CN106099964A  A kind of energystorage system participates in active distribution network runing adjustment computational methods  Google Patents
A kind of energystorage system participates in active distribution network runing adjustment computational methods Download PDFInfo
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 CN106099964A CN106099964A CN201610430803.XA CN201610430803A CN106099964A CN 106099964 A CN106099964 A CN 106099964A CN 201610430803 A CN201610430803 A CN 201610430803A CN 106099964 A CN106099964 A CN 106099964A
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Classifications

 H—ELECTRICITY
 H02—GENERATION; CONVERSION OR DISTRIBUTION OF ELECTRIC POWER
 H02J—CIRCUIT ARRANGEMENTS OR SYSTEMS FOR SUPPLYING OR DISTRIBUTING ELECTRIC POWER; SYSTEMS FOR STORING ELECTRIC ENERGY
 H02J3/00—Circuit arrangements for ac mains or ac distribution networks
 H02J3/28—Arrangements for balancing of the load in a network by storage of energy
 H02J3/32—Arrangements for balancing of the load in a network by storage of energy using batteries with converting means

 H—ELECTRICITY
 H02—GENERATION; CONVERSION OR DISTRIBUTION OF ELECTRIC POWER
 H02J—CIRCUIT ARRANGEMENTS OR SYSTEMS FOR SUPPLYING OR DISTRIBUTING ELECTRIC POWER; SYSTEMS FOR STORING ELECTRIC ENERGY
 H02J2203/00—Indexing scheme relating to details of circuit arrangements for AC mains or AC distribution networks
 H02J2203/20—Simulating, e g planning, reliability check, modelling or computer assisted design [CAD]

 Y—GENERAL TAGGING OF NEW TECHNOLOGICAL DEVELOPMENTS; GENERAL TAGGING OF CROSSSECTIONAL TECHNOLOGIES SPANNING OVER SEVERAL SECTIONS OF THE IPC; TECHNICAL SUBJECTS COVERED BY FORMER USPC CROSSREFERENCE ART COLLECTIONS [XRACs] AND DIGESTS
 Y02—TECHNOLOGIES OR APPLICATIONS FOR MITIGATION OR ADAPTATION AGAINST CLIMATE CHANGE
 Y02E—REDUCTION OF GREENHOUSE GAS [GHG] EMISSIONS, RELATED TO ENERGY GENERATION, TRANSMISSION OR DISTRIBUTION
 Y02E10/00—Energy generation through renewable energy sources
 Y02E10/50—Photovoltaic [PV] energy
 Y02E10/56—Power conversion systems, e.g. maximum power point trackers

 Y—GENERAL TAGGING OF NEW TECHNOLOGICAL DEVELOPMENTS; GENERAL TAGGING OF CROSSSECTIONAL TECHNOLOGIES SPANNING OVER SEVERAL SECTIONS OF THE IPC; TECHNICAL SUBJECTS COVERED BY FORMER USPC CROSSREFERENCE ART COLLECTIONS [XRACs] AND DIGESTS
 Y02—TECHNOLOGIES OR APPLICATIONS FOR MITIGATION OR ADAPTATION AGAINST CLIMATE CHANGE
 Y02E—REDUCTION OF GREENHOUSE GAS [GHG] EMISSIONS, RELATED TO ENERGY GENERATION, TRANSMISSION OR DISTRIBUTION
 Y02E70/00—Other energy conversion or management systems reducing GHG emissions
 Y02E70/30—Systems combining energy storage with energy generation of nonfossil origin
Abstract
The present invention provides a kind of energystorage system to participate in active distribution network runing adjustment computational methods, energystorage system for accumulator composition, with the minimum object function of distribution network system active loss, the operation constraint of consideration system self, constraint is run including system load flow constraint, working voltage constraint, branch current constraint and energystorage system, use particle cluster algorithm that example is solved, finally export under meeting system reliability premise the chargedischarge electric power of energystorage system day part as optimal solution.The present invention, compared to traditional method, can effectively reduce the active power loss of distribution network system, reduces operation of power networks cost, adds the utilization ratio of photovoltaic energy.
Description
Technical field
The present invention relates to a kind of energystorage system and participate in active distribution network runing adjustment technology, be specifically related to a kind of accumulator storage
System can participate in active distribution network runing adjustment computational methods.
Background technology
By the dualpressure of energy and environment, the distributed generation technology with renewable energy utilization as core is at world's model
Enclose interior extensive rise, be greatly promoted energy storage technology application in power system and development.On the one hand, by means of energy storage system
System can efficiently reduce distributed power source and exert oneself the impact that intermittent and randomness brought, and is formed with microcapacitance sensor as core
Selfgovernment system；On the other hand, jumbo energystorage system provides new means and side also to the runing adjustment of power distribution network
Method.In terms of distribution system angle, the application of energy storage technology can not only improve the digestion capability of distributed energy, additionally it is possible to actively
Participate in the effectively regulation of system load flow and optimize, can greatly improve economy and reliability that distribution system is run.
How to make full use of energystorage system, it is achieved the emphasis that the high efficient and reliable of distribution system is paid close attention to when running at present, domestic
It is studied by outer relevant learning, and achieves the achievement in terms of some theory and practice, as analyzed accumulator position
Put the impact of distribution and amount of capacity, and the positive role that peak regulation is played；Have studied containing distributed power source and accumulator
Power distribution network/microcapacitance sensor running optimizatin problem, give storage battery active power and mathematical model that reactive power is optimized simultaneously；
And according to the schedulable characteristic of accumulator and quantity of electric charge information, it is proposed that a kind of based on constant current constant voltage control strategy
Accumulator cell charging and discharging mathematical model.
Different from distributed power source, the operation of energystorage system has obvious temporal characteristics, and its running optimizatin no longer limits to
Discontinuity surface when single, but expand in longer time scale, there is sequential running optimizatin problem, and then cause it certainly
The increasing and increase rapidly of plan dimension section number in time.
Summary of the invention
The goal of the invention of the present invention is for solving the problems referred to above, participates in active distribution network for energystorage system of accumulator and runs
The Optimal Operation Model of regulation, it is provided that a kind of energystorage system participates in active distribution network runing adjustment computational methods.
For solving abovementioned technical problem, embodiments of the invention provide a kind of energystorage system to participate in active distribution network operation and adjust
Joint computational methods, comprise the steps:
(1) consider the meritorious of energystorage system and idle characteristic, set up energystorage system moving model；
(2) determine that energystorage system participates in the object function of active distribution network runing adjustment and is: the meritorious damage of distribution network system
Consumption minimum；
(3) the operation constraint of distribution network system self is taken into account during calculating, including system load flow constraint, working voltage about
The constraint of bundle, branch current and energystorage system run constraint；
(4) PSO Algorithm energystorage system is utilized to participate in the Optimized model of power distribution network runing adjustment；
(5) output optimal solution: under meeting distribution network system reliability premise, the chargedischarge electric power of energystorage system day part
It is optimal solution.
As a example by typical energystorage system of accumulator, it is mainly made up of accumulator and inverter, and inverter is mainly responsible for
Monitor operation of power networks situation, send the work such as control signal.The electric interfaces that inverter is connected with electrical network as accumulator, is to store
Battery energy storage system and power distribution network carry out the hinge of energy exchange, it is possible to realize the charge and discharge control of active power, and, the change of current
Utensil has certain idle miscellaneous function, while performing charging and discharging function, can be power distribution network by idle control
Voltage support is provided.
Wherein, when step (1) setting up energystorage system of accumulator moving model, it is assumed that energystorage system of accumulator is with to distribution
Net output is positive direction, considers its meritorious and idle characteristic, and running boundary constraint is as follows:
In formula: k=1,2 ..., N_{ESS}, wherein N_{ESS}For energystorage system of accumulator number；WithWhen being respectively t
Carve active power and the reactive power of the output of kth inverter；WithBe respectively kth inverter rated capacity and
The active power upper limit；WithIt is respectively the chargedischarge electric power of energystorage system of accumulator.
Step (1), it is assumed that energystorage system of accumulator with to power distribution network output as positive direction, then energystorage system of accumulator
Input power is negative direction, naturally it is also possible to assuming that energystorage system of accumulator with to power distribution network output as negative direction, then store
Battery energy storage system input power is positive direction, is suitable for this optimizing regulation computational methods.
The stateofcharge of described energystorage system of accumulator has absolute seriality in sequential, and it is suitable in strict accordance with the time
Sequence carries out accumulation according to chargedischarge electric power size and calculates, and computing formula is as follows:
In formula: k=1,2 ..., N_{ESS}；Δ t is simulation step length；Lotus for t kth energystorage system of accumulator
Electricity condition；
The energy storage capacity of each time point of described energystorage system of accumulator should meet the requirement of stateofcharge bound, expression formula
As follows:
In formula,It is respectively capacity and the stateofcharge of kth energystorage system of accumulator
Upper lower limit value.
Power distribution network running optimizatin problem containing energystorage system is generally exerted oneself with cost of electricitygenerating, the whole network active loss, transformer station
The combinations of minimum, new forms of energy receiving ability maximum and plurality of target function etc. are optimization aim, having of described distribution network system
It is each that merit loss deducts the active power that load is consumed, i.e. distribution network system by the active power that whole distribution network system is injected
The active power sum that individual node injects, with the minimum object function of distribution network system active loss in abovementioned step (2), its
Mathematic(al) representation is:
In formula, N is system node number；N_{T}For time discontinuity surface number；Pi (t) is the active power injected at t node i；
Δ t is steplength.
Wherein, in step (3), the operation constraint of described distribution network system self includes system load flow constraint, working voltage
Constraint, branch current constraint and energystorage system of accumulator run constraint, specific as follows:
(31) system load flow constraint
In formula: i=2,3 ..., N；Ω (i) is the set of the adjacent node of node i；U_{i}(t), U_{j}(t), θ_{ij}T () is respectively
T node i and the voltage magnitude of j and phase angle difference；G_{ii}, B_{ii}, G_{ij}, B_{ij}It is respectively the selfconductance in bus admittance matrix, from electricity
Receive, transconductance and mutual susceptance；P_{i} ^{PV}(t), P_{i} ^{ESS}(t), P_{i} ^{L}(t),It is respectively t node i
The active power of upper PV, accumulator, load injection and reactive power；
(32) working voltage constraint
U_{imin}≤U_{i}(t)≤U_{imax}Formula (9), i=1,2 ..., N,
In formula, U_{imin}And U_{imax}It is respectively the bound of node i voltage magnitude；
(33) branch current constraint
In formula, I_{ij}T () is that t flows through the current amplitude of branch road between node i and node j；U_{i}(t), U_{j}(t), θ_{ij}(t)
It is respectively t node i and the voltage magnitude of j and phase angle difference；G_{ii}, B_{ii}, G_{ij}, B_{ij}The electricity certainly being respectively in bus admittance matrix
Lead, from susceptance, transconductance and mutual susceptance；I_{ijmax}The current amplitude upper limit for branch road ij；
(34) energystorage system of accumulator runs constraint
In formula, k=1,2 ..., N_{ESS}, wherein N_{ESS}For energystorage system of accumulator number；WithWhen being respectively t
Carve active power and the reactive power of the output of kth inverter；WithBe respectively kth inverter rated capacity and
The active power upper limit；WithIt is respectively the chargedischarge electric power of accumulator；Δ t is simulation step length；During for t
Carve the stateofcharge of kth energystorage system of accumulator；It is respectively kth energystorage system of accumulator
Capacity and the upper lower limit value of stateofcharge.
Wherein, in step (4), by matlab software for calculation, PSO Algorithm energystorage system is utilized to participate in distribution
The Optimized model of network operation regulation.Each particle speed to particle the most as the following formula in described particle cluster algorithm
It is updated with position:
v_{t+1}=ω v_{t}+c_{1}rand()(P_{t}x_{t})+c_{2}rand()(G_{t}x_{t}) formula (11),
x_{t+1}=x_{i}+v_{t}Formula (12),
In formula, i is evolutionary generation；ω is inertia weight；c_{1}、c_{2}For accelerated factor；Rand () is random between [0,1]
Number.
Having the beneficial effect that of the technique scheme of the present invention: a kind of energystorage system that the present invention provides participates in actively joining
Operation of power networks regulating calculation method, compared to traditional method, can effectively reduce the active power loss of distribution network system, reduces electrical network fortune
Row cost, adds the utilization ratio of photovoltaic energy.
Accompanying drawing explanation
Fig. 1 is the calculation flow chart of the embodiment of the present invention one；
Fig. 2 is IEEE33 node power distribution web frame figure in embodiment one；
Fig. 3 is lightpreserved system structural representation in embodiment one；
Fig. 4 is photovoltaic and load day operation curve in embodiment one；
Fig. 5 is energystorage system of accumulator chargedischarge electric power curve in embodiment one；
Fig. 6 is energystorage system of accumulator reactive capability curve in embodiment one；
Fig. 7 is energystorage system of accumulator stateofcharge change curve in embodiment one.
Detailed description of the invention
For making the technical problem to be solved in the present invention, technical scheme and advantage clearer, below in conjunction with accompanying drawing and tool
Body embodiment is described in detail.
The present invention is as a example by energystorage system of accumulator, it is provided that a kind of energystorage system participates in active distribution network runing adjustment and calculates
Method, comprises the steps:
(1) consider the meritorious of energystorage system and idle characteristic, set up energystorage system of accumulator moving model；
(2) determine that energystorage system of accumulator participates in the object function of active distribution network runing adjustment and is: distribution network system
Active loss is minimum；
(3) the operation constraint of distribution network system self is taken into account during calculating, including system load flow constraint, working voltage about
The constraint of bundle, branch current and energystorage system of accumulator run constraint；
(4) PSO Algorithm energystorage system is utilized to participate in the Optimized model of power distribution network runing adjustment；
(5) output optimal solution: under meeting distribution network system reliability premise, the charge and discharge of energystorage system of accumulator day part
Electrical power is optimal solution.
Energystorage system participates in the calculation process of active distribution network runing adjustment computational methods as it is shown in figure 1, be embodied as
Journey is as follows:
Different from distributed power source, the operation of energystorage system has obvious temporal characteristics, and its running optimizatin no longer limits to
Discontinuity surface when single, but expand in longer time scale, define sequential running optimizatin problem, and then cause it certainly
The increasing and increase rapidly of plan dimension section number in time.Participate in actively to this end, the present invention is directed to energystorage system of accumulator
The Optimal Operation Model of power distribution network runing adjustment, it is proposed that a kind of energystorage system participates in active distribution network runing adjustment calculating side
Method.
Hereafter solving the power distribution network running optimizatin algorithm containing energystorage system with IEEE33 node example (structure such as Fig. 2)
Effectiveness and rapidity verify.8 groups of lightpreserved system, its system structure and basic configuration parameter such as figure is accessed in example
3 and table 1 shown in.Considering to carry out the energy storage optimization of one day, load day operation curve utilizes load forecasting method to obtain, takes 30min
One point, the processing mode of photovoltaic is identical.The photovoltaic of whole system is exerted oneself with load variations situation as shown in Figure 4.
Table 1 lightpreserved system configuration parameter
1, energystorage system of accumulator moving model is set up
Assuming that energystorage system of accumulator with to electrical network output as positive direction, consider its meritorious and idle characteristic,
Running boundary constraint is as follows:
In formula: k=1,2 ..., N_{ESS}, wherein N_{ESS}For energystorage system of accumulator number；WithWhen being respectively t
Carve active power and the reactive power of the output of kth inverter；WithBe respectively kth inverter rated capacity and
The active power upper limit；WithIt is respectively the chargedischarge electric power of energystorage system of accumulator.
On the other hand, the stateofcharge of energystorage system of accumulator has absolute seriality in sequential, it in strict accordance with
Time sequencing carries out accumulation according to chargedischarge electric power size and calculates, and the energy storage capacity of each time point should meet on stateofcharge
The requirement of lower limit,
In formula: k=1,2 ..., N_{ESS}；Δ t is simulation step length；Lotus for t kth energystorage system of accumulator
Electricity condition；It is respectively the capacity of kth energystorage system of accumulator and the upper and lower of stateofcharge
Limit value.
2, with the minimum object function of distribution network system active loss
The active loss of described distribution network system deducts load by the active power that whole distribution network system is injected and is disappeared
The active power sum that the active power of consumption, i.e. each node of distribution network system are injected, its mathematic(al) representation is:
In formula, N is system node number；N_{T}For time discontinuity surface number；Pi (t) is the active power injected at t node i；
Δ t is steplength.
3, the operation constraint of distribution network system self is considered, including system load flow constraint, working voltage constraint, branch current
Constraint and energystorage system of accumulator run constraint, specific as follows:
(31) system load flow constraint
In formula: i=2,3 ..., N；Ω (i) is the set of the adjacent node of node i；U_{i}(t), U_{j}(t), θ_{ij}T () is respectively
T node i and the voltage magnitude of j and phase angle difference；G_{ii}, B_{ii}, G_{ij}, B_{ij}It is respectively the selfconductance in bus admittance matrix, from electricity
Receive, transconductance and mutual susceptance；P_{i} ^{PV}(t), P_{i} ^{ESS}(t), P_{i} ^{L}(t),It is respectively t node i
The active power of upper PV, accumulator, load injection and reactive power；
(32) working voltage constraint
U_{imin}≤U_{i}(t)≤U_{imax}Formula (9), i=1,2 ..., N,
In formula, U_{imin}And U_{imax}It is respectively the bound of node i voltage magnitude；
(33) branch current constraint
In formula, I_{ij}T () is that t flows through the current amplitude of branch road between node i and node j；U_{i}(t), U_{j}(t), θ_{ij}(t)
It is respectively t node i and the voltage magnitude of j and phase angle difference；G_{ii}, B_{ii}, G_{ij}, B_{ij}The electricity certainly being respectively in bus admittance matrix
Lead, from susceptance, transconductance and mutual susceptance；I_{ijmax}The current amplitude upper limit for branch road ij；
(34) energystorage system of accumulator runs constraint
In formula, k=1,2 ..., N_{ESS}, wherein N_{ESS}For energystorage system of accumulator number；WithWhen being respectively t
Carve active power and the reactive power of the output of kth inverter；WithBe respectively kth inverter rated capacity and
The active power upper limit；WithIt is respectively the chargedischarge electric power of accumulator；Δ t is simulation step length；During for t
Carve the stateofcharge of kth energystorage system of accumulator；It is respectively kth energystorage system of accumulator
Capacity and the upper lower limit value of stateofcharge.
4, with formula (6) as object function, formula (1)formula (5), formula (7)(10) are constraints, utilize by formula (11) and formula
(12) modified particle swarm optiziation, by matlab software for calculation and substitute into concrete numerical value, utilizes PSO Algorithm energy storage
System participates in the Optimized model of power distribution network runing adjustment, and wherein, in described particle cluster algorithm, each particle is in an iterative process
Speed and position to particle are updated as the following formula:
v_{t+1}=ω v_{t}+c_{1}rand()(P_{t}x_{t})+c_{2}rand()(G_{t}x_{t}) formula (11),
x_{t+1}=x_{i}+v_{t}Formula (12),
In formula, i is evolutionary generation；ω is inertia weight；c_{1}、c_{2}For accelerated factor；Rand () is random between [0,1]
Number.
5, output optimal solution, is the chargedischarge electric power of energystorage system day part under meeting system reliability premise.
In the present embodiment, according to the photovoltaic shown in Fig. 4 and load day operation curve, abovementioned energystorage system is utilized to participate in main
Distribution network system is optimized by dynamic power distribution network runing adjustment computational methods, and result is as shown in Fig. 5～Fig. 7.
In MATLAB, use PSO Algorithm Optimized model, participate in power distribution network at energystorage system of accumulator and optimize it
Before, system loss is 1316.05kW h.Energystorage system of accumulator is exerted oneself situation and load by planning as a whole day part photovoltaic
Need for electricity, realizes peak load shifting, and provides certain reactive power support, may finally system loss be reduced to
390.64kW·h。
The above is the preferred embodiment of the present invention, it is noted that for those skilled in the art
For, on the premise of without departing from principle of the present invention, it is also possible to make some improvements and modifications, these improvements and modifications are also
Should be regarded as protection scope of the present invention.
Claims (6)
1. an energystorage system participates in active distribution network runing adjustment computational methods, it is characterised in that comprise the steps:
(1) consider the meritorious of energystorage system and idle characteristic, set up energystorage system moving model；
(2) determine that energystorage system participates in the object function of active distribution network runing adjustment and is: the active loss of distribution network system is
Little；
(3) calculate during take into account distribution network system self operation constraint, including system load flow constraint, working voltage constraint,
Branch current constraint and energystorage system run constraint；
(4) PSO Algorithm energystorage system is utilized to participate in the Optimized model of power distribution network runing adjustment；
(5) output optimal solution: under meeting distribution network system reliability premise, the chargedischarge electric power of energystorage system day part is
Optimal solution.
Energystorage system the most according to claim 1 participates in active distribution network runing adjustment computational methods, it is characterised in that step
Suddenly in (1), when setting up energystorage system moving model, it is assumed that energystorage system is positive direction to power distribution network output, considers
Its meritorious and idle characteristic, running boundary constraint is as follows:
In formula: k=1,2 ..., N_{ESS}, wherein N_{ESS}For energystorage system number；WithIt is respectively the t kth change of current
The active power of device output and reactive power；WithIt is respectively in rated capacity and the active power of kth inverter
Limit；WithIt is respectively the chargedischarge electric power of energystorage system；
The stateofcharge of described energystorage system has absolute seriality in sequential, its in strict accordance with time sequencing according to charge and discharge
Electrical power size carries out accumulation and calculates, and computing formula is as follows:
In formula: k=1,2 ..., N_{ESS}；Δ t is simulation step length；Stateofcharge for t kth energystorage system；
The energy storage capacity of each time point of described energystorage system is between the bound of stateofcharge, and expression formula is as follows:
In formula,It is respectively capacity and the upper lower limit value of stateofcharge of kth energystorage system.
Energystorage system the most according to claim 1 participates in active distribution network runing adjustment computational methods, it is characterised in that step
Suddenly, in (2), the active loss of described distribution network system deducts load by the active power that whole distribution network system is injected and is disappeared
The active power sum that the active power of consumption, i.e. each node of distribution network system are injected, its mathematic(al) representation is:
In formula, N is system node number；N_{T}For time discontinuity surface number；Pi (t) is the active power injected at t node i；Δ t is
Steplength.
Energystorage system the most according to claim 1 participates in active distribution network runing adjustment computational methods, it is characterised in that step
Suddenly, in (3), the operation constraint of described distribution network system self includes system load flow constraint, working voltage constraint, branch current about
Bundle and energystorage system run constraint, specific as follows:
(31) system load flow constraint
Formula (7),
Formula (8),
In formula: i=2,3 ..., N；Ω (i) is the set of the adjacent node of node i；U_{i}(t), U_{j}(t), θ_{ij}T () is respectively t
Node i and the voltage magnitude of j and phase angle difference；G_{ii}, B_{ii}, G_{ij}, B_{ij}Be respectively the selfconductance in bus admittance matrix, from susceptance, mutually
Conductance and mutual susceptance；It is respectively t node i glazing
The active power of overhead utility, accumulator, load injection and reactive power；
(32) working voltage constraint
U_{imin}≤U_{i}(t)≤U_{imax}Formula (9), i=1,2 ..., N,
In formula, U_{imin}And U_{imax}It is respectively the bound of node i voltage magnitude；
(33) branch current constraint
In formula, I_{ij}T () is that t flows through the current amplitude of branch road between node i and node j；U_{i}(t), U_{j}(t), θ_{ij}(t) difference
For t node i and the voltage magnitude of j and phase angle difference；G_{ii}, B_{ii}, G_{ij}, B_{ij}Be respectively the selfconductance in bus admittance matrix, from
Susceptance, transconductance and mutual susceptance；I_{ijmax}The current amplitude upper limit for branch road ij；
(34) energystorage system runs constraint
In formula, k=1,2 ..., N_{ESS}, wherein N_{ESS}For energystorage system number；WithIt is respectively the t kth change of current
The active power of device output and reactive power；WithIt is respectively in rated capacity and the active power of kth inverter
Limit；WithIt is respectively the chargedischarge electric power of accumulator；Δ t is simulation step length；For t kth energy storage
The stateofcharge of system；It is respectively the capacity of kth energystorage system and the upper of stateofcharge
Lower limit.
Energystorage system the most according to claim 1 participates in active distribution network runing adjustment computational methods, it is characterised in that step
Suddenly in the particle cluster algorithm described in (4), each particle speed and position to particle the most as the following formula is carried out more
New:
v_{t+1}=ω v_{t}+c_{1}rand()(P_{t}x_{t})+c_{2}rand()(G_{t}x_{t}) formula (11),
x_{t+1}=x_{i}+v_{t}Formula (12),
In formula, i is evolutionary generation；ω is inertia weight；c_{1}、c_{2}For accelerated factor；Rand () is the random number between [0,1].
Energystorage system the most according to claim 1 participates in active distribution network runing adjustment computational methods, it is characterised in that step
Suddenly in (4), by matlab software for calculation, PSO Algorithm energystorage system is utilized to participate in the optimization of power distribution network runing adjustment
Model.
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CN107104433A (en) *  20170515  20170829  国网江苏省电力公司电力科学研究院  A kind of lightpreserved system participates in the acquisition methods of power distribution network Optimal Operation Strategies 
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CN107403239A (en) *  20170725  20171128  南京工程学院  A kind of parameters analysis method for being used for control device in power system 
CN107947231A (en) *  20171201  20180420  国网江苏省电力有限公司电力科学研究院  A kind of mixed energy storage system control method towards power distribution network optimization operation 
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CN106998072A (en) *  20170515  20170801  国网江苏省电力公司电力科学研究院  A kind of mixed energy storage system capacity configuration optimizing method for optimizing operation towards power distribution network 
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