CN115603321B - 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 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 consumption information, and acquiring and analyzing data parameters of the consumption information and the electricity consumption information by an electricity information analysis module; transmitting the data parameters obtained by analysis to a power load calculation module, and calculating the data power change information by the power load calculation module; acquiring power consumption information change values in different time periods, transmitting the power consumption information change values to a power numerical value prediction module, and predicting the total power generation amount; the method and the device for predicting the total power generation amount of the power generation based on the power consumption information are used for transmitting the predicted total power generation amount to the server in combination with the increased power consumption information, and based on the acquisition of the consumption information and the power consumption information, analysis and prediction can be carried out according to the newly increased power consumption number and the power consumption of different months, so that the prediction accuracy is improved.
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 the predicted total power generation amount is combined with the increased power consumption information to be transmitted to a server, and the server controls the power generation control module to control the power generation amount. The total load of the power system is the sum of the total power consumption of all electric equipment in the system; adding the power consumed by industry, agriculture, post and telecommunications, traffic, municipal administration, business and urban and rural residents to obtain the comprehensive electricity load of the electric power system; the power which is consumed by the combined electric load and the network is the power which should 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 is added with the power consumed by each power plant (namely, the station service power), namely, the power which is supposed to be generated by each generator in the system, and the power is called the power generation load (power generation capacity) of the system.
In the prior art, when the power load is predicted by the power consumption data, the power consumption is predicted according to the power load condition by acquiring the consumption information, and when the prediction is performed, the prediction is inaccurate, and the analysis and the prediction cannot be performed according to the newly-increased power consumption number and the power consumption of different months, so that the prediction effect is influenced.
Disclosure of Invention
Aiming at the defects of the prior art, the invention aims to provide a power load prediction system and a method based on power consumption data.
In order to achieve the above object, the present invention is realized by the following technical scheme: the power load prediction system based on the 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 connected with the server in a data mode;
the information acquisition module acquires consumption information and electricity consumption information, and the electricity information analysis module acquires and analyzes data parameters of the consumption information and the electricity consumption information;
transmitting the data parameters obtained by analysis to a power load calculation module, wherein the power load calculation module calculates data power change information;
acquiring power consumption information change values in different time periods, transmitting the power consumption information change values to a power numerical value prediction module, wherein the server performs acquisition statistics on the increased power consumption information, and the power numerical value prediction module receives the power consumption information change values and the increased power consumption information to predict the total power generation amount;
and the predicted total power generation amount is combined with the increased power consumption information to be transmitted to a server, and the server controls the power generation control module to control the power generation amount.
Further, the consumption information includes electricity consumption total information and electricity consumption subscriber number information;
the electricity consumption information comprises electricity consumption time information, price interval information and electricity consumption type information;
the power information analysis module receives the power utilization time information, acquires a power utilization time value in the power utilization time information, and sets the power utilization time value as follows: t is a T; and respectively acquiring electricity consumption total 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 consumption user number information and newly-increased user number information by taking one year as a period when acquiring.
Further, acquiring a total electricity consumption value in total electricity consumption information in a T time period, a price interval value in price interval information and each electricity consumption type in electricity consumption type information;
the electricity consumption total value and the price interval value of each electricity consumption type are respectively obtained, and electricity consumption degree values are obtained according to the analysis of the electricity consumption total value and the price interval value;
analyzing to obtain electricity consumption values in a T time period, and respectively analyzing to obtain electricity consumption values in a 2T time period and a 3T time period … … nT time period;
the user number information comprises basic user number information and newly added user number information;
when the T is valued, if the T time period represents one month, acquiring basic power consumption information and newly-increased user number information in the 12T time period, counting, acquiring the power consumption value obtained by analysis through a server, and respectively acquiring the power consumption value in the basic power consumption information and the power consumption value in the newly-increased user number information according to the acquired power consumption information;
and defining the acquired electricity consumption value as a data parameter, and transmitting the data parameter to the power load calculation module.
Further, a plane rectangular coordinate system is established according to the acquired electricity consumption values of a plurality of time periods, wherein the abscissa represents electricity consumption time information, and the ordinate represents the electricity consumption value;
and the acquired power consumption values are represented in a plane rectangular coordinate system, the power consumption values are smoothly connected with each other through curves to form a power consumption degree curve graph, and the power consumption degree change is observed according to the power consumption degree curve graph.
Further, the power load calculation module receives and acquires a class of electricity utilization value of the electricity utilization type information of the T time period, the 2T time period and the 3T time period … … T time period; acquiring electricity utilization value in basic electricity utilization user number information and electricity utilization value in newly-added user number information in a 1T time period-12T time period; the T period represents one month;
the electricity consumption difference value between the 1T time period and the 12T time period is respectively obtained, and the electricity consumption change value of each month is obtained;
acquiring a class of electricity utilization degree values of electricity utilization type information of 13T time periods, 14T time periods and 15T time periods … … T24T time periods; acquiring electricity utilization value in basic electricity utilization user number information and electricity utilization value in newly-added user number information in a 13T time period-24T time period;
the electricity consumption difference value between the 13T time period and the 24T time period is respectively obtained, and the electricity consumption change value of each month is obtained;
respectively calculating a primary change difference value of the first month, a primary change difference value of the second month, a primary change difference value of the third month … …, a primary change difference value of the third month, a primary basic power utilization change and a primary new power utilization change value;
if n takes a value of 36; acquiring a class of electricity utilization degree values of electricity utilization type information of a 25T time period, a 26T time period and a 27T time period … … T time period; acquiring electricity utilization value in basic electricity utilization user number information and electricity utilization value in newly-added user number information in a 25T time period-36T time period;
the electricity consumption difference between the time period of 25T and the time period of 36T is respectively obtained, and the electricity consumption change value of each month is obtained;
the power load calculation module calculates a first month time secondary change difference value, a second month time secondary change difference value, a third month time secondary change difference value … … and a fourth month time secondary change difference value, and a second base electricity consumption change value secondary new electricity consumption change value.
Further, the power value prediction module analyzes the power consumption difference value of each month, the basic power consumption change value and the new power consumption change value, predicts the total power generation amount value of the next year based on the increase or decrease ratio data of the power consumption difference value, predicts the power generation amount value of the next year 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 consumption information, and acquiring and analyzing data parameters of the consumption information and the electricity consumption information by an electricity information analysis module;
step S2: transmitting the data parameters obtained by analysis to a power load calculation module, and calculating the data power change information by the power load calculation module;
step S3: acquiring power consumption information change values in different time periods, transmitting the power consumption information change values to a power numerical value prediction module, acquiring and counting the increased power consumption information by a server, and predicting the total power generation amount by the power numerical value prediction module by receiving the power consumption information change values and the increased power consumption information;
step S4: and the predicted total power generation amount is combined with the increased power consumption information to be transmitted to a server, and the server controls the power generation control module to control the power generation amount.
Further, in the step S1, the consumption information includes total electricity consumption information and user number information; the electricity consumption information comprises electricity consumption time information, price interval information and electricity consumption type information;
the user number information comprises basic user number information and newly added user number information;
when analyzing the consumption information and the electricity consumption information, the specific steps are as follows:
step S11: 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 respectively, obtaining basic electricity consumption number information and new increased number of users information,
step S12: acquiring a total electricity consumption value, a price interval value and various electricity consumption types in a time period T;
the electricity consumption total value and the price interval value of each electricity consumption type are respectively obtained, and electricity consumption degree values are obtained according to the analysis of the electricity consumption total value and the price interval value;
analyzing to obtain electricity consumption values in a T time period, and respectively analyzing to obtain electricity consumption values in a 2T time period and a 3T time period … … nT time period;
step S13: and establishing a plane rectangular coordinate system according to the acquired electricity consumption values of the time periods, representing the acquired electricity consumption values in the plane rectangular coordinate system, smoothly connecting the electricity consumption values by curves to form an electricity consumption degree curve graph, and observing the electricity consumption degree change according to the electricity consumption degree curve graph.
Further, in the step S2, the power load calculation module receives and acquires a class of electricity utilization value of the electricity utilization type information of the T time period, the 2T time period, and the 3T time period … … T time period;
the electricity consumption difference value between the 1T time period and the 12T time period is respectively obtained, and the electricity consumption change value of each month is obtained;
the electricity consumption difference value between the 13T time period and the 24T time period is respectively obtained, and the electricity consumption change value of each month is obtained;
respectively calculating a primary change difference value of the first month, a primary change difference value of the second month, a primary change difference value of the third month … …, a primary change difference value of the third month, a primary basic electricity utilization change value and a primary new electricity utilization change value;
if n takes a value of 36; acquiring a class of electricity utilization degree values of electricity utilization type information of a 25T time period, a 26T time period and a 27T time period … … T time period;
the power load calculation module calculates a first month time secondary change difference value, a second month time secondary change difference value, a third month time secondary change difference value … … and a fourth month time secondary change difference value, and a second base electricity consumption change value secondary new electricity consumption change value.
The invention has the beneficial effects that:
1. according to the invention, based on the acquisition of consumption information and electricity consumption information, the consumption information and the electricity consumption information are combined and analyzed, the data parameters obtained by the analysis are obtained to obtain the power load change conditions of different time periods, and the analysis and the prediction can be carried out according to the newly increased electricity consumption number and the electricity consumption of different months, so that the prediction accuracy is improved.
2. According to the invention, the power consumption of the basic power consumption information and the power consumption of the newly-increased power consumption information are respectively analyzed by acquiring the basic power consumption information and the newly-increased power consumption information in one year, and different change conditions of the basic power consumption information and the newly-increased power consumption information are observed, so that the prediction accuracy is further improved.
Drawings
Other features, objects and advantages of the present invention will become more apparent upon reading of the detailed description of non-limiting embodiments, given with reference to the accompanying drawings in which:
FIG. 1 is a schematic block diagram of a power load prediction system and method 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
The invention is further described in connection with the following detailed description, in order to make the technical means, the creation characteristics, the achievement of the purpose and the effect of the invention easy to understand.
In the present invention, referring to fig. 1 and 2, a power load prediction system based on power consumption data includes an information acquisition module, a power information analysis module, a power load calculation module, a power numerical 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 connected with the server in a data mode;
the information acquisition module acquires consumption information and electricity consumption information, and the electric power information analysis module acquires and analyzes data parameters of the consumption information and the electricity consumption information;
the consumption information comprises electricity consumption total information and electricity consumption subscriber number information;
the electricity consumption information comprises electricity consumption time information, price interval information and electricity consumption type information;
the power information analysis module receives the power utilization time information, acquires a power utilization time value in the power utilization time information, and sets the power utilization time value as follows: t is a T; acquiring electricity consumption total 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 respectively, and acquiring basic electricity consumption user number information and newly-increased user number information by taking one year as a period when the electricity consumption total information, the price interval information and the electricity consumption type information are acquired;
acquiring a total electricity consumption value in total electricity consumption information in a time period T, a price interval value in price interval information and each electricity consumption type in electricity consumption type information;
the electricity consumption total value and the price interval value of each electricity consumption type are respectively obtained, and electricity consumption degree values are obtained according to the analysis of the electricity consumption total value and the price interval value;
analyzing to obtain electricity consumption values in a T time period, and respectively analyzing to obtain electricity consumption values in a 2T time period and a 3T time period … … nT time period;
establishing a plane rectangular coordinate system according to the acquired electricity consumption values of a plurality of time periods, wherein the abscissa represents electricity consumption time information and the ordinate represents the electricity consumption value;
the acquired power consumption values are represented in a plane rectangular coordinate system, the power consumption values are connected in pairs through curves smoothly, a power consumption degree curve graph is formed, and the power consumption degree change is observed according to the power consumption degree curve graph;
the user number information comprises basic user number information and newly added user number information;
when the T is valued, if the T time period represents one month, acquiring basic power consumption information and newly-increased user number information in the 12T time period, counting, acquiring the power consumption value obtained by analysis through a server, and respectively acquiring the power consumption value in the basic power consumption information and the power consumption value in the newly-increased user number information according to the acquired power consumption information;
the power consumption value is defined as a data parameter, and the power load calculation module is used for transmitting the data parameter;
transmitting the data parameters obtained by analysis to a power load calculation module, and calculating the data power change information by the power load calculation module;
the power load calculation module receives and acquires a class of electricity utilization degree values of electricity utilization type information of a T time period, a 2T time period and a 3T time period … … T time period; the set electricity consumption values are respectively as follows: ylyddduz 1, ylyddduz 2, ylyddduz 3 … … ylyddduz 12; the electricity consumption value in the basic electricity consumption number information and the electricity consumption value in the newly added number information in the time period of 1T to 12T are respectively as follows: JCYDSz1, XZYDSz1;
the electricity consumption difference value between the 1T time period and the 12T time period is respectively obtained, and the electricity consumption change value of each month is obtained;
acquiring a class of electricity utilization degree values of electricity utilization type information of 13T time periods, 14T time periods and 15T time periods … … T24T time periods; the set electricity consumption values are respectively as follows: ylyddduz 13, ylyddduz 14, ylyddduz 15 … … ylyddduz 24; the electricity consumption value in the basic electricity consumption number information and the electricity consumption value in the newly added number information in the 13T time period to 24T time period are respectively as follows: JCYDSz2, XZYDSz2;
the electricity consumption difference value between the 13T time period and the 24T time period is respectively obtained, and the electricity consumption change value of each month is obtained;
the difference value of the one-time change of the one month time is set as follows: YYSJBHCZ; for specific calculations, refer to the following formula:
YYSJBHCZ＝YLydduz13-YLydduz1；
the difference value of the primary change of the february time is set as follows: EYSJBHCZ; for specific calculations, refer to the following formula:
EYSJBHCZ＝YLydduz14-YLydduz2；
thus, the first-time change difference … … and the first-time change difference … … are calculated respectively; the set basic electricity utilization change value and the newly added electricity utilization change value are respectively as follows: JCYDBHz, XZYDBHz;
the primary basic electricity consumption change value is specifically referred to as the following formula:
JCYDBHz＝JCYDSz2-JCYDSz1；
please refer to the following formula for the specific new power consumption change value:
XZYDBHz＝XZYDSz2-XZYDSz1；
if n takes a value of 36; acquiring a class of electricity utilization degree values of electricity utilization type information of a 25T time period, a 26T time period and a 27T time period … … T time period; the set electricity consumption values are respectively as follows: ylyddduz 25, ylyddduz 26, ylyddduz 27 … … ylyddduz 36; the electricity consumption value in the basic electricity consumption number information and the electricity consumption value in the newly added number information in the 25T time period to 36T time period are respectively as follows: JCYDSz3, XZYDSz3;
the electricity consumption difference between the time period of 25T and the time period of 36T is respectively obtained, and the electricity consumption change value of each month is obtained;
the power load calculation module calculates a first month time secondary change difference value, a second month time secondary change difference value, a third month time secondary change difference value … … and a fourth month time secondary change difference value, and a second new electricity utilization change value of the secondary basic electricity utilization change value;
acquiring power consumption information change values in different time periods, transmitting the power consumption information change values to a power numerical value prediction module, acquiring and counting the increased power consumption information by a server, and predicting the total power generation amount by the power numerical value prediction module by receiving the power consumption information change values and the increased power consumption information;
it should be noted that: the step of increasing the electricity consumption information is to predict the electricity consumption obtained by newly increasing the number of users in the next year;
the power value prediction module analyzes the power consumption difference value of each month, the annual basic power consumption change value and the new power consumption change value, predicts the total power generation amount value of the next year based on the increase or decrease ratio data of the power consumption difference value, predicts the power generation amount value of the next year according to the change value of each month to the month, and transmits the predicted data to the server.
And the predicted total power generation amount is combined with the increased power consumption information to be transmitted to a server, and the server controls the power generation control module to control the power generation amount.
In the invention, the power load prediction method based on the power consumption data specifically comprises the following steps of:
step S1: acquiring consumption information and electricity consumption information, and acquiring and analyzing data parameters of the consumption information and the electricity consumption information by an electricity information analysis module;
the consumption information comprises electricity consumption total information and electricity consumption subscriber number information; the electricity consumption information comprises electricity consumption time information, price interval information and electricity consumption type information;
when analyzing the consumption information and the electricity consumption information, the specific steps are as follows:
step S11: 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 respectively, obtaining basic electricity consumption number information and new increased number of users information,
step S12: acquiring a total electricity consumption value, a price interval value and various electricity consumption types in a time period T;
the electricity consumption total value and the price interval value of each electricity consumption type are respectively obtained, and electricity consumption degree values are obtained according to the analysis of the electricity consumption total value and the price interval value;
analyzing to obtain electricity consumption values in a T time period, and respectively analyzing to obtain electricity consumption values in a 2T time period and a 3T time period … … nT time period;
step S13: establishing a plane rectangular coordinate system according to the acquired electricity consumption values of a plurality of time periods, wherein the abscissa represents electricity consumption time information and the ordinate represents the electricity consumption value;
the acquired power consumption values are represented in a plane rectangular coordinate system, the power consumption values are connected in pairs through curves smoothly, a power consumption degree curve graph is formed, and the power consumption degree change is observed according to the power consumption degree curve graph;
the user number information comprises basic user number information and newly added user number information;
when the T is valued, if the T time period represents one month, acquiring basic power consumption information and newly-increased user number information in the 12T time period, counting, acquiring the power consumption value obtained by analysis through a server, and respectively acquiring the power consumption value in the basic power consumption information and the power consumption value in the newly-increased user number information according to the acquired power consumption 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: transmitting the data parameters obtained by analysis to a power load calculation module, and calculating the data power change information by the power load calculation module;
the power load calculation module receives and acquires a class of electricity utilization degree values of electricity utilization type information of a T time period, a 2T time period and a 3T time period … … T time period;
the electricity consumption difference value between the 1T time period and the 12T time period is respectively obtained, and the electricity consumption change value of each month is obtained;
the electricity consumption difference value between the 13T time period and the 24T time period is respectively obtained, and the electricity consumption change value of each month is obtained;
respectively calculating a primary change difference value of the first month, a primary change difference value of the second month, a primary change difference value of the third month … …, a primary change difference value of the third month, a primary basic electricity utilization change value and a primary new electricity utilization change value;
if n takes a value of 36; acquiring a class of electricity utilization degree values of electricity utilization type information of a 25T time period, a 26T time period and a 27T time period … … T time period;
the power load calculation module calculates a first month time secondary change difference value, a second month time secondary change difference value, a third month time secondary change difference value … … and a fourth month time secondary change difference value, and a second new electricity utilization change value of the secondary basic electricity utilization change value;
step S3: acquiring power consumption information change values in different time periods, transmitting the power consumption information change values to a power numerical value prediction module, acquiring and counting the increased power consumption information by a server, and predicting the total power generation amount by the power numerical value prediction module by receiving the power consumption information change values and the increased power consumption information;
step S4: and the predicted total power generation amount is combined with the increased power consumption information to be transmitted to a server, and the server controls the power generation control module to control the power generation amount.
The above formulas are all formulas for removing dimensions and taking numerical calculation, the formulas are formulas for obtaining the latest real situation by collecting a large amount of data and performing software simulation, preset parameters in the formulas are set by a person skilled in the art according to the actual situation, if weight coefficients and proportion coefficients exist, the set sizes are specific numerical values obtained by quantizing the parameters, the subsequent comparison is convenient, and the proportional relation between the weight coefficients and the proportion coefficients is not influenced as long as the proportional relation between the parameters and the quantized numerical values is not influenced.
In the foregoing embodiments of the present application, the descriptions of the embodiments are emphasized, and for a portion of this disclosure that is not described in detail in this embodiment, reference is made to the related descriptions of other embodiments.
It will be appreciated by those skilled in the art that 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 therein.
The above examples are only specific embodiments of the present invention, and are not intended to limit the scope of the present invention, but it should be understood by those skilled in the art that the present invention is not limited thereto, and that the present invention is described in detail with reference to the foregoing examples: any person skilled in the art may modify or easily conceive of the technical solution described in the foregoing embodiments, or perform equivalent substitution of some of the technical features, while remaining within the technical scope of the present disclosure; such modifications, changes or substitutions do not depart from the spirit and scope of the technical solutions of the embodiments of the present invention, and are intended to be included in the scope of the present invention. Therefore, the protection scope of the present invention shall be subject to the protection scope of the claims.
Claims (4)
1. The power load prediction system based on the 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 connected with the server in a data mode;
the information acquisition module acquires consumption information and electricity consumption information, and the electricity information analysis module acquires and analyzes data parameters of the consumption information and the electricity consumption information;
transmitting the data parameters obtained by analysis to a power load calculation module, wherein the power load calculation module calculates power change information;
acquiring power consumption information change values in different time periods, transmitting the power consumption information change values to a power numerical value prediction module, wherein the server performs acquisition statistics on the increased power consumption information, and the power numerical value prediction module receives the power consumption information change values and the increased power consumption information to predict the total power generation amount;
the predicted total power generation amount is combined with the increased power consumption information to be transmitted to a server, and the server controls a power generation control module to control the power generation amount;
the step of increasing the electricity consumption information is to predict the electricity consumption obtained by newly increasing the number of users in the next year;
the consumption information comprises electricity consumption total information and electricity consumption subscriber number information;
the user number information comprises basic user number information and newly added user number information;
the electricity consumption information comprises electricity consumption time information, price interval information and electricity consumption type information;
the power information analysis module receives the power utilization time information, acquires a power utilization time value in the power utilization time information, and sets the power utilization time value as T; acquiring electricity consumption total 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 respectively, and acquiring basic electricity consumption user number information and newly-increased user number information by taking one year as a period when the electricity consumption total information, the price interval information and the electricity consumption type information are acquired;
acquiring a total electricity consumption value in total electricity consumption information in a time period T, a price interval value in price interval information and each electricity consumption type in electricity consumption type information;
the electricity consumption total value and the price interval value of each electricity consumption type are respectively obtained, and electricity consumption degree values are obtained according to the analysis of the electricity consumption total value and the price interval value;
analyzing to obtain electricity consumption values in a T time period, and respectively analyzing to obtain electricity consumption values in a 2T time period and a 3T time period … … nT time period;
when the T is valued, the T time period represents one month, basic electricity utilization number information and newly added number of users information in the 12T time period are acquired, the power utilization number value obtained through analysis is acquired through the server, and the power utilization number value in the basic electricity utilization number information and the power utilization number value in the newly added number of users information are respectively acquired according to the acquired electricity utilization number information;
defining the acquired electricity consumption value as a data parameter, and transmitting the data parameter to an electric load calculation module;
establishing a plane rectangular coordinate system according to the acquired electricity consumption values of a plurality of time periods, wherein the abscissa represents electricity consumption time information and the ordinate represents the electricity consumption value;
the acquired power utilization degree values are represented in a plane rectangular coordinate system, the power utilization degree values are connected in a smooth mode through curves to form a power utilization degree curve graph, and power utilization degree change is observed according to the power utilization degree curve graph;
the power load calculation module receives and acquires a class of electricity utilization degree values of electricity utilization type information of a T time period, a 2T time period and a 3T time period … … T12T time period; the electricity consumption degree values of the first type are respectively set as follows: ylyddduz 1, ylyddduz 2, ylyddduz 3 … … ylyddduz 12; the electricity consumption value in the basic electricity consumption number information and the electricity consumption value in the newly added number information in the 1T time period to 12T time period are respectively as follows: JCYDSz1, XZYDSz1; the T period represents one month;
the electricity consumption change values of the 1T time period to the 12T time period are respectively obtained, and the electricity consumption change value of each month is obtained;
acquiring a class of electricity utilization degree values of electricity utilization type information of 13T time periods, 14T time periods and 15T time periods … … T24T time periods; the electricity consumption degree values of the first type are respectively set as follows: ylyddduz 13, ylyddduz 14, ylyddduz 15 … … ylyddduz 24; the electricity consumption value in the basic electricity consumption number information and the electricity consumption value in the newly added number information in the 13T time period to 24T time period are respectively as follows: JCYDSz2, XZYDSz2;
the electricity utilization change values of the 13T time period to the 24T time period are respectively obtained, and the electricity utilization change value of each month is obtained;
respectively calculating a primary power utilization change value of the first month, a primary power utilization change value of the second month, a primary power utilization change value of the third month … … and a primary power utilization change value of the third month, a primary basic power utilization change value and a new power utilization change value;
the change value of the primary electricity consumption in the month is set as follows: YYSJBHCZ; for specific calculations, refer to the following formula:
YYSJBHCZ＝YLydduz13-YLydduz1；
the change value of the primary electricity consumption of the february time is set as follows: EYSJBHCZ; for specific calculations, refer to the following formula:
EYSJBHCZ＝YLydduz14-YLydduz2；
thus, the primary electricity consumption change value … … of the three months and the primary electricity consumption change value of the ten months are calculated respectively; the set basic electricity utilization change value and the newly added electricity utilization change value are respectively as follows: JCYDBHz, XZYDBHz;
the primary basic electricity consumption change value is specifically referred to as the following formula:
JCYDBHz＝JCYDSz2-JCYDSz1；
please refer to the following formula for the specific new power consumption change value:
XZYDBHz＝XZYDSz2-XZYDSz1；
acquiring a class of electricity utilization degree values of electricity utilization type information of a 25T time period, a 26T time period and a 27T time period … … T time period; acquiring electricity utilization value in basic electricity utilization user number information and electricity utilization value in newly-added user number information in a 25T time period-36T time period;
the electricity utilization change values of the time periods 25T to 36T are respectively obtained, and the electricity utilization change values of each month are obtained;
the power load calculation module calculates a first month secondary power utilization change value, a second month secondary power utilization change value, a third month secondary power utilization change value … … and a third month secondary power utilization change value … …, a second basic power utilization change value and a second newly-increased power utilization change value;
the power value prediction module analyzes the power consumption change value of each month, the basic power consumption change value of each year and the new power consumption change value, predicts the total power generation amount value of the next year based on the increase or decrease ratio data of the power consumption change values, predicts the power consumption change value of each month accurately to the month, and transmits the predicted data to the server.
2. A power load prediction method based on power consumption data, which is applicable to a power load prediction system based on power consumption data as claimed in claim 1, characterized in that the prediction method comprises the following steps:
step S1: acquiring consumption information and electricity consumption information, and acquiring and analyzing data parameters of the consumption information and the electricity consumption information by an electricity information analysis module;
step S2: transmitting the data parameters obtained by analysis to a power load calculation module, and calculating power change information by the power load calculation module;
step S3: acquiring electricity consumption change values in different time periods, transmitting the electricity consumption change values to an electricity value prediction module, acquiring and counting increased electricity consumption information by a server, and predicting the total power generation amount by the electricity value prediction module by receiving the electricity consumption change values and the increased electricity consumption information;
step S4: and the predicted total power generation amount is combined with the increased power consumption information to be transmitted to a server, and the server controls the power generation control module to control the power generation amount.
3. The method according to claim 2, wherein in the step S1, the consumption information includes total electricity consumption information and user number information; the electricity consumption information comprises electricity consumption time information, price interval information and electricity consumption type information;
the user number information comprises basic user number information and newly added user number information;
when analyzing the consumption information and the electricity consumption information, the specific steps are as follows:
step S11: 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 respectively, obtaining basic electricity consumption number information and new increased number of users information,
step S12: acquiring a total electricity consumption value, a price interval value and various electricity consumption types in a time period T;
the electricity consumption total value and the price interval value of each electricity consumption type are respectively obtained, and electricity consumption degree values are obtained according to the analysis of the electricity consumption total value and the price interval value;
analyzing to obtain electricity consumption values in a T time period, and respectively analyzing to obtain electricity consumption values in a 2T time period and a 3T time period … … nT time period;
step S13: and establishing a plane rectangular coordinate system according to the acquired electricity consumption values of the time periods, representing the acquired electricity consumption values in the plane rectangular coordinate system, smoothly connecting the electricity consumption values by curves to form an electricity consumption degree curve graph, and observing the electricity consumption degree change according to the electricity consumption degree curve graph.
4. The method according to claim 2, wherein in the step S2, the power load calculation module receives a class of electricity consumption values for obtaining electricity consumption type information of T time periods, 2T time periods, and 3T time periods … … T time periods;
the electricity consumption change values of the 1T time period to the 12T time period are respectively obtained, and the electricity consumption change value of each month is obtained;
the electricity utilization change values of the 13T time period to the 24T time period are respectively obtained, and the electricity utilization change value of each month is obtained;
respectively calculating a primary power utilization change value of the first month, a primary power utilization change value of the second month, a primary power utilization change value of the third month … … and a primary power utilization change value of the third month, a primary basic power utilization change value and a new power utilization change value;
acquiring a class of electricity utilization degree values of electricity utilization type information of a 25T time period, a 26T time period and a 27T time period … … T time period;
the power load calculation module calculates a first month secondary power utilization change value, a second month secondary power utilization change value, a third month secondary power utilization change value … …, a second month secondary power utilization change value, a second basic power utilization change value and a second newly-increased power utilization change value.
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