CN109802387A - A kind of elastic power distribution network multistage service restoration method containing microgrid - Google Patents
A kind of elastic power distribution network multistage service restoration method containing microgrid Download PDFInfo
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Abstract
The elastic power distribution network multistage service restoration method containing microgrid that the invention discloses a kind of, recovery policy include that microgrid restores the three-level service restoration scheme that critical load, microgrid cooperate withs recovery critical load and microgrid to restore non-key load with power supply vehicle of meet an emergency.The three-level recovery scheme established can make full use of the electric energy supporting role of microgrid, energy-storage system to power distribution network under disaster, and then improve the elasticity of power distribution network.After guaranteeing critical load full recovery using preceding two-stage service restoration scheme, to restore non-key load to greatest extent as target start three-level service restoration scheme.Established mixed integer linear programming model is finally solved, the optimal power range of day part microgrid is obtained, and calculates power distribution network elastic index, promotion degree of the assessment this method to distribution elasticity of net.This method can maximize the elasticity of power distribution network while guaranteeing critical load full recovery.
Description
Technical field
The present invention relates to distribution network failures to restore field, extensive more particularly to a kind of multistage power supply for ensuring distribution elasticity of net
Multiple strategy.
Background technique
With Global climate change, increasingly frequent, caused massive blackout Frequent Accidents occur for extreme weather disaster,
Thus huge economic loss is brought.As the key link for directly serving in user, power distribution network is under extreme weather conditions
It operates normally, to guarantee people's production and living, resisting nature disaster accident, social development is pushed to be of great significance, the calamity of power distribution network
Thus evil adaptibility to response has received widespread attention.
Occur multiple failures under disaster, large-area power-cuts, lacks power supply and weak transmission is not uncommon for.In recent years complete
Many accidents that ball occurs highlighted electric system to it is difficult to predict extreme Disaster Event preparation it is insufficient, even extremely fragile
Weakness.Such as electric system is given in Fukushima, Japan violent earthquake and tsunami, the generation of the extreme events such as southern china ice damage in 2008
Serious destruction is brought, a wide range of, prolonged power failure is caused, seriously affects the power supply of resident living and load.
Existing many distribution network failure restoration methods are all without reference to the elasticity of power distribution network, but after disaster occurs,
The ability of promotion power distribution network reply low frequency extreme event and the ability for being restored to normal power supply state as early as possible are particularly important.Therefore
It can use the flexible resources such as distributed energy storage power station, distributed generation resource, microgrid and formulate multistage service restoration strategy to ensure to match
The elasticity of power grid makes the power distribution network under disaster be restored to normal power supply state as early as possible.
Summary of the invention
The object of the present invention is to provide a kind of multistage service restoration methods containing microgrid for being able to ascend distribution elasticity of net, originally
Invention uses master & slave control to micro-capacitance sensor, maintains microgrid stability, solves the problems, such as source lotus power-balance；It is proposed multistage service restoration
Method can optimize the confession of day part microgrid in the case where renewable energy is illuminated by the light the influence with wind speed with fluctuation
Electric range can maximize the elasticity of power distribution network on the basis of guaranteeing critical load full recovery；Calculate the elasticity of power distribution network
Index, comprehensive and accurate this recovery policy of assessing is to the promotion degree of elasticity.
To achieve the above object, specifically, the present invention provides a kind of elastic power distribution network multistage service restoration side containing microgrid
Method comprising following steps:
S1, the master-slave control method that micro-capacitance sensor is arranged simultaneously use light-preserved system to provide power supply for the micro-capacitance sensor；
The spare capacity model of S2, the mathematical model for establishing the light-preserved system and microgrid generation assets；
S3, distribution elasticity of net evaluation index and elastic probability distribution are calculated；
S4, it establishes while guaranteeing critical load full recovery, is supplied using maximizing distribution elasticity of net as the multistage of target
Electric recovery policy model；
S5, the three-level service restoration scheme for proposing multistage service restoration Policy model described in step S4；
S6, the multistage service restoration Policy model of power distribution network is solved and is obtained using the mathematical method of linear programming
The elastic index of system；
S7, simulation analysis is carried out to multistage service restoration Policy model.
Preferably, it is solved in the step S7 using CPLEX12.6 version in matlab software and the tool box YALMIP
Device carries out simulation analysis to example.
Preferably, the step S1 specifically includes the following steps:
S11, a micro- source is chosen as main control unit, other micro- sources are used as from control unit；
S12, by the controller of main control unit by PQ controlling tactic switch to Vf control strategy, adopted from the controller of control unit
It is constant with PQ control strategy.
Preferably, the step S2 specifically includes the following steps:
S21, assume in unit interval, the charge-discharge electric power of energy storage device is constant, by charging and recharging model with filling
Electricity condition indicates that mathematical model indicates are as follows:
In formula,For SOC state of the ESS in microgrid k in period t；It is ESS in microgrid k in period t-1
When SOC original state；Δ t is time step, takes Δ t=1h；For charge and discharge electric work of the ESS in microgrid k in period t-1
Rate, positive value indicate energy storage device charging, and negative value indicates ESS electric discharge；For the capacity of ESS in microgrid k；M is the collection of available microgrid
It closes；
S22, spare capacity model in microgrid is established:
Assuming that the generated energy of each a length of 1h of period analysis step, DGs and ESS are established spare in microgrid as unit of kW
In formula, T1There is spare capacity insufficient total time for the generation assets in microgrid k；xtIt is microgrid k within the t period
State, if microgrid k is that the maximum electricity that provides of its external load is less than external load aggregate demand, xt=1, if microgrid k
It is greater than external load aggregate demand for the maximum electricity that its external load provides, then xt=0；T0For the total power off time of failure；RkFor
The set for the power loss load that microgrid k restores；Δ t is time interval, takes Δ t=1h, Pi.tFor load i, power is needed within the t period
It asks；It is capable of providing in the t period to the maximum electricity of external load for microgrid k；For in microgrid k from power supply in the t period
Interior power output；It contributes within the t period for main power source in microgrid k；For critical load demand inside t period microgrid k.
Preferably, it in the step S21, to prevent ESS charge from overcharging or over-discharge, is limited using SOC state, formula
It is as follows:
In formula,For the SOC minimum value of ESS in microgrid k, take For ESS in microgrid k
SOC maximum value, take
Preferably, in the step S21, unit time period charge-discharge electric power is limited using following formula:
In formula,For maximum charge power in ESS unit time period in microgrid k；For ESS unit in microgrid k
Maximum discharge power in period；For binary variable, charged state is indicated, if ESS charges in period t in microgrid k
It is 1, if ESS discharges in period t in microgrid kIt is 0,For binary variable, discharge condition is indicated, if in microgrid k
ESS discharges then in period tIt is 1, if ESS charges in period t in microgrid kIt is not simultaneously in and fills for 0, ESS
Electricity and discharge condition.
Preferably, further, the step S3 specifically includes the following steps:
S31, distribution elasticity of net evaluation index is calculated
If td~taFor Restoration stage, guarantee to restore to restore to greatest extent on the basis of whole critical loads during this period
Non-key load, it is assumed that interruption duration T0, then failure is in td+T0When be repaired, i.e. ta=td+T0, in the period
The integral of system performance function objective function integral when subtracting Resuming agent and the failure-free operation of power supply vehicle of meet an emergency ratio
For the elasticity of power distribution network, it may be assumed that
In formula, AR is the elasticity of power distribution network；System performance function F (t) indicates the load total work for the priority weighted restored
Rate；G is the Resuming agent of power supply vehicle of meet an emergency；N is the quantity of power loss load in power distribution network；CiFor the weight factor of i-th of load；
PiIt (t) is active power of i-th of load in t moment；α is the cost loss coefficient of moving emergency supply vehicle；M is to pass through movement
The critical load number of nodes that power supply vehicle of meet an emergency restores；For restored by moving emergency supply vehicle i-thmThe wattful power of a load
Rate；
S32, the elastic model for defining system are as follows:
Wherein, n0、n1The respectively load quantity that can restore of Restoration stage；TiFor continuing for i-th of load being resumed
Power-on time；PiFor the active power of i-th of load under normal operating conditions.
Preferably, the step S4 specifically includes the following steps:
Step S41, the elastic power distribution network multistage service restoration method containing microgrid is established:
Its more intermediate service restoration strategy are made of three-level recovery scheme, restore the scheme, micro- of critical load comprising microgrid
Net cooperates with the scheme level-one microgrid for restoring critical load to restore the scheme of non-key load with power supply vehicle of meet an emergency；
It step S42, is each sharing of load weight factor to indicate its priority, the power distribution network service restoration based on microgrid
The elasticity of power distribution network maximizes match as far as possible while guaranteeing critical load full recovery power supply after strategy needs to consider to restore
Power grid elasticity, specifically:
C in formulaiFor the weight factor of i-th of load, weight factor should be greater than being equal to zero, if critical load then Ci>=1,
If non-key load then Ci≤0.05。
Preferably, detailed process is as follows by the step S5:
Step S51: the scheme that microgrid restores critical load is formulated:
A. the recovery tree from micro-capacitance sensor to critical load is determined；
For each one-to-one micro-capacitance sensor and critical load, unique restoration path is determined, the institute since micro-capacitance sensor
There is path to form the Graph Theory tree using micro-capacitance sensor as root, referred to as restore tree,
Unique restoration path problem is converted into shortest route problem to be solved, is non-directed graph G by Modeling of Distribution Network
=(V, E), wherein V and E is the set on node and side respectively, and the node in V indicates load and micro-capacitance sensor, and the arc expression in E is opened
It closes；And all micro-capacitance sensors are set as source node Vs, critical load is set as destination node Vt, each side [Vi, Vj] one weight of setting
W, value are equal to the active power of respective nodes load, Wij=∞ indicates Vi, VjTwo nodes are non-conterminous, if P is in G from VsTo Vt
A supply path, the power for defining path P is the sum of the power on all sides in P, is denoted as W (P), i.e. total load on restoration path
Amount, finds out corresponding VsTo VtAlways power and the smallest path are exactly shortest route problem in all paths, i.e., uniquely restore road
Diameter；
B. verifying initially restores the feasibility of tree:
Level-one trend constraint is constrained by the constraint of micro-capacitance sensor generation assets, energy storage device charge and discharge to assess every recovery tree
Feasibility, check whether the total load amount in each period on restoration path is more than corresponding by the constraint formula of generation assets
The available maximum power of micro-capacitance sensor, it is ensured that the continued power time of critical load is T0, trend constraint is reexamined, and utilize micro-
The control strategy of power grid come guarantee restore during micro-capacitance sensor stable operation always, it is extensive if meeting all of above constraint condition
Node on multiple path and while be added to node collection and while be concentrically formed recovery tree, restoration path is deleted if being unsatisfactory for,
After obtaining all feasible restoration paths with above method, the recovery situation of critical load can be obtained, if occurring same
When one critical load corresponds to two and two or more different recovery trees, according to the objective function in three-level recovery scheme, choosing
Always power and maximum exclusive path are selected in recovery tree, if there are two and two corresponding or more the different recoveries of same micro-capacitance sensor
When tree, it is merged into a restoration path, then verify feasibility again, if being unsatisfactory for without closing if Prescribed Properties
And retain total power and maximum restoration path, delete remaining restoration path；Final updating restores tree, determines each microgrid to pass
Unique restoration path of key load enables movement if there is also the critical loads not being resumed to use second level recovery scheme at this time
Power supply vehicle of meet an emergency goes to restore remaining critical load；
S52, microgrid cooperate with the scheme for restoring critical load with power supply vehicle of meet an emergency:
Moving emergency supply vehicle can access in any feeder line of power distribution network, both for single load power supply or can form orphan
Island is the power supply of more loads；More MEPS can combine emergency service with parallel running, supply for large-scale critical load or large-scale load group
Electricity, under disaster, if micro-capacitance sensor sends moving emergency supply vehicle pair when outage cannot restore critical load completely
The critical load not being resumed is powered, and output power indicates are as follows: PMEPS, the continued power time is T0。
S53 establishes the scheme that microgrid restores non-key load:
On the basis of critical load full recovery, in order to make full use of renewable energy in microgrid and energy-storage system
Power output, needs to start three-level recovery scheme, the purpose of three-level recovery scheme is to obtain day part micro-capacitance sensor global optimum
Supply district, but the fluctuation that renewable energy is contributed in microgrid will lead to non-key load that each period can restore not
Together, then the supply district of day part microgrid need to be successively obtained according to timing；
The scheme for restoring critical load based on microgrid, it is extensive by every after obtaining the corresponding unique recovery tree of each microgrid
Multiple tree is considered as new microgrid, and the maximum that microgrid is considered as new microgrid to the residual capacity after the upper whole load power supplies of corresponding recovery tree is gone out
Power, centered on new microgrid, the maximum output of new microgrid expands each new microgrid day part as power radius using in day part
Supply district, obtain the best supply district of each new microgrid of day part as target to restore non-key load to greatest extent:
In formula, yi,tFor binary variable, when non-key load obtains electric then y at bus i in the t periodi,tIt is 1, is otherwise 0；Dk
For the set of the microgrid k non-key load restored.
Preferably, in the step S53, guarantee that the load restored keeps the constraint of continued power state:
In formula, βi,j,tBinary variable indicates membership, the β when there is trend to flow to branch j by branch ii,j,tIt is 1, it is no
It is then 0, Si,tFor microgrid in the t period and bus i connection status, i.e. when bus i is root bus, Si,tIt is 1, is otherwise 0.
Preferably, detailed process is as follows by the step S6:
The problem of S61, application of mathematical method solve multilevel recovery scheme establishes and considers that the MIXED INTEGER of time scale is linear
Plan model；
S62, solving result can determine the non-key load that each microgrid day part restores and each non-key negative
The continued power time of lotus, in conjunction with preceding two-stage recovery scheme as a result, obtaining the operating status of each load, then calculating is elastic
Index AR.
Compared with prior art, the invention has the following advantages:
Master & slave control is used to micro-capacitance sensor, microgrid stability is maintained, solves the problems, such as source lotus power-balance；It is standby in recovery policy
With the model of capacity, it can guarantee critical load continued power in outage；It proposes multistage service restoration method, is provided in power generation
It when source is rare, can guarantee that critical load preferentially restores, there is fluctuation in the influence that renewable energy is illuminated by the light with wind speed
In the case of, the supply district of day part microgrid can be optimized, on the basis of guaranteeing critical load full recovery, can be maximized
The elasticity of power distribution network；The elastic index of power distribution network is calculated, comprehensive and accurate this recovery policy of assessing is to the promotion degree of elasticity.
Detailed description of the invention
Fig. 1 is a kind of flow chart of the elastic power distribution network multistage service restoration method containing microgrid provided by the invention；
Fig. 2 is system function function provided by the inventionF(t) change curve of t at any time；
Fig. 3 is the process that multiple microgrids provided by the invention restore tree to the most short restoration path composition of critical load
Figure；
Fig. 4 is the example structure chart of restoration methods provided by the invention；And
Fig. 5 is the typical daily output curve graph of photovoltaic provided by the invention, blower.
Specific embodiment
Below with reference to the attached drawing exemplary embodiment that the present invention will be described in detail, feature and aspect.It is identical attached in attached drawing
Icon note indicates element functionally identical or similar.Although the various aspects of embodiment are shown in the attached drawings, unless special
It does not point out, it is not necessary to attached drawing drawn to scale.
As shown in Figure 1, a kind of elastic power distribution network multistage service restoration method containing microgrid, multistage service restoration method packet
It includes:
Step 1: being that power loss load is powered on distribution feeder by micro-capacitance sensor isolated operation during disaster.It then needs to set
The control mode for setting micro-capacitance sensor establishes the charging and recharging model of energy-storage system in microgrid, spare capacity model.
Step 2: distribution is calculated according to the operating status and recovery capability of load in the multistage service restoration strategy of formulation
The elastic index of net.
Step 3: on the basis of elastic index, while to guarantee critical load full recovery, maximizing power distribution network bullet
Property for target establish controlled multistage service restoration strategy optimization model.
Step 4: restore the level-one scheme of critical load using microgrid first, it is preferential to restore critical load amount.Utilize formation
The feasible method for restoring tree, obtains the recovery situation of all critical loads.
Step 5: if critical load cannot be all resumed in the level-one recovery scheme that microgrid restores critical load, adopting
The second level scheme for restoring critical load is cooperateed with power supply vehicle of meet an emergency with microgrid, starting moving emergency supply vehicle goes to restore remaining crucial
Load.
Step 6: while guaranteeing critical load full recovery, restore the three-level scheme of non-key load using microgrid, with
Restoring non-key load to greatest extent is target, obtains the best supply district of day part microgrid.
Step 7: while finally to guarantee critical load full recovery, maximization distribution elasticity of net be target, in conjunction with
The restoration result of upper three-level power supply plan obtains the recovery policy of global optimum, and it is extensive to utilize elastic index accurately to assess this
Influence of the multiple strategy to elasticity.
Energy-storage system charging and recharging model specifically includes in the microgrid of foundation:
Energy-storage battery using lead storage battery as ESS, it is assumed that in unit interval, the charge and discharge function of battery
Rate is constant, charging and recharging model is indicated with charged state (State-of-Charge, SOC), mathematical model may be expressed as:
In formula,For SOC state of the ESS in microgrid k in period t；It is ESS in microgrid k in period t-1
When SOC original state；Δ t is time step, takes Δ t=1h；For charge and discharge electric work of the ESS in microgrid k in period t-1
Rate, positive value indicate ESS charging, and negative value indicates ESS electric discharge；For the capacity of ESS in microgrid k；M is the set of available microgrid.
For prevent ESS charge overshoot or over-discharge, have SOC state limit:
In formula,For the SOC minimum value of ESS in microgrid k, take For ESS in microgrid k
SOC maximum value, take
In view of ESS charge-discharge electric power size is related with the service life of battery, there is the limitation of unit time period charge-discharge electric power:
In formula,For maximum charge power in ESS unit time period in microgrid k；For ESS unit in microgrid k
Maximum discharge power in period；For binary variable, charged state is indicated, if ESS charges in period t in microgrid k
It is 1, is otherwise 0,For binary variable, discharge condition is indicated, if ESS discharges in period t in microgrid kIt is 1, it is no
Then charging and discharging state is not simultaneously in for 0, ESS.
Spare capacity model specifically includes in the microgrid of foundation:
The insufficient concept of spare capacity is introduced, renewable energy in micro-capacitance sensor is handled using the master & slave control of microgrid and is gone out
Power has the problem of intermittent, fluctuation.Spare capacity deficiency, which refers in micro-capacitance sensor, to be reduced from power suddenly or for circuit
When load increases suddenly in diameter, the capacity or charge-discharge electric power of main power source are not able to satisfy the power-balance on the supply path.?
The generation assets spare capacity insufficient time in statistics micro-capacitance sensor in total power off time, it is assumed that each a length of 1h of period analysis step,
This means that power is equal with generated energy.The generated energy of DGs and ESS is all as unit of kW.
In formula, T1There is spare capacity insufficient total time for the generation assets in microgrid k；xtIt is microgrid k within the t period
State, if the maximum electricity that microgrid k can provide for its external load is less than external load aggregate demand, xt=1, otherwise
xt=0；T0For the total power off time of failure；RkFor the set of the microgrid k power loss load restored；Δ t is time interval, takes Δ t=1h
Pi.tFor load i within the t period power demand；It is capable of providing in the t period to the maximum electricity of external load for microgrid k；To contribute within the t period in microgrid k from power supply (uncontrollable DG)；It is main power source (energy storage device) in microgrid k in the t period
Interior power output, when energy-storage system is as balance nodes, will not only meet above formula, also guarantee energy storage charge state (state of
Charge, SOC) within zone of reasonableness；For critical load demand inside t period microgrid k.
As shown in Fig. 2, the change curve of system function function F (t) t at any time, can characterize system load condition and
The recovery situation of system in recovery policy on the basis of load operating region, obtains power distribution network elastic index:
If td~taFor Restoration stage, guarantee to restore to restore to greatest extent on the basis of whole critical loads during this period
Non-key load, it is assumed that interruption duration T0, then failure is in td+T0When be repaired, i.e. ta=td+T0.The present invention uses
The system recovery capability of Restoration stage assesses the elasticity of power distribution network, i.e. the integral of system performance function in the period subtracts
The ratio that objective function integrates when the Resuming agent of power supply vehicle of meet an emergency and failure-free operation, it may be assumed that
In formula, system performance function F (t) indicates the load general power for the priority weighted restored；G is power supply vehicle of meet an emergency
Resuming agent.N is the quantity of power loss load in power distribution network；CiFor the weight factor of i-th of load；PiIt (t) is i-th of load in t
The active power at moment；α is the cost loss coefficient of moving emergency supply vehicle；M is the pass restored by moving emergency supply vehicle
Key load bus number；For restored by moving emergency supply vehicle i-thmThe active power of a load.
It is defined as four kinds of operating statuses in Restoration stage load, as shown in table 1
The operating status of 1 load of table
In table, n0、n1The respectively load quantity that can restore of Restoration stage；TiFor continuing for i-th of load being resumed
Power-on time；PiFor the active power of i-th of load under normal operating conditions.That is the elasticity of system is represented as:
As shown in figure 3, with formed multiple microgrids to critical load most short restoration path method, obtain micro-capacitance sensor can
Row restores the recovery situation of tree and critical load, specifically includes:
1) the recovery tree from micro-capacitance sensor to critical load is determined；
It is right for each " micro-capacitance sensor-critical load ", determine unique restoration path or they between can not walking along the street
Diameter.All paths since micro-capacitance sensor are formed using micro-capacitance sensor as the Graph Theory tree of root, and tree is referred to as restored.
Unique restoration path problem is converted into shortest route problem to be solved.It is non-directed graph G by Modeling of Distribution Network
=(V, E), wherein V and E is the set on node and side respectively, and the node in V indicates load and micro-capacitance sensor, and the arc expression in E is opened
It closes.In addition, and all micro-capacitance sensors are set as source node Vs, critical load is set as destination node Vt.Each side [V in figurei, Vj] set
A weight W is set, value is equal to the active power (W of respective nodes loadij=∞ indicates Vi, VjTwo nodes are non-conterminous), if P is
From V in GsTo VtA supply path, the power for defining path P is the sum of the power on all sides in P, is denoted as W (P), i.e. restoration path
On total load amount.Find out corresponding VsTo VtAlways power and the smallest path are exactly shortest route problem in all paths, i.e., uniquely
Restoration path.
2) the initial feasibility for restoring tree of verifying
Every is assessed by the constraint of micro-capacitance sensor generation assets, energy storage device charge and discharge constraint, trend constraint restores tree
Feasibility, the load not on restoration path disconnect.It is checked by the constraint formula of generation assets and is restored in each period
Whether the total load amount on path is more than the corresponding available maximum power of micro-capacitance sensor, it is ensured that the continued power time of critical load
For T0, reexamine trend constraint.And micro-capacitance sensor stable operation always during guaranteeing to restore using the control strategy of micro-capacitance sensor.Such as
Fruit meets all of above constraint condition, then the node on restoration path and while be added to node collection and while be concentrically formed recovery
Tree.If being unsatisfactory for deleting restoration path.
After obtaining all feasible restoration paths with above method, the recovery situation of critical load can be obtained, if occurring
When two and two corresponding or more the different recovery tree of same critical load, according to the objective function in three-level recovery scheme,
Selection restores always to weigh and maximum exclusive path in tree.If it is two and two corresponding or more different extensive same micro-capacitance sensor occur
When setting again, it is merged into a restoration path, then verify feasibility again, if being unsatisfactory for without closing if Prescribed Properties
And retain total power and maximum restoration path, delete remaining restoration path.Final updating restores tree, determines each microgrid to pass
Unique restoration path of key load enables movement if there is also the critical loads not being resumed to use second level recovery scheme at this time
Power supply vehicle of meet an emergency goes to restore remaining critical load.
Multistage service restoration strategy is solved using the mathematical method of linear programming；
Specific step is as follows:
1) the elastic power distribution network multistage service restoration method Optimized model containing microgrid is established according to elastic evaluation index.
The elasticity of power distribution network after power distribution network service restoration strategy based on microgrid needs to consider to restore is guaranteeing that key is negative
While lotus full recovery is powered, distribution elasticity of net, form are maximized as far as possible are as follows:
C in formulaiFor the weight factor of i-th of load, it is however generally that weight factor should be greater than being equal to zero, if critical load
Then Ci>=1, if non-key load then Ci≤0.05。
It includes: generation assets constraint, spoke that elastic power distribution network multistage service restoration method containing microgrid, which needs the constraint met,
Shape constraint, trend constraint are penetrated, and guarantees micro-capacitance sensor even running.
2) it assigns initial value: assigning corresponding weight value to each side, initialize network data, determine power off time；
Each side right value is the active power of corresponding load, and determines source node, destination node set；
3) it forms initial recovery tree: being formed using the method for linear programming and restore tree；
With the minimum target of total load amount on restoration path, shortest supply path is found；
4) capacity of photovoltaic according to Fig.5, blower typical case's sunrise force curve and ESS obtain the maximum of day part microgrid
Power output；
5) it calculates: critical load amount, the initial load aggregate demand restored on tree in microgrid；
6) verifying restores tree: is judged in each period initial restoration path, until all meeting in day part all
After constraint condition, path is added and restores tree；
7) recovery situation of the final recovery tree of each microgrid and critical load is determined according to level-one recovery scheme；
If 8) critical load full recovery, the linear programming model that microgrid restores non-key load is solved, day part is obtained
The best supply district of micro-capacitance sensor, and the continued power time of non-key load being resumed.
Microgrid restores the linear programming model of non-key load
The best supply district of each new microgrid of day part is obtained as target to restore non-key load to greatest extent:
In formula, yi,tFor binary variable, when non-key load obtains electric then y at bus i in the t periodi,tIt is 1, is otherwise 0；Dk
For the set of the microgrid k non-key load restored.
Guarantee that the load restored keeps the constraint of continued power state:
In formula, Si,tFor microgrid in the t period and bus i connection status, i.e. when bus i is root bus, Si,tBe 1, otherwise for
0；
9) it forms optimal recovery scheme: according to the restoration result solved in each level restoration scheme, obtaining guaranteeing to close
While key load full recovery, the optimal recovery scheme of distribution elasticity of net is maximized, sees the restoration result in example；
10) calculate: according to the recovery situation of system, the operating status of load seeks the continued power time of each load
Ti, finally calculate the elastic index AR under the recovery policy；
Simulation analysis is carried out to example with matlab software；
This paper example verifies proposed multistage herein as test macro using 69 node standard distributed system of U.S. PG&E
The validity of service restoration strategy, system nominal voltage are 12.66KV, rated power 4059.5kW+2865.8kvar, contact
Switch has 5, is indicated by Fig. 4 dotted line.Two type loads are contemplated herein, are critical load and non-key load respectively, node 43,
55,20,24,67 be critical load, and weight coefficient 1.5, other loads are all non-key load, weight coefficient 0.05.For
Influence of the microgrid to distribution elasticity of net is considered in verification process, node 7,44,64 accesses MGs, as shown in figure 4, wherein MG1
In generation assets be generation assets in photovoltaic generating system DG and energy-storage system ESS, MG2, MG3 be wind generator system and
Energy-storage system, position of failure point are shown in Fig. 4.
Using matlab software programming linear planner, with CPLEX12.6 version solver pair in the tool box YALMIP
Example carries out simulation analysis；
By emulation it is found that the model can to ESS Optimized Operation, can while guaranteeing critical load full recovery,
The elasticity for maximizing power distribution network, obtains the optimal supply district of day part power distribution network.
Microgrid restores the restoration result of the level-one scheme of critical load:
Table 1 restores tree
The restoration result of second level scheme: starting power supply vehicle of meet an emergency restores critical load 67, and the continued power time is T0.
Microgrid restores the restoration result of the three-level scheme of non-key load:
2 day part microgrid supply district of table
Each embodiment in this specification is described in a progressive manner, the highlights of each of the examples are with other
The difference of embodiment, the same or similar parts in each embodiment may refer to each other.For system disclosed in embodiment
For, since it is corresponded to the methods disclosed in the examples, so being described relatively simple, related place is said referring to method part
It is bright.
Finally, it should be noted that above-described embodiments are merely to illustrate the technical scheme, rather than to it
Limitation；Although the present invention is described in detail referring to the foregoing embodiments, those skilled in the art should understand that:
It can still modify to technical solution documented by previous embodiment, or to part of or all technical features into
Row equivalent replacement；And these modifications or substitutions, it does not separate the essence of the corresponding technical solution various embodiments of the present invention technical side
The range of case.
Claims (10)
1. a kind of elastic power distribution network multistage service restoration method containing microgrid, it is characterised in that: itself the following steps are included:
S1, the master-slave control method that micro-capacitance sensor is arranged simultaneously use light-preserved system to provide power supply for the micro-capacitance sensor；
The spare capacity model of S2, the mathematical model for establishing the light-preserved system and microgrid generation assets；
S3, distribution elasticity of net evaluation index and elastic probability distribution are calculated；
S4, it establishes while guaranteeing critical load full recovery, it is extensive as the power supply of the multistage of target to maximize distribution elasticity of net
Multiple Policy model；
S5, the three-level service restoration scheme for proposing multistage service restoration Policy model described in step S4；
S6, the multistage service restoration Policy model of power distribution network is solved using the mathematical method of linear programming and obtains system
Elastic index；
S7, simulation analysis is carried out to multistage service restoration Policy model.
2. the elastic power distribution network multistage service restoration method according to claim 1 containing microgrid, it is characterised in that: the step
Simulation analysis is carried out to example using CPLEX12.6 version solver in matlab software and the tool box YALMIP in rapid S7.
3. the elastic power distribution network multistage service restoration method according to claim 1 containing microgrid, it is characterised in that: the step
Rapid S1 specifically includes the following steps:
S11, a micro- source is chosen as main control unit, other micro- sources are used as from control unit；
S12, by the controller of main control unit by PQ controlling tactic switch to Vf control strategy, use PQ from the controller of control unit
Control strategy is constant.
4. the elastic power distribution network multistage service restoration method according to claim 3 containing microgrid, it is characterised in that: the step
Rapid S2 specifically includes the following steps:
S21, assume in unit interval, the charge-discharge electric power of energy storage device is constant, by charging and recharging model charging shape
State indicates that mathematical model indicates are as follows:
In formula,For SOC state of the ESS in microgrid k in period t；For ESS in microgrid k in period t-1 SOC
Original state；Δ t is time step, takes Δ t=1h；For charge-discharge electric power of the ESS in period t-1 in microgrid k, just
Value indicates energy storage device charging, and negative value indicates ESS electric discharge；For the capacity of ESS in microgrid k；M is the set of available microgrid；
S22, spare capacity model in microgrid is established:
Assuming that the generated energy of each a length of 1h of period analysis step, DGs and ESS establish spare capacity in microgrid as unit of kW
Model is as follows, wherein DGs is distributed generation resource, and ESS is energy-storage system:
In formula, T1There is spare capacity insufficient total time for the generation assets in microgrid k；xtFor shape of the microgrid k within the t period
State, if microgrid k is that the maximum electricity that its external load provides is less than external load aggregate demand, xt=1, if microgrid k is it
The maximum electricity that external load provides is greater than external load aggregate demand, then xt=0；T0For the total power off time of failure；RkFor microgrid
The set for the power loss load that k restores；Δ t is time interval, takes Δ t=1h, Pi.tFor load i within the t period power demand；It is capable of providing in the t period to the maximum electricity of external load for microgrid k；To go out within the t period in microgrid k from power supply
Power；It contributes within the t period for main power source in microgrid k；For critical load demand inside t period microgrid k.
5. the elastic power distribution network multistage service restoration method according to claim 4 containing microgrid, it is characterised in that: the step
In rapid S21, to prevent ESS charge from overcharging or over-discharge, limited using SOC state, formula is as follows:
In formula,For the SOC minimum value of ESS in microgrid k, take For the SOC of ESS in microgrid k
Maximum value takes
6. the elastic power distribution network multistage service restoration method according to claim 4 containing microgrid, it is characterised in that: the step
In rapid S21, unit time period charge-discharge electric power is limited using following formula:
In formula,For maximum charge power in ESS unit time period in microgrid k；For ESS unit time period in microgrid k
Interior maximum discharge power；For binary variable, charged state is indicated, if ESS charges in period t in microgrid kIt is 1,
If ESS discharges in period t in microgrid kIt is 0,For binary variable, discharge condition is indicated, if ESS exists in microgrid k
It discharges then in period tIt is 1, if ESS charges in period t in microgrid kCharging is not simultaneously in for 0, ESS and is put
Electricity condition.
7. the elastic power distribution network multistage service restoration method according to claim 1 containing microgrid, it is characterised in that: the step
Rapid S3 specifically includes the following steps:
S31, distribution elasticity of net evaluation index is calculated
If td~taFor Restoration stage, guarantee to restore during this period to restore non-pass to greatest extent on the basis of whole critical loads
Key load, it is assumed that interruption duration T0, then failure is in td+T0When be repaired, i.e. ta=td+T0, in the period is
The ratio of the integral of system performance function objective function integral when subtracting Resuming agent and the failure-free operation of power supply vehicle of meet an emergency for
The elasticity of power grid, it may be assumed that
In formula, AR is the elasticity of power distribution network；System performance function F (t) indicates the load general power for the priority weighted restored；G
For the Resuming agent of power supply vehicle of meet an emergency；N is the quantity of power loss load in power distribution network；CiFor the weight factor of i-th of load；Pi(t)
For i-th of load t moment active power；α is the cost loss coefficient of moving emergency supply vehicle；M is to pass through moving emergency
The critical load number of nodes that supply vehicle restores；For restored by moving emergency supply vehicle i-thmThe active power of a load；
S32, the elastic model for defining system are as follows:
Wherein, n0、n1The respectively load quantity that can restore of Restoration stage；TiFor the continued power for i-th of load being resumed
Time；PiFor the active power of i-th of load under normal operating conditions.
8. the elastic power distribution network multistage service restoration method according to claim 7 containing microgrid, it is characterised in that: the step
Rapid S4 specifically includes the following steps:
Step S41, the elastic power distribution network multistage service restoration method containing microgrid is established:
Its more intermediate service restoration strategy are made of three-level recovery scheme, and three-level recovery scheme includes that microgrid restores critical load
Scheme, microgrid cooperate with the scheme for restoring critical load with power supply vehicle of meet an emergency and microgrid restores the scheme of non-key load；
It step S42, is each sharing of load weight factor to indicate its priority, specifically:
C in formulaiFor the weight factor of i-th of load, weight factor should be greater than being equal to zero, if critical load then Ci>=1, if
Non-key load then Ci≤0.05。
9. the elastic power distribution network multistage service restoration method according to claim 8 containing microgrid, it is characterised in that: the step
Detailed process is as follows by rapid S5:
Step S51: the scheme that microgrid restores critical load is formulated:
A. the recovery tree from micro-capacitance sensor to critical load is determined；
For each one-to-one micro-capacitance sensor and critical load, unique restoration path is determined, all roads since micro-capacitance sensor
Diameter is formed using micro-capacitance sensor as the Graph Theory tree of root, and tree is referred to as restored,
It is non-directed graph G=(V, E) by Modeling of Distribution Network, wherein V and E is the set on node and side respectively, and the node in V indicates negative
Lotus and micro-capacitance sensor, the arc in E indicate switch；All micro-capacitance sensors are set as source node Vs, critical load is set as destination node Vt,
Each side [Vi, Vj] one weight W of setting, active power of the value equal to respective nodes load, Wij=∞ indicates Vi, VjTwo nodes
It is non-conterminous, if P is in G from VsTo VtA supply path, the weight for defining path P is the weights sum on all sides in P, note
For W (P), total load amount on W (P) i.e. restoration path finds out corresponding VsTo VtIt is always weighed with the smallest path just in all paths
It is the i.e. unique restoration path of shortest route problem；
B. verifying initially restores the feasibility of tree:
Every recovery tree is assessed by the constraint of micro-capacitance sensor generation assets, energy storage device charge and discharge constraint and level-one trend constraint
Feasibility, specifically: check total load amount in each period on restoration path is whether by the constraint formula of generation assets
More than the available maximum power of corresponding micro-capacitance sensor, it is ensured that the continued power time of critical load is T0, trend constraint is reexamined,
And micro-capacitance sensor stable operation always during guaranteeing to restore using the control strategy of micro-capacitance sensor, if meeting all of above constraint item
Part, then the node on restoration path and while be added to node collection and while be concentrically formed recovery tree, it is extensive that this is deleted if being unsatisfactory for
Multiple path can obtain the recovery situation of critical load after obtaining all feasible restoration paths with above method, if occurring same
When a critical load corresponds to two and two or more different recovery trees, according to the objective function in three-level recovery scheme, selection
Restore total weight value and maximum unique restoration path in tree, if it is two and two corresponding or more different same micro-capacitance sensor occur
When restoring tree, it is merged into a unique restoration path, then verify feasibility again, if Prescribed Properties not if being unsatisfactory for
It merges, retains total weight value and maximum restoration path, delete remaining restoration path；Final updating restores tree, determines each
Microgrid to critical load unique restoration path, if at this time there is also the critical load not being resumed use second level recovery scheme,
Enable moving emergency power up residue critical load；
S52, microgrid cooperate with the scheme for restoring critical load with power supply vehicle of meet an emergency:
Moving emergency supply vehicle can access in any feeder line of power distribution network, both can be single load power supply or form isolated island and be
More load power supplies；More MEPS can combine emergency service with parallel running, power for large-scale critical load or large-scale load group,
Under disaster, if micro-capacitance sensor sends moving emergency supply vehicle to not when outage cannot restore critical load completely
The critical load being resumed is powered, and output power indicates are as follows: PMEPS, the continued power time is T0；
S53 establishes the scheme that microgrid restores non-key load:
On the basis of critical load full recovery, in order to make full use of going out for renewable energy in microgrid and energy-storage system
Power, needs to start three-level recovery scheme, and the purpose of three-level recovery scheme is the confession in order to obtain day part micro-capacitance sensor global optimum
Electric range, but the fluctuation that renewable energy is contributed in microgrid will lead to non-key load that each period can restore not
Together, then the supply district of day part microgrid need to be successively obtained according to timing；
The scheme for being restored critical load based on microgrid is set every recovery after obtaining the corresponding unique recovery tree of each microgrid
It is considered as new microgrid, microgrid is considered as to the maximum output of new microgrid to the residual capacity after the upper whole load power supplies of corresponding recovery tree,
Centered on new microgrid, the maximum output of new microgrid expands each new microgrid day part as power radius using in day part
Supply district obtains the best supply district of each new microgrid of day part as target to restore non-key load to greatest extent:
In formula, yi,tFor binary variable, when non-key load obtains electric then y at bus i in the t periodi,tIt is 1, is otherwise 0；DkFor microgrid
The set for the non-key load that k restores；
In step S53, guarantee that the load restored keeps the constraint of continued power state:
In formula, βi,j,tBinary variable indicates membership, the β when there is trend to flow to branch j by branch ii,j,tIt is 1, is otherwise 0,
Si,tFor microgrid in the t period and bus i connection status, i.e. when bus i is root bus, Si,tIt is 1, is otherwise 0.
10. the elastic power distribution network multistage service restoration method according to claim 1 containing microgrid, it is characterised in that: described
Detailed process is as follows by step S6:
The problem of S61, application of mathematical method solve multilevel recovery scheme；
S62, solving result can determine the non-key load that each microgrid day part restores and each non-key load
Then the continued power time calculates elastic index in conjunction with preceding two-stage recovery scheme as a result, obtain the operating status of each load
AR。
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