CN106099964B - A kind of energy-storage system participation active distribution network runing adjustment computational methods - Google Patents

A kind of energy-storage system participation active distribution network runing adjustment computational methods Download PDF

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CN106099964B
CN106099964B CN201610430803.XA CN201610430803A CN106099964B CN 106099964 B CN106099964 B CN 106099964B CN 201610430803 A CN201610430803 A CN 201610430803A CN 106099964 B CN106099964 B CN 106099964B
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energy
storage
distribution network
active
power
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CN106099964A (en
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杨志超
陆文伟
葛乐
马寿虎
陆文涛
顾佳易
王蒙
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南京工程学院
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    • HELECTRICITY
    • H02GENERATION; CONVERSION OR DISTRIBUTION OF ELECTRIC POWER
    • H02JCIRCUIT ARRANGEMENTS OR SYSTEMS FOR SUPPLYING OR DISTRIBUTING ELECTRIC POWER; SYSTEMS FOR STORING ELECTRIC ENERGY
    • H02J3/00Circuit arrangements for ac mains or ac distribution networks
    • H02J3/28Arrangements for balancing of the load in a network by storage of energy
    • H02J3/32Arrangements for balancing of the load in a network by storage of energy using batteries with converting means
    • HELECTRICITY
    • H02GENERATION; CONVERSION OR DISTRIBUTION OF ELECTRIC POWER
    • H02JCIRCUIT ARRANGEMENTS OR SYSTEMS FOR SUPPLYING OR DISTRIBUTING ELECTRIC POWER; SYSTEMS FOR STORING ELECTRIC ENERGY
    • H02J2203/00Indexing scheme relating to details of circuit arrangements for AC mains or AC distribution networks
    • H02J2203/20Simulating, e g planning, reliability check, modelling or computer assisted design [CAD]
    • YGENERAL TAGGING OF NEW TECHNOLOGICAL DEVELOPMENTS; GENERAL TAGGING OF CROSS-SECTIONAL TECHNOLOGIES SPANNING OVER SEVERAL SECTIONS OF THE IPC; TECHNICAL SUBJECTS COVERED BY FORMER USPC CROSS-REFERENCE ART COLLECTIONS [XRACs] AND DIGESTS
    • Y02TECHNOLOGIES OR APPLICATIONS FOR MITIGATION OR ADAPTATION AGAINST CLIMATE CHANGE
    • Y02EREDUCTION OF GREENHOUSE GAS [GHG] EMISSIONS, RELATED TO ENERGY GENERATION, TRANSMISSION OR DISTRIBUTION
    • Y02E10/00Energy generation through renewable energy sources
    • Y02E10/50Photovoltaic [PV] energy
    • Y02E10/56Power conversion systems, e.g. maximum power point trackers
    • YGENERAL TAGGING OF NEW TECHNOLOGICAL DEVELOPMENTS; GENERAL TAGGING OF CROSS-SECTIONAL TECHNOLOGIES SPANNING OVER SEVERAL SECTIONS OF THE IPC; TECHNICAL SUBJECTS COVERED BY FORMER USPC CROSS-REFERENCE ART COLLECTIONS [XRACs] AND DIGESTS
    • Y02TECHNOLOGIES OR APPLICATIONS FOR MITIGATION OR ADAPTATION AGAINST CLIMATE CHANGE
    • Y02EREDUCTION OF GREENHOUSE GAS [GHG] EMISSIONS, RELATED TO ENERGY GENERATION, TRANSMISSION OR DISTRIBUTION
    • Y02E70/00Other energy conversion or management systems reducing GHG emissions
    • Y02E70/30Systems combining energy storage with energy generation of non-fossil origin

Abstract

The present invention provides a kind of energy-storage system participation active distribution network runing adjustment computational methods, for the energy-storage system of accumulator composition, with the minimum object function of distribution network system active loss, the operation of consideration system itself constrains, including system load flow constraint, working voltage constraint, branch current constraint and energy-storage system operation constraint, example is solved using particle cluster algorithm, the charge-discharge electric power of final output energy-storage system day part under the premise of meeting system reliability is as optimal solution.The present invention can effectively reduce the active power loss of distribution network system compared to conventional method, reduce operation of power networks cost, increase the utilization ratio of photovoltaic energy.

Description

A kind of energy-storage system participation active distribution network runing adjustment computational methods
Technical field
The present invention relates to a kind of energy-storage systems to participate in active distribution network runing adjustment technology, and in particular to a kind of accumulator storage It can system participation active distribution network runing adjustment computational methods.
Background technology
It is the distributed generation technology of core in world's model using renewable energy utilization by the dual-pressure of energy and environment Interior extensive rise is enclosed, the application and development of energy storage technology in the power system are greatly promoted.On the one hand, by means of energy storage system System can efficiently reduce distributed generation resource and contribute to be influenced caused by intermittent and randomness, is formed using micro-capacitance sensor as core Self-government system;On the other hand, the energy-storage system of large capacity also provides new means and side 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 The effective adjusting and optimization for participating in system load flow, can greatly improve the economy and reliability of distribution system operation.
How energy-storage system is made full use of, realizes the emphasis paid close attention at present when the high efficient and reliable of distribution system is run, it is domestic Outer correlation it is studied, and achieve the achievement in terms of some theory and practice, such as analyze accumulator position Set distribution and the influence of amount of capacity, and to positive effect that peak regulation is played;It has studied and contains distributed generation resource and accumulator Power distribution network/micro-capacitance sensor running optimizatin problem, give storage battery active power and reactive power be carried out at the same time the mathematical model of optimization; And schedulable characteristic and quantity of electric charge information according to accumulator, it is proposed that one kind being based on constant current-constant voltage control strategy Accumulator cell charging and discharging mathematical model.
Different from distributed generation resource, there are apparent temporal characteristics, running optimizatin no longer to limit to for the operation of energy-storage system The discontinuity surface when single, but expand in longer time scale, there are problems that sequential running optimizatin, and then it is caused to determine Discontinuity surface number increases and increases rapidly plan dimension at any time.
Invention content
The goal of the invention of the present invention is to solve the above problems, participating in active distribution network operation for energy-storage system of accumulator The Optimal Operation Model of adjusting provides a kind of energy-storage system participation active distribution network runing adjustment computational methods.
In order to solve the above technical problems, the embodiment of the present invention provides a kind of energy-storage system participation active distribution network operation tune Computational methods are saved, are included the following steps:
(1) the active and idle characteristic for considering energy-storage system, establishes energy-storage system moving model;
(2) determine that the object function that energy-storage system participates in active distribution network runing adjustment is:The active damage of distribution network system Consumption is minimum;
(3) the operation constraint of distribution network system itself is taken into account in calculating process, including system load flow constraint, working voltage are about Beam, branch current constraint and energy-storage system operation constraint;
(4) PSO Algorithm energy-storage system is utilized to participate in the Optimized model of power distribution network runing adjustment;
(5) optimal solution is exported:Under the premise of meeting distribution network system reliability, the charge-discharge electric power of energy-storage system day part As optimal solution.
By taking typical energy-storage system of accumulator as an example, it is mainly made of accumulator and transverter, and transverter is mainly responsible for Monitoring operation of power networks situation sends out the work such as control signal.The electric interfaces that transverter is connected as accumulator with power grid are to store Battery energy storage system carries out the hinge of energy exchange with power distribution network, can realize the charge and discharge control of active power, also, the change of current Utensil has certain idle miscellaneous function, can be power distribution network by idle control while executing charging and discharging function Voltage support is provided.
Wherein, when establishing energy-storage system of accumulator moving model in step (1), it is assumed that energy-storage system of accumulator is with to distribution Net output power is positive direction, considers its active and idle characteristic, and running boundary constraint is as follows:
In formula:K=1,2 ..., NESS, wherein NESSFor energy-storage system of accumulator number;WithWhen respectively t Carve the active power and reactive power of the output of k-th of transverter;WithThe rated capacity of respectively k-th transverter and The active power upper limit;WithThe respectively charge-discharge electric power of energy-storage system of accumulator.
Step (1), it is assumed that energy-storage system of accumulator using to power distribution network output power as positive direction, then energy-storage system of accumulator Input power is negative direction, naturally it is also possible to it is assumed that energy-storage system of accumulator to power distribution network output power as negative direction, then to store Battery energy storage system input power is positive direction, is suitable for this optimizing regulation computational methods.
The state-of-charge of the energy-storage system of accumulator has absolute continuity in sequential, suitable in strict accordance with the time Sequence carries out accumulation calculating according to charge-discharge electric power size, and calculation formula is as follows:
In formula:K=1,2 ..., NESS;Δ t is simulation step length;For the lotus of k-th of energy-storage system of accumulator of t moment Electricity condition;
The energy storage capacity of the energy-storage system of accumulator each time point should meet the requirement of state-of-charge bound, expression formula It is as follows:
In formula,The capacity and state-of-charge of respectively k-th energy-storage system of accumulator Upper lower limit value.
Power distribution network running optimizatin problem containing energy-storage system is usually contributed with cost of electricity-generating, the whole network active loss, substation Minimum, new energy receives ability maximum and the combination etc. of plurality of target function is optimization aim, and the distribution network system has The active power that work(loss is injected by entire distribution network system subtracts the active power that load is consumed, i.e. distribution network system is each The sum of the active power of a node injection, with the minimum object function of distribution network system active loss in above-mentioned step (2), Mathematic(al) representation is:
In formula, N is system node number;NTFor when discontinuity surface number;Pi (t) is the active power injected at t moment node i; Δ t is step-length.
Wherein, in step (3), the operation constraint of the distribution network system itself includes system load flow constraint, working voltage Constraint, branch current constraint and energy-storage system of accumulator operation constraint, it is specific as follows:
(3-1) system load flow constrains
In formula:I=2,3 ..., N;Ω (i) is the set of the adjacent node of node i;Ui(t), Uj(t), θij(t) it is respectively The voltage magnitude and phase angle difference of t moment node i and j;Gii, Bii, Gij, BijSelf-conductance respectively in node admittance matrix, from electricity It receives, transconductance and mutual susceptance;Pi PV(t), Pi ESS(t), Pi L(t),Respectively t moment node i The active power and reactive power that upper PV, accumulator, load inject;
(3-2) working voltage constrains
Uimin≤Ui(t)≤UimaxFormula (9), i=1,2 ..., N,
In formula, UiminAnd UimaxThe respectively bound of node i voltage magnitude;
(3-3) branch current constrains
In formula, Iij(t) current amplitude of branch between node i and node j is flowed through for t moment;Ui(t), Uj(t), θij(t) The respectively voltage magnitude and phase angle difference of t moment node i and j;Gii, Bii, Gij, BijElectricity certainly respectively in node admittance matrix It leads, from susceptance, transconductance and mutual susceptance;IijmaxFor the current amplitude upper limit of branch ij;
The operation constraint of (3-4) energy-storage system of accumulator
In formula, k=1,2 ..., NESS, wherein NESSFor energy-storage system of accumulator number;WithWhen respectively t Carve the active power and reactive power of the output of k-th of transverter;WithThe rated capacity of respectively k-th transverter and The active power upper limit;WithThe respectively charge-discharge electric power of accumulator;Δ t is simulation step length;For t when Carve the state-of-charge of k-th of energy-storage system of accumulator;Respectively k-th of energy-storage system of accumulator Capacity and state-of-charge upper lower limit value.
Wherein, in step (4), by matlab software for calculation, distribution is participated in using PSO Algorithm energy-storage system The Optimized model that network operation is adjusted.Each particle is in an iterative process as the following formula to the speed of particle in the particle cluster algorithm It is updated with position:
vt+1=ω vt+c1rand()(Pt-xt)+c2rand()(Gt-xt) formula (11),
xt+1=xi+vtFormula (12),
In formula, i is evolutionary generation;ω is inertia weight;c1、c2For accelerated factor;Rand () is random between [0,1] Number.
The above-mentioned technical proposal of the present invention has the beneficial effect that:A kind of energy-storage system provided by the invention participates in actively matching Operation of power networks regulating calculation method can effectively reduce the active power loss of distribution network system compared to conventional method, reduce power grid fortune Row cost increases the utilization ratio of photovoltaic energy.
Description of the drawings
Fig. 1 is the calculation flow chart of the embodiment of the present invention one;
Fig. 2 is IEEE33 node power distribution web frame figures in embodiment one;
Fig. 3 is light-preserved system structural schematic diagram in embodiment one;
Fig. 4 is photovoltaic and load day operation curve in embodiment one;
Fig. 5 is energy-storage system of accumulator charge-discharge electric power curve in embodiment one;
Fig. 6 is energy-storage system of accumulator reactive capability curve in embodiment one;
Fig. 7 is energy-storage system of accumulator state-of-charge change curve in embodiment one.
Specific implementation mode
To keep the technical problem to be solved in the present invention, technical solution and advantage clearer, below in conjunction with attached drawing and tool Body embodiment is described in detail.
The present invention provides a kind of energy-storage system participation active distribution network runing adjustment calculating by taking energy-storage system of accumulator as an example Method includes the following steps:
(1) the active and idle characteristic for considering energy-storage system, establishes energy-storage system of accumulator moving model;
(2) determine that the object function that energy-storage system of accumulator participates in active distribution network runing adjustment is:Distribution network system Active loss is minimum;
(3) the operation constraint of distribution network system itself is taken into account in calculating process, including system load flow constraint, working voltage are about Beam, branch current constraint and energy-storage system of accumulator operation constraint;
(4) PSO Algorithm energy-storage system is utilized to participate in the Optimized model of power distribution network runing adjustment;
(5) optimal solution is exported:Under the premise of meeting distribution network system reliability, the charge and discharge of energy-storage system of accumulator day part Electrical power is optimal solution.
Energy-storage system participates in the calculation process of active distribution network runing adjustment computational methods as shown in Figure 1, being embodied Journey is as follows:
Different from distributed generation resource, there are apparent temporal characteristics, running optimizatin no longer to limit to for the operation of energy-storage system The discontinuity surface when single, but expand in longer time scale, sequential running optimizatin problem is formd, and then it is caused to determine Discontinuity surface number increases and increases rapidly plan dimension at any time.For this purpose, the present invention participates in actively for energy-storage system of accumulator A kind of Optimal Operation Model of power distribution network runing adjustment, it is proposed that energy-storage system participation active distribution network runing adjustment calculating side Method.
Hereafter with the solution of IEEE33 nodes example (structure such as Fig. 2) to the power distribution network running optimizatin algorithm containing energy-storage system Validity and rapidity verified.8 groups of light-preserved systems, system structure and basic configuration parameter are accessed in example as schemed 3 and table 1 shown in.Consider that the energy storage for carrying out one day optimizes, load day operation curve is obtained using load forecasting method, takes 30min One point, the processing mode of photovoltaic are identical.The photovoltaic of whole system is contributed and load variations situation is as shown in Figure 4.
1 light-preserved system of table configures parameter
1, energy-storage system of accumulator moving model is established
It is assumed that energy-storage system of accumulator to be, as positive direction, to consider its active and idle characteristic to power grid output power, Running boundary constraint is as follows:
In formula:K=1,2 ..., NESS, wherein NESSFor energy-storage system of accumulator number;WithWhen respectively t Carve the active power and reactive power of the output of k-th of transverter;WithThe rated capacity of respectively k-th transverter and The active power upper limit;WithThe respectively charge-discharge electric power of energy-storage system of accumulator.
On the other hand, the state-of-charge of energy-storage system of accumulator in sequential have absolute continuity, it in strict accordance with Time sequencing carries out accumulation calculating according to charge-discharge electric power size, and the energy storage capacity of each time point should meet on state-of-charge The requirement of lower limit,
In formula:K=1,2 ..., NESS;Δ t is simulation step length;For the lotus of k-th of energy-storage system of accumulator of t moment Electricity condition;The capacity of respectively k-th energy-storage system of accumulator and state-of-charge up and down Limit value.
2, with the minimum object function of distribution network system active loss
The active power that the active loss of the distribution network system is injected by entire distribution network system subtracts load and is disappeared The sum of the active power of each node injection of the active power of consumption, i.e. distribution network system, mathematic(al) representation is:
In formula, N is system node number;NTFor when discontinuity surface number;Pi (t) is the active power injected at t moment node i; Δ t is step-length.
3, consider the operation constraint of distribution network system itself, including system load flow constraint, working voltage constraint, branch current Constraint and energy-storage system of accumulator operation constraint, it is specific as follows:
(3-1) system load flow constrains
In formula:I=2,3 ..., N;Ω (i) is the set of the adjacent node of node i;Ui(t), Uj(t), θij(t) it is respectively The voltage magnitude and phase angle difference of t moment node i and j;Gii, Bii, Gij, BijSelf-conductance respectively in node admittance matrix, from electricity It receives, transconductance and mutual susceptance;Pi PV(t), Pi ESS(t), Pi L(t),Respectively t moment node i The active power and reactive power that upper PV, accumulator, load inject;
(3-2) working voltage constrains
Uimin≤Ui(t)≤UimaxFormula (9), i=1,2 ..., N,
In formula, UiminAnd UimaxThe respectively bound of node i voltage magnitude;
(3-3) branch current constrains
In formula, Iij(t) current amplitude of branch between node i and node j is flowed through for t moment;Ui(t), Uj(t), θij(t) The respectively voltage magnitude and phase angle difference of t moment node i and j;Gii, Bii, Gij, BijElectricity certainly respectively in node admittance matrix It leads, from susceptance, transconductance and mutual susceptance;IijmaxFor the current amplitude upper limit of branch ij;
The operation constraint of (3-4) energy-storage system of accumulator
In formula, k=1,2 ..., NESS, wherein NESSFor energy-storage system of accumulator number;WithWhen respectively t Carve the active power and reactive power of the output of k-th of transverter;WithThe rated capacity of respectively k-th transverter and The active power upper limit;WithThe respectively charge-discharge electric power of accumulator;Δ t is simulation step length;For t when Carve the state-of-charge of k-th of energy-storage system of accumulator;Respectively k-th of energy-storage system of accumulator Capacity and state-of-charge upper lower limit value.
4, with formula (6) for object function, formula (1)-formula (5), formula (7)-(10) are constraints, using by formula (11) and formula (12) modified particle swarm optiziation by matlab software for calculation and substitutes into concrete numerical value, utilizes PSO Algorithm energy storage System participates in the Optimized model of power distribution network runing adjustment, wherein each particle is in an iterative process in the particle cluster algorithm The speed of particle and position are updated as the following formula:
vt+1=ω vt+c1rand()(Pt-xt)+c2rand()(Gt-xt) formula (11),
xt+1=xi+vtFormula (12),
In formula, i is evolutionary generation;ω is inertia weight;c1、c2For accelerated factor;Rand () is random between [0,1] Number.
5, export optimal solution, as under the premise of meeting system reliability energy-storage system day part charge-discharge electric power.
In the present embodiment, photovoltaic according to Fig.4, and load day operation curve participate in master using above-mentioned energy-storage system Dynamic power distribution network runing adjustment computational methods optimize distribution network system, as a result as shown in Fig. 5~Fig. 7.
PSO Algorithm Optimized model is used in MATLAB, participating in power distribution network in energy-storage system of accumulator optimizes it Before, system loss 1316.05kWh.Energy-storage system of accumulator is by planning as a whole day part photovoltaic output situation and load Power demand to realize peak load shifting, and provides certain reactive power support, may finally be reduced to system loss 390.64kW·h。
The above is the preferred embodiment of the present invention, it is noted that for those skilled in the art For, without departing from the principles of the present invention, it can also make several improvements and retouch, these improvements and modifications It should be regarded as protection scope of the present invention.

Claims (5)

1. a kind of energy-storage system participates in active distribution network runing adjustment computational methods, which is characterized in that include the following steps:
(1) the active and idle characteristic for considering energy-storage system, establishes energy-storage system moving model;
(2) determine that the object function that energy-storage system participates in active distribution network runing adjustment is:The active loss of distribution network system is most It is small;
(3) the operation constraint of distribution network system itself is taken into account in calculating process, including system load flow constrains, working voltage constrains, Branch current constrains and energy-storage system operation constraint, specific as follows:
(3-1) system load flow constrains
In formula:I=2,3 ..., N;Ω (i) is the set of the adjacent node of node i;Ui(t), Uj(t), θij(t) it is respectively t moment The voltage magnitude and phase angle difference of node i and j;Gii, Bii, Gij, BijSelf-conductance respectively in node admittance matrix, from susceptance, mutually Conductance and mutual susceptance;Pi PV(t), Pi ESS(t), Pi L(t),Respectively photovoltaic in t moment node i The active power and reactive power that power station, accumulator, load inject;
(3-2) working voltage constrains
Uimin≤Ui(t)≤UimaxFormula (9), i=1,2 ..., N,
In formula, UiminAnd UimaxThe respectively bound of node i voltage magnitude;
(3-3) branch current constrains
In formula, Iij(t) current amplitude of branch between node i and node j is flowed through for t moment;Ui(t), Uj(t), θij(t) respectively For the voltage magnitude and phase angle difference of t moment node i and j;Gii, Bii, Gij, BijSelf-conductance respectively in node admittance matrix, from Susceptance, transconductance and mutual susceptance;IijmaxFor the current amplitude upper limit of branch ij;
The operation constraint of (3-4) energy-storage system
In formula, k=1,2 ..., NESS, wherein NESSFor energy-storage system number;WithRespectively k-th of change of current of t moment The active power and reactive power of device output;WithIn the rated capacity and active power of respectively k-th transverter Limit;WithThe respectively charge-discharge electric power of accumulator;Δ t is simulation step length;For k-th of energy storage of t moment The state-of-charge of system;The capacity of respectively k-th energy-storage system and state-of-charge it is upper Lower limiting value;
(4) PSO Algorithm energy-storage system is utilized to participate in the Optimized model of power distribution network runing adjustment;
(5) optimal solution is exported:Under the premise of meeting distribution network system reliability, the charge-discharge electric power of energy-storage system day part is Optimal solution.
2. energy-storage system according to claim 1 participates in active distribution network runing adjustment computational methods, which is characterized in that step Suddenly in (1), when establishing energy-storage system moving model, it is assumed that energy-storage system is positive direction to power distribution network output power, is considered Characteristic that its is active and idle, running boundary constraint are as follows:
In formula:K=1,2 ..., NESS, wherein NESSFor energy-storage system number;WithRespectively k-th of change of current of t moment The active power and reactive power of device output;WithIn the rated capacity and active power of respectively k-th transverter Limit;WithThe respectively charge-discharge electric power of energy-storage system;
The state-of-charge of the energy-storage system has absolute continuity in sequential, in strict accordance with time sequencing according to charge and discharge Electrical power size carries out accumulation calculating, and calculation formula is as follows:
In formula:K=1,2 ..., NESS;Δ t is simulation step length;For the state-of-charge of k-th of energy-storage system of t moment;
For the energy storage capacity of the energy-storage system each time point between the bound of state-of-charge, expression formula is as follows:
In formula,The capacity of respectively k-th energy-storage system and the upper lower limit value of state-of-charge.
3. energy-storage system according to claim 1 participates in active distribution network runing adjustment computational methods, which is characterized in that step Suddenly in (2), active power that the active loss of the distribution network system is injected by entire distribution network system subtracts load and is disappeared The sum of the active power of each node injection of the active power of consumption, i.e. distribution network system, mathematic(al) representation is:
In formula, N is system node number;NTFor when discontinuity surface number;Pi (t) is the active power injected at t moment node i;Δ t is Step-length.
4. energy-storage system according to claim 1 participates in active distribution network runing adjustment computational methods, which is characterized in that step Suddenly each particle in an iterative process as the following formula carries out more the speed of particle and position in the particle cluster algorithm described in (4) Newly:
vt+1=ω vt+c1rand()(Pt-xt)+c2rand()(Gt-xt) formula (11),
xt+1=xi+vtFormula (12),
In formula, i is evolutionary generation;ω is inertia weight;c1、c2For accelerated factor;Random numbers of the rand () between [0,1].
5. energy-storage system according to claim 1 participates in active distribution network runing adjustment computational methods, which is characterized in that step Suddenly in (4), by matlab software for calculation, the optimization of power distribution network runing adjustment is participated in using PSO Algorithm energy-storage system Model.
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Citations (2)

* Cited by examiner, † Cited by third party
Publication number Priority date Publication date Assignee Title
CN103956758A (en) * 2014-05-20 2014-07-30 电子科技大学 Energy storage SOC optimization control method in wind storage system
CN104779630A (en) * 2015-05-08 2015-07-15 武汉大学 Capacity allocation method for hybrid energy storage system capable of restraining wind power output power fluctuation

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US20160043548A1 (en) * 2013-08-15 2016-02-11 Nec Laboratories America, Inc. Rolling stochastic optimization based operation of distributed energy systems with energy storage systems and renewable energy resources

Patent Citations (2)

* Cited by examiner, † Cited by third party
Publication number Priority date Publication date Assignee Title
CN103956758A (en) * 2014-05-20 2014-07-30 电子科技大学 Energy storage SOC optimization control method in wind storage system
CN104779630A (en) * 2015-05-08 2015-07-15 武汉大学 Capacity allocation method for hybrid energy storage system capable of restraining wind power output power fluctuation

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