CN108805621A - Price competing method containing micro-capacitance sensor, device and electronic device based on Nash Game opinion - Google Patents
Price competing method containing micro-capacitance sensor, device and electronic device based on Nash Game opinion Download PDFInfo
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Abstract
The present invention proposes a kind of price competing method containing micro-capacitance sensor discussed based on Nash Game, device and electronic device, the method is the thinking based on markon, cost of electricity-generating is divided into two parts, a part is the estimation of markon dynamic regulation coefficient, another part is the estimation to cost of electricity-generating, by the two in conjunction with the cost of rival is estimated, the result that the present invention estimates is more reasonable, reduces estimation error；The problem of present invention can regard original cost information asymmetry problem as Complete Information, can be solved using static game of complete information (Nash Game) method；Present invention reduces estimation errors, reduce cost, reduce the work period, greatly improve work efficiency.
Description
Technical field
The present invention relates to micro-capacitance sensor technical fields, more particularly to price competing method containing micro-capacitance sensor, dress based on Nash Game opinion
It sets and electronic device.
Background technology
Bidding Mechanism is the hot and difficult issue studied at present between micro-capacitance sensor, mainly due to information asymmetry, it is difficult to obtain
The cost information that rival determines is obtained, can only be the cost for estimating rival, general method of estimation is according to history number
According to being fitted to estimate the cost of rival, but the shortcomings that this mode is that error is larger.
Invention content
The present invention proposes a kind of price competing method containing micro-capacitance sensor discussed based on Nash Game, enables to estimation result more
Rationally, estimation error is reduced.
The technical proposal of the invention is realized in this way：
A kind of price competing method containing micro-capacitance sensor based on Nash Game opinion, the multiagent of participation include n independent micro- electricity
Network operation business, micro-capacitance sensor power market transaction center, distribution network operation business, described method includes following steps：
S1：Cost estimate of a certain specific micro-capacitance sensor to other micro-capacitance sensors, specifically includes：
S101：The basic data based on prediction data is generated according to the prediction data of load, photovoltaic and wind turbine, to be formed
Electricity needs；
S102：It determines the cost structure function, decision variable, cost dynamic Dynamic gene of a certain specific micro-capacitance sensor, is formed
Consider that dynamic adjusts the micro-capacitance sensor cost function of profit, the cost structure functional form of rival is identical, and cost coefficient is not
Together；
S103：Specific micro-capacitance sensor 0 estimates the cost structure of its rival using historical data, mainly pair
The cost distribution and the distribution of dynamic cost Dynamic gene of rival estimate, to build the expectation of rival at
This function；
S104：Markon is carried out to the expected cost function of rival using the thinking of step S102, obtains cost
Addition function；
S2：Form the bidding strategies of micro-capacitance sensor main body；
S201：It is expected addition function using the cost of price, output and micro-capacitance sensor, establishes each micro-capacitance sensor operator
Profit function；
S202：Build the Bidding Mechanism and Competitive Bidding Model between micro-capacitance sensor, and solving system gross capability and each micro-capacitance sensor
It is optimal to bid；
S203：According to the principle of unified clearing price, by it is all participate in the micro-capacitance sensor main body bidded quotation according to from as low as
Height sequence, highest quotation is the final cleaing price of electricity market, and the profit of each micro-capacitance sensor is determined based on the price.
Further technical solution, the basic data in the step S101 is respectively by the output of load, photovoltaic and wind turbine
It is determined, is embodied as with coefficient：Wherein φ0For the output of micro-capacitance sensor 0, C (φ0) it is micro-
The production cost of power grid 0, a, b, c are cost coefficient, and a, b indicate that the secondary and cost constant coefficient contributed, c indicate respectively
The fixed cost of micro-capacitance sensor power generation；On cost addition principle, the 0 markon letter of specific micro-capacitance sensor in the step S102
Number isWherein C is cost of electricity-generating, and θ is cost dynamic Dynamic gene, θ and electric power city
The Supply and Demand of field is related, when supply is less than demand, θ<1, otherwise θ>1.
The cost structure function of further technical solution, the rival is：
Wherein i is micro-capacitance sensor i (i=0,1 ..., n-1)；To the cost of rival by the historical data described in step S101 into
Row estimation；The cost expectation function of micro-capacitance sensor i isWherein hi,riMicro-capacitance sensor i is indicated respectively
Cost of electricity-generating type and dynamic cost Dynamic gene number of types,Indicate that micro-capacitance sensor i existsIt is corresponding when cost type
Probability, m=1 ..., hiAnd
The derivation of further technical solution, the cost expectation function of micro-capacitance sensor i is：
Assuming that micro-capacitance sensor i has hiThe different type of kind corresponds to different cost of electricity-generating functions, similarly, dynamic cost tune
There is also r for integral divisoriKind different types, equally also correspond to different probability, cost of electricity-generating and markon dynamic adjust because
It is independent from each other between son, then can obtain the cost of electricity-generating C of micro-capacitance sensor iiProbability distribution and markon dynamic Dynamic gene
θiProbability distribution be respectivelyWithWherein m=1,2 ... hiAnd And
At this point, micro-capacitance sensor 0 can face numerous micro-capacitance sensor competitions with uncertain cost dynamic Dynamic gene, add up toAccording to probability theory knowledge it is found that due to their probability distribution independence, can proper micro-capacitance sensor i cost of electricity-generating
CiProbability distribution beWith cost dynamic Dynamic gene θiProbability distribution beWhen, the probability of cost of electricity-generating function can
By formulaIt is calculated, i.e.,
Further technical solution, in the step S102, consider the micro-capacitance sensor i after cost dynamic Dynamic gene at
This expectation addition function is：I.e.Wherein τiFor the dynamic of expected cost
State Dynamic gene.
Further technical solution, the step S201-S202 are specially：
S201：The method of Bidding Mechanism between structure micro-capacitance sensor operator is it is expected addition according to the cost of micro-capacitance sensor
Function, the profit function of the cost calculation micro-capacitance sensor is subtracted using sales volume, and profit function is：
Wherein η indicates the price at electricity transaction moment, η>0；τiIndicate the dynamic adjustment proportional factor of the expected cost of micro-capacitance sensor i；
S202：The uniform output of each micro-capacitance sensor is obtained using static game of complete information theory and is bidded；According to profit
Function formula can obtain corresponding result using first derivativeWithIt is micro-
Power grid trade center predicts that the electric load situation at the moment can be obtained according to demand, so that it is determined that all micro-capacitance sensors of bidding
Gross capability situation be：φ thereinbIndicate the electricity that power grid trade center is bought to external bulk power grid
Amount；
FormulaThe desired value of the marginal cost price of micro-capacitance sensor 0 can be obtainedSimultaneous formulaπ(φi)=η φi-CiWithIt can must estimate micro-capacitance sensor 0
Rival it is expected bid rules beByIt can estimate micro- electricity
The expectation of 0 rival of net is priced atHighest quotation is the final cleaing price of electricity market, Gu Shi
Cleaing price is
A kind of bidding device containing micro-capacitance sensor based on Nash Game opinion, including：
Cost estimation module is specifically included for the cost estimate according to a certain specific micro-capacitance sensor to other micro-capacitance sensors：
Basic data module, for generating the basis based on prediction data according to the prediction data of load, photovoltaic and wind turbine
Data；
Rival's cost structure function module, for determining that the cost structure function of a certain specific micro-capacitance sensor, decision become
Amount, cost dynamic Dynamic gene form the micro-capacitance sensor cost function for considering that dynamic adjusts profit, the cost structure of rival
Functional form is identical, and cost coefficient is different；
The expected cost function module of rival, for specific micro-capacitance sensor 0 using historical data to its rival's
Cost structure is estimated, mainly estimates the distribution of the cost of rival and the distribution of dynamic cost Dynamic gene,
To build the expected cost function of rival；
Rival's markon function module carries out markon for the expected cost function to rival, obtains
Obtain markon function；
Flow measurement of bidding forms module, is used to form the bidding strategies of micro-capacitance sensor main body, specifically includes；
Profit function module is established each micro- for it is expected addition function using the cost of price, output and micro-capacitance sensor
The profit function of grid operator；
Optimal module of bidding, for building Bidding Mechanism and Competitive Bidding Model between micro-capacitance sensor, and solving system gross capability
Optimal with each micro-capacitance sensor is bidded；
Bid module, for the principle according to unified clearing price, by it is all participate in the micro-capacitance sensor main body bidded quotation by
According to sorting from low to high, highest quotation is the final cleaing price of electricity market, and the profit of each micro-capacitance sensor is determined based on the price
Profit.
A kind of electronic device, including：Processor；Memory：Storage is for processor control operation as described above
Instruction.
The beneficial effects of the invention are as follows：The present invention is based on the thinking of markon, cost of electricity-generating is divided into two parts, one
Part is the estimation of markon dynamic regulation coefficient, and another part is the estimation to cost of electricity-generating, by the two in conjunction with estimating
Count the cost of rival so that the result estimated is more reasonable；After handling in this way, originally cost information asymmetry is asked
The problem of topic can regard Complete Information as, so that it may to be solved using static game of complete information (Nash Game) method；
Present invention reduces estimation errors, reduce cost, reduce the work period, greatly improve work efficiency.
Parameter declaration
I micro-capacitance sensors i (i=0,1 ..., n-1)；
C cost of electricity-generatings；
φiThe output of micro-capacitance sensor i；
θiThe markon dynamic Dynamic gene of micro-capacitance sensor i；
A, b indicate the secondary and cost constant coefficient contributed respectively；
The fixed cost of c micro-capacitance sensors power generation；
πiIndicate the profit of micro-capacitance sensor agent i；
The price at η electricity transaction moment, η>0；
hi,riThe cost of electricity-generating type and dynamic cost Dynamic gene number of types of micro-capacitance sensor i are indicated respectively；
Indicate that micro-capacitance sensor i existsCorresponding probability, m=1 ..., h when cost typeiAnd
Indicate that micro-capacitance sensor i existsCorresponding probability, l=1 ..., r when the type of dynamic cost Dynamic geneiAnd
τiIndicate the dynamic adjustment proportional factor of the expected cost of micro-capacitance sensor i；
Specific implementation mode
The technical scheme in the embodiments of the invention will be clearly and completely described below, it is clear that described reality
It is only a part of the embodiment of the present invention to apply example, instead of all the embodiments.Based on the embodiments of the present invention, this field
The every other embodiment that those of ordinary skill is obtained without making creative work, belongs to guarantor of the present invention
The range of shield.
Containing micro-capacitance sensor price competing method proposed by the present invention based on Nash Game opinion, the multiagent of participation include that n solely
Vertical micro-capacitance sensor operator, micro-capacitance sensor power market transaction center, distribution network operation business, described method includes following steps：
S1：Cost estimate of a certain specific micro-capacitance sensor to other micro-capacitance sensors, specifically includes：
S101：The basic data based on prediction data is generated according to the prediction data of load, photovoltaic and wind turbine, to be formed
Electricity needs；
S102：It determines the cost structure function, decision variable, cost dynamic Dynamic gene of a certain specific micro-capacitance sensor, is formed
Consider that dynamic adjusts the micro-capacitance sensor cost function of profit, the cost structure functional form of rival is identical, and cost coefficient is not
Together；
S103：Specific micro-capacitance sensor 0 estimates the cost structure of its rival using historical data；Mainly pair
The cost distribution and the distribution of dynamic cost Dynamic gene of rival estimate, to build the expectation of rival at
This function；Historical data therein can be acquired from electricity market, and specific micro-capacitance sensor 0 can obtain other according to historical data
Bid micro-capacitance sensor how many plant possible type, each type corresponds to a cost, micro-capacitance sensor 0 can according to historical data come
Estimate the probability distribution of rival, the effect of historical data is to obtain the probability distribution of the various cost types of rival,
The probability distribution of cost dynamic Dynamic gene is obtained simultaneously；
S104：Markon is carried out to the expected cost function of rival using the thinking of step S102, obtains cost
Addition function；
S2：Form the bidding strategies of micro-capacitance sensor main body；
S201：It is expected addition function using the cost of price, output and micro-capacitance sensor, establishes each micro-capacitance sensor operator
Profit function；
S202：Build the Bidding Mechanism and Competitive Bidding Model between micro-capacitance sensor, and solving system gross capability and each micro-capacitance sensor
It is optimal to bid；
S203：According to the principle of unified clearing price, by it is all participate in the micro-capacitance sensor main body bidded quotation according to from as low as
Height sequence, highest quotation is the final cleaing price of electricity market, and the profit of each micro-capacitance sensor is determined based on the price.
Basic data in the step S101 determined by the output and coefficient of load, photovoltaic and wind turbine respectively, specifically
It is expressed as：Wherein φ0For the output of micro-capacitance sensor 0, C (φ0) be micro-capacitance sensor 0 production cost, a, b, c is
Cost coefficient, a, b indicate that the secondary and cost constant coefficient contributed, c indicate the fixed cost of micro-capacitance sensor power generation respectively；It presses
At cost addition principle, the specific micro-capacitance sensor markon function in the step S102 are
Wherein C is cost of electricity-generating, and θ is cost dynamic Dynamic gene, and θ is related with the Supply and Demand of electricity market, is needed when supply is less than
When asking, θ<1, otherwise θ>1.The part is to have carried out numerical analysis using excel, is exactly to set several costs to rival
Type, such as high cost, middle cost and low cost, the cost function form of the functional form of each cost and specific micro-capacitance sensor 0
Equally, but coefficient is different, is exactly coefficient a, b different with the value of c, the cost type of rival i is high-cost general
The probability of rate, middle cost and low cost can be by obtaining in the analysis of historical data；It also needs to determine rival simultaneously
Cost dynamic Dynamic gene takes the probability of different value, so as to estimate the rival cost coefficient a, b and c value
ForSuch as following formula
The cost structure function of the rival is：Wherein i is micro-
Power grid i (i=0,1 ..., n-1)；The cost of rival is estimated by the historical data described in step S101；It is micro-
The cost of power grid i is desired forWherein hi,riThe cost of electricity-generating class of micro-capacitance sensor i is indicated respectively
Type and dynamic cost Dynamic gene number of types,Indicate that micro-capacitance sensor i existsWhen cost type
The desired derivation of cost of micro-capacitance sensor i is：
Assuming that micro-capacitance sensor i has hiThe different type of kind corresponds to different cost of electricity-generating functions, similarly, dynamic cost tune
There is also r for integral divisoriKind different types, equally also correspond to different probability, cost of electricity-generating and markon dynamic adjust because
It is independent from each other between son, then can obtain the cost of electricity-generating C of micro-capacitance sensor iiProbability distribution and markon dynamic Dynamic gene
θiProbability distribution be respectivelyWithWherein m=1,2 ... hiAnd And
At this point, micro-capacitance sensor 0 can face numerous micro-capacitance sensor competitions with uncertain cost dynamic Dynamic gene, add up toAccording to probability theory knowledge it is found that due to their probability distribution independence, can proper micro-capacitance sensor i cost of electricity-generating
CiProbability distribution beWith cost dynamic Dynamic gene θiProbability distribution beWhen, the probability of cost of electricity-generating function can
By formulaIt is calculated, i.e.,The step
In S102, consider that the cost of the micro-capacitance sensor i after cost dynamic Dynamic gene it is expected that addition function is：I.e.Wherein τiFor the dynamic Dynamic gene of expected cost.The present invention basic micro-capacitance sensor 0 at
This functional form isThe footmark of rival is i, and markon function is referred in this function
Before be multiplied by coefficient, such as θ, what when cost for estimating rival obtained isIn rival
Cost it is expected on the basis of also need carry out markon then obtainReferred to as cost it is expected addition function.
The step S201-S202 is specially：
S201：The method of Bidding Mechanism between structure micro-capacitance sensor operator is it is expected addition according to the cost of micro-capacitance sensor
Function, the profit function of the cost calculation micro-capacitance sensor is subtracted using sales volume, and profit function is：
Wherein η indicates the price at electricity transaction moment, η>0；τiIndicate the dynamic adjustment proportional factor of the expected cost of micro-capacitance sensor i；
S202：The uniform output of each micro-capacitance sensor is obtained using static game of complete information theory and is bidded；According to profit
Function formula can obtain corresponding result using first derivativeWith
Micro-capacitance sensor trade center predicts that the electric load situation at the moment can be obtained according to demand, so that it is determined that all micro- electricity of bidding
The gross capability situation of net is：φ thereinbIndicate the electricity that power grid trade center is bought to external bulk power grid
Amount；
FormulaThe desired value of the marginal cost price of micro-capacitance sensor 0 can be obtainedSimultaneous formulaπ(φi)=η φi-CiWithIt can must estimate micro-capacitance sensor 0
Rival it is expected bid rules beByIt can estimate micro- electricity
The expectation of 0 rival of net is priced atHighest quotation is the final cleaing price of electricity market, Gu Shi
Cleaing price is
A kind of bidding device containing micro-capacitance sensor based on Nash Game opinion, including：
Cost estimation module is specifically included for the cost estimate according to a certain specific micro-capacitance sensor to other micro-capacitance sensors：
Basic data module, for generating the basis based on prediction data according to the prediction data of load, photovoltaic and wind turbine
Data；
Rival's cost structure function module, for determining that the cost structure function of a certain specific micro-capacitance sensor, decision become
Amount, cost dynamic Dynamic gene form the micro-capacitance sensor cost function for considering that dynamic adjusts profit, the cost structure of rival
Functional form is identical, and cost coefficient is different；
The expected cost function module of rival, for specific micro-capacitance sensor 0 using historical data to its rival's
Cost structure is estimated, mainly estimates the distribution of the cost of rival and the distribution of dynamic cost Dynamic gene,
To build the expected cost function of rival；
Rival's markon function module carries out markon for the expected cost function to rival, obtains
Obtain markon function；
Flow measurement of bidding forms module, is used to form the bidding strategies of micro-capacitance sensor main body, specifically includes；
Profit function module is established each micro- for it is expected addition function using the cost of price, output and micro-capacitance sensor
The profit function of grid operator；
Optimal module of bidding, for building Bidding Mechanism and Competitive Bidding Model between micro-capacitance sensor, and solving system gross capability
Optimal with each micro-capacitance sensor is bidded；
Bid module, for the principle according to unified clearing price, by it is all participate in the micro-capacitance sensor main body bidded quotation by
According to sorting from low to high, highest quotation is the final cleaing price of electricity market, and the profit of each micro-capacitance sensor is determined based on the price
Profit.
A kind of electronic device, including：Processor；Memory：Storage is for processor control operation as described above
Instruction.
The beneficial effects of the invention are as follows：
(1) to micro-capacitance sensor cost moved with the market supply and the variation of demand according to dynamic cost method of adjustment
State adjusts its input cost, dynamic adjustment amount dependent on the magnitude relationship between electricity needs and supply, dynamic adjustment amount it is big
It is small to depend on profit, i.e., to maximize profit as final goal；
(2) cost information of rival is asymmetric, i.e., either party can not know the cost feelings of rival
Condition, but can reasonably be predicted by historical data, mainly by predicting possible cost function and possible dynamic
The cost adjustment factor estimates the expected cost of rival using probabilistic method.It is enterprising on the expected cost basis of rival
Row markon obtains the addition of expected cost；
(3) micro-capacitance sensor --- micro-capacitance sensor marketing center --- interaction between power distribution network, i.e. micro-capacitance sensor market is realized
Trade center announces electricity needs, and cost estimate of each micro-capacitance sensor according to itself and to rival, determining keeps its profit maximum
Output wantage can be bought from power distribution network if each micro-capacitance sensor cannot meet the market demand, otherwise can be by extra electricity
Amount buys power distribution network.
(4) present invention reduces estimation errors, reduce cost, reduce the work period, substantially increase work effect
Rate.
The above embodiments of the present invention are explained in detail, but the present invention is not limited to described embodiments.For
For those skilled in the art, in the case where not departing from the principle of the invention and spirit, these embodiments are carried out a variety of
Change, modification, replacement and modification are still fallen in protection scope of the present invention.
Claims (8)
1. the price competing method containing micro-capacitance sensor based on Nash Game opinion, which is characterized in that the multiagent of participation includes that n independent
Micro-capacitance sensor operator, micro-capacitance sensor power market transaction center, distribution network operation business, described method includes following steps：
S1：Cost estimate of a certain specific micro-capacitance sensor to other micro-capacitance sensors, specifically includes：
S101：The basic data based on prediction data is generated according to the prediction data of load, photovoltaic and wind turbine, is needed with forming electric power
It asks；
S102：It determines the cost structure function, decision variable, cost dynamic Dynamic gene of a certain specific micro-capacitance sensor, is formed and considered
Dynamic adjusts the micro-capacitance sensor cost function of profit, and the cost structure functional form of rival is identical, and cost coefficient is different；
S103：Specific micro-capacitance sensor 0 estimates the cost structure of its rival using historical data, mainly to competition pair
The cost distribution and the distribution of dynamic cost Dynamic gene of hand are estimated, to build the expected cost function of rival；
S104：Markon is carried out to the expected cost function of rival using the thinking of step S102, obtains markon
Function；
S2：Form the bidding strategies of micro-capacitance sensor main body；
S201：It is expected addition function using the cost of price, output and micro-capacitance sensor, establishes the profit letter of each micro-capacitance sensor operator
Number；
S202：The Bidding Mechanism and Competitive Bidding Model between micro-capacitance sensor are built, and solving system gross capability and each micro-capacitance sensor is optimal
It bids；
S203：According to the principle of unified clearing price, the micro-capacitance sensor main body bidded quotation is participated according to arranging from low to high by all
Sequence, highest quotation are the final cleaing price of electricity market, and the profit of each micro-capacitance sensor is determined based on the price.
2. containing the micro-capacitance sensor price competing method according to claim 1 based on Nash Game opinion, which is characterized in that the step
Basic data in S101 is determined by the output and coefficient of load, photovoltaic and wind turbine respectively, is embodied as：Wherein φ0For the output of micro-capacitance sensor 0, C (φ0) be micro-capacitance sensor 0 production cost, a, b, c be at
This coefficient, a, b indicate that the secondary and cost constant coefficient contributed, c indicate the fixed cost of micro-capacitance sensor power generation respectively；According at
This addition principle, the specific micro-capacitance sensor markon function in the step S102 are
Wherein C is cost of electricity-generating, and θ is cost dynamic Dynamic gene, and θ is related with the Supply and Demand of electricity market, is needed when supply is less than
When asking, θ<1, otherwise θ>1.
3. containing the micro-capacitance sensor price competing method according to claim 2 based on Nash Game opinion, which is characterized in that the competition
The cost structure function of opponent is：Wherein i be micro-capacitance sensor i (i=0,1 ...,
n-1)；The cost of rival is estimated by the historical data described in step S101；The cost of micro-capacitance sensor i is desired forWherein hi,riIndicate respectively micro-capacitance sensor i cost of electricity-generating type and dynamic cost adjustment because
Subtype quantity,Indicate that micro-capacitance sensor i existsWhen cost type
4. containing the micro-capacitance sensor price competing method according to claim 3 based on Nash Game opinion, which is characterized in that micro-capacitance sensor i
The derivation of cost expectation function be：
Assuming that micro-capacitance sensor i has hiThe different type of kind corresponds to different cost of electricity-generating functions, similarly, dynamic cost Dynamic gene
There is also riThe different type of kind, equally also corresponds to different probability, between cost of electricity-generating and markon dynamic Dynamic gene
It is independent from each other, then can obtain the cost of electricity-generating C of micro-capacitance sensor iiProbability distribution and markon dynamic Dynamic gene θiProbability
Distribution is respectivelyWithWherein m=1,2 ... hiAnd And
At this point, micro-capacitance sensor 0 can face numerous micro-capacitance sensor competitions with uncertain cost dynamic Dynamic gene, add up to
According to probability theory knowledge it is found that due to their probability distribution independence, can proper micro-capacitance sensor i cost of electricity-generating CiProbability
It is distributed asWith cost dynamic Dynamic gene θiProbability distribution beWhen, the probability of cost of electricity-generating function can be by formulaIt is calculated, i.e.,
5. containing the micro-capacitance sensor price competing method according to claim 2 based on Nash Game opinion, which is characterized in that the step
In S102, consider that the cost of the micro-capacitance sensor i after cost dynamic Dynamic gene it is expected that addition function is：I.e.Wherein τiFor the dynamic Dynamic gene of expected cost.
6. a kind of price competing method containing micro-capacitance sensor based on Nash Game opinion according to claim 5, which is characterized in that described
Step S201-S202 is specially：
S201：The method of Bidding Mechanism between structure micro-capacitance sensor operator is it is expected addition function according to the cost of micro-capacitance sensor,
The profit function of the cost calculation micro-capacitance sensor is subtracted using sales volume, profit function is：
Wherein η indicates the price at electricity transaction moment, η>0；τiIndicate the dynamic adjustment proportional factor of the expected cost of micro-capacitance sensor i；
S202：The uniform output of each micro-capacitance sensor is obtained using static game of complete information theory and is bidded；According to profit function
Formula can obtain corresponding result using first derivativeWithIt is micro-
Power grid trade center predicts that the electric load situation at the moment can be obtained according to demand, so that it is determined that all micro-capacitance sensors of bidding
Gross capability situation is：φ thereinbIndicate the electricity that power grid trade center is bought to external bulk power grid；
FormulaThe desired value of the marginal cost price of micro-capacitance sensor 0 can be obtainedSimultaneous
Formula Ci=θi·C(φi)=θi·(aiφi 2+biφi+ci)、π(φi)=η φi-CiWithIt can obtain
The rival of estimation micro-capacitance sensor 0 it is expected that bid rules areByIt can
To estimate that the expectation of 0 rival of micro-capacitance sensor is priced atHighest quotation, which is that electricity market is final, to be gone out clearly
Price, therefore market clearing price is
7. a kind of bidding device containing micro-capacitance sensor based on Nash Game opinion, which is characterized in that including：
Cost estimation module is specifically included for the cost estimate according to a certain specific micro-capacitance sensor to other micro-capacitance sensors：
Basic data module, for generating the basic data based on prediction data according to the prediction data of load, photovoltaic and wind turbine；
Rival's cost structure function module, for determine the cost structure function of a certain specific micro-capacitance sensor, decision variable, at
This dynamic Dynamic gene forms the micro-capacitance sensor cost function for considering that dynamic adjusts profit, the cost structure function shape of rival
Formula is identical, and cost coefficient is different；
The expected cost function module of rival, for specific micro-capacitance sensor 0 using historical data to the cost of its rival
Structure is estimated, mainly estimates the distribution of the cost of rival and the distribution of dynamic cost Dynamic gene, to
Build the expected cost function of rival；
Rival's markon function module, for carrying out markon to the expected cost function of rival, obtain at
This addition function；
Flow measurement of bidding forms module, is used to form the bidding strategies of micro-capacitance sensor main body, specifically includes；
Profit function module establishes each micro-capacitance sensor fortune for it is expected addition function using the cost of price, output and micro-capacitance sensor
Seek the profit function of quotient；
Optimal module of bidding, for building Bidding Mechanism and Competitive Bidding Model between micro-capacitance sensor, and solving system gross capability and each
The optimal of micro-capacitance sensor is bidded；
Bid module, for the principle according to unified clearing price, by it is all participate in the micro-capacitance sensor main body bidded quotation according to from
Low to high sequence, highest quotation are the final cleaing price of electricity market, and the profit of each micro-capacitance sensor is determined based on the price.
8. a kind of electronic device, which is characterized in that including：
Processor；
Memory：Storage controls operational order as claimed in any one of claims 1 to 6 for the processor.
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