Method and device for analyzing source network load storage of cross-energy fusion micro-grid

Abstract

The invention relates to the technical field of energy power, in particular to a source network load storage analysis method for a cross-energy fusion microgrid, and the method comprises the steps: carrying out the initialization setting of target data and an operation upper limit of a road cross-energy system; wherein the highway energy exchange system is used for carrying out source network load storage self-consistent analysis on the micro-grid system taking the highway service area as the main body, then calculating the micro-grid total power and the electric quantity state of the highway energy exchange system based on the electric vehicle charging power, and finally calculating the electric quantity state of the highway energy exchange system based on the target data, the operation upper limit, the micro-grid total power and the electric quantity state. Therefore, according to the technical scheme, the problem that the analysis of the power supply capacity, the traffic flow loading capacity and the distribution and storage demand of the service area is not perfect at present can be solved.

Description

Technical Field

[0001] The present invention relates to the field of energy and electricity, and in particular to an analysis method and device for a microgrid source-grid-load-storage system integrating energy and electricity. Background Art

[0002] Highway transportation is the most convenient and efficient transportation infrastructure, and highway transportation accounts for more than 85% of the country's transportation emissions. At the same time, the vigorous development of new energy vehicles has brought higher requirements for highway power load. The development of microgrids in highway energy systems can organically combine primary equipment such as distributed photovoltaics, power loads and energy storage systems and their control systems to form an orderly local power supply microgrid, thereby forming a self-consistent system that can self-control, protect and manage. However, the current analysis of the power supply capacity, traffic load capacity and distribution storage requirements of service areas is not perfect.

[0003] Therefore, the present invention proposes an analysis method and device for a hybrid microgrid source-grid-load-storage to solve the current incomplete analysis of the power supply capacity, traffic load capacity and distribution and storage requirements of the service area. Summary of the invention

[0004] The present invention describes a method and device for analyzing the source, grid, load and storage of a hybrid microgrid, which can solve the problem that the current analysis of the power supply capacity, traffic load capacity and distribution and storage requirements of a service area is not perfect.

[0005] According to a first aspect, the present invention provides a method for analyzing a source-grid-load-storage hybrid microgrid, the method comprising:

[0006] Initialize and set the target data and operation upper limit of the highway traffic energy system; wherein the highway traffic energy system is used to perform source-grid-load-storage self-consistent analysis on the microgrid system with the highway service area as the main body;

[0007] Based on the charging power of the electric vehicles, the total power and power state of the microgrid of the highway traffic energy system are calculated;

[0008] Based on the target data, the operating upper limit, the total power of the microgrid and the power status, the operating requirements of the highway traffic energy system are analyzed.

[0009] According to a second aspect, an analysis device for a hybrid microgrid source-grid-load-storage system is provided, the device comprising:

[0010] The initialization unit is configured to initialize the target data and the upper limit of operation of the highway traffic energy system; wherein the highway traffic energy system is used to perform a source-grid-load-storage self-consistent analysis on the microgrid system with the highway service area as the main body;

[0011] A calculation unit configured to calculate the total power and power state of the microgrid of the highway traffic energy system based on the charging power of the electric vehicle;

[0012] The analysis unit is configured to analyze the operation requirements of the highway traffic energy system based on the target data, the operation upper limit, the total power of the microgrid and the power state.

[0013] In a third aspect, an embodiment of this specification further provides an electronic device, including a memory and a processor, wherein the memory stores a computer program, and when the processor executes the computer program, the method described in any embodiment of this specification is implemented.

[0014] In a fourth aspect, an embodiment of the present specification further provides a computer-readable storage medium on which a computer program is stored. When the computer program is executed in a computer, the computer is caused to execute the method described in any embodiment of the present specification.

[0015] According to a method and device for analyzing source, grid, load and storage of a transportation-energy-integrated microgrid provided by the present invention, the target data and operating upper limit of a highway transportation energy system are initialized and set; wherein the highway transportation energy system is used to perform self-consistent analysis of source, grid, load and storage on a microgrid system with a highway service area as the main body, and then, based on the charging power of electric vehicles, the total microgrid power and power status of the highway transportation energy system are calculated; finally, based on the target data, the operating upper limit, the total microgrid power and the power status, the operating requirements of the highway transportation energy system are analyzed. Therefore, the above technical solution can solve the problem that the current analysis of the power supply capacity, traffic load capacity and distribution and storage requirements of the service area is not perfect. BRIEF DESCRIPTION OF THE DRAWINGS

[0016] In order to more clearly illustrate the embodiments of the present invention or the technical solutions in the prior art, the drawings required for use in the embodiments or the description of the prior art will be briefly introduced below. Obviously, the drawings described below are some embodiments of the present invention. For ordinary technicians in this field, other drawings can be obtained based on these drawings without paying creative work.

[0017] Figure 1 A schematic flow chart of a method for analyzing a source-grid-load-storage hybrid microgrid according to an embodiment is shown;

[0018] Figure 2 A schematic block diagram of an analysis device for a microgrid source-grid-load-storage system with energy fusion according to an embodiment is shown;

[0019] Figure 3 The overall flow chart of a method for analyzing a source-grid-load-storage of a hybrid energy microgrid according to an embodiment is shown;

[0020] Figure 4 A practical schematic diagram of an analysis method for a hybrid microgrid source-grid-load-storage system according to an embodiment is shown. DETAILED DESCRIPTION

[0021] In order to make the purpose, technical solutions and advantages of the embodiments of this specification clearer, the technical solutions in the embodiments of this specification will be clearly and completely described below in conjunction with the drawings in the embodiments of this specification. Obviously, the described embodiments are part of the embodiments of this specification, not all of the embodiments. Based on the embodiments in this specification, all other embodiments obtained by ordinary technicians in this field without making creative work are within the scope of protection of this specification.

[0022] See also Figure 1 , shows a flow chart of an analysis method for a hybrid microgrid source-grid-load-storage according to an embodiment. It can be understood that the method can be executed by any device, equipment, platform, or device cluster with computing and processing capabilities. Figure 1 As shown, the method includes:

[0023] Step 100, initializing and setting the target data and the upper limit of operation of the highway traffic energy system; wherein the highway traffic energy system is used to perform a self-consistent analysis of the source-grid-load-storage of the microgrid system with the highway service area as the main body;

[0024] Step 102: Calculate the total power and power state of the microgrid of the highway traffic energy system based on the charging power of the electric vehicle;

[0025] Step 104: Analyze the operation requirements of the highway traffic energy system based on the target data, the operation upper limit, the total power of the microgrid and the power status.

[0026] In this embodiment, the target data and operating upper limit of the highway traffic energy system are initialized and set; wherein the highway traffic energy system is used to perform a self-consistent analysis of the source-grid-load-storage of the microgrid system with the highway service area as the main body, and then, based on the charging power of the electric vehicle, the total power and power status of the microgrid of the highway traffic energy system are calculated. Finally, based on the target data, the operating upper limit, the total power and power status of the microgrid, the operating requirements of the highway traffic energy system are analyzed. Therefore, the above technical solution can solve the problem that the current analysis of the power supply capacity, traffic load capacity and distribution and storage requirements of the service area is not perfect.

[0027] like Figure 3As shown, in some embodiments, the method sets the seasons and clarifies the seasonal influencing factors and the new energy power generation curve according to the load, traffic flow, electric vehicle load change characteristics, and the impact of new energy power generation in different seasons, and then generates the load for the time series position corresponding to each step by setting a given time step. Finally, through sensitivity analysis, the energy storage capacity, the predicted peak value of the electric vehicle load, and the initial value of the new energy output are analyzed in a certain step change mode for each cycle under different loads and power generation conditions. Whether the source-load balance and energy storage ratio of the system are sufficient.

[0028] By adjusting the iteration amount and the step size of each variable, the self-consistency of the source, grid, load and storage of a highway service area microgrid under different environmental conditions can be analyzed under various variable ranges. This method can be used to infer the characteristic curve applicable to all scenarios, clarify whether the system's source-load balance and energy storage ratio are sufficient under different loads and power generation conditions, and then guide energy and transportation planning and energy storage ratio issues.

[0029] like Figure 4 As shown, in some embodiments, in order to ensure that enough electric vehicle load scenarios can be covered and summarized, the present method is used to simulate the microgrid load changes caused by the charging of electric vehicles. In each iteration, the charging power of the electric vehicle corresponding to the time sequence in the iteration is randomly changed to generate a variety of load conditions affected by traffic energy consumption. Among them, when it is necessary to consider the determination of the capacity (P res ) in the microgrid system of renewable energy power generation, when the renewable energy fluctuates due to weather, the renewable energy output can also be introduced into the attenuation factor P d =P res R is used to cover the characteristics of renewable energy output fluctuations under different weather conditions. The load state under different convergence conditions is clarified by controlling the size of the iteration amount.

[0030] In some embodiments, for step 104, the present invention adopts sensitivity analysis for different factors such as the new energy capacity connected to the highway traffic energy system, the peak power consumption of regional electric vehicles, and the energy storage capacity configuration, such as Figure 3 As shown in the figure, by setting Δ1, Δ2 and Δ3 to clarify the analysis resolution, the system sensitivity to each factor, as well as the system response and the demand for electricity from the main grid under different configurations of source, load and storage are analyzed.

[0031] It should be noted that: when the state of charge is less than 0, d1 is gradually reduced with a certain step size (Δ1) until the energy storage configuration is completely insufficient and d1 is set to the initial value at this time;

[0032] When the power state is less than 0 and d2 is not equal to the upper limit of the new energy capacity configuration, d2 gradually increases to the feasible upper limit to the upper limit of the new energy capacity configuration with a certain step size (Δ2) and d2 is set to the initial value at this time;

[0033] When the power state is less than 0, d2 is not equal to the upper limit of the new energy capacity configuration, and d3 is not equal to the upper limit of the peak power consumption of electric vehicles, d3 gradually increases to the feasible upper limit to the upper limit of the peak power consumption of regional electric vehicles with a certain step size (Δ3).

[0034] In this step cycle, the system's sensitivity to energy storage and its demand for energy storage capacity and margin are determined by continuously reducing the energy storage ratio. The system's sensitivity to new energy output and its demand for new energy capacity configuration are determined by continuously increasing the new energy ratio. The system's sensitivity to traffic energy consumption and its ability to withstand changes in traffic energy consumption are determined by continuously increasing the power consumption of electric vehicles.

[0035] In one embodiment of the present invention, the target data includes energy storage capacity configuration, new energy capacity and regional electric vehicle peak power consumption, and the operating upper limit includes the new energy capacity configuration upper limit and the regional electric vehicle peak power consumption upper limit.

[0036] In this embodiment, a self-consistent analysis of source, grid, load and storage can be performed on the microgrid system with highway service areas as the main body, providing guidance for energy and transportation integration planning, integrating the characteristics of traffic load and general traditional power load, and using target data to analyze and judge the power supply capacity, traffic load capacity and distribution and storage requirements of the service area.

[0037] In one embodiment of the present invention, the charging power of the electric vehicle is determined by the following formula:

[0038]

[0039] In the formula, is the electric vehicle charging power corresponding to time sequence t in the i-th iteration, PEV peak is the peak charging power of the electric vehicle, and R is a random number between 0 and 1.

[0040] In this embodiment, in each iteration, the charging power of the electric vehicle corresponding to the time sequence in the iteration is randomly changed to generate a variety of load conditions affected by traffic energy consumption, and fully utilize the advantages of randomness to generate more load conditions.

[0041] In one embodiment of the present invention, the energy storage capacity configuration is determined by the following formula:

[0042]

[0043] In some embodiments, when the state of charge is less than 0, d1 is gradually reduced by a certain step size (Δ1) until the energy storage configuration is completely insufficient. In addition, d 10 is the initial value of d1;

[0044] In one embodiment of the present invention, the new energy capacity is determined by the following formula:

[0045]

[0046] In some embodiments, d2 gradually increases with a certain step size (Δ2) to the feasible upper limit to the upper limit of the new energy capacity configuration. In addition, d 20 is the initial value of d2.

[0047] In one embodiment of the present invention, the peak power consumption of electric vehicles in a region is determined by the following formula:

[0048]

[0049] In some implementations, d3 gradually increases with a certain step size (Δ3) to a feasible upper limit to a peak upper limit of regional electric vehicle power consumption.

[0050] In one embodiment of the present invention, the total power of the microgrid is determined by the following formula:

[0051]

[0052] Where P i is the power of the ith load, and n is the total number of loads.

[0053] like Figure 4 As shown, in some embodiments, by initializing and setting the number of iterations i, the unit time step t and then the unit simulation cycle step T, when the number of iterations is not equal to the total number of iterations, a loop accumulation is entered, and according to the unit step not being equal to the unit simulation cycle step, a loop accumulation is entered, and the total power of the microgrid and the power status under the unit step t are calculated in a loop.

[0054] In one embodiment of the present invention, the state of charge is determined by the following formula:

[0055]

[0056] In the formula, SOC0: initial remaining power, m is the total number of energy storage devices, is the power of the i-th energy storage device in the corresponding timing cycle, is the total capacity of the i-th energy storage device.

[0057] According to another embodiment, the present invention provides an analysis device for a hybrid microgrid source-grid-load-storage. Figure 2A schematic block diagram of an analysis device for a hybrid microgrid source-grid-load-storage according to an embodiment is shown. It can be understood that the device can be implemented by any device, equipment, platform and device cluster with computing and processing capabilities. The device includes: an initial unit 200, a computing unit 202 and an analyzing unit 204, wherein the main functions of each component unit are as follows:

[0058] The initial unit 200 is configured to initialize the target data and the upper limit of the operation of the highway traffic energy system; wherein the highway traffic energy system is used to perform a source-grid-load-storage self-consistent analysis on the microgrid system with the highway service area as the main body;

[0059] The calculation unit 202 is configured to calculate the total power and power state of the microgrid of the highway traffic energy system based on the charging power of the electric vehicle;

[0060] The analysis unit 204 is configured to analyze the operation requirements of the highway traffic energy system based on the target data, the operation upper limit, the total power of the microgrid and the power status.

[0061] As a preferred implementation, the target data includes energy storage capacity configuration, new energy capacity and regional electric vehicle peak power consumption, and the operating upper limit includes the new energy capacity configuration upper limit and the regional electric vehicle peak power consumption upper limit.

[0062] As a preferred implementation, the electric vehicle charging power is determined by the following formula:

[0063]

[0064] In the formula, is the electric vehicle charging power corresponding to time sequence t in the i-th iteration, PEV peak is the peak charging power of the electric vehicle, and R is a random number between 0 and 1.

[0065] As a preferred implementation, the energy storage capacity configuration is determined by the following formula:

[0066]

[0067] As a preferred implementation, the new energy capacity is determined by the following formula:

[0068]

[0069] As a preferred implementation, the peak power consumption of regional electric vehicles is determined by the following formula:

[0070]

[0071] As a preferred implementation, the total power of the microgrid is determined by the following formula:

[0072]

[0073] Where P t is the power of the ith load, t is a single time marker, and n is the total number of loads.

[0074] As a preferred implementation, the power state is determined by the following formula:

[0075]

[0076] In the formula, SOC0: initial remaining power, m is the total number of energy storage devices, is the power of the i-th energy storage device in the corresponding timing cycle, is the total capacity of the i-th energy storage device.

[0077] It can be understood that the information interaction, execution process and other contents between the modules in the above-mentioned device are based on the same concept as the method embodiments of this specification. The specific contents can be found in the description of the method embodiments of this specification and will not be repeated here.

[0078] According to another embodiment, there is also provided a computer-readable storage medium having a computer program stored thereon, which, when executed in a computer, causes the computer to execute a combination of Figure 1 The method described.

[0079] According to another embodiment of the present invention, an electronic device is provided, including a memory and a processor, wherein an executable code is stored in the memory, and when the processor executes the executable code, the Figure 1 method.

[0080] The various embodiments of the present invention are described in a progressive manner, and the same or similar parts between the various embodiments can be referred to each other, and each embodiment focuses on the differences from other embodiments. In particular, for the device embodiment, since it is basically similar to the method embodiment, the description is relatively simple, and the relevant parts can be referred to the partial description of the method embodiment.

[0081] Those skilled in the art should be aware that in one or more of the above examples, the functions described in the present invention can be implemented by hardware, software, firmware or any combination thereof. When implemented by software, these functions can be stored in a computer-readable medium or transmitted as one or more instructions or codes on a computer-readable medium.

[0082] The above specific implementation methods further illustrate the purpose, technical solutions and beneficial effects of the present invention in detail. It should be understood that the above are only specific implementation methods of the present invention and are not intended to limit the scope of protection of the present invention. Any modifications, equivalent substitutions, improvements, etc. made on the basis of the technical solutions of the present invention should be included in the scope of protection of the present invention.

Claims

1. A method for analyzing the source, grid, load and storage of a microgrid with energy fusion, characterized in that: The method comprises: Initialize and set the target data and operation upper limit of the highway traffic energy system; wherein the highway traffic energy system is used to perform source-grid-load-storage self-consistent analysis on the microgrid system with the highway service area as the main body; Based on the charging power of the electric vehicles, the total power and power state of the microgrid of the highway traffic energy system are calculated; Based on the target data, the operating upper limit, the total power of the microgrid and the power status, the operating requirements of the highway traffic energy system are analyzed.

2. The method according to claim 1, characterized in that: The target data includes energy storage capacity configuration, new energy capacity and regional electric vehicle peak power consumption, and the operating upper limit includes the new energy capacity configuration upper limit and the regional electric vehicle peak power consumption upper limit.

3. The method according to claim 2, characterized in that The electric vehicle charging power is determined by the following formula: In the formula, is the electric vehicle charging power corresponding to time sequence t in the i-th iteration, PEV peak is the peak charging power of the electric vehicle, and R is a random number between 0 and 1.

4. The method according to claim 3, characterized in that The energy storage capacity configuration is determined by the following formula:

5. The method according to claim 4, characterized in that The new energy capacity is determined by the following formula:

6. The method according to claim 5, characterized in that The peak power consumption of electric vehicles in the area is determined by the following formula:

7. The method according to claim 6, characterized in that The total power of the microgrid is determined by the following formula: Where P i is the power of the i-th load, n is the total number of loads; The state of charge is determined by the following formula: In the formula, SOC0: initial remaining power, m is the total number of energy storage devices, is the power of the i-th energy storage device in the corresponding timing cycle, is the total capacity of the i-th energy storage device.

8. An analysis device for a microgrid source-grid-load-storage system with energy fusion, characterized in that: The device comprises: The initialization unit is configured to initialize the target data and the upper limit of operation of the highway traffic energy system; wherein the highway traffic energy system is used to perform a source-grid-load-storage self-consistent analysis on the microgrid system with the highway service area as the main body; A calculation unit configured to calculate the total power and power state of the microgrid of the highway traffic energy system based on the charging power of the electric vehicle; The analysis unit is configured to analyze the operation requirements of the highway traffic energy system based on the target data, the operation upper limit, the total power of the microgrid and the power state.

9. An electronic device, characterized in that: The method comprises a memory and a processor, wherein the memory stores a computer program, and when the processor executes the computer program, the method according to any one of claims 1 to 7 is implemented.

10. A computer-readable storage medium, characterized in that: A computer program is stored thereon, and when the computer program is executed in a computer, the computer is caused to execute the method according to any one of claims 1 to 7.

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