CN110516855A - A kind of distributed energy storage optimization of control right dispatching method towards Load aggregation quotient - Google Patents
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Abstract
The invention discloses a kind of the distributed energy storage optimization of control right dispatching method towards Load aggregation quotient, the progress load prediction of acquisition system history data and new energy power output prediction；It establishes the user equipped with distributed energy storage and runs self scheduling objective function and user's self scheduling constraint condition；Establish distributed energy storage control it is optimal purchase strategy with traffic control objective function and distributed energy storage control it is optimal purchase strategy with traffic control constraint condition；The determining polymerization quotient's under distributed energy storage control trade mode purchases energy storage strategy and traffic control method, and optimization energy storage control purchases scheme；It polymerize quotient for the scheduling scheme of customer charge；The user cost participated in business reduces situation and the economic well-being of workers and staff for polymerizeing quotient.The present invention improves the utilization rate of distributed energy storage, reduces the peak-valley difference of electric system, also there is certain contribution to social benefit.
Description
Technical field
The invention belongs to distributed energy storage dispatching technique fields, and in particular to a kind of distributed storage towards Load aggregation quotient
It can control power Optimization Scheduling.
Background technique
The popularization of distributed new system be unable to do without distributed energy storage system.In a distributed manner for photovoltaic, when in power grid
When a certain amount of distributed photovoltaic system of a large amount of user installation, due to the fluctuation and randomness of photovoltaic power output, these light
Volt system can bring challenges and endanger to dispatching of power netwoks or even power grid security.When a certain amount of point of distributed photovoltaic user configuration
When constituting a set of light-preserved system, by the rational management to distributed energy storage, it is a large amount of to can solve distributed generation resource for cloth energy storage
Access and load increase the problem of bringing and challenge rapidly.Distributed energy storage user, which refers to, is equipped with distributed photovoltaic and distributed storage
Can, and the user with a certain amount of rigid power load.The dispatching method of existing user side distributed energy storage can be divided into 2
Class:
1) user can be led to by carrying out operation self scheduling to light-preserved system while the power demand for meeting itself
The fluctuation at any time using electricity price is crossed, the operating cost of itself is reduced, obtains certain interests.But user implements self scheduling
There are times and technical problem, and when distributed user a large amount of in certain region carries out independent self scheduling, due to each
A user power utilization load curve differs greatly, and may cause that a large amount of unordered energy storage charge and discharges are electrically operated, generates to power grid certain
Impact.Further, since single user's capacity is smaller, the issuable peak load shifting effect of self scheduling is limited, can not obtain electricity
The compensation of net.
2) the energy storage control of certain customers is bought commercially available from Load aggregation, signing is monthly to purchase contract, and it is certain to pay user
Expense, it is unified that the energy storage of the user to be contracted is controlled, while undertaking the powered operation of this certain customers.For installing
In the distributed energy storage of user side, Load aggregation quotient utilizes it by formulating reasonable distributed energy storage load group dispatching method
The feature of quick response is dispatched by reasonable charge and discharge, is stabilized the fluctuation and randomness of distributed photovoltaic power output, is stabilized it
A small amount of fluctuation in a short time be scheduled its power output can according to long period scale.It is polymerizeing a large amount of distributed energy storage
After customer charge participates in peak load shifting, user, polymerization quotient, power grid tripartite benefit may be implemented.
Existing research is the quantity of electricity transaction expansion research for energy storage mostly, is rarely had about the transaction of energy storage control
Research；Mostly for the energy-storage system of centralized large capacity, and the research of user side distributed energy storage is relatively fewer；It is negligent of considering
The interests of user side.Therefore, the present invention purchases and dispatching party towards the distributed energy storage under energy storage control trade mode is optimal
The research of two stages scheduling problem is unfolded in method.User's self scheduling is carried out to minimize user cost as optimization aim in the 1st stage
Problem optimization；In the 2nd stage, using polymerize quotient's Income Maximum as target carry out energy storage control it is optimal purchase dispatched with energy storage it is excellent
Change, implements energy storage Optimized Operation on the basis of selecting appropriate user progress energy storage control to purchase, and guarantee institute contracted user
Operating cost be lower than 1 stage when user cost.Here the quotation of user's sale energy storage control is too low will to damage user
The interests of itself, quotation is excessively high will to prevent to polymerize quotient from obtaining income；And individual user is due to energy storage and load parameter,
The interests that self-operating cost may increase or polymerize quotient after its Optimized Operation for participating in energy storage load group will be damaged, so
There are problems that the optimal of energy storage control is purchased.
Summary of the invention
In view of the above-mentioned deficiencies in the prior art, the technical problem to be solved by the present invention is that providing one kind towards load
It polymerize the distributed energy storage optimization of control right dispatching method of quotient, can is distribution on the basis of guaranteeing that user benefit is not encroached on
The economical operation that formula energy storage polymerize quotient provides strong reference.
The invention adopts the following technical scheme:
A kind of distributed energy storage optimization of control right dispatching method towards Load aggregation quotient, comprising the following steps:
S1, system history data is obtained, equipment state and information is obtained from user side by telecommunication system, born
Lotus prediction and new energy power output prediction；
S2, user's operation self scheduling objective function equipped with distributed energy storage, user's fortune equipped with distributed energy storage are established
Row self scheduling optimization aim is the total operating cost for minimizing user, and the income and expenditure of user includes receipts of the sale of electricity to power grid
Benefit, from cost, the paddy of power grid power purchase when the cost depletions of cost and energy storage charge and discharge that charge；
S3, user's self scheduling constraint condition is established according to step S2；
S4, with the interacting of power grid, polymerization quotient pays purchases strategies, and obtains sale of electricity income；It is interacted with user
In, polymerization quotient collects the expense for customer power supply, and the expense to charge to the energy storage that power grid payment is user at night；With electricity
In the interaction of net scheduling side, polymerization quotient obtains peak clipping income, establishes the optimal strategy of purchasing of distributed energy storage control and adjusts with operation
Spend objective function；
S5, established according to step S4 distributed energy storage control it is optimal purchase strategy with traffic control constraint condition；
S6, it two stages Optimized model is formed by step S2 and S4 solves, determine in distributed energy storage control
Polymerize quotient under trade mode purchases energy storage strategy and traffic control method, and optimization energy storage control purchases scheme；It polymerize quotient
For the scheduling scheme of customer charge；The user cost participated in business reduces situation and the economic well-being of workers and staff for polymerizeing quotient.
Specifically, the user equipped with distributed energy storage runs self scheduling objective function in step S2 are as follows:
Wherein, i ∈ IESS, i-th of user equipped with distributed energy storage of subscript i expression, the subscript t expression t period, subscript d
Indicate d-th of typical day；DESS、TESS、IESSRespectively indicate typical day, control time and user's set equipped with distributed energy storage；Indicate the stored energy capacitance that i-th of user is configured；Respectively d-th i-th of typical case's t period
The equivalent purchase sale of electricity load of energy-storage units；Respectively user's power purchase, the electricity price of sale of electricity from power grid；ΔT
For single period duration；Indicate the SOC of energy storage when the 1st period is initial；λuser,valleyIndicate user's night power purchase electricity
Valence；Respectively charging, discharge power；λESS,costIndicate the degree electricity cost of energy storage charge and discharge；λESS,costIndicate storage
The degree electricity cost of energy charge and discharge.
Specifically, constraint includes meeting user power utilization demand and energy-storage battery physical constraint, including energy storage list in step S3
First equivalent power constraint, energy-storage units power-balance constraint, energy-storage units SOC constraint, charge and discharge constraint, maximum charge and discharge number
Constraint.
Further, energy-storage units equivalent power constraint expression formula is as follows:
Wherein, i ∈ IESS,t∈TESS,d∈DESS,For total equivalent load；Respectively d-th of allusion quotation
Type day i-th of energy-storage units of t period prediction load and photovoltaic；
Energy-storage units power-balance constraint is as follows:
Wherein, i ∈ IESS,t∈TESS,d∈DESS；
Energy-storage units SOC constraint is as follows:
In formula, i ∈ IESS,d∈DESS,For the SOC, η of d-th of typical case's i-th of energy storage of t periodcha、ηdisPoint
Not Wei energy storage efficiency for charge-discharge；Set the lower and upper limit of energy storage SOC:
Wherein, SOCmin、SOCmaxThe respectively upper and lower limit of SOC；
Charge and discharge constraint
ai,t,d+bi,t,d≤1
Wherein, ai,t,d,bi,t,d∈ { 0,1 }, Pcha,max、Pdis,maxRespectively maximum charge and discharge power；0-1 variable ai,t,d、
bi,t,dIt is to be charged and discharged mark respectively, is that 0 expression is in idle state；
Maximum charge and discharge count constraint are as follows:
Wherein, i ∈ IESS,Maximum charge and discharge number, D in respectively energy storage one monthTypicalIt is selected
The quantity of typical day, DMonthFor the moon total number of days.
Specifically, optimization aim is the average daily income of polymerization quotient maximized in one month in step S4, polymerization quotient is daily received
Benefit is equal to the average daily acquisition cost that typical average daily operation income in a few days subtracts energy storage control, and objective function first item indicates allusion quotation
The average daily operation income of type in a few days Load aggregation quotient, Section 2 indicate the average daily acquisition cost of energy storage control, specifically:
Wherein, IESSIt is equipped with user's set of distributed energy storage,For the unit capacity of i-th of user's energy storage control
Acquisition price, αiFor 0-1 decision variable, indicates that polymerization quotient has purchased the energy storage control of i-th of user for 1, otherwise indicate do not have
There is purchase；F3,dIndicate the economical operation benefit of d-th of Load aggregation quotient distributed user business typical day；DTypicalIt is typical
The number of days of day, DMonthIt is of that month total number of days.
Specifically, in step S4, and in the interacting of power grid, in d-th of typical operation F in a few days polymerizeing quotient3,dExpression formula
It is as follows:
Wherein,The respectively practical power purchase of Load aggregation quotient, sale of electricity power,Respectively
Power purchase, sale of electricity price of the Load aggregation quotient to power grid；Respectively d-th typical case's t period load is cut
Peak amount, specific load peak clipping benifits.
Further, load peak clipping amountIt is defined as having the correction amount of former load curve after installation energy storage:
Wherein, t ∈ TESS, d ∈ DESS。
Specifically, constraint condition includes system-level power constraint, energy storage group's charge and discharge constraint, energy storage list in step S5
The technological constraint of member and the constraint for guaranteeing user benefit.
Further, general power Constraints of Equilibrium are as follows:
Wherein, t ∈ TESS,d∈DESS,For polymerization degree of negotiating the transfer of under total load,Respectively
The prediction load and photovoltaic of d typical case's i-th of energy-storage units of t period；
Energy storage group's charge and discharge constraint are as follows:
ai,t,d+bj,t,d≤1
Wherein, i, j ∈ IESS,t∈TESS,d∈DESS, subscript j also illustrates that energy storage is numbered, cannot exist simultaneously in energy storage group
Energy storage in charged state and the energy storage in discharge condition.
The constraint of energy storage control authority are as follows:
Wherein, i ∈ IESS, t ∈ TESS,DESS；
Guarantee user benefit constraint are as follows:
Wherein, i ∈ IESS,To polymerize the electricity price for commercially supplying electricity to user,Lower than user directly from power grid power purchase
Electricity price.λESS,costThe degree electricity cost for indicating energy storage charge and discharge, by energy storage overall cost of ownership, depth of discharge, maximum charge and discharge time
The parameters such as number, capacity can be converted into the degree electricity cost λ of energy storage charge and dischargeESS,cost。
Compared with prior art, the present invention at least has the advantages that
A kind of distributed energy storage optimization of control right dispatching method towards Load aggregation quotient of the present invention, first from equipped with distribution
The angle of the user of formula energy storage is set out, and establishes user's self scheduling Optimized model, model with the minimum target of user's operating cost
Optimum results provide basis for the analysis of next step；Then, it from the angle of Load aggregation quotient, is used based on it for signing
The parameter at family and with electrical feature, establishing not encroach on user benefit is that core constrains, is up to target with Load aggregation quotient's interests
Dispatching decision-making model, contract to select the suitable user equipped with distributed energy storage, and make reasonable day
Preceding schedule；Mentioned method through the invention, Load aggregation quotient is optimal to purchase distributed energy storage control and optimizing scheduling mould
Type can choose the reasonable user equipped with distributed energy storage and contract, and carry out reasonable scheduling peace to user side energy storage
Row.For polymerizeing quotient, polymerization quotient can be made a profit by polymerizeing distributed energy storage user；For a user, compared to
Family side self scheduling model, the operating cost of user are reduced；For power grid, pass through effective management of polymerization quotient and tune
Degree, will can play the peak clipping effect for cutting down itself load, and then effectively delay investing to build for new power plant.The above results were both shown
Huge schedulable potentiality existing for user side energy storage class flexible load also show Load aggregation quotient's syndication users side distribution money
Source participates in market, can bring considerable benefit, obtain the effect of all-win.
Further, it is the total operation for minimizing user i that the user equipped with distributed energy storage, which runs self scheduling objective function,
CostThe income of user and expenditure charge when including income of the sale of electricity to power grid, cost, the paddy from power grid power purchase at
The cost depletions of this and energy storage charge and discharge.The objective function mainly from the angle of user, as far as possible reduction user at
This, income mainly considers that sale of electricity gives power grid income obtained, what cost mainly considered to charge when the cost from power grid power purchase, paddy
The cost depletions of cost and energy storage charge and discharge.The objective function show to charge when user is intended to reduce to power grid power purchase, paddy with
And energy storage charge and discharge, and increase to power grid sale of electricity, this is also consistent with engineering practice.
Further, it is mainly to meet user power utilization demand that the user equipped with distributed energy storage, which runs self scheduling constraint condition,
With the constraint of energy-storage battery physics, specifically, including the constraint of energy-storage units equivalent power, energy-storage units power-balance constraint,
Energy-storage units SOC constraint, charge and discharge constraint, maximum charge and discharge count constraint.These constraint conditions have fully demonstrated distributed storage
The operation characteristic of energy, wants to cooperate with objective function, can sufficiently reflect that the user equipped with distributed energy storage runs the mistake of self scheduling
Journey.
Further, polymerization quotient's distributed energy storage control is optimal purchases strategy and traffic control objective function to maximize
The average daily income of polymerization quotient in one month, and polymerize the average daily income of quotient and subtract energy storage control equal to typical average daily operation income in a few days
Make the average daily acquisition cost of power.The objective function is divided into two parts, and a part is average daily operation income, and another part is daily to store up
It can control power acquisition cost.The objective function is mainly from the angle of Load aggregation quotient, the as far as possible receipts of increasing productivity polymerization quotient
Benefit buys energy storage control participation load scheduling to motivate commercially available from Load aggregation.
Further, it includes three parts that polymerization quotient, which daily runs earnings target mainly, and first part is to interact with power grid
Part, second part are to be and scheduling side interaction portion with user interaction part, Part III.Specifically, the receipts of the target
Income that benefit includes sale of electricity to power grid, the income powered for customer charge, peak clipping income, cost include from power grid power purchase at
Originally, the cost to charge when paddy.The target sufficiently reflects the main source of polymerization quotient's income, embodies distributed energy storage control
Weigh the superiority of trade mode.
Further, polymerization quotient's distributed energy storage control it is optimal purchase strategy with traffic control constraint condition include system
The power constraint of grade, energy storage group's charge and discharge constraint, the constraint of the technological constraint of energy-storage units and guarantee user benefit.These constraints
On the one hand condition embodies the physical characteristic of electric system and distributed energy storage, on the other hand ensure that user and load aggregation quotient
It can therefrom make a profit.Strategy and this mode of traffic control, Yong Huli are purchased by the way that polymerization quotient's distributed energy storage control is optimal
Benefit and load aggregation quotient's interests are all improved, and realize Pareto improvement.
In conclusion The present invention gives a kind of distributed energy storage optimization of control right dispatching party towards Load aggregation quotient
Method, this method have taken into account user and load aggregation quotient's common interest, and can not only reduce user uses energy cost, but also can increase negative
Lotus polymerize the income of quotient, meanwhile, the method increase the utilization rates of distributed energy storage, reduce the peak-valley difference of electric system, right
Social benefit also has certain contribution.
Below by drawings and examples, technical scheme of the present invention will be described in further detail.
Detailed description of the invention
Fig. 1 is typical certain user's self-optimizing scheduling result in a few days；
Fig. 2 is that typical polymerization quotient scheduling result and load curve in a few days improves situation；
Fig. 3 is typical polymerization quotient operating cost-performance analysis in a few days；
Fig. 4 is the user cost comparison before and after participating in polymerization degree of negotiating the transfer of；
Fig. 5, which is that the distributed energy storage under energy storage control trade mode is optimal, to be purchased and scheduling two stages optimization problem.
Specific embodiment
The present invention provides a kind of distributed energy storage optimization of control right dispatching method towards Load aggregation quotient, first from dress
The angle for being distributed the user of formula energy storage is set out, and establishes user's self scheduling optimization mould with the minimum target of user's operating cost
The optimum results of type, model provide basis for the analysis of next step.It then, can based on it from the angle of Load aggregation quotient
For the parameter and electrical feature of contracted user, establishes and constrained as core, using not encroaching on user benefit with Load aggregation quotient's interests
It is up to the dispatching decision-making model of target, contracts to select the suitable user equipped with distributed energy storage, and formulate
Reasonable schedule a few days ago out.
A kind of distributed energy storage optimization of control right dispatching method towards Load aggregation quotient of the present invention, comprising the following steps:
S1, obtained from relevant departments system history data, by telecommunication system from user side obtain equipment state and
Information carries out load prediction and new energy power output prediction based on advanced Predicting Technique；
When using institute's climbing form type of the present invention, need to obtain required data from relevant departments first.It is obtained from relevant departments
Computation model input data, which includes following data, obtains system history data from relevant departments, by telecommunication system from user
Side obtains equipment state and information, carries out load prediction and new energy power output prediction based on advanced Predicting Technique.
S2, user's operation self scheduling objective function equipped with distributed energy storage is established；
It is the total operating cost for minimizing user i that user equipped with distributed energy storage, which runs self scheduling optimization aim,The cost that the income and expenditure of user charge when including income of the sale of electricity to power grid, cost, the paddy from power grid power purchase,
And the cost depletions of energy storage charge and discharge.
In formula, i ∈ IESS, i-th of user equipped with distributed energy storage of subscript i expression, the subscript t expression t period, subscript d
Indicate d-th of typical day.DESS、TESS、IESSRespectively indicate typical day, control time and user's set equipped with distributed energy storage.Indicate the stored energy capacitance that i-th of user is configured, kWh.Respectively d-th typical case's t period
The equivalent purchase sale of electricity load of i energy-storage units.Respectively user's power purchase, the electricity price of sale of electricity from power grid.Δ
T is single period duration.Indicate the SOC of energy storage when the 1st period is initial.λuser,valleyIndicate user's night power purchase electricity
Valence.Respectively charging, discharge power.λESS,costIndicate the degree electricity cost of energy storage charge and discharge.By energy storage gross investment
The parameters such as cost, depth of discharge, maximum charge and discharge number, capacity can be converted into the degree electricity cost λ of energy storage charge and dischargeESS,cost。
S3, user's self scheduling constraint condition is established；
Constraint mainly includes meeting user power utilization demand and energy-storage battery physical constraint, including energy-storage units equivalent power is about
Beam, energy-storage units power-balance constraint, energy-storage units SOC constraint, charge and discharge constraint, maximum charge and discharge count constraint；
1) energy-storage units equivalent power constrains
There is rigid power load, distributed photovoltaic power output in energy-storage units, energy storage is charged and discharged load, overall power
Expression formula is as follows:
In formula, i ∈ IESS,t∈TESS,d∈DESS,For total equivalent load.Respectively d-th of allusion quotation
Type day i-th of energy-storage units of t period prediction load and photovoltaic.
2) energy-storage units power-balance constraint
Wherein, i ∈ IESS,t∈TESS,d∈DESS, formula (3) shows if total equivalent loadFor positive value, then energy storage list
Member has to power grid power purchaseIf total equivalent loadFor negative value, then energy-storage units have to power grid sale of electricity
3) energy-storage units SOC is constrained
SOC of the energy storage in t period end and SOC, the charge-discharge electric power of present period, charge and discharge when previous period end
The factors such as efficiency are related, and the expression formula of SOC at any time is as follows:
In formula, i ∈ IESS, d ∈ DESS,For the SOC, η of d-th of typical case's i-th of energy storage of t periodcha、ηdisPoint
Not Wei energy storage efficiency for charge-discharge.
In addition, the lower limit of energy storage SOC is set due to excessive charge and discharge acceleration cell degradation (capacity attenuation) in order to prevent
And the upper limit:
In formula, i ∈ IESS,t∈TESS,d∈DESS, SOCmin、SOCmaxThe respectively upper and lower limit of SOC.
4) charge and discharge constrain
ai,t,d+bi,t,d≤1 (7)
Wherein, ai,t,d,bi,t,d∈ { 0,1 }, i ∈ IESS,t∈TESS,d∈DESS, Pcha,max、Pdis,maxRespectively maximum fill,
Discharge power.0-1 variable ai,t,d、bi,t,dIt is to be charged and discharged mark respectively, is that 0 expression is in idle state.Formula (7)
It is charge and discharge mutual exclusion constraint, indicates that energy storage cannot charge and discharge simultaneously.
5) maximum charge and discharge count constraint
In order to reduce the start and stop loss of energy storage, the of that month maximum charge and discharge count constraint of setting energy storage, guarantee energy storage without
Continually charge and discharge is electrically operated, to reduce the cost depletions of energy storage:
In formula, i ∈ IESS,Maximum charge and discharge number, D in respectively energy storage one monthTypicalIt is selected
The quantity of typical day, DMonthFor the moon total number of days.
S4, establish distributed energy storage control it is optimal purchase strategy with traffic control objective function；
With the interacting of power grid, polymerization quotient pays purchases strategies, and obtains sale of electricity income；With in the interacting of user,
Polymerization quotient collects the expense for customer power supply, and the expense to charge to the energy storage that power grid payment is user at night；With power grid
In the interaction for dispatching side, polymerization quotient obtains peak clipping income；
Optimization aim is the average daily income of polymerization quotient maximized in one month, the polymerization average daily income of quotient be equal to it is typical in a few days
Average daily operation income subtracts the average daily acquisition cost of energy storage control:
In formula, IESSIt is equipped with user's set of distributed energy storage,Hold for the unit of i-th of user's energy storage control
Measure acquisition price, αiFor 0-1 decision variable, indicates that polymerization quotient has purchased the energy storage control of i-th of user for 1, otherwise indicate
Do not buy.F3,dIndicate the economical operation benefit of d-th of Load aggregation quotient distributed user business typical day.DTypicalIt is allusion quotation
The number of days of type day, DMonthIt is of that month total number of days.Objective function first item indicates that the average daily operation of typical in a few days Load aggregation quotient is received
Benefit, Section 2 indicate the average daily acquisition cost of energy storage control.
With the interacting of power grid, polymerization quotient pays purchases strategies, and obtains sale of electricity income；With in the interacting of user,
Polymerization quotient collects the expense for customer power supply, and the expense to charge to the energy storage that power grid payment is user at night；With power grid
In the interaction for dispatching side, polymerization quotient obtains peak clipping income.Therefore, in d-th of typical operation F in a few days polymerizeing quotient3,dExpression formula
It is as follows:
In formula,The respectively practical power purchase of Load aggregation quotient, sale of electricity power,Respectively
Power purchase from Load aggregation quotient to power grid, sale of electricity price for.Respectively d-th typical case's t period load
(only there is peak clipping income in peak period, 0) the peak clipping income of remaining period is for peak clipping amount, specific load peak clipping benifits.Formula (10)
The expression formula that polymerization quotient runs income is given, having operation income ,=- buying electric cost from power grid ,+sell and supply electricity to power grid income+sells electricity
Cost+peak clipping the income to charge when to user's income-paddy to energy storage.
In F3,dExpression formula in, load peak clipping amountIt is defined as the amendment after installation energy storage to former load curve
Amount, has:
Wherein, t ∈ TESS, d ∈ DESS。
S5, establish distributed energy storage control it is optimal purchase strategy with traffic control constraint condition；
Distributed energy storage control it is optimal purchase strategy with traffic control in constraint condition include system-level power
Constraint, the constraint of the technological constraint of energy-storage units and guarantee user benefit；
1) general power Constraints of Equilibrium
In formula, t ∈ TESS, d ∈ DESS,For polymerization degree of negotiating the transfer of under total load,Respectively
The prediction load and photovoltaic of d typical case's i-th of energy-storage units of t period.Formula (12) and (13) give polymerization quotient to outside
The expression formula of power grid power purchase and sale of electricity.
2) energy-storage units SOC constraint, charge and discharge constraint, maximum charge and discharge count constraint and phase in the case of user's self scheduling
Together, it is indicated with formula (4)-(6), (8).
The single energy storage charge and discharge constraint of formula (7) is rewritten into energy storage group's charge and discharge constraint:
ai,t,d+bj,t,d≤1 (14)
In formula, i, j ∈ IESS,t∈TESS,d∈DESS, subscript j also illustrate that energy storage number, formula (16) indicate ai,tAnd bj,tExtremely
Rare one is 0, cannot exist simultaneously the energy storage in charged state and the energy storage in discharge condition in energy storage group.
3) energy storage control authority constrains
Wherein, i ∈ IESS,t∈TESS,DESS, formula (15) shows only to work as αiBe 1, i.e., to the energy storage control of user into
It just can be carried out charge and discharge operation after row purchase.
4) guarantee user benefit constraint
In a few days, user's totle drilling cost under this model framework is not higher than the totle drilling cost under user's self-optimizing operation by typical caseIt is obtained by previous family self-optimizing scheduling model of saving.User cost and income under this model framework include
User locates the cost of power purchase, the charge and discharge cost depletions of user's energy storage, from polymerizeing the sale energy storage control obtained from quotient from polymerization quotient
Make the income of power.
In formula, i ∈ IESS,To polymerize the electricity price for commercially supplying electricity to user,Lower than user directly from power grid power purchase
Electricity price.λESS,costThe degree electricity cost for indicating energy storage charge and discharge, by energy storage overall cost of ownership, depth of discharge, maximum charge and discharge time
The parameters such as number, capacity can be converted into the degree electricity cost λ of energy storage charge and dischargeESS,cost.Formula (16) ensure that the user's benefit for participating in signing
Benefit is not encroached on, inequality left side first item be under this model framework user i the pay within d days polymerize total electricity consumption of quotient at
This, Section 2 is energy storage charge and discharge cost, Section 3 is to sell the resulting income of energy storage control, by income from it is typical in a few days
Total revenue has been converted to of that month average day income.
S6, it abovementioned steps is formed by with two stages Optimized model solves.It can determine and be controlled in distributed energy storage
It weighs under trade mode, polymerize quotient purchases energy storage strategy and traffic control method.
Optimum results include:
1. energy storage control purchases scheme；
2. polymerizeing quotient for the scheduling scheme of customer charge；
3. the user cost participated in business reduces situation；
4. polymerizeing the economic well-being of workers and staff of quotient.
In order to make the object, technical scheme and advantages of the embodiment of the invention clearer, below in conjunction with the embodiment of the present invention
In attached drawing, technical scheme in the embodiment of the invention is clearly and completely described, it is clear that described embodiment is
A part of the embodiment of the present invention, instead of all the embodiments.The present invention being described and shown in usually here in attached drawing is real
The component for applying example can be arranged and be designed by a variety of different configurations.Therefore, below to the present invention provided in the accompanying drawings
The detailed description of embodiment be not intended to limit the range of claimed invention, but be merely representative of of the invention selected
Embodiment.Based on the embodiments of the present invention, those of ordinary skill in the art are obtained without creative efforts
The every other embodiment obtained, shall fall within the protection scope of the present invention.
Referring to Fig. 1, distributed energy storage is filled in electricity price lower 16:00~18:00 period within typical day 3
Electricity, and the higher 12:00~15:00 of electricity price, in 18:00~21:00 period by electric discharge to maintain user itself load
Part powers, and reduces the electricity that the peak period buys from power grid, effectively reduces the electric cost of user.
Fig. 2 and Fig. 3 are please referred to, the schedule result for choosing the typical day 1 in its scheduling result is shown.In legend
" selling electricity " indicates that polymerization commercially supplies electricity to power grid, and " buying electricity " indicates polymerization quotient from power grid power purchase, and " electric discharge " indicates energy storage electric discharge, " fills
Electricity " indicates energy storage charging, and " amendment afterload " indicates the load value that subscriber unit is externally shown, and is distributed energy storage charge and discharge
The sum of amount and rigid load.
Although all in all the electricity consumption of each user lacks regularity, total net load curvilinear motion of user group is not
Greatly, so four typical day scheduling results are similar.Generally electricity price curve is obvious to the guiding function of energy storage charge and discharge:
In electricity price lower 16:00~18:00 period, energy storage is charged；
And in high electricity price, the 12:00~15:00 for thering is peak clipping to subsidize, 18:00~21:00 period, energy storage is discharged.
Load before amendment four it is typical have nothing in common with each other day, and revised load 12:00~15:00,18:00~
There is certain range of decrease in the 21:00 period, and is increased in 16:00~18:00 period load, and this variation tendency is the shifting of energy storage
Caused by peak load effect.
All in all, in the network load peak period of 12:00~15:00,18:00~21:00, it polymerize quotient and passes through optimization
Scheduling reduces 15% or so of itself load.
From the point of view of Fig. 2 to Fig. 3, since the capacity of distributed energy storage is limited, it is poly- that the discharge capacity of energy storage is completely used for supply
The power demand for closing user in quotient's dispatcher-controlled territory, there is no extra electricity for being fed to power grid.Thus Load aggregation quotient is simultaneously
Power grid profit cannot be supplied electricity to by selling.In 16:00~18:00 period, the net profit of Load aggregation quotient is very low or even is negative, this is
Because although load quotient by obtaining certain income for customer power supply, because user power consumption is low, electricity price is low, and needs
It to charge in advance for energy storage.And in 12:00~15:00,18:00~21:00 period, the net profit of Load aggregation quotient is higher, this
It is that polymerization quotient can be discharged by energy storage supplies a part of power load, and when peak because user power consumption is big, electricity price is high at this time
Section can obtain the peak clipping subsidy of power grid.
Referring to Fig. 4, polymerization quotient chooses 16 users and carries out signing control by model optimization decision.All users'
The performance analysis in market is participated in as shown in figure 4, wherein the cost of contracted user is not 0.As can be seen from Figure, polymerization is participated in
User cost can be saved up to 15% or more after degree of negotiating the transfer of, this is because after participating in polymerization quotient's scheduling method, the electricity consumption electricity of user
Valence reduces, and user obtains certain benefit to polymerization quotient by selling energy storage control.Wherein the cost savings rate of user 6 is up to
46%, this is because the power load peak value of user 6 and average electricity consumption level is higher and the distributed energy storage and electricity consumption peak of user
It is larger to be worth ratio.From a long-term perspective, the distributed energy storage of user installation certain capacity simultaneously participates in polymerization degree of negotiating the transfer of to this explanation, will
Be conducive to user's save the cost.
The 4 class Customs Assigned Numbers without signing are 1,12,14,15, this is because this 4 class customer charge peak value is low, energy storage
Too high etc. reasons that capacity is low, stored energy capacitance and the relatively low of load peak, energy storage control are offered, user participate in energy storage control
Own cost cannot be reduced after trade mode, or polymerization quotient cannot obtain economic effect by purchasing the energy storage control of the user
Benefit.
It purchases and dispatches towards the distributed energy storage under energy storage control trade mode is optimal referring to Fig. 5, Fig. 5 gives
The two stages scheduling flow of method.User's self scheduling problem is carried out to minimize user cost as optimization aim in the 1st stage
Optimization；In the 2nd stage, using polymerize quotient's Income Maximum as target carry out energy storage control it is optimal purchase with energy storage optimizing scheduling,
Implement energy storage Optimized Operation on the basis of selecting appropriate user progress energy storage control to purchase, and guarantees the fortune of institute contracted user
Row cost is lower than user cost when 1 stage.Here the quotation of user's sale energy storage control is too low will to damage user itself
Interests, offer it is excessively high will prevent polymerize quotient from obtaining income；And individual user joins due to energy storage and load parameter
The interests that may increase or polymerize quotient with self-operating cost after the Optimized Operation of energy storage load group will be damaged, so in the presence of
The optimal of energy storage control purchases problem.
In conclusion mentioned method through the invention, Load aggregation quotient is optimal to purchase distributed energy storage control and scheduling
Optimized model can choose the reasonable user equipped with distributed energy storage and contract, and reasonably be adjusted to user side energy storage
Degree arranges.For polymerizeing quotient, polymerization quotient can be made a profit by polymerizeing distributed energy storage user；For a user, it compares
In user side self scheduling model, the operating cost of user is reduced；For power grid, by polymerization quotient it is effective management with
Scheduling, will can play the peak clipping effect for cutting down itself load, and then effectively delay investing to build for new power plant.The above results both showed
Huge schedulable potentiality existing for user side energy storage class flexible load also show Load aggregation quotient's syndication users sides distribution
Resource participates in market, can bring considerable benefit, obtain the effect of all-win.
The above content is merely illustrative of the invention's technical idea, and this does not limit the scope of protection of the present invention, all to press
According to technical idea proposed by the present invention, any changes made on the basis of the technical scheme each falls within claims of the present invention
Protection scope within.
Claims (9)
1. a kind of distributed energy storage optimization of control right dispatching method towards Load aggregation quotient, which is characterized in that including following step
It is rapid:
S1, system history data is obtained, obtains equipment state and information from user side, carried out load prediction and new energy power output is pre-
It surveys；
S2, user's operation self scheduling objective function equipped with distributed energy storage is established, user's operation equipped with distributed energy storage is certainly
Optimizing scheduling target is the total operating cost for minimizing user, the income of user and expenditure include sale of electricity to power grid income, from
The cost depletions of the cost and energy storage charge and discharge that charge when the cost of power grid power purchase, paddy；
S3, user's self scheduling constraint condition is established according to step S2；
S4, with the interacting of power grid, polymerization quotient pays purchases strategies and obtains sale of electricity income；With in the interacting of user, polymerization
The expense that quotient collects as customer power supply, and the expense to charge to the energy storage that power grid payment is user at night；With dispatching of power netwoks
In the interaction of side, polymerization quotient obtain peak clipping income, establish distributed energy storage control it is optimal purchase strategy with traffic control target
Function；
S5, established according to step S4 distributed energy storage control it is optimal purchase strategy with traffic control constraint condition；
S6, step S2 and S4 two stages Optimized model is solved, load assembles quotient's completion user's energy storage scheduling and power grid is mutual
Dynamic optimization.
2. the distributed energy storage optimization of control right dispatching method according to claim 1 towards Load aggregation quotient, feature
It is, in step S2, the user equipped with distributed energy storage runs self scheduling objective function are as follows:
Wherein, i ∈ IESS, i-th of user equipped with distributed energy storage of subscript i expression, the subscript t expression t period, subscript d is indicated
D-th of typical day；DESS、TESS、IESSRespectively indicate typical day, control time and user's set equipped with distributed energy storage；
Indicate the stored energy capacitance that i-th of user is configured；Respectively d-th typical case's i-th of energy storage of t period
The equivalent purchase sale of electricity load of unit；Respectively user's power purchase, the electricity price of sale of electricity from power grid；Δ T is single
Period duration；Indicate the SOC of energy storage when the 1st period is initial；λuser,valleyIndicate user's night purchase electricity price；Respectively charging, discharge power；λESS,costIndicate the degree electricity cost of energy storage charge and discharge；λESS,costIndicate energy storage
The degree electricity cost of charge and discharge.
3. the distributed energy storage optimization of control right dispatching method according to claim 1 towards Load aggregation quotient, feature
It is, in step S3, constraint includes meeting user power utilization demand and energy-storage battery physical constraint, including energy-storage units equivalent power
Constraint, energy-storage units power-balance constraint, energy-storage units SOC constraint, charge and discharge constraint, maximum charge and discharge count constraint.
4. the distributed energy storage optimization of control right dispatching method according to claim 3 towards Load aggregation quotient, feature
It is, energy-storage units equivalent power constraint expression formula is as follows:
Wherein, i ∈ IESS,t∈TESS,d∈DESS,For total equivalent load；Respectively d-th typical day
The prediction load and photovoltaic of i-th of energy-storage units of t period；
Energy-storage units power-balance constraint is as follows:
Wherein, i ∈ IESS,t∈TESS,d∈DESS；
Energy-storage units SOC constraint is as follows:
In formula, i ∈ IESS,d∈DESS,For the SOC, η of d-th of typical case's i-th of energy storage of t periodcha、ηdisRespectively
The efficiency for charge-discharge of energy storage；Set the lower and upper limit of energy storage SOC:
Wherein, SOCmin、SOCmaxThe respectively upper and lower limit of SOC；
Charge and discharge constraint
ai,t,d+bi,t,d≤1
Wherein, ai,t,d,bi,t,d∈ { 0,1 }, Pcha,max、Pdis,maxRespectively maximum charge and discharge power；0-1 variable ai,t,d、bi,t,d
It is to be charged and discharged mark respectively, is that 0 expression is in idle state；
Maximum charge and discharge count constraint are as follows:
Wherein, i ∈ IESS,Maximum charge and discharge number, D in respectively energy storage one monthTypicalFor selected typical case
The quantity of day, DMonthFor the moon total number of days.
5. the distributed energy storage optimization of control right dispatching method according to claim 1 towards Load aggregation quotient, feature
It is, in step S4, optimization aim is the average daily income of polymerization quotient maximized in one month, and the polymerization average daily income of quotient is equal to typical case
Average daily operation income in a few days subtracts the average daily acquisition cost of energy storage control, and objective function first item indicates typical day internal loading
It polymerize the average daily operation income of quotient, Section 2 indicates the average daily acquisition cost of energy storage control, specifically:
Wherein, IESSIt is equipped with user's set of distributed energy storage,Unit capacity for i-th of user's energy storage control is purchased
Price, αiFor 0-1 decision variable, indicates that polymerization quotient has purchased the energy storage control of i-th of user for 1, otherwise indicate not purchase
It buys；F3,dIndicate the economical operation benefit of d-th of Load aggregation quotient distributed user business typical day；DTypicalIt is typical day
Number of days, DMonthIt is of that month total number of days.
6. the distributed energy storage optimization of control right dispatching method according to claim 1 towards Load aggregation quotient, feature
It is, in step S4, and in the interacting of power grid, in d-th of typical operation F in a few days polymerizeing quotient3,dExpression formula it is as follows:
d∈DESS
Wherein,The respectively practical power purchase of Load aggregation quotient, sale of electricity power,Respectively load is poly-
Close power purchase, sale of electricity price of the quotient to power grid；Respectively d-th typical case's t period load peak clipping amount, list
Position load peak clipping benifits.
7. the distributed energy storage optimization of control right dispatching method according to claim 6 towards Load aggregation quotient, feature
It is, load peak clipping amountIt is defined as having the correction amount of former load curve after installation energy storage:
Wherein, t ∈ TESS, d ∈ DESS。
8. the distributed energy storage optimization of control right dispatching method according to claim 1 towards Load aggregation quotient, feature
Be, in step S5, constraint condition include system-level power constraint, energy storage group's charge and discharge constraint, energy-storage units technology about
Beam and the constraint for guaranteeing user benefit.
9. the distributed energy storage optimization of control right dispatching method according to claim 8 towards Load aggregation quotient, feature
It is, general power Constraints of Equilibrium are as follows:
Wherein, t ∈ TESS,d∈DESS,For polymerization degree of negotiating the transfer of under total load,Respectively d-th
The prediction load and photovoltaic of typical i-th of energy-storage units of t period；
Energy storage group's charge and discharge constraint are as follows:
ai,t,d+bj,t,d≤1
Wherein, i, j ∈ IESS,t∈TESS,d∈DESS, subscript j also illustrates that energy storage is numbered, cannot exist simultaneously in energy storage group and be in
The energy storage of charged state and energy storage in discharge condition；
The constraint of energy storage control authority are as follows:
Wherein, i ∈ IESS, t ∈ TESS,DESS；
Guarantee user benefit constraint are as follows:
Wherein, i ∈ IESS,To polymerize the electricity price for commercially supplying electricity to user,Lower than user directly from the electricity of power grid power purchase
Valence, λESS,costThe degree electricity cost for indicating energy storage charge and discharge by energy storage overall cost of ownership, depth of discharge, maximum charge and discharge number, is held
The parameters such as amount can be converted into the degree electricity cost λ of energy storage charge and dischargeESS,cost。
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| CN115936260A (en) * | 2023-01-13 | 2023-04-07 | 智光研究院(广州)有限公司 | Virtual power plant user energy storage scheduling method and device, electronic equipment and storage medium |
| CN116070801B (en) * | 2023-04-03 | 2023-08-08 | 杭州轻舟科技有限公司 | Multi-site optimal operation strategy generation method for load aggregation platform |
| CN116070801A (en) * | 2023-04-03 | 2023-05-05 | 杭州轻舟科技有限公司 | Multi-site optimal operation strategy generation method for load aggregation platform |
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