Distributed Photovoltaic Regulation Device and Method Based on Four-Fusion Terminal

Abstract

The present invention relates to the field of optoelectronic scheduling, specifically a distributed photovoltaic regulation device and method based on a four-in-one fusion terminal, 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 obtain the reflector and convert the light intensity. The power prediction module is used to fit the distribution of the output power with a beta distribution. The demand scheduling module is used to determine the scheduling coefficient on the demand side. The power supply model module is used to establish a power supply model to perform constraint planning on the power supply power and obtain the optimal output power. The quality reduction module is used to classify the generated power and actively reduce the power supply under undervoltage. The present invention helps the power grid better balance power supply and demand, reduce input fluctuations, optimize the power scheduling process, achieve dynamic balance of energy supply, ensure the maximization of the power utilization efficiency, and guarantee the stability of the power system and the power supply quality.

Description

Technical Field

[0001] The present invention relates to the field of optoelectronic dispatching, and specifically to a distributed photovoltaic regulation device and method based on a four-feasibility fusion terminal. Background Technique

[0002] The four-feasibility fusion terminal refers to the terminal identification that performs real-time detection of key electrical factors such as voltage, current, and power on the power consumption line, can perform data exchange, and has functions such as protocol conversion, power quality analysis, flexible control, anti-islanding protection, voltage over-limit governance, and software upgrade. In a distributed photovoltaic power plant, the four-feasibility fusion terminal is usually used for the automated management of photovoltaic inverters. In order to ensure power supply stability, a distributed power plant needs to optimize the allocation and management through power production, transmission, and consumption. Therefore, the four-feasibility fusion terminal is often used to participate in the power dispatching process.

[0003] Due to the instability of natural light intensity, the wear of photovoltaic panels, and the losses of the power system, the output power of distributed photovoltaic equipment is uncertain. In the scenario of single-power-plant power supply, the dispatching center cannot accurately predict the input power, which makes the power dispatching process less intelligent, the power supply quality of important demand-side equipment unable to meet the requirements, and affects the benefits and power supply quality of distributed power plants.

[0004] In addition, the characteristics of small capacity, large quantity, and dispersion of distributed power sources lead to high costs and difficult management for single-unit grid connection. On the demand side, the means of demand response are more diverse, the combinations are more complex, and there are more influencing factors, with great uncertainty. There is an urgent need for more accurate power balance means to manage the power supply of distributed photovoltaic power plants. Summary of the Invention

[0005] The purpose of the present invention is to provide a distributed photovoltaic regulation device and method based on a four-feasibility fusion terminal to solve the problems raised in the above background technique.

[0006] To solve the above technical problems, the present invention provides the following technical solution: A distributed photovoltaic regulation device based on a four-feasibility fusion terminal, including: a fusion terminal module, a power prediction module, a demand dispatching module, a power supply model module, and a quality reduction module;

[0007] The fusion terminal module is used to set a reflector with a fixed angle on the distributed photovoltaic equipment. The reflector is located within the aperture of the fusion terminal. Every other dispatching cycle, the fusion terminal acquires the reflector image. After denoising, grayscale conversion, and contrast adjustment of the image, the light intensity is calculated based on the pixel brightness and camera parameters to obtain an estimated light intensity value, which is uploaded to the central control device. The central control device aggregates the estimated light intensity values of all fusion terminals, and after data cleaning, stores them in the database;

[0008] The power prediction module is used to take the estimated light intensity as a benchmark, perform superposition operation on the total power generation and light intensity in the previous period to obtain beta distribution parameters, and use the two-parameter beta distribution to describe the output power distribution of the photovoltaic device, so as to obtain the probability distribution function of the output power of the distributed device;

[0009] The demand scheduling module is used to obtain the power supply data on the demand side, perform weighted accumulation according to the stability requirements, electricity price, previous load reduction amount, power outage loss and power ramp rate, determine the scheduling coefficient within the scheduling interval, arrange all demand-side devices in descending order of 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;

[0010] The power supply model module is used to establish a power supply model at the terminal, integrate the scheduling model scenarios by using the power supply model, perform constraint planning on the power supply power with 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, 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, the excess part is introduced into the auxiliary power source for power supplementary supply;

[0011] 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 classifications is determined by the numerical interval spanned by the scheduling coefficient. For each level of input power, it is distributed to the power supply equipment according to the proportion of the scheduling coefficient. When the power is insufficient, the power supply is reduced according to the level and scheduling priority. After the scheduling is completed, the power data is displayed in the fusion terminal in real time to end the scheduling cycle.

[0012] Further, the fusion terminal module includes: a reflector unit, an image recognition unit and a central control unit;

[0013] The reflector unit is arranged on the distributed power generation equipment without obstruction, and is used to reflect light to the camera terminal at a fixed angle;

[0014] The image recognition unit is used to obtain the image of the reflector and estimate the light intensity on the reflector according to the pixel brightness, light-emitting range, aperture size and camera exposure rate of the reflector;

[0015] The central control unit is used to transmit image data, provide computing power support for the fusion terminal, store the data of each distributed device, and perform scheduling operation on the power of the distributed electric field.

[0016] Further, the power prediction module includes: a light intensity distribution unit and a parameter superposition unit;

[0017] The light intensity distribution unit is used to describe the output power distribution of the photovoltaic device based on the estimated light intensity by using the two-parameter beta distribution;

[0018] 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.

[0019] Furthermore, the demand scheduling module includes: a demand recording unit and a power consumption evaluation unit;

[0020] The demand recording unit is used to record the power consumption demands on the demand side and sort the demand devices according to the priority of the power consumption demands.

[0021] The power consumption evaluation unit is used to balance the input and output power of the supply side and the demand side and establish a scheduling model according to the power consumption scenarios.

[0022] Furthermore, the power supply model module includes: a scheduling model unit, a constraint programming unit, and an auxiliary power unit;

[0023] The scheduling model unit is used to establish a power supply model, screen the scenarios in the scheduling model, and integrate the circuit constraint conditions;

[0024] The constraint programming unit is used to perform linear programming on the power energy scheduling with the maximum scheduling coefficient on the demand side and the minimum network loss as the main and secondary programming conditions respectively to obtain the optimal output power of the power supply model;

[0025] The auxiliary power unit is used to supply auxiliary power to the demand side devices when the optimal output power is higher than the supply side power, and smooth out the power peaks and valleys.

[0026] Furthermore, the quality reduction module includes: a supply shunt unit and a power reduction unit;

[0027] The supply shunt unit is used to classify the power on the supply side according to the output power distribution function of the distributed photovoltaic device, taking the numerical interval spanned by the scheduling coefficient as the standard;

[0028] The power reduction unit is used to distribute the generated power of each level to the demand side devices according to the ratio of the scheduling coefficient, and actively reduce the power supply power level by level in case of power shortage.

[0029] The distributed photovoltaic regulation method based on the four-flexible fusion terminal includes the following steps:

[0030] Step S1. Set the reflector without obstruction on the distributed power generation device and at a fixed angle with the acquisition optical axis of the fusion device. At the beginning of the scheduling period, the fusion terminal acquires the reflector image, and estimates the light intensity according to the pixel brightness of the light-emitting area in the image and the camera parameters;

[0031] Step S2. Based on the estimated light intensity and using the fitting result of the power generation and light intensity in the previous period as the shape parameter, a two-parameter beta distribution is used to fit the output power of the photovoltaic device to obtain the distribution function of the output power.

[0032] Step S3. Record the electricity consumption characteristics on the demand side, perform weighted accumulation on various electricity consumption characteristics to obtain the scheduling coefficient of the demand-side equipment, use the scheduling coefficient as the priority of the electricity demand, and establish a scheduling model to balance the power between the supply side and the demand side.

[0033] Step S4. Establish a power supply model in each fusion terminal. With the maximum scheduling coefficient of 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 to obtain the optimal output power of each power supply model. When the optimal output power is higher than the supply-side power, auxiliary power supply is provided to the demand-side equipment.

[0034] Step S5. According to the distribution function of the total power generation on the supply side, using the numerical interval spanned by the scheduling coefficients of each demand-side equipment as the standard, classify the power generation, and distribute the power generation at each level to the demand-side equipment in the same proportion according to the ratio of the scheduling coefficients. When the power supply is insufficient, the power supply is actively reduced in order of power level.

[0035] Further, Step S1 includes:

[0036] Step S11. Set a reflector, an image acquisition terminal, and an image recognition terminal on the distributed photovoltaic power generation equipment. The reflector and the photovoltaic panel are at the same height, and the orientation angle of the reflector forms a fixed angle with the main optical axis of the image acquisition terminal, so that the reflector is completely within the aperture range of the acquisition terminal.

[0037] Step S12. At the start of the scheduling cycle, the acquisition terminal acquires the image of the reflector. After denoising, grayscale conversion, and contrast adjustment of the image, compare the reflector image with the original image, and estimate the light intensity at the reflector according to the following formula:

[0038] ;

[0039] 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.

[0040] Step S13. The fusion terminal at each distributed device uploads the estimated light intensity value to the central control device. The central control device aggregates the light intensity estimation values of all fusion terminals, and stores them in the database after data cleaning.

[0041] Further, step S2 includes:

[0042] Step S21. Based on the estimated light intensity value, use the two-parameter beta distribution to fit the output power of the photovoltaic device:

[0043] ;

[0044] 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 respectively, A is the area of the photovoltaic panel, and k is the photoelectric conversion rate of the photovoltaic panel;

[0045] Step S22. Substitute the output power and light intensity in the previous period into the beta distribution function, determine the values of the first and second shape parameters, make the distribution function converge under all known samples, and obtain the probability distribution function with determined parameters.

[0046] Further, step S3 includes:

[0047] Step S31. Record the electricity consumption characteristics of each demand-side device. The electricity consumption characteristics include: stability requirements, electricity price, previous load curtailment amount, power outage loss, and power ramp rate. If the input power has a positive impact on the electricity consumption characteristics, assign a positive weight according to the degree of impact. If the input power has a negative impact on the electricity consumption characteristics, assign a negative weight according to the degree of impact. Accumulate all the electricity consumption characteristics after weighting to obtain the scheduling coefficient of the demand-side device;

[0048] Step S32. Arrange all demand-side devices in descending order of the scheduling coefficient. The sorting position is used as the power supply priority of the device. Based on the condition of power balance between the supply side and the demand side, use scenario simulation software to establish a power dispatching model.

[0049] Further, step S4 includes:

[0050] Step S41. Establish a power supply model in the distributed fusion terminal and perform constraint planning on the power supply power:

[0051] ;

[0052] where ΣF(Pg) represents the sum of the demand-side scheduling coefficients under the input power Pg, G(Pg) represents the total network loss of the line under the input power Pg, Pg and Ug respectively represent the active power and reactive power of the dispatching power, Ps and Us respectively represent the active power and reactive power of the input power, Pd and Ud respectively represent the active power and reactive power of the demand-side output power, V i is the input node voltage amplitude, V j is the voltage amplitude of the jth node on the demand side, θ ijis the phase angle difference between the input node and the j-th node on the demand side, R ij and B ij respectively represent the real and imaginary parts of the mutual admittance between the input node and the j-th node on the demand side, ΣPg represents the sum of the input powers of all demand-side devices, P(Q) max represents the maximum value of the function P(Q);

[0053] Step S42. Supply power to each demand-side device according to the pg value in the planning result. When the planning result cannot be obtained, remove the planning condition ΣPg ≤ P(Q)max and re-plan, and introduce an external power source, with the introduced power Po = ΣPg - P(Q) max .

[0054] Further, Step S5 includes:

[0055] Step S51. Obtain the maximum and minimum values of the scheduling coefficients of the demand-side devices, calculate the number D of numerical intervals spanning the value range between the maximum and minimum values of the scheduling coefficients, and the numerical intervals are preset according to requirements;

[0056] Step S52. Divide the value range of the function P(Q) into D regions, classify the electric energy in each region segment into one level to obtain D levels of electric energy classification, and distribute the generated power of each level to the demand-side devices in the same proportion according to the ratio of the scheduling coefficients. When the power supply is insufficient, cut the electric energy in ascending order of the levels.

[0057] Compared with the prior art, the beneficial effects achieved by the present invention are:

[0058] 1. The present invention can obtain the image of the reflector through a visual terminal, transmit the brightness of the reflector to the fusion terminal, compare the brightness with the brightness of the nominal reflector to determine the light intensity at each photovoltaic device, and use the two-parameter beta distribution to describe the output power distribution of the photovoltaic devices. By using image recognition technology, it can intelligently predict the power input on the supply side, which helps the power grid better balance power supply and demand, reduce input fluctuations, and optimize the power dispatching process.

[0059] 2. The present invention can evaluate the power supply data on the demand side, determine the scheduling coefficients within the scheduling interval, establish a power supply model at the terminal, establish a scheduling model based on the power adjustment between the supply side and the demand side, perform constraint planning on the power supply power, integrate and manage the supply side and the demand side, and achieve dynamic balance and optimized control of energy supply and demand.

[0060] 3. The present invention can classify the generated power, and for each level of input power, distribute it to the power supply devices according to the ratio of the scheduling coefficients under the optimal output power. When the power is insufficient, supply power is cut according to the levels to ensure the balance of supply and demand and the economic optimization of system operation, ensure the maximization of the electric energy utilization efficiency, and guarantee the stability of the power system and the power supply quality. Brief Description of the Drawings

[0061] The accompanying drawings are used to provide a further understanding of the present invention and form a part of the description. They are used together with the embodiments of the present invention to explain the present invention and do not constitute a limitation to the present invention. In the accompanying drawings:

[0062] Figure 1 is a schematic structural diagram of a distributed photovoltaic regulation device based on a four-flexible fusion terminal of the present invention;

[0063] Figure 2 is a schematic diagram of the steps of a distributed photovoltaic regulation method based on a four-flexible fusion terminal of the present invention. Detailed Embodiments

[0064] Next, the technical solutions in the embodiments of the present invention will be clearly and completely described in conjunction with the accompanying drawings in the embodiments of the present invention. Obviously, the described embodiments are only a part of the embodiments of the present invention, rather than all of the embodiments. All other embodiments obtained by those of ordinary skill in the art based on the embodiments of the present invention without creative efforts shall fall within the scope of protection of the present invention.

[0065] Please refer to Figure 1 , the present invention provides a technical solution: a distributed photovoltaic regulation device based on a four-flexible fusion terminal, including: a fusion terminal module, a power prediction module, a demand scheduling module, a power supply model module, and a quality reduction module;

[0066] The fusion terminal module is used to set a reflector with a fixed angle on the distributed photovoltaic device. The reflector is located within the aperture of the fusion terminal. Every other scheduling cycle, the fusion terminal acquires the image of the reflector, performs denoising, grayscale conversion, and contrast adjustment on the image, and then calculates the light intensity based on the pixel brightness and camera parameters to obtain an estimated light intensity value, which is uploaded to the central control device. The central control device aggregates the estimated light intensity values of all fusion terminals, and after data cleaning, stores them in the database;

[0067] The fusion terminal module includes: a reflector unit, an image recognition unit, and a central control unit;

[0068] The reflector unit is set on the distributed power generation device without obstruction, and is used to reflect light to the camera terminal at a fixed angle;

[0069] The image recognition unit is used to acquire the image of the reflector and estimate the light intensity on the reflector according to the pixel brightness, light-emitting range, aperture size, and camera exposure rate of the reflector;

[0070] The central control unit is used to transmit image data, provide computing power support for the fusion terminal, store the data of each distributed device, and perform scheduling operations on the power of the distributed power grid.

[0071] The power prediction module is used to take the estimated light intensity as a reference, perform superposition operation on the total power generation and light intensity in the previous period to obtain beta distribution parameters, and use the two-parameter beta distribution to describe the output power distribution of the photovoltaic device, so as to obtain the probability distribution function of the output power of the distributed device;

[0072] The power prediction module includes: a light intensity distribution unit and a parameter superposition unit;

[0073] The light intensity distribution unit is used to describe the output power distribution of the photovoltaic device based on the estimated light intensity by using the two-parameter beta distribution;

[0074] The parameter superposition unit is used to calculate the generation parameters of the beta distribution by using big data, so that the distribution function can reflect the distribution state of the actual data.

[0075] The demand scheduling module is used to obtain the power supply data on the demand side, perform weighted accumulation according to the stability requirements, electricity price, previous load reduction amount, power outage loss and power ramp rate, determine the scheduling coefficient within the scheduling interval, arrange all demand-side devices in descending order of the scheduling coefficient, calculate the stable demand power, and establish a scheduling model based on the input and output power of the supply side and the demand side;

[0076] The demand scheduling module includes: a demand recording unit and a power consumption evaluation unit;

[0077] The demand recording unit is used to record the power consumption demands on the demand side and sort the demand devices according to the priority of the power consumption demands;

[0078] The power consumption evaluation unit is used to balance the input and output power of the supply side and the demand side and establish a scheduling model according to the power consumption scenario.

[0079] The power supply model module is used to establish a power supply model at the terminal, integrate the scheduling model scenarios by using the power supply model, perform constraint planning on the power supply power with the maximum sum of the scheduling coefficients as the first constraint condition and the minimum total network loss of the power system as the second constraint condition, obtain the optimal output power of each demand-side device, and if the optimal output power is higher than the theoretical maximum value of the total power generation, introduce the excess part into the auxiliary power source for power supplementary supply;

[0080] The power supply model module includes: a scheduling model unit, a constraint planning unit and an auxiliary power unit;

[0081] The scheduling model unit is used to establish a power supply model, screen the scenarios in the scheduling model, and integrate the circuit constraint conditions;

[0082] The constraint programming unit is used to perform linear programming on power dispatching with the maximum dispatching coefficient on the demand side and the minimum network loss as the main and secondary programming conditions respectively, so as to obtain the optimal output power of the power supply model.

[0083] The auxiliary power unit is used to supply auxiliary power to the demand-side equipment when the optimal output power is higher than the supply-side power, so as to smooth out the power peaks and valleys.

[0084] The quality reduction module is used to classify the generated power according to the distribution function of the total generated power on the supply side. The number of classification levels is determined by the numerical interval spanned by the dispatching coefficient. For each level of input power, it is distributed to the power supply equipment according to the proportion of the dispatching coefficient. When the power is insufficient, the power supply is reduced according to the level and dispatching priority. After the dispatching is completed, the power data is displayed in real time in the fusion terminal to end the dispatching cycle.

[0085] The quality reduction module includes: a supply shunt unit and a power reduction unit;

[0086] The supply shunt unit is used to classify the power on the supply side according to the output power distribution function of the distributed photovoltaic equipment, with the numerical interval spanned by the dispatching coefficient as the standard.

[0087] 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 dispatching coefficient, and actively reduce the power supply power in sequence according to the power level when the power is insufficient.

[0088] As Figure 2 shown, the distributed photovoltaic regulation method based on the four-in-one fusion terminal includes the following steps:

[0089] Step S1. Set the reflector without obstruction on the distributed power generation equipment and at a fixed angle with the acquisition optical axis of the fusion equipment. At the beginning of the dispatching cycle, the fusion terminal acquires the reflector image, and estimates the illumination intensity according to the pixel brightness of the light-emitting area in the image and the camera parameters.

[0090] Step S1 includes:

[0091] Step S11. Set a reflector, an image acquisition terminal and an image recognition terminal on the distributed photovoltaic power generation equipment. The reflector and the photovoltaic panel are at the same height, and the orientation angle of the reflector forms a fixed angle with the main optical axis of the image acquisition terminal, so that the reflector is completely within the aperture range of the acquisition terminal.

[0092] Step S12. At the beginning of the dispatching cycle, the acquisition terminal acquires the reflector image. After denoising, grayscale conversion and contrast adjustment of the image, compare the reflector image with the original image, and estimate the illumination intensity at the reflector according to the following formula:

[0093] ;

[0094] Among them, Qs represents the estimated light intensity, Q0 represents the measured light intensity 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;

[0095] Step S13. The fusion terminal at each distributed device uploads the estimated light intensity 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 the database after data cleaning.

[0096] Step S2. Based on the estimated light intensity, using the fitting result of the power generation power and the light intensity in the previous period as the shape parameter, a two-parameter beta distribution is used to fit the output power of the photovoltaic device to obtain the distribution function of the output power;

[0097] Step S2 includes:

[0098] 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:

[0099] ;

[0100] Among them, 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 respectively, A is the area of the photovoltaic panel, and k is the photoelectric conversion rate of the photovoltaic panel;

[0101] Step S22. Substitute the output power and the light intensity in the previous period into the beta distribution function to determine the values of the first and second shape parameters, so that the distribution function converges under all known samples, and obtain the probability distribution function with determined parameters.

[0102] Step S3. Record the electricity consumption characteristics of the demand side, perform weighted accumulation on various electricity consumption characteristics to obtain the scheduling coefficient of the demand side equipment, use the scheduling coefficient as the priority of the power demand, and establish a scheduling model to balance the power between the supply side and the demand side;

[0103] Step S3 includes:

[0104] Step S31. Record the electricity consumption characteristics of each demand side equipment. The electricity consumption characteristics include: stability requirements, electricity price, previous load reduction amount, power outage loss, and power ramp rate. If the input power has a positive impact on the electricity consumption characteristics, a positive weight is assigned according to the impact degree. If the input power has a negative impact on the electricity consumption characteristics, a negative weight is assigned according to the impact degree. Perform weighted accumulation on all electricity consumption characteristics to obtain the scheduling coefficient of the demand side equipment;

[0105] Step S32. Arrange all demand-side devices in descending order of the scheduling coefficient. The sorting position serves as the power supply priority of the devices. Based on the condition of power balance between the supply side and the demand side, use scenario simulation software to establish a power dispatching model.

[0106] Step S4. Establish a power supply model in each fusion terminal. With the maximum scheduling coefficient of the demand side as the first constraint condition and the minimum total network loss of the power system as the second constraint condition, conduct constraint planning on the power supply power to 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 devices;

[0107] Step S4 includes:

[0108] Step S41. Establish a power supply model in the distributed fusion terminal and conduct constraint planning on the power supply power:

[0109] ;

[0110] Among them, ΣF(Pg) represents the total sum of the demand-side scheduling coefficients under the input power Pg, G(Pg) represents the total network loss of the line under the input power Pg, Pg and Ug respectively represent the active power and reactive power of the dispatching power, Ps and Us respectively represent the active power and reactive power of the input power, Pd and Ud respectively represent the active power and reactive power of the demand-side output power, 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 angle difference between the input node and the jth node on the demand side, R ij and B ij respectively represent the real part and the imaginary part of the mutual admittance between the input node and the jth node on the demand side, ΣPg represents the total sum of the input powers of all demand-side devices, P(Q) max represents the maximum value of the function P(Q);

[0111] Step S42. Supply power to each demand-side device according to the pg value in the planning result. When the planning result cannot be obtained, remove the planning condition ΣPg ≤ P(Q)max and re-conduct the planning, and introduce an external power source. The introduced power Po = ΣPg - P(Q) max .

[0112] Step S5. According to the distribution function of the total power generation of the supply side, grade the power generation based on the numerical interval spanned by the scheduling coefficients of each demand-side device. Allocate the power generation of each grade to the demand-side devices in the same proportion according to the ratio of the scheduling coefficients. When the power supply is insufficient, actively reduce the power supply power in order of the power grades.

[0113] Step S5 includes:

[0114] Step S51. Obtain the maximum and minimum values of the demand-side device scheduling coefficient, and calculate the number D of numerical intervals spanning the value range between the maximum and minimum values of the scheduling coefficient. The numerical intervals are preset according to requirements.

[0115] Step S52. Divide the value range of the function P(Q) into D regions, classify the electric energy within each region segment into one level to obtain D levels of electric energy classification, and allocate the generated power of each level to the demand-side devices in the same proportion according to the proportion of the scheduling coefficient. When the power supply is insufficient, cut the electric energy in ascending order of the levels.

[0116] Embodiment: There are 3 photovoltaic devices on the supply side, and the estimated light intensities are 200 W / m 2 , 150 W / m 2 and 250 W / m 2 . Then, according to the estimated light intensity, the total input power is determined to be 1200 W. There are 2 demand devices on the demand side, and the scheduling coefficients at 1200 W are 1.0 and 2.0 respectively. After planning, 400 W of power is supplied to the demand-side device 1, and 800 W of power is supplied to the demand-side device 2.

[0117] It should be noted that in this article, relational terms such as first and second are only used to distinguish one entity or operation from another entity or operation, and do not necessarily require or imply any actual relationship or order between these entities or operations. Moreover, the term "comprising", "including" or any other variant thereof is intended to cover non-exclusive inclusion, so that a process, method, article or device comprising a series of elements not only includes those elements, but also includes other elements not expressly listed, or also includes elements inherent to such process, method, article or device.

[0118] Finally, it should be noted that the above are only the preferred embodiments of the present invention and are not used to limit the present invention. Although the present invention has been described in detail with reference to the foregoing embodiments, for those skilled in the art, they can still modify the technical solutions described in the foregoing embodiments, or perform equivalent replacements for some of the technical features. Any modifications, equivalent replacements, improvements, etc. made within the spirit and principle of the present invention shall be included within the protection scope of the present invention.

Claims

1. A distributed photovoltaic regulation method based on a four-integrated terminal, characterized in that The method includes the following steps: Step S1. Set the reflector on the distributed power generation device without obstruction and at a fixed angle with the shooting optical axis of the fusion device. At the start of the scheduling period, the fusion terminal captures an image of the reflector, and estimates the light intensity based on the pixel brightness of the luminous area in the image and the camera parameters. Step S2. Based on the estimated light intensity, using the fitting result of the power generation power and the light intensity in the previous period as the shape parameter, adopt a two-parameter beta distribution to fit the output power of the photovoltaic device, and obtain the distribution function of the output power. Step S3. Record the electricity consumption characteristics of the demand side, perform weighted accumulation on various electricity consumption characteristics, obtain the scheduling coefficient of the demand-side device, use the scheduling coefficient as the priority of the power demand, establish a scheduling model, and balance the power of the supply side and the demand side. Step S4. Establish a power supply model in each fusion terminal. With the maximum sum of the scheduling coefficients of 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 power to 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 devices. Step S5. According to the distribution function of the total power generation power of the supply side, using the numerical interval spanned by the scheduling coefficients of each demand-side device as the standard, classify the power generation power, and distribute the power generation power of each level to the demand-side devices in the same proportion according to the ratio of the scheduling coefficients. When the power supply is insufficient, actively reduce the power supply power in turn according to the electricity energy level. Step S3 includes: Step S31. Record the electricity consumption characteristics of each demand-side device. The electricity consumption characteristics include: stability requirements, electricity price, previous load reduction amount, power outage loss, and power ramp rate. If the input power has a positive impact on the electricity consumption characteristics, assign a positive weight according to the degree of influence. If the input power has a negative impact on the electricity consumption characteristics, assign a negative weight according to the degree of influence. Perform weighted accumulation on all electricity consumption characteristics to obtain the scheduling coefficient of the demand-side device. Step S32. Arrange all demand-side devices in descending order of the scheduling coefficient, and use the sorting position as the power supply priority of the device. Based on the condition of power balance between the supply side and the demand side, select scenario simulation software to establish a power dispatch model.

2. The distributed photovoltaic regulation method based on a four-in-one fusion terminal according to claim 1, wherein: Step S1 includes: Step S11. Set a reflector, an image capture terminal, and an image recognition terminal on the distributed photovoltaic power generation device. The reflector and the photovoltaic panel are at the same height, and the orientation angle of the reflector forms a fixed angle with the main optical axis of the image capture terminal, so that the reflector is completely within the aperture range of the capture terminal. Step S12. At the start of the scheduling period, the capture terminal captures an image of the reflector. After denoising, grayscale conversion, and contrast adjustment of the image, compare the reflector image with the original image, and estimate 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 terminals at each distributed device upload the estimated light intensity values to the central control device. The central control device aggregates the light intensity estimation values of all fusion terminals, and after data cleaning, stores them in the database.

3. The distributed photovoltaic regulation method based on the four-in-one fusion terminal according to claim 2, characterized in that: Step S2 includes: Step S21. Based on the estimated light intensity value, use the two-parameter beta distribution to fit the output power of the photovoltaic device: ； Among them, 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 respectively, A is the area of the photovoltaic panel, and k is the photoelectric conversion rate of the photovoltaic panel; Step S22. Substitute the output power and light intensity in the previous period into the beta distribution function to determine the values of the first and second shape parameters, so that the distribution function converges under all known samples, and obtain the probability distribution function with determined parameters.

4. The distributed photovoltaic regulation method based on a four-in-one fusion terminal according to claim 3, 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: ； Among them, ΣF(Pg) represents the sum of the demand-side scheduling coefficients at the input power Pg, G(Pg) represents the total network loss of the line at 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 amplitude of the input node voltage, V j is the amplitude of the voltage of the j-th node on the demand side, θ ij is the phase angle difference between the input node and the j-th node on the demand side, R ij and B ij represent the real part and the imaginary part of the mutual admittance between the input node and the j-th node on the demand side respectively, ΣPg represents the sum of the input powers 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. When the planning result cannot be obtained, remove the planning condition ΣPg ≤ P(Q)max and re-plan, and introduce an external power source, with the introduced power Po = ΣPg - P(Q) max .

5. The distributed photovoltaic regulation method based on a four-in-one fusion terminal according to claim 4, wherein: Step S5 includes: Step S51. Obtain the maximum and minimum values of the demand-side device scheduling coefficient, calculate the number D of numerical intervals spanning the value range between the maximum and minimum values of the scheduling coefficient, and the numerical intervals are preset according to the demand; Step S52. Divide the value range of the function P(Q) into D regions, classify the electric energy in each region segment into one level to obtain D levels of electric energy classification, and distribute the generated power of each level to the demand-side devices in the same proportion according to the ratio of the scheduling coefficient. When the power supply is insufficient, cut the electric energy in ascending order according to the electric energy classification.

6. A distributed photovoltaic regulation device based on a four-in-one fusion terminal, characterized in that, The device includes the following modules: Fusion terminal module, power prediction module, demand scheduling module, power supply model module, and quality reduction module; The fusion terminal module is used to set a reflector with a fixed angle on the distributed photovoltaic device. The reflector is located within the shooting aperture of the fusion terminal. Every other scheduling period, the fusion terminal takes a picture of the reflector image. After denoising, grayscale conversion, and contrast adjustment of the image, the light intensity is calculated based on the pixel brightness and camera parameters to obtain the estimated light intensity value and upload it to the central control device. The central control device aggregates the estimated light intensity values of all fusion terminals and stores them in the database after data cleaning; The power prediction module is used to use the estimated light intensity value as a reference, superimpose and calculate the total power generation in the previous period and the light intensity to obtain the beta distribution parameters, and use the two-parameter beta distribution to describe the output power distribution of the photovoltaic device to 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 the stability requirements, electricity price, previous load reduction amount, power outage loss, and power ramp rate, determine the scheduling coefficient within the scheduling interval, arrange all demand-side devices in descending order of the scheduling coefficient, calculate the stable demand power, and establish a scheduling model based on 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, integrate the dispatching model scenarios using the power supply model, and perform constraint planning on the power supply power with the maximum sum of dispatching coefficients as the first constraint condition and the minimum total network loss of the power system as the second constraint condition 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 is introduced into the auxiliary power source for power supplementary supply; The quality reduction module is used to classify the power generation power according to the distribution function of the total power generation power on the supply side. The number of classification levels is determined by the numerical interval spanned by the dispatching coefficients. For each level of input power, it is distributed to the power supply devices according to the proportion of the dispatching coefficients. When the power is insufficient, power supply reduction is carried out according to the level and dispatching priority. After the dispatching is completed, the power data is displayed in real time in the fusion terminal to end the dispatching cycle.

7. The distributed photovoltaic regulation device based on a four-in-one fusion terminal according to claim 6, characterized in that: The fusion terminal module includes: a reflector unit, an image recognition unit, and a central control unit; The reflector unit is set on the distributed power generation device without obstruction and is used to reflect light to the camera terminal at a fixed angle; The image recognition unit is used to capture the image of the reflector and estimate the light intensity on the reflector according to the pixel brightness, light-emitting 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 the data of each distributed device, and perform dispatching operations on the power of the distributed electric field.

8. The distributed photovoltaic regulation device based on a four-in-one fusion terminal according to claim 7, 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 the beta distribution with two parameters 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 dispatching module includes: a demand recording unit and a power consumption evaluation unit; The demand recording unit is used to record the power consumption demands on the demand side and sort the demand devices according to the priority of the power consumption demands; The power consumption evaluation unit is used to balance the input and output power of the supply side and the demand side and establish a dispatching model according to the power consumption scenarios.

9. The distributed photovoltaic regulation device based on a four-in-one fusion terminal according to claim 8, characterized in that: The power supply model module includes: a dispatching model unit, a constraint planning unit, and an auxiliary power unit; The dispatching model unit is used to establish a power supply model, screen the scenarios in the dispatching model, and integrate the circuit constraint conditions; The constraint planning unit is used to perform linear programming on the power energy dispatching with the maximum dispatching coefficient on the demand side and the minimum network loss as the main 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 for the demand-side devices when the optimal output power is higher than the supply-side power to smooth out the power peaks and valleys.

10. The distributed photovoltaic regulation device based on the four-in-one fusion terminal according to claim 9, wherein: The quality reduction module includes: a supply shunt unit and a power reduction unit; The supply shunt unit is used to classify the power on the supply side according to the output power distribution function of the distributed photovoltaic device with the numerical interval spanned by the dispatching coefficients as the 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 scheduling coefficient, and actively reduces the power supply level by level according to the power level when the power is insufficient.

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