CN109948954A - A kind of two-way congestion Dispatching Method of power distribution network towards electric system distributed resource - Google Patents
A kind of two-way congestion Dispatching Method of power distribution network towards electric system distributed resource Download PDFInfo
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Abstract
The invention discloses a kind of two-way congestion Dispatching Methods of the power distribution network towards electric system distributed resource for belonging to Distribution Automation Technology field.Using the distributed hair electric resources of the higher electric car of permeability in power distribution network and photovoltaic generation unit as research object, the distributed scheduling model of management electric car and photovoltaic resources is given first, the model is divided into two layers, upper layer is responsible for the power planning to Agg by DSO and carries out network check, to guarantee that distribution is safely operated；Manager of the lower layer by Agg as distributed resource, the electricity volume for being responsible for charge and discharge behavior and photovoltaic to electric car carry out reasonable management.If the network security that the power planning that Agg is reported does not pass through DSO is checked.The present invention formulates reasonable hair electricity plan to lower resource, guarantees the safe operation of distribution line, solve the two-way obstructing problem of distribution by constantly adjusting power control signal, guidance Agg.
Description
Technical field
The invention belongs to Distribution Automation Technology field, in particular to a kind of distribution towards electric system distributed resource
Net two-way congestion Dispatching Method.
Background technique
In recent years, with distributed photovoltaic (photovoltaic, PV) power generation, electric car (electric vehicle,
) etc. EV the permeability in power distribution network of novel controllable burden is continuously improved so that the conventional electrical distribution net of single direction energy supply by
Gradually change towards the new distribution net of trend two-way flow.In view of flexibly controllable distributed resource has both environmental protection and economy
Social welfare, reasonably optimizing allotment is carried out to it and is had a high potential.Under the promotion that new round electricity changes the relieving of sale of electricity side, distribution
The distributed resource of more and more price response types is willing to participate in electricity market to reduce the electricity consumption spending of itself in net.So
And since distributed resource is mostly the middle-size and small-size hair electricity user of system structure bottom dispersion, the elastic water of flexibility resource
It is flat that the threshold value for participating in electricity market is not achieved.In order to integrate demand response resource, make idle medium and small with regulating power
Type hair electricity user is able to participate in market, and the new main market players such as Load aggregation quotient, garden operator, electricity retailer is general
Thought is put forward one after another.But it is no constraint, without guidance or Agg (Aggregator, Load aggregation quotient) only consider user power utilization cost
Distributed resource scheduling result likely result in certain moment concentrate electricity consumption or concentrate electric discharge, cause forward or backwards
Load peak, or even cause the two-way obstruction of power distribution network.Therefore, it is necessary to study the distributions considered under Cybersecurity Operation constraint
Formula resource Optimized Operation strategy a few days ago.
Research at this stage is confined under the guiding function of market clearing price signal mostly, only considers the electricity consumption of user
The Optimized Operation of cost, and the trend constraint for only accounting for single direction do not count and distribution in the high-power refluence of adjustable photovoltaic
Caused by reversed backlog problem.Therefore, bi-directional current problem caused by electric car, photovoltaic distributed resource becomes new
A type power distribution network urgent problem to be solved during Optimized Operation a few days ago.
Summary of the invention
The object of the present invention is to provide a kind of two-way congestion Dispatching Method of the power distribution network towards electric system distributed resource,
It is characterized in that, using the higher electric car of permeability and photovoltaic generation unit consider as research object in power distribution network at present
It is widely distributed to electric car and photovoltaic resources, the small feature of monomer regulated quantity, if DSO is directly to these distributed resources
Be scheduled, the excessive problem of dimension may be faced, also thus to the communications burden that scheduling process has been brought greatly and
And it is unfavorable for the protection to user's hair electricity privacy information.Obviously, it is impractical.Therefore it is electronic to give management for this patent
The distributed scheduling model of automobile and photovoltaic resources, lower layer is by Agg (Aggregator Load aggregation quotient) by being installed on user
The control of side and communication equipment are managed the distributed resource in power distribution network, and upper layer is by DSO (Distribution
System operator, distribution system operator) it is responsible for carrying out network check to the power planning of Agg, guarantee that distribution is transported safely
Row.By introducing cluster management and scheduling of the Agg to user resources, can effectively realize between power distribution network and distributed resource
Interactive response avoids distributed resource during participating in Electricity Market Competition to the two-way obstructing problem of distribution bring.
It specifically includes:
1) each Agg collects the vehicle model information with vehicle habit and electric car of the electric car car owner of its management, then right
The data of electric car resource are arranged.By information such as the installation situation of acquisition distributed photovoltaic and weather conditions, to it
The maximum output of the distributed photovoltaic resource managed is predicted.
2) the energy management model of each Agg is established.The Electrical Safety and cost and photovoltaic money of each Agg consideration electric car
The maximum output situation in source carries out reasonably optimizing scheduling to two kinds of resources.
3) DSO carries out network security check.The power planning reported according to Agg, DSO carries out network security check, if not
By check, according to backlog amount calculate hair, electric power adjustment signal and be handed down to Agg guide its carry out power adjustment.
4) determination of final operation plan.
The information of the step 1) includes: the maximum charge power of electric car, the networking of car owner and off-network time, electronic
Automobile batteries status information, the charge requirement of car owner, the maximum generating watt information of photovoltaic, ahead market electricity price information.
The step 2) includes: that the Optimal Operation Model of Agg layers of electric car and photovoltaic resources is established based on step 1), will
It is divided within 24 hours a few days ago NT time interval, the time span of each time interval is Δ t, and each Agg is with electric cost minimum
Form for target, the objective function of Optimal Operation Model is as follows:
Distributed resource constraint representation is as follows:
0≤pev i,m,t≤Pmax
Wherein, pev i,m,tFor the m electric car under Aggi t scheduling slot charge power； PmaxFor electronic vapour
The maximum charge power of vehicle；Ecap,mFor the battery capacity of the m electric car； SOC0,mFor the initial state-of-charge of the m vehicle,
SOCmax,mState-of-charge when for the m vehicle off-network, ηmFor the charge efficiency of the m electric car, Δ t is each scheduling slot
Length；tm0It networks for the m electric car and starts to receive the period of scheduling, tmdIndicate the period that the m vehicle leaves；Non- tune
The charge-discharge electric power for spending electric car in the period is 0；ppv j,tFor the practical active power output value of t-th of moment photovoltaic of node j；
According to above-mentioned model, the preliminary power plan that electric car and photovoltaic resources under each Agg produce electricity consumption can be obtained
Pev i,j,tAnd ppv i,j,t。
The DSO network security of the step 3) is checked as whether the inspection Agg power planning for submitting to DSO is able to satisfy route
Security constraint, the constraint representation are as follows:
In formula:For the corresponding Lagrange multiplier of route bound security constraint；D is power transmission distribution transfer
The factor；WithThe bound for the active power that respectively branch l is allowed to flow through；PtFor each node always having at the t moment
Function injecting power matrix；For the node location matrix for being connected to EV in description Aggi；For the section for being connected to photovoltaic in description Aggi
Point location matrix.pload j,tFor each node j t moment firm demand value.
Dispatching adjustment under the hair of the step 3), electric power adjustment signal guide is the power meter submitted for Agg
The case where being unsatisfactory for line security constraint is drawn, specifically includes that the hair for calculating electric car and photovoltaic resources, electric power adjustment letter
Number and Agg Optimized Operation scheme adjustment, specifically include:
The calculation method of 5A. hair, electric power adjustment signal are as follows:
WhereinThe signal of power adjustment is carried out in t moment electric car electricity consumption plan for guiding node j,For to draw
Lead the signal that node j is adjusted in the electricity volume of t moment photovoltaic power generation resource.
Hair of the 5B. according to reaction network congestion situations, electric power adjustment signal, each Agg change its power control scheme
Objective function are as follows:
Agg respectively sends out the online of the charging scheme of electric car and photovoltaic resources according to hair, electric power adjustment signal
Electricity plan carries out re-optimization, and such iteration is until the requirement for meeting iteration convergence criterion.
The step 5A includes:
Step 5A1: it calculates and constrains corresponding Lagrange multiplier about line securitySubgradient StAre as follows:
Step 5A2:Since initial value is 0, when each iteration, is updated it:
Step 5A3: the convergence criterion of iteration:
The determination of operation plan includes: hair of the DSO according to the Agg electric car reported and photovoltaic in the step 4)
Electrical power plan does network security and checks such as formulaDetermine whether Agg can be according to
The power planning reported participates in Day-ahead electricity market, and Agg participates in ahead market transaction by the power planning reported if executable,
Otherwise return step 5A.
The beneficial effects of the invention are as follows the schedulable characteristics of model comprehensive utilization electric car and photovoltaic, consider distributed
The hair electric cost and network line of resource are safely operated constraint, solve the two-way obstructing problem of distribution.
Detailed description of the invention
Fig. 1 is the two-way congestion Dispatching Method block schematic illustration of power distribution network towards electric system distributed resource.
Fig. 2 is the flow chart of the two-way congestion Dispatching Method of power distribution network towards electric system distributed resource
Fig. 3 is network topological diagram and electric car and photovoltaic resources distribution
Fig. 4 .1 is 1 power situation of branch wherein (a) 12:00- next day 12:00 changed power；(b) 1:00-6:00 power
Variation；
Fig. 4 .2 is 29 power situation of branch, wherein (a) 12:00- next day 12:00 changed power；(b) 12:00-14:30
Changed power；
Fig. 5 is changed power situation before and after congestion cost；Wherein, function before and after the EV power congestion cost that a is 1 node Agg1
Rate situation of change；Changed power situation before and after the PV congestion cost that b is 30 node Agg2；
Fig. 6 is the convergence curve of power control signal；Wherein, it in 3:00 power control signal b is node 30 that a, which is node 1,
Power control signal of the node in 12:30.
Specific embodiment
The present invention provides a kind of two-way congestion Dispatching Method of the power distribution network towards electric system distributed resource, below with reference to
Drawings and examples further illustrate the present invention.
1. illustrating the validity of this algorithm using the IEEE33 node system of modification.The topological diagram and Agg of the system
Resource distribution it is as shown in Figure 3.The maximum charge power of electric car is 7kw, charge efficiency 0.95.This patent assumes 15 points
Zhong Weiyi dispatching cycle scheduling is optimized to next day 12:00 to 12:00 today, i.e., it will 24 hours a few days ago scheduling slots point
For 96 periods.Iteration coefficient is 1e-4, convergence parameter and be 1e-3, coefficient of sensitivity of price 1e-4DKK/KWh2。
2. congestion cost effect
Under the action of power control signal, branch 1 (node 33-1) power situation as shown in Fig. 4 .1, wherein (a) 12:
00- next day 12:00 changed power；(b) 1:00-6:00 changed power；The resistance of network 29 (node 28-29) power as shown in Fig. 4 .2
Fill in the situation of change of front and back.It can clearly find, after congestion cost, line power is in route upper and lower limits.
The variation of the charge power of electric car in 1 node Agg1 of congestion cost front and back is given with 30 node Agg2's
PV changed power situation, respectively as shown in a, b in Fig. 5.
3. joint mobility resource power variation before and after congestion cost
4. convergence
Fig. 6 show the convergence curve of power control signal；Wherein, it in 3:00 power control signal b is section that a, which is node 1,
Power control signal of 30 nodes of point in 12:30.Illustrate node 1 3:00 and 30 node of node 12:30 power control
Convergence signal curve.For the positive backlog problem for alleviating branch 1 (node 33-1), DSO passes through positive hair, electric power control
Signal processed raises Agg in the purchase sale of electricity electricity price of the node, it is intended to guide Agg to reduce the electricity consumption of the node electric car, increase
The generated energy of the node photovoltaic resources, by constantly adjusting hair, electric power control signal power control after iteration convergence is believed
It number remains unchanged.Similarly, convergent of the node 30 in 12:30 hair, electric power control signal.
The power adjustment and hair of line power before and after the congestion management of above-mentioned displaying, electric car and photovoltaic, electricity consumption
The convergent of power control signal shows the validity of proposed method.This method is efficiently solved since distribution provides
The two-way obstructing problem of power distribution network caused by the hair electricity behavior in source.
The research framework schematic diagram of this method as shown in Figure 1.Agg can be passed through with schedulable electric car (EV) and directly
The distributed photovoltaic power generation unit (PV) for participating in electricity market is research object, and scheduling process is as follows: firstly, each Agg points
A variety of flexibility resources (EV, PV) under the node that safety pin possesses it, according to they be supplied to Agg time regulatable range and
The power informations such as controllable burden capacity model resource flexibility, and then Agg is according to the ahead market electricity price of prediction with him
The minimum target of the electric cost of the resource managed optimizes management to the power of adjustable EV and PV, and by its preliminary power
Plan is reported to DSO and carries out network security check, if Agg participates in ahead market according to the power planning reported by checking；If
Not by network security check, DSO according to the congestion situations of network to set out, electric power adjustment signal guidance Agg again into
Row power adjustment, iteration is until the hair electrical power scheme that Agg submits to DSO meets the need of power distribution network safe operation repeatedly
It wants.
DSO considers the constraint of branch of a network bi-directional current can be simultaneously by determining hair, electric power adjustment signal respectively
It realizes the adjustment to distributed photovoltaic power generation unit and adjustable EV load hair electrical power, efficiently solves resulting from positive and negative
To the two-way obstructing problem of power distribution network caused by load peak.
Under above-mentioned Scheduling Framework, the present invention is detailed below.
Each Agg of step A. acquires the user information and market guidance information of the distributed resource of its management.
The information that need to be acquired includes: the maximum charge power of electric car, the networking of car owner and off-network time, electric car
Battery status information, the charge requirement of car owner, the maximum generating watt information of photovoltaic, ahead market electricity price information.Each Agg of step B.
Consider that user power utilization cost optimizes scheduling to its distributed resource.
Due to Agg ahead market go out it is clear before be not aware that the electricity price information of next day of trade, it is therefore desirable to according to going through
The predictive information of history data and next day of trade predict electricity price.Each Agg is according to the ahead market cleaing price of prediction
The distributed resource for being ready to receive Agg scheduling under it is optimized to provide an initial power plan.This patent selection one
Kind predicts cleaing price dependent on the linear market price model of node total electricity demand.
The Spot Price Model is shown below:
yt=ct+βpt (1)
In formula: β indicate active demand to the sensitivity coefficient of node electricity price, the value by ahead market history electricity price data into
Row assessment and prediction obtain.ctAnd ptThe active need of a few days ago basic electricity price and distributed resource of each moment t respectively predicted
It asks.
It will be divided within 24 hours a few days ago NT time interval, the time span of each time interval is Δ t, and each Agg is to save
Point is that the distributed resource (EV and PV) that unit possesses it is managed, and using the Spot Price Model of formula (7), each Agg is with user
The minimum target of electric cost, form is as follows:
Due to the influence of the living habit of car owner, human factor is made to have to examine as one for portraying EV charging flexibility
The link of worry.Therefore, this patent comprehensively considers owner information and EV information, establishes electric car restricted model.The restriction table
Show as follows:
0≤pev i,m,t≤Pmax (3)
The Agg of each node is pre- according to the photovoltaic maximum output that its lower distributed photovoltaic power generation unit managed is supplied to them
Measurement informationScheduling optimized to the active power output of photovoltaic generation unit, therefore its active power output is mainly by being limited are as follows:
In formula: ppvj,tFor the practical active power output value of t-th of moment photovoltaic of node j.
According to the above method, the preliminary power plan P of the production electricity consumption of distributed resource under each Agg can be obtainedevi,j,tWith
ppvi,j,t。
Step C:DSO network security is checked and the Dispatching adjustment under power adjustment signal guidance
Step C1:DSO network security is checked
DSO judges whether to meet security constraint, be expressed as follows to the preliminary power plan that Agg is submitted:
In formula:For the corresponding Lagrange multiplier of route bound security constraint；D is power transmission distribution transfer
The factor；Fl maxAnd Fl minThe bound for the active power that respectively branch l is allowed to flow through.PtIt is each node in the total active of t moment
Injecting power matrix.For the node location matrix for being connected to EV in description Aggi；For the section for being connected to photovoltaic in description Aggi
Point location matrix.ploadFor each node j t moment firm demand value
Step C2: the Dispatching adjustment under hair, the guidance of electric power adjustment signal
The formation of step C21 hair, electric power adjustment signal
It will be divided within 24 hours a few days ago NT time interval, the time span of each time interval is Δ t, with all Agg
User power utilization cost minimization be target, consider that network bi-directional trend constraint establishes the global optimization scheduling model of DSO, form is such as
Under:
s.t.(2)-(8)
In formula: B is coefficient of sensitivity of price matrix, and Na is the number of Agg in distribution.ΩiFor the distributed money of Aggi management
The distribution node set that source is connect；To be connected to EV node location matrix in description Aggi；To be connected to photovoltaic in description Aggi
Node location matrix.
DSO global optimization scheduling model decompose and change by subgradient algorithm based on Lagrange duality decomposition principle
In generation, solves, and is sent out, the calculation method of electric power adjustment signal, to realize distribution of the DSO to electric car and photovoltaic resources
Formula Optimized Operation.
Solve DSO Global Optimal Problem in a distributed manner with Lagrange duality decomposition method includes exactly institute by it originally
There are the Large-scale Optimization Problems for the resource and network constraint that Agg possesses to be decomposed into a series of independent small-sized optimization problems, often
A small-sized optimization problem only includes the related resource variable of respective Agg.Therefore, it is found by observation type DSO Global Optimal Problem,
Objective function can be decomposed directly, and constraint condition (2)-(6) are also independent from each other for each Agg, still may be used
Directly to decompose, coupling variable P is contained in Prescribed Properties (7)t, can not directly be decomposed, it is therefore desirable to first to it
It is decoupled.
Lagrange multiplier corresponding to constraint condition (7)Construction portion Lagrangian is as follows:
In formula: NL is total circuitry number in distribution, and NB is total number of nodes.
As it can be seen that coupling constraint (7) are added into target letter by introducing Lagrange multiplier in a manner of weighted sum
After number, the part Lagrangian of DSO Global Optimal Problem is also that can decouple.Obviously, dual function will can be solved
Coupling.
The then dual problem of DSO global optimization scheduling problem are as follows:
Therefore above formula is carried out to each Agg subproblem after Duality Decomposition according to Lagrange duality decomposition principle [25] are as follows:
S.t. (2)-(6) as it can be seen thatFor node j t-th of moment electric car electric power adjustment signal,Point
Not Wei node j the photovoltaic resources at t-th of moment generated output adjustment signal.
It is not difficult to find out that the adjustment signal also reflects influence of the line security constraint to Agg scheduling of resource plan.
It can be seen that dual problem (11) is the optimization problem of a nested form, outer layer is to about Lagrange multiplierVariable seeks maximum, and internal layer is to about each distributed resource power and variableMinimizing.
Step C21.1: it calculates about Lagrange multiplierSubgradient St
For dual function about Lagrange multiplierOuter layer optimization problem, this patent using subgradient algorithm into
Row solves.Subgradient algorithm is a kind of iterative solution method for solving convex function problem, due to dual functionIt is one recessed
Function, andIt is a convex function, therefore rightIt is solved using subgradient algorithm.
FunctionSubgradient S about Lagrange multipliertAre as follows:
Step C21.2:Since initial value is 0, when each iteration, is updated it:
In formula:For a constant step-size factor；K is current iteration number.Due to dual problem objective function be can
Micro-, select suitable constant step size to be iterated certifiable subgradient algorithm convergence.According to formula (12), in an iterative process, draw
Ge Lang multiplier is necessary for nonnegative number, therefore, if there is negative value appearance in iteration, the value should be set 0.WhereinIt can
When being counted as being got over line due to branch power both forward and reverse directions that formula (7) describe and being caused system congestion respectively, obstruction causes
Network cost Marginal Pricing.I.e. when the Agg production electric power plan submitted is not able to satisfy network constraint, corresponding limit
Electricity price returns to a positive number, is otherwise 0.
Step C21.3: the convergence criterion of iteration:
Two Lagrange multipliers that this patent introducesVital work is played on determining iteration convergence
With.When iterating toIterative increment be 0 when, meet just route constraint (7).The convergence criterion of iteration such as following formula institute
Show:
In formula: ε1For iteration convergence parameter.
Step C22: according to the hair of reaction network congestion situations, electric power adjustment signal, each Agg changes its Optimized Operation
Objective function in the process are as follows:
Agg carries out the hair electrical power plan of photovoltaic and electric car according to hair, electric power adjustment signal again excellent
Change, such iteration is until the requirement for meeting iteration convergence criterion.
4) operation plan is determined
DSO does network security check according to the hair electrical power plan of the Agg distributed resource reported, whether determines Agg
Day-ahead electricity market can be participated according to the power planning reported, Agg is participated in a few days ago by the power planning reported if executable
The transaction in market, otherwise return step C.
In conclusion the two-way congestion Dispatching Method of the proposed power distribution network towards electric system distributed resource
Calculation process is as follows:
(1) it initializes: settingAnd the iterative initial value of the number of iterations k is 0.
(2) each Agg according to formula (2)-(6), (12) to distributed resource optimize scheduling (can with Cplex solver into
Row solves), then by power planning as unit of nodeIt is reported to DSO.
(3) DSO considers that Cybersecurity Operation constraint calculates the hair of guidance Agg according to formula (12)-(14), electric power adjusts
SignalWith
(4) the number of iterations k=k+1 is set, convergence judgement is carried out according to formula (15), if convergence, terminates to calculate, Agg is obtained
Final hair electrical power plan.Otherwise, (2) are returned to, new power control signal is handed down to Agg, it is guided to re-start
Power adjustment.Its algorithm flow is as shown in Fig. 2.
Claims (7)
1. a kind of two-way congestion Dispatching Method of power distribution network towards electric system distributed resource, which is characterized in that with electronic vapour
Vehicle and photovoltaic generation unit are research object, give the distributed scheduling control of management electric car and adjustable photovoltaic resource first
System strategy, which is divided into two layers, and lower layer is by Load aggregation quotient Agg by being installed on control and the communication equipment pair of user side
Distributed resource in power distribution network is managed, and upper layer is responsible for carrying out net to the power planning of Agg by distribution system operator DSO
Network is checked, and guarantees distribution safe operation；This patent mention strategy can sufficiently dispatch it is mutual between power distribution network and distributed resource
Dynamic response avoids distributed resource during participating in Electricity Market Competition to the two-way obstructing problem of distribution bring, tool
Body includes:
1) each Agg collects the vehicle model information with vehicle habit and electric car of the electric car car owner of its management, then to electronic
The data of automobile resources are arranged, and by information such as the installation situation of acquisition distributed photovoltaic and weather conditions, are managed to it
The maximum output of the distributed photovoltaic resource of reason is predicted；
2) the energy management model of each Agg is established, each Agg considers the Electrical Safety and cost and photovoltaic resources of electric car
Maximum output situation carries out reasonably optimizing scheduling to it；
3) DSO carries out network security check, and the power planning reported according to Agg, DSO carries out network security check, according to route
Amount of blockage calculate hair, electric power adjustment signal and be handed down to Agg guide its carry out power adjustment；
4) determination of final operation plan.
2. the two-way congestion Dispatching Method of power distribution network according to claim 1 towards electric system distributed resource, feature
It is, the information needed after the step 1) information collection and arrangement specifically includes that the maximum charge power of electric car,
The networking of car owner and off-network time, the battery status information of electric car, the charge requirement of car owner, the maximum generating watt letter of photovoltaic
Breath, ahead market electricity price information.
3. the two-way congestion Dispatching Method of power distribution network according to claim 1 towards electric system distributed resource, feature
It is, the step 2) includes: to establish Agg layers of Optimized Operation mould a few days ago for electric car and photovoltaic resources based on step 1)
Type will be divided into NT time interval for 24 hours a few days ago, and the time span of each time interval is Δ t, and each Agg is with cost minimization
Optimal Operation Model is established for target, the form of objective function is as follows:
Distributed resource constraint representation is as follows:
0≤pev i,m,t≤Pmax
Wherein, pev i,m,tFor the m electric car under Aggi t scheduling slot charge power；PmaxMost for electric car
Big charge power；Ecap,mFor the battery capacity of the m electric car；SOC0,mFor the initial state-of-charge of the m vehicle, SOCmax,m
State-of-charge when for the m vehicle off-network, ηmFor the charge efficiency of the m electric car, Δ t is the length of each scheduling slot
Degree；tm0It networks for the m electric car and starts to receive the period of scheduling, tmdIndicate the period that the m vehicle leaves；When non-scheduled
The charge-discharge electric power of electric car is 0 in section；ppv i,j,tFor the practical active power output of t-th of moment photovoltaic of Aggi lower node j
Value；
According to above-mentioned model, the preliminary power plan P of the production electricity consumption of distributed resource under each Agg can be obtainedev i,j,tAnd ppv i,j,t。
4. the two-way congestion Dispatching Method of power distribution network according to claim 1 towards electric system distributed resource, feature
It is, the DSO of the step 3) carries out network security and checks to check whether the calculated preliminary power plan of Agg is able to satisfy line
Road security constraint, the constraint representation are
In formula:For the corresponding Lagrange multiplier of route bound security constraint；D is that power transmission is distributed transfer factor；
Fl maxAnd Fl minThe bound for the active power that respectively branch l is allowed to flow through, PtFor each node t moment total active injection
Power matrix,For the node location matrix for being connected to EV in description Aggi；For the node position for being connected to photovoltaic in description Aggi
Set matrix, ploadj,tFor each node j t moment firm demand value.
5. the two-way congestion Dispatching Method of power distribution network according to claim 1 towards electric system distributed resource, feature
It is, the hair of the step 3), the bootup process of electric power adjustment signal are that the power planning submitted for Agg is unsatisfactory for line
The case where road security constraint, comprising:
The calculation method of 5A. hair, electric power adjustment signal are as follows:
Hair of the 5B. according to reaction network congestion situations, electric power adjustment signal,
Each Agg changes the objective function during its Optimized Operation are as follows:
Agg carries out the hair electrical power plan of electric car and photovoltaic resources according to hair, electric power adjustment signal again excellent
Change, such iteration is until the requirement for meeting iteration convergence criterion.
6. the two-way congestion Dispatching Method of power distribution network according to claim 5 towards electric system distributed resource, feature
It is, the step 5A includes:
Step 5A1: it calculates about the corresponding Lagrange multiplier of network constraintSubgradient StAre as follows:
Step 5A2:Since initial value is 0, when each iteration, is updated it:
Step 5A3: the convergence criterion of iteration:
7. the two-way congestion Dispatching Method of power distribution network according to claim 1 towards electric system distributed resource, feature
It is, the determination of final operation plan includes: DSO according to the Agg electric car reported and distributed photovoltaic in the step 4)
The hair electrical power plan of resource does network security and checks such as formulaWhether determine Agg
Day-ahead electricity market can be participated according to the power planning reported, Agg is entered a few days ago by the power planning reported if executable
Market, otherwise return step 5A.
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| CN110247435A (en) * | 2019-07-17 | 2019-09-17 | 南方电网科学研究院有限责任公司 | Power distribution network blocking scheduling method |
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