CN108122171A - A kind of electric power demand side bidding strategies determine method and system - Google Patents
A kind of electric power demand side bidding strategies determine method and system Download PDFInfo
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Abstract
The present invention relates to a kind of electric power demand side bidding strategies to determine method and system, and this method includes：The cost curve of side load adjustment power determines the cost price of the corresponding adjustment power segmentation of each load data subclass according to demand, and determines the corresponding declared value of load data subclass according to the cost price and profit ratio；The corresponding declared value of load data subclass according to belonging to the load of current demand side using it determines the quotation scheme tender probability function as the history acceptance of the bid number of quotation scheme；Optimal profit ratio is determined according to the tender probability function after optimization；The bidding strategies tender probability higher that technical scheme determines is suitable for the demand of new environment, further promotes the competitiveness of Demand-side resource.
Description
Technical field
The present invention relates to electricity market fields, and in particular to a kind of electric power demand side bidding strategies determine method and system.
Background technology
Electric power demand side is bidded, and is a kind of electric power demand side response modes, and user is encouraged to disappear by changing the electric power of oneself
Expense mode is actively engaged in market competition and obtains a kind of implementation system under corresponding economic interests and Power Market.
Demand-side user is not only needed premised on the various rules of electric system and limitation, seeks number one by reasonably offering
It maximizes；And need to consider the autonomous learning and decision-making capability of quotation strategy, possess it and explore market and become according to market
Change the ability for changing oneself trade decision；How Demand-side user changes the trade decision of itself according to turn of the market at any time, fits
Electricity market new environment is answered, so as to promote the competitiveness under market environment, the problem of being one very important.
Therefore, it is urgent to provide a kind of rational Demand-side bidding strategies to determine method, promotes the competitiveness of Demand-side resource.
The content of the invention
The present invention provides a kind of electric power demand side bidding strategies and determines method and system, and the purpose is to be born according to System History
Lotus data firm offer strategy, and selected according to by the tender probability function after current trading situation and the optimization of contribution to the history of coefficient
Tender probability is taken compared with great number quotation strategy, so that it is guaranteed that success rate of bidding, promotes Demand-side resources competence.
The purpose of the present invention is what is realized using following technical proposals：
A kind of electric power demand side bidding strategies determine method, it is improved in that including：
The cost curve of side load adjustment power determines the corresponding adjustment power segmentation of each load data subclass according to demand
Cost price, and the corresponding declared value of load data subclass is determined according to the cost price and profit ratio；
The corresponding declared value of load data subclass going through as quotation scheme according to belonging to the load of current demand side using it
History acceptance of the bid number determines the quotation scheme tender probability function；
Optimal profit ratio is determined according to the tender probability function.
Preferably, the cost curve of the load adjustment power of side according to demand determines the corresponding tune of each load data subclass
The cost price of whole power segmentation, and determine that load data subclass is corresponding according to the cost price and profit ratio and declare valency
Before lattice, including：
According to preset peak load data sectional classifying to the historical load data of Demand-side, each peak load is determined
The corresponding load data subclass of data sectional.
Further, the dividing to the historical load data of Demand-side according to preset peak load data sectional
Class determines the corresponding load data subclass of each peak load data sectional, including：
If load maximum is in peak load data sectional a in the load data of history day, by the load number of the history day
According to being divided to the corresponding load data subclasses of the peak load data sectional a.
Preferably, the cost curve of the load adjustment power of side according to demand determines the corresponding tune of each load data subclass
The cost price of whole power segmentation, including：
The cost equation of Demand-side load adjustment power is obtained, according to the cost equation of the Demand-side load adjustment power
Obtain the cost curve of Demand-side load adjustment power；
Power P will be adjustedsWith adjusting power PtBetween corresponding slope of a curve as the corresponding tune of each load data subclass
Whole power is segmented (Ps,Pt) cost price, wherein, Ps＜ Pt。
Further, the cost equation of Demand-side load adjustment power is obtained as the following formula：
C (P)=eP+kP2
In formula, C (P) is the cost equation of Demand-side load adjustment power；P is the adjustment power of Demand-side user；E and k
For the Setup Cost coefficient of Demand-side user.
It is preferably, described that the corresponding declared value of load data subclass is determined according to the cost price and profit ratio,
Including：
The corresponding declared value of load data subclass is determined according to the cost price and profit ratio as the following formula：
bst=Kstα
In formula, bst(P is segmented for the corresponding adjustment power of each load data subclasss,Pt) cost price corresponding declare
Price；Kst(P is segmented for the corresponding adjustment power of each load data subclasss,Pt) cost price；α is profit ratio.
Preferably, the corresponding declared value of load data subclass according to belonging to the load of current demand side using it is report
The history acceptance of the bid number of valency scheme determines the quotation scheme tender probability function, including：
The tender probability function of the quotation scheme is determined as the following formula：
In formula, Pi N(Lk,bst) for Demand-side load i in load data subclass LkIt is interior using the declared value as quotation scheme
Initial tender probability, wherein, k takes positive integer, and N is the secondary transaction count that Demand-side load i has been completed in the market；αjFor
Profit ratio, j=1,2L m, m are the total number of setting profit ratio；It is Demand-side load i in load data subclass Δ Lk
It is interior with αjFor the transaction acceptance of the bid number of profit ratio；NiIt is Demand-side load i in load data subclass Δ LkInterior transaction count.
Preferably, it is described optimal profit ratio is determined according to tender probability function before, including：
Utilize current demand side load working as using the corresponding declared value of load data subclass belonging to it as quotation scheme
Preceding acceptance of the bid situation corrects the tender probability function.
Further, it is described using current demand side load using the corresponding declared value of load data subclass belonging to it as
The current acceptance of the bid situation of quotation scheme corrects the tender probability function, including：
The tender probability function is corrected as the following formula：
In formula, Pi N+1(Lk, bst) it is revised tender probability function；Wherein, k takes positive integer, and N is Demand-side load i
The secondary transaction count completed in the market；αjFor profit ratio, j=1,2L m, m are the total number of setting profit ratio；It is Demand-side load i in load data subclass Δ LkIt is interior with αjFor the transaction acceptance of the bid number of profit ratio；NiIt is born for Demand-side
Lotus i is in load data subclass Δ LkInterior transaction count；Q is the market clearing price currently merchandised.
Further, it is described using current demand side load using the corresponding declared value of load data subclass belonging to it as
After the current acceptance of the bid situation of quotation scheme corrects the tender probability function, including：
Optimize revised tender probability function using contribution to the history of coefficient as the following formula：
In formula, Pi N+1'(ΔLk,bst) for optimization after tender probability function；Pi N+1(Lk,bst) get the bid generally to be revised
Rate function；Wherein, k takes positive integer, and N is the secondary transaction count that Demand-side load i has been completed in the market；αjFor profit ratio
Example, j=1,2L m, m are the total number of setting profit ratio；It is Demand-side load i in load data subclass Δ LkIt is interior with αj
For the transaction acceptance of the bid number of profit ratio；NiIt is Demand-side load i in load data subclass Δ LkInterior transaction count；Q is current
The market clearing price of transaction；λ is contribution to the history of coefficient, wherein, 0 ＜ λ ＜ 1.
Preferably, it is described that optimal profit ratio is determined according to tender probability function, including：
The final tender probability is sorted from high to low, chooses the high profit ratio of tender probability as optimal profit
Ratio.
A kind of electric power demand side bidding strategies determine system, which is characterized in that the system comprises：
First determining module, according to demand the cost curve of side load adjustment power determine that each load data subclass is corresponding
The cost price of power segmentation is adjusted, and determines that load data subclass is corresponding according to the cost price and profit ratio and declares
Price；
Second determining module, for according to current demand side load with it belonging to load data subclass corresponding declare valency
Lattice determine the quotation scheme tender probability function for the history acceptance of the bid number of quotation scheme；
3rd determining module, for determining optimal profit ratio according to the tender probability function.
Preferably, the system also includes：Sort module, for according to preset peak load data sectional to Demand-side
Historical load data classify, determine the corresponding load data subclass of each peak load data sectional.
Further, the sort module, is used for：
If load maximum is in peak load data sectional a in the load data of history day, by the load number of the history day
According to being divided to the corresponding load data subclasses of the peak load data sectional a.
Preferably, first determining module includes：Curve acquisition unit, for obtaining Demand-side load adjustment power
Cost equation, the cost that Demand-side load adjustment power is obtained according to the cost equation of the Demand-side load adjustment power are bent
Line；
The cost equation of Demand-side load adjustment power is obtained as the following formula：
C (P)=eP+kP2
In formula, C (P) is the cost equation of Demand-side load adjustment power；P is the adjustment power of Demand-side user；E and k
For the Setup Cost coefficient of Demand-side user.
First determination unit, for power P will to be adjustedsWith adjusting power PtBetween corresponding slope of a curve as each negative
The corresponding adjustment power segmentation (P of lotus data subclasss,Pt) cost price, wherein, Ps＜ Pt；
Second determination unit, is used for：
The corresponding declared value of load data subclass is determined according to cost price and profit ratio as the following formula：
bst=Kstα
In formula, bst(P is segmented for the corresponding adjustment power of each load data subclasss,Pt) cost price corresponding declare
Price；Kst(P is segmented for the corresponding adjustment power of each load data subclasss,Pt) cost price；α is profit ratio.It is preferred that
Ground, second determining module, is used for：
The tender probability function of the quotation scheme is determined as the following formula：
In formula, Pi N(Lk,bst) for Demand-side load i in load data subclass LkIt is interior using the declared value as quotation scheme
Initial tender probability, wherein, k takes positive integer, and N is the secondary transaction count that Demand-side load i has been completed in the market；αjFor
Profit ratio, j=1,2L m, m are the total number of setting profit ratio；It is Demand-side load i in load data subclass Δ Lk
It is interior with αjFor the transaction acceptance of the bid number of profit ratio；NiIt is Demand-side load i in load data subclass Δ LkInterior transaction count.
Preferably, the system also includes：Optimization module, for utilizing Demand-side load in load data subclass with institute
It states the current acceptance of the bid situation that declared value is quotation scheme and corrects the tender probability function.
Further, the optimization module includes：
Amending unit, for as the following formula using the current acceptance of the bid situation according to the amendment tender probability function：
In formula, Pi N+1(Lk,bst) it is revised tender probability function；Wherein, k takes positive integer, and N is Demand-side load i
The secondary transaction count completed in the market；αjFor profit ratio, j=1,2L m, m are the total number of setting profit ratio；It is Demand-side load i in load data subclass Δ LkIt is interior with αjFor the transaction acceptance of the bid number of profit ratio；NiIt is born for Demand-side
Lotus i is in load data subclass Δ LkInterior transaction count；Q is the market clearing price currently merchandised；
Optimize unit, for as the following formula contribution to the history of coefficient being utilized to optimize revised tender probability function：
In formula, Pi N+1'(ΔLk,bst) for optimization after tender probability function；λ is contribution to the history of coefficient, wherein, 0 ＜ λ ＜
1。
Preferably, the 3rd determining module, is used for：
The final tender probability is sorted from high to low, chooses the high profit ratio of tender probability as optimal profit
Ratio.
Compared with prior art, the present invention has the advantages that：
Technical solution provided by the invention, according to demand the cost curve of side load adjustment power determine each load data
The cost price of the corresponding adjustment power segmentation of class；The corresponding declared value of the cost price is determined using profit ratio；Root
The quotation scheme is determined according to acceptance of the bid number of the Demand-side load using the declared value as quotation scheme in load data subclass
Tender probability function；Optimal profit ratio is determined according to the tender probability function after optimization；Current power market is responded
Demand, declared value is determined according to historical load data and profit ratio, and quotation is chosen according to the tender probability after optimization
Strategy, enormously simplifies the complexity of offer decision-making models, not only realizes and is safeguarded on the premise of without prejudice to system convention
The interests of Demand-side, while effectively improve the competitiveness of Demand-side resource.
Description of the drawings
Fig. 1 is the flow chart that a kind of electric power demand side bidding strategies of the present invention determine method；
Fig. 2 is the cost curve schematic diagram of Demand-side load adjustment power in the embodiment of the present invention；
Fig. 3 is the structure diagram that a kind of electric power demand side bidding strategies of the present invention determine system.
Specific embodiment
It elaborates below in conjunction with the accompanying drawings to the specific embodiment of the present invention.
To make the purpose, technical scheme and advantage of the embodiment of the present invention clearer, below in conjunction with the embodiment of the present invention
In attached drawing, the technical solution in the embodiment of the present invention is clearly and completely described, it is clear that described embodiment is
Part of the embodiment of the present invention, instead of all the embodiments.Based on the embodiments of the present invention, those of ordinary skill in the art
The all other embodiment obtained without making creative work, belongs to the scope of protection of the invention.
The present invention provides a kind of electric power demand side bidding strategies to determine method and system, is illustrated below.
Fig. 1 shows that electric power demand side bidding strategies in the embodiment of the present invention determine the flow chart of method, as shown in Figure 1,
The method may include：
101. the cost curve of side load adjustment power determines the corresponding adjustment power of each load data subclass according to demand
The cost price of segmentation, and the corresponding declared value of load data subclass is determined according to the cost price and profit ratio；
102. the corresponding declared value of load data subclass according to belonging to the load of current demand side using it is quotation scheme
History acceptance of the bid number determine the quotation scheme tender probability function；
103. optimal profit ratio is determined according to the tender probability function.
The electric power demand side is bidded (Demand-Side Bidding, DSB), and abbreviation Demand-side is bidded, and refers to encourage to use
Family is actively engaged in market competition by changing oneself electricity consumption mode and obtains corresponding economic interests, is that a kind of electric power needs
Seek a kind of implementation system under side response modes and Power Market.And Demand-side load is as market member, a side
Face on the basis of the various rules of electric system and limitation is considered, seeks number one to maximize by reasonably offering；Separately
On the one hand, it is necessary to consider its autonomous learning and decision-making capability, possess it and explore market and oneself friendship is changed according to turn of the market
The ability of easy decision-making.
Wherein, the cost curve of the load adjustment power of side according to demand determines the corresponding adjustment of each load data subclass
The cost price of power segmentation, and the corresponding declared value of load data subclass is determined according to the cost price and profit ratio
Before, can include：
According to preset peak load data sectional classifying to the historical load data of Demand-side, each peak load is determined
The corresponding load data subclass of data sectional.
Specifically, the classifying to the historical load data of Demand-side according to preset peak load data sectional, really
Determine the corresponding load data subclass of each peak load data sectional, can include：
If load maximum is in peak load data sectional a in the load data of history day, by the load number of the history day
According to being divided to the corresponding load data subclasses of the peak load data sectional a.
Fig. 2 shows that electric power demand side bidding strategies of the embodiment of the present invention determine the Demand-side load adjustment power of method
Cost curve schematic diagram, as shown in Fig. 2, the cost curve of side load adjustment power determines each load data subclass pair according to demand
The cost price for the adjustment power segmentation answered, can include：
The cost equation of Demand-side load adjustment power is obtained, according to the cost equation of the Demand-side load adjustment power
Obtain the cost curve of Demand-side load adjustment power；Piece-wise linearization processing is carried out according to adjustment power to cost curve, is needed
Side load adjustment power divider is sought as P1, tri- sections of P2, P3, each adjustment power is segmented corresponding slope of a curve as each load
The cost price of the corresponding adjustment power segmentation of data subclass；
Specifically, the cost equation of Demand-side load adjustment power is obtained as the following formula：
C (P)=eP+kP2
In formula, C (P) is the cost equation of Demand-side load adjustment power；P is the adjustment power of Demand-side user；E and k
For the Setup Cost coefficient of Demand-side user.
It is specifically, described that the corresponding declared value of load data subclass is determined according to the cost price and profit ratio,
It can include：
The corresponding declared value of load data subclass is determined according to the cost price and profit ratio as the following formula：
bst=Kstα
In formula, bst(P is segmented for the corresponding adjustment power of each load data subclasss,Pt) cost price corresponding declare
Price；Kst(P is segmented for the corresponding adjustment power of each load data subclasss,Pt) cost price；α is profit ratio, for big
For user and load are acted on behalf of, the profit margin of quotation also sets m numerical value (α1, α2... αm), i.e., assumed load has m kinds
Quotation scheme.
Based on said program, according to load data subclass corresponding declared value of the current demand side load belonging to it as
The history acceptance of the bid number of quotation scheme determines the quotation scheme tender probability function, can include：
The tender probability function of the quotation scheme is determined as the following formula：
In formula, Pi N(Lk,bst) for Demand-side load i in load data subclass LkIt is interior using the declared value as quotation scheme
Initial tender probability, wherein, k takes positive integer, and N is the secondary transaction count that Demand-side load i has been completed in the market；αjFor
Profit ratio, j=1,2L m, m are the total number of setting profit ratio；It is Demand-side load i in load data subclass Δ Lk
It is interior with αjFor the transaction acceptance of the bid number of profit ratio；NiIt is Demand-side load i in load data subclass Δ LkInterior transaction count.
After the completion of each transaction, Demand-side load is needed according to newest acceptance of the bid situation, select probability of getting the bid to quotation
It is modified study.There are many kinds of learning methods, can include Bayesian learning method, intensified learning method, statistical method.This literary grace
With a kind of self-adapting strengthened learning model, thinking is similar with learning the statistical method in initial tender probability function, therefore, institute
It states before determining optimal profit ratio according to tender probability function, can include：
Utilize current demand side load working as using the corresponding declared value of load data subclass belonging to it as quotation scheme
Preceding acceptance of the bid situation corrects the tender probability function.
Specifically, it is described using current demand side load using the corresponding declared value of load data subclass belonging to it as report
The current acceptance of the bid situation of valency scheme corrects the tender probability function, can include：
The tender probability function is corrected as the following formula：
In formula, Pi N+1(Lk,bst) it is revised tender probability function；Wherein, k takes positive integer, and N is Demand-side load i
The secondary transaction count completed in the market；αjFor profit ratio, j=1,2L m, m are the total number of setting profit ratio；It is Demand-side load i in load data subclass Δ LkIt is interior with αjFor the transaction acceptance of the bid number of profit ratio；NiIt is born for Demand-side
Lotus i is in load data subclass Δ LkInterior transaction count；Q is the market clearing price currently merchandised；Work as bstDuring≤q, this is represented
Secondary quotation is got the bid not higher than market clear price；Conversely, it does not get the bid then.
In order to which timeliness difference, the Demand-side load marketing effect nearer to the time is presented in more preferable simulation historical data
It is more valuable to predicting.For this purpose, the decreasing effect that contribution to the history of coefficient represents the time is introduced in learning process.Contribution to the history of coefficient
Represent that, often by the unit interval, previous historical quotes acceptance of the bid select probability conviction will be attenuated to λ times.Based on this thought, using working as
Preceding Demand-side load is using the corresponding declared value of load data subclass belonging to it as the current acceptance of the bid situation amendment of quotation scheme
After the tender probability function, it can include：
Optimize revised tender probability function using contribution to the history of coefficient as the following formula：
In formula, Pi N+1'(ΔLk,bst) for optimization after tender probability function；Pi N+1(Lk,bst) get the bid generally to be revised
Rate function；Wherein, k takes positive integer, and N is the secondary transaction count that Demand-side load i has been completed in the market；αjFor profit ratio
Example, j=1,2L m, m are the total number of setting profit ratio；It is Demand-side load i in load data subclass Δ LkIt is interior with αj
For the transaction acceptance of the bid number of profit ratio；NiIt is Demand-side load i in load data subclass Δ LkInterior transaction count；Q is current
The market clearing price of transaction；λ is contribution to the history of coefficient, wherein, 0 ＜ λ ＜ 1；Wherein, quotation acceptance of the bid select probability function
In habit, contribution to the history of coefficient represents that Demand-side load is more conservative more believes historical experience closer to 1；Contribution to the history of coefficient more connects
Nearly 0, then it represents that its profiteering attitude is stronger, more believes newest transaction results.It is therefore contemplated that the certain journey of contribution to the history of coefficient
The learning ability of Demand-side load has been reacted on degree.
Specifically, it is described that optimal profit ratio is determined according to tender probability function, it can include：
The final tender probability is sorted from high to low, chooses the high profit ratio of tender probability as optimal profit
Ratio；
If the same scheme of Bid acceptance probability, average profit is higher in historical data scheme or take may be selected
Random device makes choice.
Fig. 3 shows that electric power demand side bidding strategies of the embodiment of the present invention determine the structure diagram of system, such as Fig. 3 institutes
Show, the system can include：
First determining module, according to demand the cost curve of side load adjustment power determine that each load data subclass is corresponding
The cost price of power segmentation is adjusted, and determines that load data subclass is corresponding according to the cost price and profit ratio and declares
Price；
Second determining module, for according to current demand side load with it belonging to load data subclass corresponding declare valency
Lattice determine the quotation scheme tender probability function for the history acceptance of the bid number of quotation scheme；
3rd determining module, for determining optimal profit ratio according to the tender probability function.
The system can also include：Sort module, for according to preset peak load data sectional to Demand-side
History is born
Lotus data classify, and determine the corresponding load data subclass of each peak load data sectional；
Wherein, the sort module, if for load maximum in the load data of history day in peak load data sectional a
It is interior, then the load data of the history day is divided to the corresponding load data subclasses of the peak load data sectional a.
Specifically, first determining module can include：Curve acquisition unit, for obtaining Demand-side load adjustment work(
The cost equation of rate obtains the cost of Demand-side load adjustment power according to the cost equation of the Demand-side load adjustment power
Curve；
The cost equation of Demand-side load adjustment power is obtained as the following formula：
C (P)=eP+kP2
In formula, C (P) is the cost equation of Demand-side load adjustment power；P is the adjustment power of Demand-side user；E and k
For the Setup Cost coefficient of Demand-side user.
First determination unit, for power P will to be adjustedsWith adjusting power PtBetween corresponding slope of a curve as each negative
The corresponding adjustment power segmentation (P of lotus data subclasss,Pt) cost price, wherein, Ps＜ Pt。
Second determination unit, is used for：Determine that load data subclass is corresponding according to cost price and profit ratio as the following formula
Declared value：
bst=Kstα
In formula, bst(P is segmented for the corresponding adjustment power of each load data subclasss,Pt) cost price corresponding declare
Price；Kst(P is segmented for the corresponding adjustment power of each load data subclasss,Pt) cost price；α is profit ratio；Described
Two determining modules, are specifically used for：The tender probability function of the quotation scheme is determined as the following formula：
In formula, Pi N(Lk,bst) for Demand-side load i in load data subclass LkIt is interior using the declared value as quotation scheme
Initial tender probability, wherein, k takes positive integer, and N is the secondary transaction count that Demand-side load i has been completed in the market；αjFor
Profit ratio, j=1,2L m, m are the total number of setting profit ratio；It is Demand-side load i in load data subclass Δ Lk
It is interior with αjFor the transaction acceptance of the bid number of profit ratio；NiIt is Demand-side load i in load data subclass Δ LkInterior transaction count.
The system can also include：
Optimization module, for utilizing Demand-side load in load data subclass using the declared value as quotation scheme
Current acceptance of the bid situation corrects the tender probability function；
Wherein, the optimization module can include：
Amending unit, for as the following formula using the current acceptance of the bid situation according to the amendment tender probability function：
In formula, Pi N+1(Lk,bst) it is revised tender probability function；Q is the market clearing price currently merchandised；
Optimize unit, for as the following formula contribution to the history of coefficient being utilized to optimize revised tender probability function：
In formula, Pi N+1'(ΔLk,bst) for optimization after tender probability function；λ is contribution to the history of coefficient, wherein, 0 ＜ λ ＜
1。
3rd determining module, is specifically used for：The final tender probability is sorted from high to low, chooses tender probability
High profit ratio is as optimal profit ratio.The present invention considers the horizontal implicit market information of system peak load, market
The multiple influence factors such as supply/demand, market member quotation information and electric network information, and utilized certainly according to newest transaction results
It adapts to intensified learning model to be modified Bid acceptance probability, greatly improves the autonomous learning of Demand-side user and decision-making energy
Power.Meanwhile Bid acceptance probability function statistically implies mass market information, market supply and demand situation, market member report
Valency information and electric network information can greatly simplify the complexity of offer decision-making models using Bid acceptance probability function, believe
Breath open level not high Power Market Construction initial stage has more actual application value.
It should be understood by those skilled in the art that, embodiments herein can be provided as method, system or computer program
Product.Therefore, the reality in terms of complete hardware embodiment, complete software embodiment or combination software and hardware can be used in the application
Apply the form of example.Moreover, the computer for wherein including computer usable program code in one or more can be used in the application
The computer program production that usable storage medium is implemented on (including but not limited to magnetic disk storage, CD-ROM, optical memory etc.)
The form of product.
The application is with reference to the flow according to the method for the embodiment of the present application, equipment (system) and computer program product
Figure and/or block diagram describe.It should be understood that it can be realized by computer program instructions each in flowchart and/or the block diagram
The combination of flow and/or box in flow and/or box and flowchart and/or the block diagram.These computers can be provided
Program instruction is to the processor of all-purpose computer, special purpose computer, Embedded Processor or other programmable data processing devices
To generate a machine so that the instruction performed by computer or the processor of other programmable data processing devices generates use
In the dress for realizing the function of being specified in one flow of flow chart or multiple flows and/or one box of block diagram or multiple boxes
It puts.
These computer program instructions, which may also be stored in, can guide computer or other programmable data processing devices with spy
Determine in the computer-readable memory that mode works so that the instruction generation being stored in the computer-readable memory includes referring to
Make the manufacture of device, the command device realize in one flow of flow chart or multiple flows and/or one box of block diagram or
The function of being specified in multiple boxes.
These computer program instructions can be also loaded into computer or other programmable data processing devices so that counted
Series of operation steps is performed on calculation machine or other programmable devices to generate computer implemented processing, so as in computer or
The instruction offer performed on other programmable devices is used to implement in one flow of flow chart or multiple flows and/or block diagram one
The step of function of being specified in a box or multiple boxes.
Finally it should be noted that：The above embodiments are merely illustrative of the technical scheme of the present invention and are not intended to be limiting thereof, to the greatest extent
Pipe is described in detail the present invention with reference to above-described embodiment, those of ordinary skills in the art should understand that：Still
The specific embodiment of the present invention can be modified or replaced equivalently, and without departing from any of spirit and scope of the invention
Modification or equivalent substitution should all cover within the claims of the present invention.
Claims (19)
1. a kind of electric power demand side bidding strategies determine method, which is characterized in that the described method includes：
According to demand the cost curve of side load adjustment power determine each load data subclass it is corresponding adjustment power segmentation into
This price, and the corresponding declared value of load data subclass is determined according to the cost price and profit ratio；
The corresponding declared value of load data subclass according to belonging to the load of current demand side using it is in the history of quotation scheme
Mark number determines the quotation scheme tender probability function；
Optimal profit ratio is determined according to the tender probability function.
2. the method as described in claim 1, which is characterized in that the cost curve of the load adjustment power of side according to demand is true
Fixed each load data subclass is corresponding to adjust the cost price of power segmentation, and is determined according to the cost price and profit ratio
Before the corresponding declared value of load data subclass, including：
According to preset peak load data sectional classifying to the historical load data of Demand-side, each peak load data are determined
It is segmented corresponding load data subclass.
3. method as claimed in claim 2, which is characterized in that it is described according to preset peak load data sectional to Demand-side
Historical load data classify, determine the corresponding load data subclass of each peak load data sectional, including：
If load maximum is in peak load data sectional a in the load data of history day, the load data of the history day is drawn
Divide to the corresponding load data subclasses of the peak load data sectional a.
4. the method as described in claim 1, which is characterized in that the cost curve of the load adjustment power of side according to demand is true
The corresponding cost price for adjusting power and being segmented of fixed each load data subclass, including：
The cost equation of Demand-side load adjustment power is obtained, is obtained according to the cost equation of the Demand-side load adjustment power
The cost curve of Demand-side load adjustment power；
Power P will be adjustedsWith adjusting power PtBetween corresponding slope of a curve as the corresponding adjustment work(of each load data subclass
Rate is segmented (Ps,Pt) cost price, wherein, Ps＜ Pt。
5. method as claimed in claim 4, which is characterized in that obtain as the following formula Demand-side load adjustment power into we
Journey：
C (P)=eP+kP2
In formula, C (P) is the cost equation of Demand-side load adjustment power；P is the adjustment power of Demand-side user；E and k is to need
Seek the Setup Cost coefficient of side user.
6. the method as described in claim 1, which is characterized in that described that load is determined according to the cost price and profit ratio
The corresponding declared value of data subclass, including：
The corresponding declared value of load data subclass is determined according to the cost price and profit ratio as the following formula：
bst=Kstα
In formula, bst(P is segmented for the corresponding adjustment power of each load data subclasss,Pt) the corresponding declared value of cost price；
Kst(P is segmented for the corresponding adjustment power of each load data subclasss,Pt) cost price；α is profit ratio.
7. the method as described in claim 1, which is characterized in that the load number according to belonging to the load of current demand side with it
According to the corresponding declared value of subclass the quotation scheme tender probability function is determined for the history acceptance of the bid number of quotation scheme, including：
The tender probability function of the quotation scheme is determined as the following formula：
<mrow>
<msubsup>
<mi>P</mi>
<mi>i</mi>
<mi>N</mi>
</msubsup>
<mrow>
<mo>(</mo>
<msub>
<mi>L</mi>
<mi>k</mi>
</msub>
<mo>,</mo>
<msub>
<mi>b</mi>
<mrow>
<mi>s</mi>
<mi>t</mi>
</mrow>
</msub>
<mo>)</mo>
</mrow>
<mo>=</mo>
<mfrac>
<msub>
<mi>N</mi>
<msub>
<mi>&alpha;</mi>
<mi>j</mi>
</msub>
</msub>
<msub>
<mi>N</mi>
<mi>i</mi>
</msub>
</mfrac>
</mrow>
In formula, Pi N(Lk,bst) for Demand-side load i in load data subclass LkIt is interior using the declared value as quotation scheme just
Beginning tender probability, wherein, k takes positive integer, and N is the secondary transaction count that Demand-side load i has been completed in the market；αjFor profit
Ratio, j=1,2 ... m, m are the total number of setting profit ratio；It is Demand-side load i in load data subclass Δ LkIt is interior with
αjFor the transaction acceptance of the bid number of profit ratio；NiIt is Demand-side load i in load data subclass Δ LkInterior transaction count.
8. the method as described in claim 1, which is characterized in that it is described according to tender probability function determine optimal profit ratio it
Before, including：
Using current demand side load using the corresponding declared value of load data subclass belonging to it as quotation scheme it is current in
Mark situation corrects the tender probability function.
9. method as claimed in claim 8, which is characterized in that it is described using current demand side load with the load number belonging to it
The tender probability function is corrected for the current acceptance of the bid situation of quotation scheme according to the corresponding declared value of subclass, including：
The tender probability function is corrected as the following formula：
<mrow>
<msubsup>
<mi>P</mi>
<mi>i</mi>
<mrow>
<mi>N</mi>
<mo>+</mo>
<mn>1</mn>
</mrow>
</msubsup>
<mrow>
<mo>(</mo>
<msub>
<mi>L</mi>
<mi>k</mi>
</msub>
<mo>,</mo>
<msub>
<mi>b</mi>
<mrow>
<mi>s</mi>
<mi>t</mi>
</mrow>
</msub>
<mo>)</mo>
</mrow>
<mo>=</mo>
<mfenced open = "{" close = "">
<mtable>
<mtr>
<mtd>
<mrow>
<mfrac>
<mrow>
<msub>
<mi>N</mi>
<msub>
<mi>&alpha;</mi>
<mi>j</mi>
</msub>
</msub>
<mo>+</mo>
<mn>1</mn>
</mrow>
<mrow>
<msub>
<mi>N</mi>
<mi>i</mi>
</msub>
<mo>+</mo>
<mn>1</mn>
</mrow>
</mfrac>
<mo>,</mo>
<msub>
<mi>b</mi>
<mrow>
<mi>s</mi>
<mi>t</mi>
</mrow>
</msub>
<mo>&le;</mo>
<mi>q</mi>
</mrow>
</mtd>
</mtr>
<mtr>
<mtd>
<mrow>
<mfrac>
<msub>
<mi>N</mi>
<msub>
<mi>&alpha;</mi>
<mi>j</mi>
</msub>
</msub>
<mrow>
<msub>
<mi>N</mi>
<mi>i</mi>
</msub>
<mo>+</mo>
<mn>1</mn>
</mrow>
</mfrac>
<mo>,</mo>
<msub>
<mi>b</mi>
<mrow>
<mi>s</mi>
<mi>t</mi>
</mrow>
</msub>
<mo>></mo>
<mi>q</mi>
</mrow>
</mtd>
</mtr>
</mtable>
</mfenced>
</mrow>
In formula, Pi N+1(Lk,bst) it is revised tender probability function；Wherein, k takes positive integer, and N is Demand-side load i in market
In the secondary transaction count completed；αjFor profit ratio, j=1,2 ... m, m are the total number of setting profit ratio；To need
Side load i is sought in load data subclass Δ LkIt is interior with αjFor the transaction acceptance of the bid number of profit ratio；NiIt is that Demand-side load i is being born
Lotus data subclass Δ LkInterior transaction count；Q is the market clearing price currently merchandised.
10. method as claimed in claim 8, which is characterized in that it is described using current demand side load with the load belonging to it
After the corresponding declared value of data subclass corrects the tender probability function for the current acceptance of the bid situation of quotation scheme, including：
Optimize revised tender probability function using contribution to the history of coefficient as the following formula：
<mrow>
<msubsup>
<mi>P</mi>
<mi>i</mi>
<mrow>
<mi>N</mi>
<mo>+</mo>
<mn>1</mn>
</mrow>
</msubsup>
<msup>
<mrow>
<mo>(</mo>
<msub>
<mi>L</mi>
<mi>k</mi>
</msub>
<mo>,</mo>
<msub>
<mi>b</mi>
<mrow>
<mi>s</mi>
<mi>t</mi>
</mrow>
</msub>
<mo>)</mo>
</mrow>
<mo>&prime;</mo>
</msup>
<mo>=</mo>
<mfenced open = "{" close = "">
<mtable>
<mtr>
<mtd>
<mrow>
<mi>&lambda;</mi>
<mo>&CenterDot;</mo>
<msubsup>
<mi>P</mi>
<mi>i</mi>
<mrow>
<mi>N</mi>
<mo>+</mo>
<mn>1</mn>
</mrow>
</msubsup>
<mrow>
<mo>(</mo>
<msub>
<mi>L</mi>
<mi>k</mi>
</msub>
<mo>,</mo>
<msub>
<mi>b</mi>
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<mi>s</mi>
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</mrow>
</msub>
<mo>)</mo>
</mrow>
<mo>+</mo>
<mrow>
<mo>(</mo>
<mn>1</mn>
<mo>-</mo>
<mi>&lambda;</mi>
<mo>)</mo>
</mrow>
<mo>,</mo>
<msub>
<mi>b</mi>
<mrow>
<mi>s</mi>
<mi>t</mi>
</mrow>
</msub>
<mo>&le;</mo>
<mi>q</mi>
</mrow>
</mtd>
</mtr>
<mtr>
<mtd>
<mrow>
<mi>&lambda;</mi>
<mo>&CenterDot;</mo>
<msubsup>
<mi>P</mi>
<mi>i</mi>
<mrow>
<mi>N</mi>
<mo>+</mo>
<mn>1</mn>
</mrow>
</msubsup>
<mrow>
<mo>(</mo>
<msub>
<mi>L</mi>
<mi>k</mi>
</msub>
<mo>,</mo>
<msub>
<mi>b</mi>
<mrow>
<mi>s</mi>
<mi>t</mi>
</mrow>
</msub>
<mo>)</mo>
</mrow>
<mo>,</mo>
<msub>
<mi>b</mi>
<mrow>
<mi>s</mi>
<mi>t</mi>
</mrow>
</msub>
<mo>></mo>
<mi>q</mi>
</mrow>
</mtd>
</mtr>
</mtable>
</mfenced>
</mrow>
In formula, Pi N+1'(ΔLk,bst) for optimization after tender probability function；Pi N+1(Lk,bst) it is revised tender probability letter
Number；Wherein, k takes positive integer, and N is the secondary transaction count that Demand-side load i has been completed in the market；αjFor profit ratio, j=
1,2 ... m, m are the total number of setting profit ratio；It is Demand-side load i in load data subclass Δ LkIt is interior with αjFor profit
The transaction acceptance of the bid number of ratio；NiIt is Demand-side load i in load data subclass Δ LkInterior transaction count；Q currently merchandises
Market clearing price, λ are contribution to the history of coefficient, wherein, 0 ＜ λ ＜ 1.
11. the method as described in claim 1, which is characterized in that it is described that optimal profit ratio is determined according to tender probability function,
Including：
The final tender probability is sorted from high to low, chooses the high profit ratio of tender probability as optimal profit ratio
Example.
12. a kind of electric power demand side bidding strategies determine system, which is characterized in that the system comprises：
First determining module, according to demand the cost curve of side load adjustment power determine the corresponding adjustment of each load data subclass
The cost price of power segmentation, and determine that load data subclass is corresponding according to the cost price and profit ratio and declare valency
Lattice；
Second determining module, for according to load data subclass corresponding declared value of the current demand side load belonging to it as
The history acceptance of the bid number of quotation scheme determines the quotation scheme tender probability function；
3rd determining module, for determining optimal profit ratio according to the tender probability function.
13. system as claimed in claim 12, which is characterized in that the system also includes：
Sort module, for the classifying to the historical load data of Demand-side according to preset peak load data sectional,
Determine the corresponding load data subclass of each peak load data sectional.
14. system as claimed in claim 13, which is characterized in that the sort module is used for：
If load maximum is in peak load data sectional a in the load data of history day, the load data of the history day is drawn
Divide to the corresponding load data subclasses of the peak load data sectional a.
15. system as claimed in claim 12, which is characterized in that first determining module includes：Curve acquisition unit is used
In the cost equation for obtaining Demand-side load adjustment power, need are obtained according to the cost equation of the Demand-side load adjustment power
Seek the cost curve of side load adjustment power；
The cost equation of Demand-side load adjustment power is obtained as the following formula：
C (P)=eP+kP2
In formula, C (P) is the cost equation of Demand-side load adjustment power；P is the adjustment power of Demand-side user；E and k is to need
Seek the Setup Cost coefficient of side user.
First determination unit, for power P will to be adjustedsWith adjusting power PtBetween corresponding slope of a curve as each load number
According to the corresponding adjustment power segmentation (P of subclasss,Pt) cost price, wherein, Ps＜ Pt；
Second determination unit, is used for：
The corresponding declared value of load data subclass is determined according to cost price and profit ratio as the following formula：
bst=Kstα
In formula, bst(P is segmented for the corresponding adjustment power of each load data subclasss,Pt) the corresponding declared value of cost price；
Kst(P is segmented for the corresponding adjustment power of each load data subclasss,Pt) cost price；α is profit ratio.
16. system as claimed in claim 12, which is characterized in that second determining module is used for：
The tender probability function of the quotation scheme is determined as the following formula：
<mrow>
<msubsup>
<mi>P</mi>
<mi>i</mi>
<mi>N</mi>
</msubsup>
<mrow>
<mo>(</mo>
<msub>
<mi>L</mi>
<mi>k</mi>
</msub>
<mo>,</mo>
<msub>
<mi>b</mi>
<mrow>
<mi>s</mi>
<mi>t</mi>
</mrow>
</msub>
<mo>)</mo>
</mrow>
<mo>=</mo>
<mfrac>
<msub>
<mi>N</mi>
<msub>
<mi>&alpha;</mi>
<mi>j</mi>
</msub>
</msub>
<msub>
<mi>N</mi>
<mi>i</mi>
</msub>
</mfrac>
</mrow>
In formula, Pi N(Lk,bst) for Demand-side load i in load data subclass LkIt is interior using the declared value as quotation scheme just
Beginning tender probability, wherein, k takes positive integer, and N is the secondary transaction count that Demand-side load i has been completed in the market；αjFor profit
Ratio, j=1,2 ... m, m are the total number of setting profit ratio；It is Demand-side load i in load data subclass Δ LkIt is interior with
αjFor the transaction acceptance of the bid number of profit ratio；NiIt is Demand-side load i in load data subclass Δ LkInterior transaction count.
17. system as claimed in claim 12, which is characterized in that the system also includes：
Optimization module, for utilizing Demand-side load in load data subclass using the declared value as the current of quotation scheme
Acceptance of the bid situation corrects the tender probability function.
18. system as claimed in claim 17, which is characterized in that the optimization module includes：
Amending unit, for as the following formula using the current acceptance of the bid situation according to the amendment tender probability function：
<mrow>
<msubsup>
<mi>P</mi>
<mi>i</mi>
<mrow>
<mi>N</mi>
<mo>+</mo>
<mn>1</mn>
</mrow>
</msubsup>
<mrow>
<mo>(</mo>
<msub>
<mi>L</mi>
<mi>k</mi>
</msub>
<mo>,</mo>
<msub>
<mi>b</mi>
<mrow>
<mi>s</mi>
<mi>t</mi>
</mrow>
</msub>
<mo>)</mo>
</mrow>
<mo>=</mo>
<mfenced open = "{" close = "">
<mtable>
<mtr>
<mtd>
<mrow>
<mfrac>
<mrow>
<msub>
<mi>N</mi>
<msub>
<mi>&alpha;</mi>
<mi>j</mi>
</msub>
</msub>
<mo>+</mo>
<mn>1</mn>
</mrow>
<mrow>
<msub>
<mi>N</mi>
<mi>i</mi>
</msub>
<mo>+</mo>
<mn>1</mn>
</mrow>
</mfrac>
<mo>,</mo>
<msub>
<mi>b</mi>
<mrow>
<mi>s</mi>
<mi>t</mi>
</mrow>
</msub>
<mo>&le;</mo>
<mi>q</mi>
</mrow>
</mtd>
</mtr>
<mtr>
<mtd>
<mrow>
<mfrac>
<msub>
<mi>N</mi>
<msub>
<mi>&alpha;</mi>
<mi>j</mi>
</msub>
</msub>
<mrow>
<msub>
<mi>N</mi>
<mi>i</mi>
</msub>
<mo>+</mo>
<mn>1</mn>
</mrow>
</mfrac>
<mo>,</mo>
<msub>
<mi>b</mi>
<mrow>
<mi>s</mi>
<mi>t</mi>
</mrow>
</msub>
<mo>></mo>
<mi>q</mi>
</mrow>
</mtd>
</mtr>
</mtable>
</mfenced>
</mrow>
In formula, Pi N+1(Lk,bst) it is revised tender probability function；Wherein, k takes positive integer, and N is Demand-side load i in market
In the secondary transaction count completed；αjFor profit ratio, j=1,2 ... m, m are the total number of setting profit ratio；To need
Side load i is sought in load data subclass Δ LkIt is interior with αjFor the transaction acceptance of the bid number of profit ratio；NiIt is that Demand-side load i is being born
Lotus data subclass Δ LkInterior transaction count；Q is the market clearing price currently merchandised；
Optimize unit, for as the following formula contribution to the history of coefficient being utilized to optimize revised tender probability function：
<mrow>
<msubsup>
<mi>P</mi>
<mi>i</mi>
<mrow>
<mi>N</mi>
<mo>+</mo>
<mn>1</mn>
</mrow>
</msubsup>
<msup>
<mrow>
<mo>(</mo>
<msub>
<mi>L</mi>
<mi>k</mi>
</msub>
<mo>,</mo>
<msub>
<mi>b</mi>
<mrow>
<mi>s</mi>
<mi>t</mi>
</mrow>
</msub>
<mo>)</mo>
</mrow>
<mo>&prime;</mo>
</msup>
<mo>=</mo>
<mfenced open = "{" close = "">
<mtable>
<mtr>
<mtd>
<mrow>
<mi>&lambda;</mi>
<mo>&CenterDot;</mo>
<msubsup>
<mi>P</mi>
<mi>i</mi>
<mrow>
<mi>N</mi>
<mo>+</mo>
<mn>1</mn>
</mrow>
</msubsup>
<mrow>
<mo>(</mo>
<msub>
<mi>L</mi>
<mi>k</mi>
</msub>
<mo>,</mo>
<msub>
<mi>b</mi>
<mrow>
<mi>s</mi>
<mi>t</mi>
</mrow>
</msub>
<mo>)</mo>
</mrow>
<mo>+</mo>
<mrow>
<mo>(</mo>
<mn>1</mn>
<mo>-</mo>
<mi>&lambda;</mi>
<mo>)</mo>
</mrow>
<mo>,</mo>
<msub>
<mi>b</mi>
<mrow>
<mi>s</mi>
<mi>t</mi>
</mrow>
</msub>
<mo>&le;</mo>
<mi>q</mi>
</mrow>
</mtd>
</mtr>
<mtr>
<mtd>
<mrow>
<mi>&lambda;</mi>
<mo>&CenterDot;</mo>
<msubsup>
<mi>P</mi>
<mi>i</mi>
<mrow>
<mi>N</mi>
<mo>+</mo>
<mn>1</mn>
</mrow>
</msubsup>
<mrow>
<mo>(</mo>
<msub>
<mi>L</mi>
<mi>k</mi>
</msub>
<mo>,</mo>
<msub>
<mi>b</mi>
<mrow>
<mi>s</mi>
<mi>t</mi>
</mrow>
</msub>
<mo>)</mo>
</mrow>
<mo>,</mo>
<msub>
<mi>b</mi>
<mrow>
<mi>s</mi>
<mi>t</mi>
</mrow>
</msub>
<mo>></mo>
<mi>q</mi>
</mrow>
</mtd>
</mtr>
</mtable>
</mfenced>
</mrow>
In formula, Pi N+1'(ΔLk,bst) for optimization after tender probability function；λ is contribution to the history of coefficient, wherein, 0 ＜ λ ＜ 1.
19. system as claimed in claim 12, which is characterized in that the 3rd determining module is used for：
The final tender probability is sorted from high to low, chooses the high profit ratio of tender probability as optimal profit ratio
Example.
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| CN109034445A (en) * | 2018-06-08 | 2018-12-18 | 广东红海湾发电有限公司 | A kind of market-oriented electric power management system and method |
| CN112907290A (en) * | 2021-03-04 | 2021-06-04 | 上海泰豪迈能能源科技有限公司 | Data processing method, device, equipment and storage medium |
| CN112907290B (en) * | 2021-03-04 | 2022-12-27 | 上海泰豪迈能能源科技有限公司 | Data processing method, device, equipment and storage medium |
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