Low energy storage capacity configuration method based on intelligent load

Abstract

The invention discloses a low energy storage capacity configuration method based on an intelligent load, and belongs to the technical field of energy storage configuration. The low energy storage capacity configuration method based on the intelligent load comprises the following steps: acquiring power supply side information and load side information of the intelligent load from a storage unit; optimizing the configuration of the energy storage capacity according to the power supply side information and the load side information; comparing and verifying the results of the configuration; the power supply side information comprises related information of traditional power generation and renewable energy power generation and a predicted power generation curve; wherein the relevant information of renewable energy power generation comprises information such as installed capacity and voltage class; according to the low energy storage capacity configuration method based on the intelligent load, the intelligent load formed by connecting the voltage source inverter and the non-critical load in series is adopted, electricity consumption can be automatically matched with the generating capacity, the power fluctuation range allowed by the non-critical load is fully utilized, and therefore the energy storage capacity needing to be configured by the system is reduced.

Description

Technical Field

[0001] The present invention relates to the technical field of energy storage configuration, and in particular to a low energy storage capacity configuration method based on intelligent load. Background Art

[0002] In recent years, the installed capacity of renewable energy has continued to increase, and new power systems with a high proportion of renewable energy have become a development trend. The intermittent and random characteristics of renewable energy generation will lead to power fluctuations in the power grid, thereby adversely affecting the operation of certain power-consuming equipment (critical loads) that are sensitive to power fluctuations. In order to overcome the power fluctuation problem caused by renewable energy generation, traditional battery energy storage systems are widely used in power grids to balance the power fluctuations of renewable energy through the charging and discharging of energy storage batteries. However, it is worth noting that traditional battery energy storage systems cannot utilize the allowable power fluctuation range of non-critical loads. They need to be configured with a larger energy storage capacity to ensure the stable operation of the system, and the larger energy storage battery capacity leads to an increase in the construction and maintenance costs of the system.

[0003] In order to reduce the energy storage demand of the system, it is an effective means to utilize the allowable power fluctuation range of non-critical loads. The intelligent load formed by the voltage source inverter and the non-critical load in series can automatically match the power consumption with the power generation, and make full use of the allowable power fluctuation range of the non-critical load, thereby reducing the energy storage capacity required by the system. Summary of the invention

[0004] In view of the above problems existing in the prior art, the present invention is proposed.

[0005] Therefore, the technical problem to be solved by the present invention is a problem.

[0006] To achieve the above object, the present invention provides the following technical solution: a low energy storage capacity configuration method based on smart load, comprising:

[0007] Acquire power supply side information and load side information of the intelligent load in the storage unit;

[0008] Optimize the configuration of energy storage capacity based on power supply side information and load side information;

[0009] Compare and verify the configuration results.

[0010] As a further solution of the present invention: the power supply side information includes relevant information and expected power generation curves of traditional power generation and renewable energy power generation;

[0011] The relevant information of renewable energy power generation includes information such as installed capacity and voltage level.

[0012] As a further solution of the present invention: the load side information includes the size and ratio of the critical load and the non-critical load, and the power fluctuation range allowed for the non-critical load.

[0013] As a further solution of the present invention: the critical load is a load with high voltage stability requirements such as computers, precision medical equipment or electric vehicle charging facilities.

[0014] As a further solution of the present invention: the non-critical load is an electric water heater, a refrigerator or an air conditioner, which allows a certain degree of power fluctuation.

[0015] As a further solution of the present invention: the intelligent load includes a voltage source inverter and a non-critical load connected in series with the voltage source inverter.

[0016] As a further solution of the present invention: the voltage source inverter includes a battery, a coil, a capacitor connected in parallel to one end of the coil, a first switch tube and a second switch tube connected to the other end of the coil, and a third switch tube and a fourth switch tube connected in sequence to a non-critical load.

[0017] As a further solution of the present invention: the intelligent load and the critical load are connected in parallel to the line impedance;

[0018] Wherein, the line impedance is connected in series with the AC power supply.

[0019] As a further solution of the present invention: the step of optimizing the configuration of energy storage capacity according to the power supply side information and the load side information includes:

[0020] Determine the objective function of the energy storage capacity configuration model according to the power supply side information and the load side information and based on the target technical and economic benefits;

[0021] Determine the model's constraints based on generation limitations, voltage stability requirements, and the power fluctuation range allowed for non-critical loads;

[0022] The particle swarm optimization and genetic algorithm are used to solve the model.

[0023] As a further solution of the present invention: the storage unit is arranged in the upper machine position.

[0024] Compared with the prior art, the beneficial effect of the present invention is that the low energy storage capacity configuration method based on intelligent load adopts the intelligent load formed by connecting a voltage source inverter in series with a non-critical load to realize automatic matching of power consumption with power generation, and fully utilizes the power fluctuation range allowed by the non-critical load, thereby reducing the energy storage capacity required to be configured by the system, thereby reducing the configuration requirements of the energy storage capacity and reducing the construction and maintenance costs of the system. BRIEF DESCRIPTION OF THE DRAWINGS

[0025] In order to more clearly illustrate the technical solutions of the embodiments of the present invention, the following briefly introduces the drawings required for describing the embodiments. Obviously, the drawings described below are only some embodiments of the present invention. For ordinary technicians in this field, other drawings can be obtained based on these drawings without creative work. Among them:

[0026] Figure 1 The figure is an overall flow chart of the low energy storage capacity configuration method based on smart load.

[0027] Figure 2 The invention is a circuit diagram for connecting smart loads and critical loads based on a low energy storage capacity configuration method of smart loads.

[0028] Figure 3 Schematic diagram of the internal structure of the adjustment bracket for the low energy storage capacity configuration method based on smart load. DETAILED DESCRIPTION

[0029] In order to make the above-mentioned objects, features and advantages of the present invention more obvious and easy to understand, the specific embodiments of the present invention are described in detail below in conjunction with the accompanying drawings.

[0030] In the following description, many specific details are set forth to facilitate a full understanding of the present invention, but the present invention may also be implemented in other ways different from those described herein, and those skilled in the art may make similar generalizations without violating the connotation of the present invention. Therefore, the present invention is not limited to the specific embodiments disclosed below.

[0031] Secondly, the present invention is described in detail with reference to the schematic diagram. When describing the embodiments of the present invention in detail, for the sake of convenience, the cross-sectional diagrams showing the device structure will not be partially enlarged according to the general scale, and the schematic diagrams are only examples, which should not limit the scope of protection of the present invention. In addition, in actual production, the three-dimensional dimensions of length, width and depth should be included.

[0032] Furthermore, the term "one embodiment" or "embodiment" as used herein refers to a specific feature, structure, or characteristic that may be included in at least one implementation of the present invention. The term "in one embodiment" that appears in different places in this specification does not necessarily refer to the same embodiment, nor is it a separate or selective embodiment that is mutually exclusive with other embodiments.

[0033] Example 1

[0034] like Figures 1-2As shown, the present invention provides a technical solution: a low energy storage capacity configuration method based on a smart load, comprising S1: obtaining power side information and load side information of the smart load in a storage unit; S2: optimizing the configuration of the energy storage capacity according to the power side information and the load side information; S3: comparing and verifying the configuration results.

[0035] It should be noted that the storage unit is set in the upper machine position, and the power side information and load side information of the intelligent load have been entered into the storage unit through the upper machine position before being put into use. At this time, the relevant intelligent load power side information and load side information stored in the storage unit can be retrieved through the upper machine position.

[0036] Specifically, the power supply side information includes relevant information of traditional power generation and renewable energy power generation and the expected power generation curve; among which, the relevant information of renewable energy power generation includes information such as installed capacity and voltage level.

[0037] Specifically, the load side information includes the size and ratio of critical loads to non-critical loads, and the allowable power fluctuation range of non-critical loads (P NcLmin , P NcLmax ); It should be noted that critical loads are loads that have high voltage stability requirements, such as computers, precision medical equipment and / or electric vehicle charging facilities; non-critical loads are loads that allow a certain degree of power fluctuation, such as electric water heaters, refrigerators and / or air conditioners.

[0038] Further, the step of optimizing the configuration of energy storage capacity according to the power supply side information and the load side information includes:

[0039] S21: determining an objective function of the energy storage capacity configuration model according to the power supply side information and the load side information and based on the target technical and economic benefits;

[0040] S22: Determine the model's constraints based on factors such as power generation constraints, voltage stability requirements, and the power fluctuation range allowed for non-critical loads;

[0041] S23: Use particle swarm algorithm, genetic algorithm and other algorithms to solve the model.

[0042] It should be noted that voltage stability mainly refers to the voltage effective value being stable at the rated value.

[0043] Among them, the algorithm solution models such as particle swarm algorithm and genetic algorithm are trained and determined according to the specific application scenarios of the smart load, which will not be elaborated here.

[0044] It should be noted that the result of the comparison and verification configuration is to compare the system based on smart loads with the system based on traditional battery energy storage. The smart load system only needs to compensate for the fluctuating power that exceeds the allowable fluctuation range of non-critical loads, while the battery energy storage system needs to compensate for all fluctuating power. In general, the smart load system utilizes the allowable power fluctuation range of non-critical loads, while the traditional battery energy storage system does not, which allows the traditional battery energy storage system to compensate more active power than the smart load system.

[0045] In summary, the low energy storage capacity configuration method based on smart load uses a smart load formed by connecting a voltage source inverter in series with a non-critical load to realize automatic matching of power consumption with power generation, and make full use of the power fluctuation range allowed by the non-critical load, thereby reducing the energy storage capacity required to be configured in the system, thereby reducing the configuration requirements of the energy storage capacity and reducing the construction and maintenance costs of the system.

[0046] Example 2

[0047] like Figures 1-2 As shown, it is a second embodiment of the present invention, which is a method for configuring low energy storage capacity of a smart load, comprising obtaining power supply side information and load side information of the smart load in a storage unit;

[0048] Optimize the configuration of energy storage capacity based on power supply side information and load side information;

[0049] Compare and verify the configuration results.

[0050] It should be noted that the storage unit is set in the upper machine position, and the power side information and load side information of the intelligent load have been entered into the storage unit through the upper machine position before being put into use. At this time, the relevant intelligent load power side information and load side information stored in the storage unit can be retrieved through the upper machine position.

[0051] Specifically, the power supply side information includes relevant information of traditional power generation and renewable energy power generation and the expected power generation curve; among which, the relevant information of renewable energy power generation includes information such as installed capacity and voltage level.

[0052] Specifically, the load side information includes the size and ratio of critical loads and non-critical loads, as well as the allowable power fluctuation range of non-critical loads; it should be noted that critical loads are loads with high voltage stability requirements such as computers, precision medical equipment and / or electric vehicle charging facilities; non-critical loads are loads that allow a certain degree of power fluctuation, such as electric water heaters, refrigerators and / or air conditioners.

[0053] Further, the step of optimizing the configuration of energy storage capacity according to the power supply side information and the load side information includes:

[0054] Determine the objective function of the energy storage capacity configuration model based on the power supply side information and the load side information and based on the target technical and economic benefits; determine the model's constraints based on factors such as power generation limitations, voltage stability requirements, and the allowable power fluctuation range of non-critical loads; and use algorithms such as particle swarm optimization and genetic algorithms to solve the model.

[0055] It should be noted that voltage stability mainly refers to the voltage effective value being stable at the rated value.

[0056] Further, such as Figure 2 As shown, the smart load includes a voltage source inverter and a non-critical load connected in series with the voltage source inverter;

[0057] It should be noted that the voltage source inverter includes a battery, a coil, a capacitor connected in parallel to one end of the coil, a first switch tube and a second switch tube connected to the other end of the coil, and a third switch tube and a fourth switch tube connected in sequence to a non-critical load.

[0058] Specifically, the intelligent load and the critical load are connected in parallel to the line impedance; wherein the line impedance is connected in series with the AC power source.

[0059] In summary, the low energy storage capacity configuration method based on smart load uses a smart load formed by connecting a voltage source inverter in series with a non-critical load to realize automatic matching of power consumption with power generation, and make full use of the power fluctuation range allowed by the non-critical load, thereby reducing the energy storage capacity required to be configured in the system, thereby reducing the configuration requirements of the energy storage capacity and reducing the construction and maintenance costs of the system.

[0060] Example 3

[0061] like Figure 3 As shown, it is the third embodiment of the present invention. The difference between this embodiment and the previous embodiment is that in order to verify the effectiveness of the control method proposed in the present invention, a simulation experiment was carried out in PLECS, and the experimental parameters were set as follows: grid rated voltage V=220V, rated frequency f=50Hz, critical load rated power PCL=2500W, non-critical load rated power PNCL=2500W, the allowable power fluctuation range (PNCLmin, PNCLmax) of non-critical load is 2000W~3000W, and the power injected from the generator end to the load end is set to fluctuate between 4100W~6100W, and the fluctuation period is 10s; in order to highlight the significant effect of the energy storage capacity configuration method based on smart load in reducing energy storage demand, the system based on smart load is compared with the system based on traditional battery energy storage. In order to highlight the comparison effect, the battery capacity of the DC side of the two is set to the same 0.24Ah.

[0062] It should be noted that PLECS is a software specifically used for power electronic system simulation, providing simulation and analysis of motor control systems, including inverters, motors, sensors and control systems.

[0063] like Figure 3 As shown in the figure, the traditional battery energy storage system adjusts PNCL to PNCLref, while the smart load system adjusts PNCL to the maximum allowable fluctuation range. In addition, the smart load system only needs to compensate for the fluctuating power that exceeds the allowable fluctuation range of non-critical loads, while the battery energy storage system needs to compensate for all fluctuating power. In general, the smart load system utilizes the allowable power fluctuation range of non-critical loads, while the traditional battery energy storage system does not, which allows the traditional battery energy storage system to compensate for more active power than the smart load system.

[0064] In addition, by observing the state of charge of the batteries of the smart load system and the traditional battery energy storage system (the initial state of charge is set to 50%), it can be seen that the maximum change in the state of charge of the traditional battery energy storage system during operation is 19.13%, while the change of the smart load system is only 4.94%. This shows that under these simulation parameters, the battery capacity required by the smart load system is only one-fourth of the battery capacity required by the traditional battery energy storage system, indicating that the smart load system is effective in reducing energy storage requirements.

[0065] The above examples are preferred implementations of the present invention, but the implementations of the present invention are not limited to the examples. Any other changes, modifications, substitutions, combinations, simplifications that do not deviate from the spirit and principles of the present invention should be equivalent replacement methods and are included in the protection scope of the present invention:.

[0066] Importantly, it should be noted that the construction and arrangement of the present application shown in a number of different exemplary embodiments are only exemplary. Although only a few embodiments are described in detail in this disclosure, it should be readily understood by those who refer to this disclosure that many modifications are possible, for example, the size, scale, structure, shape and proportion of various elements, and parameter values ​​such as temperature, pressure, etc., mounting arrangements, use of materials, color, directional changes, etc., without substantially departing from the novel teachings and advantages of the subject matter described in the application. For example, the element shown as integrally formed can be composed of multiple parts or elements, the position of the element can be inverted or otherwise changed, and the nature or number or position of the discrete element can be changed or changed. Therefore, all such modifications are intended to be included in the scope of the present invention. The order or sequence of any process or method steps can be changed or reordered according to alternative embodiments. In the claims, any "device plus function" clause is intended to cover the structure of the execution function described herein, and is not only structurally equivalent but also equivalent structure. Without departing from the scope of the present invention, other substitutions, modifications, changes and omissions can be made in the design, operating conditions and arrangement of the exemplary embodiments. Therefore, the invention is not limited to a specific embodiment, but extends to numerous modifications still falling within the scope of the appended claims.

[0067] Furthermore, in order to provide a concise description of exemplary embodiments, all features of an actual embodiment may not be described, i.e., those features that are not relevant to the best mode presently contemplated for carrying out the invention or those features that are not relevant to implementing the invention.

[0068] It should be understood that in the development of any actual implementation, as in any engineering or design project, numerous implementation-specific decisions may be made. Such a development effort may be complex and time-consuming, but for those of ordinary skill having the benefit of this disclosure, the development effort will be a routine task of design, fabrication, and production without undue experimentation.

[0069] It should be noted that the above embodiments are only used to illustrate the technical solutions of the present invention rather than to limit it. Although the present invention has been described in detail with reference to the preferred embodiments, those skilled in the art should understand that the technical solutions of the present invention may be modified or replaced by equivalents without departing from the spirit and scope of the technical solutions of the present invention, which should all be included in the scope of the claims of the present invention.

Claims

1. A low energy storage capacity configuration method based on smart load, characterized in that: include, Acquire power supply side information and load side information of the intelligent load in the storage unit; Optimize the configuration of energy storage capacity based on power supply side information and load side information; Compare and verify the configuration results.

2. The low energy storage capacity configuration method based on smart load according to claim 1, characterized in that: The power supply side information includes relevant information of traditional power generation and renewable energy power generation and the expected power generation curve; The relevant information of renewable energy power generation includes information such as installed capacity and voltage level.

3. The low energy storage capacity configuration method based on smart load according to claim 1 or 2, characterized in that: The load side information includes the size and ratio of the critical load to the non-critical load, and the power fluctuation range allowed for the non-critical load.

4. The low energy storage capacity configuration method based on smart load according to claim 3, characterized in that: The critical loads are computers, precision medical equipment or electric vehicle charging facilities that have high voltage stability requirements.

5. The low energy storage capacity configuration method based on smart load according to claim 4, characterized in that: The non-critical load is an electric water heater, a refrigerator or an air conditioner, which allows a certain degree of power fluctuation.

6. The low energy storage capacity configuration method based on smart load according to claim 5, characterized in that: The smart load includes a voltage source inverter and a non-critical load connected in series with the voltage source inverter.

7. The low energy storage capacity configuration method based on smart load according to claim 6, characterized in that: The voltage source inverter includes a battery, a coil, a capacitor connected in parallel to one end of the coil, a first switch tube and a second switch tube connected to the other end of the coil, and a third switch tube and a fourth switch tube connected to a non-critical load in sequence.

8. The low energy storage capacity configuration method based on smart load according to claim 7, characterized in that: The smart load and the critical load are connected in parallel to the line impedance; Wherein, the line impedance is connected in series with the AC power supply.

9. The low energy storage capacity configuration method based on smart load according to any one of claims 4 to 8, characterized in that: The steps of optimizing the configuration of energy storage capacity according to the power supply side information and the load side information include: Determine the objective function of the energy storage capacity configuration model according to the power supply side information and the load side information and based on the target technical and economic benefits; Determine the model's constraints based on generation limitations, voltage stability requirements, and the power fluctuation range allowed for non-critical loads; Particle swarm optimization and genetic algorithm are used to solve the model.

10. The low energy storage capacity configuration method based on smart load according to claim 9, characterized in that: The storage unit is arranged in the upper machine position.

Images