A power grid dynamic operation method and device based on seasonal scenes and a storage medium

Abstract

This application relates to a method, apparatus, and storage medium for dynamic operation of a power grid based on seasonal scenarios. The dynamic operation includes: constructing a power topology model of a flexible microgrid; obtaining operational data for each grid partition on a target day of the current seasonal scenario; determining update indicators for each grid partition based on the operational data; adjusting the operational status of energy storage devices and the on / off states of remote control switches according to the comparison results of each update indicator with a preset update threshold; determining the grid partition structure; using the grid partition structure and the operational status of the energy storage devices as the initial partition configuration for the next seasonal scenario; and again adjusting the energy storage devices and remote control switches according to the update indicators; and adjusting the operational status of the power topology model in each seasonal scenario, using the current seasonal scenario and the next seasonal scenario respectively. This application improves the power grid's ability to dynamically operate under different seasonal scenarios.

Description

Technical Field

[0001] This application relates to the field of control technology, and in particular to a method, apparatus and storage medium for dynamic operation of power grids based on seasonal scenarios. Background Technology

[0002] A flexible microgrid is a microgrid system characterized by high flexibility, controllability, and intelligence. It can flexibly respond to load changes, renewable energy fluctuations, and changes in the external power grid, thereby achieving a highly reliable, efficient, and low-carbon energy supply.

[0003] In existing technologies, the operation of flexible microgrids focuses on fault recovery and power dispatch in extreme scenarios, adjusting the grid partition structure according to resource changes in extreme situations to achieve power restoration. However, in conventional scenarios with seasonal changes, flexible microgrids typically only adjust the grid partition structure at fixed time intervals, neglecting resource changes within the grid partition and the responsiveness of resources. Therefore, how to enable flexible microgrids to adapt to resource changes in seasonal scenarios has become an urgent problem to be solved. Summary of the Invention

[0004] This application provides a method, apparatus, and storage medium for dynamic operation of power grids based on seasonal scenarios, in order to at least address the problem in the related art of how power grids can adapt to resource changes in different seasonal scenarios.

[0005] In a first aspect, embodiments of this application provide a method for dynamic operation of a power grid based on seasonal scenarios, including:

[0006] Based on the spatial distribution characteristics of energy storage devices, distributed power sources, seasonal loads, and remote control switches, as well as power constraints, a power topology model for a flexible microgrid is constructed. The power topology model includes several grid partitions, and the boundaries of the grid partitions are controlled by the remote control switches.

[0007] On the target day of the current seasonal scenario, the operating data of each power grid partition is obtained within a preset duration and at preset time intervals.

[0008] Based on the operating data, update indicators for each power grid partition are determined, each update indicator is compared with a preset update threshold, and the operating status of the energy storage device and the on / off status of the remote control switch are adjusted based on the comparison results to determine the power grid partition structure.

[0009] The power grid partitioning structure and the operating status of the energy storage device are used as the initial partitioning configuration for the next seasonal scenario. On the target day of the next seasonal scenario, the updated indicators are obtained again, and the energy storage device and the remote control switch are adjusted according to the updated indicators.

[0010] For any two adjacent seasonal scenarios, which are respectively designated as the current seasonal scenario and the next seasonal scenario, the operating state of the power topology model in each seasonal scenario is adjusted.

[0011] In one embodiment, comparing each update index with a preset update threshold, adjusting the operating state of the energy storage device and the on / off state of the remote control switch based on the comparison results, and determining the grid zoning structure includes:

[0012] Compare each of the update metrics with the preset update threshold;

[0013] When the update index is greater than the preset update threshold, the operating status of the energy storage device and the on / off status of the remote control switch in the power grid partition mapped by the update index are adjusted.

[0014] When the update index is less than or equal to the preset update threshold, the operating status of the energy storage device and the on / off status of the remote control switch in the power grid partition mapped by the update index are maintained.

[0015] Based on the open / closed state of each of the remote control switches, the boundaries of all the power grid partitions are updated, and the power grid partition structure is determined based on the updated power grid partitions.

[0016] In one embodiment, the update metric satisfies the following configuration:

[0017] The updated indicators include comprehensive operational items and seasonal load items;

[0018] The updated index is obtained by multiplying the comprehensive operation item and the seasonal load item by weighting coefficients and then adding them together.

[0019] In one embodiment, the integrated operation item and the seasonal load item satisfy the following configuration:

[0020] The comprehensive operation item includes the line loss cost within the power grid zone and the total cost of the distributed power source;

[0021] The seasonal load item includes a seasonal importance index in the current seasonal scenario.

[0022] In one embodiment, obtaining the operating data of each power grid partition at preset time intervals within a preset duration includes:

[0023] Within the preset duration, power flow calculations and operational calculations are performed on each power grid section according to the preset time intervals to obtain operational data for each power grid section.

[0024] In one embodiment, the power grid partition is specifically configured as follows:

[0025] Any of the aforementioned power grid zones includes one of the aforementioned energy storage devices, several of the aforementioned distributed power sources, and several of the aforementioned seasonal loads;

[0026] Any two of the power grid zones are connected via the remote control switch.

[0027] In one embodiment, the power constraint condition is specifically configured as follows:

[0028] The power constraints include scenario constraints, remote control switch constraints, long-term and short-term energy storage constraints, hybrid energy storage operation constraints, nodal power injection constraints, and power flow constraints.

[0029] Secondly, embodiments of this application provide a power grid dynamic operation device based on seasonal scenarios, comprising:

[0030] The model building module is used to construct a power topology model of a flexible microgrid based on the spatial distribution characteristics of energy storage devices, distributed power sources, seasonal loads, and remote control switches, as well as power constraints. The power topology model includes several grid partitions, and the boundaries of the grid partitions are controlled by the remote control switches.

[0031] The operation data acquisition module is used to obtain the operation data of each power grid partition within a preset time period on a target day in the current seasonal scenario.

[0032] The first update module is used to determine the update index of each power grid partition based on the operating data, compare each update index with a preset update threshold, adjust the operating status of the energy storage device and the on / off status of the remote control switch based on the comparison result, and determine the power grid partition structure.

[0033] The second update module is used to take the power grid partition structure and the operating status of the energy storage device as the initial partition configuration for the next seasonal scenario, obtain the update index again on the target day of the next seasonal scenario, and adjust the energy storage device and the remote control switch according to the update index.

[0034] The dynamic adjustment module is used to adjust the operating state of the power topology model in each of the two adjacent seasonal scenarios, which are respectively the current seasonal scenario and the next seasonal scenario.

[0035] Thirdly, embodiments of this application provide an electronic device, including a memory, a processor, and a computer program stored in the memory and executable on the processor. When the processor executes the computer program, it implements the power grid dynamic operation method based on seasonal scenarios as described in the first aspect above.

[0036] Fourthly, embodiments of this application provide a computer-readable storage medium having a computer program stored thereon, which, when executed by a processor, implements the power grid dynamic operation method based on seasonal scenarios as described in the first aspect above.

[0037] The power grid dynamic operation method, apparatus, and storage medium based on seasonal scenarios provided in this application have at least the following technical effects:

[0038] A power topology model of a flexible microgrid is constructed. Based on the operational data obtained from the target day of the current seasonal scenario, update indicators are determined. The update indicators are compared with preset update thresholds. Based on the comparison results, the boundaries of the grid partitions are updated to determine the grid partition structure. The updated grid partition structure is used as the initial partition configuration for the next seasonal scenario to obtain update indicators again, so as to adjust energy storage devices and remote control switches, and determine the grid partitions again. In this way, the operating status of the grid can be adjusted in each seasonal scenario by adjusting energy storage devices and remote control switches based on the comparison results with preset update thresholds, so that the grid can adapt to different seasonal scenarios and make dynamic adjustments.

[0039] Details of one or more embodiments of this application are set forth in the following drawings and description to make other features, objects and advantages of this application more readily apparent. Attached Figure Description

[0040] The accompanying drawings, which are included to provide a further understanding of this application and form part of this application, illustrate exemplary embodiments and are used to explain this application, but do not constitute an undue limitation of this application. In the drawings:

[0041] Figure 1 This is a flowchart illustrating a dynamic power grid operation method based on a seasonal scenario, according to an exemplary embodiment.

[0042] Figure 2 This is a schematic diagram of an electrical topology model according to an exemplary embodiment;

[0043] Figure 3 This is a schematic diagram illustrating the iterative updating of power grid partitions in different seasonal scenarios according to an exemplary embodiment;

[0044] Figure 4 This is a schematic diagram illustrating the charging and discharging power and energy storage value curves of a short-term energy storage device in a power grid section, according to an exemplary embodiment.

[0045] Figure 5 This is a schematic diagram illustrating the charging and discharging power and energy storage value curves of a long-term energy storage device in a power grid section, according to an exemplary embodiment.

[0046] Figure 6This is a schematic diagram of a power grid dynamic operation device based on a seasonal scenario, according to an exemplary embodiment.

[0047] Figure 7 This is a block diagram of an electronic device according to an exemplary embodiment. Detailed Implementation

[0048] To make the objectives, technical solutions, and advantages of this application clearer, the application is described and illustrated below with reference to the accompanying drawings and embodiments. It should be understood that the specific embodiments described herein are merely illustrative and not intended to limit the scope of this application. All other embodiments obtained by those skilled in the art based on the embodiments provided in this application without inventive effort are within the scope of protection of this application.

[0049] Obviously, the accompanying drawings described below are merely some examples or embodiments of this application. Those skilled in the art can apply this application to other similar scenarios based on these drawings without any inventive effort. Furthermore, it is understood that although the efforts made in this development process may be complex and lengthy, for those skilled in the art related to the content disclosed in this application, any changes to design, manufacturing, or production based on the technical content disclosed in this application are merely conventional technical means and should not be construed as insufficient disclosure of the content of this application.

[0050] In this application, the reference to "embodiment" means that a specific feature, structure, or characteristic described in connection with an embodiment may be included in at least one embodiment of this application. The appearance of this phrase in various places in the specification does not necessarily refer to the same embodiment, nor is it a separate or alternative embodiment that is mutually exclusive with other embodiments. It will be explicitly and implicitly understood by those skilled in the art that the embodiments described in this application may be combined with other embodiments without conflict.

[0051] Unless otherwise defined, the technical or scientific terms used in this application shall have the ordinary meaning understood by one of ordinary skill in the art to which this application pertains. The terms “a,” “an,” “an,” “the,” and similar words used in this application do not indicate quantity limitation and may indicate singular or plural. The terms “comprising,” “including,” “having,” and any variations thereof used in this application are intended to cover non-exclusive inclusion; for example, a process, method, system, product, or device that includes a series of steps or modules (units) is not limited to the listed steps or units, but may also include steps or units not listed, or may include other steps or units inherent to these processes, methods, products, or devices. The terms “connected,” “linked,” “coupled,” and similar words used in this application are not limited to physical or mechanical connections, but may include electrical connections, whether direct or indirect. “Multiple” used in this application refers to two or more. “And / or” describes the relationship between related objects, indicating that three relationships may exist; for example, “A and / or B” can represent: A alone, A and B simultaneously, and B alone. The character " / " generally indicates that the preceding and following objects are in an "or" relationship. The terms "first," "second," and "third" used in this application are merely to distinguish similar objects and do not represent a specific ordering of the objects.

[0052] Firstly, embodiments of this application provide a method for dynamic operation of a power grid based on seasonal scenarios. Figure 1 This is a flowchart illustrating a dynamic power grid operation method based on seasonal scenarios, according to an exemplary embodiment, such as... Figure 1 As shown, the power grid dynamic operation method based on seasonal scenarios includes:

[0053] Step S101: Based on the spatial distribution characteristics of energy storage devices, distributed power sources, seasonal loads, and remote control switches, as well as power constraints, construct a power topology model for a flexible microgrid. The power topology model includes several grid partitions, and the boundaries of the grid partitions are controlled by remote control switches.

[0054] The spatial distribution characteristics of energy storage devices, distributed power sources, seasonal loads, and remote control switches represent the spatial distribution of each device. Furthermore, basic data and device parameters are required when constructing the power topology model. Basic data includes line parameters, load parameters, and seasonal load node importance indices. Device parameters include those for long-term and short-term hybrid energy storage devices. Based on the spatial distribution characteristics and power constraints, a power topology model for a flexible microgrid is constructed.

[0055] In the power topology model, each energy storage device, distributed generation source, seasonal load, and remote control switch is considered a node. The model includes several grid sections, each with its boundary controlled by a remote control switch. Each grid section comprises one energy storage device, several distributed generation sources, and several seasonal loads. Any two grid sections are connected via a remote control switch. It should be noted that the remote control switch generally does not cross the location of the energy storage device. Distributed generation sources and seasonal loads are located at the boundary between any two grid sections. The distributed generation sources are uncontrollable, and the energy storage devices include long-term energy storage devices, short-term energy storage devices, and hybrid long- and short-term energy storage devices.

[0056] Figure 2 This is a schematic diagram of an electrical topology model according to an exemplary embodiment, such as... Figure 2 As shown, the seasonal scenario includes nine grid zones, namely Zone 1 to Zone 9. Each grid zone includes an energy storage device, several distributed power sources, and several seasonal loads.

[0057] The power constraints include scenario constraints, remote control switching constraints, long- and short-term energy storage constraints, hybrid energy storage operation constraints, nodal power injection constraints, and power flow constraints. Each constraint specifically satisfies the following:

[0058] The scenario constraints satisfy the following formula:

[0059]

[0060]

[0061]

[0062]

[0063] in, For node partitioning variables under scene bs, These are location parameters for hybrid long-term and short-term energy storage. For line partitioning variables under scenario bs, This refers to the state variables of the line switches in scenario bs.

[0064] The constraints of the remote control switch satisfy the following formula:

[0065]

[0066] in, For the line switch state variables in scenario bs, This is the position parameter for the remote control switch. 'l' represents the index number of the remote control switch, indicating that the position of each remote control switch in the system is checked one by one.

[0067] The short-term energy storage constraints satisfy the following formula:

[0068] ,

[0069] ,

[0070] ,

[0071] ,

[0072] ,

[0073] in, , , These represent the energy storage value, charging power, and discharging power of the short-term energy storage device at time t under scenario bs, respectively. For charging and discharging state variables, , For charging efficiency and discharging efficiency. , These are the configuration capacity and capacity multiplier, respectively. For time step.

[0074] Long-term energy storage constraints satisfy the following formula:

[0075] ,

[0076] ,

[0077] ,

[0078] ,

[0079] ,

[0080] in, , , These represent the energy storage value, charging power, and discharging power of the long-term energy storage device at time t under scenario bs, respectively. , , These are self-release rate, charging efficiency, and discharging efficiency, respectively. , This represents the configuration capacity and energy rate. , Let be the charging state variables and discharging state variables at time t under scenario bs. Let BS be the probability of scene bs-1 occurring, where BS is the total number of scenes.

[0081] Hybrid energy storage operation constraints satisfy the following formula:

[0082] ,

[0083] ,

[0084] ,

[0085] ,

[0086] in, , Let i represent the charging power and discharging power of the hybrid long-term and short-term energy storage device at time t under scenario bs, respectively. , , , Let represent the charging and discharging power of the short-term energy storage device and the charging and discharging power of the long-term energy storage device at node i at time t under scenario bs, respectively. , , , These represent the upper and lower limits of charging power and discharging power for the short-term energy storage device at node i, respectively. , , , These represent the upper and lower limits of charging power and discharging power for the long-term energy storage device at node i, respectively. , , , Let represent the reactive power corresponding to the charging and discharging power of the short-term energy storage device and the reactive power corresponding to the charging and discharging power of the long-term energy storage device at node i at time t under scenario bs, respectively.

[0087] The power injection constraints satisfy the following formula:

[0088]

[0089] in, , Let represent the active and reactive power injections of all power sources at node i at time t under scenario bs, respectively. , This represents the active and reactive power output of the distributed power source connected to node i at time t under scenario bs.

[0090] Power flow constraints satisfy the following formula:

[0091] ,

[0092] ,

[0093] ,

[0094] ,

[0095] Among them, P ij and Q ij Let (i,j) represent the active power flow and reactive power flow of line (i,j). R is the square of the current amplitude in line (i,j). ij X ij and Z ij Let b represent the resistance, reactance, and impedance values ​​of line (i,j), respectively. ij These are slack variables.

[0096] Following step S101, a power topology model was constructed based on the spatial distribution characteristics of energy storage devices, distributed power sources, seasonal loads, and remote control switches, as well as power constraints. This model is designed to adjust the grid partitions through remote control switches according to the differences in different scenarios, and to regulate the energy balance during the switching of different scenarios through energy storage devices, thus providing a foundation for the dynamic operation of the power grid in the future.

[0097] Step S102: On the target day of the current seasonal scenario, obtain the operating data of each power grid partition within a preset time interval and within a preset duration.

[0098] Within the target day of the current seasonal scenario, and within a preset duration, power flow calculations and operational calculations are performed on each power grid partition at preset time intervals to obtain operational data for each power grid partition. This operational data includes the energy storage value of long-term energy storage devices, the energy storage value of short-term energy storage devices, charging and discharging power, active power injected into the grid, reactive power injected into the grid, and current.

[0099] In one embodiment, the target day is a typical day for the current seasonal scenario, and a typical day is a date that reflects the key characteristics of the current season. The target day is preset to have a duration of 24 hours, with a time interval of 1 hour. That is, every hour on the target day, power flow calculations and operational calculations are performed on each power grid partition to obtain operational data for each power grid partition.

[0100] The operational data for each power grid zone reflects the load consumption, power supply, and energy storage device charging and discharging status within that zone. This data helps determine the specific situation within the current power grid zone, providing a basis for subsequent dynamic adjustments to the power grid.

[0101] Step S103: Determine the update index for each power grid partition based on the operating data, compare each update index with the preset update threshold, adjust the operating status of the energy storage device and the on / off status of the remote control switch based on the comparison results, and determine the power grid partition structure.

[0102] Based on the operational data of each power grid partition, update indicators for each partition are determined. Each update indicator is compared with a preset update threshold, and the operational status of energy storage devices within each partition is adjusted according to the comparison results. This includes the charging and discharging status, as well as the on / off status of remote control switches. Changing a remote control switch from an open to a closed state is equivalent to expanding the boundary of the power grid partition outwards. Changing a remote control switch from a closed to an open state is equivalent to shrinking the boundary of the power grid partition inwards. There are also cases where the boundary of the power grid partition remains unchanged. Therefore, based on the updated power grid partitions, a new power grid partition structure in the power topology model can be determined.

[0103] The updated indicators include a comprehensive operational item and a seasonal load item. The updated indicators are obtained by multiplying the comprehensive operational item and the seasonal load item by their respective weighting factors and then summing them. The updated indicators satisfy the following formula:

[0104]

[0105] in, It's about updating the metrics. As a comprehensive operation item, For seasonal load items, These are the weighting coefficients.

[0106] The overall operation items satisfy the following formula:

[0107]

[0108]

[0109] in, As a comprehensive operation item, , These are the costs of line network losses and the total cost of distributed power sources, respectively. This is the cost coefficient. It contributes to the unit's power output.

[0110] The seasonal load term satisfies the following formula:

[0111]

[0112] in, For seasonal load items, Let be the importance index of the seasonal load of node i in scenario bs, and E be the mathematical expectation operator used to calculate the mean of the quantities within the parentheses.

[0113] Continuing with step S103, the updated indicators are compared with the preset update thresholds, and the operating status of the energy storage device and the on / off status of the remote control switch are adjusted according to the comparison structure. Specifically, this includes:

[0114] Each update indicator is compared with a preset update threshold. When an update indicator is greater than the preset update threshold, the operating status of the energy storage device and the on / off status of the remote control switch in the power grid partition mapped by the update indicator are adjusted.

[0115] When the update index exceeds the preset update threshold, it indicates that the load consumption within the grid zone mapped by the update index has shifted spatiotemporally with seasonal changes, and that the output fluctuations of distributed power sources have also changed significantly, causing a noticeable fluctuation in the previously balanced power supply within the grid zone. Therefore, adjusting the operating status of energy storage devices and the on / off states of remote control switches within the grid zone mapped by the update index, changing the charging and discharging states of the energy storage devices, and determining whether to absorb or remove seasonal loads through the on / off states of remote control switches are crucial to maintaining energy balance within the grid zone and ensuring stable grid operation.

[0116] When the update index is less than or equal to the preset update threshold, the operating status of the energy storage device and the on / off status of the remote control switch in the power grid partition mapped by the update index are maintained.

[0117] When the update index is less than or equal to the preset update threshold, it means that seasonal changes have little impact on energy storage devices and distributed power sources within the grid partition mapped by the update index. The grid partition can still maintain energy balance, making the grid operation stable. Therefore, there is no need to adjust the boundary of the grid partition.

[0118] Update the boundaries of all power grid zones based on the on / off status of each remote control switch, and determine the power grid zone structure based on the updated power grid zones.

[0119] After comparing the update index of each power grid partition with the preset update threshold, the operating status of the energy storage device and the on / off state of the remote control switch are adjusted according to the comparison results, thereby updating the boundaries of all power grid partitions. Based on the updated power grid partitions, the power topology model for the current seasonal scenario determines a new power grid partition structure, which serves as the initial partition configuration for the next seasonal scenario.

[0120] Continuing with step S103, update indicators for the current seasonal scenario are determined based on operational data. This enables unified quantification of seasonal load importance changes, distributed generation output fluctuations, and grid operating status, allowing for differentiated responses to different seasonal scenarios. This allows the microgrid to adjust to seasonal load migration and energy fluctuation characteristics, providing adaptability to various seasonal scenarios. Furthermore, by comparing the update indicators with preset update thresholds, grid partitions are adjusted when the update indicators exceed the preset thresholds. This achieves the "update only when necessary" operating principle, avoiding redundant switching operations caused by updating grid partitions at fixed intervals. This reduces the number of remote control switches, extends their lifespan, lowers switching costs, and reduces grid operation disturbances.

[0121] Step S104: Use the grid partition structure and the operating status of the energy storage device as the initial partition configuration for the next seasonal scenario. On the target day of the next seasonal scenario, obtain the updated indicators again and adjust the energy storage device and remote control switch according to the updated indicators.

[0122] The grid partitioning structure and the operating status of energy storage devices are used as the initial partitioning configuration for the next seasonal scenario. On the target day of the next seasonal scenario, the operating data for the next seasonal scenario are determined based on the initial partitioning configuration. Update indicators are obtained again based on the operating data, and the update indicators are compared with preset update thresholds. Based on the comparison results, the operating status of energy storage devices and the on / off state of remote control switches are adjusted to update the grid partitioning again and obtain a new grid partitioning structure.

[0123] Step S105: For any two adjacent seasonal scenarios, respectively designated as the current seasonal scenario and the next seasonal scenario, adjust the operating state of the power topology model in each seasonal scenario.

[0124] For any two adjacent seasonal scenarios, the current seasonal scenario and the next seasonal scenario are determined according to the seasonal order of spring, summer, autumn and winter. According to the content of steps S102 to S104, as the seasonal scenarios are updated, the operating state of the power topology model in each seasonal scenario is adjusted, that is, the operating state of the energy storage device and the opening and closing state of the remote control switch, so as to adjust the boundaries of different power grid partitions, so that the power grid partition structure is adapted to each seasonal scenario, thereby realizing the dynamic operation of the power grid in different seasonal scenarios.

[0125] Figure 3 This is a schematic diagram illustrating the iterative updates of power grid partitions in different seasonal scenarios according to an exemplary embodiment, such as... Figure 3As shown, BS1, BS2, BS3, and BS4 are seasonal scenarios arranged in seasonal order, and each scenario contains nine power grid partitions, namely regions 1 to 9. The parameters of the seasonal load satisfy Tables 1 and 2. Using a typical day for each seasonal scenario as the target day, with a time interval of 1 hour and each typical day being 24 hours, the four scenarios total 96 hours. The power topology model is solved using the Gurobi solver to obtain the update indices for each power grid partition. The update indices reflect the economic efficiency of power grid operation and the differences in load importance; the smaller the update index value, the better the power grid operation. Table 3 shows the corresponding values ​​of the update indices for the two operating modes. As shown in Table 3, the update index of the partitioned update operation mode is smaller than that of the non-partitioned update operation mode. Furthermore, the update indices can be used to determine the optimized non-partitioned update operation mode of the power grid based on the partitioned update operation model, with the largest optimization magnitude observed in power grid partitions 2 and 8. In scenarios 2, 3, and 4, the update indicators for grid partition 2 were reduced by 21.0%, 38.1%, and 31.7% respectively compared to the grid-unpartitioned operation mode. Similarly, in scenarios 2, 3, and 4, the update indicators for grid partition 8 were reduced by 56.9%, 45.1%, and 36.6% respectively compared to the grid-unpartitioned operation mode. Therefore, the partitioned update operation mode enables the power grid to better adapt to seasonal scenario updates.

[0126] Continue to refer to Figure 3 As shown in Table 3, there are many remote control switches in the other adjacent power grid zones of power grid zone 2 and power grid zone 8. By controlling the opening and closing status of the remote control switches, the adjustment range of seasonal loads and distributed power sources can be expanded, thereby improving the flexibility within the power grid zone and providing a larger buffer space within the power grid zone to smooth out internal fluctuations and maintain the stable operation of the power grid zone.

[0127] Table 1 Seasonal Load Parameters

[0128]

[0129] Table 2 Parameters of the power topology model

[0130]

[0131] Table 3 Comparison of Updated Indicators

[0132]

[0133] In another embodiment, Figure 4 This is a schematic diagram illustrating the charging and discharging power and energy storage value curves of a short-term energy storage device in a power grid section, according to an exemplary embodiment. Figure 4As shown, short-term energy storage devices are used for continuous, real-time regulation throughout the day. In this scenario, charging and discharging occur at every moment, with frequent changes in charging and discharging power. Taking Scenario 3 as an example, during the period from 11:00 to 13:00, the output of uncontrollable distributed power sources is high, and the short-term energy storage device is in a charging state to "absorb" the excess output of these sources. During the period from 14:00 to 16:00, the output of uncontrollable distributed power sources is low, and the short-term energy storage device is in a discharging state to "compensate" for insufficient output. During other periods, the output of uncontrollable distributed power sources fluctuates significantly, and the short-term energy storage device appropriately adjusts its charging and discharging power to maintain power flow balance.

[0134] Figure 5 This is a schematic diagram illustrating the charging and discharging power and energy storage value curves of a long-term energy storage device in a power grid section, according to an exemplary embodiment. Figure 5 As shown, long-term energy storage devices are used for long-duration daytime energy complementation and typically only perform charging or discharging in various scenarios. Due to the nature of long-term energy storage devices, their charging and discharging states often alternate under typical continuous daytime scenarios, i.e., they satisfy a charging-discharging-charging-discharging-charging-… cycle. In scenarios 1-4, the long-term energy storage device is in a charging-discharging-charging-discharging state, respectively. The energy storage value of the long-term energy storage device reaches its maximum at the beginning of scenario 4 and its minimum at the beginning of scenario 1.

[0135] It should be noted that energy storage devices include short-term energy storage devices and long-term energy storage devices. Short-term energy storage devices can suppress power fluctuations within a scenario, while long-term energy storage devices can smooth energy differences between different seasonal scenarios, thereby improving the voltage stability of the power grid and the ability to absorb renewable energy.

[0136] In summary, the power grid dynamic operation based on seasonal scenarios provided in this application determines update indicators in the power topology model based on the operating data within the power grid partition. These update indicators are compared with preset update thresholds, and the operating status of energy storage devices and the on / off states of remote control switches are adjusted based on the comparison results. This updates the power grid partition boundaries and determines the power grid partition structure, thereby better mitigating output fluctuations during distributed power generation within the power grid partition. This allows the power grid to adapt to the load migration characteristics and new energy fluctuation characteristics during seasonal transitions. Furthermore, the energy storage devices include short-term and long-term energy storage devices, used for intraday regulation and cross-scenario energy balance, respectively, achieving complementary rapid response and long-term compensation. This improves the stability of the power grid's dynamic operation and enables stable dynamic adjustment of the power grid during different seasonal scenario changes.

[0137] Secondly, embodiments of this application provide a power grid dynamic operation device based on seasonal scenarios. Figure 6This is a schematic diagram of a power grid dynamic operation device based on a seasonal scenario, as illustrated in an exemplary embodiment. Figure 6 As shown, the power grid dynamic operation device based on seasonal scenarios includes:

[0138] The model building module is used to construct a power topology model of a flexible microgrid based on the spatial distribution characteristics of energy storage devices, distributed power sources, seasonal loads, and remote control switches, as well as power constraints. The power topology model includes several grid partitions, and the boundaries of the grid partitions are controlled by remote control switches.

[0139] The operation data acquisition module is used to obtain the operation data of each power grid partition within a preset time period on the target day of the current season scenario.

[0140] The first update module is used to determine the update index of each power grid partition based on the operating data, compare each update index with the preset update threshold, adjust the operating status of the energy storage device and the on / off status of the remote control switch based on the comparison results, and determine the power grid partition structure.

[0141] The second update module is used to take the grid partition structure and the operating status of energy storage devices as the initial partition configuration for the next seasonal scenario. On the target day of the next seasonal scenario, update indicators are obtained again, and the energy storage devices and remote control switches are adjusted according to the update indicators.

[0142] The dynamic adjustment module is used to adjust the operating status of the power topology model in each seasonal scenario, taking any two adjacent seasonal scenarios as the current seasonal scenario and the next seasonal scenario respectively.

[0143] In summary, the power grid dynamic operation device based on seasonal scenarios provided in this application constructs a power topology model of a flexible microgrid. It determines update indicators based on operational data acquired on a target day of the current seasonal scenario, compares these update indicators with preset update thresholds, updates the boundaries of power grid partitions based on the comparison results, determines the power grid partition structure, and uses the updated power grid partition structure as the initial partition configuration for the next seasonal scenario to acquire update indicators again. This allows for the adjustment of energy storage devices and remote control switches, and further determination of power grid partitions. Thus, by adjusting energy storage devices and remote control switches based on the comparison results with preset update thresholds, the operating status of the power grid in each seasonal scenario can be adjusted, enabling the power grid to dynamically adapt to different seasonal scenarios.

[0144] It should be noted that the power grid dynamic operation device based on seasonal scenarios provided in this embodiment is used to implement the above-described implementation methods, and details already described will not be repeated. As used above, terms such as "module," "unit," and "subunit" can refer to combinations of software and / or hardware that perform predetermined functions. Although the device described in the above embodiments is preferably implemented in software, hardware implementation, or a combination of software and hardware, is also possible and contemplated.

[0145] Thirdly, embodiments of this application provide an electronic device, Figure 7 This is a block diagram illustrating an electronic device according to an exemplary embodiment. (e.g.) Figure 7 As shown, the electronic device may include a processor 81 and a memory 82 storing computer program instructions.

[0146] Specifically, the processor 81 may include a central processing unit (CPU), an application specific integrated circuit (ASIC), or one or more integrated circuits that can be configured to implement the embodiments of this application.

[0147] The memory 82 may include a mass storage device for data or instructions. For example, and not limitingly, the memory 82 may include a hard disk drive (HDD), a floppy disk drive, a solid-state drive (SSD), flash memory, an optical disk drive, a magneto-optical disk drive, magnetic tape, or a Universal Serial Bus (USB) drive, or a combination of two or more of these. Where appropriate, the memory 82 may include removable or non-removable (or fixed) media. Where appropriate, the memory 82 may be internal or external to a data processing device. In a particular embodiment, the memory 82 is non-volatile memory. In a particular embodiment, the memory 82 includes read-only memory (ROM) and random access memory (RAM). Where appropriate, the ROM may be a mask-programmed ROM, a programmable read-only memory (PROM), an erasable programmable read-only memory (EPROM), an electrically erasable programmable read-only memory (EEPROM), an electrically alterable read-only memory (EAROM), or flash memory, or a combination of two or more of these. Where appropriate, the RAM can be Static Random-Access Memory (SRAM) or Dynamic Random-Access Memory (DRAM). DRAM can be Fast Page Mode Dynamic Random-Access Memory (FPMDRAM), Extended Data Out Dynamic Random-Access Memory (EDODRAM), Synchronous Dynamic Random-Access Memory (SDRAM), etc.

[0148] The memory 82 can be used to store or cache various data files that need to be processed and / or communicated, as well as possible computer program instructions executed by the processor 81.

[0149] The processor 81 reads and executes computer program instructions stored in the memory 82 to implement any of the power grid dynamic operation methods based on seasonal scenarios in the above embodiments.

[0150] In one embodiment, the power grid dynamic operation device based on seasonal scenarios may further include a communication interface 83 and a bus 80. Wherein, as Figure 7 As shown, the processor 81, memory 82, and communication interface 83 are connected through bus 80 and complete communication with each other.

[0151] The communication interface 83 is used to enable communication between the various modules, devices, units, and / or equipment in the embodiments of this application. The communication interface 83 can also enable data communication with other components such as external devices, image / data acquisition devices, databases, external storage, and image / data processing workstations.

[0152] Bus 80, including hardware, software, or both, couples together components of a power grid dynamic operation device based on seasonal scenarios. Bus 80 includes, but is not limited to, at least one of the following: Data Bus, Address Bus, Control Bus, Expansion Bus, and Local Bus. For example, and not as a limitation, bus 80 may include an Accelerated Graphics Port (AGP) or other graphics bus, an Extended Industry Standard Architecture (EISA) bus, a Front Side Bus (FSB), a Hyper Transport (HT) interconnect, an Industry Standard Architecture (ISA) bus, an InfiniBand interconnect, a Low Pin Count (LPC) bus, a memory bus, a Micro Channel Architecture (MCA) bus, a Peripheral Component Interconnect (PCI) bus, a PCI-Express (PCI-X) bus, a Serial Advanced Technology Attachment (SATA) bus, a Video Electronics Standards Association Local Bus (VLB) bus, or other suitable buses, or a combination of two or more of these. Where appropriate, bus 80 may include one or more buses. Although specific buses are described and illustrated in the embodiments of this application, this application considers any suitable bus or interconnection.

[0153] Fourthly, embodiments of this application provide a computer-readable storage medium having a program stored thereon, which, when executed by a processor, implements the power grid dynamic operation method based on seasonal scenarios provided in the first aspect.

[0154] The readable storage medium may be more specifically adopted, including but not limited to: portable disk, hard disk, random access memory, read-only memory, erasable programmable read-only memory, optical storage device, magnetic storage device, or any suitable combination thereof.

[0155] In a possible implementation, the present invention can also be implemented as a program product comprising program code, which, when the program product is run on a terminal device, is used to cause the terminal device to perform the steps of implementing the power grid dynamic operation method based on seasonal scenarios provided in the first aspect.

[0156] The program code for executing the present invention can be written in any combination of one or more programming languages. The program code can be executed entirely on the user device, partially on the user device, as a standalone software package, partially on the user device and partially on a remote device, or entirely on a remote device.

[0157] The technical features of the above embodiments can be combined in any way. For the sake of brevity, not all possible combinations of the technical features in the above embodiments are described. However, as long as there is no contradiction in the combination of these technical features, they should be considered to be within the scope of this specification.

[0158] The embodiments described above are merely illustrative of several implementation methods of this application, and while the descriptions are relatively specific and detailed, they should not be construed as limiting the scope of the invention patent. It should be noted that those skilled in the art can make various modifications and improvements without departing from the concept of this application, and these all fall within the protection scope of this application. Therefore, the protection scope of this patent application should be determined by the appended claims.

Claims

1. A method for dynamic operation of a power grid based on seasonal scenarios, characterized in that, include: Based on the spatial distribution characteristics of energy storage devices, distributed power sources, seasonal loads, and remote control switches, as well as power constraints, a power topology model for a flexible microgrid is constructed. The power topology model includes several grid partitions, and the boundaries of the grid partitions are controlled by the remote control switches. On the target day of the current seasonal scenario, the operating data of each power grid partition is obtained within a preset duration and at preset time intervals. Based on the operating data, update indicators for each power grid partition are determined, each update indicator is compared with a preset update threshold, and the operating status of the energy storage device and the on / off status of the remote control switch are adjusted based on the comparison results to determine the power grid partition structure. The power grid partitioning structure and the operating status of the energy storage device are used as the initial partitioning configuration for the next seasonal scenario. On the target day of the next seasonal scenario, the updated indicators are obtained again, and the energy storage device and the remote control switch are adjusted according to the updated indicators. For any two adjacent seasonal scenarios, which are respectively designated as the current seasonal scenario and the next seasonal scenario, the operating state of the power topology model in each seasonal scenario is adjusted.

2. The power grid dynamic operation method based on seasonal scenarios according to claim 1, characterized in that, The step of comparing each of the updated indicators with a preset update threshold, adjusting the operating state of the energy storage device and the on / off state of the remote control switch based on the comparison results, and determining the grid zoning structure includes: Compare each of the update metrics with the preset update threshold; When the update index is greater than the preset update threshold, the operating status of the energy storage device and the on / off status of the remote control switch in the power grid partition mapped by the update index are adjusted. When the update index is less than or equal to the preset update threshold, the operating status of the energy storage device and the on / off status of the remote control switch in the power grid partition mapped by the update index are maintained. Based on the open / closed state of each of the remote control switches, the boundaries of all the power grid partitions are updated, and the power grid partition structure is determined based on the updated power grid partitions.

3. The power grid dynamic operation method based on seasonal scenarios according to claim 2, characterized in that, The updated metrics meet the following configuration: The updated indicators include comprehensive operational items and seasonal load items; The updated index is obtained by multiplying the comprehensive operation item and the seasonal load item by weighting coefficients and then adding them together.

4. The power grid dynamic operation method based on seasonal scenarios according to claim 3, characterized in that, The overall operation item and the seasonal load item meet the following configuration: The comprehensive operation item includes the loss cost of the lines within the power grid zone and the total cost of the distributed power source; The seasonal load item includes a seasonal importance index in the current seasonal scenario.

5. The power grid dynamic operation method based on seasonal scenarios according to claim 1, characterized in that, The step of obtaining operational data for each power grid partition at preset time intervals within a preset duration includes: Within the preset duration, power flow calculations and operational calculations are performed on each power grid section according to the preset time intervals to obtain operational data for each power grid section.

6. The power grid dynamic operation method based on seasonal scenarios according to claim 1, characterized in that, The specific configuration of the power grid partition is as follows: Any of the aforementioned power grid zones includes one of the aforementioned energy storage devices, several of the aforementioned distributed power sources, and several of the aforementioned seasonal loads; Any two of the power grid zones are connected via the remote control switch.

7. The power grid dynamic operation method based on seasonal scenarios according to claim 1, characterized in that, The specific configuration of the power constraint conditions is as follows: The power constraints include scenario constraints, remote control switch constraints, long-term and short-term energy storage constraints, hybrid energy storage operation constraints, nodal power injection constraints, and power flow constraints.

8. A power grid dynamic operation device based on seasonal scenarios, characterized in that, include: The model building module is used to construct a power topology model of a flexible microgrid based on the spatial distribution characteristics of energy storage devices, distributed power sources, seasonal loads, and remote control switches, as well as power constraints. The power topology model includes several grid partitions, and the boundaries of the grid partitions are controlled by the remote control switches. The operation data acquisition module is used to obtain the operation data of each power grid partition within a preset time period on a target day in the current seasonal scenario. The first update module is used to determine the update index of each power grid partition based on the operating data, compare each update index with a preset update threshold, adjust the operating status of the energy storage device and the on / off status of the remote control switch based on the comparison result, and determine the power grid partition structure. The second update module is used to take the power grid partition structure and the operating status of the energy storage device as the initial partition configuration for the next seasonal scenario, obtain the update index again on the target day of the next seasonal scenario, and adjust the energy storage device and the remote control switch according to the update index. The dynamic adjustment module is used to adjust the operating state of the power topology model in each of the two adjacent seasonal scenarios, which are respectively the current seasonal scenario and the next seasonal scenario.

9. An electronic device, characterized in that, It includes a memory, a processor, and a computer program stored in the memory and executable on the processor, wherein the processor, when executing the computer program, implements the power grid dynamic operation method based on any one of claims 1 to 7.

10. A computer-readable storage medium having a computer program stored thereon, characterized in that, When the program is executed by the processor, it implements the power grid dynamic operation method based on seasonal scenarios as described in any one of claims 1 to 7.

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