CN-116154963-B - Intelligent scheduling system based on Internet of things and load scheduling method thereof

CN116154963BCN 116154963 BCN116154963 BCN 116154963BCN-116154963-B

Abstract

The invention relates to an intelligent scheduling system based on the Internet of things, which at least comprises a second data processing module, a display interface and a man-machine bidirectional supervision module, wherein the second data processing module is used for creating a corresponding real-time data mapping model according to real-time state data, comparing the real-time data mapping model with a pre-stored state model to realize real-time monitoring of the Internet of things of electric power, generating or calling instruction information related to at least one load unit in a database and related to a comparison result through the comparison, displaying the obtained instruction information on an upper computer by utilizing the display interface for an operator to perform scheduling monitoring, updating the instruction information according to feedback information input by the operator through the upper computer, actively following operation information on the upper computer by the operator based on the updated instruction information, and comparing the operation information with the updated instruction information.

Inventors

CHEN WENJUN
WANG PENGCHENG
LU WANJUN
XU HUAN

Assignees

西藏先锋绿能环保科技股份有限公司
四川中英智慧质量工程技术研究院有限公司

Dates

Publication Date: 20260508
Application Date: 20230221

Claims (9)

1. An intelligent scheduling system based on the internet of things is characterized by at least comprising: a first data processing module for acquiring real-time status data of a plurality of load units accessed to the intelligent scheduling system in a manner responsive to operator input or automatic acquisition; A second data processing module for creating a corresponding real-time data mapping model according to the real-time state data, comparing the real-time data mapping model with the pre-stored state model to realize the real-time monitoring of the electric power Internet of things, The second data processing module generates or invokes instruction information related to at least one load unit in the database and related to the comparison result through the comparison, displays the obtained instruction information to the upper computer by utilizing the display interface for the operator to schedule and monitor, The second data processing module updates the instruction information according to the received feedback information input by the operator through the upper computer, actively follows the operation information of the operator on the upper computer based on the updated instruction information, compares the operation information with the updated instruction information, realizes the human-computer bidirectional supervision, The first data processing module is used for acquiring real-time state data of a plurality of load units connected into the intelligent scheduling system and establishing a load floating domain related to the system through load floating analysis based on the real-time state data, the second data processing module generates or invokes instruction information related to at least one load unit in a database according to the load floating domain, the load floating domain established by the first data processing module is contained in an uplink and downlink envelope curve and/or a load prediction curve which are drawn and formed in a virtual two-dimensional coordinate system within a sliding time window determined according to the current moment, and the uplink and downlink envelope curve is used for indicating prediction error fluctuation of the load prediction curve.
2. The intelligent scheduling system according to claim 1, wherein the first data processing module collects historical data and monitoring data related to a plurality of load units, judges states of the plurality of load units and states of a system through historical data analysis, monitors operation parameters and actual working conditions of the plurality of load units and the system in real time, and uses the internet of things to carry out system interconnection on monitoring information generated after preprocessing.
3. The intelligent scheduling system according to claim 2, wherein the second data processing module actively processes abnormal working conditions existing in the plurality of load units and/or the system according to the monitoring information generated after the first data processing module processes the collected data, and notifies the operator through the display interface to allow the operator to schedule and monitor in time.
4. The intelligent scheduling system of claim 3, further comprising a third data processing module for grouping a plurality of load units accessed to the intelligent scheduling system into corresponding groups, respectively, in a label-by-label manner.
5. The intelligent scheduling system of claim 4, further comprising a fourth data processing module for obtaining primary production-related information for a plurality of load units accessing the intelligent scheduling system by historical data analysis in combination with basic information of the device about the full life cycle ledger, and generating secondary production-related information about each group based on the primary production-related information for each load unit under each group.
6. The intelligent scheduling system of claim 1, wherein the second data processing module, upon receiving a power scheduling demand instruction containing specified load data, determines a floating load differential between a load floating domain for the system and the specified load data, and generates an inspection maintenance instruction for at least one load unit when the floating load differential triggers an inspection maintenance condition, or generates a deployment optimization instruction for an operational status of the at least one load unit when the floating load differential triggers a deployment optimization condition.
7. A load scheduling method using the intelligent scheduling system based on internet of things according to any one of claims 1 to 6, characterized by comprising at least: Acquiring real-time status data of a plurality of load units accessed to the intelligent scheduling system by using a first data processing module in a manner responsive to operator input or automatic acquisition; Creating a corresponding real-time data mapping model according to the real-time state data by using a second data processing module; Comparing the real-time data mapping model with the pre-storage state model by utilizing a second data processing module, so as to realize real-time monitoring of the electric power Internet of things; generating or calling instruction information related to at least one load unit in the database and related to the comparison result through the comparison; Displaying the obtained instruction information to an upper computer by using a display interface so as to enable an operator to schedule and monitor; Updating instruction information by using a second data processing module according to the received feedback information input by an operator through the upper computer; based on the updated instruction information, the second data processing module is utilized to actively follow the operation information of an operator on the upper computer; And comparing the operation information with the updated instruction information to realize the man-machine bidirectional supervision.
8. An intelligent scheduling system based on the internet of things is characterized by at least comprising: The first data processing module is used for acquiring real-time state data of a plurality of load units accessed to the intelligent scheduling system and establishing a load floating domain related to the system through load floating analysis based on the real-time state data; A second data processing module for determining a floating load difference between a load floating domain with respect to a system and specified load data when a power scheduling demand instruction containing the specified load data is received, and generating an inspection maintenance instruction with respect to at least one load unit when the floating load difference triggers an inspection maintenance condition, or generating a deployment optimization instruction with respect to an operation state of at least one load unit when the floating load difference triggers a deployment optimization condition; The first data processing module is used for acquiring real-time state data of a plurality of load units connected into the intelligent scheduling system and establishing a load floating domain related to the system through load floating analysis based on the real-time state data, the second data processing module generates or invokes instruction information related to at least one load unit in a database according to the load floating domain, the load floating domain established by the first data processing module is contained in an uplink and downlink envelope curve and/or a load prediction curve which are drawn and formed in a virtual two-dimensional coordinate system within a sliding time window determined according to the current moment, and the uplink and downlink envelope curve is used for indicating prediction error fluctuation of the load prediction curve.
9. An intelligent scheduling system based on the internet of things, wherein the intelligent scheduling system at least comprises a load envelope calculation module configured to: Determining a sliding time window based on the current moment and establishing a load floating domain for each load unit based on load data for the load unit within the sliding time window; The method comprises the steps that class attribution processing can be carried out on a specified load unit and a load floating domain corresponding to the specified load unit and each load unit related to the specified load unit, so that when a power dispatching demand instruction containing specified load data is received, a dispatching optimization instruction about the running state of at least one load unit can be generated based on the floating load difference between the specified load data and the load floating domain corresponding to the load unit under different classes, wherein the load floating domain is obtained by respectively calculating the upper limit and the lower limit of a load fluctuation range in a sliding time window by taking historical load data of each load unit and related data of a load prediction curve section corresponding to the historical load data as input on the basis of a load prediction curve in the current moment and the sliding time window.

Description

Intelligent scheduling system based on Internet of things and load scheduling method thereof Technical Field The invention relates to the technical field of intelligent power grids, in particular to an intelligent scheduling system based on the Internet of things and a load scheduling method thereof. Background Intelligent scheduling of electrical grids involves numerous functions such as real-time monitoring, regulation and control, scheduling planning, analysis and evaluation, etc. The real-time monitoring refers to monitoring the current operation condition of the power grid, including monitoring the dynamic and stable degree of the operation of the power grid, monitoring the operation condition of the next power grid and monitoring auxiliary services, and the like, and also monitoring the reasons that factors in the non-power grid affect the operation of the power grid, such as weather conditions, related functions, and the like. In addition, the intelligent dispatching of the power grid also has a certain early warning effect, wherein the intelligent dispatching comprises the aspects of warning the spare capacity condition, influencing the warning caused by disasters and the like. Based on the real-time monitoring information, the intelligent dispatching automation system for the power grid can control the running condition of the power grid by utilizing various analysis modes such as advanced or real-time analysis, wherein the intelligent dispatching automation system comprises an emergency scheme for generating accidents, a charge carrier for control and the like. The intelligent dispatching automation system of the power grid can combine the actual conditions to compile a scientific and reasonable scheme, the strengthening management process is carried out according to the scheme, the key objects are fault management, inspection and maintenance, information publishing and the like, and when faults occur, the emergency scheme is started at the highest speed. There are many reasons that affect the intelligent scheduling of the grid, and therefore these factors need to be considered in the actual planning. Regarding the current intelligent dispatching technical state of the domestic power grid, the technical level progress is rapid, but relatively, the cost investment is high, the implementation is difficult, and the development of the service is affected to a certain extent. Based on this, it is necessary to apply corresponding measures to reduce the extent of reliance on the operating system, more efficiently apply software, and strengthen the importance of the module. To ensure the expansibility of the architecture and ensure the safe and more efficient intelligent scheduling, certain requirements are put forward on related researches, certain countermeasures are needed to improve the technical capability, and the intelligent scheduling of the power grid is ensured to be safer and more reliable. At present, a large number of internet of things devices are conveniently and effectively controlled by assembling an intelligent scheduling system, and the intelligent scheduling system is generally composed of a sensor, an executing mechanism, a controller, an upper computer and other devices. In daily application, the intelligent scheduling system utilizes control logic preset in the controller to correspondingly adjust start-stop and operation parameters of different devices, and the intelligent scheduling system can close or start the different devices at different time points. For example, patent document with publication number CN111126885B in the prior art proposes an intelligent electricity dispatching method and system based on internet of things, and based on the recognition result and the operation data of the electric equipment, the method realizes scientific electricity management and dispatching to reduce the waste of electric energy and the occurrence of electricity utilization accident, and at least comprises the steps of firstly, acquiring the operation data of the electric equipment in each area and the acquisition information uploaded by the acquisition equipment in each area in real time; and finally, controlling the running states of the electric equipment in the area according to the personnel distribution condition of each area and the running data of the electric equipment in the area and dispatching the running states of the electric equipment in other areas according to the personnel distribution trend of other areas. When the intelligent scheduling system is adopted to automatically control each device, the intelligent scheduling system does not give any prompt before the device is started and stopped or before the operation parameters are changed, so that operators cannot know the intention of the intelligent scheduling system in advance, cannot intervene in advance or make preparation in advance, and can only find abrupt change when the device is started and stopped or after the