CN110707756A - Photothermal power station day-ahead peak regulation optimization control method for high-proportion wind power access power grid - Google Patents

Photothermal power station day-ahead peak regulation optimization control method for high-proportion wind power access power grid Download PDF

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CN110707756A
CN110707756A CN201910969181.1A CN201910969181A CN110707756A CN 110707756 A CN110707756 A CN 110707756A CN 201910969181 A CN201910969181 A CN 201910969181A CN 110707756 A CN110707756 A CN 110707756A
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thermal
photo
peak
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CN110707756B (en
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张尧翔
刘文颖
周强
夏鹏
汪宁渤
聂雅楠
赵龙
王方雨
黄蓉
张雨薇
王定美
许春蕾
张彦琪
冉忠
李宛齐
胡阳
朱丽萍
陈鑫鑫
李潇
郇悦
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State Grid Corp of China SGCC
North China Electric Power University
State Grid Gansu Electric Power Co Ltd
Electric Power Research Institute of State Grid Gansu Electric Power Co Ltd
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State Grid Corp of China SGCC
North China Electric Power University
State Grid Gansu Electric Power Co Ltd
Electric Power Research Institute of State Grid Gansu Electric Power Co Ltd
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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
    • 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
    • H02J3/48—Controlling the sharing of the in-phase component
    • 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
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    • Y02E—REDUCTION OF GREENHOUSE GAS [GHG] EMISSIONS, RELATED TO ENERGY GENERATION, TRANSMISSION OR DISTRIBUTION
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Abstract

The invention discloses a photothermal power station day-ahead peak regulation optimization control method for accessing high-proportion wind power into a power grid, and belongs to the field of power grid peak regulation control. The method comprises the following steps: reading the relevant information of various power supplies and loads; calculating active power output plans of various power supplies and loads; dividing peak shaving time periods according to different power grid peak shaving requirements; respectively establishing a photo-thermal down-peak regulation model and an up-peak regulation model at different peak regulation time periods; and solving the model to obtain an adjustment plan of the photo-thermal unit. The invention provides a photothermal power station day-ahead peak regulation optimization control method for accessing high-proportion wind power into a power grid, which improves the peak regulation capability of a system through coordinated scheduling of the photothermal power station, and further promotes the wind power consumption.

Description

Photothermal power station day-ahead peak regulation optimization control method for high-proportion wind power access power grid
Technical Field
The invention belongs to the field of active power coordination control of a new energy power system, and particularly relates to a day-ahead peak regulation optimization control method for a photo-thermal power station with high-proportion wind power accessed into a power grid.
Background
With the continuous growth of wind power in China, wind power occupies an important position in power supply structures in various regions in China. By the end of 2018, wind power of Gansu and Qinghai has become the first big power supply, and wind power of 19 provincial power grids such as Jibei and Mengdong has become the second big power supply. The rising of the wind power generation ratio aggravates the influence of the wind power random fluctuation characteristic on the power system, and improves the peak regulation requirement of the power system. However, due to the defect that a large-scale wind turbine generator of a northwest sending end power grid replaces a thermal power generating unit and an innate hydropower peak regulation unit, the system is seriously lack of peak regulation capability, and the consumption of wind power is restricted. Therefore, a new peak shaving power supply for a high-proportion wind power grid needs to be excavated.
The photo-thermal power generation is an important solar power generation form following the photovoltaic power generation, has an energy storage function naturally, can inhibit the influence of the random fluctuation of solar energy on the output, has good scheduling characteristics and peak regulation capability, has the regulation speed and depth superior to those of a conventional thermal power generating unit, and is a new energy power generation form capable of being scheduled and controlled. At present, the solar-thermal power generation is rapidly developed in China, the national energy agency plans to the end of 2020, and the solar-thermal installed capacity of China reaches 300 ten thousand kW. The method considers the excellent peak regulation capability of the future photo-thermal power station under large-scale construction, researches a system combined peak regulation control strategy of the photo-thermal power station, and is an effective measure for solving the problems of insufficient peak regulation capability and wind power absorption resistance of the existing high-proportion wind power grid.
The photo-thermal power station is higher in initial investment cost, the photo-thermal power station which is built at home and abroad at present is started later and is mostly in a test operation stage, and the control strategy and the operation mode of part of the photo-thermal power stations which run in a commercialized mode are also based on the optimized operation of the photo-thermal power station, and the peak regulation requirement of a power grid is not considered. In the aspect of academic research, few reports exist on the research of improving the peak load regulation requirement of a high-proportion wind power grid by utilizing a photo-thermal power station. According to the technical scheme, the method is based on the operation mechanism of a photo-thermal power station, the schedulability of a photo-thermal unit is researched, and a photo-thermal model for power grid scheduling is established. The literature proves that the peak regulation pressure of the thermal power generating unit can be relieved by the photo-thermal power generating unit, and the configuration method of the energy storage capacity of the photo-thermal power station is provided based on the proportional relation between the thermal power peak regulation cost and the photo-thermal energy storage capacity, so that the peak regulation cost of the system is effectively reduced. The photothermal peak regulation capability and the scheduling characteristic are researched in the literature, but the photothermal power station is not incorporated into power grid scheduling, and the peak regulation potential of the photothermal power station is not fully utilized.
Disclosure of Invention
Aiming at the defects of the prior art, the invention aims to provide a photo-thermal power station day-ahead peak regulation optimization control method for high-proportion wind power access to a power grid, which is used for solving the problem of insufficient peak regulation capacity of a high-proportion wind power access area and providing reference for power grid operation.
A photothermal power station day-ahead peak regulation optimization control method for accessing high-proportion wind power into a power grid comprises the following steps:
s1: reading the relevant information of various power supplies and loads;
s2: calculating the day-ahead active power output plans of various power supplies and loads;
s3: dividing peak shaving time periods according to different power grid peak shaving requirements;
s4: respectively establishing a photo-thermal down-peak regulation model and an up-peak regulation model at different peak regulation time periods;
s5: and solving the model to obtain a day-ahead output regulation plan of the photo-thermal unit.
The S1 includes the steps of:
s101: obtaining prediction information of day-ahead active output of wind turbine generator
Figure BDA0002231514510000021
Obtaining the active output prediction information before the day of load
Figure BDA0002231514510000022
Obtaining day-ahead active output prediction information of photo-thermal unit
Figure BDA0002231514510000023
Acquiring light field solar radiation information D of photo-thermal power stationt；
S102: and acquiring adjustment information of the thermal power generating unit and the photo-thermal unit, wherein the adjustment information comprises a unit climbing rate, unit output upper and lower limits and a photo-thermal unit energy storage upper limit.
The S2 includes the steps of:
s201: and determining the planned output of the load, the thermal power generating unit and the planned output of the wind power by taking the maximum wind power absorption as a target.
The S3 includes the steps of:
s301: dividing photo-thermal down-peak regulation time period, and comparing wind power to predict active power output
Figure BDA0002231514510000031
Wind power plan active power output
Figure BDA0002231514510000032
Will satisfy the inequality
Figure BDA0002231514510000033
That is, all the time intervals in which the wind curtailment phenomenon occurs are collectively called photo-thermal down-peak regulation time intervals which are marked as Tdown；
S302: the photothermal "peak-shaving" period is divided. Comparing load predicted power
Figure BDA0002231514510000034
And load plan power
Figure BDA0002231514510000035
Will satisfy the inequality
Figure BDA0002231514510000036
That is, all the time intervals during which the load loss phenomenon occurs are collectively called photothermal "peak-shaving" time intervals and are marked as Tup；
S303: the remaining period is divided. The rest time intervals are positioned in the time intervals outside the photothermal 'down peak regulation' time interval and the photothermal 'up peak regulation' time interval and are recorded as Tother。
The S4 includes the steps of:
s401: in the photo-thermal down-peak regulation period, a photo-thermal down-peak regulation control model is constructed with the maximum goal of consuming wind power and electric quantity;
s402: and in the photothermal peak-load-up period, constructing a photothermal peak-load-up model by taking the minimum load loss as a target.
The S5 includes the steps of:
s501, solving a photo-thermal down-peak regulation model and an up-peak regulation model to obtain the planned output of the photo-thermal power stationWind power output plan after photo-thermal participating peak shaving
Figure BDA0002231514510000038
Thermal power output plan
Figure BDA0002231514510000039
The invention provides a photothermal power station day-ahead peak regulation optimization control method for accessing high-proportion wind power into a power grid, which comprises the following steps of: reading the relevant information of various power supplies and loads; calculating active power output plans of various power supplies and loads; dividing peak shaving time periods according to different power grid peak shaving requirements; respectively establishing a photo-thermal down-peak regulation model and an up-peak regulation model according to different peak regulation requirements; and solving the model to obtain an adjustment plan of the photo-thermal unit. According to the method, the peak load regulation capacity of the system is improved, the load loss phenomenon of the system is reduced, and the wind power consumption is promoted by the coordinated dispatching of the optical and thermal power stations.
Drawings
The technical solution of the present invention is further described in detail by the accompanying drawings and embodiments.
FIG. 1 is a flow chart of a photo-thermal power station day-ahead peak regulation optimization control method for accessing high-proportion wind power into a power grid, provided by the invention;
FIG. 2 is a network diagram of an IEEE RTS-24 node test system in example 2 provided by the present invention;
FIG. 3 is example 2 wind farm day-ahead active contribution prediction information provided by the present invention;
FIG. 4 is the active power output prediction information of the optical thermal power station in the past day of example 2 provided by the present invention;
FIG. 5 is the predicted information of the optical thermal power station in light field of solar radiation day ahead in example 2 provided by the present invention;
FIG. 6 is the load day ahead active power output prediction information provided by the present invention in example 2;
FIG. 7 is a graph of photothermal participation with pre-peak load pre-day output schedule in example 2 provided by the present invention;
FIG. 8 is a thermal power plant day-ahead output plan prior to peak shaver participation in example 2 provided by the present invention;
FIG. 9 is a day-ahead output plan for a wind turbine before peak shaving with photothermal participation in example 2 provided by the present invention;
FIG. 10 is a pre-photothermal output plan for example 2 provided by the present invention;
FIG. 11 is a wind turbine day-ahead power plan after photothermal participation peak shaving in example 2 provided by the present invention.
Detailed Description
In order to clearly understand the technical solution of the present invention, a detailed structure thereof will be set forth in the following description. It is apparent that the specific implementation of the embodiments of the present invention is not limited to the specific details familiar to those skilled in the art. Exemplary embodiments of the invention are described in detail below, and other embodiments in addition to those described in detail are possible.
The present invention will be described in further detail with reference to the accompanying drawings and examples.
Example 1
FIG. 1 is a flow chart of a photo-thermal power station day-ahead peak regulation optimization control method for high-proportion wind power access to a power grid. In fig. 1, a flow chart of a photo-thermal power station day-ahead peak regulation optimization control method for accessing high-proportion wind power into a power grid provided by the invention comprises the following steps:
s1: reading the relevant information of various power supplies and loads;
s2: calculating the day-ahead active power output plans of various power supplies and loads;
s3: dividing peak shaving time periods according to different power grid peak shaving requirements;
s4: respectively establishing a photo-thermal down-peak regulation model and an up-peak regulation model at different peak regulation time periods;
s5: and solving the model to obtain a day-ahead output regulation plan of the photo-thermal unit.
The S1 includes the steps of:
s101: obtaining prediction information of day-ahead active output of wind turbine generator
Figure BDA0002231514510000051
Obtaining the active output prediction information before the day of load
Figure BDA0002231514510000052
Obtaining day-ahead active output prediction information of photo-thermal unit
Figure BDA0002231514510000053
Acquiring light field solar radiation information D of photo-thermal power stationt；
S102: and acquiring adjustment information of the thermal power generating unit and the photo-thermal unit, wherein the adjustment information comprises a unit climbing rate, unit output upper and lower limits and a photo-thermal unit energy storage upper limit.
The S2 includes the steps of:
s201: the regulation capacity of the thermal power generating unit is fully utilized, the maximum wind power consumption is the planned output of the target determined load, the planned output of the thermal power generating unit and the wind power, and the target function is as follows:
Figure BDA0002231514510000054
in the formula:
Figure BDA0002231514510000061
the planned output force at the moment t of the load is obtained;planning output for the wind power at the time t; n is a radical ofTHThe number of thermal power generating units; n is a radical ofCSPThe number of photo-thermal units;
Figure BDA00022315145100000611
and (4) outputting the planned output of the thermal power generating unit i at the moment t.
The constraint conditions comprise system power balance constraint, thermal power unit output constraint, wind power unit output constraint and system standby constraint, and specifically comprise the following steps:
1) system constraints
① power balance constraints
Figure BDA0002231514510000062
② rotating for standby
Figure BDA0002231514510000063
In the formula:
Figure BDA00022315145100000612
is the starting and stopping state of the thermal power generating unit i at the moment t,
Figure BDA00022315145100000614
indicating that the thermal power generating unit is in an operating state,
Figure BDA00022315145100000613
indicating that the thermal power generating unit is in a shutdown state; piTH，max，PiTH，minRespectively the maximum and minimum active output of the thermal power generating unit;
Figure BDA0002231514510000064
respectively for coping with system load at time tPositive and negative rotation required by the load prediction error is reserved;
Figure BDA0002231514510000065
and respectively providing positive and negative rotation standby for the wind turbine generator at the moment t.
2) Thermal power generating unit operation constraint condition
① upper and lower limit constraints of output power
Figure BDA0002231514510000066
② minimum on-off time constraint
Figure BDA0002231514510000067
In the formula:
Figure BDA0002231514510000068
respectively representing the shutdown time and the running time of the thermal power generating unit i at the moment t;
Figure BDA0002231514510000069
Figure BDA0002231514510000071
the shortest downtime and the shortest running time of the unit i are respectively
③ ramp rate constraints
3) Wind power operation constraint condition
S202: solving the models (4) - (10) to obtain a thermal power unit output plan
Figure BDA0002231514510000078
Wind turbine output plan
Figure BDA0002231514510000079
And load contribution planning
Figure BDA00022315145100000710
The S3 includes the steps of:
s301: dividing photo-thermal down-peak regulation time period, and comparing wind power to predict active power outputActive power output of wind power plan
Figure BDA0002231514510000077
Will satisfy the inequality
Figure BDA0002231514510000076
That is, all the time intervals in which the wind curtailment phenomenon occurs are collectively called photo-thermal down-peak regulation time intervals which are marked as Tdown；
S302: the photothermal "peak-shaving" period is divided. Comparing load predicted power
Figure BDA00022315145100000711
And load plan power
Figure BDA00022315145100000712
Will satisfy the inequality
Figure BDA00022315145100000713
That is, all the time intervals during which the load loss phenomenon occurs are collectively called photothermal "peak-shaving" time intervals and are marked as Tup；
S303: the remaining period is divided. The rest time intervals are positioned in the time intervals outside the photothermal 'down peak regulation' time interval and the photothermal 'up peak regulation' time interval and are recorded as Tother。
The S4 includes the steps of:
s401: the maximum of the electric quantity of the wind power consumed in the photo-thermal down-peak regulation time period is the photo-thermal down-peak regulation control model constructed by the target, and the target function is as follows:
Figure BDA0002231514510000074
in the formula:
Figure BDA00022315145100000714
planning output for the thermal power generating unit;
Figure BDA00022315145100000715
the planned output of the photothermal unit i at the time t is taken as a model decision variable;
and the constraint conditions of the 'down peak regulation' model are added with the constraint conditions of the photo-thermal unit on the basis of (5) - (10), and comprise 'down peak regulation' constraint and photo-thermal energy storage constraint of the photo-thermal unit. The photo-thermal unit constraint under different technical implementation forms is slightly different, and the photo-thermal unit constraint conditions are tower photo-thermal unit constraint conditions.
① lower limit of output power constraint of photo-thermal power station
Figure BDA0002231514510000081
In the formula:
Figure BDA0002231514510000085
starting and stopping state variables of the photothermal unit i at the time t; piCSP，minThe lower limit of output of the photo-thermal unit i.
② light-heat power generation system down climbing restraint
In the formula: piCSP，downThe maximum downward climbing output in unit time interval of the photo-thermal unit i.
③ Heat storage System Capacity constraints
The photothermal thermal storage system thermal storage capacity constraint is expressed in "full-load hours (FLH)". For example, the heat storage capacity of a typical photovoltaic plant is 15FLH, which represents the ability of the photovoltaic plant to operate at full capacity for 15 hours without light. The constraint expression is as follows:
Figure BDA0002231514510000083
in the formula: qiCSP，minThe minimum heat storage quantity of the heat storage system of the photo-thermal unit i is stored; rhoiThe number of hours of full-load operation of the photo-thermal unit i is set;
Figure BDA0002231514510000086
the heat storage amount of the heat storage system of the photo-thermal unit i at the time t is measured.
The expression of the relation between the heat storage capacity of the heat storage system of the photo-thermal power station and the output of the photo-thermal power station is as follows:
Figure BDA0002231514510000084
in the formula:
Figure BDA0002231514510000087
the heat storage amount of the heat storage system of the photo-thermal power station i at the time t-1 is obtained;the heat transfer power flowing to the heat storage system for the solar energy light field;
Figure BDA0002231514510000094
thermal power for generating electricity for a photo-thermal power station; etaSTThe solar energy light field and the heat storage system light-heat conversion efficiency; etaTEThe heat-electricity conversion efficiency from the heat storage system to the power generation system; sSFIs the area of the light field; dtSolar direct radiation index (DNI) at time t.
S402: the photothermal 'peak-up' model is constructed by taking the minimum load loss in the photothermal 'peak-up' period as a target, and the target function is as follows:
Figure BDA0002231514510000091
compared with the constraint condition of the 'down peak regulation' model, the photo-thermal 'up peak regulation' model constraint condition is added.
① upper limit of output constraint of photothermal power station
Figure BDA0002231514510000092
In the formula:
Figure BDA0002231514510000095
starting and stopping state variables of the photothermal unit i at the time t; piCSP，maxThe upper limit of output of the photothermal unit i is set;
Figure BDA0002231514510000096
for photothermal unit i at time t
Figure BDA0002231514510000097
Active power output.
② climbing restraint on photo-thermal power generation system
Figure BDA0002231514510000093
In the formula: piCSP，upThe maximum upward climbing output in unit time interval of the photo-thermal unit i.
The S5 includes the steps of:
s501, solving a photo-thermal down-peak regulation model and an up-peak regulation model to obtain the day-ahead planned output of the photo-thermal power station
Figure BDA0002231514510000098
Wind power output plan after photo-thermal participating peak shaving
Figure BDA0002231514510000099
Thermal power output plan
Figure BDA00022315145100000910
Example 2
Fig. 2 is a modified IEEE RTS-24 node test system, and taking this as an example, the method for peak shaving optimization control day ahead of a photothermal power station with high-ratio wind power accessed to a power grid provided by the present invention:
s1: reading the relevant information of various power supplies and loads;
(1) in a regional power grid, the rated power of a wind power cluster is 450MW, the rated power of a thermal power unit is 800MW, the rated power of a photothermal power unit is 100MW, the prediction information of the day-ahead active power output of wind power is shown in figure 3, the prediction information of the day-ahead active power output of photothermal power is shown in figure 4, and the solar radiation information D of the light field of the photothermal power stationtAs shown in fig. 5, the active power output prediction information before the load day is shown in fig. 6.
(2) Regulatory information for conventional thermal power generating units
Figure BDA0002231514510000101
(3) Photothermal power station information
Bus numbering 10
Upper limit of output P of photothermal power stationiCSP，max/MW 100
Lower limit of output P of photo-thermal power stationiCSP，min/MW 20
Photo-thermal power station energy storage full load operation hours rhoi/FLH 10
Ramp rate of photo-thermal power station unit/MW·min -1 9
Thermoelectric conversion efficiency ηTE/％ 40
Efficiency of photothermal conversion etaST/％ 50
Solar light field area SSF/m2 1.5*106
S2: calculating the day-ahead active power output plans of various power supplies and loads;
and solving the models (5) - (11) to obtain a load output plan as shown in the figure 7, a thermal power generating unit output plan as shown in the figure 8 and a wind power output plan as shown in the figure 9. Before the photo-thermal peak regulation, the wind power is 1966.87MWh, and the load loss power is 23.46MWh
S3: the peak shaving time periods are divided according to the peak shaving requirements of the power grid and according to the peak shaving requirements of different power grids, and the results are shown in the following table.
Figure BDA0002231514510000111
S4: respectively establishing a photo-thermal down-peak regulation model and an up-peak regulation model at different peak regulation time periods;
s5: and solving the model to obtain an adjustment plan of the photo-thermal unit as shown in the attached drawing 10, a day-ahead wind power output plan after photo-thermal participation in peak shaving control as shown in the attached drawing 11, and a load day-ahead power output plan as shown in the attached drawing 11. The increased wind power consumption and the loss load result are compared as shown in the following table, 5.1 percent of abandoned wind power quantity is reduced, and the loss load power quantity is reduced to 0, thus proving the effectiveness of the method
Wind power/MWh Loss of load electric quantity/MWh
Before peak regulation by light and heat 1966.87 23.46
After photo-thermal peak regulation 1866.44 0
Reducing the amount of electricity 100.43 23.46
Finally, it should be noted that: although the present invention has been described in detail with reference to the above embodiments, those skilled in the art can make modifications and equivalents to the specific embodiments of the invention without departing from the spirit and scope of the invention, which is set forth in the claims appended hereto.

Claims (6)

1. A photothermal power station day-ahead peak regulation optimization control method for accessing high-proportion wind power into a power grid comprises the following steps:
s1: reading the relevant information of various power supplies and loads;
s2: calculating the day-ahead active power output plans of various power supplies and loads;
s3: dividing peak shaving time periods according to different power grid peak shaving requirements;
s4: respectively establishing a photo-thermal down-peak regulation model and an up-peak regulation model at different peak regulation time periods;
s5: and solving the model to obtain a day-ahead output regulation plan of the photo-thermal unit.
2. The photothermal power station peak load regulation optimization control method of the high-proportion wind power access power grid as claimed in claim 1, wherein said S1 comprises the following steps:
s101: obtaining prediction information of day-ahead active output of wind turbine generator
Figure FDA0002231514500000012
Obtaining the active output prediction information before the day of load
Figure FDA0002231514500000014
Obtaining day-ahead active output prediction information of photo-thermal unit
Figure FDA0002231514500000013
Acquiring light field solar radiation information D of photo-thermal power stationt；
S102: and acquiring adjustment information of the thermal power generating unit and the photo-thermal unit, wherein the adjustment information comprises a unit climbing rate, upper and lower unit output limits and an upper photo-thermal power station energy storage limit.
3. The photothermal power station peak load regulation optimization control method of the high-proportion wind power access power grid as claimed in claim 1, wherein said S2 comprises the following steps:
s201: the method fully utilizes the adjusting capability of the thermal power generating unit, determines the day-ahead planned output of the thermal power generating unit, the wind power generating unit and the load by taking the maximum wind power absorption as a target, and has the following objective function:
Figure FDA0002231514500000011
in the formula:the planned output force at the moment t of the load is obtained;
Figure FDA0002231514500000017
planning output for the wind power at the time t; n is a radical ofTHThe number of thermal power generating units; n is a radical ofCSPThe number of photo-thermal units;
Figure FDA0002231514500000016
planned output of the thermal power generating unit i at the moment t is achieved;
s202: and solving the model to obtain the planned output of the thermal power generating unit, the planned output of the wind power generating unit and the planned output of the load.
4. The photothermal power station peak load regulation optimization control method of the high-proportion wind power access power grid as claimed in claim 1, wherein said S3 comprises the following steps:
s301: dividing photo-thermal down-peak regulation time period, and comparing wind power to predict active power output
Figure FDA0002231514500000023
Wind power plan active power output
Figure FDA0002231514500000024
Will satisfy the inequality
Figure FDA0002231514500000025
That is, all the time intervals in which the wind curtailment phenomenon occurs are collectively called photo-thermal down-peak regulation time intervals which are marked as Tdown；
S302: dividing a photo-thermal up-peak regulation time period; comparing load predicted power
Figure FDA0002231514500000028
And load plan power
Figure FDA0002231514500000027
Will satisfy the inequality
Figure FDA0002231514500000026
That is, all the time intervals during which the load loss phenomenon occurs are collectively called photothermal "peak-shaving" time intervals and are marked as Tup；
S303: dividing the rest time period; the rest time intervals are positioned in the time intervals outside the photothermal 'down peak regulation' time interval and the photothermal 'up peak regulation' time interval and are recorded as Tother。
5. The photothermal power station peak load regulation optimization control method of the high-proportion wind power access power grid as claimed in claim 1, wherein said S4 comprises the following steps:
s401: in the photo-thermal down-peak regulation time period, a photo-thermal down-peak regulation control model is constructed by taking the maximum consumption wind power quantity as a target, and the target function is as follows:
in the formula:
Figure FDA0002231514500000029
planning output for the thermal power generating unit;the planned output of the photothermal unit i at the time t is taken as a model decision variable;
s402: in the photo-thermal peak-shaving period, a photo-thermal peak-shaving model is constructed by taking the minimum load loss as a target, and the target function is as follows:
Figure FDA0002231514500000022
6. the photothermal power station peak load regulation optimization control method of the high-proportion wind power access power grid as claimed in claim 1, wherein said S5 comprises the following steps:
s501, solving a photo-thermal down-peak regulation model and an up-peak regulation model to obtain the day-ahead planned output of the photo-thermal power station
Figure FDA0002231514500000033
Wind power output plan after photo-thermal participating peak shaving
Figure FDA0002231514500000031
Thermal power output plan
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