CN115603321A - Power load prediction system and method based on power consumption data - Google Patents
Power load prediction system and method based on power consumption data Download PDFInfo
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Abstract
The invention provides a power load prediction system and a power load prediction method based on power consumption data, wherein the power load prediction system comprises a power information analysis module, a power load calculation module, a power numerical value prediction module and a server; acquiring consumption information and electricity utilization information, and acquiring and analyzing data parameters of the consumption information and the electricity utilization information by an electric power information analysis module; the data parameters obtained by analysis are transmitted to a power load calculation module, and the power load calculation module calculates data power change information; acquiring power utilization information change values at different time periods, and transmitting the power utilization information change values to a power numerical value prediction module to predict the total power generation amount; the predicted total power generation amount is combined with the increased power consumption information and is transmitted to the server.
Description
Technical Field
The invention relates to the technical field of power prediction, in particular to a power load prediction system and method based on power consumption data.
Background
And (4) the predicted total power generation amount is combined with the electricity increasing information and transmitted to a server, and the server controls a power generation control module to control the power generation amount. The total load of the power system is the sum of total power consumed by all the electric equipment in the system; adding the power consumed by the industrial, agricultural, post and telecommunications, traffic, municipal, commercial and urban and rural residents to obtain the comprehensive power load of the power system; the power of the comprehensive power load plus the network loss is the power to be supplied by each power plant in the system, and is called the power supply load (power supply amount) of the power system; the power supply load plus the power consumed by each power plant (i.e., the service power) is the power that each generator in the system should generate, and is called the power generation load (power generation amount) of the system.
In the prior art, when power load prediction is performed through power consumption data, power consumption prediction is performed according to power load condition by acquiring consumption information, and when prediction is performed, prediction is inaccurate, and cannot be analyzed and predicted according to newly increased power consumption number and power consumption of different months, so that prediction effect is influenced.
Disclosure of Invention
The invention aims to provide a power load prediction system and method based on power consumption data, and the system and method are based on the acquisition of consumption information and power consumption information, carry out combined analysis on the consumption information and the power consumption information, acquire data parameters obtained by analysis, and obtain the power load change conditions in different time periods.
In order to achieve the purpose, the invention is realized by the following technical scheme: a power load prediction system based on power consumption data comprises an information acquisition module, a power information analysis module, a power load calculation module, a power numerical value prediction module, a power generation control module and a server; the information acquisition module, the power information analysis module, the power load calculation module, the power numerical value prediction module and the power generation control module are respectively in data connection with the server;
the information acquisition module acquires consumption information and electricity utilization information, and the electric power information analysis module acquires and analyzes data parameters of the consumption information and the electricity utilization information;
transmitting the analyzed data parameters to a power load calculation module, wherein the power load calculation module calculates data power change information;
acquiring power utilization information change values at different time periods, and transmitting the power utilization information change values to a power numerical value prediction module, wherein the server acquires and counts the increased power utilization information, and the power numerical value prediction module receives the power utilization information change values and the increased power utilization information to predict the total power generation amount;
and transmitting the predicted total power generation amount in combination with the increased power utilization information to a server, and controlling the power generation control module by the server to control the power generation amount.
Further, the consumption information comprises total electricity consumption information and user number information;
the electricity utilization information comprises electricity utilization time information, price interval information and electricity utilization type information;
the power consumption time information is received by the power information analysis module, the power consumption time value in the power consumption time information is acquired, and the power consumption time value is set as follows: t; the method comprises the steps of respectively obtaining total electricity consumption information, price interval information and electricity consumption type information in a T time period, a 2T time period and a 3T time period … … nT time period, and obtaining basic electricity consumption user number information and new user number information in a one-year period during obtaining.
Further, acquiring a total electricity consumption value in the total electricity consumption information in the T time period, a price interval value in the price interval information and each electricity consumption type in the electricity consumption type information;
respectively acquiring the total electricity consumption value and the price interval value of each electricity consumption type, and analyzing according to the total electricity consumption value and the price interval value to obtain an electricity consumption value;
analyzing to obtain the electricity utilization degree value in the T time period, and respectively analyzing to obtain the electricity utilization degree values in the 2T time period and the 3T time period … … nT time period;
the user number information comprises basic user number information and newly added user number information;
when T is in value taking, if the T time period represents one month, acquiring basic electricity consumption number information and newly increased electricity consumption number information in 12T time periods for counting, acquiring the analyzed electricity consumption number through a server, and respectively acquiring the electricity consumption number in the basic electricity consumption number information and the electricity consumption number in the newly increased electricity consumption number information according to the acquired electricity consumption number information;
and the power load calculation module is used for defining the acquired power utilization value as a data parameter and transmitting the data parameter.
Further, according to the acquired power consumption values of a plurality of time periods, a plane rectangular coordinate system is established, the abscissa represents the electricity utilization time information, and the ordinate represents the electricity utilization numerical value;
and representing the acquired plurality of power utilization values in a plane rectangular coordinate system, smoothly connecting the power utilization values between every two power utilization values through curves to form a power utilization degree curve graph, and observing power utilization degree change according to the power utilization degree curve graph.
Further, the power load calculation module receives a class of power consumption degree values for acquiring power consumption type information of a time period T, a time period 2T and a time period 3T … … T12; acquiring a power consumption numerical value in basic user number information and a power consumption numerical value in newly added user number information within a 1T time period to 12T time period; the T period represents one month;
respectively calculating power utilization difference values in 1T time period to 12T time period, and acquiring the power utilization change value of each month;
acquiring a class of electricity consumption numerical values of electricity consumption type information in 13T time periods, 14T time periods and 15T time periods … … T24T time periods; acquiring the electricity utilization degree value in the basic user number information and the electricity utilization degree value in the newly added user number information in the 13T-24T time period;
respectively calculating power utilization difference values of 13T time period to 24T time period, and acquiring the power utilization change value of each month;
respectively calculating a once-change difference value of the time of January, a once-change difference value of the time of February, a once-change difference value of the time of March … … once-change difference value of the time of Mayue, a change value of primary base electricity utilization and a change value of primary newly-added electricity utilization;
if n takes the value of 36; acquiring a class of electricity consumption numerical values of electricity consumption type information in 25T time periods, 26T time periods and 27T time periods … … T time periods; acquiring a power consumption numerical value in basic user number information and a power consumption numerical value in newly added user number information within a 25T time period to 36T time period;
respectively calculating power utilization difference values in 25T-36T time periods, and acquiring the power utilization change value of each month;
the power load calculation module calculates a monthly time secondary change difference, a monthly time secondary change difference … … twelve month time secondary change difference and a secondary basic power change value to obtain a secondary new power change value.
Further, the power value prediction module analyzes the power utilization difference value of each month, the annual basic power utilization change value and the newly added power utilization change value, predicts the total power generation amount value of the next year based on the increase or decrease ratio data of the power utilization difference value, predicts the month accurately according to the change value of each month, and transmits the predicted data to the server.
A power load prediction method based on power consumption data, the prediction method comprising the steps of:
step S1: acquiring consumption information and electricity utilization information, and acquiring and analyzing data parameters of the consumption information and the electricity utilization information by an electric power information analysis module;
step S2: the data parameters obtained by analysis are transmitted to a power load calculation module, and the power load calculation module calculates data power change information;
and step S3: acquiring power utilization information change values at different time periods, transmitting the power utilization information change values to a power numerical value prediction module, acquiring and counting increased power utilization information by a server, and receiving the power utilization information change values and the increased power utilization information by the power numerical value prediction module to predict the total power generation amount;
and step S4: and (4) the predicted total power generation amount is combined with the electricity increasing information and transmitted to a server, and the server controls a power generation control module to control the power generation amount.
Further, in the step S1, the consumption information includes total electricity consumption information and electricity consumption user number information; the electricity utilization information comprises electricity utilization time information, price interval information and electricity utilization type information;
the user number information comprises basic user number information and newly added user number information;
when the consumption information and the electricity utilization information are analyzed, the specific steps are as follows:
step S11: respectively acquiring the total electricity consumption information, the price interval information and the electricity consumption type information in the T time period, the 2T time period and the 3T time period … … nT time period, acquiring the basic electricity consumption number information and the new electricity consumption number information,
step S12: acquiring a total electricity consumption value, a price interval value and each electricity consumption type in the T time period;
respectively acquiring the total electricity consumption value and the price interval value of each electricity consumption type, and analyzing according to the total electricity consumption value and the price interval value to obtain an electricity consumption value;
analyzing to obtain the electricity utilization degree value in the T time period, and respectively analyzing to obtain the electricity utilization degree values in the 2T time period and the 3T time period … … nT time period;
step S13: the method comprises the steps of establishing a planar rectangular coordinate system according to acquired electricity utilization numerical values of a plurality of time periods, representing the acquired electricity utilization numerical values in the planar rectangular coordinate system, smoothly connecting the electricity utilization numerical values between every two adjacent electricity utilization numerical values through curves to form an electricity utilization degree curve graph, and observing electricity utilization degree change according to the electricity utilization degree curve graph.
Further, in step S2, the power load calculation module receives a class of power consumption degree values of the power consumption type information of the T time period, the 2T time period, and the 3T time period … … T12T time period;
respectively calculating power utilization difference values in 1T time period to 12T time period, and acquiring the power utilization change value of each month;
respectively calculating power utilization difference values of 13T time period to 24T time period, and acquiring the power utilization change value of each month;
respectively calculating a once-change difference value of the time of January, a once-change difference value of the time of February, a once-change difference value of the time of March … … once-change difference value of the time of Mayue, a change value of primary base electricity utilization and a change value of primary newly-added electricity utilization;
if n takes the value of 36; acquiring a class of electricity consumption numerical values of electricity consumption type information in 25T time periods, 26T time periods and 27T time periods … … T time periods;
the power load calculation module calculates a monthly time secondary change difference, a monthly time secondary change difference … … twelve month time secondary change difference and a secondary basic power change value to obtain a secondary new power change value.
The invention has the beneficial effects that:
1. according to the method and the device, based on the acquisition of the consumption information and the power utilization information, the consumption information and the power utilization information are combined and analyzed, the data parameters obtained through the analysis are obtained to obtain the power load change conditions in different time periods, analysis and prediction can be carried out according to the newly increased power utilization number and the power utilization amount in different months, and the prediction accuracy is improved.
2. According to the invention, the information of the number of the basic users and the information of the number of the newly added users in one year are obtained, the power consumption of the information of the number of the basic users and the power consumption of the information of the newly added users are respectively analyzed, and different change conditions of the basic users and the newly added users are observed, so that the accuracy of prediction is further improved.
Drawings
Other features, objects and advantages of the invention will become more apparent upon reading of the detailed description of non-limiting embodiments with reference to the following drawings:
FIG. 1 is a schematic block diagram of a system and method for forecasting power load based on power consumption data according to the present invention;
FIG. 2 is a method step diagram of a power load prediction system and method based on power consumption data according to the present invention.
Detailed Description
In order to make the technical means, the creation characteristics, the achievement purposes and the effects of the invention easy to understand, the invention is further explained by combining the specific embodiments.
In the present invention, please refer to fig. 1 and fig. 2, a power load prediction system based on power consumption data includes an information obtaining module, a power information analyzing module, a power load calculating module, a power value prediction module, a power generation control module, and a server; the information acquisition module, the power information analysis module, the power load calculation module, the power numerical value prediction module and the power generation control module are respectively in data connection with the server;
the information acquisition module acquires consumption information and electricity utilization information, and the electric power information analysis module acquires and analyzes data parameters of the consumption information and the electricity utilization information;
the consumption information comprises total electricity consumption information and user number information;
the electricity utilization information comprises electricity utilization time information, price interval information and electricity utilization type information;
the power consumption time information is received by the power information analysis module, the power consumption time value in the power consumption time information is acquired, and the power consumption time value is set as follows: t; respectively acquiring total electricity consumption amount information, price interval information and electricity consumption type information in a T time period, a 2T time period and a 3T time period … … nT time period, and acquiring basic electricity user number information and newly increased user number information by taking one year as a period during acquisition;
acquiring a total electricity consumption value in the total electricity consumption information in the T time period, a price interval value in the price interval information and each electricity consumption type in the electricity consumption type information;
respectively acquiring the total electricity consumption value and the price interval value of each electricity consumption type, and analyzing according to the total electricity consumption value and the price interval value to obtain an electricity consumption value;
analyzing to obtain the electricity utilization numerical value in the T time period, and respectively analyzing to obtain the electricity utilization numerical values in the 2T time period and the 3T time period … … nT time period;
according to the acquired electricity utilization numerical values of a plurality of time periods, a plane rectangular coordinate system is established, the abscissa represents electricity utilization time information, and the ordinate represents the electricity utilization numerical value;
representing the obtained plurality of power utilization numerical values in a plane rectangular coordinate system, smoothly connecting the power utilization numerical values between every two power utilization numerical values through curves to form a power utilization degree curve graph, and observing power utilization degree change according to the power utilization degree curve graph;
the user number information comprises basic user number information and newly added user number information;
when T is in value taking, if the T time period represents one month, acquiring basic user number information and newly added user number information in 12T time periods for statistics, acquiring the analyzed power utilization value through a server, and respectively acquiring the power utilization value in the basic user number information and the power utilization value in the newly added user number information according to the acquired power utilization value information;
the power consumption value is defined as a data parameter, and the power load calculation module is used for transmitting the data parameter;
the data parameters obtained by analysis are transmitted to a power load calculation module, and the power load calculation module calculates data power change information;
the power load calculation module receives and acquires a class of power consumption numerical values of power consumption type information in a T time period, a 2T time period and a 3T time period … … T12T time period; the electricity utilization values are respectively set as follows: YLydduz1, YLydduz2, YLydduz3 … … YLydduz12; the electricity consumption numerical value in the basic user number information and the electricity consumption numerical value in the newly added user number information in the 1T time period to 12T time period are respectively as follows: JCYDSz1, XZYDSz1;
respectively calculating power utilization difference values in 1T time period to 12T time period, and acquiring the power utilization change value of each month;
acquiring a class of electricity consumption numerical values of electricity consumption type information in 13T time periods, 14T time periods and 15T time periods … … T24T time periods; the electricity utilization values are respectively set as follows: YLydduz13, YLydduz14, YLydduz15 … … YLydduz24; the electricity consumption degree value in the basic user number information and the electricity consumption degree value in the newly added user number information in the 13T time period to 24T time period are respectively as follows: JCYDSz2, XZYDSz2;
respectively calculating power utilization difference values of 13T time period to 24T time period, and acquiring the power utilization change value of each month;
setting the one-time change difference of the one month time as follows: YYSJBHCZ; the specific request is as follows:
YYSJBHCZ＝YLydduz13-YLydduz1；
setting the one-time change difference of the February period as follows: EYSJBHCZ; the specific request is as follows:
EYSJBHCZ＝YLydduz14-YLydduz2；
accordingly, a one-time change difference … … in twelve months is calculated respectively; the set basic power consumption change value and the newly added power consumption change value are respectively as follows: JCYDBHz, XZYDBHz;
the primary electricity consumption variation value is specifically referred to the following formula:
JCYDBHz＝JCYDSz2-JCYDSz1；
the specific reference to the following formula is to increase the power consumption change value for one time:
XZYDBHz＝XZYDSz2-XZYDSz1；
if n takes the value of 36; acquiring a class of electricity consumption numerical values of electricity consumption type information in 25T time periods, 26T time periods and 27T time periods … … T time periods; the electricity utilization values are respectively set as follows: YLydduz25, YLydduz26, YLydduz27 … … YLydduz36; the electricity consumption degree value in the basic user number information and the electricity consumption degree value in the newly added user number information in the 25T time period to 36T time period are respectively as follows: JCYDSz3, XZYDSz3;
respectively calculating power utilization difference values in 25T-36T time periods, and acquiring the power utilization change value of each month;
the power load calculation module calculates a monthly time secondary change difference, a monthly time secondary change difference … … twelve month time secondary change difference and a secondary basic power change value to obtain a secondary new power change value;
acquiring power utilization information change values at different time periods, transmitting the power utilization information change values to a power value prediction module, acquiring and counting the increased power utilization information by a server, and receiving the power utilization information change values and the increased power utilization information by the power value prediction module to predict the total power generation amount;
it should be noted that: the electricity consumption increasing information refers to the electricity consumption obtained by predicting the information of the number of newly increased users in the next year;
the power numerical value prediction module analyzes the power utilization difference value of each month, the annual basic power utilization change value and the newly added power utilization change value, predicts the total power generation quantity value of the next year based on the increase or decrease ratio data of the power utilization difference value, predicts the month accurately according to the change value of each month, and transmits the predicted data to the server.
And (4) the predicted total power generation amount is combined with the electricity increasing information and transmitted to a server, and the server controls a power generation control module to control the power generation amount.
In the invention, a power load prediction method based on power consumption data specifically includes the following steps when power consumption prediction is performed:
step S1: acquiring consumption information and electricity utilization information, and acquiring and analyzing data parameters of the consumption information and the electricity utilization information by an electric power information analysis module;
the consumption information comprises total electricity consumption information and user number information; the electricity utilization information comprises electricity utilization time information, price interval information and electricity utilization type information;
when the consumption information and the electricity utilization information are analyzed, the specific steps are as follows:
step S11: respectively acquiring the total electricity consumption information, the price interval information and the electricity consumption type information in the T time period, the 2T time period and the 3T time period … … nT time period, acquiring the basic electricity consumption number information and the new electricity consumption number information,
step S12: acquiring a total electricity consumption value, a price interval value and each electricity consumption type in a T time period;
respectively acquiring the total electricity consumption value and the price interval value of each electricity consumption type, and analyzing according to the total electricity consumption value and the price interval value to obtain an electricity consumption value;
analyzing to obtain the electricity utilization degree value in the T time period, and respectively analyzing to obtain the electricity utilization degree values in the 2T time period and the 3T time period … … nT time period;
step S13: according to the acquired electricity utilization numerical values of a plurality of time periods, a plane rectangular coordinate system is established, the abscissa represents electricity utilization time information, and the ordinate represents the electricity utilization numerical value;
representing the obtained plurality of power utilization numerical values in a plane rectangular coordinate system, smoothly connecting the power utilization numerical values between every two power utilization numerical values through curves to form a power utilization degree curve graph, and observing power utilization degree change according to the power utilization degree curve graph;
the user number information comprises basic user number information and newly added user number information;
when T is in value taking, if the T time period represents one month, acquiring basic electricity consumption number information and newly increased electricity consumption number information in 12T time periods for counting, acquiring the analyzed electricity consumption number through a server, and respectively acquiring the electricity consumption number in the basic electricity consumption number information and the electricity consumption number in the newly increased electricity consumption number information according to the acquired electricity consumption number information;
the power consumption value is defined as a data parameter, and the power load calculation module is used for transmitting the data parameter;
step S2: the data parameters obtained by analysis are transmitted to a power load calculation module, and the power load calculation module calculates data power change information;
the power load calculation module receives and acquires a class of power consumption numerical values of power consumption type information in a T time period, a 2T time period and a 3T time period … … T12T time period;
respectively calculating power utilization difference values in 1T time period to 12T time period, and acquiring the power utilization change value of each month;
respectively calculating power utilization difference values of 13T time period to 24T time period, and acquiring the power utilization change value of each month;
respectively calculating a once-changed difference of the time of January, a once-changed difference of the time of February, a once-changed difference of the time of March … … once-changed difference of the time of December, a once-basic electricity utilization change value and a once-newly-added electricity utilization change value;
if n takes the value of 36; acquiring a class of electricity consumption numerical values of electricity consumption type information in 25T time periods, 26T time periods and 27T time periods … … T time periods;
the power load calculation module calculates a monthly time secondary change difference, a monthly time secondary change difference … … twelve month time secondary change difference and a secondary basic power change value to obtain a secondary new power change value;
and step S3: acquiring power utilization information change values at different time periods, transmitting the power utilization information change values to a power numerical value prediction module, acquiring and counting increased power utilization information by a server, and receiving the power utilization information change values and the increased power utilization information by the power numerical value prediction module to predict the total power generation amount;
and step S4: and (4) the predicted total power generation amount is combined with the increased power utilization information and transmitted to a server, and the server controls a power generation control module to control the power generation amount.
The above formulas are all the formulas for taking the numerical value of the dimension, the formula is a formula for obtaining the latest real situation by software simulation of collected mass data, the preset parameters in the formula are set by the technical personnel in the field according to the actual situation, if the weight coefficient and the proportion coefficient exist, the set size is a specific numerical value obtained by quantizing each parameter, the subsequent comparison is convenient, and the size of the weight coefficient and the proportion coefficient can be obtained as long as the proportional relation between the parameter and the quantized numerical value is not influenced.
In the above embodiments of the present application, the descriptions of the respective embodiments have respective emphasis, and for parts that are not described in detail in a certain embodiment, reference may be made to related descriptions of other embodiments.
As will be appreciated by one skilled in the art, embodiments of the present invention may be provided as a method, system, or computer program product. Accordingly, the present invention may take the form of an entirely hardware embodiment, an entirely software embodiment or an embodiment combining software and hardware aspects. Furthermore, the present invention may take the form of a computer program product embodied on one or more computer-usable storage media having computer-usable program code embodied in the media.
The above-mentioned embodiments are only specific embodiments of the present invention, which are used for illustrating the technical solutions of the present invention and not for limiting the same, and the protection scope of the present invention is not limited thereto, although the present invention is described in detail with reference to the foregoing embodiments, those skilled in the art should understand that: any person skilled in the art can modify or easily conceive the technical solutions described in the foregoing embodiments or equivalent substitutes for some technical features within the technical scope of the present disclosure; such modifications, changes or substitutions do not depart from the spirit and scope of the embodiments of the present invention, and they should be construed as being included therein. Therefore, the protection scope of the present invention shall be subject to the protection scope of the appended claims.
Claims (9)
1. A power load prediction system based on power consumption data is characterized by comprising an information acquisition module, a power information analysis module, a power load calculation module, a power numerical value prediction module, a power generation control module and a server; the information acquisition module, the power information analysis module, the power load calculation module, the power numerical value prediction module and the power generation control module are respectively in data connection with the server;
the information acquisition module acquires consumption information and electricity utilization information, and the electric power information analysis module acquires and analyzes data parameters of the consumption information and the electricity utilization information;
transmitting the analyzed data parameters to a power load calculation module, wherein the power load calculation module calculates data power change information;
acquiring power utilization information change values at different time periods, and transmitting the power utilization information change values to a power numerical value prediction module, wherein the server acquires and counts the increased power utilization information, and the power numerical value prediction module receives the power utilization information change values and the increased power utilization information to predict the total power generation amount;
and transmitting the predicted total power generation amount in combination with the increased power utilization information to a server, and controlling the power generation control module by the server to control the power generation amount.
2. The system according to claim 1, wherein the consumption information includes total electricity consumption information and electricity consumption amount information;
the electricity utilization information comprises electricity utilization time information, price interval information and electricity utilization type information;
the power consumption time information is received by the power information analysis module, the power consumption time value in the power consumption time information is acquired, and the power consumption time value is set as follows: t; the method comprises the steps of respectively obtaining total electricity consumption information, price interval information and electricity consumption type information in a T time period, a 2T time period and a 3T time period … … nT time period, and obtaining basic electricity consumption user number information and new user number information in a one-year period during obtaining.
3. The power load prediction system based on power consumption data according to claim 2, wherein a total electricity consumption value in the total electricity consumption information in the T period, a price interval value in the price interval information, and each electricity consumption type in the electricity consumption type information are obtained;
respectively acquiring the total electricity consumption value and the price interval value of each electricity consumption type, and analyzing according to the total electricity consumption value and the price interval value to obtain an electricity consumption value;
analyzing to obtain the electricity utilization degree value in the T time period, and respectively analyzing to obtain the electricity utilization degree values in the 2T time period and the 3T time period … … nT time period;
the user number information comprises basic user number information and newly added user number information;
when T is in value taking, if the T time period represents one month, acquiring basic user number information and newly added user number information in 12T time periods for statistics, acquiring the analyzed power utilization value through a server, and respectively acquiring the power utilization value in the basic user number information and the power utilization value in the newly added user number information according to the acquired power utilization value information;
and the acquired power utilization value is defined as a data parameter, and the power load calculation module is used for transmitting the data parameter.
4. The system according to claim 3, wherein a rectangular plane coordinate system is established based on the obtained power consumption values of the plurality of time periods, wherein an abscissa represents power consumption time information, and an ordinate represents the power consumption value;
and representing the acquired plurality of power utilization values in a plane rectangular coordinate system, smoothly connecting the power utilization values between every two power utilization values through curves to form a power utilization degree curve graph, and observing power utilization degree change according to the power utilization degree curve graph.
5. The power consumption data-based power load prediction system according to claim 3, wherein the power load calculation module receives a type of power consumption degree value for obtaining power consumption type information of a T time period, a 2T time period, and a 3T time period … … T time period; acquiring the electricity consumption numerical value in the basic user number information and the electricity consumption numerical value in the newly added user number information within the 1T time period to 12T time period; the T period represents one month;
respectively calculating power utilization difference values in 1T time period to 12T time period, and acquiring the power utilization change value of each month;
acquiring one type of power consumption numerical values of the power consumption type information in the periods of 13T, 14T and 15T … … T24T; acquiring a power consumption numerical value in basic user number information and a power consumption numerical value in newly added user number information within a 13T time period to 24T time period;
respectively calculating power utilization difference values of 13T time period to 24T time period, and acquiring the power utilization change value of each month;
respectively calculating a once-changed difference of the time of January, a once-changed difference of the time of February, a once-changed difference of the time of March … … once-changed difference of the time of December, a once-based power utilization change and a once-added power utilization change value;
if n takes the value of 36; acquiring a class of electricity consumption numerical values of electricity consumption type information in 25T time periods, 26T time periods and 27T time periods … … T time periods; acquiring a power consumption numerical value in basic user number information and a power consumption numerical value in newly added user number information within a 25T time period to 36T time period;
respectively calculating power utilization difference values in 25T-36T time periods, and acquiring the power utilization change value of each month;
the power load calculation module calculates a monthly time secondary change difference, a monthly time secondary change difference … … twelve month time secondary change difference and a secondary basic power change value to obtain a secondary new power change value.
6. The system of claim 1, wherein the power consumption data-based power load prediction module analyzes the power consumption difference value, the annual basic power consumption change value and the newly added power consumption change value in each month, predicts the total power generation amount in the next year based on the increase or decrease ratio data of the power consumption difference value, predicts the month-based change value in each month, and transmits the predicted data to the server.
7. An electric power load prediction method based on electric power consumption data, which is applied to the electric power load prediction system based on electric power consumption data according to any one of claims 1 to 6, and is characterized in that the prediction method comprises the following steps:
step S1: acquiring consumption information and electricity utilization information, and acquiring and analyzing data parameters of the consumption information and the electricity utilization information by an electric power information analysis module;
step S2: the data parameters obtained by analysis are transmitted to a power load calculation module, and the power load calculation module calculates data power change information;
and step S3: acquiring power utilization information change values at different time periods, transmitting the power utilization information change values to a power numerical value prediction module, acquiring and counting increased power utilization information by a server, and receiving the power utilization information change values and the increased power utilization information by the power numerical value prediction module to predict the total power generation amount;
and step S4: and (4) the predicted total power generation amount is combined with the electricity increasing information and transmitted to a server, and the server controls a power generation control module to control the power generation amount.
8. The method according to claim 7, wherein in the step S1, the consumption information includes information on total electricity consumption and information on the number of users; the electricity utilization information comprises electricity utilization time information, price interval information and electricity utilization type information;
the user number information comprises basic user number information and newly added user number information;
when the consumption information and the electricity utilization information are analyzed, the specific steps are as follows:
step S11: respectively acquiring the total electricity consumption information, the price interval information and the electricity consumption type information in the T time period, the 2T time period and the 3T time period … … nT time period, acquiring the basic electricity consumption number information and the new electricity consumption number information,
step S12: acquiring a total electricity consumption value, a price interval value and each electricity consumption type in the T time period;
respectively acquiring the total electricity consumption value and the price interval value of each electricity consumption type, and analyzing according to the total electricity consumption value and the price interval value to obtain an electricity consumption value;
analyzing to obtain the electricity utilization degree value in the T time period, and respectively analyzing to obtain the electricity utilization degree values in the 2T time period and the 3T time period … … nT time period;
step S13: the method comprises the steps of establishing a planar rectangular coordinate system according to obtained electricity utilization numerical values of a plurality of time periods, representing the obtained electricity utilization numerical values in the planar rectangular coordinate system, smoothly connecting the electricity utilization numerical values between every two to form an electricity utilization degree curve graph, and observing electricity utilization degree change according to the electricity utilization degree curve graph.
9. The method according to claim 7, wherein in step S2, the power load calculation module receives a class of power consumption degree values for obtaining the power consumption type information of the T period, the 2T period, and the 3T period … … T12T period;
respectively calculating power utilization difference values in 1T time period to 12T time period, and acquiring the power utilization change value of each month;
respectively calculating power utilization difference values of 13T time period to 24T time period, and acquiring the power utilization change value of each month;
respectively calculating a once-change difference value of the time of January, a once-change difference value of the time of February, a once-change difference value of the time of March … … once-change difference value of the time of Mayue, a change value of primary base electricity utilization and a change value of primary newly-added electricity utilization;
if n takes the value of 36; acquiring a class of electricity consumption numerical values of electricity consumption type information in 25T time periods, 26T time periods and 27T time periods … … T time periods;
the power load calculation module calculates a monthly time secondary change difference value, a february time secondary change difference value, a monthly time secondary change difference value … … a laurel time secondary change difference value and a secondary basic power change value to obtain a secondary newly-added power change value.
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