CN110689239A - Auxiliary decision-making method and system for realizing income maximization by participation of power users in market - Google Patents
Auxiliary decision-making method and system for realizing income maximization by participation of power users in market Download PDFInfo
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Abstract
The invention provides an auxiliary decision-making method and an auxiliary decision-making system for realizing income maximization by participation of power consumers in a power selling market, wherein the method comprises the following steps: the method comprises the following steps: acquiring related information; step two: analyzing and classifying the acquired information, predicting the load of the power consumer, and predicting the electric power transaction price which does not definitely stipulate the transaction price; step three: solving and checking the maximum electricity selling income; step four: and outputting and storing the verified maximum electricity selling income. The invention is based on the detailed analysis of the electricity selling trading rules, market quotations, the load characteristics of the power users and the equipment conditions, and solves the electric quantity of different trade varieties participating in different power markets by taking the maximum income of the users participating in the electricity selling markets as the target, thereby assisting the power users to make reference decisions.
Description
Technical Field
The invention belongs to the technical field of power system electricity selling, and particularly relates to an auxiliary decision-making method and an auxiliary decision-making system for realizing income maximization by participation of power users in an electricity selling market.
Background
With the release of the electric power spot market and the auxiliary service market, the electricity selling market is gradually subdivided and different transaction varieties are more and more abundant, the full development from the starting of a new electricity change to the current spot commissioning province spot commissioning is realized, the electricity selling market is expanded from the medium-long term transaction of the electric energy market to the current and day spot transaction, the electric power auxiliary service market also develops marketized frequency modulation service, and the market-oriented transaction of other auxiliary services of the auxiliary service market, such as peak regulation, standby, black starting, demand side response and the like, as well as the electric power capacity market and the electric power transmission right market is believed to be carried out in the near future. With the more and more subdivided electricity selling markets and the more and more abundant transaction varieties, how to distribute the electric quantity participating in different electricity transaction varieties by power users so as to maximize the income becomes a key problem for the power users to participate in the electricity selling markets.
In the prior patent application No. CN201910016448.5, there is provided a power purchase decision method for a power selling company considering user demand response, including: the method comprises the steps of inputting the cost of an electric quantity interruption contract signed by an electric power selling company and a user, the income obtained by selling an interruptible load to the electric power selling company by the user and the income obtained by transferring a peak time period load to a valley time period load by the user into an electric power purchasing decision double-layer model of the electric power selling company, determining an electric power purchasing decision of the electric power selling company, reducing the electric power consumption cost of the user, improving the profit of the electric power selling company and achieving win-win. According to the method, the peak shifting and valley filling are carried out by utilizing the response of the user side demand side to obtain more electric energy market electric quantity trading benefits, other more trading varieties are not considered, and an auxiliary decision system for realizing the benefit maximization by the participation of power users in the electricity selling market is not involved.
The prior patent application No. CN201711066797.5 provides a system and method for evaluating the value of a power customer, the power customer value evaluation system comprises a user file information database, a user operation system database server, a user value analysis system database, a survey information input module and an FTP server, wherein the user operation system database server can obtain user file information data, the user operation system database server is connected with the user value analysis system database to transmit the user file data, meanwhile, the survey information input module is connected with a user value analysis system database to transmit survey information, the user file pictures are transmitted through the FTP server, and the user value analysis system database carries out comprehensive analysis on the user file information data, the investigation information and the user file pictures through a built-in processing analyzer, so that the comprehensive value evaluation result of the client is effectively, accurately and intelligently obtained. The patent of the invention focuses on the evaluation of the comprehensive value of a company, does not consider how to realize the value maximization, and does not relate to an auxiliary decision-making system for realizing the income maximization by the participation of power consumers in the power selling market.
At present, the electric power spot market and the auxiliary service market are just released in a few provinces and are still in a trial phase, an electric power user only has some experiences on medium-term and long-term transactions of the electric energy market, and the prior technical scheme and the electric power selling strategy do not comprehensively consider how to distribute the electric quantity of the electric power user and adjust power supply and utilization facilities to participate in transactions of different transaction types of different markets so as to realize maximization of benefits of electric power selling transactions for the medium-term and long-term transactions or the spot transactions.
Disclosure of Invention
Based on the problems in the prior art, the invention provides an auxiliary decision method and an auxiliary decision system for realizing income maximization by participation of power consumers in a power selling market.
The invention provides an auxiliary decision-making method for realizing income maximization by participation of power consumers in a power selling market, which comprises the following steps:
the method comprises the following steps: acquiring related information;
step two: analyzing and classifying the acquired information, predicting the load of the power consumer, and predicting the electric power transaction price which does not definitely stipulate the transaction price;
step three: solving and checking the maximum electricity selling income;
step four: and outputting and storing the verified maximum electricity selling income.
Further preferably, in the first step, the related information is acquired by an information acquisition module, the acquisition mode includes direct acquisition from the outside or manual input, and the related information includes:
(1) acquiring local transaction policy and rule information: the method comprises the steps of transaction time, transaction price or price limit, transaction electric quantity or power limit and transaction risk undertaking rule;
(2) obtaining market information; the system comprises historical transaction data, power grid architecture information and power plant information;
(3) acquiring power consumer information: the system comprises a historical load curve, power consumption requirements, a production and maintenance plan, a working day type, meteorological factors, power consumption equipment information and equipment adjustment and operation parameter information of controllable loads.
Further preferably, in the second step, the information analyzing and classifying module is used to analyze and classify the related information obtained in the first step, predict the load of the power consumer, predict the power transaction price without clearly regulated transaction price, and form the following information:
(1) a load prediction curve for normal production by a user;
(2) the controllable load prediction curve specifically comprises a controllable load prediction upper limit curve and a controllable load prediction lower limit curve;
(3) predicted or specified prices versus time curves for various types of power transactions;
(4) a relationship curve between risk punishment and electric quantity of various electric power transactions;
(5) and (4) calling a generated extra cost and electric quantity relation curve by the controllable load.
Further preferably, in the third step, a profit solving module is adopted to solve the maximum electricity selling profit, and the objective function is as follows:
in the formula:
c: selling electricity earnings;
n: the number of all transaction types, n represents the nth transaction;
: the total electric quantity of the transaction participated in by the nth transaction meets the requirement
QmaxThe maximum electricity consumption of the user is obtained; qnThe maximum electric quantity which can be generated by equipment of the user participating in the nth transaction is not more than or equal to;
Tn: the total time that the nth transaction is engaged in the transaction;
P(n,t): transaction price at nth transaction time t;
Q(n,t): the transaction electric quantity at the nth transaction t moment;
δQn: the punished electric quantity generated by the nth transaction or the total electric quantity of calling expense brought by calling the controllable load;
δP(n,t): penalty price generated at the nth transaction t moment or calling cost price brought by calling the controllable load;
δQ(n,t): punishment electric quantity generated at the nth transaction t moment or total electric quantity of calling cost brought by calling the controllable load;
q: one-dimensional variables, impact factors; t: the current time.
According to the load curve of the power consumer and the operation characteristics of the equipment, the upper limit of the electric quantity participating in each type of transaction is obtained, the price of each type of transaction and the generated risk or calling cost are predicted, so that the maximum value of the electricity selling income C and the corresponding Q are solved by utilizing an algorithm of solving the maximum value by mathematicsnAnd δ QnAnd forming various transaction load curves with the load curve of the time t, checking the various formed transaction load curves, judging whether the transaction load curves meet the production requirements and the constraint of equipment operation, and solving a smaller maximum value until the transaction load curves pass the checking if the transaction load curves do not pass the checking.
Further preferably, in the fourth step, the power purchase scheme which passes the verification is output through the power purchase scheme output module, and the power purchase scheme comprises the maximum profit of power selling, various transaction load curves, risk deviation electric quantity curves and a load calling scheme.
The invention provides an aid decision-making system for realizing income maximization by participation of power consumers in an electricity selling market, which comprises the following modules: the system comprises an information acquisition module, an information analysis and classification module, a profit solving module and an electricity purchasing scheme output module, wherein the information acquisition module is used for acquiring relevant information and sending the relevant information to the information analysis and classification module, the information analysis and classification module is used for completing analysis, classification and prediction to obtain relevant various curve information, the profit solving module is used for obtaining the maximum value of electricity selling profits and various transaction load curves, the maximum value and various transaction load curves are checked, and the electricity purchasing scheme after the check is passed is output through the output module.
Further preferably, the information obtaining module obtains the information directly from outside or manually, and the obtained related information includes:
(1) acquiring local transaction policy and rule information: the method comprises the steps of transaction time, transaction price or price limit, transaction electric quantity or power limit and transaction risk undertaking rule;
(2) obtaining market information; the system comprises historical transaction data, power grid architecture information and power plant information;
(3) acquiring power consumer information: the system comprises a historical load curve, power consumption requirements, a production and maintenance plan, a working day type, meteorological factors, power consumption equipment information and equipment adjustment and operation parameter information of controllable loads.
Further preferably, the information analyzing and classifying module analyzes and classifies the information acquired by the information acquiring module, predicts the load of the power consumer, predicts the power transaction price for which the transaction price is not clearly specified, and finally forms the following information:
(1) a load prediction curve for normal production by a user;
(2) the controllable load prediction curve specifically comprises a controllable load prediction upper limit curve and a controllable load prediction lower limit curve;
(3) predicted or specified prices versus time curves for various types of power transactions;
(4) a relationship curve between risk punishment and electric quantity of various electric power transactions;
(5) and (4) calling a generated extra cost and electric quantity relation curve by the controllable load.
Further preferably, the profit maximization is targeted in the profit solving module, and the objective function is as follows:
in the formula:
c: selling electricity earnings;
n: the number of all transaction types, n represents the nth transaction;
: the total electric quantity of the transaction participated in by the nth transaction meets the requirement
QmaxThe maximum electricity consumption of the user is obtained; qn is less than or equal to
The user participates in the nth transaction and the maximum amount of electricity the equipment can generate;
Tn: the total time that the nth transaction is engaged in the transaction;
P(n,t): transaction price at nth transaction time t;
Q(n,t): the transaction electric quantity at the nth transaction t moment;
δQn: the punished electric quantity generated by the nth transaction or the total electric quantity of calling expense brought by calling the controllable load;
δP(n,t): penalty price generated at the nth transaction t moment or calling cost price brought by calling the controllable load;
δQ(n,t): punishment electric quantity generated at the nth transaction t moment or total electric quantity of calling cost brought by calling the controllable load;
according to the load curve of the power consumer and the operation characteristics of the equipment, the electric quantity participating in each type of transaction is obtainedThe price and the generated risk or the calling cost of each type of transaction are predicted, so the maximum value of the electricity selling income C and the corresponding Q are solved by utilizing an algorithm of solving the maximum value by mathematicsnAnd δ QnAnd forming various transaction load curves with the load curve of the time t, checking the various formed transaction load curves, judging whether the transaction load curves meet the production requirements and the constraint of equipment operation, and solving a smaller maximum value until the transaction load curves pass the checking if the transaction load curves do not pass the checking.
Further preferably, the electricity purchasing scheme output module is configured to output the electricity purchasing scheme which passes the checking, wherein the electricity purchasing scheme includes a maximum profit of electricity selling, various transaction load curves, a risk deviation electric quantity curve, and a load calling scheme.
The invention has the advantages that:
the invention provides an auxiliary decision-making method and an auxiliary decision-making system for realizing profit maximization by participation of power consumers in a power selling market.
Drawings
Fig. 1 is a schematic flow chart of implementation of an aid decision method for realizing profit maximization by participation of power consumers in an electricity selling market provided by the invention.
Detailed Description
In the following, only certain exemplary embodiments are briefly described. As those skilled in the art can appreciate, the described embodiments can be modified in various different ways, without departing from the spirit or scope of the present disclosure. Accordingly, the drawings and description are to be regarded as illustrative in nature, and not as restrictive.
In the description of the present disclosure, it is to be understood that the terms "center", "longitudinal", "lateral", "length", "width", "thickness", "upper", "lower", "front", "rear", "left", "right", "straight", "horizontal", "top", "bottom", "inner", "outer", "clockwise", "counterclockwise", and the like, indicate orientations or positional relationships based on those shown in the drawings, and are only for convenience of description and simplicity of description, but do not indicate or imply that the device or element being referred to must have a particular orientation, be constructed in a particular orientation, and be operated, and therefore should not be considered as limiting the present disclosure. Furthermore, the terms "first", "second" and "first" are used for descriptive purposes only and are not to be construed as indicating or implying relative importance or implicitly indicating the number of technical features indicated. Thus, features defined as "first", "second", may explicitly or implicitly include one or more of the described features. In the description of the present disclosure, "a plurality" means two or more unless specifically limited otherwise.
Throughout the description of the present disclosure, it is to be noted that, unless otherwise expressly specified or limited, the terms "mounted," "connected," and "connected" are to be construed broadly, e.g., as meaning either a fixed connection, a removable connection, or an integral connection, either mechanically, electrically, or otherwise in communication with one another; either directly or indirectly through intervening media, either internally or in any other relationship. The specific meaning of the above terms in the present disclosure can be understood by those of ordinary skill in the art as appropriate.
In the present disclosure, unless expressly stated or limited otherwise, the first feature "on" or "under" the second feature may comprise the first and second features being in direct contact, or may comprise the first and second features being in contact, not directly, but via another feature in between. Also, the first feature being "on," "above" and "over" the second feature includes the first feature being directly on and obliquely above the second feature, or merely indicating that the first feature is at a higher level than the second feature. A first feature being "under," "below," and "beneath" a second feature includes the first feature being directly above and obliquely above the second feature, or simply meaning that the first feature is at a lesser level than the second feature.
The following disclosure provides many different embodiments or examples for implementing different features of the disclosure. To simplify the disclosure of the present disclosure, specific example components and arrangements are described below. Of course, they are merely examples and are not intended to limit the present disclosure. Moreover, the present disclosure may repeat reference numerals and/or reference letters in the various examples, which have been repeated for purposes of simplicity and clarity and do not in themselves dictate a relationship between the various embodiments and/or arrangements discussed. In addition, the present disclosure provides examples of various specific processes and materials, but one of ordinary skill in the art may recognize applications of other processes and/or use of other materials.
The preferred embodiments of the present disclosure will be described in conjunction with the appended drawings, it being understood that the preferred embodiments described herein are merely for purposes of illustrating and explaining the present disclosure and are not intended to limit the present disclosure
The invention is realized by the following technical scheme: the invention provides an auxiliary decision-making system for realizing income maximization by participation of power consumers in an electricity selling market, which mainly comprises the following modules: the system comprises an information acquisition module, an information analysis and classification module, a profit solving module and an electricity purchase scheme output module.
The information acquisition module is used for acquiring the following information:
acquiring local transaction policy and rule information: the method comprises the steps of transaction time, transaction price or price limit, transaction electric quantity or power limit, transaction risk undertaking rules such as electric energy market deviation assessment and the like;
obtaining market information; the system comprises historical transaction data, power grid architecture information, power plant information and the like;
acquiring power consumer information: the system comprises a historical load curve, power consumption requirements, a production and maintenance plan, a working day type, meteorological factors, power consumption equipment information, equipment adjustment and operation parameter information of controllable loads and the like.
The controllable load means that a power user has a distributed power supply, an energy storage facility and adjustable power utilization equipment (including the adjustment of a production plan) to change the load characteristics, and can participate in power selling market transactions such as power selling deviation regulation and control, demand side response, reactive power compensation, frequency modulation and the like.
The information analysis and classification module is used for analyzing and classifying the information acquired by the information acquisition module, predicting the load of the power consumer by means of the existing technology or a load prediction system and a price prediction system on the market, and predicting the electric power transaction price which does not definitely stipulate the transaction price so as to finally form the following types of information:
(1) a load prediction curve for normal production by a user;
(2) the controllable load prediction curve is a controllable load independent action curve only outside the basis of the load prediction curve in normal production, and the curve can comprise two curves, a controllable load prediction upper limit curve and a controllable load prediction lower limit curve;
(3) predicted or specified prices versus time curves for various types of power transactions;
(4) a relationship curve between risk punishment and electric quantity of various electric power transactions;
(5) and (4) calling a generated extra cost and electric quantity relation curve by the controllable load.
The profit maximization solving module aims at solving the profit maximization, and an objective function is as follows:
in the formula:
c: selling electricity earnings;
n: the number of all transaction types, n represents the nth transaction, namely the transaction ordinal number;
: the total electric quantity of the transaction participated in by the nth transaction meets the requirement
QmaxThe maximum electricity consumption of the user is obtained; qn≤
The user participates in the nth transaction and the maximum amount of electricity the equipment can generate;
Tn: the total time that the nth transaction is engaged in the transaction;
P(n,t): transaction price at nth transaction time t;
Q(n,t): the nth transactiontransaction electric quantity at the time t;
δQn: the punished electric quantity generated by the nth transaction or the total electric quantity of calling expense brought by calling the controllable load;
δP(n,t): penalty price generated at the nth transaction t moment or calling cost price brought by calling the controllable load;
δQ(n,t): punishment electric quantity generated at the nth transaction t moment or total electric quantity of calling cost brought by calling the controllable load;
q: one-dimensional variables, impact factors; t: the current time.
According to the load curve of the power consumer and the operation characteristics of the equipment, the upper limit of the electric quantity participating in each type of transaction can be obtained, the price of each type of transaction and the generated risk or calling cost are predicted, so that the maximum value of the electricity selling income C and the corresponding Q can be solved by utilizing an algorithm of solving the maximum value by mathematicsnAnd δ QnAnd forming various transaction load curves with the load curve of the time t.
And checking the formed various transaction load curves, judging whether the transaction load curves meet the production requirements and the constraint of equipment operation, and solving a smaller maximum value until the transaction load curves pass the checking if the transaction load curves do not pass the checking.
And the electricity purchasing scheme output module is used for outputting the electricity purchasing scheme which passes the checking, and the electricity purchasing scheme comprises the maximum income of electricity selling, various transaction load curves, a risk deviation electric quantity curve and a load calling scheme.
Fig. 1 is a schematic flow chart of an aid decision-making system for maximizing revenue when an electric power consumer participates in an electricity selling market according to an embodiment of the present invention. As shown in fig. 1, the aid decision method for realizing profit maximization by participating in electricity selling market of power consumers includes the following steps:
the method comprises the following steps: the relevant information is acquired through the information acquisition module, the acquisition mode comprises the direct acquisition from other external systems and the acquisition mode comprises the acquisition through manual input, and the relevant information comprises the following steps:
(1) acquiring local transaction policy and rule information: the method comprises the steps of transaction time, transaction price or price limit, transaction electric quantity or power limit, transaction risk undertaking rules such as electric energy market deviation assessment and the like;
(2) obtaining market information; the system comprises historical transaction data, power grid architecture information, power plant information and the like;
(3) acquiring power consumer information: the system comprises a historical load curve, power consumption requirements, a production and maintenance plan, a working day type, meteorological factors, power consumption equipment information, equipment adjustment and operation parameter information of controllable loads and the like.
The controllable load means that a power user has a distributed power supply, an energy storage facility and adjustable power utilization equipment (including the adjustment of a production plan) to change the load characteristics, and can participate in power selling market transactions such as power selling deviation regulation and control, demand side response, reactive power compensation, frequency modulation and the like.
Step two: the information analysis and classification module analyzes and classifies the information acquired in the step one and stores the information in different units according to different categories:
some information acquired by the information acquisition module can be directly applied to the information analysis and classification module, and some information such as a user load curve, a spot transaction price and the like can be applied after processing, at the moment, the information acquisition module is input into the existing technology or a load prediction system and a price prediction system on the market to complete the prediction of the load of the power user, the power transaction price which does not clearly stipulate the transaction price is predicted, the information processed by the load prediction system and the price prediction system is input into the information analysis and classification module, and the following types of information are finally formed after the processing of the information analysis and classification module:
(1) a load prediction curve for normal production by a user;
(2) the controllable load prediction curve is a controllable load independent action curve only outside the basis of the load prediction curve in normal production, and the curve can comprise two curves, a controllable load prediction upper limit curve and a controllable load prediction upper limit curve;
(3) predicted or specified prices versus time curves for various types of power transactions;
(4) a relationship curve between risk punishment and electric quantity of various electric power transactions;
(5) and (4) calling a generated extra cost and electric quantity relation curve by the controllable load.
Step three: the profit solving module calculates and solves the information in the information analysis and classification module to obtain the maximum profit: with the gain as the maximum, the objective function:
in the formula:
c: selling electricity earnings;
n: the number of all transaction types, n represents the nth transaction, namely the transaction ordinal number;
: the total electric quantity of the transaction participated in by the nth transaction meets the requirement
QmaxThe maximum electricity consumption of the user is obtained; qn≤
The user participates in the nth transaction and the maximum amount of electricity the equipment can generate;
Tn: the total time that the nth transaction is engaged in the transaction;
P(n,t): transaction price at nth transaction time t;
Q(n,t): the transaction electric quantity at the nth transaction t moment;
δQn: the punished electric quantity generated by the nth transaction or the total electric quantity of calling expense brought by calling the controllable load;
δP(n,t): penalty price generated at the nth transaction t moment or calling cost price brought by calling the controllable load;
δQ(n,t): punishment electric quantity generated at the nth transaction t moment or total electric quantity of calling cost brought by calling the controllable load;
q: one-dimensional variables, impact factors; t: the current time.
According to the load curve of the power consumer and the operation characteristics of the equipment, the electric quantity Q participating in each type of transaction can be obtainednThe upper limit of the total weight of the steel,the price and resulting risk or call cost for each type of transaction are predicted, so using some algorithms for mathematical minimization, the maximum value of C and the corresponding Q can be solvednAnd δ QnAnd forming various transaction load curves with the load curve of time.
And checking the formed various transaction load curves, judging whether the transaction load curves meet the production requirements and the constraint of equipment operation, and solving a smaller maximum value until the transaction load curves pass the checking if the transaction load curves do not pass the checking.
Step four: and the electricity purchase scheme output module outputs and stores the result in the profit solving module:
and outputting the checked electricity purchasing scheme, wherein the checked electricity purchasing scheme comprises the maximum income of electricity selling, various transaction load curves, a risk deviation electric quantity curve and a load calling scheme.
The auxiliary decision making system and the method for realizing the income maximization by the participation of the power users in the power selling market aim at a single power user, and the method is also suitable for a power selling company to make a power selling trading strategy.
The above description is only exemplary of the present disclosure and should not be taken as limiting the disclosure, as any modification, equivalent replacement, or improvement made within the spirit and principle of the present disclosure should be included in the scope of protection of the present disclosure.
Finally, it should be noted that: although the present disclosure has been described in detail with reference to the foregoing embodiments, it will be apparent to those skilled in the art that changes may be made in the embodiments and/or equivalents thereof without departing from the spirit and scope of the disclosure. Any modification, equivalent replacement, improvement and the like made within the spirit and principle of the present disclosure should be included in the protection scope of the present disclosure.
Claims (10)
1. An aid decision-making method for realizing income maximization by participation of power consumers in an electricity selling market is characterized by comprising the following steps:
the method comprises the following steps: acquiring related information;
step two: analyzing and classifying the acquired information, predicting the load of the power consumer, and predicting the electric power transaction price which does not definitely stipulate the transaction price;
step three: solving and checking the maximum electricity selling income;
step four: and outputting and storing the verified maximum electricity selling income.
2. The aid decision-making method for realizing profit maximization when an electric power user participates in an electricity selling market according to claim 1, wherein in the first step, the related information is obtained through an information obtaining module, the obtaining mode includes direct obtaining from outside or manual input, and the related information includes:
(1) acquiring local transaction policy and rule information: the method comprises the steps of transaction time, transaction price or price limit, transaction electric quantity or power limit and transaction risk undertaking rule;
(2) obtaining market information; the system comprises historical transaction data, power grid architecture information and power plant information;
(3) acquiring power consumer information: the system comprises a historical load curve, power consumption requirements, a production and maintenance plan, a working day type, meteorological factors, power consumption equipment information and equipment adjustment and operation parameter information of controllable loads.
3. The aid decision-making method for realizing profit maximization when an electric power consumer participates in an electricity selling market according to claim 1, wherein in the second step, the information analyzing and classifying module is used for analyzing and classifying the related information obtained in the first step, the load prediction of the electric power consumer and the electric power transaction price prediction of the transaction price which is not clearly specified are completed by means of a load prediction system and a price prediction system, and the following information is formed by the information analyzing and classifying module:
(1) a load prediction curve for normal production by a user;
(2) the controllable load prediction curve specifically comprises a controllable load prediction upper limit curve and a controllable load prediction lower limit curve;
(3) predicted or specified prices versus time curves for various types of power transactions;
(4) a relationship curve between risk punishment and electric quantity of various electric power transactions;
(5) and (4) calling a generated extra cost and electric quantity relation curve by the controllable load.
4. The aid decision-making method for realizing profit maximization by enabling power consumers to participate in an electricity selling market according to claim 1, wherein in the third step, a profit solving module is adopted to solve the maximum electricity selling profit, and an objective function is as follows:
in the formula:
c: selling electricity earnings;
n: the number of all transaction types, n represents the nth transaction;
the total electric quantity of the transaction participated in by the nth transaction meets the requirement
QmaxThe maximum electricity consumption of the user is obtained; qnThe maximum electric quantity which can be generated by equipment of the user participating in the nth transaction is not more than or equal to;
Tn: the total time that the nth transaction is engaged in the transaction;
P(n,t): transaction price at nth transaction time t;
Q(n,t): the transaction electric quantity at the nth transaction t moment;
δQn: the punished electric quantity generated by the nth transaction or the total electric quantity of calling expense brought by calling the controllable load;
δP(n,t): penalty price generated at the nth transaction t moment or calling cost price brought by calling the controllable load;
δQ(n,t): punishment electric quantity generated at the nth transaction t moment or total electric quantity of calling cost brought by calling the controllable load;
according to the load curve of the power consumer and the operation characteristics of the equipment, the upper limit of the electric quantity participating in each type of transaction is obtained, the price of each type of transaction and the generated risk or calling cost are predicted, so that the maximum value of the electricity selling income C and the corresponding Q are solved by utilizing an algorithm of solving the maximum value by mathematicsnAnd δ QnAnd forming various transaction load curves with the load curve of the time t, checking the various formed transaction load curves, judging whether the transaction load curves meet the production requirements and the constraint of equipment operation, and solving a smaller maximum value until the transaction load curves pass the checking if the transaction load curves do not pass the checking.
5. The aid decision method for realizing profit maximization when an electric power user participates in an electric power selling market according to claim 1, wherein in the fourth step, the electric power purchasing scheme which is checked is output through the electric power purchasing scheme output module, and the electric power purchasing scheme comprises an electric power selling maximum profit, various transaction load curves, a risk deviation electric quantity curve and a load calling scheme.
6. An aid decision-making system for realizing profit maximization by participation of power consumers in an electricity selling market is characterized by comprising the following modules: the system comprises an information acquisition module, an information analysis and classification module, a profit solving module and an electricity purchasing scheme output module, wherein the information acquisition module is used for acquiring relevant information and sending the relevant information to the information analysis and classification module, the information analysis and classification module is used for completing analysis, classification and prediction to obtain relevant various curve information, the profit solving module is used for obtaining the maximum value of electricity selling profits and various transaction load curves, the maximum value and various transaction load curves are checked, and the electricity purchasing scheme after the check is passed is output through the output module.
7. The aid decision making system for realizing profit maximization of power consumer participating in power selling market according to claim 6, wherein the obtaining manner of the information obtaining module comprises direct obtaining from outside or manual input, and the obtained related information comprises:
(1) acquiring local transaction policy and rule information: the method comprises the steps of transaction time, transaction price or price limit, transaction electric quantity or power limit and transaction risk undertaking rule;
(2) obtaining market information; the system comprises historical transaction data, power grid architecture information and power plant information;
(3) acquiring power consumer information: the system comprises a historical load curve, power consumption requirements, a production and maintenance plan, a working day type, meteorological factors, power consumption equipment information and equipment adjustment and operation parameter information of controllable loads.
8. The decision-making system for assisting the electric power user to participate in the electric power selling market to achieve profit maximization according to claim 6, wherein the information analyzing and classifying module analyzes and classifies the information acquired by the information acquiring module, and for the information which cannot be directly applied to the information analyzing and classifying module, the load predicting system and the price predicting system are used for predicting to complete load prediction of the electric power user and electric power transaction price prediction of transaction prices which are not clearly specified, and finally the following information is formed through the information analyzing and classifying module:
(1) a load prediction curve for normal production by a user;
(2) the controllable load prediction curve specifically comprises a controllable load prediction upper limit curve and a controllable load prediction lower limit curve;
(3) predicted or specified prices versus time curves for various types of power transactions;
(4) a relationship curve between risk punishment and electric quantity of various electric power transactions;
(5) and (4) calling a generated extra cost and electric quantity relation curve by the controllable load.
9. The aid decision making system for realizing profit maximization of power consumer participating in power selling market according to claim 6, wherein the profit solving module aims at profit maximization and has an objective function as follows:
in the formula:
c: selling electricity earnings;
n: the number of all transaction types, n represents the nth transaction;
the total electric quantity of the transaction participated in by the nth transaction meets the requirementQmaxThe maximum electricity consumption of the user is obtained; qnThe maximum electric quantity which can be generated by equipment of the user participating in the nth transaction is not more than or equal to;
Tn: the total time that the nth transaction is engaged in the transaction;
P(n,t): transaction price at nth transaction time t;
Q(n,t): the transaction electric quantity at the nth transaction t moment;
δQn: the punished electric quantity generated by the nth transaction or the total electric quantity of calling expense brought by calling the controllable load;
δP(n,t): penalty price generated at the nth transaction t moment or calling cost price brought by calling the controllable load;
δQ(n,t): punishment electric quantity generated at the nth transaction t moment or total electric quantity of calling cost brought by calling the controllable load;
according to the load curve of the power consumer and the operation characteristics of the equipment, the upper limit of the electric quantity participating in each type of transaction is obtained, the price of each type of transaction and the generated risk or calling cost are predicted, so that the maximum value of the electricity selling income C and the corresponding Q are solved by utilizing an algorithm of solving the maximum value by mathematicsnAnd δ QnAnd forming various transaction load curves with the load curve of the time t, checking the various formed transaction load curves, judging whether the transaction load curves meet the production requirements and the constraint of equipment operation, and solving a smaller maximum value until the transaction load curves pass the checking if the transaction load curves do not pass the checking.
10. The electric power consumer participating in the electricity selling market to realize profit maximization according to claim 6, wherein the electricity purchasing scheme output module is used for outputting the checked electricity purchasing schemes, wherein the electricity purchasing schemes comprise electricity selling maximum profit, various transaction load curves, risk deviation electric quantity curves and load calling schemes.
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| CN111639963A (en) * | 2020-04-30 | 2020-09-08 | 长沙理工大学 | Flexible decision-making method and circuit for electric power service provider controllable load for avoiding penalty of deviation electric quantity |
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| CN111639963A (en) * | 2020-04-30 | 2020-09-08 | 长沙理工大学 | Flexible decision-making method and circuit for electric power service provider controllable load for avoiding penalty of deviation electric quantity |
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| CN111709779A (en) * | 2020-06-01 | 2020-09-25 | 广东电网有限责任公司 | Trading variety optimization system for electric power spot market |
| CN111738854A (en) * | 2020-06-22 | 2020-10-02 | 国能日新科技股份有限公司 | New energy spot transaction decision-making data service system based on cloud computing |
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