Multi-span collaborative distribution network scheduling method

Abstract

The invention discloses a multi-span collaborative distribution network scheduling method. The method comprises the following steps: acquiring regulation and control plans based on different regions of a power distribution network; sub-scheduling tasks are determined for different areas, sub-scheduling targets are determined according to the sub-scheduling tasks, the regulation and control plan is verified according to the sub-scheduling targets, and after verification, the regulation and control plan is updated according to the sub-scheduling tasks corresponding to the sub-scheduling targets; cooperative scheduling of multiple mechanisms and multiple data sources is realized, the decision-making efficiency and the scheduling efficiency are improved, and scheduling plan lag is avoided; automatic parameter and access data checking of the new energy power station is standardized, zero time difference of power failure and power transmission is ensured, repeated power failure is reduced, and high-amount and safe consumption of clean energy is realized; which scheduling target in which scheduling event is completed can be quickly judged, and then whether a regulation and control plan needs to be updated or not is quickly judged; the scheduling plan can be directly updated after the verification of the scheduling target without approving the generation of the scheduling task, and the purpose of timely updating is achieved.

Description

Technical Field

[0001] The present invention relates to the field of inventions, and in particular to a multi-span collaborative distribution network scheduling method. Background Art

[0002] With the continuous expansion of the scale of distribution networks and the continuous improvement of power supply reliability requirements, traditional distribution networks have gradually developed from simple single-point radial power supply structures to multi-segmented, multi-connected or ring network structures, and their operations have become more complex and diverse. In particular, with the large-scale access of distributed photovoltaic, wind power, energy storage and microgrids to the distribution network, the distribution network has gradually developed from a "passive distribution network" to an "active distribution network". The current monthly plan of the distribution network is used as the basis for inputting the quantity and issuing the plan into the control cloud system. Compared with the rigid execution of the main network plan, the monthly plan of the distribution network has large deviations in work content and time execution matching. The actual monthly execution rate is less than 8%, and there are even situations where the daily maintenance application does not correspond to the monthly plan at all; the distribution network plan execution is restricted by many factors and is wide-ranging; the proportion of live operations in the distribution network plan has increased significantly; there are many plans for distribution network projects and relocation projects; there are many changes in the distribution network plan and work uncertainties; according to the actual progress of the user, it is difficult to arrange power connection into the monthly plan. For example, a "distribution network coordinated dispatching method, system and equipment" disclosed in Chinese patent literature, with announcement number: CN116402223A, discloses a game equilibrium analysis of a constructed multiple emerging load participation in electricity market trading model, wherein the multiple emerging load participation in electricity market trading model includes a 5G base station aggregator bidding model, an EV aggregator bidding model and a power trading center clearing model; according to the game equilibrium analysis results, the objective function of the multiple emerging load participation in electricity market trading model is transformed, and the 5G base station aggregator bidding model, the EV aggregator bidding model and the power trading center clearing model are solved respectively; a multiple emerging load aggregator market settlement model is constructed, including a 5G base station aggregator settlement model and an EV aggregator settlement model, but this solution does not take into account the problem of scheduling plan lag. Summary of the invention

[0003] In order to solve the problem of lagging dispatching plans in the prior art, the present invention provides a multi-span collaborative distribution network dispatching method, which improves dispatching efficiency by connecting distribution and dispatching data and visually controlling new equipment.

[0004] In order to achieve the above object, the present invention provides the following technical solutions: A multi-span collaborative distribution network dispatching method includes the following steps: obtaining a control plan based on different areas of the distribution network; determining sub-dispatching tasks for different areas, determining sub-dispatching targets according to the sub-dispatching tasks, verifying the control plan according to the sub-dispatching targets, and updating the control plan according to the sub-dispatching tasks corresponding to the sub-dispatching targets after verification. The control of dispatching events is achieved through the interconnection of dispatching targets and other data, and the control plan is updated through the verification of dynamically generated dispatching targets and control plans, avoiding the problem of delayed dispatching plans caused by event changes and data isolation in the case of multiple data sources and multiple institutions. After different data sources generate dispatching targets, their corresponding control plans can be updated.

[0005] Preferably, obtaining the control plan includes determining the scheduling tasks required in the control plan based on historical data of a fixed length, and setting a scheduling event set for the events in the area. A control plan is established based on a fixed length such as a month or a week, and a short control plan is included through a long control plan. The scheduling event set is divided to avoid temporary application and approval of scheduling events.

[0006] Preferably, the verification includes, after the control plan obtains the sub-scheduling target, searching for the corresponding event from the scheduling event set for comparison and verification, and if the comparison and verification is successful, calling the corresponding event from the scheduling event set to the control plan. The sub-scheduling target is determined by the control plan, and the verification is performed according to the pre-set control plan, so as to update the overall control plan according to the dynamic sub-scheduling target. Especially when different departments and different institutions cooperate together, the verification can be directly performed according to the control plan, avoiding data interaction between different departments of different institutions, and also eliminating the need for data interaction between different departments of different institutions, thereby improving the updating efficiency of the control plan at the node where the control plan is located.

[0007] Preferably, determining sub-scheduling tasks for different regions includes determining a first standard according to environmental factors and limiting factors of the region; determining a second standard according to an event, and dividing the control plan into two layers of sub-scheduling tasks according to the second standard and the first standard, respectively. The scheduling event and the scheduling content required for the scheduling event are determined according to the first standard and the second standard.

[0008] Preferably, the sub-scheduling target is determined according to the sub-scheduling task, including establishing a real-time scheduling plan according to the sub-scheduling task, and using the scheduling task result as the sub-scheduling target of the scheduling plan. The node where the sub-scheduling task is located establishes a scheduling plan according to the scheduling content of the sub-scheduling task, and the scheduling plan is different from the pre-set control plan and is established in real time. The overall control plan is adjusted according to the local dynamic scheduling plan.

[0009] Preferably, after determining the scheduling plan, the sub-scheduling targets and the control plan are verified, including using a cyclic redundancy check to verify the scheduling target and the scheduling event set; including using the events in the scheduling event set as event polynomials and the scheduling target as a check code to determine the scheduling event. The cyclic redundancy check is used to quickly determine the scheduling event, and it is possible to quickly determine which scheduling target in which scheduling event has been completed, and then quickly determine whether the control plan needs to be updated.

[0010] Preferably, the post-verification update includes, after verifying the sub-scheduling target, calling the data of the corresponding sub-scheduling task according to the sub-scheduling target, and adding the data of the sub-scheduling task to the data of the control plan. By directly calling the data of the sub-scheduling task, the control plan can be updated in a timely manner, and the sub-scheduling task stored in the cloud can be directly completed with the participation of multiple parties such as different institutions and departments.

[0011] Preferably, when calling the data of the corresponding sub-scheduling task, the private key of the corresponding sub-scheduling task is obtained from the data of the scheduling target, and the private key is passed as the second public key to the node where the control plan is located. At the same time, when the node where the sub-scheduling task is located transmits the sub-scheduling task, the first public key is used as the viewing key and the second public key is used as the calling key. The second public key is the key assigned by the scheduling target. The sub-scheduling task is doubly encrypted when it is generated, and the second key is generated when the scheduling target is generated. The above technical means are used to realize the de-approval of the sub-scheduling task, so that the generation of the scheduling task does not need to be approved. After the scheduling target verification is completed, the scheduling plan can be directly updated to achieve the purpose of timely update.

[0012] The present invention has the following advantages: (1) Realize the coordinated dispatch of multiple institutions and multiple data sources, improve decision-making efficiency and dispatch efficiency, and avoid delays in dispatch plans; (2) Standardize the verification of automation parameters and access data of new energy power stations to ensure zero time difference in power outages, reduce repeated power outages, and achieve high-cost safe consumption of clean energy; (3) Be able to quickly determine which dispatch target in which dispatch event has been completed, and then quickly determine whether the control plan needs to be updated; realize that there is no need to approve the generation of dispatch tasks. After the dispatch target verification is completed, the dispatch plan can be directly updated to achieve the purpose of timely update. BRIEF DESCRIPTION OF THE DRAWINGS

[0013] The drawings described below are merely exemplary. A person skilled in the art can derive other implementation drawings based on the provided drawings without inventive effort.

[0014] Figure 1 It is a schematic diagram of the steps of the embodiment.

[0015] Figure 2 is a system block diagram in an embodiment.

[0016] In the figure: 1-the first regulation model; 2-the second regulation model. DETAILED DESCRIPTION

[0017] The following is an explanation of the implementation mode of the present invention by means of specific embodiments. Based on the embodiments of the present invention, all other embodiments obtained by ordinary technicians in the field without creative work are within the scope of protection of the present invention.

[0018] like Figure 1 As shown, in a preferred embodiment, a multi-span collaborative distribution network scheduling method includes the following steps: obtaining a control plan based on different areas of the distribution network; determining sub-scheduling tasks for different areas, determining sub-scheduling targets according to the sub-scheduling tasks, verifying the control plan according to the sub-scheduling targets, and updating the control plan according to the sub-scheduling tasks corresponding to the sub-scheduling targets after verification. The control of scheduling events is achieved through the connection of scheduling targets and other data, and the control plan is updated through the verification of dynamically generated scheduling targets and control plans, which avoids the problem of scheduling plan lag caused by event changes and data isolation in the case of multiple data sources and multiple institutions. After different data sources generate scheduling targets, their corresponding control plans can be updated.

[0019] When in use, after the control plan is established, the scheduling tasks in the control plan are not issued downward, and each region determines its own scheduling tasks based on the control plan; sub-scheduling targets are generated based on the scheduling tasks, and the scheduling tasks in the control plan are determined based on the sub-scheduling targets, thereby updating the control plan.

[0020] In other embodiments, obtaining a control plan includes determining the scheduling tasks required in the control plan based on historical data of a fixed length, and setting a scheduling event set for the events in the area. A control plan is established based on a fixed length such as a month or a week, and a short control plan is included through a long control plan. The scheduling event set is divided to avoid temporary application and approval of scheduling events.

[0021] When in use, the scheduling event set is determined based on historical data, so the control plan includes the scheduling tasks that have occurred and are being executed.

[0022] In other embodiments, verification includes, after the control plan obtains the sub-scheduling target, searching for the corresponding event from the scheduling event set for comparison and verification, and if the comparison and verification is successful, calling the corresponding event from the scheduling event set to the control plan. The sub-scheduling target is determined by the control plan, and the verification is performed according to the pre-set control plan, so as to update the overall control plan according to the dynamic sub-scheduling target. Especially when different departments and different institutions cooperate together, verification can be performed directly according to the control plan, avoiding data interaction between different departments of different institutions, and also eliminating the need for data interaction between different departments of different institutions, thereby improving the updating efficiency of the control plan at the node where the control plan is located.

[0023] When in use, the sub-scheduling target is a target dynamically generated by the node where the sub-scheduling task is located according to the scheduling plan. After uploading the scheduling target to the node where the control plan is located, the control plan can adaptively adjust the control plan according to the scheduling target, so that the sudden and irregular tasks in various scheduling events can also be reflected in the control plan, and there is no need to fully specify the control tasks, which causes the problem that the control plan cannot be dynamically updated. At the same time, there is no need to specify the control targets of the control tasks, which makes the update of the control plan flexible. Especially in the actual scheduling process, when the same scheduling event generates different scheduling targets, it solves the problem of untimely update of the control plan due to the inability to unify the progress.

[0024] In other embodiments, determining sub-scheduling tasks for different regions includes determining a first standard based on environmental factors and limiting factors of the region; determining a second standard based on an event, and dividing the control plan into two layers of sub-scheduling tasks based on the second standard and the first standard, respectively. The scheduling event and the scheduling content required for the scheduling event are determined based on the first standard and the second standard.

[0025] When in use, the first criterion is the factor affecting the efficiency of scheduling events, and the second criterion is the type of scheduling events.

[0026] In other embodiments, the determination of the sub-scheduling target according to the sub-scheduling task includes establishing a real-time scheduling plan according to the sub-scheduling task, and using the scheduling task result as the sub-scheduling target of the scheduling plan. The node where the sub-scheduling task is located establishes a scheduling plan according to the scheduling content of the sub-scheduling task, and the scheduling plan is different from the pre-set control plan and is established in real time. The overall control plan is adjusted according to the local dynamic scheduling plan.

[0027] In other embodiments, after determining the scheduling plan, the sub-scheduling targets and the control plan are verified, including using a cyclic redundancy check to verify the scheduling target and the scheduling event set; including using the events in the scheduling event set as event polynomials and the scheduling target as a check code to determine the scheduling event. The cyclic redundancy check is used to quickly determine the scheduling event, and it is possible to quickly determine which scheduling target in which scheduling event has been completed, and then quickly determine whether the control plan needs to be updated.

[0028] When in use, the node where the control plan is located converts the obtained scheduling target into a verification code and verifies it with its own scheduling event set. For different scheduling targets of different departments, the converted verification code includes its department and event characteristics. The verification process avoids approval and decryption processing, and the verification process itself can complete the verification of the scheduling target. At the same time, the rationality of the scheduling target itself is verified.

[0029] In other embodiments, the post-verification update includes, after verifying the sub-scheduling target, calling the data of the corresponding sub-scheduling task according to the sub-scheduling target, and adding the data of the sub-scheduling task to the data of the control plan. By directly calling the data of the sub-scheduling task, the timely update of the control plan is realized, and the sub-scheduling task stored in the cloud can be directly completed with the participation of multiple parties such as different institutions and departments. When calling the data of the corresponding sub-scheduling task, the private key of the corresponding sub-scheduling task is obtained from the data of the scheduling target, and the private key is passed to the node where the control plan is located as the second public key. At the same time, when the node where the sub-scheduling task is located transmits the sub-scheduling task, the first public key is used as the viewing key and the second public key is used as the calling key. The second public key is the key assigned by the scheduling target. The sub-scheduling task is double encrypted when it is generated, and the second key is generated when the scheduling target is generated; the de-approval of the sub-scheduling task is realized by the above technical means, and the generation of the scheduling task does not need to be approved. After the scheduling target verification is completed, the scheduling plan can be directly updated to achieve the purpose of timely update.

[0030] When in use, the scheduling tasks that need to be updated in the control plan are determined by generating and using the second key. Before and after different departments complete their respective scheduling targets, the control plan determines the corresponding scheduling tasks based on the scheduling targets uploaded by them, realizing timely updates of scheduling tasks without interactive processing of multiple data sources, and without the need for additional encryption and desensitization of data.

[0031] In other embodiments, Figure 2 As shown, the following steps are included: establishing a first regulation model 1, wherein the first regulation model is connected to a second regulation model 2.

[0032] Determine the first control model based on monthly and quarterly historical data information, and allocate a second control model with a time length less than a natural month to the first control model; establish daily and weekly plans in the second control model, make statistical plans for the second control model and issue tasks to the task model.

[0033] The task model uploads the task to the first control model. After obtaining the task, the first control model calls the corresponding plan data from the second control model and fills the scheduling task according to the called plan data.

[0034] The scheduling task is set with a scheduling target, which is a prefabricated target. The historical data of a fixed time length is obtained, and the tasks in the historical data within the time length are screened to obtain a task data set. The task data set is clustered using KMEANS to obtain regular tasks and dynamic tasks. The regular tasks are used as prefabricated targets in the first control model, and the dynamic tasks are used as prefabricated dynamic targets in the second control model.

[0035] When in use, the second control model generates a plan identical to the prefabricated dynamic target and sends it to the task model, while the first control model calls the corresponding plan from the second control model.

[0036] The parameters of cluster analysis are the combined weight of the number of occurrences and the planned quantity. The planned quantity is the data of whether the task is in the control plan, and the number of occurrences is the number of occurrences of the task in the cycle; the combined weight includes a weight matrix. The weight determination of the planned quantity includes determining the number of tasks corresponding to the planned quantity, and taking the difference between the number of tasks and the number of occurrences as a weight parameter. The weight of the number of occurrences includes setting a number threshold, and taking the difference between the number of occurrences and the number threshold as a weight parameter.

[0037] Through cluster analysis, the tasks in the cycle are classified to determine the regular tasks and dynamic tasks. Regular tasks are tasks within the control plan, and dynamic tasks are tasks outside the control plan. In this way, the tasks in the cycle are analyzed to obtain the completion status of the tasks in the cycle, and then the task goals at the current stage are customized according to the completion status of the tasks in the cycle.

[0038] The first control model is located on the cloud platform. The first control model is a comprehensive control model. The first control model is connected to multiple second control models, and each second control model is responsible for a fixed area of ​​the distribution network. The task control of regional division of the distribution network is realized. Each second control model is connected to multiple task models, and the task model is only connected to the second control model in the area, and the task model is connected to the first control model.

[0039] In other embodiments, the following steps are included: obtaining a control plan; dividing the control plan into multiple scheduling tasks.

[0040] Each scheduling task includes at least one regular task and several dynamic tasks. When dividing the control plan into multiple scheduling tasks, the regular tasks are divided according to the time represented by the regular tasks, and then arranged in time series to form multiple cross-scheduling tasks. Scheduling tasks include tasks from different departments, different institutions, and different network locations. In this way, different institutions can jointly form scheduling tasks, which facilitates the common use of multi-source data.

[0041] When in use, the control plan is divided into the first scheduling task, the second scheduling task, and the third scheduling task according to the preset scheduling events, wherein each scheduling task includes a regular task to be completed at the scheduled time and a dynamic task that may occur. In addition, the regular task is set to a red state, and the dynamic task is set to a gray state.

[0042] Obtain sub-scheduling tasks, determine sub-plan data based on the sub-scheduling tasks, determine scheduling targets based on the sub-plan data, check and verify the scheduling targets with the scheduling tasks, and update the control plan based on the verified scheduling tasks.

[0043] In other embodiments, different organizations obtain their own sub-scheduling tasks respectively, and determine multiple scheduling targets based on at least one sub-scheduling task, upload the multiple scheduling targets to the scheduling tasks for verification, update the scheduling tasks after verification, and update the scheduling plan.

[0044] When in use, each sub-scheduling task includes at least one dynamic task. The dynamic tasks in the sub-scheduling task and the dynamic tasks in gray state in the scheduling task are verified. If they meet the requirements, the corresponding dynamic tasks will be updated to red state. When updating the scheduling plan, it will be updated according to the total number of tasks in red state and the corresponding tasks.

[0045] In other embodiments, each sub-scheduling task also includes a regular task, and the corresponding scheduling task is determined according to the regular task, and the scheduling task corresponding to the regular task is started to achieve fast scheduling and avoid the problem of scheduling delay.

[0046] In other embodiments, all tasks are determined based on historical data, all tasks are classified into regular tasks and dynamic tasks, a control plan is determined based on regular tasks, and sub-scheduled tasks are determined based on dynamic tasks. The sub-plan data includes all event data in the sub-scheduled tasks, all event data are marked with dynamic task tags, and the dynamic task tags and all event data are stored and transmitted together.

[0047] In other embodiments, the event data includes matching repeated power outage verification, household number analysis during power outage, zero-time difference verification of power outage, verification of new equipment startup and abnormal diagram, and planned management classification statistics.

[0048] In other embodiments, determining the scheduling target based on the sub-plan data includes calling the event corresponding to the corresponding sub-scheduling task based on the sub-plan data, packaging the event data and dynamic task label in the sub-plan data as a dynamic scheduling target, and then adding the dynamic scheduling target to the scheduling target.

[0049] In other embodiments, after determining the sub-plan data, the event data in the sub-plan data and the corresponding common task tags are packaged as a common scheduling target price, and then the common scheduling target is added to the scheduling target.

[0050] When in use, when obtaining the scheduling target, index verification is performed with the scheduling task based on the dynamic task label or the regular task label in the scheduling target.

[0051] In other embodiments, the control task includes a scheduling target, and the scheduling target includes a constant scheduling target and a dynamic scheduling target. The constant scheduling target includes a constant task label and a corresponding scheduling target; the dynamic scheduling target includes a dynamic task label and a corresponding scheduling target.

[0052] In other embodiments, checking and verifying the scheduling target and the scheduling task includes identifying the dynamic scheduling target and the constant scheduling target in the scheduling target, using the dynamic task label in the dynamic scheduling target as an index to extract the corresponding scheduling task, and updating the scheduling task after verification of the index and comparison; indexing and comparing the constant task label in the constant scheduling target and the corresponding task in the control plan, if the verification is successful, the constant scheduling task is maintained, and when the verification fails, it is determined whether the control plan contains the constant scheduling target, if not, the constant scheduling target is added when the control plan is updated, and if the constant scheduling target is included, the constant scheduling target is added again or the constant scheduling target is removed from the scheduling task according to the completion status of the constant scheduling target.

[0053] Although the present invention has been described in detail above by general description and specific embodiments, it is obvious to those skilled in the art that some modifications or improvements can be made to the present invention. Therefore, these modifications or improvements made without departing from the spirit of the present invention all belong to the scope of protection claimed by the present invention.

Claims

1. A multi-span coordinated distribution network scheduling method, characterized in that: The method includes the following steps: obtaining a control plan based on different areas of the distribution network; determining sub-dispatching tasks for different areas, determining sub-dispatching targets based on the sub-dispatching tasks, verifying the control plan based on the sub-dispatching targets, and updating the control plan based on the sub-dispatching tasks corresponding to the sub-dispatching targets after verification.

2. A multi-span coordinated distribution network scheduling method according to claim 1, characterized in that: Acquiring a control plan includes determining the scheduling tasks required in the control plan based on historical data of a fixed length, and setting a scheduling event set for events in the area.

3. A multi-span coordinated distribution network scheduling method according to claim 1 or 2, characterized in that: Verification includes: after the control plan obtains the sub-scheduling target, it searches for the corresponding event from the scheduling event set for comparison and verification. If the comparison and verification is successful, the corresponding event is called from the scheduling event set to the control plan.

4. A multi-span coordinated distribution network scheduling method according to claim 2, characterized in that: Determining sub-scheduling tasks for different areas includes determining a first standard based on environmental factors and limiting factors of the area; determining a second standard based on events, and dividing the control plan into two layers of sub-scheduling tasks based on the second standard and the first standard respectively.

5. A multi-span coordinated distribution network scheduling method according to claim 4, characterized in that: Determining the sub-scheduling target according to the sub-scheduling task includes establishing a real-time scheduling plan according to the sub-scheduling task and using the scheduling task result as the sub-scheduling target of the scheduling plan.

6. A multi-span coordinated distribution network scheduling method according to claim 5, characterized in that: After the scheduling plan is determined, the sub-scheduling targets and control plans are verified, including the use of cyclic redundancy checks to verify the scheduling targets and scheduling event sets; The method includes taking events in a scheduling event set as event polynomials and taking scheduling targets as check codes to determine scheduling events.

7. A multi-span coordinated distribution network scheduling method according to claim 1 or 2, characterized in that: The post-verification update includes, after verifying the sub-scheduling target, calling the data of the corresponding sub-scheduling task according to the sub-scheduling target, and adding the data of the sub-scheduling task to the data of the control plan.

8. A multi-span coordinated distribution network scheduling method according to claim 7, characterized in that: When calling the data of the corresponding sub-scheduling task, the private key of the corresponding sub-scheduling task is obtained from the data of the scheduling target, and the private key is passed as the second public key to the node where the control plan is located. At the same time, when the node where the sub-scheduling task is located transmits the sub-scheduling task, the first public key is used as the viewing key and the second public key is used as the calling key.

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