CN115545197B - Power grid regulation and control decision knowledge model construction method and device - Google Patents
Power grid regulation and control decision knowledge model construction method and device Download PDFInfo
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Abstract
The invention discloses a method and a device for constructing a power grid regulation decision knowledge model, which are used for realizing digital conversion of a power grid stable operation regulation text. The method comprises the following steps: establishing an outermost layer structure of a knowledge model of a power grid regulation decision, and determining a power grid stable operation stipulated object; establishing a second layer structure of a knowledge model, and determining a power grid stable operation stipulated object list and an operation information variable list of power grid stable operation stipulated objects; establishing a third layer structure of a knowledge model, and determining a power grid stable operation stipulated object list, a power grid stable operation stipulated other attribute object list, a mode/sub-mode object list and a mode variable list; establishing a fourth layer structure of a knowledge model, and determining a rule object list of a mode/sub-mode object list; and establishing a fifth layer structure of the knowledge model, and determining a rule list of the rule object list.
Description
Technical Field
The invention relates to the technical field of power grid regulation and control, in particular to a power grid regulation and control decision knowledge model construction method and device.
Background
At present, regulation electronic dynamic quota has been developed, but at present, knowledge such as a power grid operation mode, a security policy rule and the like is recorded and described by using a script file, and a programmed knowledge rule representation mode is adopted, so that a user is difficult to confirm and use a service rule; meanwhile, the scripted input, the correctness check and the daily maintenance are very complex, and the workload is large; and the intelligent power grid operation control system cannot be seamlessly integrated with other services of the regulation and control system to form a decision support system, and is integrated into a dispatching operation system to intelligently guide and control the power grid operation. Therefore, the current electronic application effect of the dispatching rules is poor, the dispatching rules cannot be embedded into the dispatching business main flow, and the auxiliary degree of the decision making process of a dispatcher is low.
Disclosure of Invention
Aiming at the defects of the prior art, the invention provides a method and a device for constructing a power grid regulation and control decision knowledge model.
According to one aspect of the invention, a power grid regulation and control decision knowledge model construction method is provided, which is used for realizing digital conversion of a power grid stable operation regulation text, and comprises the following steps:
establishing an outermost layer structure of a knowledge model of a power grid regulation decision, and determining a power grid stable operation stipulated object;
establishing a second layer structure of a knowledge model, and determining a power grid stable operation stipulated object list and an operation information variable list of power grid stable operation stipulated objects;
Establishing a third layer structure of a knowledge model, and determining a power grid stable operation stipulated object list, a power grid stable operation stipulated other attribute object list, a mode/sub-mode object list and a mode variable list;
establishing a fourth layer structure of a knowledge model, and determining a rule object list of a mode/sub-mode object list;
and establishing a fifth layer structure of the knowledge model, and determining a rule list of the rule object list.
Optionally, the grid steady operation regulation object includes at least one of the following properties: grid steady operation regulation catalog ID, grid steady operation regulation document ID, digital grid steady operation regulation file export time, digital grid steady operation regulation file type, basic test case name and user name.
Optionally, the grid steady operation specification object list contains a plurality of grid steady operation specifications and at least one of the following attributes: each grid steady operation specification name, each grid steady operation specification ID, whether it is a multi-way decision, whether it is a temporary grid steady operation specification, and a replacement grid steady operation specification ID.
Optionally, the multi-modal decisions include single modal decisions, multi-modal decisions, and common modal decisions, wherein
The mode and rule logic execution result in the single mode decision is unique;
executing all modes and rule logic expressions of the multi-mode decision, and returning all mode and rule execution results;
common mode decision nesting defines a multi-layer sub-mode.
Optionally, the running information variable list contains at least one of the following attributes: operation information ID, power grid stable operation regulation ID, operation information variable name, operation information variable data type, parameter identification, operation information calculation formula and equipment mapping.
Optionally, the grid stable operation specifies that the other attribute object includes at least one of the following attributes: other attribute objects of the power grid stable operation rule, effective time of the power grid stable operation rule under deduction conditions and node identification;
the mode/sub-mode object list contains at least one of the following attributes: a mode/sub-mode object list, a mode/sub-mode name, a mode/sub-mode expression, a rule object list, a formatted mode/sub-mode expression, and a gear identification;
the mode variable list contains at least one of the following attributes: a mode variable list, a running information ID and a parameter identification.
Optionally, the rule object list contains at least one of the following attributes: parent mode name, child mode expression, rule object list, whether control identification is needed, formatting child mode expression, and child mode name.
Optionally, the rule list contains at least one of the following attributes: rule ID, rule name, rule expression, section name, out-of-limit prompt information, formatted rule expression and basic power grid stable operation regulation ID.
According to another aspect of the present invention, there is provided a power grid regulation and control decision knowledge model construction device for implementing digital conversion of a power grid steady operation specification text, which is characterized by comprising:
the first building module is used for building an outermost layer structure of a knowledge model of a power grid regulation decision and determining a power grid stable operation stipulated object;
the second building module is used for building a second layer structure of the knowledge model and determining a power grid stable operation stipulated object list and an operation information variable list of the power grid stable operation stipulated object;
the third building module is used for building a third layer structure of the knowledge model and determining other attribute objects, mode/sub-mode object lists and mode variable lists of the power grid stable operation regulation object list of the power grid stable operation regulation;
A fourth building module, configured to build a fourth layer structure of the knowledge model, and determine a rule object list of the mode/sub-mode object list;
and a fifth establishing module, configured to establish a fifth layer structure of the knowledge model, and determine a rule list of the rule object list.
According to a further aspect of the present invention there is provided a computer readable storage medium storing a computer program for performing the method according to any one of the above aspects of the present invention.
According to still another aspect of the present invention, there is provided an electronic device including: a processor; a memory for storing the processor-executable instructions; the processor is configured to read the executable instructions from the memory and execute the instructions to implement the method according to any of the above aspects of the present invention.
Therefore, the modeling method of the power grid regulation decision-making knowledge model is provided, the standardized and normalized modeling of the power grid stable operation regulation document is realized by constructing the power grid stable operation regulation structure in a layering manner, the relation between the power grid operation mode and the section limit is obtained, the stable regulation rule which can be directly processed by a computer is directly generated from the stable regulation model library, and the stable regulation document which can be read and understood by a person is realized, so that the problem that the automation, standardization and digitization degree of the stable regulation is not high is fundamentally solved.
Drawings
Exemplary embodiments of the present invention may be more completely understood in consideration of the following drawings:
FIG. 1 is a schematic flow chart of a power grid regulation and control decision knowledge model construction method according to an exemplary embodiment of the invention;
FIG. 2 is a diagram of a grid steady operation regulation object provided by an exemplary embodiment of the present invention;
FIG. 3 is a schematic structural diagram of a power grid regulation and control decision knowledge model building device according to an exemplary embodiment of the present invention;
fig. 4 is a structure of an electronic device provided in an exemplary embodiment of the present invention.
Detailed Description
Hereinafter, exemplary embodiments according to the present invention will be described in detail with reference to the accompanying drawings. It should be apparent that the described embodiments are only some embodiments of the present invention and not all embodiments of the present invention, and it should be understood that the present invention is not limited by the example embodiments described herein.
It should be noted that: the relative arrangement of the components and steps, numerical expressions and numerical values set forth in these embodiments do not limit the scope of the present invention unless it is specifically stated otherwise.
It will be appreciated by those of skill in the art that the terms "first," "second," etc. in embodiments of the present invention are used merely to distinguish between different steps, devices or modules, etc., and do not represent any particular technical meaning nor necessarily logical order between them.
It should also be understood that in embodiments of the present invention, "plurality" may refer to two or more, and "at least one" may refer to one, two or more.
It should also be appreciated that any component, data, or structure referred to in an embodiment of the invention may be generally understood as one or more without explicit limitation or the contrary in the context.
In addition, the term "and/or" in the present invention is merely an association relationship describing the association object, and indicates that three relationships may exist, for example, a and/or B may indicate: a exists alone, A and B exist together, and B exists alone. In the present invention, the character "/" generally indicates that the front and rear related objects are an or relationship.
It should also be understood that the description of the embodiments of the present invention emphasizes the differences between the embodiments, and that the same or similar features may be referred to each other, and for brevity, will not be described in detail.
Meanwhile, it should be understood that the sizes of the respective parts shown in the drawings are not drawn in actual scale for convenience of description.
The following description of at least one exemplary embodiment is merely exemplary in nature and is in no way intended to limit the invention, its application, or uses.
Techniques, methods, and apparatus known to one of ordinary skill in the relevant art may not be discussed in detail, but where appropriate, the techniques, methods, and apparatus should be considered part of the specification.
It should be noted that: like reference numerals and letters denote like items in the following figures, and thus once an item is defined in one figure, no further discussion thereof is necessary in subsequent figures.
Embodiments of the invention are operational with numerous other general purpose or special purpose computing system environments or configurations with electronic devices, such as terminal devices, computer systems, servers, etc. Examples of well known terminal devices, computing systems, environments, and/or configurations that may be suitable for use with the terminal device, computer system, server, or other electronic device include, but are not limited to: personal computer systems, server computer systems, thin clients, thick clients, hand-held or laptop devices, microprocessor-based systems, set-top boxes, programmable consumer electronics, network personal computers, small computer systems, mainframe computer systems, and distributed cloud computing technology environments that include any of the foregoing, and the like.
Electronic devices such as terminal devices, computer systems, servers, etc. may be described in the general context of computer system-executable instructions, such as program modules, being executed by a computer system. Generally, program modules may include routines, programs, objects, components, logic, data structures, etc., that perform particular tasks or implement particular abstract data types. The computer system/server may be implemented in a distributed cloud computing environment in which tasks are performed by remote processing devices that are linked through a communications network. In a distributed cloud computing environment, program modules may be located in both local and remote computing system storage media including memory storage devices.
Exemplary method
Fig. 1 is a flowchart of a power grid regulation and control decision knowledge model construction method according to an exemplary embodiment of the present invention. The embodiment can be applied to an electronic device, as shown in fig. 1, the power grid regulation decision knowledge model construction method 100 includes the following steps:
Optionally, the grid steady operation regulation object includes at least one of the following properties: grid steady operation regulation catalog ID, grid steady operation regulation document ID, digital grid steady operation regulation file export time, digital grid steady operation regulation file type, basic test case name and user name.
Optionally, the grid steady operation specification object list contains a plurality of grid steady operation specifications and at least one of the following attributes: each grid steady operation specification name, each grid steady operation specification ID, whether it is a multi-way decision, whether it is a temporary grid steady operation specification, and a replacement grid steady operation specification ID.
Optionally, the multi-modal decisions include single modal decisions, multi-modal decisions, and common modal decisions, wherein
The mode and rule logic execution result in the single mode decision is unique;
executing all modes and rule logic expressions of the multi-mode decision, and returning all mode and rule execution results;
common mode decision nesting defines a multi-layer sub-mode.
Optionally, the running information variable list contains at least one of the following attributes: operation information ID, power grid stable operation regulation ID, operation information variable name, operation information variable data type, parameter identification, operation information calculation formula and equipment mapping.
Optionally, the grid stable operation specifies that the other attribute object includes at least one of the following attributes: other attribute objects of the power grid stable operation rule, effective time of the power grid stable operation rule under deduction conditions and node identification;
the mode/sub-mode object list contains at least one of the following attributes: a mode/sub-mode object list, a mode/sub-mode name, a mode/sub-mode expression, a rule object list, a formatted mode/sub-mode expression, and a gear identification;
the mode variable list contains at least one of the following attributes: a mode variable list, a running information ID and a parameter identification.
Optionally, the rule object list contains at least one of the following attributes: parent mode name, child mode expression, rule object list, whether control identification is needed, formatting child mode expression, and child mode name.
Optionally, the rule list contains at least one of the following attributes: rule ID, rule name, rule expression, section name, out-of-limit prompt information, formatted rule expression and basic power grid stable operation regulation ID.
Specifically, the modeling method of the power grid regulation decision knowledge model comprises the following steps:
step 1: the method comprises the following steps of establishing an outermost structure of a knowledge model, namely a power grid stable operation stipulated object, wherein the object comprises the following properties:
id: the power grid stably operates to define a catalog ID;
docId: the power grid stable operation regulation document ID, each new power grid stable operation regulation document has unique ID;
timeStamp: digitized grid steady operation specification file export time, e.g. "2022-09-29 09:54:29.610";
rule settype: the digital power grid steady operation rule file types are divided into a whole set and a part, wherein the whole set represents all power grid steady operation rules, and the part represents a part of power grid steady operation rules selected by a user.
exportName: the name of the basic test case can be named by a user;
userName: user name.
Step 2: establishing a knowledge model second layer structure which comprises two objects: the power grid stable operation stipulates an object list and an operation information variable list.
(1) Precision graph: a list of grid steady operation specification objects may contain a plurality of grid steady operation specifications, the objects containing the following attributes:
name: a certain power grid stable operation stipulates the name;
no: the stable operation of the power grid stipulates ID;
multitable evaluation: whether the multi-mode decision is made or not, the single-mode decision has only one decision path, and the multi-mode decision can have a plurality of decision paths;
temp title plate: whether the temporary power grid stable operation regulation is provided or not is determined, wherein the temporary power grid stable operation regulation refers to maintenance regulation;
replaceId: replacing the power grid stable operation rule ID, wherein the power grid stable operation rule ID is required to be replaced;
the object list definition graph of the stable operation of the power grid is essentially a decision graph, and the structure of the decision graph is shown in fig. 2: a power grid stable operation is defined as tree structure data, a top node (entrance) of the tree structure data controls the whole execution logic of the mode, and a logic operation expression can not be defined. The power grid stable operation regulation modes can be divided into a single mode and a multi-mode: the method comprises the steps of carrying out a first treatment on the surface of the
And (2) the single mode (N is selected 1), wherein the mode and rule logic execution result is unique, when the power grid stably operates and is regulated to execute and meet a certain mode logic, the mode execution result is returned, and the other mode logic is not executed.
Multi-mode (N-): all modes and rule logic expressions are executed, and all mode and rule execution results are returned
The mode tree nodes are divided into common nodes and decision table nodes.
The method can be used for defining a multi-layer sub-mode in a nested mode, a common mode node or a decision table node or a combined mode node of the common mode node and the decision table mode node can be defined under the node, and if the mode logic is not defined, the mode logic is defaulted to be true.
And the decision list mode is a rule data attribution mode and is set through a user interface single selection. At least one monitoring rule must be defined in the form of a decision table, and checked by a format check.
Rules: simple rules contain only one rule expression; a complex rule consists of a plurality of simple rules and rule selection logic.
(2) Pictures: the list of run information variables may contain a plurality of run information variables, the object containing the following attributes:
FactsKey: an operation information ID;
precision no: the power grid stably operates to define ID;
name: the name of the running information variable can be defined by a user;
varCategamy: the operation information variable types are 11 types of units, lines, transformers, buses, circuit breakers, stability control devices, full networks, sections, generator output/startup numbers, rotary backup and rotary backup capacities, and the operation information variable types are specifically as follows:
a set for defining variables related to the generator;
and (3) line: for defining variables related to the line;
a transformer: for defining variables related to the transformer;
a bus bar: for defining variables related to the bus;
a circuit breaker: for defining variables associated with the circuit breaker;
stability control device: for defining variables associated with the stability control device;
full network: for defining variables related to the whole network;
section: for defining variables related to the section;
generator output/start-up number: the method comprises the steps of defining variables related to the output and the start-up number of the generator;
spin-on preparation%: for defining a variable associated with a swirl;
capacity of spin-on preparation: a variable for defining a capacity related to the spin-up;
dataType: the operation information variable data types comprise Double, integer, boolean, string and other types;
paramMark: a parameter identification;
mvelExp: the operation information calculation formula:
(1) the line/transformer calculation formula format is as follows:
line/transformer ('I-side busbar name', 'J-side busbar name', 'line number'/-on-line name- /)
(2) The breaker calculation formula format is as follows:
circuit breaker ('I side busbar name', 'J side busbar name', 'line number'/-on-line name 1; on-line name 2- /)
(3) The unit calculation formula format is as follows:
equipment-units ('offline name'/online name- /)
(4) The bus calculation formula format is as follows:
bus ('offline name'/online name 1|online name 2|online name n- /)
(5) The formula format of the power output/starting-up number calculation of the generator is as follows:
the variable identifier 1, the active output and the variable identifier 2, the active output and the variable identifier n, the active output;
variable group name ({ variable identification 1, variable identification 2 });
(6) the section calculation formula format is as follows:
The power is from end to end/power end to end
(7) The spin-on% calculation formula format is as follows:
minimum spin-up (Unit variable identification 1, unit variable identification 2, unit variable identification n)
Sum of variables rotary spare (unit variable identification 1, unit variable identification 2, unit variable identification n)
Variable set spinning ratio ({ set variable identification 1, set variable identification 2, set variable identification n }, n)
(8) The format of the calculation formula of the full network/stability control device/spin-backup capacity is as follows:
real-time library ('real-time library table number', 'real-time library data name')
deviceAliases: device mapping, key: the value format character string represents the mapping relation between the device identifier and the real physical device, and the attribute only exists when the varCategory type is the type of full network, section, startup number, spin-up capacity and the like.
Step 3: a third layer structure of the knowledge model is established, and a specified object list for stable operation of the precision graph power grid in the step 2 is formed, wherein the specified object list contains three objects in total: grid stable operation specifies other attribute objects, mode/sub-mode object lists, and mode variable lists.
(1) application condition: grid stable operation specifies other attribute objects, including the following attributes:
dateTime: the power grid stable operation specifies effective time for real-time monitoring use;
reduced time: grid stable operation specifies the effective time for deduction;
nodeType: node identification, 1, indicates a service specification.
(2) optModes: the mode/sub-mode object list may contain a plurality of mode/sub-mode objects, may be nested in layers, and contains the following attributes:
modeName: run mode/sub-mode name;
expression: the run mode/sub-mode expression contains two types, one is a defined function:
full operation: indicating that all variables selected are true;
one run: indicating that one of all variables selected is true;
at least one operation: indicating that at least one of all variables selected is true;
two runs: indicating that two of all variables selected are true;
at least two operations: indicating that at least two of all variables selected are true;
three operations: three of all variables selected are indicated as true;
at least three operations: indicating that at least three of all variables selected are true;
four operations: indicating that four of all variables selected are true;
at least four runs: indicating that at least four of all variables selected are true;
Five operations: indicating that five of all variables selected are true;
at least five runs: indicating that at least five of all variables selected are true;
the second is a user-defined expression, which supports operators of +, -,/, =, <, <=, > =, (), & +.. For example, S1 &S2 indicates that the result is true when both S1 and S2 are true, otherwise the result is false; p1>10||p2<20 means that if only one of P1>10 and P2<20 results in true, then the result is true;
precision rule set: a rule object list;
format expression: formatting the run mode/sub-mode expression;
stepper: and (3) a gear identification, namely 0-no and 1-yes, identifying whether a multi-gear rule exists in the mode, wherein the multi-gear rule only needs to meet one of requirements.
(3) inputs: the mode variable list, which may contain a plurality of mode variables, a supplier/rule object reference, contains the following attributes:
precision no: the power grid stably operates to define ID;
FactsKey: an operation information ID;
paramMark: and (5) parameter identification.
Step 4: establishing a fourth layer structure of a knowledge model, belonging to an optModes mode/sub mode object list in the step 3, wherein the list contains 1 object: the definition rule set, i.e., the rule object list, contains the following attributes:
parenntname: parent mode name;
expression: the expression of the sub-mode is defined by the expression definition method which is the same as the expression attribute of the optModes in the step (2);
rules: a rule object list, which may contain a plurality of rule objects;
control: whether control identification is needed, 0-no, 1-yes, wherein the identification indicates whether the rule needs out-of-limit control;
format expression: formatting the sub-mode expression;
modeName: sub-mode name.
Step 5: establishing a fifth layer structure of the knowledge model, which belongs to a definition rule set in the step 4, namely a rule object list, and totally comprises 1 object: a rule comprising the following attributes:
id: a rule ID;
modeName: rule names;
expression: regular expressions, user-defined expressions, which support operators of +, -,/, = =, <, <=, > =, (), & +.;
prefixWarning: section name;
rule warning: the out-of-limit prompt information comprises out-of-limit and unsatisfied two conditions;
format expression: formatting the rule expression;
baseRegId: basic grid steady operation regulation ID, the modification rule is based on the existing grid steady operation regulation to have the attribute
An example of a grid steady operation regulation structure is as follows:
{
"id": "Hunan. 2022",
"docId":"hunan2022",
"timeStamp":"2022-09-29 09:54:29.610",
"rule settype": part ",
"exportName": "basic test case",
"userName":"XXX",
"decisionGraph":[
{
"name": "40 th main transformer in the city,
"no":"1573",
"multiDTableEvaluation":true,
"tempStipulate":false,
"replaceId":0,
"applyCondition":{
"dateTime":"~",
"deduceTime":"~",
"nodeType":0
},
"optModes":[
{
"modeName": "normal mode",
"expression" func. TwoInoperation (running on the city station # 1, running on the city station # 4),
"decisionRuleSet":[
{
"parthenname": "normal mode",
"expression":"true",
"rules":[
{
"id":53384,
"modeName": "sum of main changes of the city",
"expression" from last + from last >1500 "to last + from last #4,
"prefixWarning" "Wangcheng Main transformer off-line",
"rule warning": "the main transformer of the city is out of limit,
"Format expression": "the power of the city station # 1 is changed from to last + \n the power of the city station #4 is changed from to last \n > \n 1500\n'
}
],
"control":1,
"formatExpression":"true\n",
"ModeName": "sum of main changes of the city"
}
],
"Format expression": "func.twoInoperation \n (\n. The city-to-be-visited station # 1 becomes operational\n, \n. The city-to-be-visited station #4 becomes operational\n) \n",
"stepper":0
}
],
"inputs":[
{
"decisionNo":1573,
"factsKey":5225,
"ParamMark": "Ai Guchong #2 Main transformer Power from last"
},
{
"decisionNo":1573,
"factsKey":5370,
"ParamMark": "Wangcheng station # 1 becomes operational"
},
{
"decisionNo":1573,
"factsKey":5370,
"ParamMark": "Wangcheng station # 1 changes power from last"
},
{
"decisionNo":1573,
"factsKey":5371,
"ParamMark": "Wangcheng station #4 becomes operational"
},
{
"decisionNo":1573,
"factsKey":5371,
"ParamMark": "Wangcheng station #4 variable power from last"
},
{
"decisionNo":1573,
"factsKey":5798,
ParamMark operation of Aijia circuit breaker "
},
{
"decisionNo":1573,
"factsKey":5871,
"ParamMark": "expected III line operation"
},
{
"decisionNo":1573,
"factsKey":6022,
"ParamMark": "Anning #3 Main transformer Power from last"
}
]
}
],
"facts":[
{
"factsKey":5225,
"decisionNo":1573,
"name": "Ai Guchong #2 main transformer",
"varCategary": "transformer",
"dataType":"Double",
"paramMark": "Ai Guchong #2 main transformer power from end to end",
"mvelExp": "simumodel.branch ('xiang mugwort home punch 2B500', 'xiang mugwort home punch 2B', '396433' \/-Hunan. Ai Guchong station/# 2 becomes-high-,. Powerfrom2to real".
},
{
"factsKey":5370,
"decisionNo":1573,
"name": "sight station # 1 change",
"varCategary": "transformer",
"dataType":"Boolean",
"paramMark": "Wangcheng station # 1 becomes operational",
"mvelExp": "simumodel.branch (' xiangcheng 1B500', ' xiangcheng S1', '952235 '/-lakenan. City station/# 1 becomes high-/-) isttatus '
},
{
"factsKey":5370,
"decisionNo":1573,
"name": "sight station # 1 change",
"varCategary": "transformer",
"dataType":"Double",
"paramMark": "Wangcheng station # 1 changes power from end to end",
"mvelExp": "simumodel.branch (' xiangcheng 1B500', ' xiangcheng S1', '952235 '/-lakenan. City station/# 1 becomes high-/-).powerfrom2to real '
},
{
"factsKey":5371,
"decisionNo":1573,
"name": "Wangcheng station #4 variant",
"varCategary": "transformer",
"dataType":"Boolean",
"paramMark": "Wangcheng station #4 becomes active",
"mvelExp": "simumodel.branch (' xiangcheng 4B500', ' xiangcheng S2', '952232 '/-lakenan. City station/# 4 becomes-high-/") isttatus '
},
{
"factsKey":5371,
"decisionNo":1573,
"name": "Wangcheng station #4 variant",
"varCategary": "transformer",
"dataType":"Double",
"paramMark": "Wangcheng station #4 changes power from end to end",
"mvelExp": "simumodel.branch ('xiangcheng 4B500', 'xiangcheng S2', '952232'/-lakenan. City station/# 4 becomes-high-/".
},
{
"factsKey":5798,
"decisionNo":1573,
"name": "Ai Guchong kV sectionalizer",
"varCategary": "circuit breaker",
"dataType":"Boolean",
"ParamMark": "Aijia circuit breaker is running",
"mvelExp": "simumodel. Break (' xiang Ai Guchong 220-1', ' xiang Ai Guchong-2 ', '984657 '/-Hunan. Ai Guchong station \/220kV.600 circuit breaker \ /) -isttatus '
},
{
"factsKey":5871,
"decisionNo":1573,
"name": "expected III line",
"varCategary": "line",
"dataType":"Boolean",
"ParamMark": "expected III line operation",
"mvelExp": "simumodel.branch (' Hunan Ai Guchong-220-1 ', ' Hunan Wangcheng 220', '991100 '/Hunan. Aiwang III-line \ /). Isttatus '
},
{
"factsKey":6022,
"decisionNo":1573,
"name": "Anning station #3 change",
"varCategary": "transformer",
"dataType":"Double",
"ParamMark". Anning #3 main transformer power from end to end ",
"mvelExp": "simumodel branch (',' ','/'' Huazhong 'an Ning station/# 3 become-high-/powerfrom 2to real'.
}
]
}
Therefore, the modeling method of the power grid regulation decision-making knowledge model is provided, the standardized and normalized modeling of the power grid stable operation regulation document is realized by constructing the power grid stable operation regulation structure in a layering manner, the relation between the power grid operation mode and the section limit is obtained, the stable regulation rule which can be directly processed by a computer is directly generated from the stable regulation model library, and the stable regulation document which can be read and understood by a person is realized, so that the problem that the automation, standardization and digitization degree of the stable regulation is not high is fundamentally solved.
Exemplary apparatus
Fig. 3 is a schematic structural diagram of a power grid regulation and control decision knowledge model building device according to an exemplary embodiment of the present invention. As shown in fig. 3, the apparatus 300 includes:
a first building module 310, configured to build an outermost structure of a knowledge model of a power grid regulation decision, and determine a power grid steady operation specified object;
a second building module 320, configured to build a second layer structure of the knowledge model, and determine a grid stable operation specified object list and an operation information variable list of the grid stable operation specified object;
a third building module 330, configured to build a third layer structure of the knowledge model, and determine a grid steady operation rule other attribute object, a mode/sub-mode object list, and a mode variable list of the grid steady operation rule object list;
a fourth building module 340, configured to build a fourth layer structure of the knowledge model, and determine a rule object list of the mode/sub-mode object list;
a fifth building module 350 is configured to build a fifth layer structure of the knowledge model and determine a rule list of the rule object list.
Optionally, the grid steady operation regulation object includes at least one of the following properties: grid steady operation regulation catalog ID, grid steady operation regulation document ID, digital grid steady operation regulation file export time, digital grid steady operation regulation file type, basic test case name and user name.
Optionally, the grid steady operation specification object list contains a plurality of grid steady operation specifications and at least one of the following attributes: each grid steady operation specification name, each grid steady operation specification ID, whether it is a multi-way decision, whether it is a temporary grid steady operation specification, and a replacement grid steady operation specification ID.
Optionally, the multi-modal decisions include single modal decisions, multi-modal decisions, and common modal decisions, wherein
The mode and rule logic execution result in the single mode decision is unique;
executing all modes and rule logic expressions of the multi-mode decision, and returning all mode and rule execution results;
common mode decision nesting defines a multi-layer sub-mode.
Optionally, the running information variable list contains at least one of the following attributes: operation information ID, power grid stable operation regulation ID, operation information variable name, operation information variable data type, parameter identification, operation information calculation formula and equipment mapping.
Optionally, the grid stable operation specifies that the other attribute object includes at least one of the following attributes: other attribute objects of the power grid stable operation rule, effective time of the power grid stable operation rule under deduction conditions and node identification;
The mode/sub-mode object list contains at least one of the following attributes: a mode/sub-mode object list, a mode/sub-mode name, a mode/sub-mode expression, a rule object list, a formatted mode/sub-mode expression, and a gear identification;
the mode variable list contains at least one of the following attributes: a mode variable list, a running information ID and a parameter identification.
Optionally, the rule object list contains at least one of the following attributes: parent mode name, child mode expression, rule object list, whether control identification is needed, formatting child mode expression, and child mode name.
Optionally, the rule list contains at least one of the following attributes: rule ID, rule name, rule expression, section name, out-of-limit prompt information, formatted rule expression and basic power grid stable operation regulation ID.
Exemplary electronic device
Fig. 4 is a structure of an electronic device provided in an exemplary embodiment of the present invention. As shown in fig. 4, the electronic device 40 includes one or more processors 41 and memory 42.
The processor 41 may be a Central Processing Unit (CPU) or other form of processing unit having data processing and/or instruction execution capabilities, and may control other components in the electronic device to perform desired functions.
In addition, the input device 43 may also include, for example, a keyboard, a mouse, and the like.
The output device 44 can output various information to the outside. The output device 44 may include, for example, a display, speakers, a printer, and a communication network and remote output apparatus connected thereto, etc.
Of course, only some of the components of the electronic device that are relevant to the present invention are shown in fig. 4 for simplicity, components such as buses, input/output interfaces, etc. being omitted. In addition, the electronic device may include any other suitable components depending on the particular application.
Exemplary computer program product and computer readable storage Medium
In addition to the methods and apparatus described above, embodiments of the invention may also be a computer program product comprising computer program instructions which, when executed by a processor, cause the processor to perform steps in a method according to various embodiments of the invention described in the "exemplary methods" section of this specification.
The computer program product may write program code for performing operations of embodiments of the present invention in any combination of one or more programming languages, including an object oriented programming language such as Java, C++ or the like and conventional procedural programming languages, such as the "C" programming language or similar programming languages. The program code may execute entirely on the user's computing device, partly on the user's device, as a stand-alone software package, partly on the user's computing device, partly on a remote computing device, or entirely on the remote computing device or server.
Furthermore, embodiments of the present invention may also be a computer-readable storage medium, having stored thereon computer program instructions which, when executed by a processor, cause the processor to perform the steps in a method of mining history change records according to various embodiments of the present invention described in the "exemplary methods" section above in this specification.
The computer readable storage medium may employ any combination of one or more readable media. The readable medium may be a readable signal medium or a readable storage medium. The readable storage medium can include, for example, but is not limited to, an electronic, magnetic, optical, electromagnetic, infrared, or semiconductor system, or device, or a combination of any of the foregoing. More specific examples (a non-exhaustive list) of the readable storage medium would include the following: an electrical connection having one or more wires, a portable disk, a hard disk, random Access Memory (RAM), read-only memory (ROM), erasable programmable read-only memory (EPROM or flash memory), optical fiber, portable compact disk read-only memory (CD-ROM), an optical storage device, a magnetic storage device, or any suitable combination of the foregoing.
The basic principles of the present invention have been described above in connection with specific embodiments, however, it should be noted that the advantages, benefits, effects, etc. mentioned in the present invention are merely examples and not intended to be limiting, and these advantages, benefits, effects, etc. are not to be considered as essential to the various embodiments of the present invention. Furthermore, the specific details disclosed herein are for purposes of illustration and understanding only, and are not intended to be limiting, as the invention is not necessarily limited to practice with the above described specific details.
In this specification, each embodiment is described in a progressive manner, and each embodiment is mainly described in a different manner from other embodiments, so that the same or similar parts between the embodiments are mutually referred to. For system embodiments, the description is relatively simple as it essentially corresponds to method embodiments, and reference should be made to the description of method embodiments for relevant points.
The block diagrams of the devices, systems, apparatuses, systems according to the present invention are merely illustrative examples and are not intended to require or imply that the connections, arrangements, configurations must be made in the manner shown in the block diagrams. As will be appreciated by one of skill in the art, the devices, systems, apparatuses, systems may be connected, arranged, configured in any manner. Words such as "including," "comprising," "having," and the like are words of openness and mean "including but not limited to," and are used interchangeably therewith. The terms "or" and "as used herein refer to and are used interchangeably with the term" and/or "unless the context clearly indicates otherwise. The term "such as" as used herein refers to, and is used interchangeably with, the phrase "such as, but not limited to.
The method and system of the present invention may be implemented in a number of ways. For example, the methods and systems of the present invention may be implemented by software, hardware, firmware, or any combination of software, hardware, firmware. The above-described sequence of steps for the method is for illustration only, and the steps of the method of the present invention are not limited to the sequence specifically described above unless specifically stated otherwise. Furthermore, in some embodiments, the present invention may also be embodied as programs recorded in a recording medium, the programs including machine-readable instructions for implementing the methods according to the present invention. Thus, the present invention also covers a recording medium storing a program for executing the method according to the present invention.
It is also noted that in the systems, devices and methods of the present invention, components or steps may be disassembled and/or assembled. Such decomposition and/or recombination should be considered as equivalent aspects of the present invention. The previous description of the disclosed aspects is provided to enable any person skilled in the art to make or use the present invention. Various modifications to these aspects will be readily apparent to those skilled in the art, and the generic principles defined herein may be applied to other aspects without departing from the scope of the invention. Thus, the present invention is not intended to be limited to the aspects shown herein but is to be accorded the widest scope consistent with the principles and novel features disclosed herein.
The foregoing description has been presented for purposes of illustration and description. Furthermore, this description is not intended to limit embodiments of the invention to the form disclosed herein. Although a number of example aspects and embodiments have been discussed above, a person of ordinary skill in the art will recognize certain variations, modifications, alterations, additions, and subcombinations thereof.
Claims (5)
1. The utility model provides a power grid regulation and control decision knowledge model construction method, which is used for realizing the digital conversion of a power grid stable operation regulation text, and is characterized by comprising the following steps:
establishing an outermost structure of a knowledge model of a power grid regulation decision, and determining a power grid stable operation specified object, wherein the power grid stable operation specified object comprises at least one of the following attributes: grid steady operation regulation catalog ID, grid steady operation regulation document ID, digital grid steady operation regulation document export time, digital grid steady operation regulation document type, basic test case name and user name;
establishing a second layer structure of the knowledge model, and determining a grid stable operation specified object list and an operation information variable list of the grid stable operation specified object, wherein the grid stable operation specified object list comprises a plurality of grid stable operation specifications and at least one attribute of the following: each grid steady operation rule name, each grid steady operation rule ID, whether it is a multi-way decision, whether it is a temporary grid steady operation rule, and a replacement grid steady operation rule ID, and the operation information variable list contains at least one of the following attributes: operation information ID, power grid stable operation regulation ID, operation information variable name, operation information variable data type, parameter identification, operation information calculation formula and equipment mapping;
Establishing a third layer structure of the knowledge model, and determining other attribute objects, a mode/sub-mode object list and a mode variable list of the power grid stable operation specified object list, wherein the other attribute objects comprise at least one of the following attributes: other attribute objects of the power grid stable operation rule, effective time of the power grid stable operation rule under deduction conditions and node identification;
the mode/sub-mode object list contains at least one of the following attributes: a mode/sub-mode object list, a mode/sub-mode name, a mode/sub-mode expression, a rule object list, a formatted mode/sub-mode expression, and a gear identification;
the mode variable list comprises at least one of the following attributes: a mode variable list, an operation information ID and a parameter identifier;
establishing a fourth layer structure of the knowledge model, and determining a rule object list of the mode/sub-mode object list, wherein the rule object list comprises at least one attribute of the following: parent mode name, child mode expression, rule object list, whether control identification is needed, formatting child mode expression and child mode name;
Establishing a fifth layer structure of the knowledge model, and determining a rule list of the rule object list, wherein the rule list comprises at least one of the following attributes: rule ID, rule name, rule expression, section name, out-of-limit prompt information, formatted rule expression and basic power grid stable operation regulation ID.
2. The method of claim 1, wherein the multi-modal decisions include single-modal decisions, multi-modal decisions, and common-modal decisions, wherein
The single-mode decision-making mode and rule logic execution result is unique;
all modes and rule logic expressions of the multi-mode decision are executed, and all mode and rule execution results are returned;
the common mode decision nest defines a multi-layer sub-mode.
3. The utility model provides a power grid regulation and control decision knowledge model construction device for realize the digital conversion of power grid steady operation regulation text, which is characterized by comprising:
the first building module is used for building an outermost structure of a knowledge model of a power grid regulation decision and determining a power grid stable operation specified object, wherein the power grid stable operation specified object comprises at least one of the following attributes: grid steady operation regulation catalog ID, grid steady operation regulation document ID, digital grid steady operation regulation document export time, digital grid steady operation regulation document type, basic test case name and user name;
The second building module is configured to build a second layer structure of the knowledge model, and determine a grid stable operation rule object list and an operation information variable list of the grid stable operation rule object, where the grid stable operation rule object list includes a plurality of grid stable operation rules, and includes at least one attribute of: each grid steady operation rule name, each grid steady operation rule ID, whether it is a multi-way decision, whether it is a temporary grid steady operation rule, and a replacement grid steady operation rule ID, and the operation information variable list contains at least one of the following attributes: operation information ID, power grid stable operation regulation ID, operation information variable name, operation information variable data type, parameter identification, operation information calculation formula and equipment mapping;
the third building module is configured to build a third layer structure of the knowledge model, and determine an object of other properties, a mode/sub-mode object list, and a mode variable list of the power grid stable operation rule object list, where the object of other properties includes at least one of the following properties: other attribute objects of the power grid stable operation rule, effective time of the power grid stable operation rule under deduction conditions and node identification;
The mode/sub-mode object list contains at least one of the following attributes: a mode/sub-mode object list, a mode/sub-mode name, a mode/sub-mode expression, a rule object list, a formatted mode/sub-mode expression, and a gear identification;
the mode variable list comprises at least one of the following attributes: a mode variable list, an operation information ID and a parameter identifier;
a fourth building module, configured to build a fourth layer structure of the knowledge model, and determine a rule object list of the mode/sub-mode object list, where the rule object list includes at least one attribute of: parent mode name, child mode expression, rule object list, whether control identification is needed, formatting child mode expression and child mode name;
a fifth building module, configured to build a fifth layer structure of the knowledge model, and determine a rule list of the rule object list, where the rule list includes at least one attribute of: rule ID, rule name, rule expression, section name, out-of-limit prompt information, formatted rule expression and basic power grid stable operation regulation ID.
4. A computer readable storage medium, characterized in that the storage medium stores a computer program for executing the method of any of the preceding claims 1-2.
5. An electronic device, the electronic device comprising:
a processor;
a memory for storing the processor-executable instructions;
the processor is configured to read the executable instructions from the memory and execute the instructions to implement the method of any of the preceding claims 1-2.
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