CN110955782B - Knowledge graph-based scheduling control knowledge representation method - Google Patents
Knowledge graph-based scheduling control knowledge representation method Download PDFInfo
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- G06F16/30—Information retrieval; Database structures therefor; File system structures therefor of unstructured textual data
- G06F16/36—Creation of semantic tools, e.g. ontology or thesauri
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Abstract
The invention discloses a scheduling control knowledge representation method based on a knowledge graph, which adopts a knowledge graph architecture to represent power grid regulation knowledge as a network of entities and relations. The power grid regulation and control knowledge is oriented to an actually existing power system and is summarized in a power system dispatching production control link. The entity comprises: physical equipment body, system running state body, physical phenomenon body, plan management body and control operation body. The knowledge graph-based dispatching control knowledge representation method provided by the invention can comprehensively regulate and control knowledge points, establish a representation model of the regulating and controlling knowledge points, characterize the relation among the regulating and controlling knowledge points, provide a path for quickly inquiring the knowledge points for a dispatcher, and provide a basic knowledge model for storage and deepening research of dispatching knowledge such as follow-up knowledge reasoning, knowledge service and the like.
Description
Technical Field
The invention relates to a knowledge graph-based dispatching control knowledge representation method, and belongs to the technical field of dispatching control application of power systems.
Background
With the construction of extra-high voltage direct current, the large amount of access of new energy sources and the increase of direct current loads at a power distribution side, the characteristics of a power supply, a structure, loads and the like of a power system are changed, particularly, the power market is released, the reliability requirement of power supply is higher, the uncertainty factor of power grid operation is increased, the pressure of safe and stable operation of the power grid is increased, and the requirements on the in-site processing capacity of a dispatcher are higher. The power grid is guaranteed to run continuously, stably and normally, the power supply reliability is guaranteed, and the electric energy quality accords with the national standard, so that the power grid is an important part of the work of a dispatcher.
Under the current situation, the latest achievements of artificial intelligence development are utilized, field expert knowledge is concentrated, a scheduling rule knowledge base is constructed by utilizing a crowd-sourced technology, a foundation is constructed for the deep application of scheduling control knowledge, references are provided for the learning training, the regulation and control operation and the like of regulation and control personnel, and the method is an effective method for assisting the regulation and control personnel in improving the accident handling capability.
The dispatching control knowledge comprises various contents such as power grid regulation and control operation, power grid operation, fault treatment and the like, has wide range, complex related rules, builds a huge dispatcher knowledge base, also needs to provide a light weight expression method of the knowledge, provides a means for quickly inquiring the knowledge by a dispatcher, and timely meets the requirements of normal operation and accident treatment of the dispatcher.
The knowledge base construction comprises five parts of knowledge acquisition, knowledge verification, knowledge representation, inference and interpretation. The method for representing the scheduling knowledge is a key link for constructing a scheduling knowledge base, and can assist a dispatcher to learn the regulating knowledge or provide an auxiliary means in operation to assist in sensing and judging the running state of the power system and provide an auxiliary decision support means.
The existing scheduling control knowledge comprises application forms and operation tickets applied in power scheduling control work, various teaching materials, regulations, specifications, standard specifications and the like. The knowledge base is constructed, the power dispatching control knowledge is required to be analyzed into a form which can be understood by a computer, a semantic model is constructed, a knowledge representation method is formed, and knowledge storage is provided for inquiring and reasoning of the power dispatching control knowledge.
At present, no knowledge base oriented to regulatory knowledge exists, research of auxiliary scheduling by utilizing an artificial intelligence technology is just started, and a learner develops research aiming at semantic analysis of a structured text of the regulatory knowledge, but research of a representation method oriented to the regulatory knowledge is not reported yet.
Disclosure of Invention
The purpose is as follows: in order to solve the problem of light weight expression of regulatory knowledge, and simultaneously to provide a supporting means for rapid query reasoning of the regulatory knowledge, and to provide a representation mode which is convenient for knowledge service for application of the regulatory knowledge, the invention provides a scheduling control knowledge representation method based on a knowledge graph.
The technical scheme is as follows: in order to solve the technical problems, the invention adopts the following technical scheme:
a scheduling control knowledge representation method based on a knowledge graph adopts a knowledge graph architecture to represent power grid regulation knowledge as a network of entities and relations.
As a preferable scheme, the power grid regulation knowledge is oriented to an actually existing power system and is summarized in a power system dispatching production control link.
Preferably, the entity includes: physical equipment body, system running state body, physical phenomenon body, plan management body and control operation body.
Preferably, the physical device body is described as follows: { physical device name ontology, physical device parameter ontology, physical device state ontology, physical device operation parameter ontology };
the physical device name ontology describes the scheduling name of the device;
the physical equipment parameter ontology describes the model of equipment, parameters related to the equipment, characteristics and topological connection relations; the topology connection relation is based on the overall topology of the power system, an overall topology relation is built, and each device extracts respective information from the overall topology as a topology relation identification code;
the physical device state ontology describes the current running state of the device;
the physical equipment operation parameter ontology describes parameters representing the equipment operation state;
the operating state of the physical device corresponds to a particular physical device operating parameter.
Preferably, the system operation state body is described as follows:
{ System operation Normal status body, system operation alert status body, system operation Emergency status body, system operation crash status body, system operation recovery status body, status adjustment measures body };
the system operation normal state body, the system operation warning state body, the system operation emergency state body and the system operation breakdown state body are used for describing the equipment state of the system and the range of system operation parameters when the system is in the normal state, the warning state, the emergency state, the breakdown state and the recovery state; the state adjustment measure body expresses the specific measures taken to adjust the running state of the system.
Preferably, the physical phenomenon body corresponds to a physical phenomenon represented by a physical quantity representing an operation state of the system, and includes: normal, critical, out of limit, and give countermeasures, described as follows:
{ normal { voltage, current, power angle, frequency }, critical { voltage, current, power angle, frequency }, out of limit { voltage, current, power angle, frequency }, countermeasures }.
As a preferable scheme, the plan management entity is used for planning running states and controlling operation measures corresponding to different times of the physical equipment, and the following description is given:
{ planning time, planning equipment status, planning control actions }.
As a preferable solution, the control operation body corresponds to a control operation measure for the physical device, and is described as follows:
{ control time, control device, control content }.
Preferably, the relationship includes:
the relation among the physical equipment bodies is an electrical connection relation and is embodied as a physical relation among electrical quantities;
the physical equipment operation parameter body of the physical equipment body has a corresponding relation with the physical phenomenon body, and the specific content of each body in the physical phenomenon body is deduced according to the operation parameters of the physical equipment; under the normal system running state, the plan management entity adjusts the physical equipment parameter entity content of the physical equipment according to the plan content; the control operation body controls the physical equipment body according to the control content, so that the equipment switching and the equipment adjusting state in the physical equipment running state parameter body are changed;
the system running state body judges the specific content of each body in the system running state body according to the physical equipment state bodies in the plurality of physical equipment bodies; different system running state bodies correspond to different physical phenomenon bodies; when the running state of the system needs to be adjusted, issuing a control operation instruction to the control operation body according to the content of the state adjustment measure body in the running state body of the system; in a normal system operation state, the system operation state ontology manages new contents of the ontology according to a plan, and adjusts system parameters of the normal operation state;
the physical phenomenon ontology obtains physical quantity parameters from the physical equipment ontology and the system running state ontology, and deduces the specific content of each ontology in the physical phenomenon ontology; and issuing a control operation instruction to the control operation body according to the countermeasure of the physical phenomenon.
The plan management body corresponds to a working plan of the actual physical equipment, and the switching of the running state of the equipment is completed through control operation; the plan management body only acts when the system running state is normal, and issues plan control operation measures to the control operation body according to the content of the system running normal state body and the physical equipment body in the system running state body;
the control operation body receives control instructions from the planning control operation measures, the state adjustment measure body and the counter measures, and the control operation of the physical equipment state body is completed.
The beneficial effects are that: the knowledge graph-based dispatching control knowledge representation method provided by the invention can comprehensively regulate and control knowledge points, establish a representation model of the regulating and controlling knowledge points, characterize the relation among the regulating and controlling knowledge points, provide a path for quickly inquiring the knowledge points for a dispatcher, and provide a basic knowledge model for storage and deepening research of dispatching knowledge such as follow-up knowledge reasoning, knowledge service and the like.
Drawings
FIG. 1 is a schematic diagram of a regulatory ontology and ontology relationship;
fig. 2 is a schematic diagram of an example frequency control physical device body electrical coupling relationship.
Detailed Description
The invention will be further described with reference to the accompanying drawings.
The power grid regulation knowledge can adopt a representation method of a knowledge graph, wherein the knowledge graph is a network consisting of entities and relations. Nodes represent entities (concepts) in the physical world and edges represent interrelationships between the entities. The regulation knowledge is the knowledge summarized in the dispatching production control link of the power system, and therefore, the corresponding relation of the information physical system can be used for expressing the relation between the regulation knowledge points and the regulation knowledge points. The regulation knowledge representation method provided by the invention constructs an initial framework of the regulation knowledge, and the detail content can be enriched under the framework.
1 control ontology
The core of the scheduling knowledge is to ensure safe and economical operation of the power system, ensure reliable power supply of the power grid and ensure the power supply quality. The basis of dispatcher post operation is mainly data information fed back by various acquisition devices and information provided by monitoring personnel, and the actual operation parameters of a power grid are combined, so that various production work development conditions are comprehensively considered, and the on-off of the devices, voltage, current, frequency and load are controlled. Therefore, the regulation and control ontology can be built by taking the actual ontology in the physical world as a center, namely taking physical equipment as a core.
The concept and the attribute of the physical equipment are surrounded, and the system running state, the physical phenomenon, the plan management and the control operation body can be expanded aiming at the regulation management and the operation of the physical equipment.
1.1 physical device body
The physical device body directly corresponds to the actual physical device in the power grid. The concepts and attributes of the method are in one-to-one correspondence with the physical devices. The attribute facing the dispatching work is mainly an electrical attribute and can be characterized by physical quantity.
The physical device body is described as follows:
{ physical device name ontology, physical device parameter ontology, physical device state ontology, physical device operation parameter ontology }
The physical device name ontology describes the scheduling name of the device;
the physical equipment parameter ontology describes the model of equipment, parameters related to the equipment, characteristics and topological connection relations; the topology connection relation can be based on the whole topology of the power system, the whole topology relation is built, and each device extracts respective information from the whole topology as a topology relation identification code. If the electrical relationship of the power system is described in terms of device connection points, each device may identify its topological location in the system with the node number of the device connection.
The physical device state ontology describes the current running state of the device, such as input, exit, normal, overload, accident;
physical device operating parameter ontologies describe parameters that characterize the operating state of a device, such as voltage, current, power, temperature.
The operating state of the physical device corresponds to a particular physical device operating parameter.
1.2 System running State ontology
Different running states of the power system and corresponding state adjustment measures in the scheduling range corresponding to the system running state body are described as follows:
{ System operation Normal status body, system operation alert status body, system operation Emergency status body, system operation crash status body, system operation recovery status body, state adjustment measures body }
The system running state bodies are used for describing the equipment states of the system and the range of the running parameters of the system when the system is in different running states, wherein the different running states comprise a normal state, an alert state, an emergency state, a crash state and a recovery state. The state adjustment measure body expresses the specific measures taken to adjust the running state of the system.
1.3 physical phenomenon ontology
The physical phenomenon body corresponds to a physical phenomenon represented by a physical quantity representing the running state of the system, and comprises the following steps: normal, critical, out of limit, and countermeasures are given. The description is as follows:
{ normal { voltage, current, power angle, frequency }, critical { voltage, current, power angle, frequency }, out of limit { voltage, current, power angle, frequency }, countermeasures }.
1.4 plan management ontology
The plan management body is used for planning running states and controlling operation measures corresponding to different times of the physical equipment, and the description is as follows:
{ planning time, planning plant status, planning control action }
1.5 control operation body
The control operation body corresponds to a control operation measure for the physical device. Such as equipment switching, generator regulation, load regulation. The description is as follows:
{ control time, control device, control content }
2 regulating and controlling the relationship between knowledge bodies
The relationship among the regulating knowledge bodies is shown in figure 1. There is a physical relationship and also a management control relationship.
The relationship between the physical equipment bodies is an electrical connection relationship, and is embodied as a physical relationship between electrical quantities. The relationships between physical device ontologies may be described using an electrical topology matrix.
The physical equipment operation parameter body of the physical equipment body has a corresponding relation with the physical phenomenon body, and the specific content of each body in the physical phenomenon body can be deduced according to the operation parameters of the physical equipment; under the normal system running state, the plan management entity can adjust the physical equipment parameter entity content of the physical equipment according to the plan content; the control operation body can also control the physical equipment body according to the control content, so that the equipment switching and the equipment adjusting state in the physical equipment running state parameter body are changed.
The system running state bodies have no direct relation, the physical quantity of the equipment changes when the system runs, different physical phenomena are represented, and the running state changes; or through state adjustment operation, the state switching is realized. The system running state ontology judges the specific content of each ontology in the system running state ontology by reasoning according to the physical equipment state ontologies in the plurality of physical equipment ontologies; different system running state bodies correspond to different physical phenomenon bodies; when the running state of the system needs to be adjusted, issuing a control operation instruction to the control operation body according to the content of the state adjustment measure body in the running state body of the system; in the normal system operation state, the system operation state body can manage new contents of the body according to a plan and adjust system parameters of the normal operation state.
The physical phenomenon bodies are not in direct relation, different physical phenomena can be represented when the running state of the system changes, different running parameters of corresponding equipment are corresponding, and countermeasures are needed to be given according to the physical phenomena when the time limit is exceeded.
The physical phenomenon ontology obtains physical quantity parameters from the physical equipment ontology and the system running state ontology, and deduces the specific content of each ontology in the physical phenomenon ontology; and issuing a control operation instruction to the control operation body according to the countermeasure of the physical phenomenon.
The plan management body corresponds to the work plan of the actual physical equipment, and the switching of the running state of the equipment is completed through control operation.
The plan management body only acts when the system running state is normal, and issues plan control operation measures to the control operation body according to the content of the system running normal state body and the physical equipment body in the system running state body.
The control operation body receives control instructions from the planning control operation measure body, the state adjustment measure body and the counter measure body, and the control operation of the physical equipment state body is completed.
Examples:
as shown in fig. 2, taking frequency control of a power system consisting of a simple generator, a power transmission line and a load as an example, according to the regulation knowledge representation framework provided by the invention, a constructed power system frequency control knowledge graph is exemplified as follows:
2.1 physical device body
The physical equipment body related to frequency control comprises a generator, a power transmission line and a load body related to frequency change, and is described as follows:
2.1.1 generators in the system are all related to the system frequency, so the generator body comprises all generators or equivalent generators within the regulation range, and is described as follows:
{ Generator name, generator parameters { Generator Equipment parameters, generator Power frequency characteristics, topological connection relationship }, generator State { input, exit, normal, overload, accident }, generator operating parameters { Voltage, current, frequency, power }
2.1.2 the transmission line connects the generator with the load as follows:
{ Transmission line name, transmission line parameter { Transmission line Electrical parameter, topological connection relation }, transmission line State { input, exit, normal, overload, accident }, transmission line operating parameter { Voltage, current, frequency, power }
2.1.3 the load body builds only frequency dependent loads, described as follows:
{ load name, load parameter { load electrical parameter, load frequency characteristic, topological connection relation }, load state { input, exit, normal, overload, accident }, load operation parameter { voltage, current, frequency, power }
2.2 System running State ontology
The system operation state ontology of the system frequency control is described as follows:
{ System Normal status body, system alert status body, system Emergency status body, system crash status body, system recovery status body, system frequency status adjustment measures body }
Normal, alert, emergency, crash and recovery states of system operation characterize the operating condition of the system and may consist of a series of equations or inequalities that characterize the operating condition.
The system frequency state adjustment measure body is a frequency control countermeasure set, and is a frequency control measure set of a generator, a line or a load in a dispatching range.
2.3 physical phenomenon ontology
The physical phenomenon ontology of system frequency control is described as follows:
{ frequency is normal { voltage, current, power angle, frequency }, frequency out of limit { voltage }, current, power angle, frequency control countermeasures }
Specific frequency control corresponding measures can be configured according to the state values of the physical quantities under the normal or out-of-limit state of the system operating frequency.
2.4 plan management ontology
The scheduling related to the frequency control mainly comprises the steps of making a power generation plan for a generator in a normal running state according to load prediction information, arranging an overhaul and maintenance plan of equipment, and configuring corresponding switching measures, so that the range of the frequency control can be determined. The description is as follows:
{ planning time, planning plant status, planning control action }
2.5 control operation body
The frequency control operation content comprises primary frequency modulation, secondary frequency modulation, high-frequency cutting, low-frequency load shedding, low-frequency starting of a unit and load control. The frequency control operation body is described as follows:
{ control time, generator frequency control content { Primary frequency modulation, secondary frequency modulation, high frequency cut-off, low frequency Start }
{ control time, transmission line, line frequency control content { Low frequency load shedding }
{ control time, load frequency control content { load switching }
2.6 frequency control of relationships between ontologies
The physical equipment body can be established based on the electrical connection relation, the electrical connection point of the whole system is numbered, and the topology number of each physical equipment can be represented by the number of the upstream node and the downstream node. Forward current flows into the physical device from the upstream node and out from the downstream node. The electrical connection between the devices can be obtained through the number of the electrical connection points of the devices. As shown in fig. 2.
The system running state bodies have no direct relation, the physical quantity of the equipment changes when the system runs, different physical phenomena are represented, and the running state changes; or through state adjustment and frequency control operation, the state switching is realized.
The physical phenomenon bodies are not in direct relation, different physical phenomena can be represented when the running state of the system changes, different running parameters of corresponding equipment are corresponding, and countermeasures are needed to be given according to the physical phenomena when the time limit is exceeded.
The plan management body corresponds to the work plan of the actual physical equipment, and the switching of the running state of the equipment is completed through control operation.
The control operation receives the control instruction of the plan control operation measure from the plan management body, the system frequency state adjustment measure of the system running state body or the frequency control counter measure body of the physical phenomenon, and the control operation of the running state of the physical equipment is completed.
The foregoing is only a preferred embodiment of the invention, it being noted that: it will be apparent to those skilled in the art that various modifications and adaptations can be made without departing from the principles of the present invention, and such modifications and adaptations are intended to be comprehended within the scope of the invention.
Claims (1)
1. A scheduling control knowledge representation method based on a knowledge graph is characterized by comprising the following steps of: the knowledge graph architecture is adopted to represent the power grid regulation knowledge as a network of entities and relations;
the power grid regulation knowledge is oriented to an actually existing power system and is summarized in a power system dispatching production control link;
the entity comprises: physical equipment body, system running state body, physical phenomenon body, plan management body and control operation body;
the physical device body is described as follows: { physical device name ontology, physical device parameter ontology, physical device state ontology, physical device operation parameter ontology };
the physical device name ontology describes the scheduling name of the device;
the physical equipment parameter ontology describes the model of equipment, parameters related to the equipment, characteristics and topological connection relations; the topology connection relation is based on the overall topology of the power system, an overall topology relation is built, and each device extracts respective information from the overall topology as a topology relation identification code;
the physical device state ontology describes the current running state of the device;
the physical equipment operation parameter ontology describes parameters representing the equipment operation state;
the operation state of the physical equipment corresponds to specific operation parameters of the physical equipment;
the system operation state ontology is described as follows:
{ System operation Normal status body, system operation alert status body, system operation Emergency status body, system operation crash status body, system operation recovery status body, status adjustment measures body };
the system operation normal state body, the system operation warning state body, the system operation emergency state body and the system operation breakdown state body are used for describing the equipment state of the system and the range of system operation parameters when the system is in the normal state, the warning state, the emergency state, the breakdown state and the recovery state; the state adjustment measure body expresses the specific measure adopted for adjusting the running state of the system;
the physical phenomenon body corresponds to a physical phenomenon represented by a physical quantity representing the running state of the system, and comprises the following components: normal, critical, out of limit, and give countermeasures, described as follows:
{ normal { voltage, current, power angle, frequency }, critical { voltage, current, power angle, frequency }, out-of-limit { voltage, current, power angle, frequency }, countermeasures };
the plan management body is used for corresponding to the plan running states and control operation measures of the physical equipment at different times, and the description is as follows:
{ planning time, planning equipment status, planning control actions };
the control operation body corresponds to control operation measures aiming at physical equipment and is described as follows:
{ control time, control device, control content };
the relationship includes:
the relation among the physical equipment bodies is an electrical connection relation and is embodied as a physical relation among electrical quantities;
the physical equipment operation parameter body of the physical equipment body has a corresponding relation with the physical phenomenon body, and the specific content of each body in the physical phenomenon body is deduced according to the operation parameters of the physical equipment; under the normal system running state, the plan management entity adjusts the physical equipment parameter entity content of the physical equipment according to the plan content; the control operation body controls the physical equipment body according to the control content, so that the equipment switching and the equipment adjusting state in the physical equipment running state parameter body are changed;
the system running state body judges the specific content of each body in the system running state body according to the physical equipment state bodies in the plurality of physical equipment bodies; different system running state bodies correspond to different physical phenomenon bodies; when the running state of the system needs to be adjusted, issuing a control operation instruction to the control operation body according to the content of the state adjustment measure body in the running state body of the system; in a normal system operation state, the system operation state ontology manages new contents of the ontology according to a plan, and adjusts system parameters of the normal operation state;
the physical phenomenon ontology obtains physical quantity parameters from the physical equipment ontology and the system running state ontology, and deduces the specific content of each ontology in the physical phenomenon ontology; issuing a control operation instruction to the control operation body according to countermeasure of the physical phenomenon;
the plan management body corresponds to a working plan of the actual physical equipment, and the switching of the running state of the equipment is completed through control operation; the plan management body only acts when the system running state is normal, and issues plan control operation measures to the control operation body according to the content of the system running normal state body and the physical equipment body in the system running state body;
the control operation body receives control instructions from the planning control operation measures, the state adjustment measure body and the counter measures, and the control operation of the physical equipment state body is completed.
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