CN109829578A - A kind of sale of electricity quotient and polynary user demand response game method and equipment - Google Patents
A kind of sale of electricity quotient and polynary user demand response game method and equipment Download PDFInfo
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Abstract
A kind of sale of electricity quotient provided by the present application and polynary user demand response game method and equipment, wherein method includes: the corresponding earnings pattern of demand for establishing polynary user and the corresponding earnings pattern of demand of sale of electricity quotient；Establish the demand response betting model of sale of electricity quotient Yu polynary user；It establishes the optimal response electricity equation of user and demand response betting model is solved by cup ascidian group's algorithm, obtain the optimum subsidy price of sale of electricity quotient.The application breaches mathematical analysis method by the demand response problem under participating in jointly for sale of electricity quotient and polynary user, and the mathematical model parameter aspect limitation to user and sale of electricity quotient proposes that there is the intelligent algorithm of universality to solve such problem.It is long in order to solve the usual intelligent method optimization time simultaneously, cup ascidian group's algorithm is introduced, rapid solving goes out optimal solution.
Description
Technical field
This application involves electric power network technique field more particularly to a kind of sale of electricity quotient and polynary user demand response game method and
Equipment.
Background technique
With the economic steady-state growth in China, industrial structure optimization adjustment and the increasingly raising of Living consumption, electric power
Demand continue to increase, the problems such as electric power peak-valley difference continues to increase, is more prominent.When electric system catastrophic failure leads to electric energy
When insufficient, may lead electricity market Spot Price and uprushed, and sale of electricity quotient formulate sale of electricity price be it is fixed in short term,
So the sale of electricity price of sale of electricity quotient is likely lower than power purchase price, sale of electricity income is caused to be negative.In user side, electric automobile, intelligence
The accounting of the flexible loads such as household, air-conditioning, electric heater is continuously improved, so that load becomes more initiative.This is using negative
The status that lotus demand elasticity alleviates power supply shortage is had laid a good foundation.
In the above context, demand response is shown one's talent in global power development, and has obtained large-scale practice.It needs
Response (demand response, DR) is asked to refer to that power consumer receives the inductivity power price change signal of supplier of electricity sending
Or after reducing the direct compensation notice of load, change itself original power mode, the electricity consumption for reducing or elapsing certain period is negative
Lotus, thus the acts and efforts for expediency for promoting power supply and demand balance, ensureing power grid operation.The response signal issued according to publisher
Demand response is generally divided into the demand response based on price and the demand response two types based on excitation by difference.Demand is rung
Polynary user should have not only been pushed to interact with the good of power grid both sides of supply and demand；The implementation of demand response can also cut down peak simultaneously
Electric load improves Power System Reliability；In addition, demand response is improving efficiency of energy utilization and is optimizing allocation of resources
Aspect is of great significance.
Demand response implementation process includes many uncertain factors, and the result of implementation of demand response can not also carry out accurately
Prediction causes each side's main body for participating in demand response to be difficult to make reasonable decision.In this context, it is necessary to study a kind of conjunction
Effective mode is managed to provide decision references for the participant of demand response.Game theory is that the multiple rationality participants of research carry out plan
The slightly Common Methods For Research of property interaction.The continuous development of electricity market is that game theory is good using having built in terms of electric system
Good platform.In the above context, it is expected to establish the analysis method of demand response based on game theory, to participate in the more of demand response
Square main body provides decision-making foundation.
Summary of the invention
It is existing for solving this application provides a kind of sale of electricity quotient and polynary user demand response game method and equipment
Each side's main body that electric system participates in demand response is difficult to the technical issues of making reasonable decision.
A kind of sale of electricity quotient and polynary user demand that the application first aspect provides respond game method, comprising:
Establish the corresponding earnings pattern of demand of polynary user and the corresponding earnings pattern of demand of sale of electricity quotient；
Establish the demand response betting model of sale of electricity quotient Yu polynary user；
It establishes the optimal response electricity equation of user and demand response betting model is solved by cup ascidian group's algorithm, obtain
The optimum subsidy price of sale of electricity quotient.
Preferably, the corresponding earnings pattern of demand for establishing polynary user includes:
Establish the demand response revenue function of user；
The demand response revenue function of the user are as follows:
Wherein, Fi,cFor the demand response income of user i, Ci,eIndicate that user i participates in the subsidy that demand response obtains, Bi,c
Indicate that user i reduces electricity consumption income obtained,Indicate the response cost of user i.
Preferably, the user i participates in the subsidy that demand response obtains are as follows:
Wherein,In the t period for indicating demand response, the demand response subsidized price of sale of electricity quotient formulation；Indicate user i
Response electricity, i.e. the electricity consumption of user i reduction；
User i reduces electricity consumption income obtained are as follows:
Wherein,It indicates in the t period, the zero potential energy that sale of electricity quotient formulates；
The response cost of user i are as follows:
Wherein,Indicate response electricity, the i.e. electricity consumption of user's reduction；Coefficient aiWith biIt is normal for the default fixation greater than 0
Number.
Preferably, the corresponding earnings pattern of demand for establishing sale of electricity quotient includes:
Establish the demand response revenue function of sale of electricity quotient；
The demand response revenue function of the sale of electricity quotient are as follows:
Fr=Bbuy-Cs-Cr,e；
Wherein, FrIndicate the demand response income of sale of electricity quotient, BbuyIndicate the purchases strategies that sale of electricity quotient saves；CsIndicate sale of electricity
The sale of electricity income of quotient's loss；Cr,eIndicate that sale of electricity quotient is supplied to the response compensation of user.
Preferably, the purchases strategies that the sale of electricity quotient saves are as follows:
Wherein,It indicates in response period t, power spot market Spot Price；N indicates to participate in the user of demand response
Sum；Indicate the response electricity of user i, the i.e. electricity consumption of user i reduction；
The sale of electricity income of sale of electricity quotient loss are as follows:
Wherein,It indicates in the t period, the zero potential energy that sale of electricity quotient formulates；
Sale of electricity quotient is supplied to the response compensation of user are as follows:
Wherein,In the t period for indicating demand response, the demand response subsidized price of sale of electricity quotient formulation.
Preferably, described to establish sale of electricity quotient and the demand response betting model of polynary user includes:
Establish the optimization problem formula of sale of electricity quotient and the optimization problem formula of user；
The optimization problem formula of the sale of electricity quotient are as follows:
The optimization problem formula of the user are as follows:
Wherein,Indicate the response electricity of user i, the i.e. electricity consumption of user i reduction,It indicates in response period t, electricity
Power spot market Spot Price,It indicates in the t period, the zero potential energy that sale of electricity quotient formulates；Indicate the t period of demand response
Demand response subsidized price interior, that sale of electricity quotient formulates；N indicates to participate in the total number of users of demand response；Coefficient aiWith biFor greater than 0
Default fixed constant；For the highest response quautity in time period t.
Preferably, the optimal response electricity equation are as follows:
Wherein,Indicate the response electricity of user i, the i.e. electricity consumption of user i reduction,It indicates in the t period, sale of electricity quotient's system
Fixed zero potential energy；In the t period for indicating demand response, the demand response subsidized price of sale of electricity quotient formulation；N indicates to participate in needing
Seek the total number of users of response；Coefficient aiWith biFor the default fixed constant greater than 0；For the highest response quautity in time period t.
Preferably, demand response betting model is solved by cup ascidian group's algorithm, obtains the optimum subsidy price of sale of electricity quotient
Include:
S1, the upper bound of search space is set as the upper bound of subsidized priceLower bound is the lower bound 0 of subsidized price, and
It is the subsidized price group P of N × 1 according to cup ascidian group's one scale of algorithm initialization；
S2, the corresponding each user's optimal response amount of each subsidized price for calculating subsidized price group P, calculate corresponding sale of electricity
The component F of square demand response income Fr, FrriThe fitness value of as each subsidized price；
S3, position of the corresponding subsidized price of maximum fitness as target is selected；
S4, remaining N-1 subsidized price (is referred into the N-1 subsidy removed outside the corresponding subsidized price of maximum fitness
Price) fitness value sort from large to small, choose position of the corresponding subsidized price of the first half fitness value as leader,
Position of the corresponding subsidized price of later half fitness value as follower；
S5, judge whether to reach preset the number of iterations, if so, optimal benefit of the position of output target as sale of electricity quotient
Price is pasted, if it is not, thening follow the steps S6；
S6, the position that leader and follower are updated according to cup ascidian group's algorithm；
S7, the fitness for calculating leader and follower after updating position, select maximum fitness value, and with
The fitness value of the position of target is compared, and if it is greater than the fitness value of the position of target, then it is corresponding to choose the fitness
Subsidized price as new target position and return to step S4, otherwise the position of target is constant and returns to step
S4。
Preferably, the sale of electricity quotient and polynary user demand respond game method further include: with the electric power in response period t
Spot market Spot PriceFor independent variable, sale of electricity quotient is computed repeatedly according to sale of electricity quotient and polynary user demand response game method
Optimum subsidy price, obtain the relation data of the optimum subsidy price of power spot market Spot Price and sale of electricity quotient；
Chart is generated according to the relation data of power spot market Spot Price and the optimum subsidy price of sale of electricity quotient and is shown
Show.
A kind of sale of electricity quotient and polynary user demand that the application second aspect provides respond gaming device, and the equipment includes
Processor and memory:
Said program code is transferred to the processor for storing program code by the memory；
The processor is used for according to a kind of sale of electricity quotient of such as first aspect of the instruction execution in said program code and more
First user demand responds game method.
As can be seen from the above technical solutions, the application has the following advantages:
A kind of sale of electricity quotient provided by the present application and polynary user demand respond game method and equipment, and wherein method includes:
Establish the corresponding earnings pattern of demand of polynary user and the corresponding earnings pattern of demand of sale of electricity quotient；Establish sale of electricity quotient and polynary user
Demand response betting model；It establishes the optimal response electricity equation of user and demand response is solved by cup ascidian group's algorithm and win
Model is played chess, obtains the optimum subsidy price of sale of electricity quotient.The application passes through the need under participating in jointly for sale of electricity quotient and polynary user
Response problem is sought, mathematical analysis method is breached, the mathematical model parameter aspect limitation to user and sale of electricity quotient proposes to have pervasive
The intelligent algorithm of property solves such problem.It is long in order to solve the usual intelligent method optimization time simultaneously, it introduces cup ascidian group and calculates
Method, rapid solving go out optimal solution.
Detailed description of the invention
It in ord to more clearly illustrate embodiments of the present application, below will be to required use in embodiment or description of the prior art
Attached drawing be briefly described, it should be apparent that, the drawings in the following description are only some examples of the present application, for this
For the those of ordinary skill of field, without any creative labor, it can also be obtained according to these attached drawings other
Attached drawing.
Fig. 1 is showing for one embodiment of a kind of sale of electricity quotient provided by the present application and polynary user demand response game method
It is intended to；
Fig. 2 is to use in a kind of sale of electricity quotient provided by the present application and one embodiment of polynary user demand response game method
In the schematic diagram for illustrating cup ascidian group's algorithm solution betting model；
Fig. 3 is to calculate in a kind of sale of electricity quotient provided by the present application and one embodiment of polynary user demand response game method
The corresponding sale of electricity quotient optimum subsidy price schematic diagram of spot market Spot Price of example；
Fig. 4 is to calculate in a kind of sale of electricity quotient provided by the present application and one embodiment of polynary user demand response game method
The corresponding user's optimal response amount schematic diagram of spot market Spot Price of example；
Fig. 5 is to calculate in a kind of sale of electricity quotient provided by the present application and one embodiment of polynary user demand response game method
The corresponding sale of electricity quotient demand response income schematic diagram of spot market Spot Price of example；
Fig. 6 is to calculate in a kind of sale of electricity quotient provided by the present application and one embodiment of polynary user demand response game method
The corresponding user demand of the spot market Spot Price of example responds income schematic diagram.
Specific embodiment
It is existing for solving this application provides a kind of sale of electricity quotient and polynary user demand response game method and equipment
Each side's main body that electric system participates in demand response is difficult to the technical issues of making reasonable decision.
To enable present invention purpose, feature, advantage more obvious and understandable, below in conjunction with the application
Attached drawing in embodiment, the technical scheme in the embodiment of the application is clearly and completely described, it is clear that disclosed below
Embodiment be only some embodiments of the present application, and not all embodiment.Based on the embodiment in the application, this field
Those of ordinary skill's all other embodiment obtained without making creative work belongs to the application protection
Range.
Firstly, the part noun or term that occur during the embodiment of the present application is described are suitable for as follows
It explains:
Cup ascidian group's algorithm (SSA) is that in August, 2017 is put forward by Australian scholar Seyedali M, thought source
Cup ascidian group behavior in deep-sea.
Referring to Fig. 1, the implementation of a kind of sale of electricity quotient provided by the present application and polynary user demand response game method
Example, comprising:
101, the corresponding earnings pattern of demand of polynary user and the corresponding earnings pattern of demand of sale of electricity quotient are established；
102, the demand response betting model of sale of electricity quotient Yu polynary user are established；
103, it establishes the optimal response electricity equation of user and demand response betting model is solved by cup ascidian group's algorithm,
Obtain the optimum subsidy price of sale of electricity quotient.
It should be noted that the model in the application, the usually set of mathematical function, as the relationship between data
It saves in the database, is transferred and calculated as needed, the relation function as preserved a+b=c in database then calculates
The relation function of the value of the available a of machine, the value of b and a+b=c is to calculate the value of c.
It should be noted that user is used as retinue side, when the subsidized price of sale of electricity quotient based in demand response betting model
After determination, the optimal response amount of user can determine therewith, and the demand response income of sale of electricity quotient can also be determined finally.So asking
Betting model is solved, that is, seeking the subsidized price for making sale of electricity quotient's Income Maximum.
The application breaches mathematical analysis by the demand response problem under participating in jointly for sale of electricity quotient and polynary user
Method, the mathematical model parameter aspect limitation to user and sale of electricity quotient, proposes that the intelligent algorithm with universality is asked to solve such
Topic.It is long in order to solve the usual intelligent method optimization time simultaneously, cup ascidian group's algorithm is introduced, rapid solving goes out optimal solution.
Further, the corresponding earnings pattern of demand for establishing polynary user includes:
Establish the demand response revenue function of user；
The demand response revenue function of user are as follows:
Wherein, Fi,cFor the demand response income of user i, Ci,eIndicate that user i participates in the subsidy that demand response obtains, Bi,c
Indicate that user i reduces electricity consumption income obtained,Indicate the response cost of user i.
User needs to undertake certain response cost during participating in demand response, to reduce itself electricity consumption；Together
When, due to the reduction of electricity consumption, user decreases a part of electric cost；In addition to this, sale of electricity quotient also needs to mention to user
For the demand response subsidy of response, this is also the major demands response revenue stream of user.
Further, user i participates in the subsidy that demand response obtains are as follows:
Wherein,In the t period for indicating demand response, the demand response subsidized price of sale of electricity quotient formulation；Indicate user i
Response electricity, i.e. the electricity consumption of user i reduction；
User i reduces electricity consumption income obtained are as follows:
Wherein,It indicates in the t period, the zero potential energy that sale of electricity quotient formulates；
The response cost of user i are as follows:
Wherein,Indicate response electricity, the i.e. electricity consumption of user's reduction；Coefficient aiWith biIt is normal for the default fixation greater than 0
Number, it is related with part throttle characteristics, for every kind of specific user, there is specific coefficient to be corresponding to it.It can be participated in user
In the historical process of demand response, by the data relationship between the response cost of user and the response quautity of user, use is picked out
The mathematical model and relevant parameter of family response cost.
User response cost refers to that user adjusts the loss of itself electricity consumption behavior bring.Since polynary user types are numerous,
It is not necessary to be also impossible to all carry out Modeling Research one by one to every class user；In order to preferably portray user demand response cost,
Polynary user can be roughly divided into the user that comfort level is impacted in the impacted user of income in response process and response process.
The user impacted for income in response process, response quautity is bigger, then the loss of outage of user's reduction plans with
Edge loss is bigger, i.e., the response cost of user and its marginal cost are bigger；The response cost of user can be expressed as it as a result,
The quadratic expression of response quautity, and when the response quautity of user is 0, response cost is also 0, so the constant of response cost function
Item is 0.
For the user impacted for comfort level in response process, the economy of characterization users'comfort can be approximately considered
Cost responds the square directly proportional of electricity to it.
It should be noted that by real data pick out come user response cost model be not necessarily quadratic function mould
Type；But due to the support of not no real data, in the response cost model of this temporary quadratic function characterization user.
Further, the corresponding earnings pattern of demand for establishing sale of electricity quotient includes:
Establish the demand response revenue function of sale of electricity quotient；
The demand response revenue function of sale of electricity quotient are as follows:
Fr=Bbuy-Cs-Cr,e；
Wherein, FrIndicate the demand response income of sale of electricity quotient, BbuyIndicate the purchases strategies that sale of electricity quotient saves；CsIndicate sale of electricity
The sale of electricity income of quotient's loss；Cr,eIndicate that sale of electricity quotient is supplied to the response compensation of user.
In the period t of demand response, sale of electricity quotient is that user is made to cut down itself load, needs to compensate user；It sells
While electric business reduces user power consumption by issuing demand response, but also sale of electricity quotient can save part purchases strategies,
But the sale of electricity income of itself can also be reduced accordingly；
Further, the purchases strategies that sale of electricity quotient saves are as follows:
Wherein,It indicates in response period t, power spot market Spot Price；N indicates to participate in the user of demand response
Sum；Indicate the response electricity of user i, the i.e. electricity consumption of user i reduction；
The sale of electricity income of sale of electricity quotient loss are as follows:
Wherein,It indicates in the t period, the zero potential energy that sale of electricity quotient formulates；
Sale of electricity quotient is supplied to the response compensation of user are as follows:
Wherein,In the t period for indicating demand response, the demand response subsidized price of sale of electricity quotient formulation.
Further, it establishes sale of electricity quotient and the demand response betting model of polynary user includes:
Establish the optimization problem formula of sale of electricity quotient and the optimization problem formula of user；
The optimization problem formula of sale of electricity quotient are as follows:
The optimization problem formula of user are as follows:
Wherein,Indicate the response electricity of user i, the i.e. electricity consumption of user i reduction,It indicates in response period t, electricity
Power spot market Spot Price,It indicates in the t period, the zero potential energy that sale of electricity quotient formulates；Indicate the t period of demand response
Demand response subsidized price interior, that sale of electricity quotient formulates；N indicates to participate in the total number of users of demand response；Coefficient aiWith biFor greater than 0
Default fixed constant；For the highest response quautity in time period t.
In the theory of games framework of demand response, sale of electricity quotient issues demand response project in advance, determines compensation mechanism, certainly
Plan amount is that sale of electricity quotient is the demand response subsidy unit price that user formulates；Then, the compensation mechanism that user determines according to sale of electricity quotient, knot
Self-demand is closed, demand response is selectively participated in, determines the decision content of itself, i.e. response electricity.Entire demand response scene
It is consistent with Stackelberg betting model application scenarios.
So being based on Stackelberg model construction demand response Game Relationship herein；Wherein sale of electricity quotient rings as demand
The leader answered generates strategy in advance under the premise of considering user's decision；And user does as follower in leader
Out after decision, according to self-condition, the optimal strategy of oneself is made.
During demand response, the target of sale of electricity quotient is to seek optimal subsidy unit priceIt is participated in maximizing itself
The income of demand response.This, which is equivalent to, solves following optimization problem:
Wherein,For the inequality constraints of sale of electricity quotient's subsidized price；If its meaning is that sale of electricity quotient subsidizes valence
Lattice are non-just, then user will not participate in demand response；If sale of electricity quotient's subsidized price is greater thanThen the demand of sale of electricity quotient is rung
Income is answered to become negative, sale of electricity quotient will not issue demand response.
Based on the demand response subsidized price that sale of electricity quotient announces, each user is based on own situation, determines optimal response electricity
Amount is to maximize self benefits.For user i, this corresponds again to solve an optimization problem shown in following formula:
Wherein,The inequality constraints of electricity is responded for user i, if indicating, user i participates in demand response,
It responds electricityNot above the highest response quautity in time period tAnd response quautity cannot be negative.
Further, optimal response electricity equation are as follows:
Wherein,Indicate the response electricity of user i, the i.e. electricity consumption of user i reduction,It indicates in the t period, sale of electricity quotient's system
Fixed zero potential energy；In the t period for indicating demand response, the demand response subsidized price of sale of electricity quotient formulation；N indicates to participate in needing
Seek the total number of users of response；Coefficient aiWith biFor the default fixed constant greater than 0；For the highest response quautity in time period t.
Further, demand response betting model is solved by cup ascidian group's algorithm, obtains the optimum subsidy valence of sale of electricity quotient
Lattice include:
S1, the upper bound of search space is set as the upper bound of subsidized priceLower bound is the lower bound 0 of subsidized price, and
It is the subsidized price group P of N × 1 according to cup ascidian group's one scale of algorithm initialization；
S2, the corresponding each user's optimal response amount of each subsidized price for calculating subsidized price group P, calculate corresponding sale of electricity
The component F of square demand response income Fr, FrriThe fitness value of as each subsidized price；
S3, position of the corresponding subsidized price of maximum fitness as target is selected；
S4, remaining N-1 subsidized price (is referred into the N-1 subsidy removed outside the corresponding subsidized price of maximum fitness
Price) fitness value sort from large to small, choose position of the corresponding subsidized price of the first half fitness value as leader,
Position of the corresponding subsidized price of later half fitness value as follower；
S5, judge whether to reach preset the number of iterations, if so, optimal benefit of the position of output target as sale of electricity quotient
Price is pasted, if it is not, thening follow the steps S6；
S6, the position that leader and follower are updated according to cup ascidian group's algorithm；
S7, the fitness for calculating leader and follower after updating position, select maximum fitness value, and with
The fitness value of the position of target is compared, and if it is greater than the fitness value of the position of target, then it is corresponding to choose the fitness
Subsidized price as new target position and return to step S4, otherwise the position of target is constant and returns to step
S4。
The solution procedure of betting model will be described in detail below:
In the demand response betting model established based on Stackelberg theory of games, user is used as retinue side, works as sale of electricity
After the subsidized price of quotient determines, the optimal response amount of user can determine therewith, and the demand response income of sale of electricity quotient can also be final
It determines.So betting model is solved, that is, seeking the subsidized price for making sale of electricity quotient's Income Maximum.
Solve user side optimal problem, be equivalent to ask independent variable in a certain continuum when quadratic function maximum
Value.It enables the first derivative of the demand response revenue function of user i be equal to 0, obtains:
Meet constraint condition by comparing needed for above formula and response electricityIt can be concluded that for given benefit
Paste priceOptimal response electricity of the user i in demand response period t are as follows:
Above formula shows that as sale of electricity quotient be that the subsidized price that user formulates is too low, i.e.,When, the demand of user i is rung
Income is answered to be negative value, user i cannot participate in demand response at this time.When sale of electricity quotient be user formulate subsidized price it is excessively high, i.e.,When, user i will be with the peak response ability certainly within the t periodParticipate in demand response.
Seek the optimum subsidy price of sale of electricity quotient using cup ascidian group's algorithm (SSA) herein.
Cup ascidian group's algorithm is in the environment space of N × D dimension, and N refers to the number of cup ascidian, and D refers to the dimension in space,
Position F=[the F of prey in space1F2...FD]T, the position of cup ascidian group is Xn=[Xn1Xn2...XnD]T, n=1,2 ..., N.
The upper bound of environment space is ub=[ub1ub2...ubD], lower bound is lb=[lb1lb2...lbD], it is possible thereby to random initializtion
The initialization formula of the position of cup ascidian in space are as follows:
XN×D=rand (N, D) × (ub-lb)+lb；
In cup ascidian group's algorithm, the individual of population is divided into two class of leader and follower, and opsition dependent is arranged in cup ascidian population
Name, forward individual are typically selected to be leader.The location updating equation such as following formula of leader:
Indicate that the jth in cup ascidian population in i-th of individual ties up location components；FjIndicate the jth dimension position of prey
Component, by calculating the fitness of current population, population at individual corresponding to adaptive optimal control angle value is prey position；c2And c3
It is the random number in [0,1] range；c1Expression formula such as following formula:
L indicates that current iteration number, L indicate maximum number of iterations.
Moving distance R of the follower in each iterative process is indicated with following formula:
Wherein, a is acceleration of follower during an iteration, and t is the time.
v0It is speed when follower's iteration starts, vfinalIt is the speed at the end of follower's iteration, as i >=2,
Indicate i-th of follower in the position that jth is tieed up.
Due in iterative process, t can be considered the difference of front and back the number of iterations twice, so t=1；Follower opens in iteration
Speed is 0 when the beginning, so v0=0；So moving distance of the follower in each iterative process are as follows:
Therefore, the location updating equation of follower is shown below:
Wherein,It is the updated position of follower.
According to above-mentioned cup ascidian group's theory of algorithm, betting model can be solved by cup ascidian group's algorithm, it is specific such as Fig. 2
It is shown, are as follows:
1. setting the upper bound of search space as the upper bound of subsidized priceLower bound is the lower bound 0 of subsidized price, according to
Initialize the subsidized price group P that one scale of formula random initializtion is N × 1.N is the number of cup ascidian group, according to different
Problem is preset.
2. showing that each subsidized price is corresponding by optimal response electricity equation based on the initialization subsidized price P in 1.
Each user's optimal response amount, then corresponding sale of electricity side's demand response income Fr is obtained by the demand response revenue function of sale of electricity quotient,
The component F of FrriThe fitness value of as each subsidized price.It should be noted that be corresponding with each user optimal for each subsidized price
Response quautity and the demand response income for being corresponding with sale of electricity quotient are Fri, i.e., the fitness value of each subsidized price, FriIt combines as Fr
It is corresponding with subsidized price group P.
3. fitness value is sorted by size, position of the corresponding subsidized price of maximum fitness as target is selected.
4. behind selected target position, the fitness value of remaining N-1 subsidized price is sorted from large to small, the first half is chosen
Position of the corresponding subsidized price of fitness value as leader, the corresponding subsidized price of later half fitness value is as follower
Position.
5. by leader location updating equation update leader position, by follower location updating equation update with
With the position of person.
6. calculating the fitness of leader and follower after updating position, maximum fitness value is selected, and with
The fitness value of target is compared, if being higher than the fitness value of target, is chosen the corresponding subsidized price of the fitness and is made
For the position of new target, otherwise the position of target is constant.
Step is repeated with certain the number of iterations 4. to arrive 6., after terminating iteration, is exported the position of current goal, be can be obtained
The optimum subsidy price of sale of electricity quotient finally obtains the game equilibrium solution of demand response model.
Further, sale of electricity quotient and polynary user demand respond game method further include: in response period t electric power it is existing
Goods market Spot PriceFor independent variable, compute repeatedly sale of electricity quotient's according to sale of electricity quotient and polynary user demand response game method
Optimum subsidy price obtains the relation data of power spot market Spot Price and the optimum subsidy price of sale of electricity quotient；
Chart is generated according to the relation data of power spot market Spot Price and the optimum subsidy price of sale of electricity quotient and is shown
Show.
It similarly, can also be with the power spot market Spot Price in response period tFor independent variable, according to sale of electricity quotient with
Polynary user demand response game method computes repeatedly the optimum subsidy price of sale of electricity quotient, user's optimal response amount, sale of electricity quotient need
Ask response income and user demand response income, obtain power spot market Spot Price and sale of electricity quotient optimum subsidy price,
The relation data of user's optimal response amount, sale of electricity quotient's demand response income and user demand response income；
Then correlation graph is shown.
According to aforesaid way, it is as follows example can be provided:
For the sake of simplicity, this example is set as the system for containing five users and a sale of electricity quotient, it is assumed that five users
Response cost model in two-term coefficient it is all the same, be collectively expressed as 0.01, Monomial coefficient is respectively 0.62,0.58,
0.54,0.56,0.70, user's peak response amount is respectively 27,24,15,28,30kWh, and the zero potential energy of sale of electricity quotient is 0.5
Member/kWh, when market Spot Price is higher than the zero potential energy of sale of electricity quotient, sale of electricity quotient can just consider to issue subsidized price to reduce
Loss, so setting market Spot Price as 0.5 to 4 yuan/kWh.
SSA algorithm and conventional particle group algorithm (PSO) are compared in terms of convergence property first.Through testing, SSA is calculated
Method can reach convergence at iteration 30 times, and PSO algorithm needs just to can reach for iteration 900 times convergence, the time used far more than
SSA algorithm.As can be seen that SSA algorithm has more preferably performance, target position can be quickly and stably converged to.
Result is analyzed below.Fig. 3 and Fig. 4 is respectively the optimal benefit of sale of electricity quotient corresponding to the Spot Price of spot market
Paste the optimal response amount of price and user.When spot market Spot Price is lower, the subsidized price of sale of electricity quotient is also relatively low, uses
Family cannot participate in demand response；With the raising of market Spot Price, the sequence that user begins participating in demand response is different, this with
Monomial coefficient b in user response cost modeliIt is related, work as biWhen lower, the easier participation demand response of user.When real-time
When electricity price increases, the optimum subsidy price of sale of electricity quotient is totally in rising trend, and the response quautity of user also accordingly increases, until it is reached
It is remained unchanged after to highest response quautity.In the section of certain Spot Prices, the optimum subsidy price of sale of electricity quotient will not change, this
It is because the response quautity of a certain user reaches saturation, if improving subsidized price, the increased response quautity of remaining users is insufficient to allow
The income of sale of electricity quotient increases, and only after Spot Price increases to a certain extent, sale of electricity quotient can just improve subsidized price.
Fig. 5 and Fig. 6 is respectively the demand response income of sale of electricity quotient and user corresponding to the Spot Price of spot market.As a result
Show that the demand response income of sale of electricity quotient increases as market Spot Price increases approximately linear.When the use for participating in demand response
When family response quautity does not reach itself peak response amount, the demand response income of user is in steps rising, this is because it is received
Benefit is influenced by the subsidized price that response cost and sale of electricity quotient are formulated, for different market Spot Prices, as long as sale of electricity
The subsidized price of quotient is constant, the response quautity of user also just it is constant, income thus will not change.The subsidized price that sale of electricity quotient formulates is got over
Greatly, the response cost of user is smaller, and the demand response income of user is bigger；When user response amount reaches itself peak response amount
When, the income of user is also influenced by peak response amount.
The application has carried out the common stimulable type demand of the multi-party main body such as sale of electricity quotient and polynary user based on game theory and has rung
It should study, propose application framework of the game theory in stimulable type demand response, on this basis, establish polynary user and sell
The demand response earnings pattern of electric business, and the demand of sale of electricity quotient Yu polynary user are constructed based on Stackelberg model respectively
Respond betting model.The game equilibrium of model built has been acquired with SSA algorithm, is finally proposed the solution of SSA algorithm and is modeled
The algorithm and process of type.
Electric business on sale and polynary user demand response gambling process in, by the superiority of sample calculation analysis SSA algorithm with
And influence caused by strategy and income of the market Spot Price to sale of electricity quotient and user.The result shows that SSA algorithm compared to
Faster, precision is higher for PSO algorithm the convergence speed.The demand response income of sale of electricity quotient increases and approximate line with market Spot Price
Property increase.When the user response amount for participating in demand response does not reach itself peak response amount, income is by response cost
And the influence of the subsidized price of sale of electricity quotient formulation.The subsidized price that sale of electricity quotient formulates is bigger, and the response cost of user is smaller, uses
The demand response income at family is bigger；When user response amount reaches itself peak response amount, the income of user is also by maximum
The influence of response quautity.
One embodiment of a kind of sale of electricity quotient provided by the present application and polynary user demand response gaming device, equipment include
Processor and memory:
Program code is transferred to processor for storing program code by memory；
Processor is used for a kind of sale of electricity quotient and polynary user according to such as above-described embodiment of the instruction execution in program code
Demand response game method.
The above, above embodiments are only to illustrate the technical solution of the application, rather than its limitations；Although referring to before
Embodiment is stated the application is described in detail, those skilled in the art should understand that: it still can be to preceding
Technical solution documented by each embodiment is stated to modify or equivalent replacement of some of the technical features；And these
It modifies or replaces, the spirit and scope of each embodiment technical solution of the application that it does not separate the essence of the corresponding technical solution.
Claims (10)
1. a kind of sale of electricity quotient and polynary user demand respond game method characterized by comprising
Establish the corresponding earnings pattern of demand of polynary user and the corresponding earnings pattern of demand of sale of electricity quotient；
Establish the demand response betting model of sale of electricity quotient Yu polynary user；
It establishes the optimal response electricity equation of user and demand response betting model is solved by cup ascidian group's algorithm, obtain sale of electricity
The optimum subsidy price of quotient.
2. a kind of sale of electricity quotient according to claim 1 and polynary user demand respond game method, which is characterized in that described
The corresponding earnings pattern of demand for establishing polynary user includes:
Establish the demand response revenue function of user；
The demand response revenue function of the user are as follows:
Wherein, Fi,cFor the demand response income of user i, Ci,eIndicate that user i participates in the subsidy that demand response obtains, Bi,cIt indicates
User i reduces electricity consumption income obtained,Indicate the response cost of user i.
3. a kind of sale of electricity quotient according to claim 2 and polynary user demand respond game method, which is characterized in that described
User i participates in the subsidy that demand response obtains are as follows:
Wherein,In the t period for indicating demand response, the demand response subsidized price of sale of electricity quotient formulation；Indicate the sound of user i
Answer electricity, the i.e. electricity consumption of user i reduction；
User i reduces electricity consumption income obtained are as follows:
Wherein,It indicates in the t period, the zero potential energy that sale of electricity quotient formulates；
The response cost of user i are as follows:
Wherein,Indicate response electricity, the i.e. electricity consumption of user's reduction；Coefficient aiWith biFor the default fixed constant greater than 0.
4. a kind of sale of electricity quotient according to claim 1 and polynary user demand respond game method, which is characterized in that described
The corresponding earnings pattern of demand for establishing sale of electricity quotient includes:
Establish the demand response revenue function of sale of electricity quotient；
The demand response revenue function of the sale of electricity quotient are as follows:
Fr=Bbuy-Cs-Cr,e；
Wherein, FrIndicate the demand response income of sale of electricity quotient, BbuyIndicate the purchases strategies that sale of electricity quotient saves；CsIndicate sale of electricity quotient damage
The sale of electricity income of mistake；Cr,eIndicate that sale of electricity quotient is supplied to the response compensation of user.
5. a kind of sale of electricity quotient according to claim 4 and polynary user demand respond game method, which is characterized in that described
The purchases strategies that sale of electricity quotient saves are as follows:
Wherein,It indicates in response period t, power spot market Spot Price；N indicates that the user for participating in demand response is total
Number；Indicate the response electricity of user i, the i.e. electricity consumption of user i reduction；
The sale of electricity income of sale of electricity quotient loss are as follows:
Wherein,It indicates in the t period, the zero potential energy that sale of electricity quotient formulates；
Sale of electricity quotient is supplied to the response compensation of user are as follows:
Wherein,In the t period for indicating demand response, the demand response subsidized price of sale of electricity quotient formulation.
6. a kind of sale of electricity quotient according to claim 1 and polynary user demand respond game method, which is characterized in that described
It establishes sale of electricity quotient and the demand response betting model of polynary user includes:
Establish the optimization problem formula of sale of electricity quotient and the optimization problem formula of user；
The optimization problem formula of the sale of electricity quotient are as follows:
The optimization problem formula of the user are as follows:
Wherein,Indicate the response electricity of user i, the i.e. electricity consumption of user i reduction,It indicates in response period t, electric power is existing
Goods market Spot Price,It indicates in the t period, the zero potential energy that sale of electricity quotient formulates；In the t period for indicating demand response, sell
The demand response subsidized price that electric business is formulated；N indicates to participate in the total number of users of demand response；Coefficient aiWith biIt is default greater than 0
Fixed constant；For the highest response quautity in time period t.
7. a kind of sale of electricity quotient according to claim 1 and polynary user demand respond game method, which is characterized in that described
Optimal response electricity equation are as follows:
Wherein,Indicate the response electricity of user i, the i.e. electricity consumption of user i reduction,It indicates in the t period, what sale of electricity quotient formulated
Zero potential energy；In the t period for indicating demand response, the demand response subsidized price of sale of electricity quotient formulation；N indicates participation demand
The total number of users of response；Coefficient aiWith biFor the default fixed constant greater than 0；For the highest response quautity in time period t.
8. a kind of sale of electricity quotient according to claim 1 and polynary user demand respond game method, which is characterized in that pass through
Cup ascidian group's algorithm solves demand response betting model, show that the optimum subsidy price of sale of electricity quotient includes:
S1, the upper bound of search space is set as the upper bound of subsidized priceLower bound is the lower bound 0 of subsidized price, and according to
Cup ascidian group's one scale of algorithm initialization is the subsidized price group P of N × 1；
S2, the corresponding each user's optimal response amount of each subsidized price for calculating subsidized price group P, calculating corresponding sale of electricity side needs
Ask response income Fr, the component F of FrriThe fitness value of as each subsidized price；
S3, position of the corresponding subsidized price of maximum fitness as target is selected；
S4, the fitness value of remaining N-1 subsidized price is sorted from large to small, chooses the corresponding subsidy of the first half fitness value
Position of the price as leader, position of the corresponding subsidized price of later half fitness value as follower；
S5, judge whether to reach preset the number of iterations, if so, optimum subsidy valence of the position of output target as sale of electricity quotient
Lattice, if it is not, thening follow the steps S6；
S6, the position that leader and follower are updated according to cup ascidian group's algorithm；
S7, the fitness for calculating leader and follower after updating position, select maximum fitness value, and and target
The fitness value of position be compared, if it is greater than the fitness value of the position of target, then choose the corresponding benefit of the fitness
Price is pasted as the position of new target and returns to step S4, otherwise the position of target is constant and returns to step S4.
9. a kind of sale of electricity quotient according to claim 8 and polynary user demand respond game method, which is characterized in that described
Sale of electricity quotient and polynary user demand respond game method further include: with the power spot market Spot Price in response period t
For independent variable, the optimum subsidy price of sale of electricity quotient is computed repeatedly according to sale of electricity quotient and polynary user demand response game method, is obtained
The relation data of power spot market Spot Price and the optimum subsidy price of sale of electricity quotient out；
Chart is generated according to the relation data of power spot market Spot Price and the optimum subsidy price of sale of electricity quotient and is shown.
10. a kind of sale of electricity quotient and polynary user demand respond gaming device, which is characterized in that the equipment include processor and
Memory:
Said program code is transferred to the processor for storing program code by the memory；
The processor is used for according to the described in any item a kind of sales of electricity of instruction execution claim 1-9 in said program code
Quotient and polynary user demand respond game method.
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| Publication number | Priority date | Publication date | Assignee | Title |
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| CN111275285A (en) * | 2019-12-30 | 2020-06-12 | 昆明电力交易中心有限责任公司 | Power consumption regulation and control method and system considering interruptible load capacity |
| CN112634080A (en) * | 2020-12-24 | 2021-04-09 | 沈阳工程学院 | Multi-target demand response management method based on Pareto optimal theory |
| CN112688335A (en) * | 2021-01-13 | 2021-04-20 | 贵州电网有限责任公司 | Real-time demand response modeling method based on game balance |
| CN115330144A (en) * | 2022-05-17 | 2022-11-11 | 国网江苏省电力有限公司淮安供电分公司 | Demand response mechanism model establishment method considering real-time carbon emission reduction |
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| Publication number | Priority date | Publication date | Assignee | Title |
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| CN111275285A (en) * | 2019-12-30 | 2020-06-12 | 昆明电力交易中心有限责任公司 | Power consumption regulation and control method and system considering interruptible load capacity |
| CN111275285B (en) * | 2019-12-30 | 2024-02-20 | 昆明电力交易中心有限责任公司 | Power consumption regulation and control method and system considering interruptible load capacity |
| CN112634080A (en) * | 2020-12-24 | 2021-04-09 | 沈阳工程学院 | Multi-target demand response management method based on Pareto optimal theory |
| CN112688335A (en) * | 2021-01-13 | 2021-04-20 | 贵州电网有限责任公司 | Real-time demand response modeling method based on game balance |
| CN115330144A (en) * | 2022-05-17 | 2022-11-11 | 国网江苏省电力有限公司淮安供电分公司 | Demand response mechanism model establishment method considering real-time carbon emission reduction |
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