CN-121984011-A - Micro-grid energy-saving optimization system and control method

CN121984011ACN 121984011 ACN121984011 ACN 121984011ACN-121984011-A

Abstract

The embodiment of the application provides a micro-grid energy-saving optimization system and a control method, which are applied to the technical field of micro-grid energy-saving control, wherein the method is used for carrying out hierarchical division on energy objects of an enterprise level, a workshop level, a production line level and a device level in a micro-grid, constructing a micro-grid structure diagram comprising a first sub-graph, a second sub-graph and a third sub-graph, and realizing the structural management of node energy consumption information of each hierarchical level of the micro-grid; the method comprises the steps of collecting operation state and electricity demand data at equipment level nodes, forming equipment level first energy consumption adjustable states, generating enterprise level second energy consumption adjustable states by layer aggregation, screening target enterprise level nodes and production line level nodes based on the second energy consumption adjustable states, determining a target equipment set, generating a regulation strategy by combining a historical equipment regulation library, controlling target equipment to execute power regulation, realizing integral load smooth regulation and energy-saving optimization control of electric energy resources of a micro-grid, and ensuring continuity and operation stability of production tasks.

Inventors

MA SI
DENG YUANMING
TANG HAO

Assignees

湘潭芒奇信息科技有限公司

Dates

Publication Date: 20260505
Application Date: 20260122

Claims (10)

1. An energy-saving optimization control method for a micro-grid is characterized by comprising the following steps: performing hierarchical division on energy utilization objects of a micro-grid to obtain a hierarchical relation and a hierarchical node, and constructing a micro-grid structure diagram according to the hierarchical relation and the hierarchical node, wherein the hierarchical node comprises an enterprise level node, a workshop level node, a production line level node and a device level node, and the micro-grid structure diagram comprises a first sub-graph, a second sub-graph and a third sub-graph; Extracting data from the equipment-level nodes of the third sub-graph to obtain state data and electricity demand data, and carrying out information association analysis and constraint matching processing on the state data and the electricity demand data to form a first energy consumption adjustable state of the equipment level, wherein the first energy consumption adjustable state is used for representing the adjustable energy consumption capability of the equipment under the current running condition; The first energy consumption adjustable state is aggregated layer by layer upwards according to the hierarchical relationship, and a second energy consumption adjustable state of an enterprise level is obtained; screening the micro-grid structure diagram based on the second energy consumption adjustable state, determining a target enterprise level node, screening the first sub-graph and the second sub-graph layer by layer according to the hierarchical relationship, and determining a target production line level node; Obtaining a third sub-graph corresponding to the target production line level node, and determining a target equipment set from the third sub-graph according to the first energy consumption adjustable state, wherein the target equipment set at least comprises one target equipment; Matching the target equipment with a preset historical equipment adjustment library, generating a regulation strategy of the target equipment by combining the first energy consumption adjustable state, and controlling the target equipment to execute the regulation strategy to optimally control the energy conservation of the micro-grid.
2. The method of claim 1, wherein the hierarchically partitioning the micro-grid to obtain a hierarchical relationship and a hierarchical node, and constructing a micro-grid structure map from the hierarchical relationship and the hierarchical node comprises: Acquiring the belonging organization identification and operation attribute data of each energy object in the micro-grid; Performing hierarchical attribution judgment on the energy consumption object by combining a preset hierarchical division rule based on the belonging organization identifier to obtain a judgment result, wherein the judgment result comprises hierarchical nodes and a hierarchical relationship, the hierarchical nodes comprise enterprise-level nodes, workshop-level nodes, production line-level nodes and equipment-level nodes, and the hierarchical relationship comprises same-level dependency relationships and upper-lower-layer dependency relationships; mapping the operation attribute data to corresponding hierarchical nodes one by one according to the hierarchical relationship; on the basis of the judging result, respectively combining and constructing the enterprise level node, the workshop level node, the production line level node and the equipment level node with the same-level dependency relationship to obtain an initial micro-grid structure diagram, a first sub-graph, a second sub-graph and a third sub-graph; And connecting the initial micro-grid structure diagram, the first sub-diagram, the second sub-diagram and the third sub-diagram according to the upper-lower layer dependency relationship to form a micro-grid structure diagram, wherein each enterprise level node of the micro-grid structure diagram corresponds to one first sub-diagram, each workshop level node in the first sub-diagram corresponds to one second sub-diagram, and each production line level node in the second sub-diagram corresponds to one third sub-diagram.
3. The method of claim 2, wherein the extracting data from the device level node of the third sub-graph to obtain the status data and the electricity demand data includes: Acquiring an organization identifier and operation attribute data corresponding to a device-level node of a third sub-graph, wherein the operation attribute data comprises an operation state parameter and an electricity behavior parameter; Determining a target production line level node to which the equipment level node belongs according to the upper and lower layer dependency relationship of the third sub-graph and the second sub-graph and by combining the belonging organization identifier of the equipment level node; acquiring and analyzing the current production task information of the target production line level node, and determining the process role and priority played by each equipment level node in the current production task; analyzing the operation state parameters of each equipment level node according to the process role and the priority and a preset screening rule, and extracting key operation state parameters as state data, wherein the state data at least comprises an on-off state, a current load level, an operation mode and a task execution stage identifier; and carrying out electricity demand analysis on the electricity consumption behavior parameters of each equipment-level node and the current production task information, screening by combining the process roles and the priorities, determining the electricity consumption demand required by the equipment-level node to finish the current production task, and taking the electricity consumption demand as electricity consumption demand data.
4. A method according to claim 3, wherein said performing information-bearing analysis and constraint matching processing on said status data and electricity demand data to form a first energy consumption-adjustable status of the equipment level comprises: For each equipment-level node, determining an initial adjustable power range of the equipment-level node under the current production task according to the on-off state, the current load level, the running mode and the task execution stage in the state data and combining the electricity demand data; Establishing a corresponding equipment constraint parameter set for each equipment level node, wherein the equipment constraint parameter set at least comprises a minimum process power parameter corresponding to the process role of the equipment level node, a minimum guarantee power parameter corresponding to the priority of the equipment level node and a maximum allowable power parameter corresponding to the upper and lower layer dependency relationship of the equipment level node; Performing interval cutting processing on the initial adjustable power range and the equipment constraint parameter set, removing power values smaller than the minimum process power parameter or smaller than the minimum guaranteed power parameter, and removing power values larger than the maximum allowable power parameter to obtain a target adjustable power value range of the equipment level; and recording the target adjustable power value range of the equipment level as a first energy consumption adjustable state of the equipment level, wherein the first energy consumption adjustable state is used for representing the energy consumption adjusting range of the equipment level node allowed to be executed under the current production task and level dependent constraint condition.
5. The method of claim 4, wherein aggregating the first energy consumption-adjustable states layer by layer up according to the hierarchical relationship to obtain enterprise-level second energy consumption-adjustable states comprises: Reading process roles and priorities of the equipment-level nodes in a current production line task according to upper and lower layer dependency relationships of the second sub-graph and the third sub-graph, sequencing first energy consumption adjustable states of the equipment-level nodes in the third sub-graph according to the process roles and priorities, and carrying out constraint accumulation and boundary cutting processing on the sequenced first energy consumption adjustable states by combining the upper and lower layer dependency relationships to form a third energy consumption adjustable state of the production line node; Reading the process roles and the priorities of the production line level nodes in the current workshop task according to the upper and lower layer dependency relationships of the first sub-graph and the second sub-graph, sequencing the third energy consumption adjustable states of the production line level nodes in the second sub-graph according to the process roles and the priorities, and carrying out constraint accumulation and boundary cutting treatment on the sequenced third energy consumption adjustable states by combining the upper and lower layer dependency relationships to form a fourth energy consumption adjustable state of the workshop level nodes; And reading the process roles and the priorities of the workshop-level nodes in the current enterprise task according to the micro-grid structure diagram and the upper and lower layer dependency relationships of the first subgraph, sequencing the fourth energy consumption adjustable states of the workshop-level nodes in the first subgraph according to the process roles and the priorities, and carrying out constraint accumulation and boundary cutting processing on the sequenced fourth energy consumption adjustable states in combination with the upper and lower layer dependency relationships to form a second energy consumption adjustable state of the enterprise-level nodes, wherein the second energy consumption adjustable state is used for representing the whole energy consumption adjusting capacity range of the enterprise-level nodes corresponding to the enterprise-level nodes for global scheduling under the current production task and hierarchy dependency constraint conditions.
6. The method of claim 5, wherein the screening the microgrid structure map based on the second energy consumption adjustable state to determine a target enterprise level node comprises: In the micro-grid structure diagram, traversing a second energy consumption adjustable state corresponding to each enterprise-level node, and extracting an enterprise-level adjustable power interval corresponding to each enterprise-level node under the current enterprise task, wherein the enterprise-level adjustable power interval is defined by an upper limit power value and a lower limit power value; Acquiring a scheduling demand instruction corresponding to the current micro-grid operation condition, wherein the scheduling demand instruction at least comprises a demand type and a target total adjustment power value, and the demand type is one of peak clipping, valley filling or load transfer; Determining a global scheduling power interval according to the target total adjustment power value and the demand type, wherein the global scheduling power interval is used for reflecting an adjustable power range and an adjustment direction of the whole micro-grid under the constraint of the demand type, and the adjustment direction comprises downward peak clipping adjustment, upward valley filling adjustment and bidirectional load transfer adjustment; judging the interval overlapping relation between the enterprise-level adjustable power interval of each enterprise-level node and the global scheduling power interval, and marking the enterprise-level nodes with non-empty intersections as candidate enterprise-level nodes; Determining an intersection interval of the enterprise-level adjustable power interval and the global scheduling power interval, and determining a difference value between an upper limit power value and a lower limit power value of the intersection interval as a schedulable potential value of the candidate enterprise-level node; And sequencing all candidate enterprise-level nodes according to the schedulable potential value, and selecting at least one candidate enterprise-level node with the schedulable potential value larger than a preset potential threshold as a target enterprise-level node.
7. The method of claim 6, wherein the step of screening the first sub-graph and the second sub-graph layer by layer according to the hierarchical relationship to determine a target line level node comprises: taking a second energy consumption adjustable state corresponding to the target enterprise-level node as an enterprise-level constraint interval, traversing a fourth energy consumption adjustable state corresponding to each workshop-level node in the first subgraph, judging the interval overlapping relation between the fourth energy consumption adjustable state and the enterprise-level constraint interval, and screening out the workshop-level nodes with overlapping intervals; and for each target workshop level node, taking a fourth energy consumption adjustable state corresponding to the target workshop level node as a workshop level constraint interval, traversing a third energy consumption adjustable state corresponding to each production line level node in a corresponding second subgraph, judging the interval overlapping relation between the third energy consumption adjustable state and the workshop level constraint interval, and screening the target production line level nodes.
8. The method of claim 7, wherein the obtaining a third sub-graph corresponding to the target line level node, and determining the target device set from the third sub-graph according to the first energy consumption adjustable state, comprises: acquiring a first energy consumption adjustable state corresponding to each equipment level node in a third subgraph corresponding to the target production line level node; determining a production line level target regulation power interval according to a third energy consumption adjustable state corresponding to the target production line level node; In the third sub-graph, the first energy consumption adjustable state is taken as a combination unit, and equipment combination is constructed according to the current production task and in combination with the process dependency relationship among the equipment; accumulating the first energy consumption adjustable states of the equipment of each candidate equipment combination to obtain a combined adjustable power interval, and judging the interval overlapping relation between the production line level target adjustable power interval and the combined adjustable power interval; If the combined adjustable power interval belongs to a subinterval of the production line level target adjustment power interval, taking the equipment combination corresponding to the combined adjustable power interval as a candidate equipment combination; And for each candidate equipment combination, taking the length ratio of the combination adjustable power interval to the production line level target adjustable power interval as an overlapping ratio, sorting the candidate equipment combinations in a descending order according to the overlapping ratio, and selecting the candidate equipment combination with the largest overlapping ratio as a target equipment set.
9. The method of claim 8, wherein the matching the target device with a preset historical device adjustment library, in combination with the first energy consumption adjustable state, generates a regulation strategy of the target device, comprises: When executing a current production task, acquiring a first energy consumption adjustable state of each target device in the target device set; Acquiring a process role of each target device under a current production task; Inquiring and extracting at least one history adjustment record with highest matching degree from a preset history equipment adjustment library according to a preset matching rule by taking the first energy consumption adjustable state and the process role as references; And determining a power adjustment value, a power adjustment direction and an execution time sequence corresponding to the target equipment by taking the history adjustment record as a reference to form a regulation strategy.
10. A microgrid energy conservation optimization system, the system comprising: The micro-grid structure construction module is used for carrying out hierarchical division on energy utilization objects of the micro-grid to obtain a hierarchical relation and a hierarchical node, constructing a micro-grid structure diagram according to the hierarchical relation and the hierarchical node, wherein the hierarchical node comprises an enterprise level node, a workshop level node, a production line level node and a device level node, and the micro-grid structure diagram comprises a first sub-graph, a second sub-graph and a third sub-graph; the equipment-level energy consumption analysis module is used for carrying out data acquisition and analysis on the equipment-level nodes of the third sub-graph on the edge nodes close to the equipment, acquiring state data and electricity consumption demand data, and forming a first energy consumption adjustable state of the equipment level based on the state data and the electricity consumption demand data, wherein the first energy consumption adjustable state is used for representing an allowable energy consumption adjustment range of the equipment under the current running condition; the energy consumption state aggregation module is used for aggregating the first energy consumption adjustable states layer by layer upwards according to the hierarchical relationship to obtain a second enterprise-level energy consumption adjustable state; The node screening module is used for screening the micro-grid structure diagram based on the second energy consumption adjustable state, determining a target enterprise level node, screening the first sub-graph and the second sub-graph layer by layer according to the hierarchical relationship, and determining a target production line level node; the target equipment determining module is used for acquiring a third sub-graph corresponding to the target production line level node, and determining a target equipment set from the third sub-graph according to the first energy consumption adjustable state, wherein the target equipment set at least comprises one target equipment; the regulation strategy generation module is used for matching the target equipment with a preset historical equipment regulation library and generating a regulation strategy of the target equipment by combining the first energy consumption adjustable state; and the execution control module is used for controlling the target equipment to execute the regulation strategy so as to realize energy-saving optimization control of the micro-grid.

Description

Micro-grid energy-saving optimization system and control method Technical Field The application relates to the technical field of energy-saving control of micro-grids, in particular to an energy-saving optimization system and a control method of the micro-grids. Background With the development of smart grid technology, an industrial enterprise power supply and distribution system gradually evolves from a traditional single power supply mode to a mode of cooperative operation of a centralized power grid and distributed energy sources, and the distributed energy sources such as photovoltaic power generation and energy storage equipment are continuously connected, so that an enterprise side generally performs unified organization and management on multiple power supplies and multiple loads in a micro-grid mode. Under the background, with the increasing abundance of load types and the increasing requirements on energy supply reliability and economy, the fluctuation of electricity price, the constraint of demand and the pressure of energy cost are continuously aggravated, and the energy consumption optimization control requirement of enterprises on the micro-grid level is increasingly outstanding. The existing micro-grid energy-saving control technology takes equipment, a loop or a local area as an independent control unit, and performs power limitation or operation adjustment based on historical statistics or a preset energy consumption threshold value respectively, so that the micro-grid energy consumption optimization control is realized. The industrial micro-grid is used as a complex system comprising multiple elements such as a power supply, a power grid, load, energy storage and the like, the inter-coupling energy flow topological relation and process time sequence constraint exist between the equipment level and the system level, the existing dispatching mode mainly controlled by units respectively lacks a unified depicting mechanism for the active power adjusting space and the operation constraint of each level energy utilization unit, so that the consistency of the cross-layer constraint cannot be checked in the generation stage by the existing dispatching strategy, and further, the energy-saving dispatching instruction generated based on the local unit cannot land due to the fact that the operation condition or the whole power balance requirement of other units are violated in the actual execution, and even the safety risks such as voltage out-of-limit or protection misoperation are caused, so that the problem that the feasibility and the safety are difficult to consider in engineering application of the whole energy-saving optimization of the micro-grid is caused. Disclosure of Invention The embodiment of the application provides an energy-saving optimizing system and a control method for a micro-grid, which are used for reasonably distributing and regulating and controlling the power of key equipment by collecting the running state and the energy consumption characteristic of the equipment in the micro-grid and combining a hierarchical structure and the energy consumption adjustable state of the equipment, so that the quantitative management and the optimal control of the whole energy consumption regulating capacity of the micro-grid are realized, and the execution continuity and the execution stability of production tasks are ensured. In order to achieve the above purpose, the application adopts the following technical scheme: The embodiment of the application provides an energy-saving optimization control method for a micro-grid, which comprises the steps of carrying out hierarchical division on energy consumption objects of the micro-grid to obtain a hierarchical relation and hierarchical nodes, constructing a micro-grid structure diagram according to the hierarchical relation and the hierarchical nodes, wherein the hierarchical nodes comprise enterprise level nodes, workshop level nodes, production line level nodes and equipment level nodes, the micro-grid structure diagram comprises a first sub-graph, a second sub-graph and a third sub-graph, carrying out data extraction on the equipment level nodes of the third sub-graph to obtain state data and electricity consumption demand data, carrying out information association analysis and constraint matching processing on the state data and the electricity consumption demand data to form a first energy consumption adjustable state of the equipment level, wherein the first energy consumption adjustable state is used for representing the adjustable energy consumption capability of the equipment under the current operation condition, carrying out layer-by-layer aggregation according to the hierarchical relation to obtain a second energy consumption adjustable state of the enterprise level, screening the micro-grid structure diagram, determining a target level node, carrying out information association analysis on the state data and the electricity consump