Simulation control method and device for power factor of distributed photovoltaic power station

Abstract

The present invention discloses a method and device for simulating the power factor of a distributed photovoltaic power station, and relates to the technical field of power station power control. The method includes: using a measuring device to monitor the distribution network parameters of a substation in real time to obtain substation monitoring parameters; interactive inverter operation data to obtain power generation status and reactive power output capacity; analyzing the substation monitoring parameters to predict voltage fluctuations and load changes and identify reactive power demand; taking the reactive power demand as a target, performing reactive output regulation control to make the substation power factor reach the target value. The present invention solves the technical problem in the prior art that the power factor is too small, resulting in grid voltage fluctuations, affecting the power supply quality and stability of the grid, and achieves the technical effect of optimizing the power factor regulation of distributed photovoltaic power stations and improving the power supply quality and stability of the grid.

Description

Technical Field

[0001] The present invention relates to the technical field of power station power control, and in particular to a method and device for simulating control of power factor of a distributed photovoltaic power station. Background Art

[0002] In existing distributed photovoltaic power stations, the instability of photovoltaic power generation, especially the influence of external factors such as weather and environment, often leads to power generation fluctuations, which in turn affects the stability of the power factor. When the power factor is too small or unstable, it will cause excessive reactive power in the grid, which will in turn cause grid voltage fluctuations, affecting the power supply quality of the entire distribution network and the stability of the grid. Existing solutions usually rely on manual adjustment or simple automatic adjustment strategies, which fail to fully consider the operating status and reactive output capacity of each inverter in the substation, and cannot make efficient real-time adjustments to the complex and changeable grid operating environment.

[0003] In the prior art, there is a technical problem that a power factor that is too small causes grid voltage fluctuations, thereby affecting the power supply quality and grid stability of the grid. Summary of the invention

[0004] The present application provides a method and device for simulating the power factor of a distributed photovoltaic power station, which is used to solve the technical problem in the prior art that the power factor is too small, resulting in grid voltage fluctuations, affecting the power supply quality and grid stability of the grid.

[0005] In view of the above problems, the present application provides a method and device for simulating control of power factor of a distributed photovoltaic power station.

[0006] In a first aspect of the present application, a method for simulating power factor control of a distributed photovoltaic power station is provided, the method comprising:

[0007] Use measuring equipment to monitor the distribution network parameters of the substation in real time to obtain the substation monitoring parameters, including voltage, current, power factor, and load; interactive inverter operation data to obtain power generation status and reactive output capacity; the control center uses data analysis algorithms to analyze the substation monitoring parameters, predict voltage fluctuations, load changes, and identify reactive power demand; with the reactive power demand as the target, perform reactive output regulation and control based on the power generation status and reactive output capacity obtained through the interaction of the inverter, so that the substation power factor reaches the target value.

[0008] The second aspect of the present application provides a distributed photovoltaic power station power factor simulation control device, the device comprising:

[0009] A substation monitoring parameter acquisition module, which uses measuring equipment to monitor the distribution network parameters of the substation in real time to obtain substation monitoring parameters, including voltage, current, power factor, and load; an operation data interaction module, which is used to interact with inverter operation data to obtain power generation status and reactive output capacity; a reactive power demand identification module, which is used for the control center to use data analysis algorithms to analyze the substation monitoring parameters, predict voltage fluctuations and load changes, and identify reactive power demand; a reactive output regulation control module, which is used to target the reactive power demand and perform reactive output regulation control according to the power generation status and reactive output capacity obtained through inverter interaction, so that the substation power factor reaches the target value.

[0010] One or more technical solutions provided in this application have at least the following technical effects or advantages:

[0011] Use measuring equipment to monitor the distribution network parameters of the substation in real time to obtain the substation monitoring parameters; interactive inverter operation data to obtain power generation status and reactive output capacity; analyze the substation monitoring parameters to predict voltage fluctuations and load changes and identify reactive power demand; take the reactive power demand as the target, and perform reactive output regulation and control based on the power generation status and reactive output capacity obtained by the inverter interaction, so that the substation power factor reaches the target value. The technical effect of optimizing the power factor regulation of distributed photovoltaic power stations and improving the power supply quality and stability of the power grid has been achieved. BRIEF DESCRIPTION OF THE DRAWINGS

[0012] In order to more clearly illustrate the technical solutions in the embodiments of the present invention, the following briefly introduces the drawings required for use in the description of the embodiments. Obviously, the drawings described below are only some embodiments of the present invention. For ordinary technicians in this field, other drawings can be obtained based on these drawings without creative work.

[0013] Figure 1 A schematic diagram of a flow chart of a method for simulating control of power factor of a distributed photovoltaic power station provided in an embodiment of the present application;

[0014] Figure 2 A schematic diagram of the structure of a distributed photovoltaic power station power factor simulation control device provided in an embodiment of the present application.

[0015] Explanation of the reference numerals: substation monitoring parameter acquisition module 10 , operation data interaction module 20 , reactive power demand identification module 30 , reactive power output regulation control module 40 . DETAILED DESCRIPTION

[0016] The present application provides a method and device for simulating the power factor of a distributed photovoltaic power station, which is used to solve the technical problem in the prior art that the power factor is too small, causing grid voltage fluctuations, affecting the power supply quality and grid stability of the grid.

[0017] The technical solutions in the embodiments of the present application will be described clearly and completely below in conjunction with the drawings in the embodiments of the present application. Obviously, the described embodiments are only part of the embodiments of the present application, not all of the embodiments. Based on the embodiments in the present application, all other embodiments obtained by ordinary technicians in this field without creative work are within the scope of protection of this application.

[0018] Embodiment 1, as Figure 1 As shown, the present application provides a simulation control method for the power factor of a distributed photovoltaic power station, the method comprising:

[0019] Step S100: Use measurement equipment to monitor the distribution network parameters of the substation in real time to obtain substation monitoring parameters, including voltage, current, power factor, and load.

[0020] Specifically, the measuring equipment plays a key role. The measuring equipment is reasonably deployed at the relevant locations of the substation to monitor the various parameters of the distribution network in real time and accurately. Through specific monitoring technology and sensors, the measuring equipment can obtain voltage information, which is crucial for understanding the potential difference of the power grid and the dynamic situation of power transmission. At the same time, the current data can also be accurately measured. The magnitude of the current reflects the flow rate and intensity of electric energy in the power grid. As an important indicator for measuring the effective utilization of electric energy, the power factor is also monitored by the measuring equipment, reflecting the proportional relationship between the useful power and the apparent power in the power grid, which is of key significance for evaluating the operation efficiency and power quality of the power grid. In addition, load information is also one of the important contents of monitoring. It covers the total amount of electric energy consumed by various electrical equipment in the substation and the changes in load. It has important reference value for predicting the load capacity of the power grid and reasonably arranging the power supply. Through the comprehensive monitoring of the parameters of the substation distribution network by these measuring equipment, the substation monitoring parameters including voltage, current, power factor and load are obtained. These parameters provide a detailed data basis for subsequent analysis and control.

[0021] Step S200: Interact with inverter operation data to obtain power generation status and reactive power output capacity.

[0022] Specifically, first, an effective data interaction channel is established, which ensures that data can be transmitted stably and accurately between the inverter and the relevant control unit. Through this channel, the inverter can send its own operating data in real time, and can also receive instructions or information from the control unit. For the interactive content of the inverter operation data, the focus is on obtaining data related to its power generation status and reactive output capacity. The power generation status data includes information such as the current power generation power, power generation efficiency, and whether it is in normal operation mode. These data can intuitively reflect the actual performance of the inverter in the power generation process and provide a basis for subsequent control decisions. Reactive output capacity data involves the potential and limitations of the inverter in reactive power output. For example, the maximum reactive power that the inverter can output, the current reactive power output setting value, and the reactive power output adjustment range, etc. Understanding this information is crucial for reasonably arranging the reactive output of the inverter to meet the reactive power demand of the substation. Through such an interactive process, the power generation status and reactive output capacity data of the inverter can be obtained comprehensively and accurately, thereby providing the necessary basis for the adjustment and control of the substation power factor in the subsequent steps.

[0023] Step S300: The control center uses a data analysis algorithm to analyze the monitoring parameters of the substation, predict voltage fluctuations and load changes, and identify reactive power demand.

[0024] Specifically, the control center obtains the monitoring parameters of the substation, including voltage, current, power factor, load and other data, and then uses data analysis algorithms to conduct in-depth analysis of these parameters.

[0025] For the prediction of voltage fluctuations, the data analysis algorithm will consider the historical data of voltage as well as the current real-time data. By analyzing the changing trend, fluctuation amplitude and periodicity of voltage data, combined with the structure and load characteristics of the substation power grid, the possible voltage fluctuations in the future are predicted. For example, if it is found that the voltage shows a gradual downward trend in a certain period of time, and the decline exceeds a certain threshold, and considering the current load changes, it can be predicted that the voltage may continue to decline in the next period of time, or even the voltage may be too low.

[0026] In terms of load change prediction, the control center predicts future load change trends by analyzing the time series characteristics of load data, including load peaks, valleys, growth rates, and periodic changes, combined with the usage patterns of electrical equipment in the substation area and possible new electrical equipment. For example, if it is found that the load in a certain area shows a trend of rapid growth in a specific time period, and there are new industrial projects about to be put into production in the area, then it can be predicted that the load in the area will continue to increase in the future.

[0027] Based on the prediction of voltage fluctuations and load changes, the control center further identifies reactive power demand. Reactive power plays an important role in maintaining grid voltage stability and improving power quality. When voltage fluctuations or load changes are predicted, the relationship between power factor, voltage and load is analyzed, combined with the operating characteristics of the grid and relevant theoretical knowledge, to determine the size and direction of reactive power required to maintain voltage stability and meet load demand under different circumstances. For example, if it is predicted that the voltage will drop and the load will increase, then it is necessary to increase the input of reactive power to increase the voltage level to meet the power demand of the load. Through such an analysis process, the control center can accurately predict voltage fluctuations and load changes, and identify reactive power demand, providing an important basis for subsequent reactive output regulation and control.

[0028] Step S400: Taking the reactive power demand as the target, reactive output regulation control is performed according to the power generation state and reactive output capacity obtained through the interaction of the inverters, so that the power factor of the substation reaches the target value.

[0029] Specifically, the reactive power demand that has been determined is clarified. This demand is based on the prediction of voltage fluctuations and load changes and related analysis in the previous steps, and the size and direction of the reactive power required to maintain the stable operation of the power grid in the substation area are clarified. Then, specific adjustment and control are carried out based on the power generation status and reactive output capacity information obtained from the inverter interaction. For the power generation status, it is very important to understand the current power generation power, efficiency, and normal operation of the inverter. If the inverter is in an efficient and stable power generation state, then when adjusting the reactive output, it is better to combine its power generation capacity to reasonably allocate reactive power. In terms of reactive output capacity, mastering the maximum reactive power that the inverter can output, the current set value, and the adjustment range can ensure that it will not exceed its capacity range during the adjustment process. Based on this information, the reactive output of the inverter is adjusted through the control strategy. During the adjustment process, the changes in the power factor of the substation area should be continuously monitored. If the power factor has not yet reached the target value, the reactive output of the inverter needs to be continuously adjusted until the power factor of the substation area finally reaches the target value. Through such targeted reactive output regulation and control, guided by reactive power demand, the power generation status and reactive output capacity of the inverter are fully utilized to achieve the target power factor of the substation, thereby ensuring the stable operation of the substation power grid and the power quality.

[0030] In a possible implementation, step S200 further includes:

[0031] Step S210: using the communication protocol to establish a communication interaction connection between the inverter and the power grid, the inverter reports the power generation status and reactive power output capacity to the power grid in real time, receives power grid instructions, and adjusts reactive power output according to the power grid instructions.

[0032] Step S220: wherein the inverter includes one or more.

[0033] Specifically, a communication interaction connection is established between the inverter and the grid through a specific communication protocol, which is an advanced standard protocol such as IEC61850 or DL / T634. This connection method ensures stable and efficient data transmission between the inverter and the grid, laying the foundation for subsequent information interaction and control operations. After the connection is established, the inverter will report its power generation status and reactive output capacity to the grid in real time. The power generation status covers key information such as the current power generation power, power generation efficiency, and whether it is in normal operation mode. The reactive output capacity includes important parameters such as the maximum reactive power that the inverter can output, the current reactive power output setting value, and the reactive power output adjustment range. By reporting this information in a timely manner, the grid can fully understand the working conditions and capacity range of the inverter. At the same time, the inverter can also receive instructions from the grid, and the grid sends corresponding instructions to the inverter according to the power quality requirements of the entire substation and the operating status of the grid. After receiving these instructions, the inverter will adjust its own reactive output according to the requirements of the instructions. This real-time adjustment capability enables the inverter to flexibly adapt to the fluctuations of the power grid and maintain the stability of the power quality in the substation. For example, if the power grid detects that the voltage in a certain area of ​​the substation fluctuates and needs to increase reactive power input to stabilize the voltage, the power grid will send an instruction to increase reactive output to the relevant inverter. After receiving the instruction, the inverter will adjust its own reactive output accordingly, thereby achieving the purpose of stabilizing the voltage and maintaining the power quality. Whether it is a single inverter or multiple inverters, the above-mentioned communication interaction and control mechanism are followed. In the scenario of multiple inverters, this communication interaction connection and control method lays the foundation for subsequent collaborative work and optimized adjustment.

[0034] In a possible implementation, step S200 further includes:

[0035] Step S230: When there are multiple inverters, obtain the distribution positions of the inverters and their connection relationships.

[0036] Step S240: Take each inverter as a node and the connection relationship as an edge to construct a graph structure to obtain an inverter collaborative network. When performing useless power regulation control analysis, the inverter is located and adjusted based on the inverter collaborative network, and the adjustment strategy is analyzed.

[0037] Specifically, when there are multiple inverters, obtaining their distribution locations and their connection relationships is an important basic work. The specific location information of each inverter in the substation is determined by appropriate technical means or equipment, involving positioning systems, geographic information system (GIS) technology, or location identification recorded when the inverter is installed. At the same time, it is also necessary to clarify the connection relationship between each inverter, including how they are connected to each other through lines, whether in series, parallel, or more complex network connection forms. These connection relationships are crucial for the subsequent construction of inverter collaborative networks and the analysis of reactive regulation control strategies, because different connection methods will affect the transmission and distribution of reactive power between inverters.

[0038] After obtaining the distribution location and connection relationship of the inverters, a graph structure is constructed with each inverter as a node and the connection relationship as an edge, thereby obtaining an inverter collaborative network. This graph structure can intuitively reflect the topological relationship between the inverters. When performing reactive power regulation control analysis, the inverter that needs to be adjusted can be effectively located based on this inverter collaborative network. By analyzing the attributes of each node (inverter) in the network and the weights of the edges (connection relationships), it is possible to determine which inverters need to be adjusted under the current reactive power demand and the priority of the adjustment. Then, the adjustment strategy is further analyzed, which involves determining how each inverter should adjust its reactive output based on the attributes of the node such as active power, reactive output capacity, distance to the load, and the weights of the edges (such as factors such as voltage regulation response time and transmission loss). For example, if an inverter is closer to the load and has a strong reactive output capacity, and the edge weight corresponding to its connection relationship indicates that its voltage regulation response time is short and the transmission loss is small, then when reactive power needs to be increased, it will be given priority for adjustment, and the magnitude of the adjustment may be reasonably determined based on the overall reactive power demand and the conditions of other inverters.

[0039] In a possible implementation, step S400 further includes:

[0040] Step S410: The attributes of the node include the active power, reactive power output capability, physical location, and distance from the load of the inverter.

[0041] Step S420: The edges between nodes represent the connection relationship between inverters, and the weights of the edges are set according to the response time and transmission loss of voltage regulation.

[0042] Step S430: performing path search through a graph structure according to reactive power demand to obtain a reactive power compensation path.

[0043] Step S440: According to the reactive power compensation path and with the reactive power demand as the target, node compensation parameter analysis is performed to obtain node control parameters.

[0044] Step S450: Based on the graph structure, the node control parameters are optimized and adjusted for the power factor of the entire substation until the target value is reached, and a reactive output adjustment strategy for the inverter is determined.

[0045] Specifically, the node attributes involved are crucial for analyzing the role of inverters in the substation power grid. Among them, active power reflects the useful electric energy actually output by the inverter and reflects its power generation efficiency; reactive output capacity describes the potential of the inverter to output reactive power, including the maximum reactive output and adjustable range, which plays an important role in maintaining grid voltage stability; physical location refers to the actual installation location of the inverter in the substation, which affects its spatial relationship with other equipment; the distance from the load is directly related to the reactive power transmission loss and the effect on the load voltage regulation. The closer the distance, the more direct the regulation effect may be.

[0046] The edge between nodes is of great significance. It represents the connection relationship between inverters. This connection relationship is further quantified and reflected by the edge weight. The edge weight is set according to the response time of voltage regulation and the transmission loss. The response time of voltage regulation reflects the efficiency of the inverters in the process of coordinated voltage regulation. If the response time is short, it means that the two inverters can cooperate quickly when regulating the voltage, then the corresponding edge weight may be higher. The transmission loss takes into account the energy loss when reactive power is transmitted between inverters. The smaller the loss, the higher the edge weight may be. By setting the edge weight in this way, the closeness of the connection relationship between inverters and the impact on voltage regulation and reactive power transmission can be more accurately reflected.

[0047] Clarifying reactive power demand is the key basis for path search. The search is performed based on the existing graph structure, where the nodes in the graph structure represent inverters, the edges represent the connection relationship between inverters, and the edges have weights. During the search process, the information reflected by the edge weights is considered. Since the edge weights are set according to the response time and transmission loss of voltage regulation, the paths with short response time and small transmission loss corresponding to the edge weights are preferred. This is because such paths can transmit reactive power more efficiently, reduce energy loss, and quickly adjust voltage when performing reactive compensation. For example, when the voltage in a certain area is too low, the path search is conducted with the area as the target. At this time, the inverters close to the area are given priority because they are closer to the target area and the loss of reactive power transmission to the area is relatively small. At the same time, if these inverters close to the area also have strong reactive output capabilities, then the paths they are located in are more likely to be selected as reactive compensation paths. By searching for paths based on reactive power demand and comprehensively considering various factors reflected by the edge weights in the graph structure, a reactive compensation path that can meet the reactive power demand is finally obtained.

[0048] After the reactive power compensation path is determined, the reactive power demand is taken as the core goal, and the compensation parameters of the nodes on the path are analyzed to obtain the node control parameters. First, the characteristics of each node on the path are analyzed. The active power of the node is the power actually output during normal power generation. This parameter limits the ability of the node to be used for reactive compensation to a certain extent, because the node needs to adjust the reactive output under the premise of ensuring its own power generation function. The reactive output capacity directly indicates the maximum amount of reactive power that the node can provide and the adjustable range. This is one of the key factors that determine how much the node undertakes in reactive compensation. The physical location of the node cannot be ignored. It determines the path of reactive power transmission from the node to the load. Different locations may lead to different transmission losses. The distance from the load is an important consideration. When performing reactive compensation, the loss of reactive power transmission to the load is relatively small for nodes closer to the load, which can more effectively affect the load voltage. Next, a comprehensive consideration is made in combination with the reactive power demand. If the reactive power demand is to increase the voltage in a certain area, then on the reactive compensation path, nodes that are closer to the area and have stronger reactive output capabilities will be required to output more reactive power. At the same time, it is also necessary to determine the direction of node voltage regulation based on the situation of the entire power grid, such as whether to increase or decrease the voltage. Through comprehensive analysis and calculation of these characteristics of each node and the reactive power demand, the control parameters of each node are finally determined. These control parameters include the amount of reactive power that the node needs to output, the voltage adjustment amplitude, and the adjustment direction. These node control parameters will provide a key basis for the subsequent optimization and adjustment of the power factor of the entire substation, ensuring that the reasonable allocation of reactive power and the optimization of the substation power factor can be effectively achieved.

[0049] Based on the graph structure, the power factor of the entire substation is optimized and adjusted according to the node control parameters. The power factor of each node area is calculated through the node control parameters, and then compared with the target value. If the target is not reached, the adjustment direction is determined according to the node control parameters and edge weights. For example, when the power factor of a certain area is low and the node reactive output capacity is strong and the connection relationship is conducive to voltage regulation, the reactive output of the node can be considered to be increased. When adjusting, the constraints such as the maximum constraint rate of reactive adjustment and the coupling relationship between useful power and reactive power should be considered. Then, the node control parameters are updated according to the adjustment direction and constraints, and the regional power factor is calculated again and the effect is evaluated. The objective function is constructed by maximizing the power factor target value, and the fitness is calculated in combination with the coupling relationship to obtain the global evaluation value. This is repeated until the substation power factor reaches the target value. At this time, the inverter reactive output adjustment strategy is determined, which clarifies the amount, rate and timing of reactive output of each inverter, ensuring the stability of the substation power factor and guaranteeing the operation of the power grid and the quality of power.

[0050] In a possible implementation, step S430 further includes:

[0051] Step S431: Determine the load location according to the reactive power demand, and use the load location as the starting node, wherein the distance of the starting node is set to 0, and the initial distances of the remaining nodes are set to infinity.

[0052] Step S432: traverse all inverter nodes connected to the initial node based on the graph structure, search for the node with the shortest distance according to the distance between nodes and edge weights, and add it to the priority queue.

[0053] Step S433: traverse all connected inverter nodes in sequence, update the shortest path record, until all nodes are visited, output the shortest path from the priority queue, and obtain the reactive power compensation path.

[0054] Specifically, the load location is determined based on the determined reactive power demand. The load location is a key factor because the purpose of reactive power compensation is to meet the load's demand for reactive power, thereby stabilizing the voltage and improving the power factor. Once the load location is determined, its location is set as the starting node, and the distance of the starting node is defined as 0. This is to provide a benchmark for the subsequent calculation of the distance between nodes. At the same time, the initial distance of the remaining nodes is set to infinity, so that the shortest path can be found by comparing the distance during the search process.

[0055] Based on the graph structure constructed earlier, we start to traverse all the inverter nodes connected to the initial node (i.e., the location of the load). During the traversal process, we need to comprehensively consider the distance between nodes and the edge weights. The distance between nodes refers to the distance in physical location, which affects the loss of reactive power transmission. The edge weight is set according to factors such as the response time of voltage regulation and transmission loss. It reflects the closeness of the connection relationship between inverters and the impact on reactive power transmission. By comparing the distance between nodes and the edge weights, we search for the node with the shortest distance and then add it to the priority queue. The priority queue is a data structure used to store elements with priority. Here, the node with the shortest distance found during the search process is stored for further processing.

[0056] Traverse all connected inverter nodes in turn and continuously update the shortest path record. Each time a new node is traversed, re-evaluate whether the current path is shorter than the recorded shortest path. If so, update the shortest path record, and this process will continue until all nodes have been visited. When all nodes have been visited, output the shortest path from the priority queue. This path is the final reactive power compensation path. Through this search process, find an optimal path from the reactive power source to the load, so that reactive power can be transmitted to the load with minimal loss and the fastest response time, thereby meeting reactive power demand and improving the power factor of the substation.

[0057] In a possible implementation, step S450 further includes:

[0058] Step S451: Calculate the regional power factor of each node according to the node control parameter, perform difference calculation between the regional power factor and the target value, and determine the difference area.

[0059] Step S452: According to the graph structure, the difference area is projected into the graph structure, the difference area is used as the optimization target, the node control parameter is used as the starting point, the optimization direction is determined by the difference value, and the node control parameter is updated, wherein the step size of the optimization adjustment is determined according to the maximum constraint rate of the reactive power adjustment.

[0060] Step S453: construct an objective function by maximizing the target value of the power factor, take the coupling relationship between active power and reactive power as a constraint condition, calculate the fitness of the updated node control parameters, and obtain the global evaluation value of the graph structure.

[0061] Step S454: Determine a reactive output adjustment strategy for the inverter according to the global evaluation value of the graph structure.

[0062] Specifically, the node control parameters are extracted, which include the active power, reactive output capacity, physical location, and distance from the load of the inverter. For example, through communication interaction with the inverter, the current active power output value and reactive output capacity value of the inverter can be obtained in real time; the physical location of the inverter can be determined through the measuring device, and its distance from the load can be calculated. The apparent power is calculated based on the active power and reactive power. The calculation formula for the apparent power is: Where p is the active power and Q is the reactive power. For example, for a node, its active power is known to be P i , the reactive power is Q i , then the apparent power of the node The calculation formula for regional power factor is: Where p is the active power and S is the apparent power. Substituting the active power and apparent power calculated above into the formula, the regional power factor of the node can be obtained. A target power factor value is set in advance. This value is usually determined according to the requirements of the power grid and the need for stable operation. For example, the target power factor is set to PF target =0.9, compare the regional power factor of each node with the target power factor and calculate the difference. The calculation formula for the difference is ΔPF = PF terget -PF i , PF i is the regional power factor of the ith node. For example, the regional power factor of a node is PF i =0.85, then the difference between the node and the target power factor is ΔPF = 0.9-0.85 = 0.05. After calculating the difference for all nodes, the area where the nodes with a negative difference or less than a certain threshold are located is determined as the difference area.

[0063] According to the existing graph structure, the determined differential area is projected into the graph structure. This graph structure represents the connection relationship between the inverters and the attributes of each node. The differential area is used as the optimization target, which means that subsequent adjustments will focus on improving the power factor of these areas. Taking the node control parameters as the starting point means starting from the current operating status of each inverter and determining the optimization direction by analyzing the differential value, that is, judging whether the power factor is too small or too large. If the power factor is less than the target value, the optimization direction may be to increase the reactive output; if the power factor is greater than the target value, the reactive output needs to be reduced. When updating the node control parameters, the step size of the optimization adjustment is determined based on the maximum constraint rate of the reactive adjustment. The maximum constraint rate of the reactive adjustment is reflected in the constraint expression in is the reactive output adjustment speed of the ith inverter, R max is the maximum adjustment speed. This is because the speed of reactive power regulation is indeed an important limiting factor, and the response time of the inverter determines how quickly it can adjust reactive power. If the adjustment speed is too fast, it will cause system instability, because rapid reactive power changes may cause drastic fluctuations in voltage and current, affecting the operation of the entire power grid. If the adjustment speed is too slow, the voltage fluctuation may not be compensated in time, resulting in the power factor not reaching the target value in time, affecting the power quality. Therefore, when determining the step size of the optimization adjustment, this maximum constraint rate needs to be fully considered. If the current difference is large, a larger adjustment is required, but it cannot exceed the maximum constraint rate to avoid causing system instability. If the difference is small, select a smaller step size for fine-tuning to gradually bring the power factor to the target value. In this way, the power factor can be effectively optimized while ensuring stability and reliability.

[0064] First, the objective function is constructed by maximizing the target value of the power factor. The goal is to make the power factor of the substation as close to or as close to the target value as possible by adjusting the reactive power output of the inverter. The target value of the power factor is set to 0.9, and the objective function is expressed as Where X represents the control parameter of the inverter reactive output, N is the number of inverters, PF targct is the power factor target value, PF actual is the actual power factor of the current area. The purpose of this objective function is to minimize the sum of squares of the difference between the target power factor and the actual power factor, so that the actual power factor is constantly close to the target value.

[0065] At the same time, the coupling relationship between useful power (i.e., active power) and reactive power is taken as a constraint condition. There is a specific relationship between the active power and reactive power of the inverter. According to the power triangle principle, the sum of the squares of active power and reactive power cannot exceed the rated capacity of the inverter, which can be expressed as follows: Inverter set, where P i is the active power output of the inverter, Q i is the reactive power output, S rated is the rated capacity of the inverter. This means that in the process of adjusting the reactive power output to optimize the power factor, the combination of active power and reactive power cannot exceed the rated capacity range of the inverter to ensure the safe and stable operation of the inverter. Next, the fitness calculation is performed on the updated node control parameters. The fitness calculation evaluates the pros and cons of the node control parameters based on the objective function and constraints. By substituting the updated node control parameters into the objective function and constraints for calculation, a fitness value is obtained. This value reflects the degree to which the power factor of the substation is close to the target value under the current parameters and whether the coupling constraints of active power and reactive power are met. Finally, the global evaluation value of the graph structure is obtained. This global evaluation value is based on the fitness calculation results. It comprehensively considers the power factor optimization of the entire substation and the operating status of each inverter. The global evaluation value can be used to evaluate the effect of the current power factor optimization strategy and provide a basis for further adjustment and optimization. If the global evaluation value is not ideal, it may be necessary to readjust the node control parameters or optimization strategy to achieve better power factor optimization effect.

[0066] When determining the reactive output adjustment strategy of the inverter, the global evaluation value of the graph structure is used for analysis. If the global evaluation value is low, for areas where the power factor is significantly lower than the target value, check the reactive output capacity of the inverters in the area, increase the reactive output of the inverters with surplus capacity, and adjust the output direction of the relevant inverters to improve the power factor. For inverters that are close to or exceed the rated capacity, reduce their reactive output to ensure safety and stability, and re-evaluate their position and connection relationship in the graph structure, and consider sharing the reactive compensation task with other inverters. At the same time, comprehensively consider the edge weights in the graph structure, and give priority to paths with short response time and small transmission loss for reactive compensation, so as to achieve a reasonable reactive output adjustment strategy, improve the power factor of the substation area, and ensure stable operation of the system.

[0067] In a possible implementation, step S451 further includes:

[0068] Step S4511: when the difference area includes multiple inverter nodes, the contribution of each inverter is evaluated according to the location distance between the inverter and the load, reactive output capacity, response time, and transmission loss;

[0069] Step S4512: According to the contribution of each inverter, the reactive power compensation demand of the difference area is allocated to obtain the reactive power output of each inverter: Where N is the number of inverters participating in the differential area, C i is the contribution of the i-th inverter, Q i is the reactive output of the i-th inverter, Q region Reactive power compensation demand.

[0070] Specifically, when the differential area contains multiple inverter nodes, it is necessary to comprehensively consider multiple factors to evaluate the contribution of each inverter. First, the location distance between the inverter and the load is an important factor. When the inverter closer to the load performs reactive compensation, the path of reactive power transmission to the load is shorter and the transmission loss is relatively small, so it has a higher contribution potential. For example, if one inverter is only a few hundred meters away from the load, and the other inverter is a few thousand meters away from the load, then the former has a relatively high contribution in terms of location distance. Secondly, reactive output capacity also plays a key role. Inverters with strong reactive output capacity can provide more reactive power and contribute more to meeting the reactive compensation needs of the differential area. For example, if the maximum reactive output of one inverter is 100kvar, while the other inverter is only 50kvar, then under the same conditions, the former has a higher reactive output capacity contribution. Response time is also not negligible. Inverters with short response time can respond to reactive compensation needs more quickly, which helps to stabilize the power factor of the system in a timely manner. For example, if the response time of one inverter is a few milliseconds, while the response time of another inverter is tens of milliseconds, then the former has a higher contribution in terms of response time. Transmission loss is also an important basis for evaluating contribution. Inverters with small transmission loss have less energy loss when transmitting reactive power and can compensate reactive power more effectively. For example, by analyzing the connection paths of different inverters, it is determined that the transmission loss of a certain inverter is significantly lower than that of other inverters, then it has a higher contribution in terms of transmission loss.

[0071] After comprehensively considering these factors, the contribution C of each inverter is calculated. i Then, according to the contribution of each inverter, the reactive power compensation demand Q of the difference area is calculated. total The specific allocation method can be to allocate according to the proportion of contribution. For the i-th inverter, its reactive output Q i It can be calculated by the following formula: Where N is the number of inverters participating in the differential area. In this way, the amount of reactive power that each inverter should output when meeting the reactive power compensation demand in the differential area can be determined, thereby achieving a more reasonable and efficient reactive power compensation distribution.

[0072] In a possible implementation, step S300 further includes:

[0073] Step S310: Establish a time series model, train the model using historical sample data, extract the long-term dependency of voltage, and predict voltage changes at multiple moments in the future using a recursive neural network.

[0074] Step S320: using a preset voltage fluctuation threshold to determine whether the voltage change has an abnormal risk, wherein when the duration of the continuous voltage change trend exceeding the preset voltage fluctuation threshold reaches an abnormal time range, it is determined that there is an abnormal risk.

[0075] Step S330: Using the smoothed load time series data, use a local maximum detection algorithm to identify future load peaks, and determine the load increase period and its load increase forecast amount.

[0076] Step S340: Perform time alignment based on the voltage change and load increase prediction, analyze the change of power factor, and determine the size and direction of reactive power demand.

[0077] Specifically, a time series model is established, which aims to capture the law of voltage changes over time. The model is trained by collecting historical sample data, which contains voltage values ​​at different time points and related influencing factors. During the training process, a recursive neural network is used to extract the long-term dependence of voltage. The recursive neural network has a memory function, which can remember past information and use it for current calculations and process time series data. In this way, the voltage changes at multiple moments in the future are predicted, providing a basis for subsequent judgment of voltage abnormality risks and determination of reactive power demand.

[0078] A preset voltage fluctuation threshold is set. This threshold is determined based on the stable operation requirements and experience of the power grid. This threshold is used to determine whether the predicted voltage change has an abnormal risk. When the duration of the continuous voltage change trend exceeding the preset voltage fluctuation threshold reaches the abnormal time range, it is determined that there is an abnormal risk. For example, if the preset voltage fluctuation threshold is ±5%, when the voltage changes for multiple consecutive moments and the duration reaches a certain length of time, such as half an hour, it can be determined that there is an abnormal risk. In this way, potential voltage problems can be discovered in a timely manner, providing early warning for taking corresponding reactive power adjustment measures.

[0079] The load time series data is smoothed. The load time series data will be affected by various noises and short-term fluctuations. Through smoothing, these interference factors can be removed and the long-term trend of the load can be better revealed. The load data is smoothed by using methods such as the moving average method, and the load value at each time point is replaced by the average value of the load values ​​at several time points around it, so that the load curve is smoother. Then, the local maximum detection algorithm is used to identify the future load peak. The local maximum detection algorithm can determine the highest point where the load may appear in the future. The first-order difference method is used to calculate the difference between the load values ​​at adjacent time points. When the difference changes from positive to negative, it means that a local maximum may appear. In this way, the future load peak can be identified more accurately. By analyzing the change trend of the load time series data, it can be determined in which time periods the load will increase significantly. For example, if the load value continues to rise in a certain time period in the future, then this time period can be determined as a load increase period. At the same time, it is also necessary to determine the predicted amount of load increase. According to the change trend of the load time series data and the identified load peak, the magnitude of the load increase in the future can be estimated. By establishing a load forecasting model, combining historical data and current trends, the future load increase can be predicted. Determine the load increase period and its load increase forecast. Knowing this information in advance will give you enough time to adjust reactive power output to cope with the upcoming load increase. When the load increases, it often causes the power factor to drop. By adjusting reactive power output in advance, you can effectively maintain the power factor at a relatively stable level and improve the operating efficiency and stability of the power grid.

[0080] Align the voltage change with the predicted amount of load increase, and compare the voltage change trend and the expected load increase on the same timeline. By analyzing historical data and current monitoring information, determine the voltage fluctuation at different time points and the possible growth period and amplitude of the load in the future. Analyze the change of power factor. When the voltage changes and the load increases or decreases, the power factor will change accordingly. By calculating and comparing the power factor at different time points, the change trend of the power factor is clear. Finally, determine the size and direction of reactive power demand. If the voltage drops and the load increases, it means that more reactive power is needed to maintain a stable power factor. At this time, the size of reactive power demand can be calculated based on the amplitude of voltage change, the predicted amount of load increase, and the gap between the target value and the actual value of the power factor. At the same time, according to the change trend of the power factor, the direction of reactive power demand can be determined, that is, whether the output of reactive power needs to be increased or reduced. For example, if the power factor is lower than the target value and continues to decline, then it is necessary to increase the output of reactive power to improve the power factor; conversely, if the power factor is high and has an upward trend, it is possible to consider reducing the output of reactive power. Through such analysis, the size and direction of reactive power demand can be accurately determined, providing specific guidance for reactive power adjustment of the power system.

[0081] Embodiment 2 is based on the same inventive concept as the analog control method for the power factor of a distributed photovoltaic power station in the above embodiment. Figure 2 As shown, the present application provides a distributed photovoltaic power station power factor simulation control device, and the device and method embodiments in the present application embodiment are based on the same inventive concept. Among them, the device includes:

[0082] The substation monitoring parameter acquisition module 10 uses a measuring device to monitor the distribution network parameters of the substation in real time to obtain the substation monitoring parameters, including voltage, current, power factor, and load.

[0083] The operation data interaction module 20 is used to interact with the inverter operation data to obtain the power generation status and reactive power output capacity.

[0084] The reactive power demand identification module 30 is used for the control center to analyze the monitoring parameters of the substation using a data analysis algorithm, predict voltage fluctuations and load changes, and identify reactive power demand.

[0085] The reactive output regulation control module 40 is used to take the reactive power demand as the target, and to perform reactive output regulation control according to the power generation state and reactive output capacity obtained through the interaction of the inverters, so as to make the power factor of the substation reach the target value.

[0086] Furthermore, the reactive power demand identification module 20 further includes:

[0087] A power grid instruction receiving unit, the power grid instruction receiving unit is used to establish a communication interaction connection between the inverter and the power grid using a communication protocol, the inverter reports the power generation status and reactive output capacity to the power grid in real time, and receives power grid instructions, and adjusts the reactive output according to the power grid instructions; wherein the inverter includes one or more.

[0088] Furthermore, the reactive power demand identification module also includes:

[0089] The inverter information acquisition unit is used to acquire the distribution positions and connection relationships of the inverters when there are multiple inverters.

[0090] An inverter collaborative network acquisition unit is used to construct a graph structure with each inverter as a node and connection relationships as edges to obtain an inverter collaborative network. When performing useless power regulation and control analysis, the inverter is located and adjusted based on the inverter collaborative network, and the adjustment strategy is analyzed.

[0091] Furthermore, the reactive output regulation control module 40 further includes:

[0092] The attributes of the node include the active power of the inverter, reactive power output capability, physical location, and distance from the load.

[0093] The edges between nodes represent the connection relationship between inverters, and the weights of the edges are set according to the response time and transmission loss of voltage regulation.

[0094] A reactive compensation path acquisition unit is used to perform path search through a graph structure according to reactive power demand to obtain a reactive compensation path.

[0095] A node control parameter acquisition unit is used to perform node compensation parameter analysis according to the reactive power compensation path and with the reactive power demand as the target, so as to obtain node control parameters.

[0096] The reactive output adjustment strategy acquisition unit is used to optimize the power factor of the entire substation for the node control parameters based on the graph structure, so as to reach the target value and determine the reactive output adjustment strategy of the inverter.

[0097] Furthermore, the reactive power compensation path acquisition unit further includes:

[0098] A shortest path record updating unit, the shortest path record updating unit is used to determine the load location according to the reactive power demand, and take the load location as the starting node, wherein the distance of the starting node is set to 0, and the initial distances of the remaining nodes are set to infinity; based on the graph structure, traverse all inverter nodes connected to the initial node, search for the node with the shortest distance according to the distance between the nodes and the edge weight, and add it to the priority queue; traverse all connected inverter nodes in turn, update the shortest path record, until all nodes are visited, output the shortest path from the priority queue, and obtain the reactive compensation path.

[0099] Furthermore, the reactive output adjustment strategy acquisition unit further includes:

[0100] A difference area determination unit is used to calculate the regional power factor of each node according to the node control parameter, and perform difference calculation using the regional power factor and the target value to determine the difference area.

[0101] A node control parameter updating unit is used to project the difference area into the graph structure according to the graph structure, take the difference area as the optimization target, take the node control parameter as the starting point, determine the optimization direction according to the difference value, and update the node control parameter, wherein the step size of the optimization adjustment is determined according to the maximum constraint rate of the reactive power adjustment.

[0102] A global evaluation value acquisition unit is used to construct an objective function by maximizing the target value of the power factor, taking the coupling relationship between active power and reactive power as a constraint condition, performing fitness calculation on the updated node control parameters, and obtaining a global evaluation value of the graph structure.

[0103] A reactive output adjustment strategy determining unit is used to determine the reactive output adjustment strategy of the inverter according to the global evaluation value of the graph structure.

[0104] Furthermore, the reactive output adjustment strategy acquisition unit further includes:

[0105] The inverter contribution evaluation unit is used to evaluate the contribution of each inverter according to the location distance between the inverter and the load, reactive output capacity, response time, and transmission loss when the difference area includes multiple inverter nodes.

[0106] A reactive output acquisition unit is used to allocate reactive compensation requirements in the difference area according to the contribution of each inverter to obtain the reactive output of each inverter: Where N is the number of inverters participating in the differential area, Ci is the contribution of the i-th inverter, Q i is the reactive output of the i-th inverter, Q region Reactive power compensation demand.

[0107] Furthermore, the reactive power demand identification module 30 further includes:

[0108] A voltage change prediction unit is used to establish a time series model, perform model training through historical sample data, extract long-term voltage dependencies, and predict voltage changes at multiple moments in the future through a recursive neural network.

[0109] An abnormal risk determination unit is used to determine whether there is an abnormal risk in the voltage change by using a preset voltage fluctuation threshold, wherein when the duration of the continuous voltage change trend exceeding the preset voltage fluctuation threshold reaches an abnormal time range, it is determined that there is an abnormal risk.

[0110] The load peak identification unit is used to identify the future load peak through the smoothed load time series data using a local maximum detection algorithm to determine the load increase period and its load increase forecast amount.

[0111] A power factor analysis unit is used to perform time alignment according to the voltage change and load increase prediction, analyze the change of power factor, and determine the size and direction of reactive power demand.

[0112] It should be noted that the above-mentioned sequence of the embodiments of the present application is only for description and does not represent the advantages and disadvantages of the embodiments. And the above-mentioned specific embodiments of this specification are described. In addition, the processes depicted in the accompanying drawings do not necessarily require the specific order or continuous order shown to achieve the desired results. In some embodiments, multitasking and parallel processing are also possible or may be advantageous.

[0113] The above description is only a preferred embodiment of the present application and is not intended to limit the present application. Any modifications, equivalent substitutions, improvements, etc. made within the spirit and principles of the present application should be included in the protection scope of the present application.

[0114] This specification and the drawings are merely exemplary illustrations of the present application and are deemed to cover any and all modifications, variations, combinations or equivalents within the scope of the present application. Obviously, a person skilled in the art may make various modifications and variations to the present application without departing from the scope of the present application. Thus, if these modifications and variations of the present application fall within the scope of the present application and its equivalents, the present application intends to include these modifications and variations.

Claims

1. A method for simulating the power factor of a distributed photovoltaic power station, characterized in that: The method comprises: Use measurement equipment to monitor the distribution network parameters of the substation in real time and obtain the substation monitoring parameters, including voltage, current, power factor, and load; Interactive inverter operation data to obtain power generation status and reactive power output capacity; The control center uses data analysis algorithms to analyze the monitoring parameters of the substation, predict voltage fluctuations and load changes, and identify reactive power demand; Taking the reactive power demand as the target, reactive output regulation control is performed according to the power generation state and reactive output capacity obtained through the interaction of the inverters, so that the power factor of the substation reaches the target value.

2. The method for simulating the power factor of a distributed photovoltaic power station according to claim 1, characterized in that: The interactive inverter operation data previously included: The communication protocol is used to establish an interactive communication connection between the inverter and the power grid. The inverter reports the power generation status and reactive power output capacity to the power grid in real time, receives power grid instructions, and adjusts reactive power output according to the power grid instructions. The inverter comprises one or more inverters.

3. The method for simulating control of power factor of a distributed photovoltaic power station according to claim 2, characterized in that: Also includes: When there are multiple inverters, obtaining the distribution positions of the inverters and their connection relationships; With each inverter as a node and the connection relationship as an edge, a graph structure is constructed to obtain an inverter collaborative network. When performing useless power regulation and control analysis, the inverter is positioned and adjusted based on the inverter collaborative network, and the adjustment strategy is analyzed.

4. The method for simulating the power factor of a distributed photovoltaic power station as claimed in claim 3, characterized in that: Taking the reactive power demand as the target, reactive output regulation control is performed according to the power generation state and reactive output capacity obtained by the inverter interaction, so that the power factor of the substation reaches the target value, including: The attributes of the node include the active power, reactive output capacity, physical location, and distance from the load of the inverter; the edges between the nodes represent the connection relationship between the inverters, and the weights of the edges are set according to the response time and transmission loss of the voltage regulation; according to the reactive power demand, the path search is performed through the graph structure to obtain the reactive compensation path; According to the reactive power compensation path, taking the reactive power demand as the target, performing node compensation parameter analysis to obtain node control parameters; Based on the graph structure, the node control parameters are optimized and adjusted for the power factor of the entire substation until the target value is reached, and the reactive output adjustment strategy of the inverter is determined.

5. The method for simulating control of power factor of a distributed photovoltaic power station according to claim 4, characterized in that: The method of performing path search through a graph structure according to reactive power demand to obtain a reactive compensation path includes: Determine the load location according to the reactive power demand, and use the load location as the starting node, wherein the distance of the starting node is set to 0, and the initial distances of the remaining nodes are set to infinity; Based on the graph structure, all inverter nodes connected to the initial node are traversed, and the node with the shortest distance is searched according to the distance between the nodes and the edge weight, and the node is added to the priority queue; All connected inverter nodes are traversed in sequence, and the shortest path record is updated until all nodes are visited, and the shortest path is output from the priority queue to obtain the reactive power compensation path.

6. The method for simulating control of power factor of a distributed photovoltaic power station according to claim 4, characterized in that: Based on the graph structure, the node control parameters are optimized and adjusted for the power factor of the entire substation until the target value is reached, and the reactive output adjustment strategy of the inverter is determined, including: Calculating the regional power factor of each node according to the node control parameter, performing difference calculation between the regional power factor and the target value, and determining the difference area; According to the graph structure, the difference area is projected into the graph structure, the difference area is used as the optimization target, the node control parameter is used as the starting point, the optimization direction is determined by the difference value, and the node control parameter is updated, wherein the step size of the optimization adjustment is determined according to the maximum constraint rate of the reactive power adjustment; The objective function is constructed by maximizing the target value of the power factor, the coupling relationship between active power and reactive power is used as a constraint condition, the fitness of the updated node control parameters is calculated, and the global evaluation value of the graph structure is obtained; A reactive output adjustment strategy of the inverter is determined according to the global evaluation value of the graph structure.

7. The method for simulating control of power factor of a distributed photovoltaic power station according to claim 6, characterized in that: When the difference area includes multiple inverter nodes, the contribution of each inverter is evaluated according to the location distance between the inverter and the load, reactive output capacity, response time, and transmission loss; According to the contribution of each inverter, the reactive power compensation demand in the difference area is allocated to obtain the reactive power output of each inverter: Where N is the number of inverters participating in the differential area, C i is the contribution of the i-th inverter, Q i is the reactive output of the i-th inverter, Q region Reactive power compensation demand.

8. The method for simulating control of power factor of a distributed photovoltaic power station according to claim 1, characterized in that: The identifying reactive power demand comprises: Establish a time series model, train the model through historical sample data, extract the long-term dependency of voltage, and predict voltage changes at multiple moments in the future through recursive neural networks; Using a preset voltage fluctuation threshold to determine whether the voltage change has an abnormal risk, wherein when the duration of the continuous voltage change trend exceeding the preset voltage fluctuation threshold reaches an abnormal time range, it is determined that there is an abnormal risk; Through the smoothed load time series data, the local maximum detection algorithm is used to identify the future load peak, determine the load increase period and its load increase forecast; Time alignment is performed based on the voltage change and load increase forecast, the change in power factor is analyzed, and the size and direction of reactive power demand are determined.

9. A simulation control device for power factor of a distributed photovoltaic power station, characterized in that: The device comprises: The substation monitoring parameter acquisition module uses a measuring device to monitor the distribution network parameters of the substation in real time to obtain the substation monitoring parameters, including voltage, current, power factor, and load; An operation data interaction module, which is used to interact with inverter operation data to obtain power generation status and reactive power output capacity; A reactive power demand identification module, wherein the reactive power demand identification module is used for the control center to analyze the monitoring parameters of the substation using a data analysis algorithm, predict voltage fluctuations and load changes, and identify reactive power demand; The reactive output regulation control module is used to take the reactive power demand as the target, and perform reactive output regulation control according to the power generation state and reactive output capacity obtained through the interaction of the inverters, so that the power factor of the substation reaches the target value.

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