CN106099964A - A kind of energy-storage system participates in active distribution network runing adjustment computational methods - Google Patents

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

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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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energy
storage
distribution network
formula
constraint
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CN106099964B (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 to participate in active distribution network runing adjustment computational methods, energy-storage 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 energy-storage system, use particle cluster algorithm that example is solved, finally export under meeting system reliability premise the charge-discharge electric power of energy-storage 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

A kind of energy-storage system participates in active distribution network runing adjustment computational methods
Technical field
The present invention relates to a kind of energy-storage 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 dual-pressure 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 micro-capacitance sensor as core Self-government system;On the other hand, jumbo energy-storage 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 energy-storage 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/micro-capacitance 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 energy-storage 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 energy-storage system of accumulator and runs The Optimal Operation Model of regulation, it is provided that a kind of energy-storage system participates in active distribution network runing adjustment computational methods.
For solving above-mentioned technical problem, embodiments of the invention provide a kind of energy-storage system to participate in active distribution network operation and adjust Joint computational methods, comprise the steps:
(1) consider the meritorious of energy-storage system and idle characteristic, set up energy-storage system moving model;
(2) determine that energy-storage 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 energy-storage system run constraint;
(4) PSO Algorithm energy-storage 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-discharge electric power of energy-storage system day part It is optimal solution.
As a example by typical energy-storage 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 energy-storage system of accumulator moving model, it is assumed that energy-storage 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 ..., NESS, wherein NESSFor energy-storage 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 charge-discharge electric power of energy-storage system of accumulator.
Step (1), it is assumed that energy-storage system of accumulator with to power distribution network output as positive direction, then energy-storage system of accumulator Input power is negative direction, naturally it is also possible to assuming that energy-storage 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 state-of-charge of described energy-storage system of accumulator has absolute seriality in sequential, and it is suitable in strict accordance with the time Sequence carries out accumulation according to charge-discharge electric power size and calculates, and computing formula is as follows:
In formula: k=1,2 ..., NESS;Δ t is simulation step length;Lotus for t kth energy-storage system of accumulator Electricity condition;
The energy storage capacity of each time point of described energy-storage system of accumulator should meet the requirement of state-of-charge bound, expression formula As follows:
In formula,It is respectively capacity and the state-of-charge of kth energy-storage system of accumulator Upper lower limit value.
Power distribution network running optimizatin problem containing energy-storage system is generally exerted oneself with cost of electricity-generating, 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 above-mentioned step (2), its Mathematic(al) representation is:
In formula, N is system node number;NTFor time discontinuity surface number;Pi (t) is the active power injected at t node i; Δ t is step-length.
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 energy-storage system of accumulator run constraint, specific as follows:
(3-1) system load flow constraint
In formula: i=2,3 ..., N;Ω (i) is the set of the adjacent node of node i;Ui(t), Uj(t), θijT () is respectively T node i and the voltage magnitude of j and phase angle difference;Gii, Bii, Gij, BijIt is respectively the self-conductance in bus admittance matrix, from electricity Receive, transconductance and mutual susceptance;Pi PV(t), Pi ESS(t), Pi L(t),It is respectively t node i The active power of upper PV, accumulator, load injection and reactive power;
(3-2) working voltage constraint
Uimin≤Ui(t)≤UimaxFormula (9), i=1,2 ..., N,
In formula, UiminAnd UimaxIt is respectively the bound of node i voltage magnitude;
(3-3) branch current constraint
In formula, IijT () is that t flows through the current amplitude of branch road between node i and node j;Ui(t), Uj(t), θij(t) It is respectively t node i and the voltage magnitude of j and phase angle difference;Gii, Bii, Gij, BijThe electricity certainly being respectively in bus admittance matrix Lead, from susceptance, transconductance and mutual susceptance;IijmaxThe current amplitude upper limit for branch road ij;
(3-4) energy-storage system of accumulator runs constraint
In formula, k=1,2 ..., NESS, wherein NESSFor energy-storage 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 charge-discharge electric power of accumulator;Δ t is simulation step length;During for t Carve the state-of-charge of kth energy-storage system of accumulator;It is respectively kth energy-storage system of accumulator Capacity and the upper lower limit value of state-of-charge.
Wherein, in step (4), by matlab software for calculation, PSO Algorithm energy-storage 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:
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.
Having the beneficial effect that of the technique scheme of the present invention: a kind of energy-storage 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 light-preserved system structural representation 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.
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 energy-storage system of accumulator, it is provided that a kind of energy-storage system participates in active distribution network runing adjustment and calculates Method, comprises the steps:
(1) consider the meritorious of energy-storage system and idle characteristic, set up energy-storage system of accumulator moving model;
(2) determine that energy-storage 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 energy-storage system of accumulator run constraint;
(4) PSO Algorithm energy-storage 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 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 it is shown in figure 1, be embodied as Journey is as follows:
Different from distributed power source, the operation of energy-storage 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 energy-storage system of accumulator The Optimal Operation Model of power distribution network runing adjustment, it is proposed that a kind of energy-storage system participates in active distribution network runing adjustment calculating side Method.
Hereafter solving the power distribution network running optimizatin algorithm containing energy-storage system with IEEE33 node example (structure such as Fig. 2) Effectiveness and rapidity verify.8 groups of light-preserved 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 light-preserved system configuration parameter
1, energy-storage system of accumulator moving model is set up
Assuming that energy-storage 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 ..., NESS, wherein NESSFor energy-storage 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 charge-discharge electric power of energy-storage system of accumulator.
On the other hand, the state-of-charge of energy-storage system of accumulator has absolute seriality in sequential, it in strict accordance with Time sequencing carries out accumulation according to charge-discharge electric power size and calculates, 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;Lotus for t kth energy-storage system of accumulator Electricity condition;It is respectively the capacity of kth energy-storage system of accumulator and the upper and lower of state-of-charge 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;NTFor time discontinuity surface number;Pi (t) is the active power injected at t node i; Δ t is step-length.
3, the operation constraint of distribution network system self is considered, including system load flow constraint, working voltage constraint, branch current Constraint and energy-storage system of accumulator run constraint, specific as follows:
(3-1) system load flow constraint
In formula: i=2,3 ..., N;Ω (i) is the set of the adjacent node of node i;Ui(t), Uj(t), θijT () is respectively T node i and the voltage magnitude of j and phase angle difference;Gii, Bii, Gij, BijIt is respectively the self-conductance in bus admittance matrix, from electricity Receive, transconductance and mutual susceptance;Pi PV(t), Pi ESS(t), Pi L(t),It is respectively t node i The active power of upper PV, accumulator, load injection and reactive power;
(3-2) working voltage constraint
Uimin≤Ui(t)≤UimaxFormula (9), i=1,2 ..., N,
In formula, UiminAnd UimaxIt is respectively the bound of node i voltage magnitude;
(3-3) branch current constraint
In formula, IijT () is that t flows through the current amplitude of branch road between node i and node j;Ui(t), Uj(t), θij(t) It is respectively t node i and the voltage magnitude of j and phase angle difference;Gii, Bii, Gij, BijThe electricity certainly being respectively in bus admittance matrix Lead, from susceptance, transconductance and mutual susceptance;IijmaxThe current amplitude upper limit for branch road ij;
(3-4) energy-storage system of accumulator runs constraint
In formula, k=1,2 ..., NESS, wherein NESSFor energy-storage 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 charge-discharge electric power of accumulator;Δ t is simulation step length;During for t Carve the state-of-charge of kth energy-storage system of accumulator;It is respectively kth energy-storage system of accumulator Capacity and the upper lower limit value of state-of-charge.
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:
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, output optimal solution, is the charge-discharge electric power of energy-storage 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, above-mentioned energy-storage 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 energy-storage system of accumulator and optimize it Before, system loss is 1316.05kW h.Energy-storage 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 energy-storage system participates in active distribution network runing adjustment computational methods, it is characterised in that comprise the steps:
(1) consider the meritorious of energy-storage system and idle characteristic, set up energy-storage system moving model;
(2) determine that energy-storage 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 energy-storage system run constraint;
(4) PSO Algorithm energy-storage 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-discharge electric power of energy-storage system day part is Optimal solution.
Energy-storage 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 energy-storage system moving model, it is assumed that energy-storage 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 ..., NESS, wherein NESSFor energy-storage 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 charge-discharge electric power of energy-storage system;
The state-of-charge of described energy-storage 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 ..., NESS;Δ t is simulation step length;State-of-charge for t kth energy-storage system;
The energy storage capacity of each time point of described energy-storage system is between the bound of state-of-charge, and expression formula is as follows:
In formula,It is respectively capacity and the upper lower limit value of state-of-charge of kth energy-storage system.
Energy-storage 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;NTFor time discontinuity surface number;Pi (t) is the active power injected at t node i;Δ t is Step-length.
Energy-storage 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 energy-storage system run constraint, specific as follows:
(3-1) system load flow constraint
P i ( t ) = G i i ( U i ( t ) ) 2 + Σ j ∈ Ω ( i ) ( U i ( t ) U j ( t ) G i j c o s ( θ i j ( t ) ) + U i ( t ) U j ( t ) B i j s i n ( θ i j ( t ) ) ) = P i P V ( t ) + P i E S S ( t ) - P i L ( t )
Formula (7),
Q i ( t ) = - B i i ( U i ( t ) ) 2 - Σ j ∈ Ω ( i ) ( U i ( t ) U j ( t ) B i j c o s ( θ i j ( t ) ) - U i ( t ) U j ( t ) G i j s i n ( θ i j ( t ) ) ) = Q i P V ( t ) + Q i E S S ( t ) - Q i L ( t )
Formula (8),
In formula: i=2,3 ..., N;Ω (i) is the set of the adjacent node of node i;Ui(t), Uj(t), θijT () is respectively t Node i and the voltage magnitude of j and phase angle difference;Gii, Bii, Gij, BijBe respectively the self-conductance 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;
(3-2) working voltage constraint
Uimin≤Ui(t)≤UimaxFormula (9), i=1,2 ..., N,
In formula, UiminAnd UimaxIt is respectively the bound of node i voltage magnitude;
(3-3) branch current constraint
In formula, IijT () is that t flows through the current amplitude of branch road between node i and node j;Ui(t), Uj(t), θij(t) difference For t node i and the voltage magnitude of j and phase angle difference;Gii, Bii, Gij, BijBe respectively the self-conductance in bus admittance matrix, from Susceptance, transconductance and mutual susceptance;IijmaxThe current amplitude upper limit for branch road ij;
(3-4) energy-storage system runs constraint
In formula, k=1,2 ..., NESS, wherein NESSFor energy-storage 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 charge-discharge electric power of accumulator;Δ t is simulation step length;For t kth energy storage The state-of-charge of system;It is respectively the capacity of kth energy-storage system and the upper of state-of-charge Lower limit.
Energy-storage 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:
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 the random number between [0,1].
Energy-storage 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 energy-storage system is utilized to participate in the optimization of power distribution network runing adjustment Model.
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CN107403239A (en) * 2017-07-25 2017-11-28 南京工程学院 A kind of parameters analysis method for being used for control device in power system
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