Distributed photovoltaic regulation and control device and method based on four fusible terminals

Abstract

The invention relates to the field of photoelectric scheduling, in particular to a distributed photovoltaic regulation and control device and method based on four fusible terminals, and the device comprises a fusion terminal module, a power prediction module, a demand scheduling module, a power supply model module and a quality reduction module. The power prediction module is used for fitting distribution of output power with beta distribution, the demand scheduling module is used for determining a scheduling coefficient of a demand side, the power supply model module is used for establishing a power supply model to carry out constraint planning on power supply power to obtain optimal output power, and the quality reduction module is used for grading power generation power and actively reducing power supply during undervoltage. According to the method, the power grid can better balance power supply and demand, input fluctuation is reduced, the power dispatching process is optimized, dynamic balance of energy supply is achieved, the utilization efficiency of electric energy is ensured to be maximized, and the stability and power supply quality of a power system are guaranteed.

Description

Technical Field

[0001] The present invention relates to the field of photovoltaic scheduling, and in particular to a distributed photovoltaic control device and method based on four fusion terminals. Background Art

[0002] The four-integrated terminal refers to a terminal identification that performs real-time detection of key electrical factors of power lines such as voltage, current, and power. It can exchange data with other terminals and has functions such as protocol conversion, power quality analysis, flexible control, anti-islanding protection, voltage over-limit management, and software upgrade. In distributed photovoltaic power fields, the four-integrated terminal is usually used for the automated management of photovoltaic inverters. In order to ensure the stability of power supply, distributed power fields need to optimize and manage power production, transmission, and consumption. Therefore, the four-integrated terminal is often used to participate in the power dispatching process.

[0003] Due to the instability of natural light intensity, wear and tear of photovoltaic panels and power system losses, the output power of distributed photovoltaic equipment is uncertain. In the scenario of single electric field power supply, the dispatch center cannot accurately predict the input power, which makes the power dispatch process not intelligent enough, and the power supply quality of important demand-side equipment cannot meet the demand, affecting the income and power supply quality of distributed power plants.

[0004] In addition, the characteristics of distributed power sources such as small capacity, large number and dispersion lead to high cost and difficult management of single-machine access to the grid. On the demand side, the means of demand response are more diverse, the combinations are more complex, and there are more influencing factors, which are extremely uncertain. More precise power balancing means are urgently needed to manage the power supply of distributed photovoltaic power fields. Summary of the invention

[0005] The purpose of the present invention is to provide a distributed photovoltaic control device and method based on four fusion terminals to solve the problems raised in the above background technology.

[0006] In order to solve the above technical problems, the present invention provides the following technical solutions: a distributed photovoltaic control device based on four fusionable terminals, comprising: a fusion terminal module, a power prediction module, a demand scheduling module, a power supply model module and a quality reduction module; The fusion terminal module is used to set a fixed-angle reflector on the distributed photovoltaic equipment. The reflector is located within the aperture of the fusion terminal. Every other scheduling period, the fusion terminal obtains the reflector image, performs denoising, grayscale and contrast adjustment on the image, and converts the light intensity according to the pixel brightness and camera parameters to obtain the light intensity estimation value and upload it to the central control device. The central control device summarizes the light intensity estimation values ​​of all fusion terminals and stores them in the database after data cleaning. The power prediction module is used to take the light intensity estimation value as a reference, superimpose the total power generation in the previous time period with the light intensity, obtain the Beta distribution parameters, use the two-parameter Beta distribution to describe the output power distribution of the photovoltaic device, and obtain the probability distribution function of the output power of the distributed device; The demand scheduling module is used to obtain the power supply data on the demand side, perform weighted accumulation according to stability requirements, electricity prices, previous load reduction, power outage losses and power ramp rate, determine the scheduling coefficient within the scheduling interval, arrange all demand side devices in descending order according to the scheduling coefficient, calculate the stable demand power, and establish a scheduling model according to the input and output power of the supply side and the demand side; The power supply model module is used to establish a power supply model at the terminal, use the power supply model to integrate the scheduling model scenario, and use the maximum sum of scheduling coefficients as the first constraint condition and the minimum total network loss of the power system as the second constraint condition to perform constraint planning on the power supply power, so as to obtain the optimal output power of each demand-side device. If the optimal output power is higher than the theoretical maximum value of the total power generation power, the excess part will be introduced into the auxiliary power source for supplementary power supply; The quality reduction module is used to classify the power generation according to the distribution function of the total power generation on the supply side. The number of levels is determined by the numerical range spanned by the scheduling coefficient. For each level of input power, it is allocated to the power supply equipment in proportion to the scheduling coefficient. When power is insufficient, power supply is reduced according to the level and scheduling priority. After the scheduling is completed, the power data is displayed in real time in the fusion terminal, and the scheduling cycle ends.

[0007] Furthermore, the fusion terminal module includes: a reflection plate unit, an image recognition unit and a central control unit; The reflector unit is disposed on the distributed power generation equipment without any shielding, and is used to reflect light toward the camera terminal at a fixed angle; The image recognition unit is used to obtain an image of the reflector and estimate the light intensity on the reflector according to the pixel brightness, luminous range, aperture size and camera exposure rate of the reflector; The central control unit is used to transmit image data, provide computing power support for the fusion terminal, store data of each distributed device, and perform scheduling operations on the power of the distributed electric field.

[0008] Further, the power prediction module includes: a light intensity distribution unit and a parameter superposition unit; The light intensity distribution unit is used to describe the output power distribution of the photovoltaic device using a two-parameter Beta distribution based on the estimated light intensity; The parameter superposition unit is used to calculate the generation parameters of the Beta distribution using big data, so that the distribution function can reflect the distribution state of the actual data.

[0009] Further, the demand scheduling module includes: a demand recording unit and a power consumption evaluation unit; The demand recording unit is used to record the power demand of the demand side and sort the demand devices according to the priority of the power demand; The power consumption evaluation unit is used to balance the input and output power of the supply side and the demand side, and to establish a scheduling model according to the power consumption scenario.

[0010] Further, the power supply model module includes: a scheduling model unit, a constraint planning unit and an auxiliary power unit; The scheduling model unit is used to establish a power supply model, screen the scenarios in the scheduling model, and integrate circuit constraints; The constraint planning unit is used to perform linear planning on electric energy scheduling with the maximum dispatch coefficient and the minimum network loss on the demand side as the primary and secondary planning conditions, respectively, to obtain the optimal output power of the power supply model; The auxiliary power unit is used to provide auxiliary power supply to demand-side equipment when the optimal output power is higher than the supply-side power, thereby smoothing out power peaks and valleys.

[0011] Further, the quality reduction module includes: a supply diversion unit and a power reduction unit; The supply shunting unit is used to classify the power on the supply side according to the output power distribution function of the distributed photovoltaic equipment and the numerical range spanned by the dispatch coefficient as a standard; The power reduction unit is used to distribute the generated power of each level to the demand side equipment according to the proportion of the dispatch coefficient, and actively reduce the power supply power in sequence according to the power level when the power is insufficient.

[0012] The distributed photovoltaic control method based on four fusion terminals includes the following steps: Step S1. The reflector is set on the distributed power generation equipment without any obstruction and at a fixed angle to the acquisition optical axis of the fusion device. At the beginning of the scheduling cycle, the fusion terminal obtains the image of the reflector and estimates the light intensity according to the pixel brightness of the luminous area in the image and the camera parameters; Step S2. Based on the estimated light intensity, the fitting result of the power generation and light intensity in the previous time period is used as the shape parameter, and the output power of the photovoltaic device is fitted using the two-parameter Beta distribution to obtain the distribution function of the output power; Step S3. Record the power consumption characteristics of the demand side, perform weighted accumulation of various power consumption characteristics, obtain the dispatch coefficient of the demand side equipment, use the dispatch coefficient as the priority of power demand, establish a dispatch model, and balance the power of the supply side and the demand side; Step S4. Establish a power supply model in each fusion terminal, take the maximum dispatch coefficient on the demand side as the first constraint condition, and the minimum total network loss of the power system as the second constraint condition, perform constraint planning on the power supply, and obtain the optimal output power of each power supply model. When the optimal output power is higher than the supply side power, provide auxiliary power supply to the demand side equipment; Step S5. Based on the distribution function of the total power generation on the supply side and the numerical range spanned by the dispatch coefficient of each demand-side device, the power generation is graded, and each grade of power generation is allocated to the demand-side equipment in the same proportion according to the proportion of the dispatch coefficient. When the power supply is insufficient, the power supply is actively reduced in sequence according to the power level.

[0013] Further, step S1 includes: Step S11. A reflector, an image acquisition terminal and an image recognition terminal are arranged on the distributed photovoltaic power generation equipment, wherein the reflector and the photovoltaic panel are located at the same height, and the orientation angle of the reflector and the main optical axis of the image acquisition terminal form a fixed angle, so that the reflector is completely located within the aperture range of the acquisition terminal; Step S12: The scheduling cycle starts, the acquisition terminal acquires the reflector image, denoises, grayscales and adjusts the contrast of the image, compares the reflector image with the original image, and estimates the light intensity at the reflector according to the following formula: ; Where Qs represents the estimated light intensity, Q0 represents the light intensity measured in the original image, n represents the number of pixels in the image, wi represents the brightness of the i-th pixel in the reflector image, Ei represents the brightness of the i-th pixel in the original image, and r represents the camera exposure rate; Step S13. The fusion terminal at each distributed device uploads the light intensity estimation value to the central control device, and the central control device aggregates the light intensity estimation values ​​of all fusion terminals and stores them in a database after data cleaning.

[0014] Further, step S2 includes: Step S21. Based on the light intensity estimation value, a two-parameter Beta distribution is used to fit the output power of the photovoltaic device: ; Where P(Q) represents the distribution function of the output power, Q represents the light intensity, τ represents the lower incomplete gamma function, α and β are the first and second shape parameters, A is the area of ​​the photovoltaic panel, and k is the photoelectric conversion efficiency of the photovoltaic panel; Step S22. Substitute the output power and light intensity in the previous cycle into the Beta distribution function, determine the first and second shape parameter values, make the distribution function converge under all known samples, and obtain a probability distribution function with determined parameters.

[0015] Further, step S3 includes: Step S31. Record the power consumption characteristics of each demand-side device, the power consumption characteristics include: stability requirements, electricity prices, previous load reduction, power outage losses and power ramp rate. If the input power has a positive impact on the power consumption characteristics, a positive weight is assigned according to the degree of impact. If the input power has a negative impact on the power consumption characteristics, a negative weight is assigned according to the degree of impact. All power consumption characteristics are weighted and accumulated to obtain the dispatch coefficient of the demand-side device. Step S32. Arrange all demand-side devices in descending order according to the dispatch coefficient, use the sorting position as the power supply priority of the device, and use scenario simulation software to establish a power dispatch model based on the power balance between the supply side and the demand side.

[0016] Further, step S4 includes: Step S41. Establish a power supply model in the distributed fusion terminal and perform constraint planning on the power supply power: ; Wherein, ΣF(Pg) represents the sum of the demand-side dispatch coefficients under the input power Pg, G(Pg) represents the total network loss of the line under the input power Pg, Pg and Ug represent the active power and reactive power of the dispatched power respectively, Ps and Us represent the active power and reactive power of the input power respectively, Pd and Ud represent the active power and reactive power of the demand-side output power respectively, V i is the input node voltage amplitude, V j is the voltage amplitude of the jth node on the demand side, θ ij is the phase difference between the input node and the jth node on the demand side, R ij and B ij represents the real and imaginary parts of the mutual admittance between the input node and the jth node on the demand side, ΣPg represents the sum of the input power of all demand-side devices, P(Q) max represents the maximum value of the function P(Q); Step S42. Supply power to each demand-side device according to the pg value in the planning result. If the planning result cannot be obtained, remove the planning condition ΣPg≤P(Q)max and re-plan, and introduce an external power source, and introduce power Po=ΣPg-P(Q) max .

[0017] Further, step S5 includes: Step S51. Obtain the maximum and minimum values ​​of the demand-side device dispatch coefficient, and calculate the number of numerical intervals D spanned by the maximum and minimum values ​​of the dispatch coefficient, where the numerical intervals are preset according to demand; Step S52. Divide the value range of the function P(Q) into D areas. The electric energy in each area segment is divided into one level, and D electric energy grades are obtained. The generated power of each level is allocated to the demand-side equipment in the same proportion according to the proportion of the dispatch coefficient. When the power supply is insufficient, the electric energy is reduced in ascending order of the levels.

[0018] Compared with the prior art, the beneficial effects achieved by the present invention are: 1. The present invention can obtain the image of the reflector with a visual terminal, transmit the brightness of the reflector to the fusion terminal, compare the brightness with the brightness of the nominal reflector, determine the light intensity at each photovoltaic device, and use a two-parameter Beta distribution to describe the output power distribution of the photovoltaic device. The image recognition technology is used to intelligently predict the power input on the supply side, which helps the power grid to better balance the supply and demand of electricity, reduce input fluctuations, and optimize the power dispatch process.

[0019] 2. The present invention can evaluate the power supply data on the demand side, determine the dispatch coefficient within the dispatch interval, establish a power supply model at the terminal, establish a dispatch model based on the power adjustment on the supply side and the demand side, perform constraint planning on the power supply, integrate the supply side and the demand side, and achieve dynamic balance and optimal regulation of energy supply and demand.

[0020] 3. The present invention can classify the generated power, and allocate each level of input power to the power supply equipment in proportion to the dispatch coefficient under the optimal output power. When power is insufficient, power supply is reduced according to the level to ensure the balance of supply and demand and the economic optimization of system operation, ensure the maximization of power utilization efficiency, and guarantee the stability of the power system and the quality of power supply. BRIEF DESCRIPTION OF THE DRAWINGS

[0021] The accompanying drawings are used to provide a further understanding of the present invention and constitute a part of the specification. Together with the embodiments of the present invention, they are used to explain the present invention and do not constitute a limitation of the present invention. In the accompanying drawings: Figure 1 It is a structural schematic diagram of a distributed photovoltaic control device based on four fusion terminals of the present invention; Figure 2 It is a schematic diagram of the steps of the distributed photovoltaic control method based on four fusion terminals of the present invention. DETAILED DESCRIPTION

[0022] The following will be combined with the drawings in the embodiments of the present invention to clearly and completely describe the technical solutions in the embodiments of the present invention. Obviously, the described embodiments are only part of the embodiments of the present invention, not all of the embodiments. Based on the embodiments of the present invention, all other embodiments obtained by ordinary technicians in this field without creative work are within the scope of protection of the present invention.

[0023] See also Figure 1 , the present invention provides a technical solution: a distributed photovoltaic control device based on four fusionable terminals, including: a fusion terminal module, a power prediction module, a demand scheduling module, a power supply model module and a quality reduction module; The fusion terminal module is used to set a fixed-angle reflector on the distributed photovoltaic equipment. The reflector is located within the aperture of the fusion terminal. Every other scheduling period, the fusion terminal obtains the reflector image, performs denoising, grayscale and contrast adjustment on the image, and converts the light intensity according to the pixel brightness and camera parameters to obtain the light intensity estimation value and upload it to the central control device. The central control device summarizes the light intensity estimation values ​​of all fusion terminals and stores them in the database after data cleaning. The fusion terminal module includes: a reflection plate unit, an image recognition unit and a central control unit; The reflector unit is disposed on the distributed power generation equipment without any shielding, and is used to reflect light toward the camera terminal at a fixed angle; The image recognition unit is used to obtain an image of the reflector and estimate the light intensity on the reflector according to the pixel brightness, luminous range, aperture size and camera exposure rate of the reflector; The central control unit is used to transmit image data, provide computing power support for the fusion terminal, store data of each distributed device, and perform scheduling operations on the power of the distributed electric field.

[0024] The power prediction module is used to take the light intensity estimation value as a reference, superimpose the total power generation in the previous time period with the light intensity, obtain the Beta distribution parameters, use the two-parameter Beta distribution to describe the output power distribution of the photovoltaic device, and obtain the probability distribution function of the output power of the distributed device; The power prediction module includes: a light intensity distribution unit and a parameter superposition unit; The light intensity distribution unit is used to describe the output power distribution of the photovoltaic device using a two-parameter Beta distribution based on the estimated light intensity; The parameter superposition unit is used to calculate the generation parameters of the Beta distribution using big data, so that the distribution function can reflect the distribution state of the actual data.

[0025] The demand scheduling module is used to obtain the power supply data on the demand side, perform weighted accumulation according to stability requirements, electricity prices, previous load reduction, power outage losses and power ramp rate, determine the scheduling coefficient within the scheduling interval, arrange all demand side devices in descending order according to the scheduling coefficient, calculate the stable demand power, and establish a scheduling model according to the input and output power of the supply side and the demand side; The demand scheduling module includes: a demand recording unit and a power consumption evaluation unit; The demand recording unit is used to record the power demand of the demand side and sort the demand devices according to the priority of the power demand; The power consumption evaluation unit is used to balance the input and output power of the supply side and the demand side, and to establish a scheduling model according to the power consumption scenario.

[0026] The power supply model module is used to establish a power supply model at the terminal, use the power supply model to integrate the scheduling model scenario, and use the maximum sum of scheduling coefficients as the first constraint condition and the minimum total network loss of the power system as the second constraint condition to perform constraint planning on the power supply power, so as to obtain the optimal output power of each demand-side device. If the optimal output power is higher than the theoretical maximum value of the total power generation power, the excess part will be introduced into the auxiliary power source for supplementary power supply; The power supply model module includes: a scheduling model unit, a constraint planning unit and an auxiliary power unit; The scheduling model unit is used to establish a power supply model, screen the scenarios in the scheduling model, and integrate circuit constraints; The constraint planning unit is used to perform linear planning on electric energy scheduling with the maximum dispatch coefficient and the minimum network loss on the demand side as the primary and secondary planning conditions, respectively, to obtain the optimal output power of the power supply model; The auxiliary power unit is used to provide auxiliary power supply to demand-side equipment when the optimal output power is higher than the supply-side power, thereby smoothing out power peaks and valleys.

[0027] The quality reduction module is used to classify the power generation according to the distribution function of the total power generation on the supply side. The number of levels is determined by the numerical range spanned by the scheduling coefficient. For each level of input power, it is allocated to the power supply equipment in proportion to the scheduling coefficient. When power is insufficient, power supply is reduced according to the level and scheduling priority. After the scheduling is completed, the power data is displayed in real time in the fusion terminal, and the scheduling cycle ends.

[0028] The quality reduction module includes: a supply diversion unit and a power reduction unit; The supply shunting unit is used to classify the power on the supply side according to the output power distribution function of the distributed photovoltaic equipment and the numerical range spanned by the dispatch coefficient as a standard; The power reduction unit is used to distribute the generated power of each level to the demand side equipment according to the proportion of the dispatch coefficient, and actively reduce the power supply power in sequence according to the power level when the power is insufficient.

[0029] like Figure 2 As shown, the distributed photovoltaic control method based on four fusion terminals includes the following steps: Step S1. The reflector is set on the distributed power generation equipment without any obstruction and at a fixed angle to the acquisition optical axis of the fusion device. At the beginning of the scheduling cycle, the fusion terminal obtains the image of the reflector and estimates the light intensity according to the pixel brightness of the luminous area in the image and the camera parameters; Step S1 includes: Step S11. A reflector, an image acquisition terminal and an image recognition terminal are arranged on the distributed photovoltaic power generation equipment, wherein the reflector and the photovoltaic panel are located at the same height, and the orientation angle of the reflector and the main optical axis of the image acquisition terminal form a fixed angle, so that the reflector is completely located within the aperture range of the acquisition terminal; Step S12: The scheduling cycle starts, the acquisition terminal acquires the reflector image, denoises, grayscales and adjusts the contrast of the image, compares the reflector image with the original image, and estimates the light intensity at the reflector according to the following formula: ; Where Qs represents the estimated light intensity, Q0 represents the light intensity measured in the original image, n represents the number of pixels in the image, wi represents the brightness of the i-th pixel in the reflector image, Ei represents the brightness of the i-th pixel in the original image, and r represents the camera exposure rate; Step S13. The fusion terminal at each distributed device uploads the light intensity estimation value to the central control device, and the central control device aggregates the light intensity estimation values ​​of all fusion terminals and stores them in a database after data cleaning.

[0030] Step S2. Based on the estimated light intensity, the fitting result of the power generation and light intensity in the previous time period is used as the shape parameter, and the output power of the photovoltaic device is fitted using the two-parameter Beta distribution to obtain the distribution function of the output power; Step S2 includes: Step S21. Based on the light intensity estimation value, a two-parameter Beta distribution is used to fit the output power of the photovoltaic device: ; Where P(Q) represents the distribution function of the output power, Q represents the light intensity, τ represents the lower incomplete gamma function, α and β are the first and second shape parameters, A is the area of ​​the photovoltaic panel, and k is the photoelectric conversion efficiency of the photovoltaic panel; Step S22. Substitute the output power and light intensity in the previous cycle into the Beta distribution function, determine the first and second shape parameter values, make the distribution function converge under all known samples, and obtain a probability distribution function with determined parameters.

[0031] Step S3. Record the power consumption characteristics of the demand side, perform weighted accumulation of various power consumption characteristics, obtain the dispatch coefficient of the demand side equipment, use the dispatch coefficient as the priority of power demand, establish a dispatch model, and balance the power of the supply side and the demand side; Step S3 includes: Step S31. Record the power consumption characteristics of each demand-side device, the power consumption characteristics include: stability requirements, electricity prices, previous load reduction, power outage losses and power ramp rate. If the input power has a positive impact on the power consumption characteristics, a positive weight is assigned according to the degree of impact. If the input power has a negative impact on the power consumption characteristics, a negative weight is assigned according to the degree of impact. All power consumption characteristics are weighted and accumulated to obtain the dispatch coefficient of the demand-side device. Step S32. Arrange all demand-side devices in descending order according to the dispatch coefficient, use the sorting position as the power supply priority of the device, and use scenario simulation software to establish a power dispatch model based on the power balance between the supply side and the demand side.

[0032] Step S4. Establish a power supply model in each fusion terminal, take the maximum dispatch coefficient on the demand side as the first constraint condition, and the minimum total network loss of the power system as the second constraint condition, perform constraint planning on the power supply, and obtain the optimal output power of each power supply model. When the optimal output power is higher than the supply side power, provide auxiliary power supply to the demand side equipment; Step S4 includes: Step S41. Establish a power supply model in the distributed fusion terminal and perform constraint planning on the power supply power: ; Wherein, ΣF(Pg) represents the sum of the demand-side dispatch coefficients under the input power Pg, G(Pg) represents the total network loss of the line under the input power Pg, Pg and Ug represent the active power and reactive power of the dispatched power respectively, Ps and Us represent the active power and reactive power of the input power respectively, Pd and Ud represent the active power and reactive power of the demand-side output power respectively, V i is the input node voltage amplitude, V j is the voltage amplitude of the jth node on the demand side, θ ij is the phase difference between the input node and the jth node on the demand side, R ij and B ij represents the real and imaginary parts of the mutual admittance between the input node and the jth node on the demand side, ΣPg represents the sum of the input power of all demand-side devices, P(Q) max represents the maximum value of the function P(Q); Step S42. Supply power to each demand-side device according to the pg value in the planning result. If the planning result cannot be obtained, remove the planning condition ΣPg≤P(Q)max and re-plan, and introduce an external power source, and introduce power Po=ΣPg-P(Q) max .

[0033] Step S5. Based on the distribution function of the total power generation on the supply side and the numerical range spanned by the dispatch coefficient of each demand-side device, the power generation is graded, and each grade of power generation is allocated to the demand-side equipment in the same proportion according to the proportion of the dispatch coefficient. When the power supply is insufficient, the power supply is actively reduced in sequence according to the power level.

[0034] Step S5 includes: Step S51. Obtain the maximum and minimum values ​​of the demand-side device dispatch coefficient, and calculate the number of numerical intervals D spanned by the maximum and minimum values ​​of the dispatch coefficient, where the numerical intervals are preset according to demand; Step S52. Divide the value range of the function P(Q) into D areas. The electric energy in each area segment is divided into one level, and D electric energy grades are obtained. The generated power of each level is allocated to the demand-side equipment in the same proportion according to the proportion of the dispatch coefficient. When the power supply is insufficient, the electric energy is reduced in ascending order of the levels.

[0035] Example: There are three photovoltaic devices on the supply side, and the estimated light intensity is 200W / m 2 、150W / m 2 and 250W / m 2 , the total input power is determined to be 1200W according to the estimated light intensity. There are 2 demand devices on the demand side, and the dispatch coefficients under 1200W are 1.0 and 2.0 respectively. After planning, 400W of power will be supplied to demand side device 1, and 800W of power will be supplied to demand side device 2.

[0036] It should be noted that, in this article, relational terms such as first and second, etc. are only used to distinguish one entity or operation from another entity or operation, and do not necessarily require or imply any such actual relationship or order between these entities or operations. Moreover, the terms "include", "comprise" or any other variants thereof are intended to cover non-exclusive inclusion, so that a process, method, article or device including a series of elements includes not only those elements, but also other elements not explicitly listed, or also includes elements inherent to such process, method, article or device.

[0037] Finally, it should be noted that the above description is only a preferred embodiment of the present invention and is not intended to limit the present invention. Although the present invention has been described in detail with reference to the aforementioned embodiments, those skilled in the art can still modify the technical solutions described in the aforementioned embodiments or replace some of the technical features therein by equivalents. Any modification, equivalent replacement, improvement, etc. made within the spirit and principle of the present invention shall be included in the protection scope of the present invention.

Claims

1. A distributed photovoltaic control method based on four fusion terminals, characterized in that: The method comprises the following steps: Step S1. The reflector is set on the distributed power generation equipment without any obstruction and at a fixed angle to the acquisition optical axis of the fusion device. At the beginning of the scheduling cycle, the fusion terminal obtains the image of the reflector and estimates the light intensity according to the brightness of the luminous area in the image; Step S2. Based on the estimated light intensity, the fitting result of the power generation and light intensity in the previous time period is used as the shape parameter, and the output power of the photovoltaic device is fitted using the two-parameter Beta distribution to obtain the distribution function of the output power; Step S3. Record the power consumption characteristics of the demand side, perform weighted accumulation of various power consumption characteristics, obtain the dispatch coefficient of the demand side equipment, use the dispatch coefficient as the priority of power demand, establish a dispatch model, and balance the power of the supply side and the demand side; Step S4. Establish a power supply model in each fusion terminal, take the maximum dispatch coefficient on the demand side as the first constraint condition, and the minimum total network loss of the power system as the second constraint condition, perform constraint planning on the power supply, and obtain the optimal output power of each power supply model. When the optimal output power is higher than the supply side power, provide auxiliary power supply to the demand side equipment; Step S5. Based on the distribution function of the total power generation on the supply side and the numerical range spanned by the dispatch coefficient of each demand-side device, the power generation is graded, and each grade of power generation is allocated to the demand-side equipment in the same proportion according to the proportion of the dispatch coefficient. When the power supply is insufficient, the power supply is actively reduced in sequence according to the power level.

2. The distributed photovoltaic control method based on four fusion terminals according to claim 1 is characterized in that: Step S1 includes: Step S11. A reflector, an image acquisition terminal and an image recognition terminal are arranged on the distributed photovoltaic power generation equipment, wherein the reflector and the photovoltaic panel are located at the same height, and the orientation angle of the reflector and the main optical axis of the image acquisition terminal form a fixed angle, so that the reflector is completely located within the aperture range of the acquisition terminal; Step S12: The scheduling cycle starts, the image acquisition terminal acquires the reflector image, performs denoising, grayscale and contrast adjustment on the image, compares the reflector image with the original image, and estimates the light intensity at the reflector according to the following formula: ； Where Qs represents the estimated light intensity, Q0 represents the light intensity measured in the original image, n represents the number of pixels in the image, wi represents the brightness of the i-th pixel in the reflector image, Ei represents the brightness of the i-th pixel in the original image, and r represents the camera exposure rate; Step S13. The fusion terminal at each distributed device uploads the light intensity estimation value to the central control device, and the central control device aggregates the light intensity estimation values ​​of all fusion terminals and stores them in a database after data cleaning.

3. The distributed photovoltaic control method based on four fusion terminals according to claim 2 is characterized in that: Step S2 includes: Step S21. Based on the light intensity estimation value, a two-parameter Beta distribution is used to fit the output power of the photovoltaic device: ； Where P(Q) represents the distribution function of the output power, Q represents the light intensity, τ represents the lower incomplete gamma function, α and β are the first and second shape parameters, A is the area of ​​the photovoltaic panel, and k is the photoelectric conversion efficiency of the photovoltaic panel; Step S22. Substitute the output power and light intensity in the previous cycle into the Beta distribution function, determine the first and second shape parameter values, make the distribution function converge under all known samples, and obtain a probability distribution function with determined parameters; Step S3 includes: Step S31. Record the power consumption characteristics of each demand-side device, the power consumption characteristics include: stability requirements, electricity prices, previous load reduction, power outage losses and power ramp rate. If the input power has a positive impact on the power consumption characteristics, a positive weight is assigned according to the degree of impact. If the input power has a negative impact on the power consumption characteristics, a negative weight is assigned according to the degree of impact. All power consumption characteristics are weighted and accumulated to obtain the dispatch coefficient of the demand-side device. Step S32. Arrange all demand-side devices in descending order according to the dispatch coefficient, use the sorting position as the power supply priority of the device, and use scenario simulation software to establish a power dispatch model based on the power balance between the supply side and the demand side.

4. The distributed photovoltaic control method based on four fusion terminals according to claim 3 is characterized in that: Step S4 includes: Step S41. Establish a power supply model in the distributed fusion terminal and perform constraint planning on the power supply power: ； Wherein, ΣF(Pg) represents the sum of the demand-side dispatch coefficients under the input power Pg, G(Pg) represents the total network loss of the line under the input power Pg, Pg and Ug represent the active power and reactive power of the dispatched power respectively, Ps and Us represent the active power and reactive power of the input power respectively, Pd and Ud represent the active power and reactive power of the demand-side output power respectively, V i is the input node voltage amplitude, V j is the voltage amplitude of the jth node on the demand side, θ ij is the phase difference between the input node and the jth node on the demand side, R ij and B ij represents the real and imaginary parts of the mutual admittance between the input node and the jth node on the demand side, ΣPg represents the sum of the input power of all demand-side devices, P(Q) max represents the maximum value of the function P(Q); Step S42. Supply power to each demand-side device according to the pg value in the planning result. If the planning result cannot be obtained, remove the planning condition ΣPg≤P(Q)max and re-plan, and introduce an external power source, and introduce power Po=ΣPg-P(Q) max .

5. The distributed photovoltaic control method based on four fusion terminals according to claim 4 is characterized in that: Step S5 includes: Step S51. Obtain the maximum and minimum values ​​of the demand-side device dispatch coefficient, and calculate the number of numerical intervals D spanned by the maximum and minimum values ​​of the dispatch coefficient, where the numerical intervals are preset according to demand; Step S52. Divide the value range of the function P(Q) into D areas. The electric energy in each area segment is divided into one level, and D electric energy grades are obtained. The generated power of each level is allocated to the demand-side equipment in the same proportion according to the proportion of the dispatch coefficient. When the power supply is insufficient, the electric energy is reduced in ascending order of the levels.

6. A distributed photovoltaic control device based on four fusion terminals, characterized in that: The system includes the following modules: a fusion terminal module, a power prediction module, a demand scheduling module, a power supply model module and a quality reduction module; The fusion terminal module is used to set a fixed-angle reflector on the distributed photovoltaic equipment. The reflector is located within the aperture of the fusion terminal. Every other scheduling period, the fusion terminal obtains the reflector image, performs denoising, grayscale and contrast adjustment on the image, and converts the light intensity according to the pixel brightness and camera parameters to obtain the light intensity estimation value and upload it to the central control device. The central control device summarizes the light intensity estimation values ​​of all fusion terminals and stores them in the database after data cleaning. The power prediction module is used to take the light intensity estimation value as a reference, superimpose the total power generation in the previous time period with the light intensity, obtain the Beta distribution parameters, use the two-parameter Beta distribution to describe the output power distribution of the photovoltaic device, and obtain the probability distribution function of the output power of the distributed device; The demand scheduling module is used to obtain the power supply data on the demand side, perform weighted accumulation according to stability requirements, electricity prices, previous load reduction, power outage losses and power ramp rate, determine the scheduling coefficient within the scheduling interval, arrange all demand side devices in descending order according to the scheduling coefficient, calculate the stable demand power, and establish a scheduling model according to the input and output power of the supply side and the demand side; The power supply model module is used to establish a power supply model at the terminal, use the power supply model to integrate the scheduling model scenario, and use the maximum sum of scheduling coefficients as the first constraint condition and the minimum total network loss of the power system as the second constraint condition to perform constraint planning on the power supply power, so as to obtain the optimal output power of each demand-side device. If the optimal output power is higher than the theoretical maximum value of the total power generation power, the excess part will be introduced into the auxiliary power source for supplementary power supply; The quality reduction module is used to classify the power generation according to the distribution function of the total power generation on the supply side. The number of levels is determined by the numerical range spanned by the scheduling coefficient. For each level of input power, it is allocated to the power supply equipment in proportion to the scheduling coefficient. When power is insufficient, power supply is reduced according to the level and scheduling priority. After the scheduling is completed, the power data is displayed in real time in the fusion terminal, and the scheduling cycle ends.

7. The distributed photovoltaic control device based on four fusion terminals according to claim 6 is characterized in that: The fusion terminal module includes: a reflection plate unit, an image recognition unit and a central control unit; The reflector unit is disposed on the distributed power generation equipment without any shielding, and is used to reflect light toward the camera terminal at a fixed angle; The image recognition unit is used to obtain an image of the reflector and estimate the light intensity on the reflector according to the pixel brightness, luminous range, aperture size and camera exposure rate of the reflector; The central control unit is used to transmit image data, provide computing power support for the fusion terminal, store data of each distributed device, and perform scheduling operations on the power of the distributed electric field.

8. The distributed photovoltaic control device based on four fusion terminals according to claim 7 is characterized in that: The power prediction module includes: a light intensity distribution unit and a parameter superposition unit; The light intensity distribution unit is used to describe the output power distribution of the photovoltaic device using a two-parameter Beta distribution based on the estimated light intensity; The parameter superposition unit is used to calculate the generation parameters of the Beta distribution using big data so that the distribution function can reflect the distribution state of the actual data; The demand scheduling module includes: a demand recording unit and a power consumption evaluation unit; The demand recording unit is used to record the power demand of the demand side and sort the demand devices according to the priority of the power demand; The power consumption evaluation unit is used to balance the input and output power of the supply side and the demand side, and to establish a scheduling model according to the power consumption scenario.

9. The distributed photovoltaic control device based on four fusion terminals according to claim 8 is characterized in that: The power supply model module includes: a scheduling model unit, a constraint planning unit and an auxiliary power unit; The scheduling model unit is used to establish a power supply model, screen the scenarios in the scheduling model, and integrate circuit constraints; The constraint planning unit is used to perform linear planning on electric energy scheduling with the maximum dispatch coefficient and the minimum network loss on the demand side as the primary and secondary planning conditions, respectively, to obtain the optimal output power of the power supply model; The auxiliary power unit is used to provide auxiliary power supply to demand-side equipment when the optimal output power is higher than the supply-side power, thereby smoothing out power peaks and valleys.

10. The distributed photovoltaic control device based on four fusion terminals according to claim 9 is characterized in that: The quality reduction module includes: a supply diversion unit and a power reduction unit; The supply shunting unit is used to classify the power on the supply side according to the output power distribution function of the distributed photovoltaic equipment and the numerical range spanned by the dispatch coefficient as a standard; The power reduction unit is used to distribute the generated power of each level to the demand side equipment according to the proportion of the dispatch coefficient, and actively reduce the power supply power in sequence according to the power level when the power is insufficient.

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