CN112987802B - Photovoltaic power generation method and device, electronic equipment and storage medium - Google Patents
Photovoltaic power generation method and device, electronic equipment and storage medium Download PDFInfo
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- G—PHYSICS
- G05—CONTROLLING; REGULATING
- G05D—SYSTEMS FOR CONTROLLING OR REGULATING NON-ELECTRIC VARIABLES
- G05D3/00—Control of position or direction
- G05D3/12—Control of position or direction using feedback
- G05D3/20—Control of position or direction using feedback using a digital comparing device
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- G05F—SYSTEMS FOR REGULATING ELECTRIC OR MAGNETIC VARIABLES
- G05F1/00—Automatic systems in which deviations of an electric quantity from one or more predetermined values are detected at the output of the system and fed back to a device within the system to restore the detected quantity to its predetermined value or values, i.e. retroactive systems
- G05F1/66—Regulating electric power
- G05F1/67—Regulating electric power to the maximum power available from a generator, e.g. from solar cell
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- Y02E—REDUCTION OF GREENHOUSE GAS [GHG] EMISSIONS, RELATED TO ENERGY GENERATION, TRANSMISSION OR DISTRIBUTION
- Y02E10/00—Energy generation through renewable energy sources
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- Y02E10/56—Power conversion systems, e.g. maximum power point trackers
Abstract
The application discloses a photovoltaic power generation method, a photovoltaic power generation device, electronic equipment and a storage medium, wherein the method comprises the following steps: determining the motion track of the sun and the relative position information between the sun and the photovoltaic power station; dividing time intervals by using the illumination intensity and the change rate as extraction factors through a time domain search and double-layer cluster analysis method; determining parameter ranges of the adjustment angle and the frequency of the photovoltaic power generation equipment based on the relation between the operation energy consumption of the photovoltaic power generation equipment of the photovoltaic power generation station and the economic benefits brought by the adjustment angle and the frequency; determining a variable time interval according to equipment information and meteorological information of an illumination sensor, and optimizing the variable time interval in real time by a self-adaptive dynamic programming method; and adjusting the parameter ranges of the adjustment angle and the frequency of the photovoltaic power generation equipment in a rolling optimization mode based on the optimized variable time interval. The application can reduce the difficulty of tracking control on the solar light variable frequency and improve the accuracy of control.
Description
Technical Field
The present disclosure relates to the field of solar power generation technologies, and in particular, to a photovoltaic power generation method, a photovoltaic power generation device, an electronic device, and a storage medium.
Background
The solar panel is used as a device capable of absorbing solar heat radiation energy, and the radiation energy is directly or indirectly converted into electric energy through a photoelectric effect or a photochemical effect. In consideration of feasibility of practical large-scale photovoltaic power generation equipment application of photovoltaic power generation stations, a fixed-step tracking control method is generally adopted, namely a fixed-step (fixed-time and fixed-time starting) method is adopted to track the running track of the sun, and the angle of the solar panel is adjusted according to the tracked track. However, the step length of the method cannot be adjusted in real time, so that tracking delay is caused in some time periods with a high sun running speed, and unnecessary resource waste is caused.
In the process of implementing the embodiments of the present disclosure, it is found that at least the following problems exist in the related art:
in the related art, the solar light variation frequency is tracked and controlled to save energy consumption, but the control difficulty is increased, and the control accuracy is lower.
In view of the above problems, no effective solution has been proposed.
Disclosure of Invention
In order to solve the technical problems, the application provides a photovoltaic power generation method, a photovoltaic power generation device, an electronic device and a storage medium, and solves the technical problems that the control difficulty and the control accuracy are high in the related art of tracking and controlling the solar light variation frequency.
In a first aspect, the present application provides a method of photovoltaic power generation, the method comprising the steps of:
determining the motion track of the sun and the relative position information between the sun and the photovoltaic power station;
dividing time intervals by using the illumination intensity and the change rate as extraction factors through a time domain search and double-layer clustering analysis method;
determining parameter ranges of the adjustment angle and the frequency of the photovoltaic power generation equipment based on the relation between the operation energy consumption of the photovoltaic power generation equipment of the photovoltaic power generation station and the economic benefits brought by the adjustment angle and the frequency;
determining a variable time interval according to equipment information and meteorological information of an illumination sensor, and optimizing the variable time interval in real time by a self-adaptive dynamic programming method;
and adjusting the parameter ranges of the adjustment angle and the frequency of the photovoltaic power generation equipment in a rolling optimization mode based on the optimized variable time interval.
In some embodiments, determining the trajectory of the sun and the relative position information between the sun and the photovoltaic power plant comprises:
collecting ephemeris information of the photovoltaic power station through a GPS system;
determining the geographic coordinate position and standard time of the solar power generation system according to the relation between the solar motion track and the earth;
and converting the motion trail of the sun and the relative position information between the sun and the photovoltaic power station based on the relation between the ground plane coordinate system and the astronomical triangle.
In some embodiments, the time interval is divided by a method of time domain search and double-layer cluster analysis with the illumination intensity and the change rate as extraction factors, and the method comprises the following steps:
analyzing a received energy rule of the photovoltaic power station based on sample historical data of different situations;
establishing a geographical coordinate system with a photovoltaic power station as an origin, and establishing a solar running track;
performing cluster analysis on the illumination segments, and dividing time intervals of similar characteristics into the same time interval;
performing double-layer clustering analysis by adopting a time-amplitude domain selection method, and extracting the existence moment of the illumination fragment according to the historical data of the sample;
and selecting an illumination segment with large illumination fluctuation, and performing clustering analysis based on the illumination intensity, the illumination change rate and the double-layer clustering factor to divide a final time interval.
In some embodiments, a variable time interval is determined based on device information and weather information of the illumination sensor, and the variable time interval is optimized in real time by an adaptive dynamic programming method, comprising:
calculating a second derivative of an influence curve of meteorological conditions and illumination intensity on output power;
determining variable time nodes under different meteorological conditions;
and analyzing according to the illumination intensity signal transmitted by the illumination sensor, and optimizing the time interval by a self-adaptive dynamic programming method.
In some embodiments, the analyzing is performed according to the illumination intensity signal transmitted by the illumination sensor, and the time interval is optimized by an adaptive dynamic programming method, including:
inputting the time segment phase variable and the illumination intensity state variable into a first evaluation network of a dynamic programming nonlinear relation model to obtain an optimal solution function estimation value of the subprocess;
calculating a partial derivative of the optimal solution function estimation value to the illumination output power decision variable;
updating the input of the execution network according to the partial derivative;
when the calculation of any stage is carried out, the processes are executed in an iterative mode, and a state transition equation of the Kth sub-process is obtained through comparison of a second evaluation network;
and obtaining the optimized time interval according to the boundary condition of the state transition equation.
In some embodiments, the first evaluation network includes an error between the light output power and the expected power, and the second evaluation network includes an expected yield error and a yield of the photovoltaic power plant after adjusting the parameters.
In a second aspect, the present application provides a photovoltaic power generation apparatus, the apparatus comprising:
a determination unit configured to determine a sun movement trajectory and relative position information between the sun and the photovoltaic power plant;
the time interval dividing unit is configured to divide time intervals by a method of time-amplitude domain search and double-layer clustering analysis by taking the illumination intensity and the change rate as extraction factors;
the parameter range determining unit is configured to determine the parameter ranges of the adjustment angle and the frequency of the photovoltaic power generation equipment based on the relation between the operation energy consumption of the photovoltaic power generation equipment of the photovoltaic power generation station and the economic benefits brought by the adjustment angle and the frequency;
the time interval optimization unit is configured to determine a variable time interval according to the equipment information and the meteorological information of the illumination sensor, and the variable time interval is optimized in real time through an adaptive dynamic programming method;
and the parameter adjusting unit is configured to adjust the parameter ranges of the adjustment angle and the frequency of the photovoltaic power generation equipment in a rolling optimization mode on the basis of the optimized variable time interval.
In some embodiments, the determining unit comprises:
the information collection subunit is configured to collect the ephemeris information of the photovoltaic power station through a GPS system;
the geographic position determining subunit is configured to determine the geographic coordinate position and the standard time of the solar power generation system according to the relation between the solar motion trail and the earth;
and the position information conversion subunit is configured to convert the motion trail of the sun and the relative position information between the sun and the photovoltaic power station based on the relation between the ground plane coordinate system and the astronomical triangle.
In a third aspect, the present application provides an electronic device comprising: at least one processor, memory, at least one network interface, and a user interface;
the at least one processor, the memory, the at least one network interface, and the user interface are coupled together by a bus system;
the processor is operable to perform the steps of the photovoltaic power generation method of the first aspect by invoking a program or instructions stored by the memory.
In a fourth aspect, the present application provides a computer readable storage medium having stored thereon a computer program which, when executed by a processor, performs the steps of the method of photovoltaic power generation according to the first aspect.
Compared with the prior art, the technical scheme provided by the embodiment of the application has the following advantages:
according to the photovoltaic power generation method, the photovoltaic power generation device, the electronic equipment and the storage medium, the parameter ranges of the adjustment angle and the adjustment frequency are determined based on the relation between the operation energy consumption and the economic benefits brought by the adjustment angle and the adjustment frequency, and the economic adaptability of the photovoltaic power generation method and the device is improved; determining a variable time interval according to equipment information and meteorological information of an illumination sensor, and optimizing the variable time interval in real time by a self-adaptive dynamic programming method; based on the optimized variable time interval, the parameter ranges of the adjustment angle and the frequency of the photovoltaic power generation equipment are adjusted in a rolling optimization mode, closed-loop control of a tracking system is achieved, photovoltaic daily power generation is improved, energy consumption of the photovoltaic power generation equipment is reduced, the difficulty of tracking control of the solar variable frequency is reduced, and accuracy of control is improved.
Drawings
The accompanying drawings, which are incorporated in and constitute a part of this specification, illustrate embodiments consistent with the invention and together with the description, serve to explain the principles of the invention.
In order to more clearly illustrate the embodiments of the present invention or the technical solutions in the prior art, the drawings used in the description of the embodiments or the prior art will be briefly described below, and it is obvious for those skilled in the art that other drawings can be obtained according to the drawings without inventive exercise.
Fig. 1 is a schematic flow chart of a photovoltaic power generation method provided in an embodiment of the present application;
FIG. 2 is a schematic flow chart of another photovoltaic power generation method provided by an embodiment of the present application;
FIG. 3 is a schematic diagram of an implementation scenario in which embodiments of the present application are applicable;
fig. 4 is a schematic structural diagram of a photovoltaic power generation apparatus provided in an embodiment of the present application;
fig. 5 is a schematic structural diagram of an electronic device according to an embodiment of the present application.
Detailed Description
In order to make the objects, technical solutions and advantages of the embodiments of the present application clearer, the technical solutions in the embodiments of the present application will be clearly and completely described below with reference to the drawings in the embodiments of the present application, and it is obvious that the described embodiments are some embodiments of the present application, but not all embodiments. All other embodiments, which can be derived by a person skilled in the art from the embodiments given herein without making any creative effort, shall fall within the protection scope of the present application.
Fig. 1 is a schematic flow chart of a photovoltaic power generation method provided in an embodiment of the present application, where the method specifically includes the following steps:
s101, determining a motion track of the sun and relative position information between the sun and the photovoltaic power station.
The solar motion track can be pre-judged according to the position and the time difference information.
And S102, dividing time intervals by using the illumination intensity and the change rate as extraction factors through a time domain search and double-layer clustering analysis method.
S103, determining parameter ranges of the adjusting angle and the adjusting frequency of the photovoltaic power generation equipment based on the relation between the operation energy consumption of the photovoltaic power generation equipment of the photovoltaic power generation station and economic benefits brought by the adjusting angle and the adjusting frequency.
By establishing the relationship between the operation energy consumption of the photovoltaic power generation equipment of the photovoltaic power station and the economic benefits brought by the adjustment angle and frequency. The economic benefit is mainly photovoltaic output power per unit time, and the electric power income of the photovoltaic power generation end is calculated in a time-of-use electricity price presentation mode. Based on the method, the relation between the operation energy consumption of the photovoltaic power generation equipment and the economic benefit of the photovoltaic end can be obtained, and the optimal selection interval of the control parameters is determined.
Alternatively, the cost-benefit composition of the photovoltaic generator is considered, for example consisting essentially of: the operation cost (taking standard service scale as an example) of the photovoltaic power generation equipment and the photovoltaic power generation profit (taking on-grid electricity price as a standard) are increased by taking 0.25 degrees as a reference, the rotation frequency is taken 1 time/min as a standard, and a curve graph of photovoltaic follow-up tracking power generation energy consumption and photovoltaic power generation net profit is drawn. The operation cost of the photovoltaic power generation equipment is represented by the operation energy consumption of the photovoltaic power generation equipment for calculation, the power source is calculated and analyzed by photovoltaic power generation, and the extreme value area of the interactive influence curve is analyzed.
The operation cost of the photovoltaic power generation equipment is represented by equipment operation energy consumption for calculation, the power source is calculated and analyzed by photovoltaic power generation, an extreme value area of a curve of interaction influence is analyzed, and an optimal frequency and angle combination strategy range is determined in the time interval divided in the step S102.
And S104, determining a variable time interval according to the equipment information and the meteorological information of the illumination sensor, and optimizing the variable time interval in real time by using a self-adaptive dynamic programming method.
Optionally, a second derivative of an influence curve of meteorological conditions and illumination intensity on output power is calculated, variable time nodes under different meteorological conditions are determined, a daily operation strategy is selected, meanwhile, analysis is carried out according to an illumination intensity signal transmitted by a real-time illumination sensor, and a tracking time interval is optimized by using an adaptive dynamic programming ADP method.
Firstly, receiving meteorological signals, preliminarily prejudging the basic weather condition and the illumination intensity, and selecting a tracking scheme. Secondly, optimizing by adopting a self-adaptive dynamic programming ADP method, inputting time segment stage variables and illumination intensity state variables into a first evaluation network of a dynamic programming nonlinear relation model to obtain an optimal solution function estimation value of the subprocess, then calculating a partial derivative of the illumination output power decision variable, updating the input of an execution network in real time, continuing the previous process when calculating at any stage, comparing by using a second evaluation network to obtain a state transition equation of a kth subprocess, and obtaining an optimized real-time interval according to the boundary condition. The first evaluation network consists of errors of the illumination output power and the expected power, the second evaluation network consists of adjusted photovoltaic power generation income and expected income errors, the utility function of the second evaluation network is set to be a photovoltaic power generation operation income function, and the constraint conditions of the second evaluation network are a frequency limit value and an operation safety limit value.
And S105, adjusting the parameter ranges of the adjustment angle and the frequency of the photovoltaic power generation equipment in a rolling optimization mode based on the optimized variable time interval.
According to the embodiment of the application, the photovoltaic array angle is adjusted through designing variable frequency time control, the photovoltaic daily generated energy can be improved, the photovoltaic power generation efficiency is improved, the energy consumption of photovoltaic power generation equipment is reduced, the income of a photovoltaic power generation end is improved, the difficulty of tracking control on the solar variable frequency is reduced, and the accuracy of control is improved.
In another embodiment of the present application, determining the movement track of the sun and the relative position information between the sun and the photovoltaic power plant comprises:
collecting ephemeris information of the photovoltaic power station through a GPS system;
determining the geographic coordinate position and the standard time of the solar power generation system according to the relation between the solar motion track and the earth;
and converting the motion trail of the sun and the relative position information between the sun and the photovoltaic power station based on the relation between the ground plane coordinate system and the astronomical triangle.
Optionally, according to real-time transmission of a GPS system and a time difference system, scale, position information, and the like of the photovoltaic power station are comprehensively input into a monitoring system, a solar running track is simulated, a solar running periodic variation characteristic is recorded, that is, a model for calculating a solar altitude angle and an azimuth angle is established according to longitude and latitude information and time zone time information, a typical time day is selected for historical data simulation verification, and a model error is judged and corrected.
The solar position is composed of two coordinate information of height and azimuth angle in a terrestrial coordinate system, and a solar position model is established as follows:
μ＝(T-12)×15°；
h＝arcsin(sinαsinδ+cosαcosδcosμ)；
A＝arccos(cosαsinδ-sinαcosδcosμ/cosh)；
wherein δ represents the solar declination angle; m represents the product day; μ represents the solar time angle; t represents the time of the sun; alpha represents the latitude of the area where the photovoltaic power station is located; h represents the solar altitude; a represents the solar azimuth.
In another embodiment of the present application, dividing time intervals by methods of time-amplitude domain search and two-tier cluster analysis with the illumination intensity and the change rate as extraction factors includes:
analyzing a received energy rule of the photovoltaic power station based on sample historical data of different situations;
establishing a geographical coordinate system with a photovoltaic power station as an origin, and establishing a solar running track;
performing cluster analysis on the illumination segments, and dividing time intervals of similar characteristics into the same time interval;
performing double-layer clustering analysis by adopting a time-amplitude domain selection method, and extracting the existence moment of the illumination fragment according to the historical data of the sample;
and selecting an illumination segment with large illumination fluctuation, and performing clustering analysis based on the illumination intensity, the illumination change rate and the double-layer clustering factor to divide a final time interval.
Optionally, a time-amplitude domain selection method is adopted for double-layer clustering analysis, characteristic time, namely illumination existence time, is extracted according to historical data, a segment with large illumination fluctuation in the stage is selected, clustering analysis is carried out on the basis of double-layer clustering factors of illumination intensity and illumination change rate, and time intervals are divided (a given threshold value epsilon: the illumination angle deviation is more than 5 degrees).
Optionally, the photovoltaic power plant received energy law is explored and analyzed based on the sample historical data, and time domain division is performed. Establishing a geographical coordinate system with the power station as an origin, and establishing a solar running track; and extracting segments with large fluctuation of the illumination intensity based on the characteristic moment of the illumination, performing one-layer clustering analysis based on the segments, and performing secondary clustering analysis on the clustering result according to the illumination intensity to divide a final time interval.
In another embodiment of the present application, the method further includes dividing the control area of the photovoltaic power plant uniformly mainly in different directions, dividing the control area into four-quadrant areas by using the physical center position of the photovoltaic power plant as an area dividing center point, and dividing the control area into four-quadrant areas in different quadrants for respective control.
On the basis of the establishment of a sun position model, analyzing the periodic characteristics of photovoltaic power generation based on the periodicity of a sun running track, extracting the power generation characteristic moment, wherein the extraction principle is that the illumination existence time T is greater than 0, the amplitude domain search takes an illumination intensity fluctuation signal as an extraction factor, and takes the illumination intensity and the illumination change rate as double-layer clustering variable factors, so as to perform clustering analysis and perform discretization fragment processing on continuous time;
in the process, the periodic variation of photovoltaic power generation is obviously better than other illumination intensities in noon time, for the clustering analysis in the process, the factor of the first-layer clustering analysis is the illumination variation rate, the result of the first-layer clustering analysis is subjected to two-layer clustering, the factor of the second-layer clustering analysis is the illumination intensity, the time segments in one day are discretized, and different attributes of the time segments are determined. Optionally, in the process, the change rate used is a rate of change of the unit illumination intensity of the photovoltaic array based on a fixed angle.
In another embodiment of the present application, the method further includes analyzing the variation frequency of the illumination angle, performing spectrum analysis on the variation frequency, and continuously processing the time when the variation frequency of the illumination angle is higher, so as to avoid the undersize of the discrete segment distance caused by the illumination intensity factor.
In another embodiment of the present application, a variable time interval is determined according to device information and weather information of an illumination sensor, and the variable time interval is optimized in real time by an adaptive dynamic programming method, including:
calculating a second derivative of an influence curve of meteorological conditions and illumination intensity on output power;
determining variable time nodes under different meteorological conditions;
and analyzing according to the illumination intensity signal transmitted by the illumination sensor, and optimizing the time interval by a self-adaptive dynamic programming method.
In another embodiment of the present application, analyzing the illumination intensity signal transmitted by the illumination sensor, and optimizing the time interval by an adaptive dynamic programming method includes:
inputting the time segment phase variable and the illumination intensity state variable into a first evaluation network of a dynamic programming nonlinear relation model to obtain an optimal solution function estimation value of the subprocess;
calculating a partial derivative of the optimal solution function estimation value to the illumination output power decision variable;
updating the input of the execution network according to the partial derivative;
when the calculation of any stage is carried out, the processes are executed in an iterative mode, and a state transition equation of the Kth sub-process is obtained through comparison of a second evaluation network;
and obtaining the optimized time interval according to the boundary condition of the state transition equation.
Optionally, the selected phase variables (meteorological variables, illumination intensity) and state variables (frequency) are input into an evaluation network of the dynamic programming nonlinear relation model by using an adaptive dynamic programming ADP method to obtain an optimal solution function estimation value of the subprocess, then a partial derivative of the estimation value on the decision variable (output power) is obtained, the input of the execution network is updated in real time, and the optimal time interval of each phase is obtained by recursion according to a state transfer equation.
In another embodiment of the present application, the first evaluation network includes an error between the output power of the illumination and the expected power, and the second evaluation network includes an error between the yield of the photovoltaic power plant and the expected yield after the parameters are adjusted.
Optionally, the time interval under the time control condition is optimized based on real-time parameter change, the control of the parameters is researched by a self-adaptive dynamic planning method, namely, a dynamic planning algorithm is combined with a neural network, and the optimized time interval is obtained by prediction estimation, strategy superposition and feedback control.
In another embodiment of the application, a photovoltaic power station revenue function is established, the operation energy consumption cost is composed of adjustment frequency and angle, photovoltaic power generation revenue is obtained by calculating daily power generation amount and photovoltaic internet power price, an influence curve graph is established according to the relation between the photovoltaic revenue and the adjustment angle and the adjustment frequency, and the optimal frequency control range and the optimal adjustment angle are judged.
In the process, the single tracking energy consumption of the motor in the tracking process is calculated by a method of converting the total load torque to the rotating shaft of the motor (the two-stage worm and gear speed reducing mechanism is adopted for driving), and the energy consumption cost calculation formula is as follows:
wherein F represents the equipment load, L represents the equipment length, Delta theta represents the azimuth angle adjustment angle, and W d Representing the power consumed by the motor operating azimuth angle Delta theta, k t (i j ) Is the torque coefficient of the j phase, theta e Is a mechanical angle value, i is a current, Te represents an electromagnetic torque, W f Represents the starting energy consumption of the motor, x is the adjusting times in a time slice, omega (t) represents the resistance coefficient, n represents the number of the time slices,
representing the running electricity price of the photovoltaic follow-up equipment; wherein, the calculation modes of the elevation angle and the azimuth angle are similar, W e Representing the power consumed by the motor at the motor action altitude, G e Which is an energy consumption cost.
The photovoltaic power generation benefit depends on the photovoltaic intensity and the illumination radiation amount, and assuming that the adjustment incidence angle is used as a vertical calculation, the photovoltaic power generation benefit model is as follows:
in the formula, eta represents photoelectric conversion rate, S k Represents the average radiation amount of different time segments, Q represents the power generation amount of different time segments, and omega k Photovoltaic grid-connected electricity price, G, representing different periods of time s Representing the photovoltaic power generation yield.
The overall utility function is as follows:
G＝G s -G e ；
and G represents the comprehensive income of the photovoltaic power station, and in the process, the extreme value area of the interactive influence curve is analyzed to determine the optimal control frequency range and angle of the photovoltaic power generation daily strategy. Optionally, this step is implemented based on a prospective prediction of historical states, providing a basis for a photovoltaic power plant day-ahead strategy.
The photovoltaic follow-up system determines variable time nodes according to meteorological conditions and real-time illumination intensity, establishes a multi-stage decision model based on related information transmitted in real time, and optimizes tracking time intervals by using a self-adaptive dynamic programming method. Adjusting an expected strategy according to meteorological conditions, carrying out adaptive adjustment according to the difference value of the illumination real-time intensity and the strategy intensity, and accordingly constructing a planning model network as follows:
wherein k represents the kth stage in the multi-stage decision model;
representing an overall benefit function; f. of k (x m ,u n ) A utility function representing a kth stage; (x) m ,u n ) An input representing an evaluation network; u shape k (x m ,u n ) A decision variable representing the kth stage; conversion rate of lossThe value range of gamma is as follows: 0<γ<1；E c (k) Indicating an output error; Δ w c Representing an evaluation network weight; Δ w a Representing the connection weight; l c And l a The mathematical meaning of (1) is to evaluate the network and execute the network learning rate;
the values are updated in reverse for the purpose of performing error correction of the network.
In another embodiment of the application, frequency selection of different segments is equivalent to multi-stage decision making, an optimal function is set according to benefits of photovoltaic power generation, feedback adjustment is performed through errors of expected output power, adjustment strategy evaluation is achieved through a two-stage evaluation network, and finally the optimal time interval is obtained. Wherein the state transition equations and boundary conditions are as follows:
where V represents learning efficiency, in a specific embodiment, the performance index and the error feedback function are set as follows:
in the formula, g e Representing the stage gain function, p e Indicating an output power error at a time, p ex Indicating that a difference is expected to be input at a time.
In another embodiment of the application, the difference value between the actual power output and the expected power output is used as an error feedback signal, the photovoltaic power station income is used as an income function, and the time interval is updated in real time, wherein the variation interval of the time interval is within +/-10 min of the time segment interval in the pre-strategy.
According to real-time segment division, calculating optimal control parameters under different time domain constraint conditions, adjusting control frequency parameters in a rolling time domain to achieve expected benefits, and establishing a rolling optimization model as follows:
g(k)＝F[g(0),u(0),u(1),…,u(k-1)]；
in the formula, x r (k) Representing the power state at time k, u r (k) Representing frequency state input, g representing fractional revenue, and J (N) representing overall revenue objective function; in the process, the optimization of the integral frequency conversion strategy is realized through frequency input, benefit feedback, frequency optimization and next-stage rolling propulsion. In the process, constraint conditions are formed by adopting the power balance constraint, the safe voltage constraint and the expected benefit constraint which are obtained by calculation.
As shown in fig. 2, which is a flowchart of another photovoltaic power generation method provided in the embodiment of the present application, the present invention performs real-time optimal control on a photovoltaic tracking device by using an expected strategy and a real-time correction strategy for frequency control, and discretizes a frequency domain, thereby reducing difficulty in centralized control
As shown in fig. 3, which is a schematic diagram of an implementation scenario applicable to the embodiment of the present invention, when the photovoltaic power generation method of the present invention is applied to a specific embodiment, a plurality of system platforms are required to participate together, including a geographic information system, a meteorological information platform, an illumination intensity monitoring system, an output monitoring system, a feedback control system, and a centralized computing platform, information fusion is implemented through multi-sensor fusion, information analysis of each information platform is input to the centralized computing platform, a digital signal is converted into an electrical signal, a dual-axis control motor is driven to perform a frequency conversion operation, and photovoltaic follow-up is implemented. Optionally, the real-time interval optimization and the control parameter optimization are synchronized in time, and the implementation of the method is based on the photovoltaic power plant adopting dual-axis unified control. Optionally, the electricity price parameter in the profit has a regional difference, and is different according to the difference of the electricity flow direction, in practical application, the calculation can be performed by referring to the local electricity price and the subsidy policy.
According to the method, the overall profit of the photovoltaic power generation station is maximized as a target benefit function, the energy consumption of the photovoltaic power generation follow-up equipment and the photovoltaic power generation profit are comprehensively considered, the optimal frequency control range and the optimal control angle are determined according to the periodic rule of the solar running track and the relation between the photovoltaic power generation net profit and the running frequency and angle of the follow-up equipment, so that the photovoltaic power generation can be comprehensively efficient, the running energy consumption is reduced, and the comprehensive benefit maximization of the photovoltaic power generation station is realized.
The invention adopts the combination of the pre-selection scheme and the real-time correction strategy to complete the illumination tracking function, simplifies the calculation process of the real-time tracking operation, completes the selection of the initial time segment by the search section of the time domain and the cluster analysis method of the control method, judges whether the operation strategy needs to be adjusted according to the real-time weather condition and the error feedback signal, and performs real-time adjustment on the time interval and the operation frequency by combining the self-adaptive dynamic programming algorithm and the rolling optimization algorithm.
The invention adopts variable time domain variable frequency control, and the frequency adopts a method of combining fixed frequency setting in the same time segment and variable frequency setting in time segments with different attributes. The frequency setting firstly selects an adjustable range according to a second-order optimal condition, when real-time control is carried out, the optimal fragment frequency is determined according to a limiting value according to an error feedback signal and constraint conditions of a time fragment and illumination intensity, and the error feedback comprehensively selects a threshold value according to the ratio of an expected value and an actual value of output power, so that the photovoltaic follow-up device can keep high-efficiency utilization rate.
As shown in fig. 4, an embodiment of the present application further provides a photovoltaic power generation apparatus, including:
a determination unit 41 configured to determine a movement trajectory of the sun and relative position information between the sun and the photovoltaic power plant;
a time interval dividing unit 42 configured to divide time intervals by a method of time domain search and double-layer cluster analysis with the illumination intensity and the change rate as extraction factors;
a parameter range determining unit 43 configured to determine a parameter range of the adjustment angle and the frequency of the photovoltaic power generation equipment based on a relationship between operation energy consumption of the photovoltaic power generation equipment of the photovoltaic power generation station and economic benefits brought by the adjustment angle and the frequency;
a time interval optimization unit 44 configured to determine a variable time interval according to the device information and the weather information of the illumination sensor, and optimize the variable time interval in real time by an adaptive dynamic programming method;
and a parameter adjusting unit 45 configured to adjust the parameter ranges of the adjustment angle and the frequency of the photovoltaic power generation device by means of roll optimization based on the optimized variable time interval.
In some embodiments, the determining unit 41 may include:
the information collection subunit is configured to collect the ephemeris information of the photovoltaic power station through a GPS system;
the geographic position determining subunit is configured to determine the geographic coordinate position and the standard time of the solar power generation system according to the relation between the solar motion trail and the earth;
and the position information conversion subunit is configured to convert the motion trail of the sun and the relative position information between the sun and the photovoltaic power station based on the relation between the ground plane coordinate system and the astronomical triangle.
Embodiments of the present application further provide a computer-readable storage medium, on which a computer program is stored, where the computer program, when executed by a processor, implements the steps as described in the method embodiments, for example, including:
determining the movement track of the sun and the relative position information between the sun and a photovoltaic power station;
dividing time intervals by using the illumination intensity and the change rate as extraction factors through a time domain search and double-layer clustering analysis method;
determining parameter ranges of the adjustment angle and the frequency of the photovoltaic power generation equipment based on the relation between the operation energy consumption of the photovoltaic power generation equipment of the photovoltaic power generation station and the economic benefits brought by the adjustment angle and the frequency;
determining a variable time interval according to equipment information and meteorological information of an illumination sensor, and optimizing the variable time interval in real time by a self-adaptive dynamic programming method;
and adjusting the parameter ranges of the adjustment angle and the frequency of the photovoltaic power generation equipment in a rolling optimization mode based on the optimized variable time interval.
Fig. 5 is a schematic structural diagram of an electronic device according to another embodiment of the present invention. The electronic device 500 shown in fig. 5 includes: at least one processor 501, memory 502, at least one network interface 504, and other user interfaces 503. The various components in the electronic device 500 are coupled together by a bus system 505. It is understood that the bus system 505 is used to enable connection communications between these components. The bus system 505 includes a power bus, a control bus, and a status signal bus in addition to a data bus. For clarity of illustration, however, the various buses are labeled as bus system 505 in FIG. 5.
The user interface 503 may include, among other things, a display, a keyboard, or a pointing device (e.g., a mouse, trackball, touch pad, or touch screen, among others.
It is to be understood that the memory 502 in embodiments of the present invention may be either volatile memory or nonvolatile memory, or may include both volatile and nonvolatile memory. The non-volatile Memory may be a Read-Only Memory (ROM), a Programmable ROM (PROM), an Erasable PROM (EPROM), an Electrically Erasable PROM (EEPROM), or a flash Memory. Volatile Memory can be Random Access Memory (RAM), which acts as external cache Memory. By way of illustration and not limitation, many forms of RAM are available, such as Static random access memory (Static RAM, SRAM), Dynamic Random Access Memory (DRAM), Synchronous Dynamic random access memory (Synchronous DRAM, SDRAM), Double Data Rate Synchronous Dynamic random access memory (ddr Data Rate SDRAM, ddr SDRAM), Enhanced Synchronous SDRAM (ESDRAM), synchlronous SDRAM (SLDRAM), and Direct Rambus RAM (DRRAM). The memory 502 described herein is intended to comprise, without being limited to, these and any other suitable types of memory.
In some embodiments, memory 502 stores elements, executable units or data structures, or a subset thereof, or an expanded set thereof as follows: an operating system 5021 and application programs 5022.
The operating system 5021 includes various system programs, such as a framework layer, a core library layer, a driver layer, and the like, and is used for implementing various basic services and processing hardware-based tasks. The application 5022 includes various applications, such as a media player (MediaPlayer), a Browser (Browser), and the like, for implementing various application services. The program for implementing the method according to the embodiment of the present invention may be included in the application program 5022.
In the embodiment of the present invention, by calling a program or an instruction stored in the memory 502, specifically, a program or an instruction stored in the application 5022, the processor 501 is configured to execute the method steps provided by the method embodiments, for example, including:
determining the motion track of the sun and the relative position information between the sun and the photovoltaic power station;
dividing time intervals by using the illumination intensity and the change rate as extraction factors through a time domain search and double-layer clustering analysis method;
determining parameter ranges of the adjustment angle and the frequency of the photovoltaic power generation equipment based on the relation between the operation energy consumption of the photovoltaic power generation equipment of the photovoltaic power generation station and the economic benefits brought by the adjustment angle and the frequency;
determining a variable time interval according to equipment information and meteorological information of an illumination sensor, and optimizing the variable time interval in real time by a self-adaptive dynamic programming method;
and adjusting the parameter ranges of the adjustment angle and the frequency of the photovoltaic power generation equipment in a rolling optimization mode based on the optimized variable time interval.
The method disclosed by the above-mentioned embodiments of the present invention may be applied to the processor 501, or implemented by the processor 501. The processor 501 may be an integrated circuit chip having signal processing capabilities. In implementation, the steps of the above method may be performed by integrated logic circuits of hardware or instructions in software form in the processor 501. The Processor 501 may be a general-purpose Processor, a Digital Signal Processor (DSP), an Application Specific Integrated Circuit (ASIC), an off-the-shelf Programmable Gate Array (FPGA) or other Programmable logic device, discrete Gate or transistor logic device, or discrete hardware components. The various methods, steps and logic blocks disclosed in the embodiments of the present invention may be implemented or performed. A general purpose processor may be a microprocessor or the processor may be any conventional processor or the like. The steps of the method disclosed in connection with the embodiments of the present invention may be directly implemented by a hardware decoding processor, or implemented by a combination of hardware and software elements in the decoding processor. The software elements may be located in ram, flash, rom, prom, or eprom, registers, among other storage media that are well known in the art. The storage medium is located in the memory 502, and the processor 501 reads the information in the memory 502 and completes the steps of the method in combination with the hardware.
It is to be understood that the embodiments described herein may be implemented in hardware, software, firmware, middleware, microcode, or any combination thereof. For a hardware implementation, the Processing units may be implemented within one or more Application Specific Integrated Circuits (ASICs), Digital Signal Processors (DSPs), Digital Signal Processing Devices (DSPDs), Programmable Logic Devices (PLDs), Field Programmable Gate Arrays (FPGAs), general purpose processors, controllers, micro-controllers, microprocessors, other electronic units configured to perform the functions described herein, or a combination thereof.
For a software implementation, the techniques described herein may be implemented by means of units performing the functions described herein. The software codes may be stored in a memory and executed by a processor. The memory may be implemented within the processor or external to the processor.
For convenience of description, the above devices are described as being divided into various units by function, and are described separately. Of course, the functions of the units may be implemented in the same software and/or hardware or in a plurality of software and/or hardware when implementing the invention.
The embodiments in the present specification are described in a progressive manner, and the same and similar parts among the embodiments are referred to each other, and each embodiment focuses on the differences from the other embodiments. In particular, for apparatus or system embodiments, since they are substantially similar to method embodiments, they are described in relative terms, as long as they are described in partial descriptions of method embodiments. The above-described embodiments of the apparatus and system are merely illustrative, and the units described as separate parts may or may not be physically separate, and the parts displayed as units may or may not be physical units, may be located in one place, or may be distributed on a plurality of network units. Some or all of the modules may be selected according to actual needs to achieve the purpose of the solution of the present embodiment. One of ordinary skill in the art can understand and implement it without inventive effort.
It is noted that, in this document, relational terms such as "first" and "second," and the like, may be used solely to distinguish one entity or action from another entity or action without necessarily requiring or implying any actual such relationship or order between such entities or actions. Also, the terms "comprises," "comprising," or any other variation thereof, are intended to cover a non-exclusive inclusion, such that a process, method, article, or apparatus that comprises a list of elements does not include only those elements but may include other elements not expressly listed or inherent to such process, method, article, or apparatus. Without further limitation, an element defined by the phrase "comprising an … …" does not exclude the presence of other identical elements in a process, method, article, or apparatus that comprises the element.
The foregoing are merely exemplary embodiments of the present invention, which enable those skilled in the art to understand or practice the present invention. Various modifications to these embodiments will be readily apparent to those skilled in the art, and the generic principles defined herein may be applied to other embodiments without departing from the spirit or scope of the invention. Thus, the present invention is not intended to be limited to the embodiments shown herein but is to be accorded the widest scope consistent with the principles and novel features disclosed herein.
Claims (10)
1. A method of photovoltaic power generation, the method comprising the steps of:
determining the motion track of the sun and the relative position information between the sun and the photovoltaic power station;
dividing time intervals by using the illumination intensity and the change rate as extraction factors through methods of time domain search, breadth domain search and double-layer clustering analysis, wherein the time intervals are obtained by dividing a time domain into different time segments and taking time contained between the beginning and the end of each time segment as the time intervals;
determining the parameter ranges of the adjustment angle and the adjustment frequency of the photovoltaic power generation equipment based on the relationship between the operation energy consumption of the photovoltaic power generation equipment of the photovoltaic power station and the economic benefits brought by the adjustment angle and the adjustment frequency;
determining a variable time interval according to equipment information and meteorological information of an illumination sensor, and optimizing the variable time interval in real time by a self-adaptive dynamic programming method;
and adjusting the parameter ranges of the adjustment angle and the frequency of the photovoltaic power generation equipment in a rolling optimization mode based on the optimized variable time interval.
2. The method of claim 1, wherein determining the trajectory of the sun and the relative position information between the sun and the photovoltaic power plant comprises:
collecting ephemeris information of the photovoltaic power station through a GPS system;
determining the geographic coordinate position and the standard time of the solar power generation system according to the relation between the solar motion track and the earth;
and converting the motion trail of the sun and the relative position information between the sun and the photovoltaic power station based on the relation between the ground plane coordinate system and the astronomical triangle.
3. The method of claim 1, wherein the time interval is divided by a method of time domain search and two-tier cluster analysis with the illumination intensity and the change rate as extraction factors, comprising:
analyzing a received energy rule of the photovoltaic power station based on sample historical data of different situations;
establishing a geographical coordinate system with the photovoltaic power station as an origin, and establishing a solar running track;
performing cluster analysis on the illumination segments, and dividing time intervals of similar characteristics into the same time interval;
performing double-layer clustering analysis by adopting a time-amplitude domain selection method, and extracting the existence moment of the illumination fragment according to the sample historical data;
and selecting an illumination segment with large illumination fluctuation, and performing clustering analysis based on the illumination intensity, the illumination change rate and the double-layer clustering factor to divide a final time interval.
4. The method of claim 1, wherein the variable time interval is determined based on the device information and the weather information of the illumination sensor, and the variable time interval is optimized in real time by an adaptive dynamic programming method, comprising:
calculating a second derivative of an influence curve of meteorological conditions and illumination intensity on output power;
determining variable time nodes under different meteorological conditions;
and analyzing according to the illumination intensity signal transmitted by the illumination sensor, and optimizing the time interval by a self-adaptive dynamic programming method.
5. The method of claim 4, wherein analyzing the illumination intensity signal transmitted by the illumination sensor and optimizing the time interval by an adaptive dynamic programming method comprises:
inputting the time segment phase variable and the illumination intensity state variable into a first evaluation network of a dynamic programming nonlinear relation model to obtain an optimal solution function estimation value of the subprocess;
calculating a partial derivative of the optimal solution function estimation value to the illumination output power decision variable;
updating the input of the execution network according to the partial derivative;
when the calculation of any stage is carried out, the processes are executed in an iterative mode, and a state transition equation of the Kth sub-process is obtained through comparison of a second evaluation network;
and obtaining the optimized time interval according to the boundary condition of the state transition equation.
6. The method of claim 5, wherein the first evaluation network comprises an error between the output power of the illumination and an expected power, and the second evaluation network comprises an error between a yield and an expected yield of the photovoltaic power plant after adjusting the parameters.
7. A photovoltaic power generation apparatus, characterized in that the apparatus comprises:
a determination unit configured to determine a sun movement trajectory and relative position information between the sun and the photovoltaic power plant;
the time interval dividing unit is configured to divide time intervals by methods of time domain searching, breadth domain searching and double-layer clustering analysis by taking the illumination intensity and the change rate as extraction factors, wherein the time intervals are time intervals obtained by dividing time domains into different time segments and taking time contained between the beginning and the end of each time segment as the time intervals;
the parameter range determining unit is configured to determine the parameter ranges of the adjusting angles and the frequencies of the photovoltaic power generation equipment based on the relation between the operation energy consumption of the photovoltaic power generation equipment of the photovoltaic power generation station and the economic benefits brought by the adjusting angles and the frequencies;
the time interval optimization unit is configured to determine a variable time interval according to the equipment information and the meteorological information of the illumination sensor, and the variable time interval is optimized in real time through an adaptive dynamic programming method;
and the parameter adjusting unit is configured to adjust the parameter ranges of the adjustment angle and the frequency of the photovoltaic power generation equipment in a rolling optimization mode on the basis of the optimized variable time interval.
8. The apparatus of claim 7, wherein the determining unit comprises:
the information collection subunit is configured to collect the ephemeris information of the photovoltaic power station through a GPS system;
the geographic position determining subunit is configured to determine the geographic coordinate position and the standard time of the solar power generation system according to the relation between the solar motion trail and the earth;
and the position information conversion subunit is configured to convert the motion trail of the sun and the relative position information between the sun and the photovoltaic power station based on the relation between the ground plane coordinate system and the astronomical triangle.
9. An electronic device, characterized in that the electronic device comprises: at least one processor, memory, at least one network interface, and a user interface;
the at least one processor, memory, at least one network interface, and user interface are coupled together by a bus system;
the processor is configured to perform the steps of the photovoltaic power generation method of any one of claims 1 to 6 by calling a program or instructions stored in the memory.
10. A computer-readable storage medium, characterized in that a computer program is stored thereon, which computer program, when being executed by a processor, realizes the steps of the photovoltaic power generation method according to any one of claims 1 to 6.
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