, and PF is the power factor (for AC loads).

[0144] After the step of obtaining current based on the power supply sustainability of the microgrid to determine the subsequent output power,

[0145] Obtain external energy factors and integrate big data content to determine the available time and intensity of the microgrid.

[0146] Embodiment 3

[0147] A grid-connected control method for a bidirectional energy storage inverter, the method comprising:

[0148] Obtain the current and voltage status information of the main grid and microgrid as well as the external target load demand;

[0149] Compensating output load or being charged based on a preset microgrid current threshold;

[0150] Calculating the power loss of switching between AC and DC according to the target load;

[0151] The subsequent output power is determined based on the power supply sustainability of the microgrid by acquiring the current.

[0152] In the step of obtaining the current and voltage status information of the main grid and the microgrid and the external target load demand,

[0153] Obtain the target area data and labels of the user's main power grid;

[0154] Determine the current output frequency of the main power grid according to the target area data and tags;

[0155] The time stability interval of the user's main power grid is determined by training and learning big data models.

[0156] After the step of determining the time stability interval of the user's main power grid by training and learning the big data model,

[0157] The time compensation interval that the microgrid needs to compensate is calculated through the time stability interval of the main power grid.

[0158] In the step of compensating the output load or being charged based on the preset microgrid current threshold,

[0159] Determine the preset microgrid output current;

[0160] If the microgrid output storage energy is lower than a first percentage, the microgrid shuts down the output;

[0161] If the microgrid outputs stored energy higher than the second percentage, the microgrid directly outputs;

[0162] If the microgrid output stored energy is lower than the second percentage and lower than the first percentage, the microgrid compensates the main grid output.

[0163] When the microgrid output energy storage is lower than the first percentage, the microgrid shuts down the output.

[0164] The microgrid is also charged with energy storage through the main grid via the inverter.

[0165] In the step of calculating the power loss of switching between AC and DC according to the target load,

[0166] Determine the target load and use the formula:

[0167] [P_{\text{load}}=V_{\text{load}}\times I_{\text{load}}\times\text{PF}]

[0168] Where (V_{\text{load}}) is the load voltage, (I_{\text{load}}) is the load current, and PF is the power factor (for AC loads).

[0169] Specifically,

[0170] Consider other loss factors

[0171] Heat loss: Heat loss due to resistance in inverters and other electrical components;

[0172] Switching loss: The loss generated by the inverter during the switching process, which is usually related to the switching frequency and the characteristics of the switching elements;

[0173] Harmonic losses: If the load is nonlinear, harmonic distortion can cause additional energy losses;

[0174] Comprehensive consideration

[0175] After taking all the loss factors into consideration, the total power loss is:

[0176] [P_{\text{total loss}}=P_{\text{loss}}+P_{\text{thermal}}+P_{\text{switching}}+P_{\text{harmonic}}]

[0177] Calculate total power loss

[0178] To calculate the total power loss over a certain period of time, the following formula can be used:

[0179] [E_{\text{loss}}=P_{\text{total loss}}\times t]Where (t) is time (unit: hour);

[0180] Assuming the target load is 1000W, the inverter efficiency is 95%, and considering other losses (heat loss, switching loss, and harmonic loss) of 50W, the power loss can be calculated as follows:

[0181] Calculate the DC input power:

[0182] [P_{\text{in}}=\frac{1000,\text{W}}{0.95}\approx 1052.63,\text{W}]

[0183] Calculate the power loss:

[0184] [P_{\text{loss}}=1052.63,\text{W}-1000,\text{W}\approx 52.63,\text{W}]

[0185] Taking other losses into consideration:

[0186] [P_{\text{total loss}}=52.63,\text{W}+50,\text{W}=102.63,\text{W}]

[0187] Calculate the total energy loss in 1 hour: [E_{\text{loss}}=102.63,\text{W}\times1,\text{h}=102.63,\text{Wh}]

[0188] Through the above steps and algorithms, the power loss during the switching process between AC and DC can be systematically calculated.

[0189] In this embodiment, after the step of obtaining current based on the power supply sustainability of the microgrid to determine the subsequent output power,

[0190] Obtain external energy factors and merge big data content to determine the available time and intensity of the microgrid;

[0191] Specifically,

[0192]

[0193]

[0194] By acquiring external energy factors and integrating big data content, the available time and intensity of the microgrid can be determined more accurately. This process not only improves the grid-connected control efficiency of the bidirectional energy storage inverter, but also enhances the intelligence level of the microgrid, ensuring optimal energy management and utilization under different environmental conditions.

[0195] Those skilled in the art will appreciate that embodiments of the present invention may be provided as methods, systems, or computer program products. Therefore, the present invention may take the form of a complete hardware embodiment, a complete software embodiment, or an embodiment combining software and hardware. Moreover, the present invention may take the form of a computer program product implemented 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.

[0196] The present invention is described with reference to flowcharts and / or block diagrams of methods, devices (systems) and computer program products according to embodiments of the present invention. It should be understood that each process and / or block in the flowchart and / or block diagram, as well as the combination of processes and / or blocks in the flowchart and / or block diagram, can be implemented by computer program instructions. These computer program instructions can be provided to a processor of a general-purpose computer, a special-purpose computer, an embedded processor or other programmable data processing device to produce a machine, so that the instructions executed by the processor of the computer or other programmable data processing device generate instructions for implementing the process in the flowchart. Figure 1 A process or multiple processes and / or boxes Figure 1 A device that provides the functions specified in a block or multiple blocks.

[0197] These computer program instructions may also be stored in a computer-readable memory capable of directing a computer or other programmable data processing device to operate in a specific manner, so that the instructions stored in the computer-readable memory produce an article of manufacture comprising an instruction device, which implements the process Figure 1 A process or multiple processes and / or boxes Figure 1 A function specified in one or more boxes.

[0198] These computer program instructions can also be loaded onto a computer or other programmable data processing device so that a series of operating steps are executed on the computer or other programmable device to produce a computer-implemented process, thereby providing instructions for implementing the process. Figure 1 A process or multiple processes and / or boxes Figure 1 The steps for the functions specified in one or more boxes.

[0199] Although the embodiments of the present application have been shown and described, it will be appreciated by those skilled in the art that various changes, modifications, substitutions and variations may be made to the embodiments without departing from the principles and spirit of the present application, and that the scope of the present application is defined by the appended claims and their equivalents.

Claims

1. A grid-connected control method for a bidirectional energy storage inverter, characterized in that: The method comprises: Obtain the current and voltage status information of the main grid and microgrid as well as the external target load demand; Compensating output load or being charged based on a preset microgrid current threshold; Calculating the power loss of switching between AC and DC according to the target load; The subsequent output power is determined based on the power supply sustainability of the microgrid by acquiring the current.

2. The grid-connected control method of the bidirectional energy storage inverter according to claim 1, characterized in that: In the step of obtaining the current and voltage status information of the main grid and the microgrid and the external target load demand, Obtain the target area data and labels of the user's main power grid; Determine the current output frequency of the main power grid according to the target area data and tags; The time stability interval of the user's main power grid is determined by training and learning big data models.

3. The grid-connected control method of the bidirectional energy storage inverter according to claim 2, characterized in that: After the step of determining the time stability interval of the user's main power grid by training and learning the big data model, The time compensation interval that the microgrid needs to compensate is calculated through the time stability interval of the main power grid.

4. The grid-connected control method of the bidirectional energy storage inverter according to claim 1, characterized in that: In the step of compensating the output load or being charged based on the preset microgrid current threshold, Determine the preset microgrid output current; If the microgrid output storage energy is lower than a first percentage, the microgrid shuts down the output; If the microgrid outputs stored energy higher than the second percentage, the microgrid directly outputs; If the microgrid output stored energy is lower than the second percentage and lower than the first percentage, the microgrid compensates the main grid output.

5. The grid-connected control method of the bidirectional energy storage inverter according to claim 4, characterized in that: When the microgrid output energy storage is lower than the first percentage, the microgrid shuts down the output. The microgrid is also charged with energy storage through the main grid via the inverter.

6. The grid-connected control method of the bidirectional energy storage inverter according to claim 1, characterized in that: In the step of calculating the power loss of switching between AC and DC according to the target load, Determine the target load and use the formula: [P_{\text{load}}=V_{\text{load}}\times I_{\text{load}}\times\text{PF}] Where (V_{\text{load}}) is the load voltage, (I_{\text{load}}) is the load current, and PF is the power factor (for AC loads).

7. The grid-connected control method of the bidirectional energy storage inverter according to claim 1, characterized in that: After the step of obtaining current based on the power supply sustainability of the microgrid to determine the subsequent output power, Obtain external energy factors and integrate big data content to determine the available time and intensity of the microgrid.

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