CN104979850A - Wind-power-contained power system scheduling method with involvement of energy storage for standby - Google Patents

Abstract

The invention discloses a wind-power-contained power system scheduling method with involvement of energy storage for standby. The method comprises the following steps: monitoring a power of a thermal power generating unit, a creep speed, and a power of an active load in real time; carrying out statistics on a wind-power historical prediction error to generate a wind-power scene; according to a constraint condition of the system, establishing a scheduling model and solving the model; and carrying out statistics on a scheduling result. The energy storage system effect is taken into consideration in standby configuration and the energy storage system can change the charging/discharging powers to provide standby application for dealing with a wind-power uncertainty problem, so that an effect of elimination of the wind-power and load uncertainty can be realized during secondary and primary adjustment. Meanwhile, the frequency adjustment effect is considered and thus the pressure of the standby configuration of the conventional unit can be reduced, thereby enhancing the capability of wind-power absorption of the power grid.

Description

A kind of energy storage participates in the power system dispatching method containing wind-powered electricity generation for subsequent use

Technical field

The present invention relates to a kind of energy storage and participate in the power system dispatching method containing wind-powered electricity generation for subsequent use.

Background technology

Biological environment goes from bad to worse, and threatens human survival, and it is imperative that clean energyization is changed, and electric power system must to green, low-carbon (LC), environmental protection and the development of energy-conservation intelligent direction.In this context, the renewable energy power generations such as scene obtain fast development, and making must in the face of the test of strong uncertain receiving ability in power system operation process.

The patent No. is the Chinese patent of 201110001574.7: " the bulk power grid real-time scheduling method of wind power integration of dissolving ", give a kind of bulk power grid real-time scheduling method of wind power integration of dissolving, this patent is passed through the whole network computer-assisted classification, then the plan a few days ago of unit is obtained from system, exert oneself in real time, the relevant informations such as interconnection plan and numerical weather forecast, carry out ultra-short term and wind power output prediction, the regulated quantity of exerting oneself of trying to achieve subsequent time Real-Time Scheduling unit also builds the meritorious Real-Time Scheduling model abandoning wind loss reduction, simplex method is adopted to try to achieve the Real-Time Scheduling adjustmentcapacity of unit comprising Wind turbines.

The patent No. is the Chinese patent of 201210371334.0: " the power system dispatching method based on wind power output indefinite set ", disclose a kind of power system dispatching method based on wind power output indefinite set, solve in the electric power system Robust Scheduling problem containing large-scale wind power, a difficult problem for wind power output uncertainties model, ensure the security reliability of electrical network Unit Commitment and operation plan, effectively improve the utilance of wind energy turbine set wind power output.

The patent No. is the Chinese patent of 201210176522.8: " a kind of electric automobile and wind-powered electricity generation work in coordination with Real-Time Scheduling optimization method ", and the electric network model according to actual electric network sets up the Optimized model being target with meritorious total electricity to the maximum; The punishment amount that always meritorious power curve changes relation is joined in optimization aim, obtains the Optimal Operation Model considering generating curve smoothing; By the non-linear factor linearisation in model, adopt dual simplex method to solve, draw the Active Generation curve of wind-solar-storage joint electricity generation system, report to higher level control centre, and obtain the discharge and recharge plan of energy storage device, issue subsystem and perform.

Dispatching method described in above patent is all in scheduling, lock energy-storage system charge/discharge power, bears for subsequent use of coping with uncertainty completely by conventional power unit.Under the situation that conventional power unit leading position weakens gradually, this Research Thinking will be difficult to prove effective.

Summary of the invention

The present invention is in order to solve the problem, propose a kind of energy storage and participate in the power system dispatching method containing wind-powered electricity generation for subsequent use, this method considers energy-storage system effect in standby configuration, energy-storage system can provide for subsequent use by changing charge/discharge power for tackling wind-powered electricity generation uncertainty, the effect eliminating wind-powered electricity generation, negative rules is played in secondary, once adjustment, consider frequency adjustment effect simultaneously, finally can alleviate the pressure of conventional power unit standby configuration, improve electrical network and to dissolve the ability of wind-powered electricity generation.

To achieve these goals, the present invention adopts following technical scheme:

Energy storage participates in the power system dispatching method containing wind-powered electricity generation for subsequent use, comprises the following steps:

(1) power of Real-Time Monitoring fired power generating unit power, creep speed and active load;

(2) the wind energy turbine set historical forecast error of access electrical network is added up, generate wind-powered electricity generation scene;

(3) according to the constraints of system, set up power system dispatching model, solve this model;

In described step (1), the data of Real-Time Monitoring comprise: unit peak power output, minimum output power, unit creep speed and the maximum charge/discharge power of active load.

In described step (2), adopt autoregressive moving average (ARMA) model to estimate Power Output for Wind Power Field predicated error, expression formula is,

${\mathrm{\Δp}}_{gw}^t=\underset{i=1}{\overset{p}{\Σ}}{\mathrm{\α}}_i\·{\mathrm{\Δp}}_{gw}^{t-i}+{\mathrm{\ϵ}}_t+\underset{j=1}{\overset{q}{\Σ}}{\mathrm{\β}}_i\·{\mathrm{\ϵ}}_{t-j}---\left(1\right)$

In formula, p, q are respectively the exponent number in arma modeling; α _i, β _jfor model parameter, by estimating to obtain; ε is 0 for obeying average, and variance is σ ²the white noise of Gaussian Profile; for predicated error.

By adding up wind-powered electricity generation historical forecast error, least square method is adopted to obtain the value of parameter in formula (1).Due to ε Normal Distribution, stochastic simulation produces ε, can generate the wind-powered electricity generation scene of needs.

In described step (3), power system dispatching model is:

Consider wind-powered electricity generation not consume fuel, disregard cost and the operating cost of energy-storage system, target function is expressed as following form:

$min\underset{t=1}{\overset{T}{\Σ}}\underset{i=1}{\overset{N_g}{\Σ}}{C}_{Gi}\left(P_{Gi,t}\right)+C_{Gi}^{res}({\mathrm{\ΔP}}_{Gi,t}^{up},{\mathrm{\ΔP}}_{Gi,t}^{dn})---\left(2\right)$

In formula, P _w,tfor t period Power Output for Wind Power Field predicted value; P _l,tfor t period predicted load; P _{eSS, t}for t period energy-storage system active power, P _{eSS, t}>0 represents that energy-storage system charges, P _{eSS, t}<0 represents energy storage system discharges.

In described step (3), need to consider constraints, constraints comprises:

Power-balance retrains:

$\underset{i=1}{\overset{N_g}{\&Sigma;}}{P}_{Gi,t}+P_{W,t}-P_{L,t}=P_{ESS,t}---\left(3\right)$

In formula, P _w,tfor t period Power Output for Wind Power Field predicted value; P _l,tfor t period predicted load; P _{eSS, t}for t period energy-storage system active power, P _{eSS, t}>0 represents that energy-storage system charges, P _{eSS, t}<0 represents energy storage system discharges.

In described step (3), constraints comprises:

Unit power output bound retrains:

$P_{Gi}^{\min }\&le;P_{Gi,t}\&le;P_{Gi}^{\max }---\left(4\right)$

In formula, with be respectively lower limit and the upper limit of unit i power output.

In described step (3), constraints comprises:

Unit ramping rate constraints:

-r _Gi·Δt≤P _Gi,t+1-P _Gi,t≤r _Gi·Δt (5)

In formula, r _gifor unit i power output maximum adjustment, Δ t is Period Length.

In described step (3), constraints comprises: energy-storage system inverter charge-discharge electric power retrains:

$-P_{ESS}^{\max }\&le;P_{ESS,t}\&le;P_{ESS}^{\max }---\left(6\right)$

In formula, for the charge-discharge electric power maximum that inverter allows.

In described step (3), constraints comprises: the energy-storage system stored energy constraint of day part end,

E _t＝E _t-1+P _ESS,tΔt

In described step (3), constraints comprises: energy-storage system stored energy retrains,

E ^min≤E _t≤E ^max(7)

In formula, E ^minand E ^maxbe respectively minimum value and the maximum of energy-storage system storage power.

In described step (3), constraints comprises, the constraint based on each scene: establish for wind-powered electricity generation in scene s is in the power output of period t, for t period load value in scene s, work as P _{eSS, t}> 0, namely during energy-storage system charging, energy-storage system is by increasing charge power reply wind power output power higher than planned value or the load scene lower than predicted value, the charge power that the lockable fluctuation range of energy-storage system is allowed by inverter and the quantitative limitation of maximum storage energy, specifically can be expressed as

${\mathrm{\&Delta;P}}_{\mathrm{ESS},t}^{\mathrm{dn}}=\min \{\frac{E^{\max }-E_{t-1}}{\mathrm{\&Delta;t}},P_{\mathrm{ESS}}^{\max }\}-P_{\mathrm{ESS},t}---\left(8\right)$

Work as P _{eSS, t}> 0, namely during energy-storage system charging, energy-storage system is by reducing charge power or electric discharge reply wind power output power is less than planned value or the load scene higher than predicted value, the discharge power that lockable scope is allowed by inverter and the quantitative limitation of minimum memory energy, specifically can be expressed as

${\mathrm{\&Delta;P}}_{ESS,t}^{up}=\min \{\frac{E_{t-1}-E^{\min }}{\mathrm{\&Delta;}t},P_{ESS}^{\max }\}+P_{ESS,t}---\left(9\right)$

For scene s, need the adjustment reserve capacity up and down that fired power generating unit provides can be expressed as,

$\{\begin{array}{c}{\mathrm{RES}}_t^{up,s}=\max \{0,(P_{W,t}-P_{W,t}^s+P_{L,t}^s-P_{L,t})-{\mathrm{\&Delta;P}}_{ESS,t}^{up}\}\\ {\mathrm{RES}}_t^{dn,s}=\max \{0,(P_{W,t}^s-P_{W,t}+P_{L,t}-P_{L,t}^s)-{\mathrm{\&Delta;P}}_{ESS,t}^{dn}\}\end{array}---\left(10\right)$

Fired power generating unit i regulates reserve capacity to be expressed as in the t period up and down consider that system frequency deviation is time load frequency adjustment effect, when wind-powered electricity generation and load actual power depart from desired value, if tolerance frequency changes within the specific limits, should meet,

$\{\begin{array}{c}\underset{i=1}{\overset{Ng}{\&Sigma;}}{\mathrm{\&Delta;P}}_{Gi,t}^{up,s}+{\mathrm{D\&Delta;f}}_t^s\&GreaterEqual;{\mathrm{RES}}_t^{up,s}\\ \underset{i=1}{\overset{Ng}{\&Sigma;}}{\mathrm{\&Delta;P}}_{Gi,t}^{dn,s}+{\mathrm{D\&Delta;f}}_t^s\&GreaterEqual;{\mathrm{RES}}_t^{dn,s}\end{array}---\left(11\right)$

In formula, the D coefficient that load active power increases or reduces caused by unit frequency change; Fired power generating unit regulates reserve capacity to meet up and down,

$\{\begin{array}{c}{\mathrm{\&Delta;P}}_{Gi,t}^{up,s}\&le;r_{Gi}\&CenterDot;\mathrm{\&Delta;}t+R_{Gi}{\mathrm{\&Delta;f}}_t^s\\ {\mathrm{\&Delta;P}}_{Gi,t}^{dn,s}\&le;r_{Gi}\&CenterDot;\mathrm{\&Delta;}t+R_{Gi}{\mathrm{\&Delta;f}}_t^s\end{array}---\left(12\right)$

In formula, R _githe coefficient that the caused unit i power output of cell frequency change increases or reduces;

Meanwhile, fired power generating unit power output should meet bound constraint, namely

$\{\begin{array}{c}{P}_{Gi,t}+{\mathrm{\&Delta;P}}_{Gi,t}^{up,s}\&le;P_{Gi}^{\max }\\ P_{Gi,t}-{\mathrm{\&Delta;P}}_{Gi,t}^{dn,s}\&GreaterEqual;P_{Gi}^{\min }\end{array}---\left(13\right)$

System frequency deviation should meet,

${\mathrm{\&Delta;f}}^{\min }\&le;{\mathrm{\&Delta;f}}_t^s\&le;{\mathrm{\&Delta;f}}^{max}---\left(14\right)$

In formula, Δ f ^min, Δ f ^maxbe respectively the minimum and maximum frequency deviation that system allows.

In described step (3), get secondary according to cost function in target function or linearly express, quadratic programming or linear programming relax can be utilized respectively to solve.

Beneficial effect of the present invention is:

(1) the present invention considers energy-storage system effect in standby configuration, and energy-storage system can provide for subsequent use by changing charge/discharge power for reply wind-powered electricity generation uncertainty, in secondary, once adjustment, play the effect eliminating wind-powered electricity generation, negative rules;

(2) contemplated by the invention frequency adjustment effect, finally can alleviate the pressure of conventional power unit standby configuration, improve electrical network and to dissolve the ability of wind-powered electricity generation.

Accompanying drawing explanation

Fig. 1 is load, wind power curve chart.

Embodiment:

Below in conjunction with accompanying drawing and embodiment, the invention will be further described.

Energy-storage system participates in the power system dispatching method containing wind-powered electricity generation for subsequent use, comprises the following steps:

1) fired power generating unit, initiatively load relevant parameter and information is obtained.Fired power generating unit maximal regulated speed is unit capacity 1% per minute, and fired power generating unit difference coefficient is 4%, and namely system frequency change 4% causes the change of unit power output 100%.Energy-storage system parameter is in table 1.

Table 1 energy-storage system parameter

2) according to the statistics of wind-powered electricity generation historical forecast error, wind-powered electricity generation scene is generated.Wind-powered electricity generation and load are looking forward to the prospect the desired value in the period as shown in Figure 1.

3) set up scheduling model, and model is solved;

Scheduling model is:

Consider wind-powered electricity generation not consume fuel, disregard cost and the operating cost of energy-storage system, target function is expressed as following form:

$\min \underset{t=1}{\overset{T}{\&Sigma;}}\underset{i=1}{\overset{Ng}{\&Sigma;}}{C}_{Gi}\left(P_{Gi,t}\right)+C_{Gi}^{res}({\mathrm{\&Delta;P}}_{Gi,t}^{up},{\mathrm{\&Delta;P}}_{Gi,t}^{dn})---\left(1\right)$

In formula, P _w,tfor t period Power Output for Wind Power Field predicted value; P _l,tfor t period predicted load; P _{eSS, t}for t period energy-storage system active power, P _{eSS, t}>0 represents that energy-storage system charges, P _{eSS, t}<0 represents energy storage system discharges.

Constraints comprises:

1) power-balance constraint

$\underset{i=1}{\overset{Ng}{\&Sigma;}}{P}_{Gi,t}+P_{W,t}-P_{L,t}=P_{ESS,t}---\left(2\right)$

In formula, P _w,tfor t period Power Output for Wind Power Field predicted value; P _l,tfor t period predicted load; P _{eSS, t}for t period energy-storage system active power, P _{eSS, t}>0 represents that energy-storage system charges, P _{eSS, t}<0 represents energy storage system discharges.

2) unit power output bound constraint

$P_{Gi}^{\min }\&le;P_{Gi,t}\&le;P_{Gi}^{\max }---\left(3\right)$

In formula, with be respectively lower limit and the upper limit of unit i power output.

3) unit ramping rate constraints

-r _Gi·Δt≤P _Gi,t+1-P _Gi,t≤r _Gi·Δt (4)

In formula, r _gifor unit i power output maximum adjustment, Δ t is Period Length.

4) energy-storage system inverter charge-discharge electric power constraint

$-P_{ESS}^{\max }\&le;P_{ESS,t}\&le;P_{ESS}^{\max }---\left(5\right)$

In formula, for the charge-discharge electric power maximum that inverter allows.

5) day part end energy-storage system stored energy constraint

E _t＝E _t-1+P _ESS,tΔt (6)

6) energy-storage system stored energy constraint

E ^min≤E _t≤E ^max(7)

In formula, E ^minand E ^maxbe respectively minimum value and the maximum of energy-storage system storage power.

7) based on the constraint of each scene

By the uncertainty of the scenario simulation wind-powered electricity generation that may occur and load.Suppose for wind-powered electricity generation in scene s is in the power output of period t, for t period load value in scene s.In actual motion, if Power Output for Wind Power Field departs from planned value or load departs from predicted value, energy-storage system can change power output at secondary with in once adjusting, and wind-powered electricity generation and load are locked as planned value as far as possible.

Work as P _{eSS, t}> 0, namely during energy-storage system charging, energy-storage system is by increasing charge power reply wind power output power higher than planned value or the load scene lower than predicted value, the charge power that the lockable fluctuation range of energy-storage system is allowed by inverter and the quantitative limitation of maximum storage energy, specifically can be expressed as

${\mathrm{\&Delta;P}}_{ESS,t}^{dn}=\min \{\frac{E^{max}-E_{t-1}}{\mathrm{\&Delta;}t},P_{ESS}^{\max }\}-P_{ESS,t}---\left(8\right)$

Work as P _{eSS, t}> 0, namely during energy-storage system charging, energy-storage system is by reducing charge power or electric discharge reply wind power output power is less than planned value or the load scene higher than predicted value, the discharge power that lockable scope is allowed by inverter and the quantitative limitation of minimum memory energy, specifically can be expressed as

${\mathrm{\&Delta;P}}_{ESS,t}^{up}=min\{\frac{E_{t-1}-E^{\min }}{\mathrm{\&Delta;}t},P_{ESS}^{\max }\}+P_{ESS,t}---\left(9\right)$

For scene s, need the adjustment reserve capacity up and down that fired power generating unit provides can be expressed as,

$\left\{\begin{array}{c}{\mathrm{RES}}_t^{up,s}=\max \{0,(P_{W,t}-P_{W,t}^s+P_{L,t}^s-P_{L,t})-{\mathrm{\&Delta;P}}_{ESS,t}^{up}\}\\ {\mathrm{RES}}_t^{dn,s}=\max \{0,(P_{W,t}^s-P_{W,t}+P_{L,t}-P_{L,t}^s)-{\mathrm{\&Delta;P}}_{ESS,t}^{du}\}\end{array}\right.---\left(10\right)$

Fired power generating unit i regulates reserve capacity to be expressed as in the t period up and down consider that system frequency deviation is time load frequency adjustment effect, when wind-powered electricity generation and load actual power depart from desired value, if tolerance frequency changes within the specific limits, should meet,

$\{\begin{array}{c}\underset{i=1}{\overset{Ng}{\&Sigma;}}{\mathrm{\&Delta;P}}_{Gi,t}^{up,s}+{\mathrm{D\&Delta;f}}_t^s\&GreaterEqual;{\mathrm{RES}}_t^{up,s}\\ \underset{i=1}{\overset{Ng}{\&Sigma;}}{\mathrm{\&Delta;P}}_{Gi,t}^{dn,s}+{\mathrm{D\&Delta;f}}_t^s\&GreaterEqual;{\mathrm{RES}}_t^{dn,s}\end{array}---\left(11\right)$

In formula, the D coefficient that load active power increases or reduces caused by unit frequency change.

Fired power generating unit regulates reserve capacity to meet up and down,

$\{\begin{array}{c}{\mathrm{\&Delta;P}}_{Gi,t}^{up,s}\&le;r_{Gi}\&CenterDot;\mathrm{\&Delta;}t+R_{Gi}{\mathrm{\&Delta;f}}_t^s\\ {\mathrm{\&Delta;P}}_{Gi,t}^{dn,s}\&le;r_{Gi}\&CenterDot;{\mathrm{\&Delta;tR}}_{Gi}{\mathrm{\&Delta;f}}_t^s\end{array}---\left(12\right)$

In formula, R _githe coefficient that the caused unit i power output of cell frequency change increases or reduces.

Fired power generating unit power output should meet bound constraint, namely

$\{\begin{array}{c}{P}_{Gi,t}+{\mathrm{\&Delta;P}}_{Gi,t}^{up,s}\&le;P_{Gi}^{\max }\\ P_{Gi,t}-{\mathrm{\&Delta;P}}_{Gi,t}^{dn,s}\&GreaterEqual;P_{Gi}^{\min }\end{array}---\left(13\right)$

System frequency deviation should meet,

${\mathrm{\&Delta;f}}^{\min }\&le;{\mathrm{\&Delta;f}}_t^s\&le;{\mathrm{\&Delta;f}}^{max}---\left(14\right)$

In formula, Δ f ^min, Δ f ^maxbe respectively the minimum and maximum frequency deviation that system allows.

Formula (1)-(14) constitute basic scheduling model, get secondary or linearly express, quadratic programming or linear programming relax can be utilized respectively to solve according to cost function in target function.

4) scheduling result is added up.

Suppose that wind-powered electricity generation predicated error progressively increases with fixed step size 10%, corresponding scene apoplexy electro-mechanical wave strengthens, and following table gives the Comparative result situation of context of methods and conventional scheduling method

Two kinds of method contrast situations when table 2 wind-powered electricity generation uncertainty strengthens

As shown in Table 2, along with wind-powered electricity generation uncertainty strengthens, cost corresponding to two kinds of methods all can increase.Wind-powered electricity generation predicated error increases identical amount, and the recruitment of context of methods cost is less than conventional method.Further, when the predicated error of correspondence reaches 40%, conventional method is without solution, and context of methods participates in for subsequent use owing to considering energy storage, can tackle the fluctuation that wind-powered electricity generation is wider, adds electrical network and to dissolve the ability of renewable energy power generation.

By reference to the accompanying drawings the specific embodiment of the present invention is described although above-mentioned; but not limiting the scope of the invention; one of ordinary skill in the art should be understood that; on the basis of technical scheme of the present invention, those skilled in the art do not need to pay various amendment or distortion that creative work can make still within protection scope of the present invention.

Claims (10)

1. energy storage participates in the power system dispatching method containing wind-powered electricity generation for subsequent use, it is characterized in that: comprise the following steps:

(1) power of Real-Time Monitoring fired power generating unit power, creep speed and active load;

(2) the wind energy turbine set historical forecast error of access electrical network is added up, generate wind-powered electricity generation scene;

(3) according to the constraints of system, set up power system dispatching model, solve this model.

2. a kind of energy storage as claimed in claim 1 participates in the power system dispatching method containing wind-powered electricity generation for subsequent use, it is characterized in that: in described step (1), the data of Real-Time Monitoring comprise: unit peak power output, minimum output power, unit creep speed and the maximum charge/discharge power of active load.

3. a kind of energy storage as claimed in claim 1 participates in the power system dispatching method containing wind-powered electricity generation for subsequent use, it is characterized in that: in described step (2), adopt autoregressive moving average (ARMA) model to estimate Power Output for Wind Power Field predicated error, expression formula is

${\mathrm{\&Delta;p}}_{gw}^t=\underset{i=1}{\overset{p}{\&Sigma;}}{\mathrm{\&alpha;}}_i\&CenterDot;{\mathrm{\&Delta;p}}_{gw}^{t-i}+{\mathrm{\&epsiv;}}_t+\underset{j=1}{\overset{q}{\&Sigma;}}{\mathrm{\&beta;}}_j\&CenterDot;{\mathrm{\&epsiv;}}_{t-j}---\left(1\right)$

In formula, p, q are respectively the exponent number in arma modeling; α _i, β _jfor model parameter, by estimating to obtain; ε is 0 for obeying average, and variance is σ ²the white noise of Gaussian Profile; for predicated error.

By adding up wind-powered electricity generation historical forecast error, least square method is adopted to obtain the value of parameter in formula (1).Due to ε Normal Distribution, stochastic simulation produces ε, can generate the wind-powered electricity generation scene of needs.

4. a kind of energy storage as claimed in claim 1 participates in the power system dispatching method containing wind-powered electricity generation for subsequent use, it is characterized in that: in described step (3), power system dispatching model is:

Consider wind-powered electricity generation not consume fuel, disregard cost and the operating cost of energy-storage system, target function is expressed as following form:

$min\underset{t=1}{\overset{T}{\&Sigma;}}\underset{i=1}{\overset{Ng}{\&Sigma;}}{C}_{Gi}\left(P_{Gi,t}\right)+C_{Gi}^{res}({\mathrm{\&Delta;P}}_{Gi,t}^{up},{\mathrm{\&Delta;P}}_{Gi,t}^{dn})---\left(2\right)$

In formula, P _w,tfor t period Power Output for Wind Power Field predicted value; P _l,tfor t period predicted load; P _{eSS, t}for t period energy-storage system active power, P _{eSS, t}>0 represents that energy-storage system charges, P _{eSS, t}<0 represents energy storage system discharges.

5. a kind of energy storage as claimed in claim 1 participates in the power system dispatching method containing wind-powered electricity generation for subsequent use, it is characterized in that: in described step (3), and need to consider constraints, constraints comprises:

Power-balance retrains:

$\underset{i=1}{\overset{Ng}{\&Sigma;}}{P}_{Gi,t}+P_{W,t}-P_{L,t}=P_{ESS,t}---\left(3\right)$

In formula, P _w,tfor t period Power Output for Wind Power Field predicted value; P _l,tfor t period predicted load; P _{eSS, t}for t period energy-storage system active power, P _{eSS, t}>0 represents that energy-storage system charges, P _{eSS, t}<0 represents energy storage system discharges;

Unit power output bound retrains:

$P_{Gi}^{\min }\&le;P_{Gi,t}\&le;P_{Gi}^{\max }---\left(4\right)$

In formula, with be respectively lower limit and the upper limit of unit i power output.

6. a kind of energy storage as claimed in claim 1 participates in the power system dispatching method containing wind-powered electricity generation for subsequent use, it is characterized in that: in described step (3), constraints comprises:

Unit ramping rate constraints:

-r _Gi·Δt≤P _Gi,t+1-P _Gi,t≤r _Gi·Δt (5)

In formula, r _gifor unit i power output maximum adjustment, Δ t is Period Length.

7. a kind of energy storage as claimed in claim 1 participates in the power system dispatching method containing wind-powered electricity generation for subsequent use, it is characterized in that: in described step (3), constraints comprises: energy-storage system inverter charge-discharge electric power retrains:

$-P_{ESS}^{\max }\&le;P_{ESS,t}\&le;P_{ESS}^{\max }---\left(6\right)$

In formula, for the charge-discharge electric power maximum that inverter allows.

8. a kind of energy storage as claimed in claim 1 participates in the power system dispatching method containing wind-powered electricity generation for subsequent use, it is characterized in that: in described step (3), constraints comprises: the energy-storage system stored energy constraint of day part end,

E _t＝E _t-1+P _ESS,tΔt

In described step (3), constraints comprises: energy-storage system stored energy retrains,

E ^min≤E _t≤E ^max(7)

In formula, E ^minand E ^maxbe respectively minimum value and the maximum of energy-storage system storage power.

9. a kind of energy storage as claimed in claim 1 participates in the power system dispatching method containing wind-powered electricity generation for subsequent use, it is characterized in that: in described step (3), constraints comprises, the constraint based on each scene: establish for wind-powered electricity generation in scene s is in the power output of period t, for t period load value in scene s, work as P _{eSS, t}> 0, namely during energy-storage system charging, energy-storage system is by increasing charge power reply wind power output power higher than planned value or the load scene lower than predicted value, the charge power that the lockable fluctuation range of energy-storage system is allowed by inverter and the quantitative limitation of maximum storage energy, specifically can be expressed as

${\mathrm{\&Delta;P}}_{ESS,i}^{dn}=\min \{\frac{E^{max}-E_{t-1}}{\mathrm{\&Delta;}t},P_{ESS}^{\max }\}-P_{ESS,i}---\left(8\right)$

Work as P _{eSS, t}> 0, namely during energy-storage system charging, energy-storage system is by reducing charge power or electric discharge reply wind power output power is less than planned value or the load scene higher than predicted value, the discharge power that lockable scope is allowed by inverter and the quantitative limitation of minimum memory energy, specifically can be expressed as

${\mathrm{\&Delta;P}}_{ESS,i}^{up}=\min \{\frac{E_{t-1}-E^{\min }}{\mathrm{\&Delta;}t},P_{ESS}^{\max }\}+P_{ESS,t}---\left(9\right)$

For scene s, need the adjustment reserve capacity up and down that fired power generating unit provides can be expressed as,

$\left\{\begin{array}{c}{\mathrm{RES}}_t^{up,s}=max\{0,\left(P_{W,t}-P_{W,t}^s+P_{L,t}^s-P_{L,t}\right)-{\mathrm{\&Delta;P}}_{ESS,t}^{up}\}\\ {\mathrm{RES}}_t^{dn,s}=max\{0,\left(P_{W,t}^s-P_{W,t}+P_{L,t}-P_{L,t}^s\right)-{\mathrm{\&Delta;P}}_{ESS,t}^{dn}\}\end{array}\right.---\left(10\right)$

Fired power generating unit i regulates reserve capacity to be expressed as in the t period up and down consider that system frequency deviation is time load frequency adjustment effect, when wind-powered electricity generation and load actual power depart from desired value, if tolerance frequency changes within the specific limits, should meet,

$\left\{\begin{array}{c}\underset{i=1}{\overset{Ng}{\&Sigma;}}{\mathrm{\&Delta;P}}_{Gi,t}^{up,s}+{\mathrm{D\&Delta;f}}_t^s\&GreaterEqual;{\mathrm{RES}}_t^{up,s}\\ \underset{i=1}{\overset{Ng}{\&Sigma;}}{\mathrm{\&Delta;P}}_{Gi,t}^{dn,s}+{\mathrm{D\&Delta;f}}_t^s\&GreaterEqual;{\mathrm{RES}}_t^{dn,s}\end{array}\right.---\left(11\right)$

In formula, the D coefficient that load active power increases or reduces caused by unit frequency change; Fired power generating unit regulates reserve capacity to meet up and down,

$\{\begin{array}{c}{\mathrm{\&Delta;P}}_{Gi,i}^{up,s}\&le;r_{Gi}\&CenterDot;\mathrm{\&Delta;}t+R_{Gi}{\mathrm{\&Delta;f}}_t^s\\ {\mathrm{\&Delta;P}}_{Gi,i}^{dn,s}\&le;r_{Gi}\&CenterDot;\mathrm{\&Delta;}t+R_{Gi}{\mathrm{\&Delta;f}}_t^s\end{array}---\left(12\right)$

In formula, R _githe coefficient that the caused unit i power output of cell frequency change increases or reduces;

Meanwhile, fired power generating unit power output should meet bound constraint, namely

$\left\{\begin{array}{c}{P}_{Gi,t}+{\mathrm{\&Delta;P}}_{Gi,t}^{up,s}\&le;P_{Gi}^{\max }\\ P_{Gi,t}-{\mathrm{\&Delta;P}}_{Gi,t}^{dn,s}\&GreaterEqual;P_{Gi}^{\min }\end{array}\right.---\left(13\right)$

System frequency deviation should meet,

${\mathrm{\&Delta;f}}^{\min }\&le;{\mathrm{\&Delta;f}}_t^s\&le;{\mathrm{\&Delta;f}}^{max}---\left(14\right)$

In formula, Δ f ^min, Δ f ^maxbe respectively the minimum and maximum frequency deviation that system allows.

10. a kind of energy storage as claimed in claim 1 participates in the power system dispatching method containing wind-powered electricity generation for subsequent use, it is characterized in that: in described step (3), get secondary according to cost function in target function or linearly express, utilizing quadratic programming or linear programming relax to solve respectively.