CN108537363A - A kind of ration separates sale of electricity company power purchase amount control method under environment - Google Patents
A kind of ration separates sale of electricity company power purchase amount control method under environment Download PDFInfo
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Abstract
The invention discloses a kind of the placings to separate sale of electricity company power purchase amount control method under environment, and the control method includes the following steps：Three layers of purchase sale of electricity service architecture of grid company-sale of electricity company-user are established according to sale of electricity company Agent and User interface Agent；Based on three layers of purchase sale of electricity service architecture, the user's electricity elastic model formed by uncontrollable load, transferable load and variable dynamic load is built；According to user's electricity price elastic model, the operation of sale of electricity company and assessment parameter, sale of electricity company purchase of electricity Controlling model is established, which includes：It is up to object function with the sum of sale of electricity company sale of electricity income and potential income, considers market stability constraint, purchase sale of electricity Constraints of Equilibrium respectively.The present invention has fully considered the purchase sale of electricity of sale of electricity company and the uncertainty to expected future, establishes sale of electricity company to the decision model of electricity, is solved using Chaos particle swarm optimization algorithm, realizes the optimization to purchase of electricity.
Description
Technical field
The present invention relates to electric system power domains more particularly to a kind of the placing to separate sale of electricity company purchase of electricity control under environment
Method processed.
Background technology
The renewable new energies power generation such as current wind-powered electricity generation, photovoltaic is to the replacement of traditional fossil energy, and electric vehicle is to traditional vapour
The replacement of vehicle becomes trend, causes the power generation of system and power load to have randomness and intermittence, while power consumer passes through
Power consuming administrative system or equipment respond energy value, carry out the translation or reduction of load.It is uncertain in " source ", " lotus "
In the case of implement power retailing business so that the operation of sale of electricity company attracts attention [1].
One complete electricity market is generally divided into medium-term and long-term contract trade market, futures market, day-ahead power market
Market, real-time deal (balance) market and ancillary service trade market are several.In China, power market reform and the placing detach
Under background, for grid company in order to ensure that the equilibrium of supply and demand, maintenance system are stablized, electricity market operation department passes through spot exchange city
, determine the generation schedule in second day each trading session, and calculate on each area reference node and generating set
The bulk sale electricity price of the spot price of site, i.e. sale of electricity company to power grid power purchase.Sale of electricity company is in addition to long-term contract, futures exchange
Etc. forms power purchase from power grid, it is also necessary to power purchase is carried out from day-ahead trading, and the decision of sale of electricity company purchase of electricity, to electricity
The benefit of the safe operation and sale of electricity company of Force system all has larger impact.
For sale of electricity company, need to submit next day purchase of electricity curve, every 30 points of generally use to be a trading session, integral point
Terminate or half an hour terminates.In the case where sale of electricity company zero potential energy is not decontroled, the purchase of electricity decision of sale of electricity company only need to be by
Institute's sale of electricity user in predicting load is determined with Contract Energy difference.But in the abundant market-oriented stage, sale of electricity company has zero potential energy
Discretionary power, the electricity consumption of the power consumer within the scope of service provided will be influenced by zero potential energy, Jin Erhui
It influences sale of electricity company and needs the purchase of electricity in day-ahead trading.Since there are spot market electricity prices and next day user power utilization
The factors such as the uncertainty of amount, the purchase of electricity decision-making technique for causing sale of electricity company traditional face certain risk.How to formulate
The purchase of electricity decision strategy of effect, makes sale of electricity company be obtained in spot market electricity price and the uncertain of next day user power consumption
Maximum return is obtained, the content of sale of electricity company concern is become.
Invention content
The present invention provides a kind of the placings to separate sale of electricity company power purchase amount control method under environment, and the present invention is negative by analyzing
Lotus elasticity establishes the user demand elastic model of protection privacy of user and considers the optimal power purchase of electricity price factor of can making decisions on one's own
Decision model is measured, and Conditional Lyapunov ExponentP (CVaR) is introduced into the assessment of sale of electricity corporate risk, realizes sale of electricity company to power purchase
The optimization of amount, it is described below：
A kind of ration separates sale of electricity company power purchase amount control method under environment, and the control method includes the following steps：
Three layers of purchase that grid company-sale of electricity company-user is established according to sale of electricity company Agent and User interface Agent are sold
Electric service architecture；Based on three layers of purchase sale of electricity service architecture, build by uncontrollable load, transferable load and variable dynamic load
Composition user's electricity elastic model；
According to user's electricity price elastic model, the operation of sale of electricity company and assessment parameter, the purchase of electricity control of sale of electricity company is established
Simulation, the model include：It is up to object function with the sum of sale of electricity company sale of electricity income and potential income, considers market respectively
Scleronomic constraint, purchase sale of electricity Constraints of Equilibrium.
When specific implementation, the sale of electricity company Agent, after receiving all customer charge information, according to itself
Benefit is target making purchase of electricity optimisation strategy, and the purchase of electricity finally predicted is reported grid company.
Preferably, the User interface Agent is interacted for passing through physical interface with intelligent power equipment, and realization pair is set
Standby intelligent control；The User interface Agent, is additionally operable to the information based on history consumption habit information or setting, and prediction time is daily
The electricity consumption curve and demand elasticity parameter at family, polymerize customer charge data, and are reported to sale of electricity company Agent；It is described
User interface Agent is additionally operable to the zero potential energy information issued based on sale of electricity company, and optimizing the use of itself can plan, and realize user's
Energy management.User interface Agent can be applied to industry, business and resident load.
Further, user's electricity elastic model is specially：
In formula：Hop count when I is total,Indicate that each moment benchmark electricity prices of user k areWhen
User's daily power consumption curve, WkIt is and the relevant matrix of user's electricity price elasticity；Indicate negative
The initial electricity consumption vectors of lotus m；EmFor power load Price elasticity matrix；For electricity price vector.
Wherein, the market stability, which constrains, is specially：
ρsmin≤ρs,t≤ρsmax
Pbmin≤Pb,t≤Pbmax
In formula, ρsmax、ρsminRespectively hour electricity price bound a few days ago, ρbmax、ρbminRespectively power purchase power bound,
Pa,minIndicate that day electricity sales amount minimum value, T are decision period set, T=[1,2 ..., I].
Wherein, the purchase sale of electricity Constraints of Equilibrium is specially：
Pb,t=Ps,t+Ploss,t=(1+ α) Ps,t
In formula, ρs,tFor the hour electricity price a few days ago of formulation, Ploss,tFor the total electricity lost in electricity transmission process, α is line loss ratio
Example coefficient.
Further, the control method further includes：
Sale of electricity company Agent transmits information by broadcast mode to user；User interface Agent upload information includes load number
According to, it is therefore desirable to encrypted transmission.
The advantageous effect of technical solution provided by the invention is：
1, the purchase sale of electricity of sale of electricity company and the uncertainty to expected future have been fully considered, has established sale of electricity company to electricity
Decision model, solved using Chaos particle swarm optimization algorithm, realize the optimization to purchase of electricity；
2, it is optimized, is increased between user and electric system by the purchase of electricity under electricity price factor that pair can make decisions on one's own
Linkage effect, be conducive to excavate user side electricity consumption elasticity, and can be improved total social benefit, realize the energy Green Development.
Description of the drawings
Fig. 1 is the purchase sale of electricity services framework schematic diagram provided by the invention based on MAS；
Fig. 2 is the flow chart that a kind of the placing provided by the invention separates sale of electricity company power purchase amount control method under environment；
Fig. 3 is the spot market forecasted electricity market price of embodiment；
Fig. 4 is embodiment difference σPUnder selling benefit；
Fig. 5 is embodiment difference σPUnder sale of electricity Conditional Lyapunov ExponentP；
Fig. 6 is embodiment difference B(0)Under sale of electricity corporate decision electricity price；
Fig. 7 is embodiment difference σPWith σBUnder selling benefit.
Specific implementation mode
To make the object, technical solutions and advantages of the present invention clearer, embodiment of the present invention is made below further
It is described in detail on ground.
Embodiment 1
A kind of ration separates sale of electricity company power purchase amount control method under environment, and referring to Fig. 1 and Fig. 2, this method includes following
Step：
101：Three layers of grid company-sale of electricity company-user are established according to sale of electricity company Agent and User interface Agent
Purchase sale of electricity service architecture；
102：Based on three layers of purchase sale of electricity service architecture, build by uncontrollable load, transferable load and variable dynamic load
Composition user's electricity elastic model；
103：According to user's electricity price elastic model, the operation of sale of electricity company and assessment parameter, sale of electricity company power purchase is established
Controlling model is measured, which includes：It is up to object function with the sum of sale of electricity company sale of electricity income and potential income, considers respectively
Market stability constraint, purchase sale of electricity Constraints of Equilibrium.
Further, sale of electricity company Agent, after receiving all customer charge information, most according to number one
Target making purchase of electricity optimisation strategy is turned to greatly, and the purchase of electricity finally predicted is reported into grid company.
Further, User interface Agent is interacted for passing through physical interface with intelligent power equipment, is realized to equipment
Intelligent control；
User interface Agent is additionally operable to the information based on history consumption habit information or setting, predicts that the electricity consumption of next day user is bent
Line and demand elasticity parameter, polymerize customer charge data, and are reported to sale of electricity company Agent；
User interface Agent is additionally operable to the zero potential energy information issued based on sale of electricity company, and optimizing the use of itself can plan, real
The energy management at current family.User interface Agent can be applied to industry, business and resident load.
When specific implementation, which further includes：
Sale of electricity company Agent transmits information by broadcast mode to user；User interface Agent upload information includes load number
According to, it is therefore desirable to encrypted transmission.
In conclusion the embodiment of the present invention is optimized by the purchase of electricity under electricity price factor that pair can make decisions on one's own, increase
Linkage effect between user and electric system is conducive to the electricity consumption elasticity for excavating user side, but can be improved total social benefit,
Realize the Green Development of the energy.
Embodiment 2
The scheme in embodiment 1 is further introduced with reference to Fig. 1, Fig. 2, calculation formula and example, in detail
See below description：
201：Sale of electricity company purchases sale of electricity service architecture and Agent settings；
In the embodiment of the present invention based on " grid company-sale of electricity company-user " three-layer structure, including sale of electricity company
The concrete function of Agent and User interface Agent, required implementation is as follows：
One, sale of electricity company Agent, including：
A) it is interacted with grid company information platform, obtains the bulk sale of power grid current operating conditions and grid company
Electricity price information；
B) it is responsible for issuing zero potential energy information to lower layer Agent, and receives the information on load of lower layer Agent feedbacks；
C) after receiving all customer charge information, target making purchase of electricity is turned to according to number one maximum and optimizes plan
Slightly, and the purchase of electricity finally predicted is reported into grid company.
Two, User interface Agent, including：
A) it is interacted by physical interface and intelligent power equipment, realizes the intelligent control to equipment；
B) it is based on history consumption habit information or information set by user, predicts the electricity consumption curve and demand bullet of next day user
Property parameter, polymerize customer charge data, and be reported to sale of electricity company Agent；
C) the zero potential energy information based on the publication of sale of electricity company, optimizing the use of itself can plan, and realize the energy pipe of user
Reason.User interface Agent can be applied to industry, business and resident load.
202：Decision of the sale of electricity company to purchase of electricity under purchase sale of electricity framework；
User interface Agent can be applied to industry, business and resident load, only be analysis with resident for simplifying the analysis
Same procedure can be used in object, other types load.
One, according to variety classes part throttle characteristics, include based on power load elastic model structure：Uncontrollable load can turn
The user's electricity elastic model for moving load and variable dynamic load, first builds the power load elastic matrix of different load
Mould obtains user's electricity elastic model, and the above flow is completed by User interface Agent, and detailed step is as follows：
(1) uncontrollable load, including lighting installation, TV etc. are to demand and the more stringent load of time requirement, electricity consumption
Characteristic is relatively fixed, and electricity consumption curve can be obtained by load prediction, it is believed that the type load electricity consumption elastic matrixElasticity system
Number is 0, i.e.,：
In formula, U is uncontrollable load set, and m is some load in the set.
(2) transferable load, refer mainly to it is a kind of demand is required it is stringent but to electricity consumption time not stringent load, it is such as electronic
Automobile, water heater etc..The characteristics of the type load, which is electricity consumption total amount, to be changed, and the distribution of electricity consumption in time is only influenced,
Electricity consumption is by just shifting relatively according to electricity consumption period zero potential energy.
To simplify load model, it is assumed that in the operation interval of transferable load, load total electricity consumption is in operation interval
It is evenly distributed, and the initial electricity consumption of day part is equal definite value, and electricity elastic matrixElasticity system meet such as ShiShimonoseki
System：
In formula, S is transferable load aggregation, eij,mFor electricity elastic matrix the i-th row jth row coefficient of transferable load m,
am、bmFor the time lower and upper limit of load m operation intervals.
(3) dynamic load is can be changed, is specifically included：Air-conditioning etc. have continuous drain characteristic load and can according to electricity price height
The load interrupted at any time, it is not stringent to demand requirement, electricity consumption can be adjusted in time to save with the variation of electricity consumption period zero potential energy
The about electricity charge.Ignore air storage it is cold in the case of, transfer characteristic unobvious, it will be assumed that the coefficient of cross elasticity of the type load is
0, i.e. electricity elastic matrixCoefficient of elasticity meet following relationship：
In formula, A is variable load aggregation.
(4) the demand elasticity relational expression between the electricity consumption and electricity price of load m is represented by：
In formula, Pm=[P1,m,P2,m,…,PI,m]TIt is vectorial for the electricity consumption at load m each moment,
Indicate that the initial electricity consumptions of load m are vectorial, hop count when I is total,Indicate withEach element is the diagonal of diagonal element
Battle array, price item ρs,mIt is expressed as：
In formula, ρs,iIndicate i (i=1,2 ..., I) moment sale of electricity electricity price,For constant term.
(5) the demand elasticity relational expression of all loads is added, obtains the demand elasticity relational expression of user k：
In formula：Indicate that each moment benchmark electricity prices of user k areWhen user's daily power consumption
Curve, WkIt is and the relevant matrix of user's electricity price elasticity.
Formula (6) is the electricity price elastic model of user k.After User interface Agent receives control commencing signal, user
Agent willWkAndThree parameters are uploaded to sale of electricity company Agent.
Two, the parameter obtained needed for the control of sale of electricity company purchase of electricity
With marketing development, sale of electricity company type and service connotation are expanded.Under power retailing environment, sale of electricity is public
The type of department can be roughly divided into three classes：
(1) the increment distribution network operation business invested by grid company or social capital is set up, and is had and is provided confession of guaranteeing the minimum
The obligation of electricity service and power transmission and distribution service；
(2) it is invested and is set up by genco or distributed generation resource owner, sale of electricity transaction can be directly established with user
Company；
(3) it is set up by the fully reinforced social undertakings investment of assets, does not have power grid operation power and generating capacity.It should
Class sale of electricity company is large number of, competitive spirit is strong, is that power sales are most basic, most common type.
In this case, the control of sale of electricity company purchase of electricity needs to consider that the parameter obtained includes：Purchases strategies it is expected
Value, line loss proportionality coefficient, sale of electricity electricity price bound, purchase of electricity bound, day sale of electricity minimum value, potential income influence coefficient, when
Day sale of electricity company power supply number of users, sale of electricity zone user total scale number, the market share estimate that coefficient, risk assessment confidence level are sold
Electricity, purchases strategies, latency influence coefficient distribution standard deviation, the risk averse factor.
Three, sale of electricity company purchase of electricity Controlling model
(1) transaction between grid company and sale of electricity company may be designed as multiple types, including：In the form of Power Pool
It is bought in spot market, or determines power purchase price in the form of bilateral contract etc..To simplify the analysis, it mainly studies sale of electricity company and uses
Operational mode between family simplifies power purchase side, it is believed that sale of electricity company is ρ in the purchases strategies of period next day tb,t, can
By predicting to obtain desired value a few days ago.
(2) according to user's electricity price elastic model and the operation of sale of electricity company and assessment parameter, sale of electricity company power purchase is established
Controlling model is measured, including：It is up to object function with the sum of sale of electricity company sale of electricity income and potential income, considers that market is steady respectively
Conclude a contract or treaty beam, purchase sale of electricity Constraints of Equilibrium；
1) above-mentioned electricity price of making decisions on one's own is specially hour electricity price a few days ago；
2) the sum of above-mentioned sale of electricity company sale of electricity income and potential income are up to object function and are represented by：
MaxB=B '+B " (7)
In formula, B ' expression sales of electricity company sale of electricity income, B " indicates sale of electricity company potential income, indicates as follows respectively：
Wherein：
f(os)=r1+r2os+r3os 2 (12)
In formula, T is decision period set, and T=[1,2 ..., I], K gather for all participation users, Ps,tFor t period sales of electricity
Amount, is the variable of decision, ρs,tFor the hour electricity price a few days ago of formulation, ρb,tIt is P for the purchases strategies of tb,tFor sale of electricity company power purchase
Amount, B(0)Potential income influences coefficient, and U is sale of electricity zone user total scale number, U0Indicate same day sale of electricity company power supply number of users,
r1、r2With r3Coefficient, o are estimated for the market sharesFor the average price of sale of electricity price, Ps,tIt is represented by the function of sale of electricity price, that is, is used
T in the demand elasticity relational expression of family k, the information on load that User interface Agent upload is received by sale of electricity company Agent obtains
It takes.
3) above-mentioned market stability constraint：
ρsmin≤ρs,t≤ρsmax (13)
Pbmin≤Pb,t≤Pbmax (14)
In formula, ρsmin、ρsmaxRespectively hour electricity price bound a few days ago, ρbmin、ρbmaxRespectively power purchase power bound,
Pa,minIndicate day electricity sales amount minimum value.
4) above-mentioned purchase sale of electricity Constraints of Equilibrium：
Pb,t=Ps,t+Ploss,t=(1+ α) Ps,t (16)
In formula, Ploss,tFor the total electricity lost in electricity transmission process, α is line loss proportionality coefficient.
(3) since there are the uncertainty that next day user power utilization and future market potential income are predicted, power purchase sides for sale of electricity side
There are the uncertainty of spot market electricity price, these enchancement factors cause sale of electricity company to need in purchase of electricity decision to uncertain
Sexual factor carries out risk assessment, to minimize the market risk.CVaR indexs overcome variance, VaR assesses the one of risk
A little defects, in terms of being widely applied to Electricity market risk assessment.
According to the sale of electricity company purchase of electricity deterministic control model that step (2) is established, consider that there are next day users for sale of electricity side
The uncertainty of electricity consumption and the prediction of future market potential income, there are the uncertainties of spot market electricity price for power purchase side, in this base
It is established on plinth and considers probabilistic sale of electricity company purchase of electricity risk control model, including：
1) it sets certain return on assets and meets normal distribution N (μ, σ2) under the premise of model, the parsing meter of the opposite CVaR of assets
Formula is calculated to be shown below：
In formula, β is confidence level,For the probability density function of (1,0) standardized normal distribution N, Φ-1(β) is standard normal
It is distributed the upside β quantiles of N (1,0).
2) above-mentioned next day user power utilization, the probability distribution of future market potential income and grid company spot market electricity price
For normal distribution, i.e.,：
In formula,WithFor next day user power utilization, the reality of future market potential income and spot market electricity price
Value, σP、σρAnd σBRespectively electricity sales amount, purchases strategies, latency influence the standard deviation of coefficient probability distribution, and three parameters
Between independently of each other.
3) user power utilization error is introduced with after the electricity price error of spot market, and sale of electricity company actual profit is represented by：
In formula,
It can obtain, sale of electricity company benefit meets：
B~N (E (B), σ2) (21)
Wherein, the expression formula of sale of electricity company expected revenus E (B) and risk quantifier CVaR (B) are as follows：
Based on the Risk Model, sale of electricity company purchase of electricity Risk Decision-making Model is established, wherein object function can
It is expressed as：
MaxW (B)=E (B)-λ CVaR (B) (25)
In formula, λ is the risk averse factor, and E (B) is sale of electricity company expected revenus, and CVaR (B) is risk quantifier.
The constraints of optimization problem (25) has (6), (13-16).
(4) sale of electricity company purchase of electricity risk control flow.
It includes three steps that sale of electricity company, which participates in ahead market,：
A) next day spot market electricity price and estimation parameter fluctuation situation are predicted according to historical data；
B) sale of electricity company interacts with user, controls optimal purchase of electricity；
C) sale of electricity company reports end user's load curve.
Photos and sending messages are for all users under sale of electricity company Agent, therefore can be transmitted and be believed to user by broadcast mode
Breath；User interface Agent upload information includes load data, it is therefore desirable to encrypted transmission.In purchase of electricity control flow, user
Agent uploads content twice altogether, the load curve of second feedback can reduce the deviation due to model and caused by load it is poor
It is different, make sale of electricity company report curve closer to next day practical electricity consumption, reduces the loss that uneven electricity is brought to sale of electricity company.
If final optimization pass curve and the curve being calculated by user's elastic information have larger gap, the User interface Agent need to
Family model data is updated, but sale of electricity company Agent no longer re-starts price policy, negative with the network for reducing MAS systems
Load.
The electricity price decision process of sale of electricity company is as shown in Fig. 2, the solution of wherein formula (25) model is the pass of this method application
Key.The model is nonlinear programming problem, and decision variable is the hour electricity price of 24 periods, and chaotic particle swarm optimization calculation can be used
Method solves it.
In conclusion the purchase of electricity risk control side of sale of electricity company based on multi-agent system that the embodiment of the present invention is established
Method has fully considered the purchase sale of electricity of sale of electricity company and to expected future based on the formulation for solving the problems, such as sale of electricity company purchase of electricity
Uncertainty, establish sale of electricity company purchase of electricity risk control method, solved using Chaos particle swarm optimization algorithm, carried for sale of electricity company
For optimal purchase of electricity.
Embodiment 3
Feasibility verification is carried out to the scheme in Examples 1 and 2 with reference to specific example, it is described below：
The forecasted electricity market price of grid company spot market is as shown in Figure 3.Customer parameter is subject to according to typical intelligent power user
Setting.The sale of electricity company same day possesses 30,000 family of user altogether, and the total userbase in region is 60,000 families.Load demand elasticity coefficient is by user
Agent is calculated for the historical data in one period.Each moment power constraint bound of sale of electricity company be set as 20MW with
40MW, initial electricity price is set as 50/MWh after conversion, and price bound is set as 40/MWh and 120/MWh, is always sold in one day
Electricity is not less than the 70% of initial quantity of electricity；α takes 0.05, and confidence level β takes 0.95.
It is programmed using Matlab and carries out model solution, chaos intialization is carried out to 100 particles, final selection 50 is more excellent
Primary optimizes solution.The factor for influencing sale of electricity managing performance purchase of electricity includes customer parameter and sale of electricity company parameter,
Pricing strategy will be analyzed in terms of the two below.
1) user's factor influences.
Fig. 4 and Fig. 5 be set forth sale of electricity company total benefit and CVaR with the practical electricity consumption of user and theoretical electricity consumption it
Between error percentage fluctuation variance between relationship.As can be seen that when mono- timings of λ, with σPIncrease, the sale of electricity corporate income phase
Prestige is gradually reduced, and CVaR gradually increases.This is because when mono- timings of λ, σPIncreasing leads to the increase of Trading risk, the purchase of sale of electricity company
Electricity strategy tends to be conservative, and electricity is sold in reduction, and income is caused to reduce.σPIncrease makes sale of electricity company avoid risk, and CVaR is whole
Or it is in increase tendency.
2) sale of electricity company factor influences.
Power purchase price expectation error, B mainly study in sale of electricity company factor(0)Influence and B of the error to sale of electricity income(0)Greatly
The small influence to sale of electricity price.Fig. 6 has studied B(0)The influence for the electricity price that pair can make decisions on one's own, is divided into 5 scenes, it can be seen that with
B(0)Be continuously increased, electricity price reduce amplitude it is increasing, until close to minimum electricity price limitation, this is because with potential receipts
The increase of beneficial ratio, sale of electricity company formulate electricity price and are more likely to low electricity price to attract more users to be added to the sale of electricity company.Fig. 7
It can be seen that working as B(0)When fluctuation is smaller, sale of electricity corporate income is with σρIncrease first increases and then decreases (σBMonotone decreasing when being 0)；
It illustrates in range, with σBIncrease, sale of electricity corporate income only with σρIncrease and increases.This is by σρWith σBTo the shadow of purchase of electricity
Caused by ringing on the contrary, σρIncrease can cause sale of electricity company pass through promoted sale of electricity price reduce purchase of electricity, σBIncrease can cause to sell
Electric company formulates lower sale of electricity price, and the two acts on electricity price opposite.Note does not consider optimal sale of electricity price when risk factors
For ρop, the two acts on simultaneously so that electricity price occurs first close to ρopAfterwards far from ρopThe case where, cause income appearance first to increase reduces afterwards
The case where.Work as σBWhen larger, the case where only growth, this is by σBProportion is too big, so that in σρReach research range most
When big value, can not still it make electricity price far from ρopCaused by.
Bibliography：
[1] sale of electricity company purchase sale of electricity strategy study [D] Shanghai Communications Universitys under Luo Qin market environments, 2014.
[2] Agent system of Baily Fermi Buddhist nun, Cairo, Green's Wood based on JADE develops [M] Cheng Zhi cutting edges of a knife or a sword, waits and translates
Beijing：National Defense Industry Press, 2013.
It will be appreciated by those skilled in the art that attached drawing is the schematic diagram of a preferred embodiment, the embodiments of the present invention
Serial number is for illustration only, can not represent the quality of embodiment.
The foregoing is merely presently preferred embodiments of the present invention, is not intended to limit the invention, it is all the present invention spirit and
Within principle, any modification, equivalent replacement, improvement and so on should all be included in the protection scope of the present invention.
Claims (7)
1. it is a kind of the placing separate environment under sale of electricity company power purchase amount control method, which is characterized in that the control method include with
Lower step：
Three layers of purchase sale of electricity clothes of grid company-sale of electricity company-user are established according to sale of electricity company Agent and User interface Agent
Business framework；Based on three layers of purchase sale of electricity service architecture, build by uncontrollable load, the group of transferable load and variable dynamic load
At user's electricity elastic model；
According to user's electricity price elastic model, the operation of sale of electricity company and assessment parameter, sale of electricity company purchase of electricity control mould is established
Type, the model include：It is up to object function with the sum of sale of electricity company sale of electricity income and potential income, considers market stability respectively
Constraint, purchase sale of electricity Constraints of Equilibrium.
2. a kind of the placing according to claim 1 separates sale of electricity company power purchase amount control method under environment, which is characterized in that
The sale of electricity company Agent turns to target after receiving all customer charge information according to number one maximum
Purchase of electricity optimisation strategy is formulated, and the purchase of electricity finally predicted is reported into grid company.
3. a kind of the placing according to claim 1 separates sale of electricity company power purchase amount control method under environment, which is characterized in that
The User interface Agent is interacted for passing through physical interface with intelligent power equipment, realizes the intelligence control to equipment
System；
The User interface Agent is additionally operable to the information based on history consumption habit information or setting, predicts that the electricity consumption of next day user is bent
Line and demand elasticity parameter, polymerize customer charge data, and are reported to sale of electricity company Agent；
The User interface Agent is additionally operable to the zero potential energy information issued based on sale of electricity company, and optimizing the use of itself can plan, real
The energy management at current family.User interface Agent can be applied to industry, business and resident load.
4. a kind of the placing according to claim 1 separates sale of electricity company power purchase amount control method under environment, which is characterized in that
User's electricity elastic model is specially：
In formula：Hop count when I is total,Indicate that each moment benchmark electricity prices of user k areWhen user day
Electricity consumption curve, WkIt is and the relevant matrix of user's electricity price elasticity；Indicate that load m is initially used
Electricity vector；EmFor power load Price elasticity matrix；For electricity price vector.
5. a kind of the placing according to claim 1 separates sale of electricity company power purchase amount control method under environment, which is characterized in that
The market stability constrains：
ρsmin≤ρs,t≤ρsmax
Pbmin≤Pb,t≤Pbmax
In formula, ρsmin、ρsmaxRespectively hour electricity price bound a few days ago, ρbmin、ρbmaxRespectively power purchase power bound, Pa,min
Indicate that day electricity sales amount minimum value, T are decision period set, T=[1,2 ..., I].
6. a kind of the placing according to claim 1 separates sale of electricity company power purchase amount control method under environment, which is characterized in that
The purchase sale of electricity Constraints of Equilibrium is specially：
Pb,t=Ps,t+Ploss,t=(1+ α) Ps,t
In formula, ρs,tFor the hour electricity price a few days ago of formulation, Ploss,tFor the total electricity lost in electricity transmission process, α is line loss ratio system
Number.
7. a kind of the placing according to claim 1 separates sale of electricity company power purchase amount control method under environment, which is characterized in that
The control method further includes：
Sale of electricity company Agent transmits information by broadcast mode to user；User interface Agent upload information includes load data, because
This needs encrypted transmission.
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| CN109193623A (en) * | 2018-09-10 | 2019-01-11 | 广东工业大学 | A kind of ahead market and Real-time markets combined optimization method of combination electric car |
| CN109492905A (en) * | 2018-11-08 | 2019-03-19 | 四川大学 | A kind of controllable resources control method based on purchase of electricity transfer |
| CN111144657A (en) * | 2019-12-27 | 2020-05-12 | 国网辽宁省电力有限公司 | Multi-family energy optimization method for two parties for cooperative sale and use |
| CN112257994A (en) * | 2020-10-08 | 2021-01-22 | 国家电网公司华中分部 | Cross-provincial electricity quantity base transaction method capable of coordinating multiple time scales |
| CN112465303A (en) * | 2020-11-06 | 2021-03-09 | 上海交通大学 | Multi-agent-based bilateral power market optimization decision method considering demand response |
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| CN109193623A (en) * | 2018-09-10 | 2019-01-11 | 广东工业大学 | A kind of ahead market and Real-time markets combined optimization method of combination electric car |
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| CN112257994A (en) * | 2020-10-08 | 2021-01-22 | 国家电网公司华中分部 | Cross-provincial electricity quantity base transaction method capable of coordinating multiple time scales |
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| CN112465303A (en) * | 2020-11-06 | 2021-03-09 | 上海交通大学 | Multi-agent-based bilateral power market optimization decision method considering demand response |
| CN114926213A (en) * | 2022-05-26 | 2022-08-19 | 北京中电普华信息技术有限公司 | Electricity purchasing information determining method and device based on proxy electricity purchasing |
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