CN101794995A - Energy management method of off-gird type wind power generation system - Google Patents

Abstract

The invention discloses an energy management method of an off-grid type wind power generation system, which comprises the following steps: (1) dividing the work state of the wind power generation system into various work state modes according to electric power Pg generated by a motor, electric power Pi consumed by loads, electric power Pbc consumed by accumulator charging and electric power Pbd discharged by the accumulator; (2) detecting the values of various electric power; (3) judging the work state mode of the wind generation system; and (4) controlling according to the work state mode of a wind power generator. The invention realizes the effective regulation and control of the energy flow mode of the off-gird type wind power generation system by dividing the work state modes of the off-gird type wind generation system, and can improve the preference degree of the load power supply according to the requirement, so that the energy utilization ratio of the off-grid type wind power generation system is improved, the reality of the loading and power supply is improved, and the safety and the reliability of system operation are ensured.

Description

A kind of energy management method from net type wind generator system

Technical field

The present invention relates to wind power generation field, particularly a kind of energy management method from net type wind generator system.

Background technology

Wind generator system has two kinds of different types, that is: " grid type " of " from the net type " of independent operating and access power system operation." from the net type " wind generator system and electrical network break away from, and are stored by the electric energy that equipment such as storage battery send electricity generation system, solve the powerup issue of remote districts well." grid type " wind generator system inserts electrical network, by energy management control system, can provide electric energy for electrical network, and ensures the reliability service of load.

In China, from net type wind generator system is the principal mode of family with miniature wind power generation system, and its energy Flow process is fairly simple, generally by storage battery the electric energy that wind-driven generator sends is stored, after finishing Deng charge in batteries, power to the load by storage battery.If the electric energy that wind-driven generator sends is excessive, wind generator system will use unloader with the energy removal.Lack effective energy management because China is most at present from net type wind generator system, feasible capacity usage ratio from net type wind generator system is low, and the power supply of load is stable inadequately.

Summary of the invention

For addressing the above problem, thus the invention provides a kind of can be to effectively manage the energy management method that improves from the energy utilization efficiency of net type wind generator system from the energy of net type wind generator system.

The technical scheme that the present invention is adopted for its problem of solution is:

A kind of energy management method from net type wind generator system may further comprise the steps:

(1) electrical power P of sending according to wind-driven generator _g, the consumption of electric power P of load institute _l, the electrical power P that consumes of charge in batteries _BcAnd the electrical power P that can emit of storage battery _BdThe operating state of wind generator system is divided into multiple operating state pattern, and described operating state pattern comprises:

A, pattern one, the electrical power P that wind-driven generator sends _gGreater than the consumption of electric power P of load institute _lElectrical power P with charge in batteries consumption _BcSum;

B, pattern two, the electrical power P that wind-driven generator sends _gGreater than the consumption of electric power P of load institute _l, the electrical power P that wind-driven generator sends _gLess than the consumption of electric power P of load institute _lElectrical power P with charge in batteries consumption _BcSum;

C, pattern three, the electrical power P that wind-driven generator sends _gLess than the consumption of electric power P of load institute _l, the electrical power P that wind-driven generator sends _gThe electrical power P that can emit with storage battery _BdSum is greater than the consumption of electric power P of load institute _l

D, pattern four, the electrical power P that wind-driven generator sends _gThe electrical power P that can emit with storage battery _BdSum is less than the consumption of electric power P of load institute _l, the electrical power P that wind-driven generator sends _gElectrical power P greater than charge in batteries consumption _Bc

E, pattern five, the electrical power P that wind-driven generator sends _gThe electrical power P that can emit with storage battery _BdSum is less than the consumption of electric power P of load institute _l, the electrical power P that wind-driven generator sends _gElectrical power P less than charge in batteries consumption _Bc

(2) detect the electrical power P that wind-driven generator sends _g, the consumption of electric power P of load institute _l, the electrical power P that consumes of charge in batteries _BcAnd the electrical power P that can emit of storage battery _BdSize;

(3) judge the residing operating state pattern of wind-driven generator according to the detected value that obtains in the step (2);

(4) control according to the residing operating state pattern of wind-driven generator: when being in pattern for the moment, battery charging circuit is opened, charge in batteries, and wind-driven generator powers to the load by dc bus; When being in pattern two, battery charging circuit and discharge circuit are closed, and wind-driven generator powers to the load by dc bus, and the rotating speed of wind-driven generator is changed simultaneously, and the electrical power that the restriction wind-driven generator sends realizes the electrical power balance; When being in pattern three, the battery discharging circuit is opened, and storage battery and wind-driven generator power to the load simultaneously by dc bus; When being in pattern four, the electric loop is cut off, and battery charging circuit is opened, charge in batteries; When being in pattern five, relief arrangement is opened, the removal energy.

Preferably, step (3) adopts the Bayesian decision method that the residing operating state pattern of wind-driven generator is judged.

Further, this determination methods may further comprise the steps:

A determines sample space U={ ω ₁, ω ₂, ω ₃, ω ₄, ω ₅, ω wherein _j(1≤j≤5) are five operating state patterns of wind generator system;

B determines parameter space Γ={ x ₁, x ₂, x ₃, x ₄, wherein be x ₁The electrical power P of representing wind-driven generator to send _g, x ₂Represent the consumption of electric power P of load institute _l, x ₃The electrical power P of representing charge in batteries to consume _Bc, x ₄The electrical power P of representing storage battery to emit _Bd

C determines each operating state pattern ω _j(1≤j≤5) shared time scale in duration T, promptly $P_{{\mathrm{\ω}}_j}(1\≤j\≤5),$ $\underset{j=1}{\overset{5}{\mathrm{\Σ}}}{P}_{{\mathrm{\ω}}_j}=1;$

D determines conditional probability P (the x| ω of concrete characteristic vector x in each operating state pattern among the parameter space Γ _j), ω wherein _j(1≤j≤5);

E calculates the probability that concrete characteristic vector x belongs to each operating state pattern

$P\left({\mathrm{\ω}}_j\right|x)=\frac{P\left({\mathrm{\ω}}_j\right)\×P\left(x\right|{\mathrm{\ω}}_j)}{\underset{i=1}{\overset{5}{\mathrm{\Σ}}}{P}_{{\mathrm{\ω}}_i\×}P\left(x\right|{\mathrm{\ω}}_j)},$ 1≤j≤5 wherein;

F utilizes the discrimination method of following Bayesian decision based on minimal error rate that operating state pattern under the concrete characteristic vector x is judged: if P is (ω _j| x)=max{P (ω _j| x) },, then x belongs to operating state pattern ω _j, j=1,2 ..., 5.

The invention has the beneficial effects as follows: the present invention is by to dividing from the operating state pattern of net type wind generator system, realization is to the effective planning and the control of its energy Flow mode, and can improve the preference of electric as required, thereby improve energy utilization efficiency from net type wind generator system, improve the electric reliability, also guaranteed the safe and reliable of system's operation simultaneously.

Description of drawings

The invention will be further described below in conjunction with drawings and Examples:

Fig. 1 is the system block diagram from net type wind generator system;

Fig. 2 is the energy Flow schematic diagram of pattern one of the present invention;

Fig. 3 is the energy Flow schematic diagram of pattern two of the present invention;

Fig. 4 is the energy Flow schematic diagram of pattern three of the present invention;

Fig. 5 is the energy Flow schematic diagram of pattern four of the present invention;

Fig. 6 is the energy Flow schematic diagram of pattern five of the present invention.

Embodiment

Referring to figs. 1 through Fig. 6, energy management method of the present invention generally is applied to comprise wind energy conversion system, wind-driven generator, drain charge device, storage battery, load etc. from net type wind generator system from net type wind generator system, as shown in Figure 1, this energy management method may further comprise the steps:

(1) electrical power P of sending according to wind-driven generator _g, the consumption of electric power P of load institute _l, the electrical power P that consumes of charge in batteries _BcAnd the electrical power P that can emit of storage battery _BdThe operating state of wind generator system is divided into multiple operating state pattern, and described operating state pattern comprises:

A, pattern one, the electrical power P that wind-driven generator sends _gGreater than the consumption of electric power P of load institute _lElectrical power P with charge in batteries consumption _BcSum;

B, pattern two, the electrical power P that wind-driven generator sends _gGreater than the consumption of electric power P of load institute _l, the electrical power P that wind-driven generator sends _gLess than the consumption of electric power P of load institute _lElectrical power P with charge in batteries consumption _BcSum;

C, pattern three, the electrical power P that wind-driven generator sends _gLess than the consumption of electric power P of load institute _l, the electrical power P that wind-driven generator sends _gThe electrical power P that can emit with storage battery _BdSum is greater than the consumption of electric power P of load institute _l

D, pattern four, the electrical power P that wind-driven generator sends _gThe electrical power P that can emit with storage battery _BdSum is less than the consumption of electric power P of load institute _l, the electrical power P that wind-driven generator sends _gElectrical power P greater than charge in batteries consumption _Bc

E, pattern five, the electrical power P that wind-driven generator sends _gThe electrical power P that can emit with storage battery _BdSum is less than the consumption of electric power P of load institute _l, the electrical power P that wind-driven generator sends _gElectrical power P less than charge in batteries consumption _Bc

(2) detect the electrical power P that wind-driven generator sends _g, the consumption of electric power P of load institute _l, the electrical power P that consumes of charge in batteries _BcAnd the electrical power P that can emit of storage battery _BdSize;

(3) judge the residing operating state pattern of wind-driven generator according to the detected value that obtains in the step (2), the present invention preferably adopts the Bayesian decision method to judge when judging, this determination methods may further comprise the steps:

A determines sample space U={ ω ₁, ω ₂, ω ₃, ω ₄, ω ₅, ω wherein _j(1≤j≤5) are five operating state patterns of wind generator system;

B determines parameter space Γ={ x ₁, x ₂, x ₃, x ₄, wherein be x ₁The electrical power P of representing wind-driven generator to send _g, x ₂Represent the consumption of electric power P of load institute _l, x ₃The electrical power P of representing charge in batteries to consume _Bc, x ₄The electrical power P of representing storage battery to emit _Bd

C determines each operating state pattern ω _j(1≤j≤5) are shared time scale in duration T (for example 24 hours), promptly $P_{{\mathrm{\ω}}_j}(1\≤j\≤5),$ $\underset{j=1}{\overset{5}{\mathrm{\Σ}}}{P}_{{\mathrm{\ω}}_j}=1;$

D determines conditional probability P (the x| ω of concrete characteristic vector x in each operating state pattern among the parameter space Γ _j), ω wherein _j(1≤j≤5);

E calculates the probability that concrete characteristic vector x belongs to each operating state pattern $P\left({\mathrm{\ω}}_j\right|x)=\frac{P\left({\mathrm{\ω}}_j\right)\×P\left(x\right|{\mathrm{\ω}}_j)}{\underset{i=1}{\overset{5}{\mathrm{\Σ}}}{P}_{{\mathrm{\ω}}_i\×}P\left(x\right|{\mathrm{\ω}}_j)},$ 1≤j≤5 wherein;

F utilizes the discrimination method of following Bayesian decision based on minimal error rate that operating state pattern under the concrete characteristic vector x is judged: if P is (ω _j| x)=max{P (ω _j| x) },, then x belongs to operating state pattern ω _j, j=1,2 ..., 5;

(4) control according to the residing operating state pattern of wind-driven generator: when being in pattern for the moment, battery charging circuit is opened, charge in batteries, and wind-driven generator powers to the load by dc bus, as shown in Figure 2; When being in pattern two, battery charging circuit and discharge circuit are closed, and wind-driven generator powers to the load by dc bus, and the rotating speed of wind-driven generator is changed simultaneously, and the electrical power that the restriction wind-driven generator sends realizes the electrical power balance, as shown in Figure 3; When being in pattern three, the battery discharging circuit is opened, and storage battery and wind-driven generator power to the load simultaneously by dc bus, as shown in Figure 4; When being in pattern four, the electric loop is cut off, and battery charging circuit is opened, charge in batteries, as shown in Figure 5; When being in pattern five, relief arrangement is opened, the removal energy, as shown in Figure 6.

The above only is a preferred implementation of the present invention, should be pointed out that for those skilled in the art, under the prerequisite that does not break away from the principle of the invention, can make some improvement, and these improvement also should be considered as protection scope of the present invention.

Claims (3)

1. energy management method from net type wind generator system is characterized in that may further comprise the steps:

(1) electrical power P of sending according to wind-driven generator _g, the consumption of electric power P of load institute _l, the electrical power P that consumes of charge in batteries _BcAnd the electrical power P that can emit of storage battery _BdThe operating state of wind generator system is divided into multiple operating state pattern, and described operating state pattern comprises:

A, pattern one, the electrical power P that wind-driven generator sends _gGreater than the consumption of electric power P of load institute _lElectrical power P with charge in batteries consumption _BcSum;

B, pattern two, the electrical power P that wind-driven generator sends _gGreater than the consumption of electric power P of load institute _l, the electrical power P that wind-driven generator sends _gLess than the consumption of electric power P of load institute _lElectrical power P with charge in batteries consumption _BcSum;

C, pattern three, the electrical power P that wind-driven generator sends _gLess than the consumption of electric power P of load institute _l, the electrical power P that wind-driven generator sends _gThe electrical power P that can emit with storage battery _BdSum is greater than the consumption of electric power P of load institute _l

D, pattern four, the electrical power P that wind-driven generator sends _gThe electrical power P that can emit with storage battery _BdSum is less than the consumption of electric power P of load institute _l, the electrical power P that wind-driven generator sends _gElectrical power P greater than charge in batteries consumption _Bc

E, pattern five, the electrical power P that wind-driven generator sends _gThe electrical power P that can emit with storage battery _BdSum is less than the consumption of electric power P of load institute _l, the electrical power P that wind-driven generator sends _gElectrical power P less than charge in batteries consumption _Bc

(2) detect the electrical power P that wind-driven generator sends _g, the consumption of electric power P of load institute _l, the electrical power P that consumes of charge in batteries _BcAnd the electrical power P that can emit of storage battery _BdSize;

(3) judge the residing operating state pattern of wind-driven generator according to the detected value that obtains in the step (2);

(4) control according to the residing operating state pattern of wind-driven generator: when being in pattern for the moment, battery charging circuit is opened, charge in batteries, and wind-driven generator powers to the load by dc bus; When being in pattern two, battery charging circuit and discharge circuit are closed, and wind-driven generator powers to the load by dc bus, and the rotating speed of wind-driven generator is changed simultaneously, and the electrical power that the restriction wind-driven generator sends realizes the electrical power balance; When being in pattern three, the battery discharging circuit is opened, and storage battery and wind-driven generator power to the load simultaneously by dc bus; When being in pattern four, the electric loop is cut off, and battery charging circuit is opened, charge in batteries; When being in pattern five, relief arrangement is opened, the removal energy.

2. a kind of energy management method from net type wind generator system according to claim 1 is characterized in that step (3) adopts the Bayesian decision method that the residing operating state pattern of wind-driven generator is judged.

3. a kind of energy management method from net type wind generator system according to claim 2 is characterized in that this determination methods may further comprise the steps:

A determines sample space U={ ω ₁, ω ₂, ω ₃, ω ₄, ω ₅, ω wherein _j(1≤j≤5) are five operating state patterns of wind generator system;

B determines parameter space Γ={ x ₁, x ₂, x ₃, x ₄, wherein be x ₁The electrical power P of representing wind-driven generator to send _g, x ₂Represent the consumption of electric power P of load institute _l, x ₃The electrical power P of representing charge in batteries to consume _Bc, x ₄The electrical power P of representing storage battery to emit _Bd

C determines each operating state pattern ω _j(1≤j≤5) shared time scale in duration T, promptly

(1≤j≤5),

D determines conditional probability P (the x| ω of concrete characteristic vector x in each operating state pattern among the parameter space Γ _j), ω wherein _j(1≤j≤5);

E calculates the probability that concrete characteristic vector x belongs to each operating state pattern $P\left({\mathrm{\ω}}_j\right|x)=\frac{P\left({\mathrm{\ω}}_j\right)\×P\left(x\right|{\mathrm{\ω}}_j)}{\underset{i=1}{\overset{5}{\mathrm{\Σ}}}{P}_{{\mathrm{\ω}}_i}\×P\left(x\right|{\mathrm{\ω}}_j)},$ 1≤j≤5 wherein;

F utilizes the discrimination method of following Bayesian decision based on minimal error rate that operating state pattern under the concrete characteristic vector x is judged: if P is (ω _j| x)=max{P (ω _j| x) },, then x belongs to operating state pattern ω _j, j=1,2 ..., 5.

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