CN108551166B - Power grid equipment and section ultra-short-term load prediction, alarm and stability control method - Google Patents
Power grid equipment and section ultra-short-term load prediction, alarm and stability control method Download PDFInfo
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- CN108551166B CN108551166B CN201810322845.0A CN201810322845A CN108551166B CN 108551166 B CN108551166 B CN 108551166B CN 201810322845 A CN201810322845 A CN 201810322845A CN 108551166 B CN108551166 B CN 108551166B
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- H—ELECTRICITY
- H02—GENERATION; CONVERSION OR DISTRIBUTION OF ELECTRIC POWER
- H02J—CIRCUIT ARRANGEMENTS OR SYSTEMS FOR SUPPLYING OR DISTRIBUTING ELECTRIC POWER; SYSTEMS FOR STORING ELECTRIC ENERGY
- H02J3/00—Circuit arrangements for ac mains or ac distribution networks
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- H—ELECTRICITY
- H02—GENERATION; CONVERSION OR DISTRIBUTION OF ELECTRIC POWER
- H02J—CIRCUIT ARRANGEMENTS OR SYSTEMS FOR SUPPLYING OR DISTRIBUTING ELECTRIC POWER; SYSTEMS FOR STORING ELECTRIC ENERGY
- H02J3/00—Circuit arrangements for ac mains or ac distribution networks
- H02J3/001—Methods to deal with contingencies, e.g. abnormalities, faults or failures
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- H—ELECTRICITY
- H02—GENERATION; CONVERSION OR DISTRIBUTION OF ELECTRIC POWER
- H02J—CIRCUIT ARRANGEMENTS OR SYSTEMS FOR SUPPLYING OR DISTRIBUTING ELECTRIC POWER; SYSTEMS FOR STORING ELECTRIC ENERGY
- H02J3/00—Circuit arrangements for ac mains or ac distribution networks
- H02J3/003—Load forecast, e.g. methods or systems for forecasting future load demand
Abstract
The invention relates to the technical field of power grid risk safety assessment, in particular to a power grid equipment and section ultra-short-term load prediction, alarm and stability control method, which specifically comprises the following steps: s01: initializing a system, acquiring a power grid structure model, a real-time power grid running state, historical load and historical temperature data from an EMS system, and performing topology analysis on equipment and a section according to a power grid topological structure and a running mode; analyzing 24-hour weather data; s02: BP neural network model sample data processing; s03: predicting the power grid load based on the BP neural network model; s04: calculating the load of the power grid equipment or the section integral point; s05: early warning of the load of power grid equipment or a section; s06: analyzing power grid equipment or a section stability control mode; s07: and comprehensively counting and inquiring the load out-of-limit condition. The method and the device realize accurate prediction of the ultra-short-term power grid load, are beneficial to timely discovering the possible safety risk of the power grid, and improve the safety and the stability of the power grid.
Description
Technical Field
The invention relates to the technical field of power grid risk safety assessment, in particular to a power grid device and a section ultra-short-term load prediction, alarm and stability control method.
Background
With the increasing expansion of the scale of the power system, the safety and stability of the power grid are continuously challenged, the traditional short-term and medium-term power grid load prediction cannot meet the working requirement of a power dispatching department on safety assessment of power grid risks, and higher requirements are provided for the accuracy of power grid equipment and section ultra-short-term load prediction results. The ultra-short term power grid load prediction refers to the prediction of power load in the future 24 hours, and an accurate load prediction result is helpful for timely finding out possible safety risks of a power grid, and early warning is sent to a power dispatching department in advance to take relevant stable control measures, so that the safety and the stability of the power grid are improved.
Disclosure of Invention
The invention aims to overcome at least one defect in the prior art and provides a power grid device and a section ultra-short-term load prediction, alarm and stability control method.
In order to solve the technical problems, the technical scheme of the invention is as follows: a power grid equipment and section ultra-short-term load prediction, alarm and stability control method comprises the following steps: s01: initializing a system, acquiring a power grid structure model, a power grid real-time running state, historical load and historical temperature data from an EMS (electric energy management system), and performing topology analysis on equipment and a section according to a power grid topology structure and a running mode; analyzing 24-hour weather data; s02: BP neural network model sample data processing; s03: predicting the power grid load based on the BP neural network model; s04: calculating the load of the power grid equipment or the section integral point; s05: early warning of the load of power grid equipment or a section; s06: analyzing power grid equipment or a section stability control mode; s07: and comprehensively counting and inquiring the load out-of-limit condition.
Further, the power grid structure in step S01 includes connection relationships among substations, devices, measurement points, and device terminal points; the device also comprises a historical measured current value of the 10kV outgoing switch or a load value and a historical environment temperature value converted from the measured current value.
Further, step S02 may specifically include: the method specifically comprises the steps of obtaining the current value of each 10kV outgoing line switch; acquiring real-time temperature; acquiring the maximum current value and the minimum current value of the switch within nearly 24 hours; acquiring current value information of the switch in the last 1-2 hours; obtaining legal holiday and working day information of the same day; acquiring the interval between the maximum current occurrence time or the minimum current occurrence time and the current time yesterday; converting the current value into a load value; and confirming and deleting the influencing factors.
Further, step S04 may specifically include: acquiring equipment or section equipment information needing to be calculated; obtaining all the mounted 10kV outgoing switches of the equipment through topology and power flow analysis; and summarizing the predicted outlet switch load as the predicted load of the equipment or the section.
Further, step S05 may specifically include: acquiring the upper limit of the load or current operation of the equipment, and early warning when the predicted value exceeds the rated value of the load; and acquiring a control value of the section, and performing early warning when the predicted value exceeds the load control value.
Further, step S06 may specifically include the following steps:
when the equipment is a 110kV main transformer, whether a hot standby main transformer becomes a low-voltage switch is searched through topology and power flow analysis, and the load of the main transformer can be transferred to other main transformers; if a 10kV bus busbar heat standby switch exists, the load can be transferred to other main transformers; if any one of the conditions exists, judging that a load stabilizing and switching measure exists when the load is overloaded and no voltage loss is caused, otherwise, judging that the load is overloaded, and the risk of stably switching off a line or causing equipment voltage loss and the like is caused;
when the equipment is a 110kV line switch, whether a hot standby line switch exists or not is searched through topology and power flow analysis, and the line switch is mounted on a main power grid; if the 110kV bus section switch exists, the line mounting load can be transferred to another section of 110kV bus; whether a main transformer low-level switch transfers the load to a main transformer which is not on the line path exists; if the 10kV bus coupler switch exists, transferring the 10kV line load carried by the line to other 10kV buses on a path other than the line; if any one of the conditions exists, judging that a load stabilizing and switching measure exists when the load is overloaded and no voltage loss is caused, otherwise, judging that the load is overloaded, and the risk of stably switching off a line or causing equipment voltage loss and the like is caused;
when the equipment is a 220kV main transformer, finding a corresponding arrangement measure of the main transformer, and cutting off the main transformer line by line until the predicted load value is reduced to be within the limit value of the main transformer, wherein the default cut-off line has a voltage loss risk; analyzing topology and power flow to cut off all the electric equipment mounted on the line;
when the monitored object is a section, performing stable control operation on the transformer substations one by one according to the sequence with smaller influence caused by the stable control measures through analysis of the system section stable control measures; when no stability control measure exists, the risk of voltage loss and the like of the safety and stability cut-off line or the equipment can be caused when the load is judged to be overloaded, and when the stability control measure exists, the risk of voltage loss and the like of the safety and stability cut-off line or the equipment can be caused when the load is judged to be overloaded.
Further, when it is determined that the overload may cause a risk of stably cutting off a line or causing a voltage loss of equipment, the following operations are performed: calculating the possible voltage loss load; calculating important user information influenced by topology, customer line relation and the like; counting equipment causing pressure loss; and judging the risk level of the event according to the survey regulation of the electric power accident event of the China southern Power grid Limited liability company.
Drawings
FIG. 1 is a schematic overall flow diagram of the present invention.
Fig. 2 is a schematic diagram of the system structure of the invention.
FIG. 3 is a schematic diagram of the forward propagation model of the present invention.
FIG. 4 is a schematic representation of the back propagation model of the present invention.
FIG. 5 is a diagram of a forward modified weight model according to the present invention.
Detailed Description
The drawings are for illustrative purposes only and are not to be construed as limiting the patent; for the purpose of better illustrating the embodiments, certain features of the drawings may be omitted, enlarged or reduced, and do not represent the size of an actual product; it will be understood by those skilled in the art that certain well-known structures in the drawings and descriptions thereof may be omitted. The positional relationships depicted in the drawings are for illustrative purposes only and are not to be construed as limiting the present patent.
The technical scheme of the invention is further described in detail in the following with the attached drawings of the specification as shown in figures 1-5.
S1, reading an EMS system power grid structure model: firstly, acquiring a structural model of a power grid from an EMS system, wherein the power grid structure comprises a transformer substation, equipment, measuring points, equipment terminal points and connection relations among the terminal points; and reading the historical measured current value (converted into a load value) and the historical environmental temperature value of the 10kV outgoing switch in the EMS system.
S2BP neural network model sample data processing: and (3) finishing the current data of all 10kV outgoing switches in 2016: the development scale of the power grid is gradually enlarged, long-term data cannot represent the current scale, and the system is built in 17 years, so sample data can represent or approach the current power grid scale by adopting data in 16-17 years, 96 current day data are provided, 3.5 thousands of data in one year, 7 thousands of data in 2 years, and the data capacity is large.
1) Acquiring the current value of each 10kV outgoing switch;
2) acquiring temperature data at the moment;
3) acquiring the maximum current value of the switch within the last 24 hours;
4) acquiring the minimum current value of the switch within the last 24 hours;
5) obtaining the current value of the switch in the last 1 hour;
6) obtaining the current value of the switch in the last 2 hours;
7) obtaining legal holiday and working day information of the same day;
8) acquiring the time interval between the maximum current occurrence time of yesterday and the current time interval;
9) acquiring a current time interval between yesterday minimum current occurrence time and current time;
10) converting the current value into a load value, namely a current value/58.5 × 0.92;
11) and confirming and deleting the influencing factors.
S3 preparing sample data and preparing data required by predicted load according to steps S01 and S02
Load prediction of the BP neural network model:
1) forward propagation, as in fig. 3:
wherein Wij represents the weight from the input layer X to the hidden layer Y;
Y1＝θ(W11X1+W21X2+W31X3)；
wherein Sij represents the weight between hiding and the output layer Z;
Z1＝θ(S11Y1+S11Y2)；
＝U-Z1。
2) counter-propagating, as in fig. 4:
wherein y is1＝*S11；
x1＝y1*W11+y2＊W12；
3) Forward correction weights, as shown in fig. 5:
wherein
η is learning rate of 0.4. in the classic BP algorithm, the training rate is empirically determined, and learning becomes more refined as the learning rate becomes smaller.
4) The method ends when the error of two adjacent times is less than 0.4 or all learning is completed.
And S4 calculating the load of the power grid equipment or the section integral point.
1) Acquiring power grid equipment or section equipment information needing to be calculated;
2) obtaining all the mounted 10kV outgoing switches of the equipment through topology and power flow analysis;
3) and counting the related outgoing line switch load as the predicted load of the equipment or the section.
And S5 early warning of power grid equipment or section load.
Acquiring the load or current operation of the equipment, and performing early warning when a predicted value exceeds a load rated value;
and acquiring a control value of the section, and performing early warning when the predicted value exceeds the control value.
And S6 analyzing the power grid equipment or the section in a stable control mode.
When the equipment is a 110kV main transformer, whether a hot standby main transformer change-over switch (the switch is disconnected and is not overhauled, and the disconnecting switches or trolleys on two sides are closed) exists or not is searched through topology and power flow analysis, and the load of the main transformer can be transferred to other main transformers; if a 10kV bus busbar heat standby switch exists, the load can be transferred to other main transformers; if any one of the conditions exists, a stable control load shedding measure exists when the load is overloaded, no voltage loss is caused, otherwise, the risk of stably shedding a line or causing the voltage loss of equipment and the like can be caused when the load is overloaded.
When the equipment is a 110kV line switch, whether a hot standby line switch exists or not is searched through topology and power flow analysis, and the line switch is mounted on a main power grid; if the 110kV bus section switch exists, the line mounting load can be transferred to another section of 110kV bus;
whether a main transformer low-level switch transfers the load to a main transformer which is not on the line path exists; if the 10kV bus coupler switch exists, transferring the 10kV line load carried by the line to other 10kV buses on a path other than the line; if any one of the situations exists, a stable control load shedding measure exists when the load is overloaded, no voltage loss is caused, otherwise, the risk of stably shedding a line or equipment voltage loss and the like can be caused when the load is overloaded;
when the equipment is a 220kV main transformer, finding safety measures corresponding to the main transformer, and cutting off the main transformer line by line until the predicted load value is reduced to be within the limit value of the main transformer, wherein the default cut-off line has a voltage loss risk; analyzing topology and power flow to cut off all the electric equipment mounted on the line;
when the monitored object is a section, performing stable control operation on the transformer substations one by one according to the sequence with smaller influence caused by the stable control measures through analysis of the system section stable control measures; when no stability control measure exists, the risk of stably cutting off a line or equipment voltage loss and the like can be caused, and when the stability control measure exists, no load loss exists.
The situation that the line is cut off stably or the equipment is in voltage loss risk and the like when the load B is overloaded specifically comprises the following steps:
(a) calculating the possible voltage loss load;
(b) calculating important user information influenced by topology, customer line relation and the like;
(c) counting equipment causing pressure loss;
(d) and (4) judging the risk level of the event according to the survey regulation of the electric power accident of the southern Power grid Limited liability company in China (2014 edition).
S7 comprehensive statistics and query load out-of-limit condition:
1) counting the occurrence times of the load exceeding the rated value in the nearly one year of the equipment or the section;
2) and counting the number of the devices with the loads exceeding the rated values in any time period.
The corresponding power grid equipment based on the neural network and the system for predicting, early warning and stably controlling the section ultra-short term load, as shown in fig. 1, at least comprise the following functions:
1) initializing a system, acquiring data such as a power grid structure model, a power grid real-time operation state, historical load, historical temperature and the like from an EMS system, and performing topology analysis on equipment and a section according to a power grid topology structure and an operation mode; analyzing the 24-hour weather forecast of the Yahu;
2) preparing and summarizing data required by a model algorithm;
3) displaying the ultra-short-term load prediction data of the equipment or the section in a chart form;
4) displaying the ultra-short term overload equipment or the section in a table form;
5) and (5) displaying the stability control measures of the overload equipment or the section in a table form.
The system specifically includes the following functional modules, as shown in fig. 2:
a data interface module: initializing a system, acquiring data such as a power grid structure model, a power grid real-time operation state, historical load, historical temperature and the like from an EMS system, and performing topology analysis on equipment and a section according to a power grid topology structure and an operation mode; analyzing the 24-hour weather forecast of the Yahu;
parameter configuration of a neural network prediction model: selecting influence factors and correcting a prediction model;
and (3) power grid equipment or section ultra-short term load prediction: displaying the load prediction result of any power grid equipment or section at the integral point, and displaying in a curve form;
and (3) power grid equipment or section ultra-short term load prediction warning: displaying equipment or sections for predicting the existence of overload in the future 24 hours;
the ultra-short term power grid load overload stabilizing and controlling module comprises: and when the load is overloaded, selectable stability control measures are provided.
It should be understood that the above-described embodiments of the present invention are merely examples for clearly illustrating the present invention, and are not intended to limit the embodiments of the present invention. Other variations and modifications will be apparent to persons skilled in the art in light of the above description. And are neither required nor exhaustive of all embodiments. Any modification, equivalent replacement, and improvement made within the spirit and principle of the present invention should be included in the protection scope of the claims of the present invention.
Claims (2)
1. A power grid equipment and section ultra-short-term load prediction, alarm and stability control method is characterized by comprising the following steps:
s01: initializing a system, acquiring a power grid structure model, a real-time power grid running state, historical load and historical temperature data from an EMS system, and performing topology analysis on equipment and a section according to a power grid topological structure and a running mode; analyzing 24-hour weather data;
s02: BP neural network model sample data processing; the method specifically comprises the steps of obtaining the current value of each 10kV outgoing line switch in the power grid; acquiring real-time temperature; acquiring the maximum current value and the minimum current value of the switch within nearly 24 hours; acquiring current value information of the switch in the last 1-2 hours; obtaining legal holiday and working day information of the same day; acquiring the interval between the maximum current occurrence time or the minimum current occurrence time and the current time yesterday; converting the current value into a load value; confirming and deleting the influencing factors;
s03: load prediction based on the BP neural network model;
s04: calculating the load of the power grid equipment or the section integral point;
s05: early warning of the load of power grid equipment or a section;
s06: analyzing power grid equipment or a section stability control mode;
s07: comprehensive statistics and query;
the power grid structure in the step S01 includes a connection relationship among a substation, equipment, a measurement point, and an equipment terminal point; the 10kV outgoing switch also comprises a 10kV outgoing switch historical value 20 measuring current value or a load value and a historical environment temperature value converted from the historical value;
the step S04 specifically includes: acquiring equipment or section equipment information needing to be calculated; obtaining all the mounted 10kV outgoing switches of the equipment through topology and power flow analysis; summarizing the predicted outlet switch load as the predicted load of the equipment or the section;
the step S05 specifically includes:
acquiring the upper limit of load or current operation of equipment, and performing early warning when a predicted value exceeds a load rated value; acquiring a control value of the section, and performing early warning when a predicted value exceeds a load rated value;
the step S06 specifically includes the following steps:
when the equipment is a 110kV main transformer, whether a hot standby main transformer becomes a low-voltage switch is searched through topology and power flow analysis, and the load of the main transformer is transferred to other main transformers; if a 10kV bus connection hot standby switch exists, transferring the load to other main transformers; if any one of the conditions is yes, judging that a stable control load shedding measure exists when the load is overloaded and no voltage loss is caused, otherwise, judging that a safe and stable line is cut off or equipment voltage loss risk is caused when the load is overloaded;
when the equipment is a 110kV line switch, whether a hot standby line switch exists or not is searched through topology and power flow analysis, and the line switch is mounted on a main power grid; if the 110kV bus section switch exists, transferring the line mounting load to another 110kV bus; whether a main transformer low-level switch transfers the load to a main transformer which is not on the line path exists; if the 10kV bus coupler switch exists, transferring the 10kV line load carried by the line to other 10kV buses on a path other than the line; if any one of the conditions is yes, judging that a stable control load shedding measure exists when the load is overloaded and no voltage loss is caused, otherwise, judging that a line is cut off stably or equipment voltage loss risk is caused when the load is overloaded;
when the equipment is a 220kV main transformer, finding a corresponding arrangement measure of the main transformer, and cutting off the main transformer line by line until the predicted load value is reduced to be within the limit value of the main transformer, wherein the default cut-off line has a voltage loss risk; analyzing topology and power flow to cut off all the electric equipment mounted on the line;
when the monitored object is a section, performing stable control operation on the transformer substations one by one according to the sequence with smaller influence caused by the stable control measures through analysis of the system section stable control measures; when no stability control measure exists, the judgment result shows that the load is overloaded, the safety and stability of the circuit is cut off, or the equipment voltage loss risk is caused.
2. The method of claim 1, wherein: when the risk that the line is cut off stably or the equipment is subjected to voltage loss and the like when the load is determined to be overloaded is carried out, the following operations are carried out: calculating the possible voltage loss load; calculating important user information influenced by the topology and the customer line relationship; and counting the equipment causing the pressure loss.
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| CN110311369B (en) * | 2019-05-31 | 2020-09-25 | 广东电网有限责任公司 | Power grid stable section short-term load curve prediction method and system |
| CN110458405A (en) * | 2019-07-10 | 2019-11-15 | 清华大学 | It is a kind of based on electric power-Characteristics of micrometeorology data power system security method for early warning |
| CN111028486A (en) * | 2019-12-26 | 2020-04-17 | 杭州电力设备制造有限公司 | High-temperature early warning method, device, equipment and storage medium for electrical equipment |
| CN111931980A (en) * | 2020-07-02 | 2020-11-13 | 广东电网有限责任公司 | Line historical load recording method for marking operation mode |
| CN113326897A (en) * | 2021-06-25 | 2021-08-31 | 国网冀北电力有限公司承德供电公司 | Temperature measurement plan generation method and device for overhead transmission line and electronic equipment |
| CN114374205B (en) * | 2022-03-23 | 2022-06-14 | 广东电网有限责任公司佛山供电局 | Load transfer analysis method and device |
| CN114912853B (en) * | 2022-07-18 | 2022-12-09 | 广东电网有限责任公司佛山供电局 | Method and device for evaluating stability of power grid |
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