CN107220889A - The distributed resource method of commerce of microgrid community under a kind of many agent frameworks - Google Patents
The distributed resource method of commerce of microgrid community under a kind of many agent frameworks Download PDFInfo
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Abstract
The present invention relates to a kind of distributed resource method of commerce of microgrid community under many agent frameworks, including three layers of iterative electricity price clearance, first layer:The optimization of microgrid internal operation is calculated；The second layer:Assemble the optimization of business's internal schedule to calculate；Third layer:The transaction assembled between business is calculated.Each layer of three layers of iterative calculating all carries out Spot Price clearance, by local to overall, seek microgrid, aggregation business, the maximizing the benefits of microgrid community respectively, in each stage of iteration, the distributed resource owner and aggregation business can be transferred through method proposed by the present invention and calculate profit so that market clearing process becomes apparent from.Distributed resource configuration of this pattern while all participant in the market's interests are ensured in optimization microgrid community, reaches the purpose for ensuring the security of each microgrid, ensureing the reasonable income of the distributed resource owner and the whole machine balancing ability by price incentive lifting regenerative resource.
Description
Technical field
The present invention relates to resource allocation and electricity market field, and in particular to point of microgrid community under a kind of many agent frameworks
Cloth resource transaction method.
Background technology
Attention and a series of appearance of policies with country to regenerative resource, distribution type renewable energy have welcome height
Speed development.Because distribution type renewable energy is directly accessed power network, the problems such as easily triggering overvoltage, obstruction, it generates electricity out in addition
Power randomness and fluctuation are by force and load simultaneity factor is poor, and grid company takes all kinds of limitation distribution type renewable energies online
Measure, causes and largely abandons generated energy.
Microgrid community is connected to the microgrid collection that same feeder line and microgrid comprising distributed resource (DER) are constituted by multiple
Distributed resource (DER) in group, microgrid community not only includes distribution type renewable energy unit (Distributed
Generator, DG), in addition to energy-storage system (Energy Storage System, ESS) and flexible load (Price-
Responsive Load, PRL)；And microgrid community can realize that the autonomous of self-contr ol, protection and management is as a kind of
System, can both run with external electrical network, can also isolated operation, therefore it is more flexible to dissolving for distributed energy, more
Efficiently.
In recent years, microgrid community is controlled in power-balance control, running Optimization, default detection and protection, the quality of power supply
Critical technological break-through is achieved in terms of reason, such as how marketized tools are ensureing distributed energy spirit in microgrid community
Live and seek the maximizing the benefits for participating in each side on the premise of dissolving, the multi-party autonomous participation of excitation, it has also become microgrid Community Commercial mould
The important directions of formula research.
The content of the invention
The distributed resource that the technical problems to be solved by the invention are to provide microgrid community under a kind of many agent frameworks is handed over
Easy method, so that distributed resource adapts to the uncertainty of regenerative resource by runing with transaction, ensures that all markets are participated in
Optimize the distributed resource configuration in microgrid community while person's interests, reaching ensures the security of each microgrid, ensures distribution
The reasonable income of formula Resource Owner and by price incentive lifted regenerative resource whole machine balancing ability purpose.
The technical scheme that the present invention solves above-mentioned technical problem is as follows：
The distributed resource method of commerce of microgrid community, comprises the following steps under a kind of many agent frameworks：
First layer:Microgrid internal operation optimizes：
Step 1：According to each independent micro-grid in micro-grid system and the market information of aggregation business, the profit of each independent micro-grid is set up
Maximum target function, DG marginal cost functions, ESS marginal returns model and PRL marginal return models, and calculate each independent micro-grid
Spot Price；
Step 2：Clear Spot Price：Whether the Spot Price for each independent micro-grid that judgment step 1 is obtained meets microgrid hair
The equilibrium of supply and demand condition dissolved inside electricity, if be unsatisfactory for, corrects Spot Price for mark post rate for incorporation into the power network or major network electricity price,
Obtain the Spot Price of each independent micro-grid；
The second layer:Assemble the optimization of business's internal schedule：
Step 3：Find out the maximum of each independent micro-grid Spot Price that each aggregation business that first layer obtains is controlled with most
Small value；
Step 4：Each independent micro-grid Spot Price maximum that each aggregation business obtained according to step 3 is controlled and minimum
Value, calculates arithmetic average as the Spot Price initial value of each aggregation business；
Step 5：The initial value of each aggregation business's Spot Price is substituted into object function and the aggregation business of aggregation business's profit maximization
The constraints of the internal equilibrium of supply and demand starts iteration, constantly amendment aggregation business's Spot Price, until uneven work(inside aggregation business
Rate terminates iteration when being 0, obtains each aggregation optimal Spot Price of business；
Third layer:Assemble the method for commerce between business：
Step 6：Calculate the sales rate of electricity of all independent micro-grids of each aggregation business control and purchase electricity price in microgrid community；
Step 7：Highest in the independent micro-grid of each aggregation business control is bought into electricity price as the purchase electricity price of aggregation business,
Using minimum sales rate of electricity as aggregation business sales rate of electricity；
Step 8：The purchase electricity price and sales rate of electricity of relatively more each aggregation business, if the purchase electricity price of a certain aggregation business is higher than another
The sales rate of electricity of one aggregation business, then the two aggregation business strike a bargain and transaction value cleared purchase electricity price and sales rate of electricity for this
Arithmetic average, and update the sales rate of electricity and purchase electricity price of each independent micro-grid participated in business；Otherwise terminate.
The beneficial effects of the invention are as follows：
(1) marginal cost function for the distribution type renewable energy that the present invention is set up, has quantified distribution type renewable energy
Uncertainty.
(2) the energy-storage system optimum value curve values that the present invention is set up, realize the discharge and recharge of energy storage being worth decoupling, can
To provide algorithm support for the real-time charge and discharge strategy of energy storage.
(3) present invention establishes a kind of three layers of iterative interactive market, and this new market has concurrently micro- there is provided one kind
The high applicability mechanism of exchange of net physical characteristic and aggregation business's nature of business.In each iteration phase, the distributed resource owner
With polymerization business can be transferred through set forth herein scheme calculate profit so that market clearing process becomes apparent from.This pattern is being protected
Distributed resource configuration while hindering all participant in the market's interests in optimization microgrid community, reaching ensures the peace of each microgrid
Quan Xing, the reasonable income for ensureing the distributed resource owner and the whole machine balancing energy that regenerative resource is lifted by price incentive
The purpose of power.
(4) business operation model proposed by the present invention is conducive to optimizing the configuration of the distributed resource in microgrid community, side
Help distributed resource owner's addressing constant volume and select aggregation business.Assemble business based on the distributed resource that it is managed,
Inside optimizes operation, and energy transaction is carried out between different aggregation business, makes the distributed money in whole microgrid community scope
Source operating mode has Best Economy.
On the basis of above-mentioned technical proposal, the present invention can also do following improvement.
Further, the maximum profit object function of each independent micro-grid of the step 1 is converted by marketing economics principle
For：
Wherein, qi schRepresent the estimated consumption power of PRL in i-th of microgrid, qi ESSAnd qi DGRepresent respectively in i-th of system
EES and DG demand response, qloadThe workload demand response in i-th of microgrid is represented, pi spot represent the reality of i-th of system
When electricity price.
Beneficial effect using above-mentioned further scheme is：The uncertainty of distribution type renewable energy is quantified, has been based on
This sets up the marginal cost function of distribution type renewable energy.
Further, the DG marginal cost function method for solving of the step 1 is：It is close according to the DG probability actually exerted oneself
Degree, it, which is quadratured, to calculate to exert oneself can not meet the risk probability function F that aggregation business requiresDG, export its corresponding anti-letter
Count, its marginal cost function expression formula is：
Wherein, PspotIt is real time price, PDNOIt is the price that electricity is bought from DNO, kpenIt is point penalty coefficient.
Further, the ESS marginal return models of the step 1 are the storages of the discharge and recharge value decoupling based on ESS and foundation
Energy system balancing worth curve, the profit of discrete charge/discharge action is reflected with SOC value：
ESS operation control strategy and charging and discharging state SOC and Spot Price pspotRelation fESS() represents such as
Under：
qESS=fESS(SOC,pspot)
Wherein, qESSIt is the target adjustment power of ESS in unit scheduling time inter, implements after adjustment, ESS states updates
It is as follows：
SOC+=qESS+SOC
0=fESS(SOC+,pspot)
Wherein, SOC+It is the SOC, SOC after optimization+With Spot Price pspotRelation be expressed as：
SOC+=FESS(pspot)
Beneficial effect using above-mentioned further scheme is：What the function reflected is SOC worth curve, net with the producer
The difference that remaining computational methods try to achieve producer's net surplus of whole story state correspondence position is exactly ESS individually charging action/electric discharges
The profit of action, is achieved in the decoupling of ESS discharge and recharges value.
Further, the PRL marginal return models in the step 1 are：
qload=(pspot/psch)εqsch
Wherein, ε is Price elasticity coefficient, qloadIt is PRL actual power consumption, pspotIt is Spot Price, qschIn being microgrid
PRL estimated consumption power.
Beneficial effect using above-mentioned further scheme is：Work as pspotIt is not equal to pschWhen, it can use with seeking ESS profits
Similar method, the difference with regard to producer's net surplus between any two time point on PRL worth curves can obtain PRL and need
Seek the profit of response.
Further, whether the Spot Price for each independent micro-grid that judgment step 1 is obtained meets microgrid generating in the step 2
The internal equilibrium of supply and demand condition dissolved of amount, it is with electricity price constraint representation：
pinj＜ pspot＜ pgrid
Wherein, pinjRepresent online stake electrovalence, pspotIt is Spot Price, pgridIt is the power purchase price of major network.
Further, the profit maximization object function of aggregation business is in the step 5：
Wherein, Pi (t) represents the profit of each elastic load PRL in the microgrid community that aggregation business controls, PM ESS (t) and CM
DG (t) represents large-scale ESS profit and large-scale DG cost respectively, because each microgrid has different Spot Price pi spot,
Therefore, the object function, which is converted to, finds the side that pi spot points make aggregation business inside imbalance power Δ qAGG sum be equal to 0
Journey：
Wherein, Δ qAGG sum are represented to assemble the imbalance power inside business, and qM ESS (t) and qM DG (t) are represented respectively
ESS and DG demand response that aggregation business is controlled, Δ qiRepresent the workload demand response of the PRL in i-th of microgrid, pi spotTable
Show the Spot Price of i-th of microgrid, pMGC spot represent microgrid community Spot Price.
Beneficial effect using above-mentioned further scheme is：The overall unbalanced power problem of business will be assembled and be converted into its control
The unbalanced power problem of each microgrid of system, and the object function of multivariable is converted into simply using Spot Price to be single
The simple target function of one variable, calculating is simplified.
Further, the step 6 calculate in microgrid community the sales rate of electricity of all independent micro-grids of each aggregation business control with
Buying electricity price detailed process is：
According to the imbalance power Δ q in microgrid community Spot Price pMGC spot and microgridiBetween corresponding relation：
Wherein, SOC is the existing capacity of energy-storage system, qESSIt is the target adjustment work(of ESS in unit scheduling time inter
Rate, SOC+It is the SOC, p after optimizationi spotRepresent the Spot Price of i-th of microgrid, pi schAnd q (t)i sch(t) represent respectively i-th
PRL planned price and planned supply and use of electric power amount, P in microgridi ESSAnd P (t)i DR(t) represent that EES and demand are rung in i-th of system respectively
The profit answered, Ci DG(t) cost of DG in i-th of microgrid, q are representedi schThe estimated consumption power of PRL in i-th of microgrid is represented,
qi ESSAnd qi DGThe demand response of EES and DG in i-th of system, q are represented respectivelyi loadRepresent that the workload demand of i-th of microgrid rings
Should, Δ qiThe imbalance power of i-th of microgrid is represented, pAGG spot represent to assemble business's Spot Price, kchaRepresent charge coefficients.
By microgrid community Spot Price and the pMGC spot and imbalance power Δ q in microgridiBetween correspondence pass
System is designated as：
Obtained according to the corresponding relation：
Wherein,The sales rate of electricity of i-th of microgrid is represented,The purchase electricity price of i-th of microgrid is represented, x represents micro-
The net electricity for producing or using less more.
Further, the step 8 is expressed as with mathematical linguistics：
Invalid and Δ qj=0 sets up.
Pi sell and pibuy are the sales rates of electricity and purchase electricity price, Δ q of i-th of aggregation businessjIt is the injustice of j-th of microgrid
Weigh power.
It is with simple price and imbalance power constraint representation microgrid using the beneficial effect of above-mentioned further scheme
Do not assemble that distributed resource concluded price is reached an agreement in the microgrid that business controls with regard to it and each microgrid reaches again in community again
New power-balance state.
Brief description of the drawings
Fig. 1 is the applicable microgrid community structure of the present invention；
Fig. 2 is flow chart of the method for the present invention；
Fig. 3 is the distributed power generation unit DG of present invention cost of electricity-generating curve；
Fig. 4 is the energy-storage system ESS of present invention prediction optimum value curve；
Fig. 5 is the flexible load PRL of present invention demand response curve；
The change schematic diagram of microgrid electricity price when Fig. 6 is assembles business's interior optimization in the present invention；
Fig. 7 is the market structure for the microgrid community being applicable in the present invention.
Embodiment
The principle and feature of the present invention are described below in conjunction with accompanying drawing, the given examples are served only to explain the present invention, and
It is non-to be used to limit the scope of the present invention.
For microgrid community system as shown in Figure 1, the present invention is under multi-agent system framework, using three suboptimization, three
The method of secondary clearance.Establish a kind of three layers of interactive market using alternative and iterative algorithm as core herein, three stacking generations it is each
Layer all carries out Spot Price clearance, and microgrid, aggregation business, the maximizing the benefits of microgrid community are sought respectively to overall by local,
Each stage of iteration, the distributed resource owner and aggregation business can be transferred through set forth herein method calculate profit so that
Market clearing process becomes apparent from, so that distributed resource adapts to the uncertainty of regenerative resource by runing with transaction, together
When network structure there is good autgmentability.Similar to sharing economy pattern, the owner of distributed resource can select any
Qualified aggregation business carrys out working balance as agency by agreement business.Agent is based on the distributed resource that it is managed, inside
Portion optimizes operation, and energy transaction is carried out between agent, so that the distributed resource operation in whole microgrid community scope
Mode has Best Economy.In order to ensure each microgrid security, ensure the reasonable income, simultaneously of the distributed resource owner
The energy trading scheme proposed in the whole machine balancing ability of regenerative resource, text is lifted by price incentive to ensure all
Participant in the market's interests, meanwhile, the distributed resource configuration in optimization microgrid community, this is to promoting the commercialization in microgrid community
Autonomous operation is significant.
With reference to Fig. 2 method flow, illustrate the specific implementation method of this method：
First layer --- microgrid internal operation optimizes：
Step 1：All microgrids and agential market information in micro-grid system are obtained, for each independent micro-grid, is set up
Its maximum profit object function and its DER included marginal cost, marginal return constraints, solve the optimal fortune of the microgrid
Spot Price under the conditions of row.The Optimized Operation scheme of microgrid is by the limit of DG marginal cost, PRL marginal return and EES
Profit is determined.Because large-scale energy-storage system (MESS) and large fan (MWT) are directly connected to main feeder, this suboptimum is not involved in
Change.Therefore, the object function of microgrid maximum profit is represented by：
DG marginal cost can be represented by exporting the inverse function of its default risk probability-distribution function：
Wherein PspotIt is Spot Price.PDNOIt is the price that electricity is bought from DNO, kpenThe point penalty coefficient referred to, this is
Number is set as 2 herein.
As shown in figure 3, DG marginal cost is simply set up as constant in this research, but k is arrived 0pen·PDNO
In the range of change.According to the general principle of electricity market, when unit marginal cost is equal to real time price, exerting oneself for DG is optimal
(maximum profit).
ESS strategy is relevant with charging and discharging state (SOC) and real-time real time price, and its relation can use following relational expression
Represent：
qESS=fESS(SOC,pspot) (3)
Wherein qESSIt is the discharge and recharge of ESS in unit scheduling time inter.Implement after discharge and recharge adjustment, ESS states update
It is as follows：
SOC+=qESS+SOC (4)
0=fESS(SOC+,pspot) (5)
Wherein SOC+It is the SOC after optimization.The SOC in given model+And pspotIt is negatively correlated.The two variables
Relation can be expressed as：
SOC+=FESS(pspot) (6)
In the formula, larger pspotValue corresponds to less SOC+.Without loss of generality, Fig. 4 can be used to simplify
Shown linear function represents the parity value curve of (6) formula：
As shown in figure 4, the real time price p that SOC value corresponds at point 1spot,1.It can be obtained to formula (5) by formula (3), when real-time valency
Lattice are by pspot,1Change into pspot,2, also response comes a little 2 to SOC therewith.Parity value curve illustrates the corresponding values of SOC, fills
Electric cost is pspot,2.Therefore, the expected charging profit from point 1 to point 2 can be calculated in the following manner：
Formula (7) represents Fig. 3 midpoints 1 to the grid area between point 2.Similarly, when real time price is by pspot,3Change into
pspot,4.Expected electric discharge profit from 3 points to 4 points can be calculated by below equation：
The result of calculation of above-mentioned two formula is the SOC values of decoupling.(as put 1) i.e. when SOC returns to initial point, they
Actual profit be equal to the summation of its expected profit, the i.e. summation of shadow region in Fig. 4.If within the longer time cycle, i.e.,
SOC is set not return to original state, actual profit is also no better than the summation of expected profit.
PRL marginal return can by PRL price elastic coefficientExpression formula integration push away：
qload=(pspot/psch)εqsch (9)
Wherein qschIt is PRL planned supply and use of electric power amount, pspotRepresent Spot Price, pschRepresent anticipated price.Work as pspotIt is not equal to
pschWhen, the curve method of profit is calculated using similar ESS, the profit of PRL demand responses is calculated, as shown in Figure 5.Using above-mentioned
The object function listed can solve the Spot Price under the conditions of microgrid optimized operation with constraints.
Step 2：Clear Spot Price：Whether the microgrid Spot Price tried to achieve in judgment step 1 meets microgrid generated energy
The equilibrium of supply and demand condition that inside is dissolved：
pinJ ＜ pspot＜ pgrid (10)
pinjRate for incorporation into the power network is represented, and the power purchase price of major network is pgrid.If Spot Price is unsatisfactory for inside and dissolved bar
Part, amendment Spot Price is mark post rate for incorporation into the power network or major network electricity price.
Step 3：Step 1,2 are performed to each microgrid in microgrid community, the Spot Price of each independent micro-grid is obtained.
The second layer --- aggregation business internal schedule optimization：
Step 4：Find out the maxima and minima of each microgrid Spot Price that each aggregation business is controlled in step 3：
pmax=max (pi opt),pmin=min (pi opt) (11)
pmaxRepresent Spot Price maximum, p in the microgrid of aggregation business controlminIn the microgrid for representing aggregation business control
Spot Price minimum value, pi optRepresent the optimal Spot Price of each microgrid that clearance is obtained in (3).
Step 5：The arithmetic average of Spot Price maxima and minima in step 4 is taken as the real-time electricity of aggregation business
Valency initial value：
pspot=[pmax+pmin]/2 (12)
pmaxRepresent Spot Price maximum, p in the microgrid of aggregation business controlminIn the microgrid for representing aggregation business control
Spot Price minimum value, pspotRepresent aggregation business's Spot Price.
Step 6：The initial value of aggregation business's Spot Price is substituted into the object function of aggregation business's profit maximization with assembling in business
The constraints of portion's equilibrium of supply and demand starts iteration, constantly amendment aggregation business's Spot Price, until imbalance power inside aggregation business
Untill obtaining 0.
The target for assembling optimized operation inside business is its profit maximization：
Wherein PM ESS (t) and CM DG (t) represent large-scale ESS profit and large-scale DG cost.From formula (1),
After first layer, the power in each microgrid is balance.However, each microgrid has different Spot Price pi spot.Pass through
It is rational to coordinate, the method for operation is adjusted, aggregation business's profit can be increased.Therefore, object function (13) can be converted to searching pi
Spot points make the equation that Δ qAGG sum are equal to 0：
Δ q in formulai(pi spot) represents the uneven electricity of i-th of microgrid.
The uneven electricity of microgrid will produce certain influence to microgrid community.Accordingly, it would be desirable to impose extra charge.This
When, the real time price of i-th of microgrid can be expressed as：
Wherein kchaIt is charge coefficients.
Step 7：Clearance aggregation business's Spot Price：Result after step 6 iteration is optimal aggregation business's Spot Price.
The characteristics of first layer clearance remains microgrid.There is no the second layer calculating process of EES microgrid as shown in fig. 6, wherein DG costs
Curve has only intercepted the part near pi spot.In the microgrid containing EES, corresponding pi can also be found by formula (15)
spot。
Step 8：Step 4,5,6,7 are performed to all aggregation commercial cities in microgrid community, the optimal of each independent aggregation business is obtained
Spot Price.
Third layer --- the method for commerce between aggregation business：
Step 9：Calculate the sales rate of electricity of all microgrids of each aggregation business control and purchase electricity price in microgrid community.According to
The microgrid community Spot Price pMGC spot and imbalance power Δ q in microgridiBetween corresponding relation：
Wherein, SOC is the existing capacity of energy-storage system, qESSIt is the target adjustment work(of ESS in unit scheduling time inter
Rate, SOC+It is the SOC, p after optimizationi spotRepresent the Spot Price of i-th of microgrid, pi schAnd q (t)i sch(t) represent respectively i-th
PRL planned price and planned supply and use of electric power amount, P in microgridi ESSAnd P (t)i DR(t) represent that EES and demand are rung in i-th of system respectively
The profit answered, Ci DG(t) cost of DG in i-th of microgrid, q are representedi schThe estimated consumption power of PRL in i-th of microgrid is represented,
qi ESSAnd qi DGThe demand response of EES and DG in i-th of system, q are represented respectivelyi loadRepresent that the workload demand of i-th of microgrid rings
Should, Δ qiThe imbalance power of i-th of microgrid is represented, pAGG spot represent to assemble business's Spot Price, kchaRepresent charge coefficients.
By microgrid community Spot Price and the pMGC spot and imbalance power Δ q in microgridiBetween correspondence pass
System is designated as：
Obtained according to the corresponding relation：
Wherein,The sales rate of electricity of i-th of microgrid is represented,The purchase electricity price of i-th of microgrid is represented, X represents microgrid
The electricity for producing or using less more.
Step 10：Take highest in the microgrid of aggregation business's control to buy electricity price as the purchase electricity price of aggregation business, take most
Low sales rate of electricity as aggregation business sales rate of electricity：
Pmax=max (pj buy),pmin=min (pj sell) (19)
pmaxAnd pminThe highest purchase electricity price and minimum sales rate of electricity of aggregation business is represented respectively.
Step 11：Compare the purchase electricity price and sales rate of electricity of two different aggregation business, if the purchase electricity of a certain aggregation business
Valency strikes a bargain higher than another sales rate of electricity for assembling business, then the two aggregation business and transaction value is cleared the calculation for the two prices
Number average value.
pspot=(pmax+pmin)/2 (21)
Ph sell and pjbuy. represent the sales rate of electricity and purchase electricity price of two aggregation business respectively, and both electricity prices are being handed over
If the form of expression at easy center as shown in fig. 7, many productions of microgrid or use x electricity less, the method for operation is corresponding optimal
Price will bring up to pi sell.And if few production of microgrid or use x electricity, then the corresponding most favorable rates of the method for operation
Lattice will be reduced to pibuy.The two electricity prices can directly be obtained by formula (17), (18).
Step 12：The sales rate of electricity and purchase electricity price for the microgrid participated in business are updated, repeat step 9,10,11 is until step
Terminate to calculate when terms of trade are invalid in 11：
Often once merchandised, the microgrid of conclusion of the business just update an imbalance power Δ q and recalculate ph sell and
Pj buy value, untilInvalid and Δ qj=0 terminates to calculate when setting up.Pi sell and
Pibuy is the sales rate of electricity and purchase electricity price, Δ q of i-th of aggregation businessjIt is the imbalance power of j-th of microgrid.Now microgrid society
Qu Zhongzai does not assemble that distributed resource concluded price is reached an agreement in the microgrid that business controls with regard to it and each microgrid has reached newly again
Power-balance state, now whole microgrid community converge to optimal running status.
The step 7 and step 10 of the present invention has cleared the Spot Price of aggregation business, sales rate of electricity and purchase electricity price respectively, this
Three electricity prices substantially reflect the market competitiveness of aggregation business, are also a kind of price incentive for the DER owners, right
The suitable aggregation Shang dynasty reason of DER owners selection has important directive significance.
The method of commerce that the present invention is provided substantially proposes one kind and has microgrid physical characteristic and aggregation business's nature of business concurrently
High applicability market mechanism.This market mechanism can not only ensure micro- under existing distributed resource (DER) configuration condition
Community's optimized operation is netted, farthest ensures that the benefit of the DER owners and aggregation Shang Deng each side is optimal, while in this market
The scheduling controlling scheme produced under mechanism can also instruct later stage DER to configure to more rationally more efficient beneficial direction is developed, therefore
Its configuring to microgrid community also has important practical meaning.
The interactive market of three layers using iterative algorithm as core that the present invention is set up, it is intended to ensure all participant in the market's interests
While optimization microgrid community in distributed resource configuration, reaching ensures the security of each microgrid, ensures distributed resource
The reasonable income of the owner and by price incentive lifted regenerative resource whole machine balancing ability purpose.
The foregoing is only presently preferred embodiments of the present invention, be not intended to limit the invention, it is all the present invention spirit and
Within principle, any modification, equivalent substitution and improvements made etc. should be included in the scope of the protection.
Claims (8)
1. the distributed resource method of commerce of microgrid community under a kind of many agent frameworks, it is characterised in that comprise the following steps：
First layer:Microgrid internal operation optimizes：
Step 1：According to each independent micro-grid in micro-grid system and the market information of aggregation business, the maximum profit of each independent micro-grid is set up
Object function, DG marginal cost functions, ESS marginal returns model and PRL marginal return models, and calculate the reality of each independent micro-grid
When electricity price；
Step 2：Clear Spot Price：Whether the Spot Price for each independent micro-grid that judgment step 1 is obtained meets microgrid generated energy
The equilibrium of supply and demand condition that inside is dissolved, if be unsatisfactory for, amendment Spot Price is mark post rate for incorporation into the power network or major network electricity price, is obtained
The Spot Price of each independent micro-grid；
The second layer:Assemble the optimization of business's internal schedule：
Step 3：Find out the maxima and minima for each independent micro-grid Spot Price that each aggregation business that first layer obtains is controlled；
Step 4：Each independent micro-grid Spot Price maxima and minima that each aggregation business obtained according to step 3 is controlled, meter
Arithmetic average is calculated as the Spot Price initial value of each aggregation business；
Step 5：The initial value of each aggregation business's Spot Price is substituted into the object function of aggregation business's profit maximization with assembling inside business
The constraints of the equilibrium of supply and demand starts iteration, constantly amendment aggregation business's Spot Price, until imbalance power is 0 inside aggregation business
When terminate iteration, obtain it is each aggregation the optimal Spot Price of business；
Third layer:Assemble the method for commerce between business：
Step 6：Calculate the sales rate of electricity of all independent micro-grids of each aggregation business control and purchase electricity price in microgrid community；
Step 7：Highest in the independent micro-grid of each aggregation business control is bought into electricity price as the purchase electricity price of aggregation business, will most
Low sales rate of electricity as aggregation business sales rate of electricity；
Step 8：The purchase electricity price and sales rate of electricity of relatively more each aggregation business, if the purchase electricity price of a certain aggregation business is poly- higher than another
Collect the sales rate of electricity of business, then the two aggregation business strike a bargain and transaction value is cleared purchase electricity price and sales rate of electricity for this and count
Average value, and update the sales rate of electricity and purchase electricity price of each independent micro-grid participated in business；Otherwise terminate.
2. the distributed resource method of commerce of microgrid community under many agent frameworks according to claim 1, it is characterised in that
The maximum profit object function of each independent micro-grid of the step 1 is converted into by marketing economics principle：
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Wherein, qi schRepresent the estimated consumption power of PRL in i-th of microgrid, qi ESSAnd qi DGEES in i-th of system is represented respectively
With DG demand response, qloadThe workload demand response in i-th of microgrid is represented, pi spot represent the real-time electricity of i-th of system
Valency.
3. the distributed resource method of commerce of microgrid community under many agent frameworks according to claim 1, it is characterised in that
The DG marginal cost function method for solving of the step 1 is：According to the DG probability density actually exerted oneself, calculating of being quadratured to it
The risk probability function F that aggregation business requires can not be met by exerting oneselfDG, export its corresponding inverse function, its marginal cost function
Expression formula is：
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Wherein, PspotIt is real time price, PDNOIt is the price that electricity is bought from DNO, kpenIt is point penalty coefficient.
4. the distributed resource method of commerce of microgrid community under many agent frameworks according to claim 1, it is characterised in that
The ESS marginal return models of the step 1 are the energy-storage system parity value songs of the discharge and recharge value decoupling based on ESS and foundation
Line, the profit of discrete charge/discharge action is reflected with SOC value：
ESS operation control strategy and charging and discharging state SOC and Spot Price pspotRelation fESS() is expressed as follows：
qESS=fESS(SOC,pspot)
Wherein, qESSIt is the target adjustment power of ESS in unit scheduling time inter, implements after adjustment, ESS states updates as follows：
SOC+=qESS+SOC
0=fESS(SOC+,pspot)
Wherein, SOC+It is the SOC, SOC after optimization+With Spot Price pspotRelation be expressed as SOC+=FESS(pspot)。
5. the distributed resource method of commerce of microgrid community under many agent frameworks according to claim 1, it is characterised in that
PRL marginal return models in the step 1 are：
qload=(pspot/psch)εqsch
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Wherein, ε is Price elasticity coefficient, qloadIt is PRL actual power consumption, pspotIt is Spot Price, qschIt is PRL in microgrid
It is expected that consumption power.
6. the distributed resource method of commerce of microgrid community under many agent frameworks according to claim 1, it is characterised in that
Whether the Spot Price for each independent micro-grid that judgment step 1 is obtained meets the confession dissolved inside microgrid generated energy in the step 2
Equilibrium condition is needed, it is with electricity price constraint representation：
pinj＜ pspot＜ pgrid
Wherein, pinjRepresent online stake electrovalence, pspotIt is Spot Price, pgridIt is the power purchase price of major network.
7. the distributed resource method of commerce of microgrid community under many agent frameworks according to claim 1, it is characterised in that
The profit maximization object function of aggregation business is in the step 5：
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Wherein, Pi (t) represents the profit of each elastic load PRL in the microgrid community that aggregation business controls, PMESS (t) and CM DG
(t) large-scale ESS profit and large-scale DG cost are represented respectively, because each microgrid has different Spot Price pi spot, because
This, the object function, which is converted to, finds the side that pi spot points make aggregation business inside imbalance power Δ qAGG sum be equal to 0
Journey：
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The Spot Price of i microgrid, pMGC spot represent microgrid community Spot Price.
8. the distributed resource method of commerce of microgrid community under many agent frameworks according to claim 1, it is characterised in that
The step 6 calculates the sales rate of electricity of all independent micro-grids of each aggregation business control and purchase electricity price detailed process in microgrid community
For：
According to the imbalance power Δ q in microgrid community Spot Price pMGC spot and microgridiBetween corresponding relation：
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<msubsup>
<mi>p</mi>
<mrow>
<mi>s</mi>
<mi>p</mi>
<mi>o</mi>
<mi>t</mi>
</mrow>
<mrow>
<mi>A</mi>
<mi>G</mi>
<mi>G</mi>
</mrow>
</msubsup>
<mo>+</mo>
<msub>
<mi>k</mi>
<mrow>
<mi>c</mi>
<mi>h</mi>
<mi>a</mi>
</mrow>
</msub>
<mo>&CenterDot;</mo>
<msup>
<mi>&Delta;q</mi>
<mi>i</mi>
</msup>
<mrow>
<mo>(</mo>
<msubsup>
<mi>p</mi>
<mrow>
<mi>s</mi>
<mi>p</mi>
<mi>o</mi>
<mi>t</mi>
</mrow>
<mi>i</mi>
</msubsup>
<mo>)</mo>
</mrow>
</mrow>
</mtd>
</mtr>
</mtable>
</mfenced>
Wherein, SOC is the existing capacity of energy-storage system, qESSIt is the target adjustment power of ESS in unit scheduling time inter, SOC+
It is the SOC, p after optimizationi spotRepresent the Spot Price of i-th of microgrid, pi schAnd q (t)i sch(t) represent respectively in i-th of microgrid
PRL planned price and planned supply and use of electric power amount, Pi ESSAnd P (t)i DR(t) profit of EES and demand response in i-th of system is represented respectively
Profit, Ci DG(t) cost of DG in i-th of microgrid, q are representedi schRepresent the estimated consumption power of PRL in i-th of microgrid, qi ESSWith
qi DGThe demand response of EES and DG in i-th of system, q are represented respectivelyi loadRepresent the workload demand response of i-th of microgrid, Δ qi
The imbalance power of i-th of microgrid is represented, pAGG spot represent to assemble business's Spot Price, kchaRepresent charge coefficients；
By microgrid community Spot Price and the pMGC spot and imbalance power Δ q in microgridiBetween corresponding relation note
For：
<mrow>
<msubsup>
<mi>p</mi>
<mrow>
<mi>s</mi>
<mi>p</mi>
<mi>o</mi>
<mi>t</mi>
</mrow>
<mrow>
<mi>M</mi>
<mi>G</mi>
<mi>C</mi>
</mrow>
</msubsup>
<mo>=</mo>
<msub>
<mi>f</mi>
<mrow>
<mi>t</mi>
<mi>r</mi>
<mi>a</mi>
<mi>d</mi>
</mrow>
</msub>
<mrow>
<mo>(</mo>
<msup>
<mi>&Delta;q</mi>
<mi>i</mi>
</msup>
<mo>)</mo>
</mrow>
</mrow>
Obtained according to the corresponding relation：
<mrow>
<msubsup>
<mi>p</mi>
<mrow>
<mi>s</mi>
<mi>e</mi>
<mi>l</mi>
<mi>l</mi>
</mrow>
<mi>i</mi>
</msubsup>
<mo>=</mo>
<msub>
<mi>f</mi>
<mrow>
<mi>t</mi>
<mi>r</mi>
<mi>a</mi>
<mi>d</mi>
</mrow>
</msub>
<mrow>
<mo>(</mo>
<msup>
<mi>&Delta;q</mi>
<mi>i</mi>
</msup>
<mo>-</mo>
<mi>x</mi>
<mo>)</mo>
</mrow>
</mrow>
<mrow>
<msubsup>
<mi>p</mi>
<mrow>
<mi>b</mi>
<mi>u</mi>
<mi>y</mi>
</mrow>
<mi>i</mi>
</msubsup>
<mo>=</mo>
<msub>
<mi>f</mi>
<mrow>
<mi>t</mi>
<mi>r</mi>
<mi>a</mi>
<mi>d</mi>
</mrow>
</msub>
<mrow>
<mo>(</mo>
<msup>
<mi>&Delta;q</mi>
<mi>i</mi>
</msup>
<mo>+</mo>
<mi>x</mi>
<mo>)</mo>
</mrow>
</mrow>
Wherein,The sales rate of electricity of i-th of microgrid is represented,The purchase electricity price of i-th of microgrid is represented, x represents that microgrid is given birth to more
Production or the electricity used less.
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| Publication number | Priority date | Publication date | Assignee | Title |
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| CN108306288A (en) * | 2018-02-13 | 2018-07-20 | 华东理工大学 | A kind of microgrid community distributed energy distribution method based on Demand Side Response |
| CN109636245A (en) * | 2019-01-08 | 2019-04-16 | 广东电力交易中心有限责任公司 | The power generation limit fuel cost calculation method and device of generating set |
| CN110555606A (en) * | 2019-08-21 | 2019-12-10 | 天津大学 | method for improving DG consumption level of power distribution network based on total amount |
| CN111062513A (en) * | 2019-11-14 | 2020-04-24 | 四川大学 | Distributed community energy transaction system and method based on self-adaptive consensus mechanism |
| CN112862175A (en) * | 2021-02-01 | 2021-05-28 | 天津天大求实电力新技术股份有限公司 | Local optimization control method and device based on P2P power transaction |
| CN116205293A (en) * | 2023-03-06 | 2023-06-02 | 浙江华云信息科技有限公司 | Data processing method and device based on multi-party green electricity polymerization transaction system |
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2017
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| Publication number | Priority date | Publication date | Assignee | Title |
|---|---|---|---|---|
| CN108306288A (en) * | 2018-02-13 | 2018-07-20 | 华东理工大学 | A kind of microgrid community distributed energy distribution method based on Demand Side Response |
| CN108306288B (en) * | 2018-02-13 | 2021-03-02 | 华东理工大学 | Micro-grid community distributed energy distribution method based on demand side response |
| CN109636245A (en) * | 2019-01-08 | 2019-04-16 | 广东电力交易中心有限责任公司 | The power generation limit fuel cost calculation method and device of generating set |
| CN110555606A (en) * | 2019-08-21 | 2019-12-10 | 天津大学 | method for improving DG consumption level of power distribution network based on total amount |
| CN110555606B (en) * | 2019-08-21 | 2023-01-13 | 天津大学 | Method for improving DG consumption level of power distribution network based on total amount |
| CN111062513A (en) * | 2019-11-14 | 2020-04-24 | 四川大学 | Distributed community energy transaction system and method based on self-adaptive consensus mechanism |
| CN111062513B (en) * | 2019-11-14 | 2023-08-18 | 四川大学 | Distributed community energy trading system and method based on self-adaptive consensus mechanism |
| CN112862175A (en) * | 2021-02-01 | 2021-05-28 | 天津天大求实电力新技术股份有限公司 | Local optimization control method and device based on P2P power transaction |
| CN116205293A (en) * | 2023-03-06 | 2023-06-02 | 浙江华云信息科技有限公司 | Data processing method and device based on multi-party green electricity polymerization transaction system |
| CN116205293B (en) * | 2023-03-06 | 2023-08-08 | 浙江华云信息科技有限公司 | Data processing method and device based on multi-party green electricity polymerization transaction system |
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