CN114460890B - Remote monitoring system and method for unattended power distribution room - Google Patents
Remote monitoring system and method for unattended power distribution room Download PDFInfo
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- CN114460890B CN114460890B CN202210117998.8A CN202210117998A CN114460890B CN 114460890 B CN114460890 B CN 114460890B CN 202210117998 A CN202210117998 A CN 202210117998A CN 114460890 B CN114460890 B CN 114460890B
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Abstract
The invention discloses a remote monitoring system and a remote monitoring method for an unattended power distribution room. According to the invention, through remote monitoring, not only can comprehensive management be realized for a plurality of power distribution rooms, reasonable distribution of human resources be realized, but also accurate prediction can be carried out on power utilization data corresponding to each user equipment in the power distribution room in the current time period according to historical power utilization data of each user equipment in the power distribution room, so that the power utilization data in the power distribution room at the current time can be predicted, and accurate monitoring on the power distribution room can be realized through the difference between the predicted power utilization data and the actual power utilization data in the power distribution room at the current time.
Description
Technical Field
The invention relates to the technical field of remote monitoring, in particular to a remote monitoring system and a remote monitoring method for an unattended power distribution room.
Background
With the rapid development of computer technology, people have more and more extensive application of computer technology, and in combination with the recent years, china has greatly developed smart power grids, and the intellectualization, informatization and technicalization of power transmission and transformation systems have higher levels, but still have larger defects in the power distribution link, so that the monitoring of power distribution equipment is becoming a problem which needs to be solved by people at present.
At present among the present remote monitering system to joining in marriage electrical room, only the simple environmental aspect from joining in marriage electrical room monitors, what consider is the safety problem of joining in marriage electrical room environment, but for monitoring user equipment's power consumption condition, can't monitor the early warning according to user equipment's actual power consumption condition.
In view of the above, there is a need for a system and method for remotely monitoring an unattended power distribution room.
Disclosure of Invention
The present invention is directed to a system and a method for remotely monitoring an unattended power distribution room, so as to solve the problems in the background art.
In order to solve the technical problems, the invention provides the following technical scheme: a remote monitoring system for an unattended power distribution room, comprising:
the equipment management module is used for managing each user equipment in the power distribution room;
the historical electricity utilization data acquisition module acquires historical electricity utilization data corresponding to each user equipment at different time;
the historical electricity utilization data screening module screens the historical electricity utilization data obtained by the historical electricity utilization data obtaining module and marks abnormal data in the historical electricity utilization data;
the historical electricity utilization relation coefficient acquisition module acquires the historical electricity utilization data screened by the historical electricity utilization data screening module and processes the acquired data to obtain the historical electricity utilization relation coefficients corresponding to the user equipment;
the power utilization prediction module predicts the power utilization data corresponding to the current time period of each user equipment according to the historical power utilization relation coefficient corresponding to each user equipment and the corresponding historical power utilization data, calibrates the prediction result and further predicts the power utilization data corresponding to the current time in the power distribution room;
and the monitoring and early warning module acquires a theoretical deviation value corresponding to the actual power consumption data of the current time of the power distribution room according to the predicted power consumption data corresponding to the current time in the power distribution room and the corresponding actual power consumption data, further judges whether the actual power consumption data of the power distribution room at the current time is normal or not, gives an alarm for abnormal conditions, and displays the abnormal conditions on a remote monitoring screen.
According to the method and the system, through the cooperative cooperation of all the modules, the power utilization data of all the user equipment in the power distribution room are predicted together, the power utilization data corresponding to the current time of the power distribution room are further predicted according to the current time, whether the actual power utilization data of the current power distribution room are abnormal or not is judged according to the theoretical deviation value between the prediction result of the power utilization data of the power distribution room and the measured actual power utilization data, and an alarm is given through a remote monitoring screen according to the abnormal condition.
Furthermore, when the device management module manages each user device, each user device in the distribution room is numbered, one user device corresponds to one number, and the numbers corresponding to each user device in one distribution room are continuous.
Further, the historical electricity consumption data acquisition module acquires historical electricity consumption data corresponding to each user equipment at different times, wherein the different times refer to different time intervals in different time periods in different data year differences,
the historical electricity consumption data acquisition module divides a year into a1 shares, the historical electricity consumption data of each year corresponds to a1 time periods, the time periods are numbered in sequence,
the one-year calculation is carried out according to 365 days, and when leap years occur, the historical electricity utilization data acquisition module randomly rejects the historical electricity utilization data corresponding to one day in the year;
the historical electricity consumption data acquisition module divides each day into a2 parts, the historical electricity consumption data of each day corresponds to a2 time intervals, and the time intervals are numbered in sequence;
the historical electricity consumption data acquisition module subtracts the year corresponding to each piece of historical electricity consumption data from the year corresponding to the current time, and each obtained difference value is used as a data year difference and is recorded as k;
the historical electricity utilization data acquisition module is used for acquiring the jth time interval pair of the mth user equipment in the ith time period in the kth data year differenceThe historical electricity consumption data is recorded as
The historical electricity consumption data acquisition module divides one year into different time periods, because the electricity consumption conditions corresponding to different time periods of the same user equipment are possibly different, for example, in summer, the user needs to turn on an air conditioner, and the electricity consumption data of the user is higher than that of other time periods; the day is divided into different time intervals because the corresponding electricity utilization conditions of different time intervals of the same user are possibly different, the electricity utilization data distribution of the common user in one day is uneven, and the electricity consumption in the evening is generally higher than that in the early morning; the reason for calculating the data year difference is that the power utilization conditions corresponding to the same time interval in the same time period are generally different in different years of the user, and the power utilization data corresponding to the same time interval in the same time period of the user generally increases year by year along with the improvement of the life quality of people.
Further, the historical electricity utilization data screening module acquires the historical electricity utilization data acquired by the historical electricity utilization data acquiring module, compares the acquired historical electricity utilization data with a first threshold value respectively,
when the historical electricity utilization data is larger than a first threshold value, judging that the historical electricity utilization data is normal;
and when the historical electricity utilization data is smaller than or equal to the first threshold value, judging that the historical electricity utilization data is abnormal, and marking the historical electricity utilization data.
The historical electricity consumption data screening module screens the historical data, so that the corresponding historical electricity consumption data of a user caused by special conditions are selected to be extremely small and even 0, further the calculation of the subsequent historical electricity consumption relation coefficient is influenced, further the calculated historical electricity consumption relation coefficient corresponding to the user equipment has larger deviation, and even the historical electricity consumption relation coefficient corresponding to the user equipment cannot be calculated; the screened abnormal historical electricity utilization data are marked, so that the influence caused by the abnormal historical electricity utilization data is reduced in the subsequent process of calculating the historical electricity utilization relation coefficient corresponding to the user equipment.
Further, the method for acquiring the historical electricity consumption relationship coefficient corresponding to each user equipment by the historical electricity consumption relationship coefficient acquisition module includes the following steps:
s1.1, respectively obtaining the maximum data year difference corresponding to each user equipment, and recording the maximum data year difference corresponding to the mth user equipment as Nm;
s1.2, respectively calculating various normalization processing results corresponding to the historical electricity utilization data corresponding to each user device when k is different values, wherein k is a positive integer;
and S1.3, obtaining a historical electricity utilization relation coefficient corresponding to each user equipment according to each normalization processing result corresponding to each user equipment obtained in the S1.2.
The historical electricity utilization relation coefficient acquisition module calculates each normalization processing result corresponding to the historical electricity utilization data corresponding to each user equipment in S1.2, so that the influence of the marked historical electricity utilization data in the subsequent historical electricity utilization relation coefficient calculation is eliminated in advance, the acquired historical electricity utilization relation coefficient is more accurate and more fit with the actual situation, and the subsequent prediction result of the electricity utilization data in the power distribution room is more accurate.
Further, when k is calculated to be different values in S1.2, each normalization processing result corresponding to the historical electricity consumption data corresponding to each user equipment is used
A normalization processing result of the quotient of the historical electricity utilization data corresponding to the jth time interval in the ith time period in the kth data year difference of the mth user equipment and the historical electricity utilization data corresponding to the jth time interval in the ith time period in the kth +1 data year difference of the mth user equipment is represented,
when the temperature is higher than the set temperature
Or alternatively
When marked, at that time
When the temperature is higher than the set temperature
And
when none are marked, at this time
The method for obtaining the historical electricity consumption relation coefficient corresponding to each user equipment in the step S1.3 is as follows: recording the historical electricity utilization relation coefficient corresponding to the jth time interval of the mth user equipment in the ith time period as Emij,
the described
Wherein b represents that the mth user equipment corresponds to when k is different value
The number of the cells.
In the invention, in the process of acquiring the corresponding normalization processing result of the historical electricity consumption data, the invention needs to be applied to the condition that the historical electricity consumption data is not normalized
Or
When marked, set up
The reason is that the marked historical electricity consumption data are all less than or equal to the first threshold value, the numerical values of the marked historical electricity consumption data are all smaller, even 0, when the marked data are taken as
When the molecule is (b), the compound (b) is (a)
The result of (2) is extremely small, even 0, when the data is marked as
When the molecule is (b), the compound (b) is (a)
The result of (2) is extremely large even when the denominator is 0, so that
Meaningless, and further order when Emij is found
Or
When the mark is marked,
b, acquiring the influence of the marked historical electricity utilization data on the historical electricity utilization relation coefficient; in the summing process, the upper limit of k is set to Nm-1 because the maximum data year difference corresponding to the mth user equipment is recorded as Nm, and the upper limit of k can be obtained as Nm-1 by k +1= Nm.
Further, the method for predicting the electricity consumption data corresponding to the current time period of each user equipment by the electricity consumption prediction module comprises the following steps:
s2.1, acquiring a time period I and a time interval J corresponding to the current time period, respectively acquiring historical power utilization relation coefficients corresponding to the J-th time interval of each user equipment in the I-th time period and historical power utilization data corresponding to the J-th time interval of each user equipment in the I-th time period in the non-marked and latest 1 data year difference,
recording a historical electricity utilization relation coefficient corresponding to the J-th time interval of the mth user equipment in the I-th time period as EmIJ, and recording historical electricity utilization data corresponding to the J-th time interval of the mth user equipment in the I-th time period in the unmarked and latest 1 data year difference as EmIJ
S2.2, when m is different values, obtaining historical electricity utilization relation coefficients corresponding to 2c time intervals adjacent to the J time interval in the I time period and the m user equipment
Corresponding to historical electricity utilization data corresponding to a corresponding time interval in the I time period in the data year difference,
and recording historical electricity utilization relation coefficients respectively corresponding to w-th time intervals adjacent to the J-th time interval in the I-th time period of the mth user equipment as EmIJ w Obtaining EmIJ w Is the same as the method for obtaining EmIJ,
the mth user equipment is in
The historical electricity utilization data corresponding to the w-th time interval adjacent to the J-th time interval in the I-th time period in the corresponding data year difference is recorded as
S2.3, respectively predicting the electricity utilization data corresponding to the current time period of each piece of user equipment, recording the prediction result of the electricity utilization data corresponding to the current time period of the mth piece of user equipment as BmIJ,
the above-mentioned
S2.4, respectively predicting historical electricity utilization data BmIJw corresponding to a w-th time interval adjacent to a J-th time interval corresponding to the current time period in the I-th time period when w is different values,
the described
S2.5, calculating the sum CmIJ of the predicted result of the electricity utilization data corresponding to the current time period of the mth user equipment and the predicted results of the historical electricity utilization data respectively corresponding to 2c time intervals adjacent to the J-th time interval corresponding to the current time period in the corresponding I-th time period, wherein the m-th time period is the same as the J-th time period in the current time period, and the m-th time period is the same as the J-th time period in the current time period
S2.6, acquiring the sum beta of actual power utilization data respectively corresponding to all time intervals with the time interval number smaller than J and the number beta 1 of all time intervals with the time interval number smaller than J in 2c time intervals adjacent to the J time interval corresponding to the current time period in the I time period of the mth user equipment;
s2.7, calculating a calibration value of a prediction result of the electricity consumption data corresponding to the mth user equipment in the current time period, and recording the calibration value as DmIJ, where DmIJ = (CmIJ- β)/(2 c- β 1);
the 2c time intervals adjacent to the J-th time interval in the I-th time period of the mth user equipment are also changed according to the difference of the corresponding values of J,
when J =1, regarding the 2 nd to 2c +1 st time intervals of the mth user equipment in the I-th time period as 2c time intervals adjacent to the J-th time interval of the user equipment in the I-th time period;
when 1 < J < c +1, taking the 1 st to J-1 st time intervals of the mth user equipment in the I time period as the 1 st to J-1 st time intervals adjacent to the J time interval in the I time period,
taking the J +1 th to 2c +1 th time intervals of the mth user equipment in the I time period as J-th to 2 c-th time intervals adjacent to the J-th time interval in the I time period;
when the temperature is higher than the set temperature
And a2 < 24 and
taking the J-c to J-1 time intervals of the mth user equipment in the I time period as the 1 st to c time intervals adjacent to the J time interval in the I time period,
taking the J +1 th to J + c th time intervals of the mth user equipment in the I time period as the c +1 th to 2c th time intervals adjacent to the J time interval in the I time period;
when in use
When the m user equipment is in the J +1 th to the I time period
A time interval as the second time interval adjacent to the J-th time interval in the I-th time period
By the time interval of 2c, the time interval,
the mth user equipment is in the ith time period
To J-1 time interval as 1 st to J-1 th time intervals adjacent to the J-th time interval in the I-th time period
A time interval;
when in use
When m user equipment is in the I time period
Time interval to
And the time intervals are 2c time intervals adjacent to the J-th time interval in the I-th time period of the user equipment.
When the power utilization prediction module predicts the power utilization data corresponding to the current time period of each user equipment, the power utilization prediction module predicts the power utilization data corresponding to the current time period of each user equipment
The reason is that the EmIJ can reflect the average value of the change conditions of the electricity utilization data corresponding to two adjacent years in the J time interval of the mth user equipment in the historical electricity utilization data in the I time period, and then the EmIJ and the electricity utilization data are compared
(the historical electricity utilization data corresponding to the J-th time interval in the I-th time period of the m-th user equipment in the non-marked and latest 1 data year difference) are multiplied, so that the electricity utilization data corresponding to the current time period of the m-th user equipment can be predicted.
Further, the method for predicting the electricity utilization data corresponding to the current time in the power distribution room by the electricity utilization prediction module comprises the following steps:
s3.1, respectively obtaining calibration values of power utilization data corresponding to current time periods of all user equipment in a power distribution room, and obtaining the number of days Q1 of the current time from the starting point of the time period to which the current time belongs and the duration Q2 of the current time from the starting point of the time interval to which the current time belongs;
s3.2, predicting the electricity utilization data P corresponding to the current time in the power distribution room,
the above-mentioned
Wherein m1 is the total number of the user equipment in the power distribution room.
In the process of predicting the electricity utilization data corresponding to the current time in the electricity distribution room by the electricity utilization prediction module, 365 ÷ a1 can obtain the number of days corresponding to each time period, 24 ÷ a2 can obtain the time length corresponding to each time interval, and Q2 ÷ (24 ÷ a 2) is calculated to obtain the ratio of the electricity utilization time length corresponding to the J-th time interval of the electricity distribution room on the same day to the total time length of the corresponding time interval, which is equivalent to the working time length (day) of the electricity distribution room in the corresponding time period, so that the total working time length of the electricity distribution room in the corresponding time period is Q1 < -1 > + Q2 ÷ (24 ÷ a 2) (day) because the day corresponding to the current time of the electricity distribution room is not fully worked;
the sum of the calibration values of the prediction results of the power consumption data corresponding to the current time period of each user equipment in the power distribution room is shown, but the time period and the time interval corresponding to the current time may not be over, so that the power consumption data corresponding to the current time in the power distribution room needs to be further subjected to time conversion according to the number of days Q1 from the current time to the start point of the time period and the duration Q2 from the current time to the start point of the time interval, and the prediction value of the power consumption data corresponding to the current time in the power distribution room is relatively accurate.
Further, the monitoring and early warning module acquires a theoretical deviation value g corresponding to the actual power utilization data of the power distribution room at the current time,
the above-mentioned
Wherein, P1 is the actual electricity consumption data of the current time of the power distribution room,
comparing g with a second preset value,
when g is larger than or equal to a second preset value, judging that P1 is abnormal, displaying the P1 on a remote monitoring screen, and early warning a monitor;
and when the g is smaller than the second preset value, judging that the P1 is normal, and displaying that the power distribution room is normal on the remote monitoring screen.
The monitoring and early warning module calculates g to obtain the deviation condition between the power utilization data corresponding to the power distribution room and the actual power utilization data at the current time, the larger g is, the larger the amount of the corresponding actual power utilization data exceeding the predicted power utilization data is, and when g is larger than or equal to a second preset value, the actual power utilization data is judged to exceed a specified bearing range, manual confirmation is needed, and then warning is carried out.
A method of remotely monitoring an unattended power distribution room, the method comprising the steps of:
s1, managing each user device in a power distribution room through a device management module;
s2, acquiring historical power utilization data corresponding to each user equipment at different time through a historical power utilization data acquisition module;
s3, screening the historical electricity utilization data obtained from the historical electricity utilization data obtaining module in the historical electricity utilization data screening module, and marking abnormal data in the historical electricity utilization data;
s4, acquiring historical power utilization data screened by the historical power utilization data screening module through the historical power utilization relation coefficient acquisition module, and processing the acquired data to obtain historical power utilization relation coefficients corresponding to the user equipment;
s5, in the power utilization prediction module, predicting power utilization data corresponding to the current time period of each user equipment according to the historical power utilization relation coefficient corresponding to each user equipment and corresponding historical power utilization data, calibrating a prediction result, and further predicting the power utilization data corresponding to the current time in the power distribution room;
and S6, in the monitoring and early warning module, acquiring a theoretical deviation value corresponding to the actual power utilization data of the current time of the power distribution room according to the predicted power utilization data corresponding to the current time in the power distribution room and the corresponding actual power utilization data, further judging whether the actual power utilization data of the power distribution room at the current time are normal or not, alarming according to abnormal conditions, and displaying on a remote monitoring screen.
Compared with the prior art, the invention has the following beneficial effects: according to the invention, not only can comprehensive management be carried out on a plurality of power distribution rooms through remote monitoring, reasonable distribution of human resources is realized, but also accurate prediction can be carried out on power utilization data corresponding to each user equipment in the power distribution room in the current time period according to historical power utilization data of each user equipment in the power distribution room, so that the power utilization data in the power distribution room in the current time is predicted, and accurate monitoring on the power distribution room is realized through the difference between the predicted power utilization data and the actual power utilization data in the power distribution room in the current time.
Drawings
The accompanying drawings, which are included to provide a further understanding of the invention and are incorporated in and constitute a part of this specification, illustrate embodiments of the invention and together with the description serve to explain the principles of the invention and not to limit the invention. In the drawings:
fig. 1 is a schematic structural diagram of a remote monitoring system of an unattended power distribution room according to the invention;
fig. 2 is a schematic flow chart of a method for acquiring historical electricity consumption relationship coefficients corresponding to user equipment by a historical electricity consumption relationship coefficient acquisition module in a remote monitoring system of an unattended power distribution room according to the present invention;
fig. 3 is a schematic flow chart of a remote monitoring method for an unattended power distribution room according to the present invention.
Detailed Description
The technical solutions in the embodiments of the present invention will be clearly and completely described below with reference to the drawings in the embodiments of the present invention, and it is obvious that the described embodiments are only a part of the embodiments of the present invention, and not all of the embodiments. All other embodiments, which can be obtained by a person skilled in the art without making any creative effort based on the embodiments in the present invention, belong to the protection scope of the present invention.
Referring to fig. 1-3, the present invention provides a technical solution: a remote monitoring system for an unattended power distribution room, comprising:
the equipment management module is used for managing each user equipment in the power distribution room;
the historical electricity utilization data acquisition module acquires historical electricity utilization data corresponding to each user equipment at different time;
the historical electricity utilization data screening module screens the historical electricity utilization data obtained by the historical electricity utilization data obtaining module and marks abnormal data in the historical electricity utilization data;
the historical power utilization relation coefficient acquisition module acquires the historical power utilization data screened by the historical power utilization data screening module and processes the acquired data to obtain the historical power utilization relation coefficients corresponding to the user equipment;
the power utilization prediction module predicts the power utilization data corresponding to the current time period of each user equipment according to the historical power utilization relation coefficient corresponding to each user equipment and the corresponding historical power utilization data, calibrates the prediction result and further predicts the power utilization data corresponding to the current time in the power distribution room;
and the monitoring and early warning module acquires a theoretical deviation value corresponding to the actual power consumption data of the current time of the power distribution room according to the predicted power consumption data corresponding to the current time in the power distribution room and the corresponding actual power consumption data, further judges whether the actual power consumption data of the power distribution room at the current time is normal or not, gives an alarm for abnormal conditions, and displays the abnormal conditions on a remote monitoring screen.
The method and the system jointly realize the prediction of the power utilization data of each user equipment in the power distribution room through the cooperative cooperation of each module, further predict the power utilization data corresponding to the current time of the power distribution room according to the current time, judge whether the actual power utilization data of the current power distribution room is abnormal according to the theoretical deviation value between the prediction result of the power utilization data of the power distribution room and the measured actual power utilization data, and give an alarm through a remote monitoring screen according to the abnormal condition.
When the equipment management module manages each user equipment, each user equipment in the power distribution room is numbered respectively, one user equipment corresponds to one number, and the numbers corresponding to the user equipment in one power distribution room are continuous.
The historical electricity utilization data acquisition module acquires historical electricity utilization data corresponding to each user equipment at different time, wherein the different time refers to different time intervals in different time periods in different data year differences,
the historical electricity consumption data acquisition module divides a year into a1 shares, the historical electricity consumption data of each year corresponds to a1 time periods, the time periods are numbered in sequence,
the one-year calculation is carried out according to 365 days, and when leap years occur, the historical electricity utilization data acquisition module randomly eliminates historical electricity utilization data corresponding to one day in the one-year calculation;
the historical electricity utilization data acquisition module divides each day into a2 parts, the historical electricity utilization data of each day corresponds to a2 time intervals, and the time intervals are numbered in sequence;
the historical electricity consumption data acquisition module subtracts the year corresponding to each piece of historical electricity consumption data from the year corresponding to the current time, and each obtained difference value is used as a data year difference and is marked as k;
the historical electricity consumption data acquisition module records the historical electricity consumption data corresponding to the jth time interval of the ith time period of the mth user equipment in the kth data year difference as
The historical electricity consumption data acquisition module divides one year into different time periods, because the electricity consumption conditions corresponding to different time periods of the same user equipment are possibly different, for example, in summer, the user needs to turn on an air conditioner, and the electricity consumption data of the user is higher than that of other time periods; the day is divided into different time intervals because the corresponding electricity utilization conditions of different time intervals of the same user are possibly different, the electricity utilization data distribution of the common user in one day is uneven, and the electricity consumption in the evening is generally higher than that in the early morning; the reason for calculating the data year difference is that the power utilization conditions corresponding to the same time interval in the same time period are generally different in different years of the user, and the power utilization data corresponding to the same time interval in the same time period of the user generally increases year by year along with the improvement of the life quality of people.
The historical electricity utilization data screening module acquires the historical electricity utilization data acquired by the historical electricity utilization data acquiring module and respectively compares the acquired historical electricity utilization data with a first threshold value,
when the historical electricity utilization data is larger than a first threshold value, judging that the historical electricity utilization data is normal;
and when the historical electricity utilization data is smaller than or equal to the first threshold value, judging that the historical electricity utilization data is abnormal, and marking the historical electricity utilization data.
The historical electricity utilization data screening module screens the historical data, and is used for screening out that the corresponding historical electricity utilization data of a user is extremely small or even 0 due to special conditions, so that the calculation of the subsequent historical electricity utilization relation coefficient is influenced, the calculated historical electricity utilization relation coefficient corresponding to the user equipment has larger deviation, and the historical electricity utilization relation coefficient corresponding to the user equipment cannot be calculated; the screened abnormal historical electricity utilization data are marked, so that the influence caused by the abnormal historical electricity utilization data is reduced in the subsequent process of calculating the historical electricity utilization relation coefficient corresponding to the user equipment.
The method for acquiring the historical power utilization relation coefficient corresponding to each user equipment by the historical power utilization relation coefficient acquisition module comprises the following steps:
s1.1, respectively obtaining the maximum data year difference corresponding to each user equipment, and recording the maximum data year difference corresponding to the mth user equipment as Nm;
s1.2, respectively calculating each normalization processing result corresponding to the historical electricity utilization data corresponding to each user equipment when k is different values, wherein k is a positive integer;
and S1.3, obtaining a historical electricity utilization relation coefficient corresponding to each user equipment according to each normalization processing result corresponding to each user equipment obtained in the S1.2.
The historical electricity utilization relation coefficient acquisition module calculates each normalization processing result corresponding to the historical electricity utilization data corresponding to each user device in S1.2, so that the influence of the marked historical electricity utilization data in the subsequent calculation of the historical electricity utilization relation coefficient is eliminated in advance, the acquired historical electricity utilization relation coefficient is more accurate and more suitable for the actual situation, and the subsequent prediction result of the electricity utilization data in the power distribution room is more accurate.
Calculating each normalization processing result corresponding to the historical electricity utilization data corresponding to each user equipment when k is different in S1.2, and using
A normalization processing result of the quotient of the historical electricity utilization data corresponding to the jth time interval in the ith time period in the kth data year difference of the mth user equipment and the historical electricity utilization data corresponding to the jth time interval in the ith time period in the kth +1 data year difference of the mth user equipment is represented,
when in use
Or alternatively
When marked, at that time
When in use
And with
Are not marked, at this time
The method for obtaining the historical electricity consumption relation coefficient corresponding to each user equipment in the step S1.3 is as follows: recording the historical electricity utilization relation coefficient corresponding to the jth time interval of the mth user equipment in the ith time period as Emij,
the above-mentioned
Wherein b represents that the mth user equipment corresponds to when k is different in value
The number of the cells.
In this embodiment, the historical electricity consumption data corresponding to the 01 th time interval in the 01 th time period from the 1 st data year difference to the 5 th data year difference of the ue 001 are 40, 36, 8, 30 and 28, respectively, where 8 is the mark data,
then the
Further, a historical power utilization relation coefficient corresponding to the 01 th time interval of the user equipment 001 in the 01 th time period is obtained
In the invention, in the process of acquiring the corresponding normalization processing result of the historical electricity consumption data, the invention can be used as the method for normalizing the historical electricity consumption data
Or
When marked, set up
The reason is that the marked historical electricity consumption data are all less than or equal to the first threshold value, the numerical values of the marked historical electricity consumption data are all small and even 0, and when the marked data are taken as
When the molecule is middle, the
Result of (2) is extremely small, even 0, when the data is marked as
When the molecule is (b), the compound (b) is (a)
Is extremely large even when the denominator is 0, so that
Meaningless, and further order when Emij is found
Or alternatively
When the mark is marked,
b, acquiring the influence of the marked historical electricity utilization data on the historical electricity utilization relation coefficient; in the summing process, the reason why the upper limit of k is set to Nm-1 is that the maximum data year difference corresponding to the mth user equipment is recorded as Nm, and the upper limit of k can be obtained as Nm-1 by k +1= Nm.
The method for predicting the electricity utilization data corresponding to the current time period of each piece of user equipment by the electricity utilization prediction module comprises the following steps:
s2.1, acquiring a time period I and a time interval J corresponding to the current time period, respectively acquiring historical power utilization relation coefficients corresponding to the J-th time interval of each user equipment in the I-th time period and historical power utilization data corresponding to the J-th time interval of each user equipment in the I-th time period in the non-marked and latest 1 data year difference,
recording a historical electricity utilization relation coefficient corresponding to the J-th time interval of the mth user equipment in the I-th time period as EmIJ, and recording historical electricity utilization data corresponding to the J-th time interval of the mth user equipment in the I-th time period in the unmarked and latest 1 data year difference as EmIJ
S2.2, when m is different values, obtaining historical electricity utilization relation coefficients corresponding to 2c time intervals adjacent to the J time interval in the I time period and of the m user equipment respectively and obtaining
Corresponding to historical electricity utilization data corresponding to a corresponding time interval in the I-th time period in the data year difference,
and recording historical electricity utilization relation coefficients respectively corresponding to w-th time intervals adjacent to J-th time interval in the I-th time period of the mth user equipment as EmIJ w Obtaining EmIJ w Is the same as the method for obtaining EmIJ,
the mth user equipment is in
Recording historical electricity consumption data corresponding to a w-th time interval adjacent to the J-th time interval in the I-th time period in the corresponding data year difference as
S2.3, respectively predicting the electricity utilization data corresponding to the current time period of each piece of user equipment, recording the prediction result of the electricity utilization data corresponding to the current time period of the mth piece of user equipment as BmIJ,
the above-mentioned
In this embodiment, if the historical power utilization relationship coefficient corresponding to the 03 th time interval of the ue 002 in the 03 th time period is as
The maximum data year difference corresponding to the user equipment is recorded as 4, and the historical electricity utilization data corresponding to the 03 th time interval in the 03 th time period from the 1 st data year difference to the 4 th data year difference of the user equipment 002 are respectively 6, 36, 32 and 30;
the historical power consumption data corresponding to the 03 th time interval in the 03 th time period in the unmarked and latest 1 data year difference of the 002 th user equipment is 36,
the prediction result of the electricity consumption data corresponding to the current time period of the 002 th user equipment is
S2.4, respectively predicting historical electricity utilization data BmIJw corresponding to a w-th time interval adjacent to a J-th time interval corresponding to the current time period in the I-th time period when w is different values,
the above-mentioned
S2.5, calculatingThe sum CmIJ of the predicted results of the electricity consumption data corresponding to the m user equipment in the current time period and the predicted results of the historical electricity consumption data corresponding to 2c time intervals adjacent to the J-th time interval corresponding to the current time period in the corresponding I-th time period respectively, wherein the m user equipment is a power consumption data set
S2.6, acquiring the sum beta of actual power utilization data respectively corresponding to all time intervals with the time interval number smaller than J and the number beta 1 of all time intervals with the time interval number smaller than J in 2c time intervals adjacent to the J time interval corresponding to the current time period in the I time period of the mth user equipment;
s2.7, calculating a calibration value of a prediction result of the electricity utilization data corresponding to the current time period of the mth user equipment, and recording the calibration value as DmIJ, wherein DmIJ = (CmIJ-beta)/(2 c-beta 1);
the 2c time intervals adjacent to the J-th time interval in the I-th time period of the mth user equipment are also changed according to the difference of the corresponding values of J,
when J =1, regarding a2 nd time interval to a 2c +1 nd time interval of the mth user equipment in the I th time period as a 2c time interval adjacent to the J th time interval of the user equipment in the I th time period;
when 1 < J < c +1, taking the 1 st to J-1 st time intervals of the mth user equipment in the I time period as the 1 st to J-1 st time intervals adjacent to the J time interval in the I time period,
taking the J +1 th to 2c +1 th time intervals of the mth user equipment in the I time period as J-th to 2 c-th time intervals adjacent to the J-th time interval in the I time period;
when the temperature is higher than the set temperature
And a2 < 24 and
when the m user equipment is at the secondThe J-c to J-1 time intervals in the I time period are used as the 1 st to c time intervals adjacent to the J time interval in the I time period,
taking the J +1 th to J + c th time intervals of the mth user equipment in the I time period as the c +1 th to 2c th time intervals adjacent to the J time interval in the I time period;
when in use
The mth user equipment is arranged from J +1 to J +1 in the ith time period
A time interval as the second time interval adjacent to the J-th time interval in the I-th time period
By the time interval of 2c, the time interval,
the mth user equipment is in the ith time period
To J-1 time interval as the 1 st to J-1 st time intervals adjacent to the J-1 st time interval in the I-th time period
A time interval;
when in use
When m user equipment is in the I time period
Time interval to
And the time intervals are 2c time intervals adjacent to the J-th time interval in the I-th time period of the user equipment.
In this embodiment, if a2=3 and c =3, the time period corresponding to the current time period of the 005 th ue is 01, the corresponding time interval is J1,
when J1=1, since 2c +1=2 × 3+1=7, the 005 th ue in the time interval adjacent to the J1 th time interval in the 01 th time cycle is from the 2 nd time interval to the 7 th time interval in the 01 th time cycle respectively;
when J1=3, since 3 > 1 and 3 < 4, and J1-1=3-1=2, J1+1=3+1=4,2c +1=2 × 3+1=7, the 1 st to 2 nd time intervals of the 005 th ue in the 01 th time cycle are regarded as the 1 st to 2 nd time intervals of the ue adjacent to the J1 th time interval in the 01 th time cycle,
taking the 4 th to 7 th time intervals of the 005 th user equipment in the 01 th time cycle as the 3 rd to 6 th time intervals adjacent to the J1 th time interval in the 005 th time cycle;
when J1=4, since 4=4 and 4 < 5 and 8 < 24 and 3 < 4, and J1-c =4-3=1, J1-1=4-1=3, J1+1=4+1=5, J1+ c =4+3=7, c +1=4+ 4, the 1 st to 3 rd time intervals of the 005 th ue in the 01 th time cycle are regarded as the 1 st to 3 rd time intervals of the 005 th ue adjacent to the J1 st time interval in the 01 th time cycle,
taking the 5 th to 7 th time intervals of the 005 th user equipment in the 01 th time cycle as the 4 th to 6 th time intervals adjacent to the J1 th time interval in the 01 th time cycle;
when J1=6, since 6 > 5 and 6 < 6, and J1+1=6+1=7,
J1-1＝6-1＝5，
the 7 th to 8 th time intervals of the 005 th UE in the 01 th time period are used as the 5 th to 6 th time intervals adjacent to the J1 th time interval in the 01 th time period,
taking the 2 nd to 5 th time intervals of the 005 th user equipment in the 01 th time cycle as the 1 st to 4 th time intervals adjacent to the J1 th time interval in the 01 th time cycle;
when J1=8, the
And taking the 2 nd time interval to the 7 th time interval of the 005 th user equipment in the 01 th time cycle as the 6 th time intervals adjacent to the J1 th time interval in the 01 th time cycle.
When the power utilization prediction module predicts the power utilization data corresponding to the current time period of each user equipment, the power utilization prediction module predicts the power utilization data corresponding to the current time period of each user equipment
The reason is that EmIJ can reflect the average value of the change conditions of the electricity utilization data corresponding to two adjacent years of the mth user equipment in the historical electricity utilization data in the jth time interval in the ith time period, and then EmIJ and the historical electricity utilization data are compared
(the historical electricity utilization data corresponding to the J-th time interval in the I-th time period in the unmarked and latest 1 data year difference of the mth user equipment) are multiplied, and the electricity utilization data corresponding to the current time period of the mth user equipment can be predicted.
The method for predicting the electricity utilization data corresponding to the current time in the power distribution room by the electricity utilization prediction module comprises the following steps:
s3.1, respectively obtaining calibration values of power utilization data corresponding to current time periods of all user equipment in a power distribution room, and obtaining the number of days Q1 of the current time from the starting point of the time period to which the current time belongs and the duration Q2 of the current time from the starting point of the time interval to which the current time belongs;
s3.2, predicting the electricity utilization data P corresponding to the current time in the power distribution room,
the above-mentioned
Wherein m1 is the total number of the user equipment in the power distribution room.
In this embodiment, for example, the first distribution room includes three user equipments, and the calibration values of the prediction results of the electricity consumption data corresponding to the three user equipments in the current time period are 40, 30, and 35 respectively,
a1 is 73, a2 is 6, the number of days of the current time from the starting point of the time period to which the current time belongs is 3, the time length of the current time from the starting point of the time interval to which the current time belongs is 2 hours,
predicting the electricity utilization data corresponding to the current time in the power distribution room
In the process of predicting the electricity utilization data corresponding to the current time in the electricity distribution room by the electricity utilization prediction module, 365 ÷ a1 can obtain the number of days corresponding to each time period, 24 ÷ a2 can obtain the time length corresponding to each time interval, and Q2 ÷ (24 ÷ a 2) is calculated to obtain the ratio of the electricity utilization time length corresponding to the J-th time interval of the electricity distribution room on the same day to the total time length of the corresponding time interval, which is equivalent to the working time length (day) of the electricity distribution room in the corresponding time period, so that the total working time length of the electricity distribution room in the corresponding time period is Q1 < -1 > + Q2 ÷ (24 ÷ a 2) (day) because the day corresponding to the current time of the electricity distribution room is not fully worked;
the sum of the calibration values of the prediction results of the power consumption data corresponding to the current time period of each user equipment in the power distribution room is shown, but the time period and the time interval corresponding to the current time may not be over, so that the power consumption data corresponding to the current time in the power distribution room needs to be further subjected to time according to the number of days Q1 from the current time to the starting point of the time period and the time length Q2 from the current time to the starting point of the time intervalAnd converting to obtain a relatively accurate predicted value of the electricity utilization data corresponding to the current time in the power distribution room.
The monitoring and early warning module acquires a theoretical deviation value g corresponding to actual power utilization data of the power distribution room at the current time,
the above-mentioned
Wherein, P1 is the actual electricity consumption data of the current time of the power distribution room,
comparing g with a second preset value,
when g is larger than or equal to a second preset value, judging that P1 is abnormal, displaying the P1 on a remote monitoring screen, and early warning a monitor;
and when the g is smaller than the second preset value, judging that the P1 is normal, and displaying that the power distribution room is normal on the remote monitoring screen.
The monitoring and early warning module calculates g to obtain the deviation condition between the power utilization data corresponding to the power distribution room and the actual power utilization data at the current time, the larger g is, the larger the amount of the corresponding actual power utilization data exceeding the predicted power utilization data is, and when g is larger than or equal to a second preset value, the actual power utilization data is judged to exceed a specified bearing range, manual confirmation is needed, and then warning is carried out.
A method of remotely monitoring an unattended power distribution room, the method comprising the steps of:
s1, managing each user device in a power distribution room through a device management module;
s2, acquiring historical power utilization data corresponding to each user equipment at different time through a historical power utilization data acquisition module;
s3, screening the historical electricity utilization data obtained from the historical electricity utilization data obtaining module in the historical electricity utilization data screening module, and marking abnormal data in the historical electricity utilization data;
s4, acquiring historical power utilization data screened by the historical power utilization data screening module through the historical power utilization relation coefficient acquisition module, and processing the acquired data to obtain historical power utilization relation coefficients corresponding to the user equipment;
s5, in the power utilization prediction module, predicting power utilization data corresponding to the current time period of each user equipment according to the historical power utilization relation coefficient corresponding to each user equipment and corresponding historical power utilization data, calibrating a prediction result, and further predicting the power utilization data corresponding to the current time in the power distribution room;
and S6, in the monitoring and early warning module, acquiring a theoretical deviation value corresponding to the actual power utilization data of the current time of the power distribution room according to the predicted power utilization data corresponding to the current time in the power distribution room and the corresponding actual power utilization data, further judging whether the actual power utilization data of the power distribution room at the current time are normal or not, alarming according to abnormal conditions, and displaying on a remote monitoring screen.
It should be noted that, in this document, relational terms such as first and second, and the like are used solely to distinguish one entity or action from another entity or action without necessarily requiring or implying any actual such relationship or order between such entities or actions. Also, the terms "comprises," "comprising," or any other variation thereof, are intended to cover a non-exclusive inclusion, such that a process, method, article, or apparatus that comprises a list of elements does not include only those elements but may include other elements not expressly listed or inherent to such process, method, article, or apparatus.
Finally, it should be noted that: although the present invention has been described in detail with reference to the foregoing embodiments, it will be apparent to those skilled in the art that changes may be made in the embodiments and/or equivalents thereof without departing from the spirit and scope of the invention. Any modification, equivalent replacement, or improvement made within the spirit and principle of the present invention should be included in the protection scope of the present invention.
Claims (4)
1. A remote monitoring system of an unattended power distribution room is characterized by comprising:
the equipment management module is used for managing each user equipment in the power distribution room;
the historical electricity utilization data acquisition module acquires historical electricity utilization data corresponding to each user equipment at different time;
the historical electricity utilization data screening module screens the historical electricity utilization data obtained by the historical electricity utilization data obtaining module and marks abnormal data in the historical electricity utilization data;
the historical power utilization relation coefficient acquisition module acquires the historical power utilization data screened by the historical power utilization data screening module and processes the acquired data to obtain the historical power utilization relation coefficients corresponding to the user equipment;
the power utilization prediction module predicts the power utilization data corresponding to the current time period of each user equipment according to the historical power utilization relation coefficient corresponding to each user equipment and the corresponding historical power utilization data, calibrates the prediction result and further predicts the power utilization data corresponding to the current time in the power distribution room;
the monitoring and early warning module acquires a theoretical deviation value corresponding to the actual power consumption data of the current time of the power distribution room according to the predicted power consumption data corresponding to the current time in the power distribution room and the corresponding actual power consumption data, further judges whether the actual power consumption data of the power distribution room at the current time is normal or not, gives an alarm for abnormal conditions, and displays the abnormal conditions on a remote monitoring screen;
when the equipment management module manages each user equipment, each user equipment in the power distribution room is numbered respectively, one user equipment corresponds to one number, and the numbers corresponding to the user equipment in one power distribution room are continuous;
the historical electricity utilization data acquisition module acquires historical electricity utilization data corresponding to each user equipment at different time, wherein the different time refers to different time intervals in different time periods in different data year differences,
the historical electricity consumption data acquisition module divides a year into a1 shares, the historical electricity consumption data of each year corresponds to a1 time periods, the time periods are numbered in sequence,
the one-year calculation is carried out according to 365 days, and when leap years occur, the historical electricity utilization data acquisition module randomly eliminates historical electricity utilization data corresponding to one day in the one-year calculation;
the historical electricity utilization data acquisition module divides each day into a2 parts, the historical electricity utilization data of each day corresponds to a2 time intervals, and the time intervals are numbered in sequence;
the historical electricity consumption data acquisition module subtracts the year corresponding to each piece of historical electricity consumption data from the year corresponding to the current time, and each obtained difference value is used as a data year difference and is recorded as k;
the historical electricity consumption data acquisition module records the obtained historical electricity consumption data corresponding to the jth time interval of the mth user equipment in the ith time period in the kth data year difference as
The historical electricity utilization data screening module acquires the historical electricity utilization data acquired by the historical electricity utilization data acquisition module and respectively compares the acquired historical electricity utilization data with a first threshold value,
when the historical electricity utilization data is larger than a first threshold value, judging that the historical electricity utilization data is normal;
when the historical electricity utilization data is smaller than or equal to a first threshold value, judging that the historical electricity utilization data is abnormal, and marking the historical electricity utilization data;
the method for acquiring the historical power utilization relation coefficient corresponding to each user equipment by the historical power utilization relation coefficient acquisition module comprises the following steps:
s1.1, respectively obtaining the maximum data year difference corresponding to each user equipment, and recording the maximum data year difference corresponding to the mth user equipment as Nm;
s1.2, respectively calculating each normalization processing result corresponding to the historical electricity utilization data corresponding to each user equipment when k is different values, wherein k is a positive integer;
s1.3, obtaining a historical electricity utilization relation coefficient corresponding to each user equipment according to each normalization processing result corresponding to each user equipment obtained in the S1.2;
calculating each normalization processing result corresponding to the historical electricity utilization data corresponding to each user equipment when k is different in S1.2, and using
Indicating the normalization processing result of the quotient of the historical electricity utilization data corresponding to the jth time interval in the ith time period in the kth data year difference of the mth user equipment and the historical electricity utilization data corresponding to the jth time interval in the ith time period in the kth +1 data year difference of the mth user equipment,
when in use
Or
When marked, at this time
When in use
And
are not marked, at this time
The method for obtaining the historical electricity consumption relation coefficient corresponding to each user equipment in the step S1.3 is as follows: recording the historical electricity utilization relation coefficient corresponding to the jth time interval of the mth user equipment in the ith time period as Emij,
the above-mentioned
Wherein b represents that the mth user equipment corresponds to when k is different value
The number of (2);
the method for predicting the electricity utilization data corresponding to the current time period of each user device by the electricity utilization prediction module comprises the following steps:
s2.1, acquiring a time period I and a time interval J corresponding to the current time period, respectively acquiring historical power utilization relation coefficients corresponding to the J-th time interval of each user equipment in the I-th time period and historical power utilization data corresponding to the J-th time interval of each user equipment in the I-th time period in the non-labeled and latest 1 data year difference,
recording a historical electricity utilization relation coefficient corresponding to the J-th time interval of the mth user equipment in the I-th time period as EmIJ, and recording historical electricity utilization data corresponding to the J-th time interval of the mth user equipment in the I-th time period in the non-marked and latest 1 data year difference as EmIJ
S2.2, when m is different values, obtaining historical electricity utilization relation coefficients corresponding to 2c time intervals adjacent to the J time interval in the I time period and of the m user equipment respectively and obtaining
Corresponding data yearHistorical electricity utilization data corresponding to a corresponding time interval in the I-th time period in the difference,
and recording historical electricity utilization relation coefficients respectively corresponding to w-th time intervals adjacent to the J-th time interval in the I-th time period of the mth user equipment as EmIJ w Obtaining EmIJ w Is the same as the method for obtaining EmIJ,
the mth user equipment is in
The historical electricity utilization data corresponding to the w-th time interval adjacent to the J-th time interval in the I-th time period in the corresponding data year difference is recorded as
S2.3, respectively predicting the electricity utilization data corresponding to the current time period of each piece of user equipment, recording the prediction result of the electricity utilization data corresponding to the current time period of the mth piece of user equipment as BmIJ,
the above-mentioned
S2.4, respectively predicting historical electricity utilization data BmIJw corresponding to a w-th time interval adjacent to a J-th time interval corresponding to the current time period in the I-th time period when w is different values,
the above-mentioned
S2.5, calculating the sum CmIJ of the predicted result of the electricity utilization data corresponding to the mth user equipment in the current time period and the predicted results of the historical electricity utilization data respectively corresponding to 2c time intervals adjacent to the J-th time interval corresponding to the current time period in the corresponding I-th time period, wherein the CmIJ is the sum of the predicted results of the electricity utilization data of the mth user equipment in the current time period and the predicted results of the historical electricity utilization data of the 2c time intervals adjacent to the J-th time interval corresponding to the current time period in the current time period
S2.6, acquiring the sum beta of actual power utilization data respectively corresponding to all time intervals with the time interval number smaller than J and the number beta 1 of all time intervals with the time interval number smaller than J in 2c time intervals adjacent to the J time interval corresponding to the current time period in the I time period of the mth user equipment;
s2.7, calculating the calibration value of the prediction result of the electricity consumption data corresponding to the current time period of the mth user equipment as DmIJ,
the DmIJ = (CmIJ- β)/(2 c- β 1);
the 2c time intervals adjacent to the J-th time interval in the I-th time period of the mth user equipment are also changed according to the difference of the corresponding values of J,
when J =1, regarding the 2 nd to 2c +1 st time intervals of the mth user equipment in the I-th time period as 2c time intervals adjacent to the J-th time interval of the user equipment in the I-th time period;
when 1 < J < c +1, taking the 1 st to J-1 st time intervals of the mth user equipment in the I time period as the 1 st to J-1 st time intervals adjacent to the J time interval in the I time period,
taking the J +1 th to 2c +1 th time intervals of the mth user equipment in the I time period as the J-th to 2 c-th time intervals adjacent to the J time interval in the I time period;
when the temperature is higher than the set temperature
And a2 < 24 and
taking the J-c to J-1 time intervals of the mth user equipment in the I time period as the 1 st to c time intervals adjacent to the J time interval in the I time period,
taking the J +1 th to J + c th time intervals of the mth user equipment in the I time period as the c +1 th to 2c th time intervals adjacent to the J time interval in the I time period;
when in use
The mth user equipment is arranged from J +1 to J +1 in the ith time period
A time interval as a J-th time interval adjacent to the user equipment in the I-th time period
By the time interval of 2c, the time interval,
the mth user equipment is in the ith time period
To J-1 time interval as the 1 st to J-1 st time intervals adjacent to the J-1 st time interval in the I-th time period
A time interval;
when the temperature is higher than the set temperature
When m user equipment is in the I time period
Time interval to
And the time intervals are 2c time intervals adjacent to the J-th time interval in the I-th time period of the user equipment.
2. The system of claim 1, wherein the system comprises: the method for predicting the electricity utilization data corresponding to the current time in the power distribution room by the electricity utilization prediction module comprises the following steps:
s3.1, respectively obtaining calibration values of power utilization data corresponding to current time periods of all user equipment in a power distribution room, and obtaining the number of days Q1 of the current time from the starting point of the time period to which the current time belongs and the duration Q2 of the current time from the starting point of the time interval to which the current time belongs;
s3.2, predicting the electricity utilization data P corresponding to the current time in the power distribution room,
the described
Wherein m1 is the total number of the user equipment in the power distribution room.
3. The system of claim 2, wherein the remote monitoring system comprises: the monitoring and early warning module acquires a theoretical deviation value g corresponding to actual power utilization data of the power distribution room at the current time,
the above-mentioned
Wherein, P1 is the actual electricity consumption data of the current time of the power distribution room,
comparing g with a second preset value,
when g is larger than or equal to a second preset value, judging that P1 is abnormal, displaying the P1 on a remote monitoring screen, and early warning a monitor;
and when the g is smaller than the second preset value, judging that the P1 is normal, and displaying that the power distribution room is normal on the remote monitoring screen.
4. The method for remotely monitoring an unattended distribution room of a remote monitoring system of an unattended distribution room according to any one of claims 1-3, wherein: the method comprises the following steps:
s1, managing each user device in a power distribution room through a device management module;
s2, acquiring historical power utilization data corresponding to each user equipment at different time through a historical power utilization data acquisition module;
s3, screening the historical electricity utilization data obtained from the historical electricity utilization data obtaining module in the historical electricity utilization data screening module, and marking abnormal data in the historical electricity utilization data;
s4, acquiring historical power utilization data screened by the historical power utilization data screening module through the historical power utilization relation coefficient acquisition module, and processing the acquired data to obtain historical power utilization relation coefficients corresponding to the user equipment;
s5, in the power utilization prediction module, predicting power utilization data corresponding to the current time period of each user equipment according to the historical power utilization relation coefficient corresponding to each user equipment and corresponding historical power utilization data, calibrating a prediction result, and further predicting the power utilization data corresponding to the current time in the power distribution room;
and S6, in the monitoring and early warning module, acquiring a theoretical deviation value corresponding to the actual power utilization data of the current time of the power distribution room according to the predicted power utilization data corresponding to the current time in the power distribution room and the corresponding actual power utilization data, further judging whether the actual power utilization data of the power distribution room at the current time are normal or not, alarming according to abnormal conditions, and displaying on a remote monitoring screen.
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