CN111881576A - Optimal scheduling control method for heliostat field of solar tower-type photo-thermal power station - Google Patents

Optimal scheduling control method for heliostat field of solar tower-type photo-thermal power station Download PDF

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CN111881576A
CN111881576A CN202010730314.2A CN202010730314A CN111881576A CN 111881576 A CN111881576 A CN 111881576A CN 202010730314 A CN202010730314 A CN 202010730314A CN 111881576 A CN111881576 A CN 111881576A
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heliostat
establishing
coordinate system
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heat absorber
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CN111881576B (en
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赵鹏翔
王楠
李振
周喜超
杨佳霖
李娜
余强
尤东昶
王志峰
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State Grid Comprehensive Energy Service Group Co ltd
Institute of Electrical Engineering of CAS
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Institute of Electrical Engineering of CAS
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Abstract

A heliostat field optimal scheduling control method for a solar tower-type photothermal power station comprises the following steps: establishing a framework of a solar tower type photo-thermal power station model; establishing a modeling process of heliostat field condensation and optimized scheduling control of a solar tower type photo-thermal power station; establishing a mathematical model of the spliced reflecting surface; establishing a mirror reflection point and a sunlight cone model; establishing a direction and position model of a main incident ray; establishing a model of the direction and the position of the reflected light by using a coordinate transformation method; establishing a heliostat sun tracking motion model, counting the number of rays at different drop point positions, and calculating energy flow density distribution; establishing a tracking error model of the heliostat, and simulating the energy flow density distribution condition when tracking errors exist; establishing an optimized scheduling control model of the heliostat field; solving and obtaining an optimized scheduling control strategy by using a genetic algorithm; the method can accurately simulate the heliostat field condensation characteristics and the energy flux density distribution on the surface of the heat absorber, and can also homogenize the energy flux density on the surface of the heat absorber.

Description

Optimal scheduling control method for heliostat field of solar tower-type photo-thermal power station
Technical Field
The invention relates to a heliostat field condensation and optimal scheduling control modeling method for a solar tower type photo-thermal power station.
Background
The solar power generation has the characteristics of intermittence, fluctuation and randomness. The heliostat field focuses solar radiation energy to the central point of the heat absorber, so that high-temperature damage of the heat absorber or high-temperature decomposition of an internal heat transfer working medium is easily caused, and new challenges are brought to safe and stable operation of the solar tower type photo-thermal power station. The heliostat field condensing and optimal scheduling control modeling method for the solar tower type photo-thermal power station is researched, an efficient and reliable heliostat field optimal scheduling control model is established, and the method has important significance for efficient, stable and safe operation of the solar tower type photo-thermal power station.
Although the application scale of solar tower type photo-thermal power stations is gradually increasing, the optimal scheduling model of heliostat fields is not yet fully developed. In the operation process of the solar tower type photo-thermal power station, in order to solve the problem that a heliostat field and a heat absorber are contradictory to each other and improve the utilization rate of the heliostat field and the economic benefit of the tower type photo-thermal power station, optimal scheduling must be carried out on the heliostat field, the operation state of the heliostat field is scientifically and efficiently scheduled, and the operation requirement expected by people is met. An effective heliostat field scheduling strategy should take into account both energy and heat absorber safety factors, and focus solar radiation as much as possible on the premise of ensuring the heat absorber safety.
Currently, in the tower-type solar thermal power generation technology, the current research focuses on the collection efficiency and the high-efficiency heat storage technology of the solar concentrating system, the storage and transmission technology of the high-temperature heat transfer fluid and the like, but the research on the heliostat field optimization scheduling control which is crucial in the system becomes the technical bottleneck in the tower-type solar power station industry, and the large-scale development of the system is restricted.
Disclosure of Invention
In order to improve the economic benefit and the operation stability of the solar tower type photo-thermal power station, the invention provides a heliostat field optimization scheduling control method of the solar tower type photo-thermal power station based on a genetic algorithm.
In order to achieve the aim, the optimal scheduling control method for the heliostat field of the solar tower-type photothermal power station comprises the following steps:
step 1: establishing a frame structure of a model of the solar tower type photo-thermal power station;
step 2: establishing a modeling process of heliostat field condensation and optimized scheduling control of a solar tower type photo-thermal power station;
and step 3: establishing a mathematical model of a heliostat splicing type reflecting surface;
and 4, step 4: establishing heliostat mirror reflection points and a sunlight cone model;
and 5: establishing a direction and position model of a main incident ray;
step 6: establishing a model of the direction and the position of the reflected light by using a coordinate transformation method;
and 7: establishing a heliostat sun tracking motion model, counting the number of rays at different drop point positions, and calculating energy flow density distribution;
and 8: establishing a tracking error model of the heliostat, and simulating the energy flow density distribution condition when tracking errors exist;
and step 9: establishing an optimized scheduling control model of the heliostat field;
step 10: and solving the optimized scheduling control model by using a genetic algorithm to obtain an optimized scheduling control strategy.
In the step 1, the frame structure of the established model of the tower type photo-thermal power station comprises a ground coordinate system, a mirror surface coordinate system and a heat absorber coordinate system. And (3) establishing each coordinate system in the step (1) as a Cartesian right-handed system.
Ground coordinate system (X)g,Yg,Zg) The origin of (A) is the projection of the center of the heat absorption tower on the ground, XgThe positive direction of the axis is south and YgThe positive direction of the axis is east, ZgThe vertical ground of the shaft points skyward; mirror coordinate system (X)h,Yh,Zh) Is the geometric center of the mirror surface, XhAxis and YhThe plane formed by the axes being parallel to the plane of the mirror opening, XhThe axis being parallel to the horizontal plane, ZhThe axis is coincident with the normal of the origin point, and the direction is upward; absorber coordinate system (X)t,Yt,Zt) The origin of (A) is the geometric center of the heat absorber, the cavity type heat absorber is the geometric center of the opening plane of the heat absorber, and XtAxis parallel to YgAxial and in the same direction, YtAxis parallel to ZgAxial and directional being the same, ZtAxis parallel to XgThe axes and directions are the same.
In the step 2, the establishing of the modeling process of heliostat field condensation and optimal scheduling control of the solar tower-type photo-thermal power station comprises the following steps:
(1) analysis of the solar ray propagation path: respectively determining the light incidence direction, the light reflection direction and the light falling point position of each propagation path by using a method combining a Monte Carlo light ray tracing method and coordinate transformation;
(2) and adjusting the focusing position of the heliostat on the surface of the heat absorber by using an optimal scheduling control model, and calculating the energy flux density distribution on the surface of the heat absorber.
In the step 3, the established mathematical model of the spliced reflecting surface of the heliostat comprises a model of an ideal reflecting surface and a model of the spliced reflecting surface;
step 3-1: the model of the ideal reflecting surface is established as follows: the ideal reflecting surface is a part of a spherical surface, and the expression is as follows:
Figure BDA0002602948290000021
wherein R is the radius of the spherical surface, xs,h,ys,h,zs,hIs the coordinate of any point on the spherical surface;
step 3-2: the built spliced reflecting surface model is as follows: in the concatenation formula plane of reflection, all unit mirrors are the level crossing and constitute, the expression of single level crossing be:
xSa-c,h×(Xa-xa,h)+ySa-c,h×(Ya-ya,h)+zSa-c,h×(Za-za,h)＝0 (2)
wherein x isSa-c,h，ySa-c,h，zSa-c,hThe components of the vector of the normal direction of the unit plane mirror on the x, y and z axes are shown; x is the number ofa,h，ya,h，za,hThe geometric center point of the unit plane mirror; xa，Ya，ZaIs the coordinate of any point on the plane.
The ideal mirror surface is subjected to gridding treatment according to the size of the unit plane mirror, the central point of each grid is selected to be a tangent plane of a curved surface, the unit plane mirror is positioned on the tangent plane at the center of the grid, and all the unit plane mirrors are sequentially combined and spliced to approach the curved surface.
In the step 4, the method for establishing the mirror reflection point and the solar cone model comprises the following steps of obtaining the distribution of the solar cone on the reflecting surface of the parabolic heliostat and the distribution of the solar rays in the solar cone:
step 4-1: due to the sun-ground distance, the solar beams are in a non-parallel light cone form, and the positions of the solar light cones falling on the reflecting surfaces of the heliostats need to be selected at equal intervals on the reflecting surfaces of the heliostats;
step 4-2: the cone angle of the sunlight cone is 9.3mrad, the rays are randomly distributed in the sunlight cone, and the expression of the cone angle of the sunlight cone is as follows:
Figure BDA0002602948290000031
wherein R issRadius of the sun, Ds-eDistance between day and earth, χsThe cone angle of the solar cone.
The method for establishing the direction and position model of the main incident ray in the step 5 comprises the following steps:
step 5-1: establishing a ground coordinate system (X)g,Yg,Zg) Calculating the position of the sun;
the origin of the ground coordinate system is the projection of the center of the heat absorption tower on the ground, XgThe positive direction is south and YgThe positive direction is east, ZgThe vertical ground is directed skyward. The expression of the sun position in ground coordinates is:
zenith angle thetaZ：
θz＝arccos(coscosφcosω+sinsinφ) (4)
Azimuth angle gammas：
Figure BDA0002602948290000032
Step 5-2: establishing a direction vector of a main incident ray under a ground coordinate system;
the direction vector expression of the main incident ray in the sunlight cone under the ground coordinate is as follows:
Figure BDA0002602948290000033
Figure BDA0002602948290000041
wherein, the declination angle, omega is the solar hour angle, phi isGeographical latitude, α, at which the observer is locatedsIs the solar altitude angle and is the complementary angle of the zenith angle. x is the number ofi,g，yi,g，zi,gIs the position coordinate of the central ray of the sunlight cone under a Cartesian coordinate system,
Figure BDA0002602948290000042
is the direction vector of the main incident ray in the sunlight cone under the ground coordinate.
In the step 6, establishing the direction and position model of the reflected light by using a coordinate transformation method comprises the following steps:
step 6-1: establishing a mirror coordinate system (X)h,Yh,Zh) Transformation matrix T from ground coordinate system to mirror coordinate systemg-hAnd a transformation matrix T from the mirror coordinate system to the ground coordinate systemh-g；
Mirror coordinate system (X)h,Yh,Zh) Is the geometric center of the mirror surface, XhAxis and YhThe plane formed by the axes being parallel to the plane of the mirror opening, XhThe axis being parallel to the horizontal plane, ZhThe axis coincides with the origin normal, with the direction up.
Transformation matrix Tg-hThe expression of (a) is:
Figure BDA0002602948290000043
transformation matrix Th-gThe expression of (a) is:
Figure BDA0002602948290000044
wherein A isHAzimuth angle of heliostat, EHThe pitch angle of the heliostat.
Step 6-2, establishing a direction vector expression of the main reflection light in a ground coordinate system:
Figure BDA0002602948290000045
Figure BDA0002602948290000046
wherein, thetaHIs the azimuth angle of the heliostat, lambda is the included angle between the connecting line of the origin of the mirror coordinate system and the focus point of the heat absorber and the vertical direction, and xf,g,yf,g,zf,gIs the position coordinate of the main reflected light ray in a Cartesian coordinate system,
Figure BDA0002602948290000051
is the direction vector of the main reflected light ray in the sunlight cone under the ground coordinate.
In step 7, a heliostat sun tracking movement model is established, the number of light rays at different drop point positions is counted, and energy flux density distribution is calculated, wherein the method specifically comprises the following steps:
step 7-1: establishing a heliostat sun tracking motion model, wherein the operation model is expressed by the azimuth angle and the pitch angle of an ideal heliostat, and the expression is as follows:
ideal heliostat azimuth A'HComprises the following steps:
Figure BDA0002602948290000052
ideal heliostat pitch angle E'HComprises the following steps:
Figure BDA0002602948290000053
step 7-2: establishing a heat absorber coordinate system (X)t,Yt,Zt) Heat absorber height variation matrix TheightAnd a transformation matrix T from the ground coordinate system to the heat absorber coordinate systemg-t；
The origin of the heat absorber coordinate system is the geometric center of the heat absorber, XtAxis parallel to YgAxial and in the same direction, YtAxis parallel to ZgAxial and directional being the same, ZtAxis parallel to XgThe axes and directions are the same.
The expression of the heat absorber heating surface in the heat absorber coordinate system is as follows:
Figure BDA0002602948290000054
heat absorber height variation matrix TheightThe expression of (a) is:
Figure BDA0002602948290000055
transformation matrix T from ground coordinate system to heat absorber coordinate systemg-tThe expression of (a) is:
Figure BDA0002602948290000061
wherein x ist，yt，ztIs the coordinate of the focal point, Rrec,HrecRespectively the radius and height of the heat absorber, XQ,g，YQ,g，ZQ,gIs the position coordinate of the heliostat in the ground coordinate system, HtowerIs the height of the endothermic column.
And 7-3: counting the quantity of light rays at different drop point positions, and calculating energy flow density distribution, wherein the expression of the energy flow density distribution is shown as follows;
Figure BDA0002602948290000062
where Q is the fluence in the region, NtotThe number of rays in a certain region, S is the area of the region, and q is the energy of a single ray.
In the step 6 and the step 7, the directions of the incident light and the reflected light are calculated by adopting a coordinate transformation method.
In step 8, a tracking error model of the heliostat is established, and the distribution situation of energy flux density in the presence of tracking error is simulated, which is specifically described as follows:
the heliostat tracking error expression can be expressed by heliostat pitch angle offset and heliostat azimuth angle offset, and the expression is as follows:
heliostat pitch angle offset:
Figure BDA0002602948290000063
heliostat azimuth offset:
Figure BDA0002602948290000064
where ω is the direction of heliostat tracking error, f is heliostat focal length, dcen-hDistance of horizontal deviation of the center of the spot, dcen-vThe distance of the center of the light spot in the vertical direction is offset, and the lambda is the included angle between the connecting line of the original point of the mirror coordinate system and the focus point of the heat absorber and the vertical direction.
The expression for the actual pitch angle of the heliostat is:
EH＝E'H+ΔEH(18)
the expression for the actual azimuth angle of the heliostat is:
AH＝A'H+ΔAH(19)
wherein, E'H，A'HIdeal pitch and azimuth for the heliostat, EH,AHThe actual pitch and azimuth angles of the heliostat.
The step 9 of establishing an optimal scheduling control model of the heliostat field comprises the following specific steps:
step 9-1: the selection of the focus point position considers the size of an actual light spot and the truncation efficiency as large as possible, and the following heliostat focus point selection principle is designed:
(1) selecting the maximum effective range of a focusing point on the heated surface, and avoiding the edge part of the heat absorber to reduce the overflow of light spots;
(2) the distance between two adjacent focusing points is not less than the minimum distance capable of distinguishing the centers of the light spots of the heliostats in different subareas;
(3) and carrying out grid division in the effective range of the focus point, and selecting the central point of the grid as the focus point.
Step 9-2: based on the similarity between the contribution degree and the incident cosine of the heliostat at the same moment as a grouping standard, dividing the whole heliostat field into a plurality of sub-regions, and grouping the heliostats according to the following basic principle:
(1) the number of heliostats in each group cannot be different by more than 3;
(2) the heliostats of the same group should be adjacent in position;
step 9-3: considering an optimal heliostat field focusing strategy from the two aspects of the safety and the received energy of the heat absorber, the mathematical expression of the optimization target of the heliostat optimization scheduling control model is as follows:
f＝min (20)
the standard deviation of the lattice energy flux density on the surface of the heat absorber is expressed as follows:
Figure BDA0002602948290000071
n is the number of all grids, ωiAnd f is an optimization target of the heliostat optimization scheduling control model.
The constraint conditions for ensuring the safety of the heat absorber are as follows:
F≤F0(22)
wherein F is the actual maximum energy flux density on the heat sink; f0The maximum energy flow density that the heat absorber can bear;
the constraint conditions for ensuring the full use of the focusing energy are as follows:
ηint≤15％ (23)
ηintis the spill loss of the heliostat.
And 10, solving the heliostat optimal scheduling control model by adopting a genetic algorithm to obtain an optimal scheduling control strategy.
The genetic algorithm fitness function is represented as:
fsy＝C- (24)
wherein f issyIs an expression of a fitness function, a heat absorber surface gridThe standard deviation of fluence, C, is a sufficiently large, normal number.
The adaptive crossover probability is:
Figure BDA0002602948290000081
wherein f ismaxIs the maximum fitness value in the population, favgIs the mean fitness value of the population, fcFor greater fitness values in the two individuals to be crossed, pc1、pc2Is a constant between 0 and 1, and pc1＜pc2。
The adaptive mutation probability is:
Figure BDA0002602948290000082
wherein f ismaxIs the maximum fitness value in the population, favgIs the mean fitness value of the population, fmFitness value of the individual to whom the variation is made, pm1、pm2Is a constant between 0 and 1, and pm1＜pm2。
The coordinate systems in step 1 are all cartesian right-handed systems, and the directions of the coordinate axes are described in step 1 in detail.
Compared with the prior art, the invention has the beneficial effects that:
1) the heliostat field optimal scheduling control model is established by taking the uniform distribution of the energy flux density on the surface of the heat absorber of the solar tower type photo-thermal power station as a target, so that the safety performance of the heat absorber is improved, and the maximum received energy is ensured;
2) the spliced reflecting surface model established by the invention can well simulate the reflecting surface of an actual heliostat, and the simulated light spots are not different from the actual focusing light spots;
3) the modeling method can be widely applied to heliostat field optimization scheduling control analysis of various types of heat absorbers of the solar tower type photo-thermal power station, and has universal applicability.
Drawings
FIG. 1 is a coordinate system diagram of a solar tower type photo-thermal power station;
FIG. 2 is a modeling flow of heliostat field condensation and optimal scheduling control;
FIG. 3 is a schematic diagram of a tiled mirror creation;
FIG. 4 is a schematic view of a solar cone;
FIG. 5 is a schematic view of the sun position;
FIG. 6 is a schematic view of heliostat tracking error;
FIG. 7 is a schematic view of heliostat field optimized scheduling control focusing;
FIG. 8 is a schematic view of a heliostat field segment;
FIG. 9 is a flow chart of an adaptive genetic algorithm.
Detailed Description
The present invention will be described in further detail with reference to the accompanying drawings.
The invention discloses an optimization scheduling control modeling method for a heliostat field of a solar tower type photo-thermal power station, which is provided according to the requirements of energy and the safety performance of a heat absorber on the basis of researching heliostat field condensation analysis and heat absorber surface energy flux density distribution. The modeling method is based on an ideal mirror surface, and a spliced reflecting mirror surface is established; establishing solar incident light by adopting a Monte Carlo light ray tracing method, and simulating the distribution condition of the solar light rays on the reflecting surface of the heliostat; establishing corresponding Cartesian rectangular coordinate systems on a heat absorption tower, a heliostat and a heat absorber, determining the relation of each coordinate system by using a coordinate transformation method, accurately analyzing and calculating the directions of incident light and reflected light, determining the falling point position of the light on the surface of the heat absorber, and simulating the distribution of energy flux density on the surface of the heat absorber; and establishing a heliostat field optimization scheduling model according to the standard deviation of the energy flux density on the surface of the heat absorber, and adjusting the focusing state of the heliostat to ensure that the energy flux density on the surface of the heat absorber is uniformly distributed. The invention provides basic support and a platform for the research of heliostat field optimization scheduling of the solar tower-type photothermal power station.
The optimal scheduling control method for the heliostat field of the solar tower-type photothermal power station comprises the following steps of:
step 1: establishing a frame structure of a model of the solar tower type photo-thermal power station;
step 2: establishing a modeling process of heliostat field condensation and optimized scheduling control of a solar tower type photo-thermal power station;
and step 3: establishing a mathematical model of the spliced reflecting surface;
and 4, step 4: establishing a mirror reflection point and a sunlight cone model;
and 5: establishing a direction and position model of a main incident ray;
step 6: establishing a model of the direction and the position of the reflected light by using a coordinate transformation method;
and 7: establishing a heliostat sun tracking motion model, counting the number of rays at different drop point positions, and calculating energy flow density distribution;
and 8: establishing a tracking error model of the heliostat, and simulating the energy flow density distribution condition when tracking errors exist;
and step 9: establishing an optimized scheduling control model of the heliostat field;
step 10: and solving the optimized scheduling control model by using a genetic algorithm to obtain an optimized scheduling strategy.
In the step 1, a frame structure of a model of the solar tower-type photo-thermal power station is shown in fig. 1, and includes three parts, namely a ground coordinate system, a mirror coordinate system and a heat absorber coordinate system, and based on the ground coordinate system, the three coordinate systems can be converted by using an euler matrix. Ground coordinate system (X)g,Yg,Zg) The origin of (A) is the projection of the center of the heat absorption tower on the ground, XgThe positive direction of the axis is south and YgThe positive direction of the axis is east, ZgThe vertical ground of the shaft points skyward; mirror coordinate system (X)h,Yh,Zh) Is the geometric center of the mirror surface, XhAxis and YhThe plane formed by the axes being parallel to the plane of the mirror opening, XhThe axis being parallel to the horizontal plane, ZhThe axis is coincident with the normal of the origin point, and the direction is upward; absorber coordinate system (X)t,Yt,Zt) The origin of the heat absorber is the geometric center of the heat absorber, and the cavity type heat absorber is the geometric center of the opening plane of the heat absorber，XtAxis parallel to YgAxial and in the same direction, YtAxis parallel to ZgAxial and directional being the same, ZtAxis parallel to XgThe axes and directions are the same.
As shown in fig. 2, in step 2, the establishing of the modeling process of solar tower-type photothermal power station heliostat field condensation and optimal scheduling control includes the following steps: analyzing the propagation path of the solar rays; establishing a flow chart of an energy flow density simulation model; respectively determining the light incidence direction, the light reflection direction and the light falling point position of each propagation path by using a method combining a Monte Carlo light ray tracing method and coordinate transformation; and adjusting the focusing position of the heliostat on the surface of the heat absorber by using an optimal scheduling control model, and calculating the energy flux density distribution on the surface of the heat absorber.
As shown in fig. 3, in step 3, the method for establishing the mathematical model of the tiled reflecting surface includes: modeling of ideal reflecting surface and establishing ground coordinate system (X)g,Yg,Zg) The origin of the ground coordinate system is the projection of the center of the heat absorption tower on the ground, XgThe positive direction of the axis is south and YgThe positive direction of the axis is east, ZgThe axis is vertical to the ground and directed skyward. Mirror coordinate system (X)h,Yh,Zh) Is the geometric center of the mirror surface, XhAxis and YhThe plane formed by the axes being parallel to the plane of the mirror opening, XhThe axis being parallel to the horizontal plane, ZhThe axis coincides with the origin normal, with the direction up. Absorber coordinate system (X)t,Yt,Zt) The origin of (A) is the geometric center of the heat absorber, the cavity type heat absorber is the geometric center of the opening plane of the heat absorber, and XtAxis parallel to YgAnd in the same direction, YtAxis parallel to ZgAnd in the same direction, ZtAxis parallel to XgAnd the directions are the same.
Step 3-1: the ideal reflecting surface is established as a part of a spherical surface, and the expression is as follows:
Figure BDA0002602948290000101
wherein R is the radius of the spherical surface, xs,h,ys,h,zs,hIs the coordinate of any point on the spherical surface;
step 3-2: in the concatenation formula plane of reflection, all unit mirrors are the level crossing and constitute, the expression formula of unit mirror is:
xSa-c,h×(Xa-xa,h)+ySa-c,h×(Ya-ya,h)+zSa-c,h×(Za-za,h)＝0 (2)
wherein x isSa-c,h，ySa-c,h，zSa-c,hIs the normal direction vector, x, of the unit plane mirrora,h，ya,h，za,hThe geometric center point of the unit plane mirror; xa，Ya，ZaIs the coordinate of any point on the plane.
The ideal mirror surface is subjected to gridding treatment according to the size of the unit plane mirror, the central point of each grid is selected to be a tangent plane of a curved surface, the unit plane mirror is positioned on the tangent plane at the center of the grid, and all the unit plane mirrors are sequentially combined and spliced to approach the curved surface.
In the step 4, the established specular reflection point and solar cone model is as shown in fig. 4, and the establishment process of the specular reflection point and the solar cone model includes the following steps: and analyzing the distribution of the sunlight cone on the reflecting surface of the parabolic heliostat and the distribution of the sunlight in the sunlight cone.
Step 4-1: due to the sun-ground distance, the solar beams are in a non-parallel light cone form, and the positions of the light cones falling on the reflecting surface of the heliostat are selected at equal intervals on the reflecting surface;
step 4-2: the cone angle of the sunlight cone is 9.3mrad, the rays are randomly distributed in the sunlight cone, and the expression of the sunlight in the sunlight cone angle is as follows:
Figure BDA0002602948290000111
wherein R issRadius of the sun, Ds-eIs the distance between the day and the ground.
As shown in fig. 5, in step 5, establishing a direction and position model of the main incident ray includes the following steps: establishing a ground coordinate system, and calculating the position of the sun as shown in fig. 5; establishing a direction vector of a main incident ray under a ground coordinate system, which comprises the following steps:
step 5-1: establishing a ground coordinate system (X)g,Yg,Zg) The origin of the ground coordinate system is the projection of the center of the heat absorption tower on the ground, XgThe positive direction of the axis is south and YgThe positive direction of the axis is east, ZgThe axis is vertical to the ground and points to the sky, and the position of the sun is expressed in the ground coordinate as follows:
zenith angle thetaZ：
θz＝arccos(coscosφcosω+sinsinφ) (4)
Azimuth angle gammas：
Figure BDA0002602948290000112
Step 5-2: in the sunlight cone, the direction vector expression of the central ray under the ground coordinate is as follows:
Figure BDA0002602948290000113
wherein;
Figure BDA0002602948290000121
wherein, the declination angle, omega is the solar hour angle, phi is the geographical latitude of the observer, alphasIs the solar altitude angle and is the complementary angle of the zenith angle.
In the step 6, a coordinate transformation method is used for establishing a model of the direction and the position of the reflected light, and the method comprises the following steps:
step 6-1: establishing a mirror coordinate system (X)h,Yh,Zh) Transformation matrix T from ground coordinate system to mirror coordinate systemg-hAnd a transformation matrix T from the mirror coordinate system to the ground coordinate systemh-gThe origin of the mirror coordinate system is the geometric center of the mirror surface, XhAxis and YhThe plane formed by the axes being parallel to the plane of the mirror opening, XhThe axis being parallel to the horizontal plane, ZhAxis coincident with origin normal, direction up, matrix Tg-hThe expression of (a) is:
Figure BDA0002602948290000122
matrix Th-gThe expression of (a) is:
Figure BDA0002602948290000123
step 6-2, establishing a direction vector expression of the main reflection light in a ground coordinate system
Figure BDA0002602948290000124
Figure BDA0002602948290000125
Wherein, thetaHIs the azimuth angle of the heliostat, and lambda is the included angle between the connecting line of the origin of the mirror coordinate system and the focusing point of the heat absorber and the vertical direction.
In step 7, a heliostat sun tracking movement model is established, the number of light rays at different drop point positions is counted, and energy flux density distribution is calculated, which is specifically as follows:
step 7-1: establishing a heliostat sun tracking motion model, and calculating an ideal azimuth angle and an ideal pitch angle expression of the heliostat:
ideal azimuth angle of heliostat is A'H：
Figure BDA0002602948290000131
Ideal pitch angle E 'of heliostat'H：
Figure BDA0002602948290000132
Step 7-2: establishing a heat absorber coordinate system Xt,Yt,ZtHeight variation matrix T of heat absorberheightAnd a transformation matrix T from the ground coordinate system to the heat absorber coordinate systemg-tThe origin of the heat absorber coordinate system is the geometric center of the heat absorber, XtAxis parallel to YgAxial and in the same direction, YtAxis parallel to ZgAxial and directional being the same, ZtAxis parallel to XgThe axes and directions are the same. The expression of the heat absorber heating surface in the heat absorber coordinate system is as follows:
Figure BDA0002602948290000133
matrix TheightThe expression of (a) is:
Figure BDA0002602948290000134
matrix Tg-tThe expression of (a) is:
Figure BDA0002602948290000135
wherein x ist,ztIs a coordinate value of the focus point, Rrec,HrecIs the radius and height of the heat absorber, XQ,g,YQ,g,ZQ,gIs the position coordinate of the heliostat in the ground coordinate system, HtowerIs the height of the endothermic column.
And 7-3: counting the quantity of light rays at different drop point positions, and calculating the energy flow density distribution, wherein the expression of the energy flow density distribution is as follows:
Figure BDA0002602948290000141
where Q is the fluence of the region, NtotThe number of rays in a certain region, S is the area of the region, and q is the energy of a single ray.
In the step 8, a tracking error model of the heliostat is established, and the energy flow density distribution condition when tracking error exists is simulated, and a schematic diagram is shown in fig. 6.
The heliostat tracking error expression is as follows:
heliostat pitch angle offset:
Figure BDA0002602948290000142
heliostat azimuth offset:
Figure BDA0002602948290000143
where ω is the direction of heliostat tracking error, f is heliostat focal length, dcen-hDistance of horizontal deviation of the center of the spot, dcen-vIs the distance of the vertical offset of the center of the light spot.
The expression for the actual pitch angle of the heliostat is:
EH＝E'H+ΔEH(18)
the expression for the actual azimuth angle of the heliostat is:
AH＝A'H+ΔAH(19)
in step 9, the step of establishing the heliostat field optimal scheduling control model is as follows:
step 9-1: designing a heliostat focusing point selection principle, wherein a heliostat optimal scheduling focusing schematic diagram is shown in fig. 7, the selection of the focusing point position takes the size of an actual light spot and truncation efficiency as large as possible into consideration, and the following selection principle is designed:
(1) selecting the maximum effective range of a focusing point on the heated surface, and avoiding the edge part of the heat absorber to reduce the overflow of light spots;
(2) the distance between two adjacent focusing points is not less than the minimum distance which can distinguish the centers of the light spots of the heliostats in different subareas;
(3) and carrying out grid division in the effective range of the focus point and selecting the central point of the grid as the focus point.
Step 9-2: based on the similarity between the contribution degree and the incident cosine of the heliostat at the same moment as a grouping standard, the whole heliostat field is divided into a plurality of sub-regions, and a grouping schematic diagram is shown in fig. 8. The grouping of heliostats should follow the following basic principles:
(1) the number of heliostats in each group cannot be different by more than 3;
(2) the heliostats of the same group should be adjacent in position;
step 9-3: the optimal heliostat field focusing strategy is considered from two aspects of the safety and the received energy of the heat absorber, so the mathematical expression of the optimization objective function of the heliostat field optimization scheduling control model is as follows:
f＝min (20)
the standard deviation of the lattice energy flux density on the surface of the heat absorber is expressed as follows:
Figure BDA0002602948290000151
n is the number of all grids, ωiThe fluence of the ith grid, i is the number of the grid, and μ is the arithmetic mean of the fluence of all grids.
The constraint conditions for ensuring the safety of the heat absorber are as follows:
F≤F0(22)
wherein F is the actual maximum energy flux density on the heat sink; f0The maximum energy flow density that the heat absorber can bear;
the constraint conditions for ensuring the full use of the focusing energy are as follows:
ηint≤15％ (23)
ηintis the loss of spillage of the heliostat;
in the step 10: and (3) solving the heliostat field optimal scheduling control model by using a genetic algorithm to obtain an optimal scheduling strategy, wherein a flow chart of the genetic algorithm is shown in FIG. 9, and a fitness function of the genetic algorithm is represented as:
fsy＝C- (24)
wherein, the standard deviation of the lattice energy flux density on the surface of the heat absorber; c is a normal number.
The adaptive crossover probability is:
Figure BDA0002602948290000152
wherein f ismaxIs the maximum fitness value in the population, favgIs the mean fitness value of the population, fcFor greater fitness values in the two individuals to be crossed, pc1、pc2Is a constant between 0 and 1, and pc1＜pc2。
The adaptive mutation probability is:
Figure BDA0002602948290000161
wherein f ismaxIs the maximum fitness value in the population, favgIs the mean fitness value of the population, fmAs fitness value of the individual to be mutated, pm1、pm2Is a constant between 0 and 1, and pm1＜pm2。

Claims (11)

1. A heliostat field optimal scheduling control method for a solar tower-type photothermal power station is characterized by comprising the following steps: the method comprises the following steps:
step 1: establishing a frame structure of a solar tower type photo-thermal power station model; the frame structure of the solar tower type photo-thermal power station model comprises a ground coordinate system, a mirror surface coordinate system and a heat absorber coordinate system;
step 2: establishing a modeling process of heliostat field condensation and optimized scheduling control of a solar tower type photo-thermal power station;
and step 3: establishing a mathematical model of the spliced reflecting surface;
and 4, step 4: establishing a mirror reflection point and a sunlight cone model;
and 5: establishing a direction and position model of a main incident ray;
step 6: establishing a model of the direction and the position of the reflected light by using a coordinate transformation method;
and 7: establishing a heliostat sun tracking motion model, counting the number of rays at different drop point positions, and calculating energy flow density distribution;
and 8: establishing a tracking error model of the heliostat, and simulating the energy flow density distribution condition when tracking errors exist;
and step 9: establishing an optimized scheduling control model of the heliostat field;
step 10: and solving the optimized scheduling control model by using a genetic algorithm to obtain an optimized scheduling control strategy.
2. The heliostat field optimal scheduling control method of claim 1 wherein: all the coordinate systems established in the step 1 are Cartesian right-handed systems; in the frame structure of the model of solar tower-type photo-thermal power station, the ground coordinate system (X)g,Yg,Zg) The origin of (A) is the projection of the center of the heat absorption tower on the ground, XgThe positive direction of the axis is south and YgThe positive direction of the axis is east, ZgThe vertical ground of the shaft points skyward; mirror coordinate system (X)h,Yh,Zh) Is the geometric center of the mirror surface, XhAxis and YhThe plane formed by the axes being parallel to the plane of the mirror opening, XhThe axis being parallel to the horizontal plane, ZhThe axis is coincident with the normal of the origin point, and the direction is upward; absorber coordinate system (X)t,Yt,Zt) The origin of (A) is the geometric center of the heat absorber, the cavity type heat absorber is the geometric center of the opening plane of the heat absorber, and XtAxis parallel to YgAxial and in the same direction, YtAxis parallel to ZgAxial and directional being the same, ZtAxis parallel to XgThe axes and directions are the same.
3. The heliostat field optimal scheduling control method of claim 1 wherein: the step 2 of establishing a modeling process of heliostat field condensation and optimized scheduling control of the solar tower-type photo-thermal power station comprises the following steps: analyzing the propagation path of the solar rays; establishing a flow chart of an energy flow density simulation model; respectively determining the light incidence direction, the light reflection direction and the light falling point position of each propagation path by using a method combining a Monte Carlo light ray tracing method and coordinate transformation; and adjusting the focusing position of the heliostat on the surface of the heat absorber by using an optimal scheduling control model, and calculating the energy flux density distribution on the surface of the heat absorber.
4. The heliostat field optimized scheduling method of claim 1, wherein: the method for establishing the mathematical model of the spliced reflecting surface in the step 3 comprises the following steps: establishing a model of an ideal reflecting surface and a model of a spliced reflecting surface;
step 3-1: the model of the ideal reflecting surface is established as follows: the ideal reflecting surface is a part of a spherical surface, and the expression of the ideal reflecting surface is as follows:
Figure FDA0002602948280000021
wherein R is the radius of the spherical surface, xs,h，ys,h，zs,hIs the coordinate of any point on the spherical surface;
step 3-2: the built spliced reflecting surface model is as follows: in the concatenation formula plane of reflection, all unit mirrors are the level crossing and constitute, and the expression of its single level crossing is:
xSa-c,h×(Xa-xa,h)+ySa-c,h×(Ya-ya,h)+zSa-c,h×(Za-za,h)＝0 (2)
wherein x isSa-c,h，ySa-c,h，zSa-c,hIs the component of the normal direction vector of the unit plane mirror on the x, y and z axes, xa,h，ya,h，za,hThe coordinate of the geometric center point of the unit plane mirror is obtained; xa，Ya，ZaIs the coordinate of any point on the plane;
the ideal mirror surface is subjected to gridding treatment according to the size of the unit plane mirror, the central point of each grid is selected to be a tangent plane of a curved surface, the unit plane mirror is positioned on the tangent plane at the center of the grid, and all the unit plane mirrors are sequentially combined and spliced to approach the curved surface.
5. The heliostat field optimal scheduling control method of claim 1 wherein: the method for establishing the mirror reflection point and the solar cone model in the step 4 comprises the following steps: selecting the position of a sunlight cone on the reflecting surface of a parabolic heliostat, and the distribution of sunlight rays in the sunlight cone;
step 4-1: due to the sun-ground distance, the solar beams are in a non-parallel light cone form, and positions of the solar light cones falling on the reflecting surface are selected at equal intervals on the reflecting surface of the heliostat;
step 4-2: the cone angle of the sunlight cone is 9.3mrad, the rays are randomly distributed in the sunlight cone, and the expression of the cone angle of the sunlight cone is as follows:
Figure FDA0002602948280000022
wherein R issRadius of the sun, Ds-eDistance between day and earth, χsThe cone angle of the solar cone.
6. The heliostat field optimal scheduling control method of claim 1 wherein: the method for establishing the direction and position model of the main incident ray in the step 5 comprises the following steps: establishing a ground coordinate system and calculating the position of the sun; establishing a direction vector of a main incident ray under a ground coordinate system;
step 5-1: establishing a ground coordinate system (X)g,Yg,Zg) Ground coordinate system (X)g,Yg,Zg) The origin of (A) is the projection of the center of the heat absorption tower on the ground, XgThe positive direction is south and YgThe positive direction is east, ZgThe vertical ground is pointed to the sky, and the expression of the sun position under the ground coordinates is as follows:
zenith angle thetaZ：
θz＝arccos(coscosφcosω+sinsinφ) (4)
Azimuth angle gammas：
Figure FDA0002602948280000031
Step 5-2:in the sunlight cone, the direction vector expression of the central ray under the ground coordinate
Figure FDA0002602948280000032
Figure FDA0002602948280000033
Wherein, the declination angle, omega is the solar hour angle, phi is the geographical latitude of the observer, alphasIs the solar altitude angle and is the complementary angle of the zenith angle.
7. The heliostat field optimal scheduling control method of claim 1 wherein: the method for establishing the direction and position model of the reflected light by using the coordinate transformation method in the step 6 comprises the steps of establishing a mirror coordinate system and establishing the direction and position of the main reflected light;
step 6-1: establishing a mirror coordinate system (X)h,Yh,Zh) Transformation matrix T from ground coordinate system to mirror coordinate systemg-hAnd a transformation matrix T from the mirror coordinate system to the ground coordinate systemh-gThe origin of the mirror coordinate system is the geometric center of the mirror surface, XhAnd YhThe plane formed is parallel to the plane of the mirror opening, XhThe axis being parallel to the horizontal plane, ZhThe direction is upward and is coincident with the normal of the origin;
the transformation matrix of the ground coordinate system and the mirror coordinate system is Tg-hThe matrix Tg-hThe expression of (a) is:
Figure FDA0002602948280000034
the transformation matrix of the mirror coordinate system and the ground coordinate system is Th-gThe matrix Th-gThe expression of (a) is:
Figure FDA0002602948280000035
wherein E isHIs the ideal heliostat pitch angle, AHIs the azimuth of the ideal heliostat.
Step 6-2, establishing a direction vector expression of the main reflection light in a ground coordinate system
Figure FDA0002602948280000041
Figure FDA0002602948280000042
Wherein the content of the first and second substances,
Figure FDA0002602948280000043
is the principal reflected ray vector, xf,g，yf,g，zf,gThe components of the principal reflected ray vector in the x, y, z axes, θHIs the azimuth angle of the heliostat, and lambda is the included angle between the connecting line of the origin of the mirror coordinate system and the focusing point of the heat absorber and the vertical direction.
8. The heliostat field optimal scheduling control method of claim 1 wherein: step 7, establishing a heliostat sun tracking motion model, counting the number of rays at different drop point positions, and calculating the energy flux density distribution, wherein the method comprises the following steps:
step 7-1: establishing a heliostat sun tracking motion model, wherein the motion model is expressed by the azimuth angle and the pitch angle of an ideal heliostat as follows:
azimuth angle of ideal heliostat is A'H：
Figure FDA0002602948280000044
Pitch angle E 'of ideal heliostat'H：
Figure FDA0002602948280000045
Step 7-2: establishing a heat absorber coordinate system(Xt,Yt,Zt) Heat absorber height variation matrix TheightAnd a transformation matrix T from the ground coordinate system to the heat absorber coordinate systemg-tThe origin of the heat absorber coordinate system is the geometric center of the heat absorber, XtParallel to Yg，YtParallel to Zg，ZtParallel to XgAnd their directions are the same; the expression of the heat absorber heating surface in the heat absorber coordinate system is as follows:
Figure FDA0002602948280000046
the heat absorber height variation matrix TheightAnd a transformation matrix T from the ground coordinate system to the heat absorber coordinate systemg-tThe matrix TheightThe expression is as follows:
Figure FDA0002602948280000051
matrix Tg-tThe expression is as follows:
Figure FDA0002602948280000052
wherein, XQ,g,YQ,g,ZQ,gIs the position coordinate of the heliostat in the ground coordinate system, HtowerIs the height of the heat absorption tower;
and 7-3: counting the quantity of light rays at different drop point positions, and calculating energy flow density distribution, wherein the expression of the energy flow density distribution is shown as follows;
Figure FDA0002602948280000053
where θ is the incident angle of the central ray of the light cone, and R isrec、HrecIs the radius and height of the heat sink, NtotThe number of rays in a certain region, S is the area of the region, and q is the energy of a single ray.
9. The heliostat field optimal scheduling control method of claim 1 wherein: the tracking error model of the heliostat, which is established in the step 8, simulates the following energy flow density distribution condition when the tracking error exists;
the heliostat tracking error model is as follows:
heliostat pitch angle offset delta EH：
Figure FDA0002602948280000054
Heliostat azimuth offset Δ aH：
Figure FDA0002602948280000055
Where ω is the direction of heliostat tracking error, f is heliostat focal length, dcen-hDistance of horizontal deviation of the center of the spot, dcen-vThe distance of the center of the light spot in the vertical direction is offset, and the lambda is the included angle between the connecting line of the original point of the mirror coordinate system and the focus point of the heat absorber and the vertical direction.
The expression for the actual pitch angle of the heliostat with tracking error is:
EH＝E'H+ΔEH(18)
the expression for the actual azimuth angle of the heliostat with tracking error is:
AH＝A'H+ΔAH(19)
wherein E isH,AHRespectively, the actual pitch angle and azimuth angle of the heliostat.
10. The heliostat field optimal scheduling control method of claim 1 wherein: in the step 9, the method for establishing the optimal scheduling model of the heliostat field is as follows;
step 9-1: designing a heliostat focusing point selection principle; the selection of the focus point position considers the size of an actual light spot and the truncation efficiency as large as possible, and the selection principle of the heliostat focus point is as follows:
(1) selecting the maximum effective range of a focusing point on the heated surface, and avoiding the edge part of the heat absorber to reduce the overflow of light spots;
(2) the distance between two adjacent focusing points is not less than the minimum distance capable of distinguishing the centers of the light spots of the heliostats in different subareas;
(3) carrying out grid division in the effective range of the focus point, and selecting the central point of the grid as the focus point;
step 9-2: based on the similarity of the contribution degree and the incidence cosine of the heliostats at the same moment as a grouping standard, the whole heliostat field is divided into a plurality of sub-areas, and the basic principle of the heliostat grouping is as follows:
(1) the number of heliostats in each group cannot be different by more than 3;
(2) the heliostats of the same group should be adjacent in position;
step 9-3: the heliostat field focusing strategy is considered from the two aspects of the safety and the received energy of the heat absorber, so the mathematical expression of the optimization target of the optimal scheduling control model of the heliostat field is as follows:
f＝min (20)
the standard deviation of the lattice energy flux density on the surface of the heat absorber is expressed as follows:
Figure FDA0002602948280000061
n is the number of all grids, ωiThe fluence density of the ith grid is shown, i is the serial number of the grid, and mu is the arithmetic mean value of the fluence densities of all grids;
the constraint conditions for ensuring the safety of the heat absorber are as follows:
F≤F0(22)
wherein F is the actual maximum energy flux density on the heat sink; f0The maximum energy flow density that the heat absorber can bear;
the constraint conditions for ensuring the full use of the focusing energy are as follows:
ηint≤15％ (23)
ηintis the spill loss of the heliostat.
11. The heliostat field optimal scheduling control method of claim 1 wherein: in the step 10, the heliostat field optimal scheduling control strategy is solved by using a genetic algorithm, and the fitness function of the genetic algorithm is represented as:
fsy＝C- (24)
wherein, the standard deviation of the lattice energy flux density on the surface of the heat absorber; c is a normal number, fsyIs a genetic algorithm fitness function;
the adaptive crossover probability is:
Figure FDA0002602948280000071
wherein f ismaxIs the maximum fitness value in the population, favgIs the mean fitness value of the population, fcFor greater fitness values in the two individuals to be crossed, pc1、pc2Is a constant between 0 and 1, and pc1＜pc2，pcIs an adaptive crossover probability;
the adaptive mutation probability is:
Figure FDA0002602948280000072
wherein f ismaxIs the maximum fitness value in the population, favgIs the mean fitness value of the population, fmAs fitness value of the individual to be mutated, pm1、pm2Is a constant between 0 and 1, and pm1＜pm2，pmIs an adaptive mutation probability.
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