Method for constructing power supply capacity measurement and calculation model of micro-grid in extreme scene

Abstract

The invention discloses a method for constructing a power supply capacity measuring and calculating model in an extreme scene of a micro-grid, and belongs to the technical field of power system control. Taking the maximum weighted value of the node power supply reliability, the node power supply capability, the power transmission efficiency of the power grid and the energy storage utilization rate as a target function, and taking the maximum weighted value of the power supply capability evaluation index of the micro-grid as a target, considering the output characteristics and the power transmission line capacity of the schedulable unit and the energy storage equipment of the micro-grid; taking the condition that the actual power of the preset load node is not lower than the required power of the preset load node as a node load power supply constraint, considering the maximum power constraint which can be provided for each node load by the micro-grid in the extreme scene of continuous low generating capacity of new energy, and finally establishing a power supply capacity measurement and calculation model of the micro-grid in the extreme scene. And the power supply capability of the micro-grid in an extreme scene can be accurately measured and calculated.

Description

Technical Field

[0001] The present invention belongs to the technical field of power system control, and more specifically, relates to a method for constructing a power supply capacity calculation model under extreme scenarios of a microgrid. Background Art

[0002] With the continuous increase in power load demand and the increasingly urgent demand for sustainable energy, microgrid technology, as a technology that can flexibly integrate new energy resources and improve the stability of the power system, has received widespread attention and application. Microgrids can not only achieve efficient access and coordinated operation of multiple distributed power sources, but also provide reliable power supply in extreme weather or power system failures. However, compared with the traditional method of calculating the theoretical power supply capacity mainly by studying the power generation characteristics of the power source, the grid structure of the transmission line will also affect the actual power supply capacity of the microgrid. It may be impossible to meet the power transmission demand of the power source to the node load due to the blockage of some lines, thereby overestimating the overall power supply capacity of the microgrid. Therefore, considering the impact of the grid structure on the power transmission of the microgrid and determining the actual power that the power source can supply to the node load is the basis for studying the power supply capacity of the microgrid.

[0003] At present, the evaluation of microgrid power supply capacity is mainly based on the power supply side, and the evaluation system is established from the perspective of expected power supply, load shedding rate and wind and solar power abandonment rate. There are few evaluation systems from the grid side about the impact of transmission line characteristics on microgrid power supply capacity. At the same time, in the existing microgrid power supply capacity calculation method, the main consideration is how much power each power source of the microgrid needs to provide in order to maintain the power balance of the system in normal scenarios, and less consideration is given to the maximum power that the microgrid can provide to each node load in extreme scenarios.

[0004] Therefore, under the premise of ensuring the power demand of important node loads, how to construct a power supply capacity calculation model for microgrids in extreme scenarios considering the grid structure is an urgent problem to be solved in the power system control scenario. Summary of the invention

[0005] In view of the above defects or improvement needs of the prior art, the present invention provides a method for constructing a power supply capacity calculation model for a microgrid under extreme scenarios, which aims to solve the technical problem of how to construct a power supply capacity calculation model for a microgrid under extreme scenarios taking into account the grid structure.

[0006] To achieve the above object, according to one aspect of the present invention, a method for constructing a power supply capacity calculation model in an extreme scenario of a microgrid is provided, comprising:

[0007] A1: Generate an extreme scenario of a microgrid corresponding to a continuous low power generation of new energy, and map the scenario probability of the extreme scenario of the microgrid to the load supply ratio of a preset load node;

[0008] A2: taking the product of the load supply ratio of the preset load node and the original load power as the required power of the preset load node;

[0009] A3: Determine the evaluation indicators of the microgrid power supply capacity, including node power supply reliability h1, node power supply capacity h2, grid transmission efficiency h3 and energy storage utilization rate h4;

[0010] A4: Taking the power supply reliability of the node, the power supply capacity of the node, the power transmission efficiency of the power grid and the maximum weighted value of the energy storage utilization rate as the objective function, and taking the actual power of the preset load node not less than the required power of the preset load node as the node load power supply constraint, a power supply capacity calculation model for the microgrid under extreme scenarios is constructed.

[0011] In one embodiment, the A1 comprises:

[0012] A11: Extract the scenario of continuous low power generation of new energy from the original power generation curve in the low power generation state;

[0013] A12: Determine the microgrid extreme scenario corresponding to the continuous low power generation of new energy from the continuous low power generation scenario of new energy;

[0014] A13: Map the scenario probability of the extreme scenario of the microgrid to the load supply ratio of the preset load node.

[0015] In one embodiment, the A12 comprises:

[0016] The K-means clustering algorithm is used to cluster the scenario of continuous low power generation of new energy. The extreme scenario of microgrid corresponding to continuous low power generation of new energy is expressed as:

[0017]

[0018] is the scenario of low power generation of new energy for consecutive days, d = 1 means the scenario of low power generation of new energy for two consecutive days, d = 2 means the scenario of low power generation of new energy for three consecutive days, and d = 3 means the scenario of low power generation of new energy for more than three consecutive days; K-means (·) is the clustering process; is the sth typical multi-day electricity scenario obtained by clustering, s∈[1,2,3]; is the scene probability corresponding to each scene,

[0019] In one of the embodiments, the node power supply reliability h1 is expressed as: h1=g1+m1g2; g1 and g2 are the node voltage margin and the node power generation margin respectively; m1 is the power supply reliability bias.

[0020] In one of the embodiments, the node power supply capacity h2 is expressed as: h2=θ1+m2θ2, θ1 and θ2 are the node power generation rate and load power supply rate respectively; m2 is the system preset load power supply bias.

[0021] In one embodiment, the power grid transmission efficiency h3 is expressed as: N L is the total number of transmission lines; P l , P l,max are the actual power and maximum power transmitted by the lth transmission line respectively.

[0022] In one embodiment, the energy storage utilization rate h4 is expressed as: T d The duration of the scenario of low renewable energy power generation for consecutive days; is the output power of the energy storage device at time t.

[0023] In one of the embodiments, the constraints of the power supply capacity calculation model under the extreme scenario of the microgrid also include: node power balance constraints, which require that the incoming power and the outgoing power of each node be balanced.

[0024] According to another aspect of the present invention, a method for calculating power supply capacity of a microgrid in an extreme scenario is provided, comprising:

[0025] The power supply capacity calculation model of the microgrid under extreme scenarios is used to construct a power supply capacity calculation model of the microgrid under extreme scenarios;

[0026] The extreme scenario of the microgrid corresponding to the current continuous low power generation of new energy is input into the power supply capacity calculation model under the extreme scenario of the microgrid to obtain the unit output and the transmission line transmission power, which are used to characterize the power supply capacity of the microgrid under the extreme scenario.

[0027] According to another aspect of the present invention, an electronic device is provided, comprising a memory and a processor, wherein the memory stores a computer program, and the processor implements the steps of the above method when executing the computer program.

[0028] In general, the above technical solutions conceived by the present invention can achieve the following beneficial effects compared with the prior art:

[0029] (1) The present invention provides a method for constructing a power supply capacity calculation model for a microgrid under extreme scenarios, which takes the maximum weighted value of the node power supply reliability, the node power supply capacity, the power transmission efficiency of the power grid and the energy storage utilization rate as the objective function, takes the maximum weighted value of the microgrid power supply capacity evaluation index as the goal, takes into account the output characteristics of the microgrid dispatchable units and energy storage equipment and the transmission line capacity, effectively optimizes the resource allocation of the microgrid, improves the safety and economy of power supply, and thus enhances the risk resistance and operation efficiency of the microgrid under extreme scenarios. Further, the actual power of the preset load node is not less than the required power of the preset load node as the node load power supply constraint, takes into account the maximum power constraint that the microgrid can provide to each node load under the extreme scenario of continuous low power generation of new energy, ensures that each link can still meet the actual load demand when the new energy power generation is insufficient, improves the system's ability to respond to extreme scenarios, improves the power supply reliability and stability of the microgrid, ensures the continuity and safety of power supply, and the power supply capacity calculation model finally constructed can accurately calculate the power supply capacity of the microgrid under extreme scenarios compared with the existing model.

[0030] (2) This scheme extracts the scenario of continuous low power generation of renewable energy from the original power generation curve in the low power generation state; it takes into account the power generation fluctuations under different meteorological conditions and time scales, and can provide a data basis for evaluating the power supply capacity and response measures of the power grid.

[0031] (3) This solution uses the K-means clustering algorithm to cluster the scenarios of continuous low power generation of new energy and the extreme microgrid scenarios corresponding to continuous low power generation of new energy. Compared with the existing scenario determination method, the K-means clustering algorithm is used to cluster the scenarios of continuous low power generation of new energy for multiple days, and the extreme typical scenarios of continuous low power generation of new energy are obtained. The operation is simple and the accuracy is high.

[0032] (4) The node power supply reliability h1 described in this scheme is expressed as: h1=g1+m1g2; compared with the existing node power supply reliability, the importance of each load node and its dynamic changes in the power system are taken into account, and the contribution of different load nodes to the grid stability can be more accurately evaluated.

[0033] (5) The node power supply capacity h2 described in this scheme is expressed as: h2 = θ1 + m2θ2; compared with the existing node power supply capacity, it takes into account the fluctuation of new energy, load change characteristics and meteorological influence, and can comprehensively evaluate the power supply flexibility of the node under different conditions.

[0034] (6) The power transmission efficiency h3 of the power grid described in this scheme is expressed as: Compared with the transmission efficiency of the existing power grid, the loss factors under various operating conditions are taken into account, which can fully reflect the actual performance and stability of the power grid under different loads.

[0035] (7) The energy storage utilization rate h4 described in this scheme is expressed as: Compared with the existing energy storage utilization rate, the effects of different working modes and environmental conditions on the charging and discharging of the energy storage system are taken into account, which can accurately evaluate the contribution and economy of the energy storage to the power system.

[0036] (8) The constraints of the power supply capacity calculation model for the microgrid under extreme scenarios described in this scheme also include: node power balance constraints, which require that the incoming power and outgoing power of each node be balanced; such a design takes into account the dynamic balance of power at each node under different load conditions, which can effectively prevent power shortages or surpluses and ensure the quality and continuity of power supply. BRIEF DESCRIPTION OF THE DRAWINGS

[0037] Figure 1 It is a flowchart of a method for constructing a power supply capacity calculation model for a microgrid under extreme scenarios provided in Example 1 of the present invention. DETAILED DESCRIPTION

[0038] In order to make the purpose, technical solutions and advantages of the present invention more clearly understood, the present invention is further described in detail below in conjunction with the accompanying drawings and embodiments. It should be understood that the specific embodiments described herein are only used to explain the present invention and are not intended to limit the present invention. In addition, the technical features involved in the various embodiments of the present invention described below can be combined with each other as long as they do not conflict with each other.

[0039] Example 1

[0040] like Figure 1 As shown, this embodiment provides a method for constructing a power supply capacity calculation model under extreme scenarios of a microgrid, including: A1: generating an extreme scenario of a microgrid corresponding to continuous low power generation of new energy, and mapping the scenario probability of the extreme scenario of the microgrid to the load supply ratio of a preset load node; A2: taking the product of the load supply ratio of the preset load node and the original power of the load as the required power of the preset load node; A3: determining the evaluation index of the power supply capacity of the microgrid, including the node power supply reliability h1, the node power supply capacity h2, the power grid transmission efficiency h3 and the energy storage utilization rate h4; A4: taking the maximum weighted value of the node power supply reliability, the node power supply capacity, the power grid transmission efficiency and the energy storage utilization rate as the objective function, and taking the actual power of the preset load node not less than the required power of the preset load node as the node load power supply constraint, to construct a power supply capacity calculation model under extreme scenarios of the microgrid. Among them, the preset load node refers to an important load node, for example, it can be an industrial load such as a steel plant, a chemical plant, an infrastructure load such as a transportation hub, a hospital, a school, a public utility load such as a water plant, a sewage treatment plant, and a communication data load such as a base station and computer equipment.

[0041] Specifically, the microgrid power supply capacity calculation model under extreme scenarios aims to maximize the weighted values ​​of node power supply reliability, node power supply capacity, grid transmission efficiency, and energy storage utilization, and its expression is: In the formula, β i is the indicator weight of the ith indicator. Regarding the node load power supply constraint, due to the existence of important loads, the actual power of the node with important loads cannot be lower than the required power of the important loads. The expression is: When there is no significant load on the node, At this time, the actual power of the node load is the additional power supply capacity of the microgrid.

[0042] It should be understood that although Figure 1 The steps in the flowchart are shown in sequence as indicated by the arrows, but these steps are not necessarily executed in the order indicated by the arrows. Unless otherwise specified in this document, there is no strict order restriction for the execution of these steps, and these steps can be executed in other orders. Moreover, Figure 1 At least part of the steps may include multiple sub-steps or multiple stages. These sub-steps or stages are not necessarily executed at the same time, but can be executed at different times. The execution order of these sub-steps or stages is not necessarily sequential, but can be executed in turn or alternately with other steps or at least part of the sub-steps or stages of other steps.

[0043] As a preferred implementation, A1 includes: A11: extracting a scenario of continuous low power generation of new energy from the original power generation curve of the low power generation state, wherein the average power generation of new energy for multiple consecutive days can be defined. Below rated power generation When the power grid is considered to be in a low power generation state when the power grid is in a low power generation state, A12: Determine the microgrid extreme scenario corresponding to the continuous low power generation of new energy from the scenario of continuous low power generation of new energy; A13: Map the scenario probability of the microgrid extreme scenario to the load supply ratio of the preset load node, and the scenario probability of the above microgrid extreme scenario According to the demand for important load supply in the extreme typical scenario of continuous low power generation of each new energy source, the important load supply ratio is mapped, and its expression is: In the formula, The supply ratio of important loads corresponding to each scenario.

[0044] As a preferred implementation, A12 includes: using a K-means clustering algorithm to cluster the scenario of continuous low power generation of new energy sources. The extreme scenario of the microgrid corresponding to the continuous low power generation of new energy sources is expressed as follows: is the scenario of low power generation of new energy for consecutive days, d = 1 means the scenario of low power generation of new energy for two consecutive days, d = 2 means the scenario of low power generation of new energy for three consecutive days, and d = 3 means the scenario of low power generation of new energy for more than three consecutive days; K-means (·) is the clustering process; is the sth typical multi-day electricity scenario obtained by clustering, s∈[1,2,3]; is the scene probability corresponding to each scene,

[0045] As a preferred implementation, the node power supply reliability h1 is expressed as: h1=g1+m1g2; g1 and g2 are the node voltage margin and the node power generation margin respectively; m1 is the power supply reliability bias, m1 is the power supply reliability bias, m1∈[0.5,1.5], when m1 is between 0.5 and 1.0, it means that the node voltage margin is emphasized, and when m1 is between 1.0 and 1.5, it means that the node power generation margin is emphasized. The calculation formulas for the node voltage margin and the node power generation margin g1 and g2 are:

[0046]

[0047] Where N E 、N G are the total number of points and the total number of power generation nodes in the microgrid grid structure respectively; k j is the weight ratio of the jth node; is the voltage margin of the jth node; P j is the power output power of the jth node; P j,max is the maximum power output of the jth node.

[0048] As a preferred implementation, the node power supply capacity h2 is expressed as: h2=θ1+m2θ2, θ1 and θ2 are the node power generation rate and load power supply rate respectively; m2 is the system preset load power supply bias, m2∈[0.5,1.5], when m2 takes a value between 0.5 and 1.0, it means that the focus is on maximizing the system power generation, when m2 takes a value between 1.0 and 1.5, it means that the focus is on ensuring the power supply of important loads, and usually m2 takes 1.0.

[0049] It should be noted that the calculation formulas for the node power generation rate and the load power supply rate θ1, θ2 are:

[0050]

[0051] Where N I is the total number of load nodes in the microgrid grid structure; L j is the actual load power of the jth node; is the original load power of the jth node.

[0052] As a preferred implementation, the power grid transmission efficiency h3 is expressed as: N L is the total number of transmission lines; P l , P l,max are the actual power and maximum power transmitted by the lth transmission line respectively.

[0053] As a preferred implementation, the energy storage utilization rate h4 is expressed as: T d The duration of the scenario of low renewable energy power generation for consecutive days; is the output power of the energy storage device at time t.

[0054] As a preferred implementation, the constraints of the power supply capacity calculation model under extreme scenarios of the microgrid also include: node power balance constraints, which require that the incoming power and outgoing power of each node be balanced, and the expression is: Where P l + , P l - They are the incoming and outgoing power of the lth transmission line to the jth node. Furthermore, the upper and lower limits of the adjustable power output, the upper and lower limits of the energy storage device output, the capacity constraints of the energy storage device, and the capacity constraints of the transmission line can be comprehensively considered to establish a more accurate power supply capacity calculation model for microgrids in extreme scenarios.

[0055] Example 2

[0056] The present embodiment provides a method for calculating the power supply capacity of a microgrid under extreme scenarios, including: using the power supply capacity calculation model for the microgrid under extreme scenarios provided in Example 1 to construct a power supply capacity calculation model for the microgrid under extreme scenarios; inputting the microgrid extreme scenario corresponding to the current continuous low power generation of new energy into the power supply capacity calculation model for the microgrid under extreme scenarios, and obtaining the unit output and the transmission power of the transmission line to characterize the power supply capacity of the microgrid under extreme scenarios; wherein the microgrid extreme scenario refers to a series of parameters, which constitute a scenario.

[0057] Example 3

[0058] This embodiment provides an electronic device, including a memory and a processor, wherein the memory stores a computer program, and the processor implements the steps of the above method when executing the computer program.

[0059] It will be easily understood by those skilled in the art that the above description is only a preferred embodiment of the present invention and is not intended to limit the present invention. Any modifications, equivalent substitutions and improvements made within the spirit and principles of the present invention should be included in the protection scope of the present invention.

Claims

1. A method for constructing a power supply capacity calculation model for a microgrid under extreme scenarios, characterized in that: include: A1: Generate a microgrid extreme scenario corresponding to continuous low power generation of new energy, and map the scenario probability of the microgrid extreme scenario to the load supply ratio of the preset load node; A2: taking the product of the load supply ratio of the preset load node and the original load power as the required power of the preset load node; A3: Determine the evaluation indicators of the microgrid power supply capacity, including node power supply reliability h1, node power supply capacity h2, grid transmission efficiency h3 and energy storage utilization rate h4; A4: Taking the power supply reliability of the node, the power supply capacity of the node, the power transmission efficiency of the power grid and the maximum weighted value of the energy storage utilization rate as the objective function, and taking the actual power of the preset load node not less than the required power of the preset load node as the node load power supply constraint, a power supply capacity calculation model for the microgrid under extreme scenarios is constructed.

2. The method for constructing a power supply capacity calculation model for a microgrid under extreme scenarios as claimed in claim 1, characterized in that: The A1 includes: A11: Extract the scenario of continuous low power generation of new energy from the original power generation curve in the low power generation state; A12: Determine the microgrid extreme scenario corresponding to the continuous low power generation of new energy from the continuous low power generation scenario of new energy; A13: Map the scenario probability of the extreme scenario of the microgrid to the load supply ratio of the preset load node.

3. The method for constructing a power supply capacity calculation model for a microgrid under extreme scenarios as claimed in claim 2, characterized in that: The A12 includes: The K-means clustering algorithm is used to cluster the scenario of continuous low power generation of new energy. The extreme scenario of microgrid corresponding to continuous low power generation of new energy is expressed as: is the scenario of low power generation of new energy for consecutive days, d = 1 means the scenario of low power generation of new energy for two consecutive days, d = 2 means the scenario of low power generation of new energy for three consecutive days, and d = 3 means the scenario of low power generation of new energy for more than three consecutive days; K-means (·) is the clustering process; is the sth typical multi-day electricity scenario obtained by clustering, s∈[1,2,3]; is the scene probability corresponding to each scene, 4. The method for constructing a power supply capacity calculation model for a microgrid under extreme scenarios as claimed in claim 1, characterized in that: The node power supply reliability h1 is expressed as: h1=g1+m1g2; g1 and g2 are the node voltage margin and the node power generation margin respectively; m1 is the power supply reliability bias.

5. The method for constructing a power supply capacity calculation model for a microgrid under extreme scenarios as claimed in claim 1, characterized in that: The node power supply capacity h2 is expressed as: h2=θ1+m2θ2, θ1 and θ2 are the node power generation rate and load power supply rate respectively; m2 is the system preset load power supply bias.

6. The method for constructing a power supply capacity calculation model for a microgrid under extreme scenarios as claimed in claim 1, characterized in that: The power grid transmission efficiency h3 is expressed as: N L is the total number of transmission lines; P l , P l,max are the actual power and maximum power transmitted by the lth transmission line respectively.

7. The method for constructing a power supply capacity calculation model for a microgrid under extreme scenarios as claimed in claim 1, characterized in that: The energy storage utilization rate h4 is expressed as: T d The duration of the scenario of low renewable energy power generation for consecutive days; is the output power of the energy storage device at time t.

8. The method for constructing a power supply capacity calculation model for a microgrid in extreme scenarios according to any one of claims 1 to 7, characterized in that: The constraints of the power supply capacity calculation model under the extreme scenario of the microgrid also include: node power balance constraints, which require that the incoming power and outgoing power of each node be balanced.

9. A method for calculating power supply capacity of a microgrid under extreme scenarios, characterized in that: include: A power supply capacity calculation model for a microgrid in extreme scenarios is constructed using the power supply capacity calculation model for a microgrid in extreme scenarios as described in any one of claims 1 to 8; The extreme scenario of the microgrid corresponding to the current continuous low power generation of new energy is input into the power supply capacity calculation model under the extreme scenario of the microgrid to obtain the unit output and the transmission line transmission power, which are used to characterize the power supply capacity of the microgrid under the extreme scenario.

10. An electronic device comprising a memory and a processor, wherein the memory stores a computer program, wherein: When the processor executes the computer program, the steps of the method according to any one of claims 1 to 9 are implemented.

Images