A bidirectional grid-connected control system for small power energy storage converters

Abstract

The invention discloses a bidirectional grid-connected control system for a small-power energy storage inverter, and relates to the technical field of inverter grid-connected control. Aiming at the needs of the small-power energy storage inverter in a restricted scattering environment, a communication and control scheme is proposed, a channel attenuation matrix and an interference feature list are generated by measuring point layout and a multi-factor attenuation function, and a channel environment model is formed by nonlinear fitting; a multi-node multi-band communication topology is constructed and feasible routes are screened, the optimal or alternative combination is dynamically solved and the network topology configuration is output; multi-dimensional scoring and multi-path capacity allocation are performed on data streams with different sensitivities, and high-priority data is preferentially scheduled to a better route; when the network abnormality cannot be restored, the local buffering and offline control algorithm can calculate the inverter operating parameters based on the cached data and perform load reduction protection, and smoothly switch back to the online mode after the network is restored, so as to ensure that the energy storage inverter is still safe and controllable in the disconnected state.

Description

Technical Field

[0001] The present invention relates to the technical field of converter grid-connected control, and in particular to a bidirectional grid-connected control system for a small-power energy storage converter. Background Art

[0002] Against the backdrop of the rapid development of distributed energy, small-power energy storage converters are increasingly being used in independent power supply or grid-connected systems in homes, commercial buildings and remote areas. Such converters often need to operate in environments such as basements, parking lots, densely built areas or agricultural buildings far from the main power grid. These scenarios are usually characterized by closed spaces, numerous obstacles and complex wireless propagation paths, which make communication channels prone to severe attenuation, reflection or multipath interference. At the same time, the loads on the microgrid or user side change frequently and unpredictably in terms of time periods and demands, which puts energy storage converters under great pressure in terms of power scheduling, grid interaction and data communication. If there is a lack of real-time monitoring and adaptive control methods for the combined effects of low-power operation and changing environments, the system's operating efficiency and safety are easily restricted.

[0003] In the Chinese invention patent with the authorization announcement number CN110266044B, a microgrid grid-connected control system and method based on energy storage converter is publicly proposed. First, the virtual sine and cosine function is used to quickly detect the negative sequence current, harmonics and reactive current of the grid; a proportional resonant controller is used to realize power output control and frequency division compensation control of the microgrid grid-connected current reactive power and harmonics according to the system margin, and multi-objective control of the energy storage converter is performed; the compensation and balance of the microgrid grid-connected current can be realized, and the power quality of the microgrid can be improved. At the same time, due to the complex design of the control parameters of the proportional resonant controller, the online adjustment of the proportional resonant parameters is combined with the fuzzy algorithm, so that the system has better dynamic performance.

[0004] Existing grid-connected control solutions for small-power energy storage devices often cannot fully cope with the dual challenges of complex wireless environments and load dynamics. Specifically, when the network quality fluctuates greatly due to scattering, shadowing, etc., the converter cannot continue to receive key control instructions from the central dispatch or remote server, which can easily lead to safety hazards such as grid-connected power output deviation and instantaneous voltage and current overshoot. In addition, once the communication link is interrupted, some systems lack edge-side buffering and offline control mechanisms, making it difficult to make local decisions in time based on battery charge status and load changes, resulting in the failure of charging and discharging strategies and causing problems such as battery over-discharge, short-term power outages, or grid instability.

[0005] To this end, the present invention provides a bidirectional grid-connected control system for a small-power energy storage converter. Summary of the invention

[0006] 1. Technical issues to be resolved In view of the deficiencies in the prior art, the present invention provides a bidirectional grid-connected control system for a small-power energy storage inverter. According to the needs of the small-power energy storage inverter in a restricted scattering environment, a communication and control scheme is proposed. A channel attenuation matrix and an interference feature list are generated through measurement point layout and a multi-factor attenuation function, and a channel environment model is formed through nonlinear fitting; a multi-node multi-band communication topology is constructed and feasible routes are screened, and the optimal or alternative combination is dynamically solved and the network topology configuration is output; multi-dimensional scoring and multi-path capacity allocation are performed on data streams with different sensitivities, and high-priority data is preferentially scheduled to a better route; when the network abnormality cannot be restored, the local buffering and offline control algorithm can calculate the inverter operating parameters based on the cached data and perform load reduction protection, and smoothly switch back to the online mode after the network is restored, so as to ensure that the energy storage inverter is still safe and controllable in the disconnected state; a set of technical solutions with both communication reliability adaptive strategy and offline control guarantee are proposed to ensure that the small-power energy storage inverter can still safely and stably perform grid-connected control and realize efficient energy management in a restricted scattering environment, thereby solving the technical problems raised in the background technology.

[0007] (II) Technical solution To achieve the above objectives, the present invention is implemented through the following technical solutions: a bidirectional grid-connected control system for a small power energy storage converter, comprising: deploying a number of measuring points in a target deployment area, measuring and recording radio frequency indicators and environmental parameters, integrating the measuring point data into a channel attenuation matrix and an interference feature list through a multi-factor attenuation function and path integral, performing nonlinear fitting and correlation on the integrated data, and obtaining a channel environment model; Generate a multi-node and multi-band communication topology structure, screen feasible routes according to the channel attenuation threshold and include them in the candidate set; build a communication quality prediction model and quantitatively analyze the core indicators of each candidate route, dynamically solve the optimal or alternative route combination, and output the network topology configuration plan; The transmission indicators are scored in multiple dimensions according to the different sensitivities of data categories, and the distinction between instantaneous and cumulative interference is strengthened. High-priority data is injected into routes and frequency bands with better scores through multi-path capacity allocation, and ordinary data is limited or sent later. The current grid-connected instructions, battery SOC and operating history data are written into the local buffer unit. The offline control algorithm calculates the operating parameters of the inverter based on the local prediction model. Local load reduction protection is performed for over-limit conditions or fault risks and alarms are recorded. After the network is restored, data is synchronized with the remote end and smoothly switched back to online mode.

[0008] Furthermore, the distance mark of each measuring point , measuring point coordinates and nearby obstacle characteristics Record; for each possible working frequency band, measure the received signal strength indicator in turn and packet loss , stored in the initial environment tag table; Define a multi-factor attenuation function for the measurement point In the working frequency band The comprehensive attenuation is calculated as When all measurement points and all possible frequency bands Calculate the comprehensive attenuation one by one , and record the result in matrix form as , combined with the number of packet losses and received signal strength indicator , fuse the interference intensity reference value in the same matrix dimension; Extract key interference feature sets based on obstacle type or spatial distribution and compare them with the measurement point coordinates. Correspondingly, a list of interference features is formed.

[0009] Furthermore, a multidimensional nonlinear fitting matrix And interference feature list for multi-parameter fitting, generate any coordinate and carrier frequency band Quickly estimate the attenuation value as a function of the interference factor: In the formula represents a function mapping trained by a machine learning algorithm using the channel attenuation matrix and the interference feature list obtained in step 102; The above fitting function is encapsulated and stored in the channel environment model, and the parameter index is retained; the final output channel environment model includes: obstacle interference feature index, reference correction value corresponding to the frequency band , channel attenuation function , the correspondence between spatial coordinates and measuring point numbers.

[0010] Furthermore, based on the environmental attributes and geographic coordinate information of each measuring point, combined with the actual installation location of the energy storage converter and the location of the optional access point, a potential communication node set is generated. , each node in the set All contain corresponding coordinates and available frequency bands ; For node collection Any two nodes and , retrieve its frequency band from the channel environment model The attenuation value under If the attenuation value exceeds the tolerable threshold, the link is switched to Otherwise, it is temporarily recorded as a candidate link and included in subsequent routing calculations.

[0011] Furthermore, based on the candidate links, a graph search method is used to generate a set of feasible routing sets under various available frequency bands. ; Each route Record the node sequence passed and the available bandwidth and reference delay of the corresponding link; Output candidate route set records, which contain available frequency bands The feasible paths under the condition are obtained, and the attenuation and interference parameters in the channel environment model are associated with each path.

[0012] Furthermore, in order to comprehensively evaluate the quality of candidate routes, the following multidimensional routing weight vector is defined: : in: Indicates the route In the frequency band The estimated packet loss coefficient under Indicates the estimated delay; Indicates the available bandwidth indicator; All candidate paths Multidimensional routing feature values ​​at the predicted time or time period The data are summarized and constructed into a communication quality prediction model.

[0013] Furthermore, combined with the grid-connected control requirements of the energy storage converter and the potential transmission capacity requirements, the objective function is set , select one or more key dimensions in the transmission index for optimization, and define a composite objective function: in is a weighting factor that can be allocated according to priority; Among all the route and frequency band combinations output by the communication quality prediction model, select The smallest several paths are taken as the main candidates, and the selected optimal or alternative paths and their corresponding frequency bands, estimated transmission capacity, priority and other information are integrated to form a network topology configuration plan.

[0014] Furthermore, the data stream to be transmitted is divided into categories such as key grid control instructions, battery status data, and general monitoring information. Each category is indexed by Indicates that for data categories In routing , frequency band The scoring value under the condition defines the multi-dimensional scoring function : is a three-dimensional index vector, a weighted matrix , dimension , is the data category The designed weight or penalty matrix, is the upper limit of time integral; For additional routing / band environment correction items, Representation and Routing and frequency band Related topological features or environmental markers, is a one-dimensional weight vector, is the real-time interference correction; For all data categories The actual transmission demand is calculated according to the comprehensive scoring function. Sort by size and map the data categories to the corresponding priority queues.

[0015] Further, one or more routes suitable for the high priority data volume are selected from the network topology configuration scheme. And the corresponding frequency band In order to distribute data load among multiple feasible paths and reduce the risk of packet loss and delay, the following multi-path capacity allocation formula is introduced to obtain the capacity allocation coefficient : Among them, obtain the capacity allocation coefficient Indicates the data category In routing , Frequency Band The capacity allocation coefficient on For all currently available options Combine candidate sets; For data category Sensitivity tuning coefficient of Based on capacity allocation factor The quality of each data category is determined by the corresponding traffic ratio. Calculated capacity allocation factor , and issue specific scheduling instructions to network nodes.

[0016] Furthermore, each active route is continuously monitored during the multipath scheduling process. The actual packet loss rate and delay are detected. If an abnormal increase is detected or the difference with the communication quality prediction model is too large, the instant switching logic is triggered; Once it is determined that switching is required, new transmission control instructions and priority settings are quickly output to the corresponding network nodes based on the multi-path capacity allocation alternative plan.

[0017] Furthermore, if the current route is found The measured packet loss rate or delay value is significantly different from the predicted value in the communication quality prediction model, and the cumulative difference exceeds the difference threshold. , then a network anomaly alarm is triggered; the following formula is used to measure network anomaly : in, is the measured packet loss rate, For the communication quality prediction model at time The predicted value of packet loss rate, Indicates the length of the abnormal evaluation interval; when When A serious exception occurs and it is necessary to immediately evaluate whether there are other feasible routes available: if there is no feasible route, enter offline mode.

[0018] Furthermore, if there is still no available alternative route after abnormal determination, an offline mode activation signal will be sent to the local buffer unit; the control algorithm module will be notified to prepare to switch to the offline control strategy so that key parameters such as the grid-connected power, output voltage / current reference, etc. of the energy storage inverter can be stably controlled without remote communication.

[0019] The minimum required historical data is written into the security cache area, and multi-level version management is adopted for key grid-connected parameters. The latest version parameters are marked as , historical versions are marked as , Indicates the storage order or time slice; uses the priority of key grid-connected parameters and common monitoring data to set the capacity allocation of the cache area.

[0020] Furthermore, the offline control algorithm is loaded to take over the output power, charge and discharge instructions and safety protection logic of the converter; the offline control algorithm can adopt a local prediction model based on the state equation; When the battery SOC approaches the limit threshold, or the converter temperature is detected to be too high, the offline control algorithm activates protection measures without remote instructions, including automatic load reduction or limiting the charge and discharge power. Refer to the fault diagnosis table inside the system, make local records of alarms that require manual intervention, and report them to the remote platform when the network is restored next time; While the offline mode continues to execute, check whether the network is restored by using minimum power consumption or low-speed polling; When the network status improves significantly and satisfies ,First, confirm that the network link is stable through a verification mechanism, and then the cached data is bidirectionally synchronized with the remote system.

[0021] (III) Beneficial effects The present invention provides a bidirectional grid-connected control system for a small power energy storage converter, which has the following beneficial effects: Through a multi-step, full-process technical solution, the communication reliability of small-power energy storage inverters in restricted scattering environments is deeply combined with adaptive grid-connected control, effectively making up for the shortcomings of existing technologies in complex deployment scenarios. Specifically, it has the following beneficial effects: Through the comprehensive calculation of multi-factor attenuation functions, environmental impact matrices and interference feature lists, it is possible to provide refined measurements of multiple scattering, obstacle penetration and frequency band differences in non-ideal scenarios such as basements and remote farms, forming a "channel environment model" to lay a solid foundation for subsequent network topology design.

[0022] With the help of network topology configuration and communication quality prediction model, the optimal or alternative communication path is selected from the bandwidth, delay, packet loss and other indicators of candidate routes and frequency bands, so that small-power energy storage inverters can still obtain highly reliable data interaction channels under limited bandwidth and unstable channels. On this basis, the adaptive transmission strategy uses multi-dimensional scoring functions and capacity allocation formulas to prioritize grid-connected control instructions, battery status data and general monitoring information and dynamically allocate bandwidth. Once congestion occurs or key indicators deteriorate significantly, the route can be switched immediately to ensure the real-time and integrity of key data.

[0023] When a serious abnormality occurs in the network and cannot be repaired, the local buffering and offline control strategy can perform predictive calculations based on the cached grid-connected instructions and battery historical data to ensure that the energy storage inverter maintains the safety and controllability of voltage, current, and charging and discharging processes in the event of a temporary loss of connection; it also has fault detection and automatic load reduction capabilities to prevent battery over-discharge or overheating failure. After the network is restored, the system can automatically complete data synchronization and smoothly switch back to online mode.

[0024] The multiple links from channel modeling, network topology design to adaptive scheduling and offline control are progressively advanced, which not only enhances the applicability of wireless communication in closed or remote environments, but also ensures the grid-connected stability and safety of energy storage inverters, significantly improving the adaptability of application scenarios and overall operating efficiency of small-power energy storage systems. BRIEF DESCRIPTION OF THE DRAWINGS

[0025] Figure 1 The present invention is a schematic diagram of the structure of a bidirectional grid-connected control system for a small power energy storage converter. DETAILED DESCRIPTION

[0026] The following will be combined with the drawings in the embodiments of the present invention to clearly and completely describe the technical solutions in the embodiments of the present invention. Obviously, the described embodiments are only part of the embodiments of the present invention, not all of the embodiments. Based on the embodiments of the present invention, all other embodiments obtained by ordinary technicians in this field without creative work are within the scope of protection of the present invention.

[0027] See also Figure 1 The present invention provides a bidirectional grid-connected control system for a small power energy storage converter, comprising: Step 1: Set up several measurement points in the target deployment area, measure and record the RF indicators and environmental parameters, integrate the measurement point data into the channel attenuation matrix and interference feature list through multi-factor attenuation function and path integral, perform nonlinear fitting and correlation on the integrated data, and obtain the channel environment model; Step 101: deploy several fixed measuring points at the deployment site, and perform initial measurement and marking of environmental parameters and radio frequency signal indicators at each location according to the preset measurement routes and measuring point numbers. The specific technical logic is as follows: Use mobile or fixed acquisition equipment to mark the distance of each measuring point , measuring point coordinates and nearby obstacle characteristics Record; measure the received signal strength indicator for each possible operating frequency band (such as 24GHz, 5GHz or a specific frequency band of LoRa, etc.) and packet loss , while recording the acquisition time In order to associate the time variable later; The measurement point number, coordinate information, obstacle type and RF measurement value are stored in the initial environment marking table. All measurement points complete the preliminary measurement and marking of environmental parameters and RF indicators. When in use, through the systematic measurement of the distance, coordinates and obstacle types of the measuring points, the real situation of the deployment area in terms of spatial distribution, terrain structure and potential shielding factors can be fully understood, providing an accurate basis for subsequent model construction; the signal strength, packet loss number, etc. of possible frequency bands such as 2.4GHz, 5GHz, LoRa, etc. are collected and recorded one by one, so that the system can evaluate the feasibility or advantages and disadvantages of different frequency bands in multiple dimensions in subsequent design, and can take into account the characteristics of multiple frequency bands; these measuring point numbers, obstacle characteristics and real-time collection results are uniformly stored in the initial environment tag table, which helps to ensure data consistency, support the scalability of subsequent algorithm analysis, and realize unified data management; Step 102: By establishing a multi-factor attenuation function, the channel attenuation and interference conditions of each measuring point are integrated and calculated to generate a channel attenuation matrix and extract interference characteristics. The core technical logic is as follows: Define a multi-factor attenuation function for the measurement point In the working frequency band The comprehensive attenuation is calculated as When introducing the environmental impact matrix The combined form with the path integral is defined as follows: Where: Indicates measuring point In the frequency band The comprehensive attenuation under the condition is used to compare with the measured received signal strength indicator in the subsequent steps. And the number of lost packets Compare or merge the differences to form the final channel attenuation matrix and interference feature list. The larger the value, the more serious the attenuation of the wireless signal. The environmental impact matrix E discretizes the overall test scene into several grids or blocks (such as coordinate grids), and defines an environmental impact vector for each grid (including humidity, temperature, wall material, scattering coefficient, etc.). These vectors are combined to form the environmental impact matrix E. When you are in the environment, you can use the environmental impact matrix The index in the measurement point environment vector is obtained , i.e. measuring point The corresponding environmental impact vector.

[0028] Band weight vector , indicating the frequency band The weighted coefficients of each component of the environmental impact vector under the same conditions as the environmental vector of the measuring point After vector dot multiplication, the basic attenuation of the measurement point in the corresponding frequency band can be obtained, which is obtained through machine learning or empirical calibration in the early stage, and may be adapted and adjusted for different regions in the future; Measurement point environment vector , from the environmental impact matrix The points extracted from The corresponding environmental attribute vector, such as humidity, temperature, and scattering coefficient; reflects the static or semi-static environmental factors in the area where the measuring point is located.

[0029] Path Collection , refers to the distance from the transmitting source (or reference source) to the measuring point The set of discrete paths passed may include several grids or regions. The path can be determined by the shortest path algorithm or a multipath model based on beam direct / reflection / diffraction; is the path along the integral The variable can usually be understood as a distance or some path parameter, which changes with the path discreteness; is the instantaneous attenuation coefficient on the path integration segment, Indicates the path location The type of medium or obstacle at the location; this function can be determined by the local obstacle refraction / reflection characteristics, material penetration loss, and frequency band The attenuation law of the path integral term is used to accumulate the local attenuation effect, making the modeling of complex scenes (multi-path reflection, wall penetration, diffraction, etc.) more accurate; Representation and measurement points Main types of surrounding obstacles Related offset or compensation items, when the measuring point When there are large-scale or special material obstacles, The value of reflects the additional impact of the area on attenuation. In actual calculations, it can be positive or negative. For all measurement points and all possible frequency bands Calculate the comprehensive attenuation one by one , and record the result in matrix form as , combined with the number of packet losses and received signal strength indicator , the interference intensity reference value is integrated in the same matrix dimension; in the matrix After the calculation is completed, the key interference feature set is further refined according to the obstacle type or spatial distribution, such as extreme loading positions, high interference areas, etc., and is compared with the measurement point coordinates. Make corresponding connections and form a list of interference features; When used, the combination of the environmental impact matrix and the path integral can provide a more sophisticated cumulative modeling of complex scattering, reflection and other factors, avoiding the errors caused by the traditional simple distance model. After calculating the channel attenuation matrix, the measurement points that may have extreme attenuation or high interference are aggregated and analyzed to form an interference feature list, providing a direct reference for risk management during network planning.

[0030] Step 103: Based on the channel attenuation matrix and the interference feature list, a deeper level of fitting and model solidification is performed to output the final channel environment model for subsequent network topology design and communication quality prediction. The specific technical logic is as follows: a multi-dimensional nonlinear fitting or machine learning algorithm (such as Gaussian process regression based on kernel function, etc.) is used to fit the matrix And interference feature list for multi-parameter fitting, generate any coordinate and carrier frequency band Quickly estimate the attenuation value as a function of the interference factor: In the formula represents a function mapping trained by a machine learning algorithm using the channel attenuation matrix and the interference feature list obtained in step 102; The above fitting function is encapsulated and stored in the channel environment model, and the parameter indexes such as frequency band, coordinates, obstacle type, etc. are retained respectively, so that the corresponding attenuation and interference estimation values ​​can be quickly obtained when querying any coordinates and frequency bands in the subsequent steps; the final output channel environment model includes: obstacle interference feature index, reference correction value corresponding to the frequency band , channel attenuation function , the correspondence between spatial coordinates and measuring point numbers; When in use, the fitted attenuation function and interference information are encapsulated in the channel environment model, allowing the attenuation and interference estimation values ​​to be quickly obtained under any coordinate and frequency band combination, greatly reducing the complexity of subsequent topology design and prediction operations. Through the training and solidification of interference characteristics and multi-dimensional attenuation matrices, the model can be quickly updated when expanding to new coordinates, adding or removing obstacles, or adding new frequency bands. It has good versatility and scalability and can flexibly adapt to new scenarios.

[0031] Step 2: Generate a multi-node and multi-band communication topology structure, screen feasible routes according to the channel attenuation threshold and include them in the candidate set; build a communication quality prediction model and quantitatively analyze the core indicators of each candidate route, dynamically solve the optimal or alternative route combination, and output the network topology configuration plan; Step 201: Generate a set of potential communication nodes based on the environmental attributes and geographic coordinate information of each measuring point in the channel environment model obtained in step 1, combined with the actual installation location of the energy storage converter, the location of the optional access point, etc. , each node in the set All contain corresponding coordinates and available frequency bands ; For node collection Any two nodes and , retrieve its frequency band from the channel environment model The attenuation value under If the attenuation value exceeds the tolerable threshold, the link is switched to The link is marked as unavailable; otherwise, it is temporarily recorded as a candidate link and included in the subsequent routing calculation; Based on the candidate links, a graph search method (such as Dijkstra, A*, or custom multi-weighted search) is used to generate a set of feasible routing sets for each pair of key nodes (such as energy storage inverter device nodes and gateway nodes) under multiple available frequency bands. ; Each route Record the node sequence and the available bandwidth, reference delay and other information of the corresponding link to provide input for the next communication quality prediction; output candidate routing set records, which include available frequency bands The feasible paths under the condition of , and associate the attenuation and interference parameters in the channel environment model with each path; When in use, the deployment location of the energy storage inverter, the location of the optional access point, etc. are uniformly abstracted as nodes. Combined with the channel environment model in step 1, it can quickly determine in which frequency bands the communication between nodes is feasible, so as to clarify the communicative nodes and frequency bands; by retrieving the attenuation value between each candidate node, the links with excessive attenuation or exceeding the system threshold are automatically screened out, ensuring that the subsequent route search is only for the actual available links, reducing invalid calculations and eliminating unavailable links; Step 202: To comprehensively evaluate the quality of candidate routes, define the following multi-dimensional route weight vector: : in: Indicates the route In the frequency band The estimated packet loss coefficient under Indicates the estimated delay; Indicates the available bandwidth indicator; In order to achieve high-precision modeling of packet loss and delay, a prediction formula based on integration and environmental cumulative effects is introduced to obtain the estimated packet loss rate. : Where: represents the candidate path, Represents pairs of adjacent nodes in the path; For slave nodes To Node Spatial distance Position on the path The environmental feature vector at can be obtained by indexing from the channel environment model; For the frequency band The instantaneous coefficient of the cumulative packet loss attenuation is used to quantify the additional interference caused by the medium or obstacles to the signal; Corrections introduced to take into account multiple factors such as node switching overhead and potential collision domain diffusion; In this way, the links between different nodes can be accumulated section by section to obtain the estimated packet loss value of the entire route; the corresponding delay It can also be calculated by combining the transmission rate and processing time through similar principles, and fine-tuned based on the real-time / offline parameters provided by the channel environment model; Based on the available bandwidth estimation of the candidate path, the concurrent transmission and interference conditions of other nodes in the network are comprehensively considered to make a secondary correction to the available bandwidth of each link to form the final available bandwidth index. ; The collaborative prediction or bandwidth competition model can be used to dynamically estimate the bandwidth of multiple paths under different load conditions, and the results are also synchronously stored in the submodule of the communication quality prediction model; All candidate paths Multidimensional routing feature values ​​at the predicted time or time period Summarize and build a communication quality prediction model, covering multi-dimensional indicators such as packet loss, latency, bandwidth, etc. in different frequency bands, paths, and time windows. The model can be trained in time series as needed (for example, using deep neural networks or recursive models); The use of comprehensive metrics such as packet loss, latency, and bandwidth helps the system to make quantitative comparisons among multiple candidate paths, rather than just looking at a single indicator, improves the refinement of network deployment, and realizes multi-dimensional routing indicator evaluation; the introduction of integral calculations of obstacles and medium characteristics on the path segment can more realistically present the propagation loss of wireless signals in local scenarios, making the prediction results closer to reality. Incorporating the evaluation of concurrent transmissions of other nodes, the bandwidth resources can be further flexibly corrected during peak loads and idle times to avoid blindly overestimating or underestimating the available bandwidth of a certain path. The packet loss, latency, and bandwidth of each route at different times and environmental conditions are processed in a time series, which can be combined with machine learning or deep neural network training to have a certain self-learning ability.

[0032] Step 203: Combine the grid-connected control requirements of the energy storage converter and the potential transmission capacity requirements to set the objective function , select one or more key dimensions for optimization among transmission indicators such as packet loss, latency, and bandwidth, and define a composite objective function: in is a weighting factor that can be allocated according to priority; Among all the route and frequency band combinations output by the communication quality prediction model, select Several paths with the smallest (or largest bandwidth) bandwidth are selected as the main candidates and can be dynamically allocated according to different time periods. Alternative paths with no obvious differences are also listed to serve as switching reserves in subsequent adaptive scheduling.

[0033] The selected optimal or alternative paths and their corresponding frequency bands, estimated transmission capacity, priority and other information are integrated to form a network topology configuration plan. The plan includes: the available frequency bands and rated throughput of the physical or logical links between nodes, the priority recommended routes under different time windows or environmental conditions; the estimation of the packet loss and delay thresholds for each route; When in use, by weighted combination of multi-dimensional indicators such as packet loss, latency, bandwidth, etc., it can adapt to the specific needs of the system in different application scenarios (such as focusing on high bandwidth, low latency or high reliability, etc.), quickly select several optimal paths from all candidate combinations, and mark their priorities; when the network is running, switching or load distribution can be carried out at any time to improve communication reliability and efficiency and determine the optimal or alternative routes; key information such as frequency band, rated throughput, packet loss threshold, etc. are integrated in the same configuration plan to ensure that the system can directly reference it when implementing subsequent transmission strategies, greatly shortening the response time of deployment and scheduling.

[0034] Step 3: Perform multi-dimensional scoring on transmission indicators based on the different sensitivities of data categories, and strengthen the distinction between instantaneous and cumulative interference; inject high-priority data into routes and frequency bands with better scores through multi-path capacity allocation, limit the speed of ordinary data or delay its transmission, and trigger the switching of alternative routes in real time if the performance of the main route continues to deteriorate; Step 301: Divide the data stream to be transmitted into categories such as key grid-connected control instructions, battery status data, and general monitoring information. Each category is indexed by It indicates that the target routing performance requirements required in the communication quality prediction model in step 2 are also different.

[0035] Combined with packet loss indicators , Latency Indicators Bandwidth Index , and add the link status correction items obtained from real-time monitoring (e.g. attenuation correction caused by transient interference), For data categories In routing , frequency band The scoring value under the condition is defined as follows: : in: is a three-dimensional index vector, describing the time The following are the network indicators that are of most concern in this solution: Among them, the packet loss indicator Indicates at time For routing , frequency band Measurement of actual packet loss rate or packet loss coefficient, delay index Indicates at time For routing , Frequency Band The round-trip delay or latency characteristics, available bandwidth indicators Indicates time Available bandwidth or throughput metrics; Weighting Matrix , dimension , is the data category The designed weight or penalty matrix is ​​used to reflect the interaction between packet loss, delay and bandwidth. For example, if the key network connection instruction is extremely sensitive to both packet loss and delay, it can be Increase the weight of the corresponding position to make the scoring function more sensitive to the changes of these two indicators; in terms of numerical setting, it is generally required Be positive definite or semi-positive definite to ensure that the integral produces positive penalties for negative factors (such as packet loss) and can produce incentives or negative inhibition for positive factors (such as high bandwidth); is the upper limit of time integration, representing the data category The length of the time window concerned when conducting network quality assessment can be designed based on the real-time nature or fault tolerance of the data. Critical control instructions may only require a very short window to ensure a quick response, while ordinary monitoring information can use a longer window for comprehensive assessment. For additional routing / band environment correction items, Representation and Routing and frequency band Relevant topological features or environmental markers (such as the number of nodes, coverage, available access points, etc.) can be extracted from the network topology configuration scheme or channel environment model. is a one-dimensional weight vector, through The mapping calculation reflects the spatial advantages or disadvantages of specific paths or frequency bands, such as improving the score to prefer more stable or better covered frequency bands; This is a real-time interference correction value. When it is monitored that the network is experiencing instantaneous congestion or strong external interference causes packet loss or large fluctuations in delay, a quick correction can be made here and this item can be added to the integral result to achieve a sharp response to unexpected fluctuations.

[0036] For all data categories The actual transmission demand is calculated according to the comprehensive scoring function. The higher the score, the more sensitive the data in this category is to the network quality, or the selected The worse the combination, the higher the priority guarantee is needed (or the need to find a better route and frequency band is needed). The data category can be mapped to the corresponding priority queue; When in use, it is possible to distinguish data categories such as grid control instructions, battery status data, and general monitoring information, and to target the three major indicators of packet loss, latency, and bandwidth with different sensitivities, so that key data can be protected at a higher level. By adding real-time interference correction items to the scoring function, the difference between the communication quality prediction model and the current actual situation can be taken into account to prevent lags caused by relying solely on predictions. If a scoring method based on time integration and matrix weighting is used, the interaction effects between indicators such as packet loss and latency can be fully included, making the scoring results more reliable and accurate.

[0037] Step 302: According to the priority classification result obtained in step 301, one or more routes suitable for the high priority data volume are selected from the network topology configuration scheme generated in step 2. And the corresponding frequency band ,At the same time, other different routes can be selected for common monitoring data or ,secondary priority data to reduce interference with high priority data; In order to distribute data load among multiple feasible paths and reduce the risk of packet loss and delay, the following multi-path capacity allocation formula is introduced to obtain the capacity allocation coefficient : Among them, obtain the capacity allocation coefficient Indicates the data category In routing , Frequency Band The capacity allocation coefficient on The comprehensive scoring function defined in step 301; For data category The sensitivity tuning coefficient is used to amplify or reduce the impact of score differences on capacity allocation; Based on capacity allocation factor The smaller the score value (the better the network quality), the larger the capacity allocation coefficient; according to each data category Calculated capacity allocation factor , and sends specific scheduling instructions to network nodes, including: which data streams take which routes at which time periods, which frequency bands to use for the allocation ratio of multi-path parallel transmission of key data, and speed limit or delayed transmission strategies for ordinary monitoring data to avoid occupying too much bandwidth.

[0038] When in use, it makes full use of network redundancy and sends or distributes data streams in parallel on different paths. It can quickly divert traffic when congestion or attenuation increases on any path, thereby increasing the success rate of high-priority data. It performs index normalization allocation based on score differences, automatically directs traffic to routes and frequency bands with better scores, reduces the impact of main route bottlenecks on the overall transmission of the system, and realizes capacity allocation adaptation; it not only prioritizes the real-time nature of key data, but also reasonably arranges the transmission of ordinary monitoring data on the remaining bandwidth, making the overall bandwidth utilization rate higher and reducing unnecessary delays.

[0039] Step 303: Continuously monitor each active route during the multipath scheduling process. If the actual packet loss rate and delay are detected to be abnormally increased or the difference with the communication quality prediction model in step 2 is too large, the instant switching logic is triggered; Introduce the following switching judgment function: in: is the actual packet loss index at the current moment, It is the actual measured delay index at the current moment; is a nonlinear gain function, which is used to amplify the delay effect after exceeding a certain critical value, so as to trigger the switching more quickly; if Exceeding the preset threshold , then it is determined that the performance of this route is degraded, and it should be immediately switched to the next high-quality route selected in step 302.

[0040] Once it is determined that switching is required, according to the multi-path capacity allocation alternative scheme left in step 302, a new transmission control instruction and priority setting are quickly output to the corresponding network node, wherein: stop sending high priority data on the currently failed or degraded route; immediately enable the alternative route and perform the above calculation on the route. Allocate capacity; resynchronize the sending queues of key grid control instructions and battery status data.

[0041] When in use, the actual measured values ​​and predicted differences such as packet loss and delay are monitored synchronously. Once the degradation degree exceeds the threshold, the alternative route is switched immediately to avoid the high risk of packet loss for critical data for a long time, so as to achieve rapid detection and response to route degradation; through the multi-path allocation scheme pre-stored in step 302, the backup route can be quickly connected to ensure that the interruption of critical data during the switching process is minimized and seamless switching is completed; after the switch, the grid-connected instructions and battery data sending queues are synchronized immediately to achieve transparent switching of upper-level applications without affecting the logical continuity of the grid-connected control of the energy storage inverter.

[0042] Step 4: Write the current grid-connected instruction, battery SOC and operation history data into the local buffer unit, and use the offline control algorithm to calculate the inverter operation parameters based on the local prediction model, perform local load reduction protection for over-limit status or fault risk and record alarms, synchronize data with the remote end after the network is restored and smoothly switch back to online mode; Step 401: Receive the link monitoring result output from step 3 in real time. If the current route is found The measured packet loss rate or delay value is significantly different from the predicted value in the communication quality prediction model, and the cumulative difference exceeds the difference threshold. , then a network anomaly alarm is triggered; Use the following formula to measure network anomalies : in, is the measured packet loss rate, For the communication quality prediction model at time The predicted value of packet loss rate, Indicates the length of the abnormal evaluation interval; when When If a serious exception occurs, it is necessary to immediately evaluate whether there are other feasible routes available: if there is no feasible route, enter offline mode; If there is still no available alternative route after the above abnormal determination (or the alternative route is also in an abnormal state in the same time period), an offline mode activation signal will be sent to the local buffer unit; the control algorithm module will be notified to prepare to switch to the offline control strategy, so that the grid-connected power, output voltage / current reference and other key parameters of the energy storage inverter can be stably controlled without remote communication.

[0043] When in use, the difference between the measured packet loss and the predicted value is evaluated in an integral form, which can better distinguish between continuous degradation and instantaneous fluctuations and reduce the frequency of unnecessary offline switching. If there is no feasible route to choose from, the offline mode is automatically activated and an alarm signal is issued to ensure that the energy storage converter will not fall into an unprotected and dangerous state when the network is completely disconnected.

[0044] Step 402: Receive the latest batch of grid-connected control instructions, battery status data (including SOC, SOH) and historical operation information retained in step 3 and package and archive them in a local buffer unit; write the minimum required historical data (such as the charge and discharge records of the last few minutes or hours, voltage and current reference curves, etc.) into the safe cache area, so that the subsequent offline control algorithm can infer the real-time working status of the converter based on these data; Multi-level version management is used for key grid-connected parameters, and the latest version parameters are marked as , historical versions are marked as ( represents storage order or time slice), ensuring that any damaged or incomplete version can be replaced by an earlier version; Introduce hash verification or related encryption verification methods to generate verification information for each batch of cached data to prevent data corruption caused by unexpected power outages or cache failures, resulting in erroneous offline control; use the priority of key grid-connected parameters and general monitoring data to set the capacity allocation of the cache area: key data enjoys higher storage priority and longer retention time. When the local buffer unit space becomes tight, some historical general monitoring information will be automatically eliminated, and only the necessary grid-connected parameters and battery health data will be retained.

[0045] When in use, version management and hash verification can effectively prevent erroneous control caused by accidental damage to the cache, ensure that the energy storage converter can rely on the latest batch of complete and correct data in offline mode, and realize multi-level version protection of key data; priority-driven cache allocation can give priority to retaining key grid-connected parameters and battery health information when space is insufficient, taking into account system safety and storage efficiency. Prepare the necessary historical operating data and grid-connected instruction versions for the offline control algorithm, and enter autonomous control without additional waiting once switched offline.

[0046] Step 403: When step 401 determines to enter the offline mode and step 402 cache operation is completed, load the offline control algorithm to take over the output power, charge and discharge instructions and safety protection logic of the converter; the offline control algorithm uses a local prediction model based on the state equation to calculate the voltage of the converter. With current ( The reference trajectory is autonomously calculated: Where: The system matrix of the local model is dynamically adjusted according to the key grid-connected parameters and battery status data stored in the early stage. is the control gain mapping matrix; It means that the offline control algorithm is A correction given to keep power, frequency or voltage within safe limits.

[0047] When the battery SOC approaches the limit threshold, or the converter temperature is detected to be too high, the offline control algorithm activates protection measures without remote instructions, including automatic load reduction or limiting the charge and discharge power. Refer to the fault diagnosis table inside the system, make local records of alarms that require manual intervention, and report them to the remote platform when the network is restored next time; While the offline mode continues to execute, check whether the network is restored by using minimum power consumption or low-speed polling; When the network status improves significantly and satisfies ,First, the network link is confirmed to be stable through a verification mechanism and then the cached data is bidirectionally synchronized with the remote system; After the synchronization is completed, the offline control algorithm is gradually disabled, and the control is returned to the adaptive transmission strategy and real-time scheduling. The new grid-connected instructions and network strategy are updated to the converter control loop, and finally the online mode is restored.

[0048] Through state equations and rolling predictions, the energy storage inverter can still finely adjust the voltage, current and power output without remote commands, avoiding simple one-size-fits-all or shutdown strategies. When the battery or temperature exceeds the limit, the local algorithm can automatically reduce the load, limit the current and record the alarm to maintain the bottom line of system safety; after the network is restored, it will report uniformly. After the network is restored, the communication stability is confirmed first, and then all data is synchronized with the remote end. Finally, the control is transferred back to the online adaptive scheduling in an orderly manner to avoid secondary shocks caused by abrupt switching.

[0049] Those of ordinary skill in the art will appreciate that the units and algorithm steps of each example described in conjunction with the embodiments disclosed herein can be implemented in electronic hardware, or a combination of computer software and electronic hardware. Whether these functions are performed in hardware or software depends on the specific application and design constraints of the technical solution. Professional and technical personnel can use different methods to implement the described functions for each specific application, but such implementation should not be considered to be beyond the scope of this application.

[0050] Those skilled in the art can clearly understand that, for the convenience and brevity of description, the specific working processes of the systems, devices and units described above can refer to the corresponding processes in the aforementioned method embodiments and will not be repeated here.

[0051] In the several embodiments provided in the present application, it should be understood that the disclosed systems, devices and methods can be implemented in other ways. For example, the device embodiments described above are only schematic. For example, the division of the units is only some logical function divisions. There may be other division methods in actual implementation, such as multiple units or components can be combined or integrated into another system, or some features can be ignored or not executed. Another point is that the mutual coupling or direct coupling or communication connection shown or discussed can be through some interfaces, indirect coupling or communication connection of devices or units, which can be electrical, mechanical or other forms.

[0052] The units described as separate components may or may not be physically separated, and the components shown as units may or may not be physical units, that is, they may be located in one place or distributed on multiple network units. Some or all of the units may be selected according to actual needs to achieve the purpose of the solution of this embodiment.

[0053] The above is only a specific implementation of the present application, but the protection scope of the present application is not limited thereto. Any person skilled in the art who is familiar with the present technical field can easily think of changes or substitutions within the technical scope disclosed in the present application, which should be included in the protection scope of the present application. Therefore, the protection scope of the present application should be based on the protection scope of the claims.

Claims

1. A bidirectional grid-connected control system for small power energy storage converters, characterized in that: include, Several measurement points are deployed in the target deployment area to measure and record RF indicators and environmental parameters. The measurement point data are integrated into the channel attenuation matrix and interference feature list through multi-factor attenuation function and path integral. The integrated data is nonlinearly fitted and correlated to obtain the channel environment model. Generate a multi-node and multi-band communication topology structure, screen feasible routes according to the channel attenuation threshold and include them in the candidate set; build a communication quality prediction model and quantitatively analyze the core indicators of each candidate route, dynamically solve the optimal or alternative route combination, and output the network topology configuration plan; The transmission indicators are scored in multiple dimensions according to the different sensitivities of data categories, and the distinction between instantaneous and cumulative interference is strengthened. High-priority data is injected into routes and frequency bands with better scores through multi-path capacity allocation, and ordinary data is limited or sent later. The current grid-connected instructions, battery SOC and operating history data are written into the local buffer unit. The offline control algorithm calculates the operating parameters of the inverter based on the local prediction model. Local load reduction protection is performed for over-limit conditions or fault risks and alarms are recorded. After the network is restored, data is synchronized with the remote end and smoothly switched back to online mode.

2. The bidirectional grid-connected control system for a small power energy storage converter according to claim 1, characterized in that: Distance mark for each measuring point , measuring point coordinates and nearby obstacle characteristics Record; for each possible working frequency band, measure the received signal strength indicator in turn and packet loss , stored in the initial environment tag table; Define a multi-factor attenuation function for the measurement point In the working frequency band The comprehensive attenuation is calculated as When all measurement points and all possible frequency bands Calculate the comprehensive attenuation one by one , and record the result in matrix form as , combined with the number of packet losses and received signal strength indicator , fuse the interference intensity reference value in the same matrix dimension; Extract key interference feature sets based on obstacle type or spatial distribution and compare them with the measurement point coordinates. Correspondingly, a list of interference features is formed.

3. The bidirectional grid-connected control system for a small power energy storage converter according to claim 2, characterized in that: Based on multidimensional nonlinear fitting matrix And interference feature list for multi-parameter fitting, generate any coordinate and carrier frequency band Quickly estimate the attenuation value as a function of the interference factor: In the formula Represents the function mapping between the channel attenuation matrix and the interference feature list trained under the machine learning algorithm; The fitting function is encapsulated and stored in the channel environment model, and the parameter index is retained; the output channel environment model includes: obstacle interference feature index, reference correction value corresponding to the frequency band , channel attenuation function , the correspondence between spatial coordinates and measuring point numbers.

4. The bidirectional grid-connected control system for a small power energy storage converter according to claim 3, characterized in that: According to the environmental attributes and geographic coordinate information of each measuring point, combined with the actual installation location of the energy storage converter and the location of the optional access point, a potential communication node set is generated. , each node in the set All contain corresponding coordinates and available frequency bands ; For node collection Any two nodes and , retrieve its frequency band from the channel environment model The attenuation value under If the attenuation value exceeds the tolerable threshold, the link is switched to Otherwise, it is temporarily recorded as a candidate link and included in subsequent routing calculations.

5. The bidirectional grid-connected control system for a small power energy storage converter according to claim 4, characterized in that: Based on the candidate links, a graph search method is used to generate a set of feasible routing sets in multiple available frequency bands. ; Each route Record the node sequence passed and the available bandwidth and reference delay of the corresponding link; Output candidate route set records, which contain available frequency bands The feasible paths under the condition are obtained, and the attenuation and interference parameters in the channel environment model are associated with each path.

6. The bidirectional grid-connected control system for a small power energy storage converter according to claim 5, characterized in that: In order to comprehensively evaluate the quality of candidate routes, the following multidimensional routing weight vector is defined: : in: Indicates the route In the frequency band The estimated packet loss coefficient under Indicates the estimated delay; Indicates the available bandwidth indicator; All candidate paths Multidimensional routing feature values ​​at the predicted time or time period The data are summarized and constructed into a communication quality prediction model.

7. The bidirectional grid-connected control system for a small power energy storage converter according to claim 6, characterized in that: Combined with the grid-connected control requirements of the energy storage converter and the potential transmission capacity requirements, the objective function is set , select one or more key dimensions in the transmission index for optimization, and define a composite objective function: in is a weighting factor that can be allocated according to priority; Among all the route and frequency band combinations output by the communication quality prediction model, select The smallest several paths are taken as the main candidates, and the selected optimal or alternative paths and their corresponding frequency bands, estimated transmission capacity, and priority information are integrated to form a network topology configuration plan.

8. The bidirectional grid-connected control system for a small power energy storage converter according to claim 7, characterized in that: The data stream to be transmitted is divided into key grid-connected control instructions, battery status data, and general monitoring information. Each category is indexed Indicates that for data categories In routing , frequency band The scoring value under the condition defines the multi-dimensional scoring function : is a three-dimensional index vector, a weight matrix , dimension , is the data category The designed weight or penalty matrix, is the upper limit of time integral; For additional routing / band environment correction items, Representation and Routing and frequency band Related topological features or environmental markers, is a one-dimensional weight vector, is the real-time interference correction; For all data categories The actual transmission demand is calculated according to the comprehensive scoring function. Sort by size and map the data categories to the corresponding priority queues.

9. The bidirectional grid-connected control system for a small power energy storage converter according to claim 8, characterized in that: Select one or more routes from the network topology configuration that are suitable for the high-priority data volume And the corresponding frequency band In order to distribute data load among multiple feasible paths and reduce the risk of packet loss and delay, the following multi-path capacity allocation formula is introduced to obtain the capacity allocation coefficient : Among them, obtain the capacity allocation coefficient Indicates the data category In routing , Frequency Band The capacity allocation coefficient on For all currently available options Combine candidate sets; For data category Sensitivity tuning coefficient of Based on capacity allocation factor The quality of each data category is determined by the corresponding traffic ratio. Calculated capacity allocation factor , and issue specific scheduling instructions to network nodes.

10. The bidirectional grid-connected control system for a small power energy storage converter according to claim 9, characterized in that: Continuously monitor each active route during multipath scheduling The actual packet loss rate and delay are detected. If an abnormal increase is detected or the difference with the communication quality prediction model is too large, the instant switching logic is triggered; Once it is determined that switching is required, new transmission control instructions and priority settings are quickly output to the corresponding network nodes based on the multi-path capacity allocation alternative plan.

11. The bidirectional grid-connected control system for a small power energy storage converter according to claim 10, characterized in that: If the current route is found The measured packet loss rate or delay value is significantly different from the predicted value in the communication quality prediction model, and the cumulative difference exceeds the difference threshold. , then a network anomaly alarm is triggered; the following formula is used to measure network anomaly : in, is the measured packet loss rate, For the communication quality prediction model at time The predicted value of packet loss rate, Indicates the length of the abnormal evaluation interval; when When A serious exception occurs and it is necessary to immediately evaluate whether there are other feasible routes available: if there is no feasible route, enter offline mode.

12. The bidirectional grid-connected control system for a small power energy storage converter according to claim 11, characterized in that: If there is still no available alternative route after abnormal determination, an offline mode activation signal will be sent to the local buffer unit; the control algorithm module will be notified to prepare to switch to the offline control strategy so that the grid-connected power and output voltage / current reference of the energy storage inverter can be stably controlled without remote communication; The minimum required historical data is written into the security cache area, and multi-level version management is adopted for key grid-connected parameters. The current latest version parameters are marked as , historical versions are marked as , Indicates the storage order or time slice; uses the priority of key grid-connected parameters and common monitoring data to set the capacity allocation of the cache area.

13. The bidirectional grid-connected control system for a small power energy storage converter according to claim 12, characterized in that: Loading the offline control algorithm takes over the output power, charge and discharge instructions and safety protection logic of the converter; the offline control algorithm can adopt a local prediction model based on the state equation; When the battery SOC approaches the limit threshold, or the converter temperature is detected to be too high, the offline control algorithm activates protection measures without remote instructions, including automatic load reduction or limiting the charge and discharge power. Refer to the fault diagnosis table inside the system, make local records of alarms that require manual intervention, and report them to the remote platform when the network is restored next time; While the offline mode continues to execute, check whether the network is restored by using minimum power consumption or low-speed polling; When the network status improves significantly and satisfies ,First, confirm that the network link is stable through a verification mechanism, and then the cached data is bidirectionally synchronized with the remote system.

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