CN112436559A - Electric power system scheduling method based on wind power active power control - Google Patents

Electric power system scheduling method based on wind power active power control Download PDF

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CN112436559A
CN112436559A CN201910786951.9A CN201910786951A CN112436559A CN 112436559 A CN112436559 A CN 112436559A CN 201910786951 A CN201910786951 A CN 201910786951A CN 112436559 A CN112436559 A CN 112436559A
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constraint
power plant
wind power
power
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CN112436559B (en
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郑铭洲
卜京
夏凡吴双
卞婉春
张飞云
孙莹
夏星星
殷明慧
谢云云
邹云
刘建坤
周前
汪成根
张宁宇
孙蓉
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Nanjing University of Science and Technology
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    • H—ELECTRICITY
    • H02—GENERATION; CONVERSION OR DISTRIBUTION OF ELECTRIC POWER
    • H02J—CIRCUIT ARRANGEMENTS OR SYSTEMS FOR SUPPLYING OR DISTRIBUTING ELECTRIC POWER; SYSTEMS FOR STORING ELECTRIC ENERGY
    • H02J3/00—Circuit arrangements for ac mains or ac distribution networks
    • H02J3/38—Arrangements for parallely feeding a single network by two or more generators, converters or transformers
    • H02J3/46—Controlling of the sharing of output between the generators, converters, or transformers
    • Y—GENERAL 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
    • Y02—TECHNOLOGIES OR APPLICATIONS FOR MITIGATION OR ADAPTATION AGAINST CLIMATE CHANGE
    • Y02E—REDUCTION OF GREENHOUSE GAS [GHG] EMISSIONS, RELATED TO ENERGY GENERATION, TRANSMISSION OR DISTRIBUTION
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Abstract

The invention discloses a power system scheduling method based on wind power active power control. The method comprises the following steps: firstly, calculating three electric quantities of adjustable capacity, adjustable rate and reserve capacity of each wind turbine in a wind power plant, which reflect the active power control capability, completing the calculation of the power control capability of the whole wind power plant by using the parameters of a single wind turbine, and quantitatively obtaining the adjustable capacity, the adjustable rate and the reserve capacity of the wind power plant; and then, by analogy with the output constraint and the climbing rate constraint of a conventional unit, two constraint conditions of the wind power plant output constraint and the wind power plant regulation rate constraint are constructed by using two parameters of the wind power plant regulation capacity and the regulation rate. And constructing a power system scheduling model based on wind power active power control by taking the optimal system scheduling economy as a target. And finally, solving the model by using CPLEX and obtaining an optimal scheduling scheme of the power system with optimal economy. The method can perform economic optimization scheduling on the power system under the condition of considering the active power control of the fan.

Description

Electric power system scheduling method based on wind power active power control
Technical Field
The invention belongs to the field of optimal scheduling of power systems, and particularly relates to a power system scheduling method based on wind power active power control.
Background
At present, with the large amount of grid connection of wind power, the wind power becomes one of the power generation modes with the largest scale, the strongest market competitiveness and the best development prospect in renewable energy except for water power, and the development of the wind power has the better prospect. However, wind power volatility, inverse peakedness and other characteristics bring more difficult challenges to the scheduling of the power grid. At present, most researches are carried out on the condition that wind power is regarded as negative load, the capability of the wind power to actively participate in scheduling is not considered, and other AGC units are required to be used for relieving the unstable characteristic of the wind power.
The national grid company standard requires that a grid-connected wind power plant has certain active regulation and control capability and can participate in power grid peak regulation and active control of a power system, so that the pressure of a conventional unit is reduced. Therefore, it is necessary to provide an economic dispatching method for an electric power system based on wind power active power control, which exerts its initiative and flexibility under the condition that a wind farm has a certain dispatching capability, and develops a new economic dispatching method for an electric power system under the condition that the requirement of economy is satisfied.
Disclosure of Invention
The invention aims to provide a power system scheduling method based on wind power active power control under the condition of considering wind power scheduling capability.
The technical solution for realizing the purpose of the invention is as follows: a power system scheduling method based on wind power active power control comprises the following steps:
step 1, calculating the active power control capability of each wind turbine in the wind power plant. Calculating three electrical quantities reflecting the active power control capability of each wind turbine in the wind power plant, namely the adjustable capacity, the adjustable speed and the fan reserve capacity, and taking the three electrical quantities as basic data of the active power control capability of the wind power plant in the step 2. The adjustable capacity of the wind turbine generator is obtained by subtracting the output power of the current period from the maximum power of the predicted wind speed of the next period, the adjusting rate is obtained by summarizing the test power change rate, and the standby capacity of the fan is obtained by calculating five percent of the adjustable capacity.
And 2, calculating the active power control capability of the wind power plant. The method comprises the steps of calculating the adjustable capacity, the adjusting rate and the wind field reserve capacity of the wind power plant, and obtaining the wind power plant by summing the parameters calculated in the step 1 by all the fans in the wind power plant. And 3, constructing a wind power constraint condition in the step 3 and constructing three parameters of a power system scheduling model based on wind power active power control in the step 4.
And 3, constructing related constraint conditions of the wind power plant. By analogy with the output constraint and the climbing rate constraint of a conventional unit, two constraint conditions of the wind power plant output constraint and the wind power plant regulation rate constraint are constructed by using two parameters of the wind power plant regulation capacity and the regulation rate. The output constraint of the wind power plant requires that the difference between the output power of the wind power plant in the next period and the output power of the wind power plant in the current period is smaller than the adjustable capacity of the wind power plant; the wind farm regulation rate constraint requires that the regulation capacity of the wind farm be less than the regulation rate.
And 4, constructing a power system scheduling model based on wind power active power control. This model targets the economic optimality of system scheduling, with costs including: the starting and stopping cost and the output cost of the conventional unit, and the output cost and the wind abandoning cost of the wind power plant. The constraints of this model include: the method comprises the following steps of (1) power balance constraint, tidal current safety constraint, hot standby constraint, conventional unit output constraint, conventional unit climbing constraint, conventional unit start-stop time constraint, conventional unit start-stop cost constraint, wind power plant output constraint and wind power plant regulation rate constraint constructed in step (3). Wherein the parameter of the wind farm spare capacity calculated in step 2 is involved in the hot spare constraint.
And 5, solving the model based on CPLEX and obtaining a scheduling scheme. Setting basic information and scenes such as grid structure, node parameters, line parameters, generator parameters and wind power plant parameters, and calculating a scheduling scheme of a power system scheduling model based on wind power active power control in the corresponding scene through a commercial CPELX solver. The scheduling scheme comprises the start-stop condition and the power output condition of the conventional unit and the wind power plant in each period.
Further, the method for calculating the active power control capability of each wind turbine in the wind farm in step 1 specifically includes:
and calculating three parameters of schedulable capacity, regulation rate and spare capacity of the single fan.
The adjustable capacity of the fan indicates that a single fan can actively participate in scheduling capacity, and a calculation formula is as follows:
Figure BDA0002178363580000021
in the formula, Pi,max,t+1Predicting the wind speed of the wind turbine generator i in the next periodMaximum power, Pi,tIs the output power P of the wind turbine generator i at the wind speed of the periodN,iThe rated power of the wind turbine generator i.
Secondly, the fan regulation rate is the embodiment of the regulation efficiency when a single fan participates in the scheduling, and the calculation formula is as follows:
Figure BDA0002178363580000022
in the formula,. DELTA.Pi,aThe power variation value of the wind turbine generator i in the a-th test is obtained; m is the total number of tests.
Thirdly, the spare capacity of the fan is the capacity which needs to be reserved when the single fan participates in scheduling, generally 5% of the adjustable capacity is taken, and the calculation formula is as follows:
Figure BDA0002178363580000031
in the formula,. DELTA.Pi *The adjustable capacity of the single fan is calculated by the formula (1).
Further, the method for calculating the active participation scheduling capability of the wind farm in step 2 specifically comprises the following steps:
and under the condition of the single fan parameter calculated according to the step one, calculating three parameters of the wind power plant.
The adjustable capacity of the wind power plant represents the active scheduling capacity of a single wind power plant, and the calculation formula is as follows:
Figure BDA0002178363580000032
in the formula, Pi,max,t+1Predicting the maximum power P of the wind turbine generator set i in the next periodi,tIs the output power P of the wind turbine generator i at the wind speed of the periodN,iIs the rated power of a wind turbine generator i, j represents the jth wind farm, njAnd the number of wind turbine sets in the wind power plant j is represented.
Secondly, the wind power plant regulation rate is the embodiment of regulation efficiency when a single wind power plant participates in scheduling, and the calculation formula is as follows:
Figure BDA0002178363580000033
in the formula,. DELTA.Pi,aIs the power variation value of the wind turbine generator i in the a-th test, m is the total number of tests, j represents the j-th wind power plant, njAnd the number of wind turbine sets in the wind power plant j is represented.
Thirdly, the spare capacity of the fan is the capacity which needs to be reserved when the single fan participates in scheduling, generally 5% of the adjustable capacity is taken, and the calculation formula is as follows:
Figure BDA0002178363580000034
in the formula,. DELTA.Pi *Capacity adjustable for a single fan, j denotes the jth wind farm, njAnd the number of wind turbine sets in the wind power plant j is represented.
Further, the construction of the relevant constraint conditions of the wind power plant in the step 3 is specifically as follows:
compared with the conventional unit, two constraints of the output constraint of the wind power plant and the regulation rate constraint of the wind power plant are obtained.
Output constraint of wind power plant
Figure BDA0002178363580000035
In the formula, Pj,tThe output of the wind power plant j at the moment t,
Figure BDA0002178363580000041
the capacity of the wind power plant can be adjusted.
Wind farm regulation rate constraint
Figure BDA0002178363580000042
In the formula (I), the compound is shown in the specification,
Figure BDA0002178363580000043
for capacity regulation of wind farms, vjThe rate is adjusted for the wind farm.
Further, the power system scheduling model based on wind power active power control in step 4 is specifically as follows:
the model takes the economic optimization of system scheduling as a target, and the target function is as follows:
Figure BDA0002178363580000044
in the formula (I), the compound is shown in the specification,
Figure BDA0002178363580000045
and
Figure BDA0002178363580000046
respectively the start-stop cost of the conventional unit i,
Figure BDA0002178363580000047
in order to reduce the output cost of the conventional unit i,
Figure BDA0002178363580000048
for the output cost of the wind farm j,
Figure BDA0002178363580000049
the wind curtailment cost for wind farm j.
The constraint conditions of the model are power grid constraint, conventional generator constraint and wind power plant constraint, and are as follows:
power balance constraint of system
Figure BDA00021783635800000410
In the formula, Pi,tThe output of a conventional unit i at the moment t, Pj,tIs the output of the wind farm j at the moment t, Pd,tThe load demand of node d at time t.
② safety constraint of power flow
Pl,min≤Pl,t≤Pl,max (11)
In the formula, Pl,tIs the active power of line l at time t, Pl,minAnd Pl,maxThe upper and lower power limits of line l.
Thirdly hot standby restraint
Figure BDA00021783635800000411
In the formula ui,tIs the start-stop state of the conventional unit i at the moment t,
Figure BDA00021783635800000412
reserving a spare for the wind turbine generator, wherein rho is a hot spare coefficient.
Output restraint of conventional unit
ui,tPi,min≤Pi≤ui,tPi,max (13)
In the formula ui,tIs the start-stop state of the conventional unit i at the moment t, Pi,minIs the minimum output, P, of the conventional unit at the moment ti,maxThe maximum output of the conventional unit at the time t.
Fifth, conventional unit climbing restraint
-Rd≤Pi,t-Pi,t-1≤Ru (14)
In the formula, RdAnd RuThe down/up climbing rate of the conventional unit.
Sixth, the start-stop time constraint of the conventional unit
Figure BDA0002178363580000051
Figure BDA0002178363580000052
Where TS and TO are the minimum off/on time.
Seventhly, the start-stop cost constraint of the conventional unit
Figure BDA0002178363580000053
Figure BDA0002178363580000054
In the formula, HiAnd JiIs the single start-up/shut-down cost of the conventional unit i.
Output constraint of wind power plant
Figure BDA0002178363580000055
In the formula, PjtThe output of the wind power plant j at the moment t,
Figure BDA0002178363580000056
the capacity of the wind power plant can be adjusted.
Ninthly wind farm regulation rate constraint
Figure BDA0002178363580000057
In the formula (I), the compound is shown in the specification,
Figure BDA0002178363580000058
for capacity regulation of wind farms, vjThe rate is adjusted for the wind farm.
Further, the solving model based on CPLEX and obtaining the scheduling scheme in step 5 are specifically as follows:
and (3) programming by using Matlab, and directly solving by using a commercial toolkit CPLEX because the problem is a hybrid integration planning problem to obtain the economic dispatching scheme of the electric power system based on the wind power active power control. Setting basic information and scenes such as grid structure, node parameters, line parameters, generator parameters and wind power plant parameters, and calculating a scheduling scheme of a power system scheduling model based on wind power active power control in the corresponding scene through a commercial CPELX solver. The scheduling scheme comprises the start-stop condition and the power output condition of the conventional unit and the wind power plant in each period.
Compared with the prior art, the invention has the following remarkable advantages: the method can perform economic optimization scheduling on the power system under the condition of considering the active power control of the fan, and solves the problem of high scheduling pressure of the traditional generator.
Drawings
FIG. 1 is a flow chart of a power system scheduling method based on wind power active power control according to the present invention.
Detailed Description
The invention discloses a power system dispatching method based on wind power active power control, which is used for carrying out economic dispatching on a power system on the basis of considering that wind power has certain dispatching capability and solving the problem of high dispatching pressure of a traditional generator. The method comprises the steps of firstly calculating the active power control capability of each wind turbine in the wind power plant, and calculating the power control capability of the whole wind power plant after calculation to quantitatively obtain the adjustable capacity of the wind power plant, the adjusting rate of the wind power plant and the reserve capacity of the wind power plant. And then, according to the quantified parameters, simulating a conventional generator set to construct a power system scheduling model based on wind power active power control. And solving the model by using CPLEX and obtaining an optimal scheduling scheme of the power system with optimal economy. The method can perform economic optimization scheduling on the power system under the condition of considering the active power control of the fan.
With reference to fig. 1, the method for scheduling a power system based on wind power active power control of the present invention includes the following specific steps:
step 1, calculating the active power control capability of each wind turbine in a wind power plant, specifically as follows:
and calculating three parameters of schedulable capacity, regulation rate and spare capacity of the single fan.
The adjustable capacity of the fan indicates that a single fan can actively participate in scheduling capacity, and a calculation formula is as follows:
Figure BDA0002178363580000061
in the formula, Pi,max,t+1Predicting the maximum power P of the wind turbine generator set i in the next periodi,tIs the output power P of the wind turbine generator i at the wind speed of the periodN,iThe rated power of the wind turbine generator i.
Secondly, the fan regulation rate is the embodiment of the regulation efficiency when a single fan participates in the scheduling, and the calculation formula is as follows:
Figure BDA0002178363580000062
in the formula,. DELTA.Pi,aThe power variation value of the wind turbine generator i in the a-th test is obtained; m is the total number of tests.
Thirdly, the spare capacity of the fan is the capacity which needs to be reserved when the single fan participates in scheduling, generally 5% of the adjustable capacity is taken, and the calculation formula is as follows:
Figure BDA0002178363580000063
in the formula,. DELTA.Pi *The adjustable capacity of the single fan is calculated by the formula (1).
Step 2, calculating the active participation scheduling capability of the wind power plant, specifically as follows:
and under the condition of the single fan parameter calculated according to the step one, calculating three parameters of the wind power plant.
The adjustable capacity of the wind power plant represents the active scheduling capacity of a single wind power plant, and the calculation formula is as follows:
Figure BDA0002178363580000071
in the formula, Pi,max,t+1Predicting the maximum power P of the wind turbine generator set i in the next periodi,tIs the output power P of the wind turbine generator i at the wind speed of the periodN,iIs the rated power of a wind turbine generator i, j represents the jth wind farm, njAnd the number of wind turbine sets in the wind power plant j is represented.
Secondly, the wind power plant regulation rate is the embodiment of regulation efficiency when a single wind power plant participates in scheduling, and the calculation formula is as follows:
Figure BDA0002178363580000072
in the formula,. DELTA.Pi,aIs the power variation value of the wind turbine generator i in the a-th test, m is the total number of tests, j represents the j-th wind power plant, njAnd the number of wind turbine sets in the wind power plant j is represented.
Thirdly, the spare capacity of the fan is the capacity which needs to be reserved when the single fan participates in scheduling, generally 5% of the adjustable capacity is taken, and the calculation formula is as follows:
Figure BDA0002178363580000073
in the formula,. DELTA.Pi *Capacity adjustable for a single fan, j denotes the jth wind farm, njAnd the number of wind turbine sets in the wind power plant j is represented.
Step 3, constructing related constraint conditions of the wind power plant, which are as follows:
compared with the conventional unit, two constraints of the output constraint of the wind power plant and the regulation rate constraint of the wind power plant are obtained.
Output constraint of wind power plant
Figure BDA0002178363580000074
In the formula, PtThe output of the wind power plant j at the moment t,
Figure BDA0002178363580000075
the capacity of the wind power plant can be adjusted.
Wind farm regulation rate constraint
Figure BDA0002178363580000076
In the formula (I), the compound is shown in the specification,
Figure BDA0002178363580000081
for capacity regulation of wind farms, vjThe rate is adjusted for the wind farm.
Step 4, constructing a power system scheduling model based on wind power active power control, which specifically comprises the following steps:
the model takes the economic optimization of system scheduling as a target, and the target function is as follows:
Figure BDA0002178363580000082
in the formula (I), the compound is shown in the specification,
Figure BDA0002178363580000083
and
Figure BDA0002178363580000084
respectively the start-stop cost of the conventional unit i,
Figure BDA0002178363580000085
in order to reduce the output cost of the conventional unit i,
Figure BDA0002178363580000086
for the output cost of the wind farm j,
Figure BDA0002178363580000087
the wind curtailment cost for wind farm j.
The constraint conditions of the model are power grid constraint, conventional generator constraint and wind power plant constraint, and are as follows:
power balance constraint of system
Figure BDA0002178363580000088
In the formula, Pi,tThe output of a conventional unit i at the moment t, Pj,tIs the output of the wind farm j at the moment t, Pd,tThe load demand of node d at time t.
② safety constraint of power flow
Pl,min≤Pl,t≤Pl,max (11)
In the formula, Pl,tIs the active power of line l at time t, Pl,minAnd Pl,maxThe upper and lower power limits of line l.
Thirdly hot standby restraint
Figure BDA0002178363580000089
In the formula ui,tIs the start-stop state of the conventional unit i at the moment t,
Figure BDA00021783635800000810
reserving a spare for the wind turbine generator, wherein rho is a hot spare coefficient.
Output restraint of conventional unit
ui,tPi,min≤Pi≤ui,tPi,max (13)
In the formula ui,tIs the start-stop state of the conventional unit i at the moment t, Pi,minIs the minimum output, P, of the conventional unit at the moment ti,maxThe maximum output of the conventional unit at the time t.
Fifth, conventional unit climbing restraint
-Rd≤Pi,t-Pi,t-1≤Ru (14)
In the formula, RdAnd RuThe down/up climbing rate of the conventional unit.
Sixth, the start-stop time constraint of the conventional unit
Figure BDA0002178363580000091
Figure BDA0002178363580000092
Where TS and TO are the minimum off/on time.
Seventhly, the start-stop cost constraint of the conventional unit
Figure BDA0002178363580000093
Figure BDA0002178363580000094
In the formula, HiAnd JiIs the single start-up/shut-down cost of the conventional unit i.
Output constraint of wind power plant
Figure BDA0002178363580000095
In the formula, Pj,tThe output of the wind power plant j at the moment t,
Figure BDA0002178363580000096
the capacity of the wind power plant can be adjusted.
Ninthly wind farm regulation rate constraint
Figure BDA0002178363580000097
In the formula (I), the compound is shown in the specification,
Figure BDA0002178363580000098
for capacity regulation of wind farms, vjThe rate is adjusted for the wind farm.
Step 5, solving the model based on CPLEX and obtaining a scheduling scheme, which comprises the following steps:
and (3) programming by using Matlab, and directly solving by using a commercial toolkit CPLEX because the problem is a hybrid integration planning problem to obtain the economic dispatching scheme of the electric power system based on the wind power active power control. Setting basic information and scenes such as grid structure, node parameters, line parameters, generator parameters and wind power plant parameters, and calculating a scheduling scheme of a power system scheduling model based on wind power active power control in the corresponding scene through a commercial CPELX solver. The scheduling scheme comprises the start-stop condition and the power output condition of the conventional unit and the wind power plant in each period.

Claims (5)

1. A power system scheduling method based on wind power active power control is characterized by comprising the following steps:
step 1, calculating the active power control capability of each wind turbine in a wind power plant; calculating the adjustable capacity, the adjustable speed and the fan reserve capacity of each wind turbine in the wind power plant; the adjustable capacity of the wind turbine generator is obtained by subtracting the maximum power at the predicted wind speed of the next period from the output power of the current period, the adjusting rate is obtained by summarizing the test power change rate, and the standby capacity of the fan is obtained by calculating five percent of the adjustable capacity;
step 2, calculating the active power control capability of the wind power plant; calculating the adjustable capacity, the adjusting rate and the wind field reserve capacity of the wind power plant, and summing the parameters calculated in the step 1 by all the fans in the wind power plant;
step 3, constructing related constraint conditions of the wind power plant; by analogy with the output constraint and the climbing rate constraint of a conventional unit, two constraint conditions of wind power plant output constraint and wind power plant regulation rate constraint are constructed by using two parameters of wind power plant regulation capacity and regulation rate; the output constraint of the wind power plant requires that the difference between the output power of the wind power plant in the next period and the output power of the wind power plant in the current period is smaller than the adjustable capacity of the wind power plant; the wind power plant regulation rate constraint requires that the regulation capacity of the wind power plant is smaller than the regulation rate;
step 4, constructing a power system scheduling model based on wind power active power control; this model targets the economic optimality of system scheduling, with costs including: the starting and stopping cost and the output cost of the conventional unit and the output cost and the wind abandoning cost of the wind power plant are reduced; the constraints of this model include: power balance constraint, power flow safety constraint, hot standby constraint, conventional unit output constraint, conventional unit climbing constraint, conventional unit start-stop time constraint, conventional unit start-stop cost constraint, wind power plant output constraint and wind power plant regulation rate constraint constructed in the step 3;
step 5, solving the model based on CPLEX and obtaining a scheduling scheme; setting basic information and scenes of a power grid, including a grid structure, node parameters, line parameters, generator parameters and wind power plant parameters, and calculating a scheduling scheme of a power system scheduling model based on wind power active power control in the corresponding scene through a CPELX solver; the scheduling scheme comprises the start-stop condition and the power output condition of the conventional unit and the wind power plant in each period.
2. The power system scheduling method based on wind power active power control according to claim 1, wherein the method for calculating the active power control capability of each wind turbine in the wind farm in step 1 specifically comprises the following steps:
three parameters of adjustable capacity of a fan, the adjustment rate of the fan and the spare capacity of the fan are used for representing the active power control capability of the fan;
the adjustable capacity of the fan indicates that a single fan can actively participate in scheduling capacity, and a calculation formula is as follows:
Figure FDA0002178363570000011
in the formula, Pi,max,t+1Predicting the maximum power P of the wind turbine generator set i in the next periodi,tIs the output power P of the wind turbine generator i at the wind speed of the periodN,iThe rated power of the wind turbine generator i;
secondly, the fan regulation rate is the embodiment of the regulation efficiency when a single fan participates in the scheduling, and the calculation formula is as follows:
Figure FDA0002178363570000021
in the formula,. DELTA.Pi,aThe power variation value of the wind turbine generator i in the a-th test is obtained; m is the total number of tests;
thirdly, the spare capacity of the fan is the capacity which needs to be reserved when the single fan participates in scheduling, 5% of the adjustable capacity is taken, and the calculation formula is as follows:
Figure FDA0002178363570000022
in the formula,. DELTA.Pi *The adjustable capacity of the single fan is calculated by the formula (1).
3. The power system scheduling method based on wind power active power control according to claim 1, wherein the calculation method for calculating the active power control capability of the wind farm in step 2 specifically comprises the following steps:
the adjustable capacity of the wind power plant represents the active scheduling capacity of a single wind power plant, and the calculation formula is as follows:
Figure FDA0002178363570000023
in the formula, Pi,max,t+1Predicting the maximum power P of the wind turbine generator set i in the next periodi,tIs the output power P of the wind turbine generator i at the wind speed of the periodN,iIs the rated power of a wind turbine generator i, j represents the jth wind farm, njRepresenting the number of wind turbine sets in the wind power plant j;
secondly, the wind power plant regulation rate is the embodiment of regulation efficiency when a single wind power plant participates in scheduling, and the calculation formula is as follows:
Figure FDA0002178363570000024
in the formula,. DELTA.Pi,aIs the power variation value of the wind turbine generator i in the a-th test, m is the total number of tests, j represents the j-th wind power plant, njRepresenting the number of wind turbine sets in the wind power plant j;
thirdly, the reserve capacity of the wind farm is the capacity which needs to be reserved when a single fan participates in scheduling, 5% of the adjustable capacity is taken, and the calculation formula is as follows:
Figure FDA0002178363570000031
in the formula,. DELTA.Pi *Capacity adjustable for a single fan, j denotes the jth wind farm, njAnd the number of wind turbine sets in the wind power plant j is represented.
4. The power system scheduling method based on wind power active power control according to claim 1, wherein the construction of the wind farm related constraint condition in step 3 is specifically as follows:
output constraint of wind power plant
Figure FDA0002178363570000032
In the formula, Pj,tThe output of the wind power plant j at the moment t,
Figure FDA0002178363570000033
capacity is adjustable for the wind farm;
wind farm regulation rate constraint
Figure FDA0002178363570000034
In the formula (I), the compound is shown in the specification,
Figure FDA0002178363570000035
for capacity regulation of wind farms, vjThe rate is adjusted for the wind farm.
5. The power system scheduling method based on wind power active power control according to claim 1, wherein the step 4 of constructing the power system scheduling model based on wind power active power control specifically comprises the following steps:
the model takes the economic optimization of system scheduling as a target, and the target function is as follows:
Figure FDA0002178363570000036
in the formula (I), the compound is shown in the specification,
Figure FDA0002178363570000037
and
Figure FDA0002178363570000038
respectively the start-stop cost of the conventional unit i,
Figure FDA0002178363570000039
in order to reduce the output cost of the conventional unit i,
Figure FDA00021783635700000310
for the output cost of the wind farm j,
Figure FDA00021783635700000311
the wind abandon cost of the wind power plant j;
the constraint conditions of the model are power grid constraint, conventional generator constraint and wind power plant constraint, and are as follows:
power balance constraint of system
Figure FDA00021783635700000312
In the formula, Pi,tThe output of a conventional unit i at the moment t, Pj,tIs the output of the wind farm j at the moment t, Pd,tThe load requirement of the node d at the moment t is represented;
② safety constraint of power flow
Pl,min≤Pl,t≤Pl,max (11)
In the formula, Pl,tIs the active power of line l at time t, Pl,minAnd Pl,maxThe upper and lower power limits of the line l;
thirdly hot standby restraint
Figure FDA0002178363570000041
In the formula ui,tIs the start-stop state of the conventional unit i at the moment t, Pi,maxThe maximum output of the conventional unit at the time t,
Figure FDA0002178363570000042
reserving a spare for the wind turbine generator, wherein rho is a hot spare coefficient.
Output restraint of conventional unit
ui,tPi,min≤Pi≤ui,tPi,max (13)
In the formula ui,tIs the start-stop state of the conventional unit i at the moment t, Pi,minIs the minimum output, P, of the conventional unit at the moment ti,maxThe maximum output of the conventional unit at the time t;
fifth, conventional unit climbing restraint
-Rd≤Pi,t-Pi,t-1≤Ru (14)
In the formula, RdAnd RuThe down/up climbing rate of the conventional unit;
sixth, the start-stop time constraint of the conventional unit
Figure FDA0002178363570000043
Figure FDA0002178363570000044
In the formula, TS and TO are minimum shutdown/startup time;
seventhly, the start-stop cost constraint of the conventional unit
Figure FDA0002178363570000045
Figure FDA0002178363570000046
In the formula, HiAnd JiThe cost of single start-up/shut-down of the conventional unit i;
output constraint of wind power plant
Figure FDA0002178363570000047
In the formula, Pj,tThe output of the wind power plant j at the moment t,
Figure FDA0002178363570000051
capacity is adjustable for the wind farm;
ninthly wind farm regulation rate constraint
Figure FDA0002178363570000052
In the formula (I), the compound is shown in the specification,
Figure FDA0002178363570000053
for capacity regulation of wind farms, vjIs windThe electric field regulates the rate.
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Citations (3)

* Cited by examiner, † Cited by third party
Publication number Priority date Publication date Assignee Title
CN102856925A (en) * 2012-09-03 2013-01-02 北京科诺伟业科技有限公司 Comprehensive power distribution method for wind power plant
CN106712075A (en) * 2016-04-26 2017-05-24 武汉大学 Peaking strategy optimization method considering safety constraints of wind power integration system
CN109284878A (en) * 2018-11-26 2019-01-29 武汉大学 Multi-source optimized scheduling method considering coordination of wind power, nuclear power and pumped storage

Patent Citations (3)

* Cited by examiner, † Cited by third party
Publication number Priority date Publication date Assignee Title
CN102856925A (en) * 2012-09-03 2013-01-02 北京科诺伟业科技有限公司 Comprehensive power distribution method for wind power plant
CN106712075A (en) * 2016-04-26 2017-05-24 武汉大学 Peaking strategy optimization method considering safety constraints of wind power integration system
CN109284878A (en) * 2018-11-26 2019-01-29 武汉大学 Multi-source optimized scheduling method considering coordination of wind power, nuclear power and pumped storage

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