CN110297456B - System and method for regulating and controlling oil-electricity integrated supply process - Google Patents

System and method for regulating and controlling oil-electricity integrated supply process Download PDF

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CN110297456B
CN110297456B CN201810247712.1A CN201810247712A CN110297456B CN 110297456 B CN110297456 B CN 110297456B CN 201810247712 A CN201810247712 A CN 201810247712A CN 110297456 B CN110297456 B CN 110297456B
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CN110297456A (en
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张洪阳
时振堂
钱志红
孙进
陶丽楠
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Sinopec Dalian Petrochemical Research Institute Co ltd
China Petroleum and Chemical Corp
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Sinopec Dalian Research Institute of Petroleum and Petrochemicals
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Abstract

The invention provides a regulation and control system and a regulation and control method for an oil-electricity integrated supply process, wherein the system comprises: the system comprises an oil-electricity separation control and protection unit, an external SCADA system interface, an execution interface, a PLC minimum system of an oil-electricity integrated supply regulation and control system, a data collection and monitoring unit and a system data processing unit; the oil-electricity separation control and protection unit is used for realizing the separation of oil and electricity on hardware; the external SCADA system interface is used for realizing remote parameter regulation and control and upward and downward sharing of data; the execution interface is used for realizing real-time control on the oiling machine and the charger on hardware; and the PLC minimum system is used for realizing the oil-electricity regulation and distribution optimization control of the whole system, outputting the optimized oil-electricity regulation and distribution and transmitting the optimized oil-electricity regulation and distribution to centralized control through the external SCADA system interface. The invention is applied to the oil-electricity supplement of fuel automobiles, oil-electricity hybrid electric vehicles, pure electric vehicles and the like, and can realize the optimization of the oil-electricity integrated supply process.

Description

System and method for regulating and controlling oil-electricity integrated supply process
Technical Field
The invention relates to the technical field of energy regulation and control, in particular to a system and a method for regulating and controlling an oil-electricity integrated supply process.
Background
In view of the development trend of the automobile industry, the development of electric vehicles is a trend. The reason for this is mainly the result of domestic and foreign policy-oriented continuous support and natural industry selection. The ' guiding opinions for accelerating the construction of electric vehicle charging infrastructures ', ' thirteen five ' planning for energy development ', the ' 2017 energy work guiding opinions ' and the like in China all put forward the requirements for the product popularization and infrastructure construction of electric vehicles and charging piles. Abroad, europe, america and other countries are also accelerating the pace of replacing traditional automobiles with new energy automobiles, and the two countries of the english and the french definitely start from 2040 years, and the two countries will stop selling gasoline and diesel automobiles in an effort to reduce environmental pollution and carbon emission causing global warming, while germany announces that fuel automobiles are stopped in 2030 years, and the proposal of the german national electric automobile plan shows that the german government intends to accelerate the development of the electric automobile market and supports green energy. In order to cooperate with the development of electric vehicles, the construction of electric vehicle charging infrastructure is very important.
It can be seen that the realization of the integrated oil-electricity supply in the future is a necessary result, while the current technology mainly focuses on the independent research of the related oil filling technology and the related charging technology, and the regulation and control of the integrated oil-electricity supply are in the initial exploration stage.
Disclosure of Invention
Aiming at the defects in the prior art, the invention provides a regulation and control system and a regulation and control method for an oil-electricity integrated supply process, and the regulation and control system and the regulation and control method can realize the optimization of the oil-electricity integrated supply process.
In order to achieve the purpose, the invention provides the following technical scheme:
in a first aspect, the present invention provides a regulation and control system for an integrated oil-electricity supply process, comprising: the system comprises an oil-electricity separation control and protection unit, an external SCADA system interface, an execution interface, a PLC minimum system of an oil-electricity integrated supply regulation and control system, a data collection and monitoring unit and a system data processing unit;
the oil-electricity separation control and protection unit, the execution interface, the PLC minimum system of the oil-electricity integrated supply regulation and control system, the data collection and monitoring unit and the system data processing unit are used as self-built parts in the system; the external SCADA system interface is used as a part for connecting with the outside;
the oil-electricity separation control and protection unit is used for realizing the separation of oil and electricity on hardware; the external SCADA system interface is used for realizing remote parameter regulation and control and upward and downward sharing of data; the execution interface is used for realizing real-time control on the oiling machine and the charger on hardware; the PLC minimum system is used for realizing the optimal control of the oil-electricity regulation and distribution of the whole system, outputting the optimized oil-electricity regulation and distribution and transmitting the optimized oil-electricity regulation and distribution to centralized control through the external SCADA system interface; the data collection and monitoring unit is used for realizing data uploading and issuing; the system data processing unit is used for unifying and initially processing data formats and sending the processed data to the PLC minimum system.
Further, the PLC minimum system is configured to perform the following processing procedures:
receiving the oil-electricity demand of the current month obtained through predictive analysis, and taking the oil-electricity demand as a target reference input value 1 of the PLC minimum system;
receiving actual consumption cost of refueling and charging calculated according to oil price and electricity price, and taking the actual consumption cost as a target reference input value 2 of the PLC minimum system;
receiving oil and electricity replenishment data actually selected by a user in the current month, and taking the oil and electricity replenishment data as an actual input value 1 of the PLC minimum system;
and determining the optimal values of the oil quantity reserve and the power load demand of the supply station by using an iterative search method according to the target reference input value 1, the target reference input value 2 and the actual input value 1.
Further, the model adopted by the iterative search is as follows:
prediction model function:
Cp1＝f1(N1,N2,C1,C2)＝N1*C1+N2*C2
Figure GDA0002628872740000031
an iterative matrix parameter estimation model:
Figure GDA0002628872740000032
Figure GDA0002628872740000033
in the formula, Cp1Is the statistical historical energy consumption; c1Is the monthly consumption of oil; c2Is the monthly consumption of electricity; n is a radical of1Is the natural month of the oil quantity statistics; n is a radical of2Is the natural month of the electricity statistics; d1Is the natural day of oil mass statistics; d2Is the natural day of the electricity counted; p is a radical of11、p12、…、pD1Is the daily oil consumption in the statistical month; p is a radical of21、p22、…、pD2Counting the daily electricity consumption in the month; x1…XMIs a predictive estimator variable and is subjected to Cp1The direct effect of (a); x is the number of11…xMQIs a parameter estimate; f. of1…fQIs a parameter estimation variable; u. of1….uMIs an estimated variable influence factor regulated and controlled in the last natural month; cGeneral assemblyIs the final iterative function fitted, representing a cluster of predicted curves based on historical data.
Further, in the cluster of prediction curves, on the premise that a regulation region is met, free and flexible regulation and control are performed based on the existing oil and electricity storage amount in the last natural month, wherein the selection of the regulation and control region is related to the parameter estimation value and the estimation variable influence factor.
Further, the PLC minimum system has a remote parameter adjusting function.
Further, the PLC minimum system is matched with an external SCADA system to realize data sharing and instruction execution.
In a second aspect, the present invention further provides a method for regulating and controlling an oil-electricity integrated supply process, including:
step S1: according to the historical traffic flow and the oil and electricity consumption data, performing predictive analysis in advance, and determining the oil and electricity demand in the current month as a target reference value 1 input by a regulation and control system;
step S2: calculating actual consumption cost of refueling and charging according to the difference between the oil price and the electricity price, and using the actual consumption cost as a target reference value 2 input by a regulation and control system;
step S3: feeding back the oil and electricity replenishment data actually selected by the user in the current month to the regulation and control system as an actual value 1 input by the regulation and control system;
step S4: and determining the optimal values of the oil quantity reserve and the power load demand of the supply station by using an iterative search method according to the target reference value 1, the target reference value 2 and the actual value 1.
Further, the model adopted by the iterative search is as follows:
prediction model function:
Cp1＝f1(N1,N2,C1,C2)＝N1*C1+N2*C2
Figure GDA0002628872740000041
an iterative matrix parameter estimation model:
Figure GDA0002628872740000042
Figure GDA0002628872740000043
in the formula, Cp1Is the statistical historical energy consumption; c1Is the monthly consumption of oil; c2Is the monthly consumption of electricity; n is a radical of1Is the natural month of the oil quantity statistics; n is a radical of2Is the natural month of the electricity statistics; d1Is the natural day of oil mass statistics; d2Is made throughThe natural day of the electricity measured; p is a radical of11、p12、…、pD1Is the daily oil consumption in the statistical month; p is a radical of21、p22、…、pD2Counting the daily electricity consumption in the month; x1…XMIs a predictive estimator variable and is subjected to Cp1The direct effect of (a); x is the number of11…xMQIs a parameter estimate; f. of1…fQIs a parameter estimation variable; u. of1….uMIs an estimated variable influence factor regulated and controlled in the last natural month; cGeneral assemblyIs the final iterative function fitted, representing a cluster of predicted curves based on historical data.
Further, in the cluster of prediction curves, on the premise that a regulation region is met, free and flexible regulation and control are performed based on the existing oil and electricity storage amount in the last natural month, wherein the selection of the regulation and control region is related to the parameter estimation value and the estimation variable influence factor.
Furthermore, the regulation and control system is realized by adopting a PLC minimum system and has a remote parameter regulation function.
According to the technical scheme, the oil-electricity separation of hardware is realized through the oil-electricity separation control and protection unit by the oil-electricity integrated supply process regulation and control system; remote parameter regulation and control and upward and downward sharing of data are realized through an external SCADA system interface; the oiling machine and the charger are controlled in real time on hardware through an execution interface; the oil-electricity regulation and distribution optimization control of the whole system is realized through a PLC minimum system, the optimized oil-electricity regulation and distribution is output, and the optimized oil-electricity regulation and distribution is transmitted to centralized control through an external SCADA system interface. The regulation and control system for the integrated oil-electricity supply process can realize optimization of the integrated oil-electricity supply process.
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In order to more clearly illustrate the embodiments of the present invention or the technical solutions in the prior art, the drawings used in the description of the embodiments or the prior art will be briefly introduced below, and it is obvious that the drawings in the following description are some embodiments of the present invention, and for those skilled in the art, other drawings can be obtained according to these drawings without creative efforts.
Fig. 1 is a schematic structural diagram of a regulation and control system for an integrated oil-electricity supply process according to an embodiment of the present invention;
FIG. 2 is a schematic diagram of a system regulation optimization process;
fig. 3 is a flowchart of a method for controlling an integrated oil-electricity supply process according to another embodiment of the present invention;
the meaning of the reference symbols in figure 1 above is explained as follows:
1 represents an oil-electricity separation control and protection unit; 2 denotes an external SCADA system interface; 3 denotes an execution interface; 4 represents a PLC minimum system of the oil-electricity integrated supply regulation system; 5 denotes a data collection and monitoring unit; and 6, a system data processing unit.
Detailed Description
In order to make the objects, technical solutions and advantages of the embodiments of the present invention clearer, the technical solutions in the embodiments of the present invention will be clearly and completely described below with reference to the drawings in the embodiments of the present invention, and it is obvious that the described embodiments are some, but not all, embodiments of the present invention. All other embodiments, which can be derived by a person skilled in the art from the embodiments given herein without making any creative effort, shall fall within the protection scope of the present invention.
The regulation and control system for the integrated oil-electricity supply process provided by the embodiment of the invention can be applied to an automobile energy supply station integrating a gas station and a charging station, for example, oil-electricity supply to an oil automobile, an oil-electricity hybrid electric vehicle, a pure electric automobile and the like, and can realize optimized allocation and rapid supply of oil-electricity energy.
An embodiment of the present invention provides a regulation and control system for an oil-electricity integrated supply process, referring to fig. 1, including: the system comprises an oil-electricity separation control and protection unit 1, an external SCADA system interface 2, an execution interface 3, a PLC minimum system 4 of an oil-electricity integrated supply regulation and control system, a data collection and monitoring unit 5 and a system data processing unit 6;
the oil-electricity separation control and protection unit 1, the execution interface 3, the PLC minimum system 4 of the oil-electricity integrated supply regulation and control system, the data collection and monitoring unit 5 and the system data processing unit 6 are used as self-built parts in the system; the external SCADA system interface 2 is used as a part for connecting with the outside;
the oil-electricity separation control and protection unit 1 is used for realizing the separation of oil and electricity on hardware; the external SCADA system interface 2 is used for realizing remote parameter regulation and control and upward and downward sharing of data; the execution interface 3 is used for realizing real-time control on the oiling machine and the charger on hardware; the PLC minimum system 4 is used for realizing the oil-electricity regulation and distribution optimization control of the whole system, outputting the optimized oil-electricity regulation and distribution, and transmitting the optimized oil-electricity regulation and distribution to a centralized control (the centralized control is not shown in figure 1) through the external SCADA system interface 2; the data collection and monitoring unit 5 is used for realizing data uploading and issuing; the system data processing unit 6 is used for unifying and initially processing data formats, and sending the processed data to the PLC minimum system 4.
According to the technical scheme, the oil-electricity separation of hardware is realized through the oil-electricity separation control and protection unit by the oil-electricity integrated supply process regulation and control system provided by the embodiment; remote parameter regulation and control and upward and downward sharing of data are realized through an external SCADA system interface; the oiling machine and the charger are controlled in real time on hardware through an execution interface; and the oil-electricity regulation and distribution optimization control of the whole system is realized through a PLC minimum system, the optimized oil-electricity regulation and distribution is output, and the optimized oil-electricity regulation and distribution is transmitted to centralized control through the external SCADA system interface. The regulation and control system of the integrated oil-electricity supply process provided by the embodiment can realize the optimization of the integrated oil-electricity supply process.
In a preferred embodiment, the PLC minimum system 4 is configured to perform the following processes:
receiving the oil-electricity demand of the current month obtained through predictive analysis, and taking the oil-electricity demand as a target reference input value 1 of the PLC minimum system;
receiving actual consumption cost of refueling and charging calculated according to oil price and electricity price, and taking the actual consumption cost as a target reference input value 2 of the PLC minimum system;
receiving oil and electricity replenishment data actually selected by a user in the current month, and taking the oil and electricity replenishment data as an actual input value 1 of the PLC minimum system;
and determining the optimal values of the oil quantity reserve and the power load demand of the supply station by using an iterative search method according to the target reference input value 1, the target reference input value 2 and the actual input value 1.
In a preferred embodiment, referring to fig. 2, the model used for the iterative search is as follows:
prediction model function:
Cp1＝f1(N1,N2,C1,C2)＝N1*C1+N2*C2
Figure GDA0002628872740000071
an iterative matrix parameter estimation model:
Figure GDA0002628872740000072
Figure GDA0002628872740000073
in the formula, Cp1Is the statistical historical energy consumption; c1Is the monthly consumption of oil; c2Is the monthly consumption of electricity; n is a radical of1Is the natural month of the oil quantity statistics; n is a radical of2Is the natural month of the electricity statistics; d1Is the natural day of oil mass statistics; d2Is the natural day of the electricity counted; p is a radical of11、p12、…、pD1Is the daily oil consumption in the statistical month; p is a radical of21、p22、…、pD2Counting the daily electricity consumption in the month; x1…XMIs a predictive estimator variable and is subjected to Cp1The direct effect of (a); x is the number of11…xMQIs a parameter estimate; f. of1…fQIs a parameter estimation variable；u1….uMIs an estimated variable influence factor regulated and controlled in the last natural month; cGeneral assemblyIs the final iterative function fitted, representing a cluster of predicted curves based on historical data.
It can be understood that, in the cluster of prediction curves, on the premise that a regulation region is satisfied, free and flexible regulation can be performed based on the existing oil and electricity storage in the last natural month, wherein the selection of the regulation region is closely related to the parameter estimation value and the estimation variable influence factor.
It will be appreciated that predictive analysis may be based on methods of quantitative prediction, including 3 parts of predicting objects and targets, predicting model and parameter estimation, model verification and correction, etc. During specific treatment, the actual consumption cost is counted according to the month data, and then the actual consumption cost is used as a basis for predicting the consumption behavior of the client. And updating the system feedback quantity according to different selections of the user in the current month, and based on the prediction model object and the target.
In a preferred embodiment, the PLC minimum system is provided with a remote parameter adjustment function.
In a preferred embodiment, the PLC minimum system cooperates with an external SCADA system to implement data sharing and instruction execution.
The following explains the regulation and optimization process of the regulation and control system of the integrated oil-electricity supply process provided by the embodiment of the invention with a specific example. The principle is described as follows: the prediction object is oil and electricity supply data in 3 years; the prediction target is to give quantitative data of oil and electricity supply of 1-12 months in each year, and the total number is 36; the predictive model is a fitted curve based on the supply data; the prediction model parameter estimation is: one is that the fluctuation rate is predicted according to plus or minus 5 percent and can be adjusted; two are within 36 months of month selection and are adjustable; the prediction months can be adjusted according to 1-3 months; the model test takes the measured data within 1 month as comparison and correction; and the actual consumption cost is counted according to the consumption data within 3 years, so that the basis of the consumption behavior of the client is predicted. Corresponding to the above embodiment, N may be selected1Is 36; n is a radical of2Is 24; d1Is 30 or 31；D2Is 30 or 31; x1Is fluctuation of oil price, X2The electricity price fluctuates and is subjected to Cp1The direct effect of (a); x is the number of11Is 3%, x21Is 1%; f. of1Is the oil variable, f2Is an electrical variable; u. of1 Is 1%, u2Is 1.5%, and is an estimated variable influence factor predicted to be regulated in the last natural month. Based on the above, the regulation of oil and electricity supply in the next month can be obtained as the optimization of resource allocation.
Therefore, the regulation and control system for the integrated oil-electricity supply process provided by the embodiment of the invention can be applied to an automobile energy supply station integrating a gas station and a charging station, and is used for supplying oil and electricity to an oil automobile, an oil-electricity hybrid electric vehicle, a pure electric automobile and the like, so that optimal energy allocation and rapid supply are realized. In the present embodiment, the variable "X1”…“XM”，“x11”…“xMQ”，“f1”…“fQ"is a parameter estimate," u1”…“uM"merely represents variables and parameters, and the symbols themselves have no material difference, only distinction in expression.
Another embodiment of the present invention provides a method for controlling an oil-electricity integrated supply process, referring to fig. 3, the method including the steps of:
step 101: according to the historical traffic flow and the oil and electricity consumption data, performing predictive analysis in advance, and determining the oil and electricity demand in the current month as a target reference value 1 input by a regulation and control system;
step 102: calculating actual consumption cost of refueling and charging according to the difference between the oil price and the electricity price, and using the actual consumption cost as a target reference value 2 input by a regulation and control system;
step 103: feeding back the oil and electricity replenishment data actually selected by the user in the current month to the regulation and control system as an actual value 1 input by the regulation and control system;
step 104: and determining the optimal values of the oil quantity reserve and the power load demand of the supply station by using an iterative search method according to the target reference value 1, the target reference value 2 and the actual value 1.
In a preferred embodiment, the model used in the iterative search is as follows:
prediction model function:
Cp1＝f1(N1,N2,C1,C2)＝N1*C1+N2*C2
Figure GDA0002628872740000091
an iterative matrix parameter estimation model:
Figure GDA0002628872740000101
Figure GDA0002628872740000102
in the formula, Cp1Is the statistical historical energy consumption; c1Is the monthly consumption of oil; c2Is the monthly consumption of electricity; n is a radical of1Is the natural month of the oil quantity statistics; n is a radical of2Is the natural month of the electricity statistics; d1Is the natural day of oil mass statistics; d2Is the natural day of the electricity counted; p is a radical of11、p12、…、pD1Is the daily oil consumption in the statistical month; p is a radical of21、p22、…、pD2Counting the daily electricity consumption in the month; x1…XMIs a predictive estimator variable and is subjected to Cp1The direct effect of (a); x is the number of11…xMQIs a parameter estimate; f. of1…fQIs a parameter estimation variable; u. of1…uMIs an estimated variable influence factor regulated and controlled in the last natural month; cGeneral assemblyIs the final iterative function fitted, representing a cluster of predicted curves based on historical data.
In a preferred embodiment, in the cluster of prediction curves, on the premise that a regulation region is satisfied, free flexible regulation and control are performed based on the existing oil and electricity storage in the last natural month, wherein the selection of the regulation region is related to the parameter estimation value and the estimation variable influence factor.
In a preferred embodiment, the regulation and control system is realized by a PLC minimum system and has a remote parameter adjustment function.
The above examples are only for illustrating the technical solutions of the present invention, and not for limiting the same; although the present invention has been described in detail with reference to the foregoing embodiments, it will be understood by those of ordinary skill in the art that: the technical solutions described in the foregoing embodiments may still be modified, or some technical features may be equivalently replaced; and such modifications or substitutions do not depart from the spirit and scope of the corresponding technical solutions of the embodiments of the present invention.

Claims (10)

1. A regulation and control system of oil-electricity integration supply process, characterized by includes: the system comprises an oil-electricity separation control and protection unit, an external SCADA system interface, an execution interface, a PLC minimum system of an oil-electricity integrated supply regulation and control system, a data collection and monitoring unit and a system data processing unit;
the oil-electricity separation control and protection unit, the execution interface, the PLC minimum system of the oil-electricity integrated supply regulation and control system, the data collection and monitoring unit and the system data processing unit are used as self-built parts in the system; the external SCADA system interface is used as a part for connecting with the outside;
the oil-electricity separation control and protection unit is used for realizing the separation of oil and electricity on hardware; the external SCADA system interface is used for realizing remote parameter regulation and control and upward and downward sharing of data; the execution interface is used for realizing real-time control on the oiling machine and the charger on hardware; the PLC minimum system is used for realizing the optimal control of the oil-electricity regulation and distribution of the whole system, outputting the optimized oil-electricity regulation and distribution and transmitting the optimized oil-electricity regulation and distribution to centralized control through the external SCADA system interface; the data collection and monitoring unit is used for realizing data uploading and issuing; the system data processing unit is used for unifying and initially processing data formats and sending the processed data to the PLC minimum system.
2. The system of claim 1, wherein the PLC minimum system is configured to perform the following process:
receiving the oil-electricity demand of the current month obtained through predictive analysis, and taking the oil-electricity demand as a target reference input value 1 of the PLC minimum system;
receiving actual consumption cost of refueling and charging calculated according to oil price and electricity price, and taking the actual consumption cost as a target reference input value 2 of the PLC minimum system;
receiving oil and electricity replenishment data actually selected by a user in the current month, and taking the oil and electricity replenishment data as an actual input value 1 of the PLC minimum system;
and determining the optimal values of the oil quantity reserve and the power load demand of the supply station by using an iterative search method according to the target reference input value 1, the target reference input value 2 and the actual input value 1.
3. The system of claim 2, wherein the iterative search employs a model as follows:
prediction model function:
Cp1＝f1(N1,N2,C1,C2)＝N1*C1+N2*C2
Figure FDA0002628872730000021
an iterative matrix parameter estimation model:
Figure FDA0002628872730000022
Figure FDA0002628872730000023
in the formula, Cp1Is the statistical historical energy consumption; c1Is the monthly consumption of oil; c2Is the monthly consumption of electricity; n is a radical of1Is the natural month of the oil quantity statistics; n is a radical of2Is the natural month of the electricity statistics; d1Is the natural day of oil mass statistics; d2Is the natural day of the electricity counted; p is a radical of11、p12、…、pD1Is the daily oil consumption in the statistical month; p is a radical of21、p22、…、pD2Counting the daily electricity consumption in the month; x1…XMIs a predictive estimator variable and is subjected to Cp1The direct effect of (a); x is the number of11…xMQIs a parameter estimate; f. of1…fQIs a parameter estimation variable; u. of1…uMIs an estimated variable influence factor regulated and controlled in the last natural month; cGeneral assemblyIs the final iterative function fitted, representing a cluster of predicted curves based on historical data.
4. The system according to claim 3, wherein in the cluster of prediction curves, free flexible regulation is performed based on the existing oil and electricity storage amount in the last natural month on the premise that a regulation region is satisfied, wherein the regulation region is selected in relation to the parameter estimation value and the estimation variable influence factor.
5. The system according to any one of claims 1 to 4, wherein the PLC minimal system is provided with a remote parameter adjustment function.
6. The system according to any one of claims 1 to 4, wherein the PLC minimal system cooperates with an external SCADA system to realize data sharing and instruction execution.
7. A method for regulating and controlling an oil-electricity integrated supply process is characterized by comprising the following steps:
step S1: according to the historical traffic flow and the oil and electricity consumption data, performing predictive analysis in advance, and determining the oil and electricity demand in the current month as a target reference value 1 input by a regulation and control system;
step S2: calculating actual consumption cost of refueling and charging according to the difference between the oil price and the electricity price, and using the actual consumption cost as a target reference value 2 input by a regulation and control system;
step S3: feeding back the oil and electricity replenishment data actually selected by the user in the current month to the regulation and control system as an actual value 1 input by the regulation and control system;
step S4: and determining the optimal values of the oil quantity reserve and the power load demand of the supply station by using an iterative search method according to the target reference value 1, the target reference value 2 and the actual value 1.
8. The method of claim 7, wherein the iterative search uses the following model:
prediction model function:
Cp1＝f1(N1,N2,C1,C2)＝N1*C1+N2*C2
Figure FDA0002628872730000031
an iterative matrix parameter estimation model:
Figure FDA0002628872730000032
Figure FDA0002628872730000033
in the formula, Cp1Is the statistical historical energy consumption; c1Is the monthly consumption of oil; c2Is the monthly consumption of electricity; n is a radical of1Is the natural month of the oil quantity statistics; n is a radical of2Is the natural month of the electricity statistics; d1Is the natural day of oil mass statistics; d2Is the natural day of the electricity counted; p is a radical of11、p12、…、pD1Is the daily oil consumption in the statistical month; p is a radical of21、p22、…、pD2Counting the daily electricity consumption in the month; x1…XMIs a predictive estimator variable and is subjected to Cp1The direct effect of (a); x is the number of11…xMQIs a parameter estimate; f. of1…fQIs a parameter estimation variable; u. of1….uMIs an estimated variable influence factor regulated and controlled in the last natural month; cGeneral assemblyIs the final iterative function fitted, representing a cluster of predicted curves based on historical data.
9. The method according to claim 8, wherein in the cluster of prediction curves, free flexible regulation is performed based on the existing oil and electricity storage amount in the last natural month on the premise that a regulation region is met, wherein the regulation region is selected in relation to the parameter estimation value and the estimation variable influence factor.
10. The method according to any one of claims 7 to 9, wherein the regulation and control system is implemented by a PLC minimum system and has a remote parameter adjustment function.
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