Distributed photovoltaic double-layer cooperative control system based on inter-group coordination and intra-group autonomy

Abstract

The invention relates to the technical field of distributed photovoltaic power generation, in particular to a distributed photovoltaic double-layer cooperative control system based on inter-group coordination and intra-group autonomy. The distributed photovoltaic double-layer cooperative control system based on inter-group coordination and intra-group autonomy comprises an intra-group autonomy control layer, an inter-group coordination control layer, a data acquisition module, a communication module, an energy storage management module and a load prediction module. According to the invention, through the inter-group coordination control layer, the current photovoltaic output, the energy storage adjustable power, the load demand and the key node voltage measurement value of each photovoltaic group can be collected in real time, the power surplus values are calculated, and when the power surplus values of adjacent photovoltaic groups exceed the preset threshold values at the same time, the system triggers cross-group power mutual aid and performs priority ranking, so that the power surplus values of the adjacent photovoltaic groups are calculated. And the photovoltaic group with the maximum power surplus is preferentially scheduled to supply power to the vacant group, so that the problem of light abandoning caused by lack of cross-group coordination in a traditional system is effectively solved, and the utilization efficiency of photovoltaic energy is improved.

Description

TECHNICAL FIELD

[0001] The present application relates to the field of distributed photovoltaic power generation technology, in particular to a distributed photovoltaic double-layer collaborative control system based on inter-group coordination and intra-group autonomy. BACKGROUND

[0002] With the large-scale access of distributed photovoltaic in rural areas, the existing photovoltaic control system faces new challenges in complex power grid environment. The traditional centralized control mode is difficult to adapt to the characteristics of node dispersion and significant fluctuation of light resources in rural distribution network, and the system relying solely on local autonomous control cannot realize cross-regional power exchange. Especially in the rural microgrid in the central and western regions of China where the light resources are rich but the grid-connected conditions are weak, the existing system has two outstanding problems:

[0003] 1. Lack of inter-group coordination: when multiple adjacent village photovoltaic groups simultaneously have excess output, the lack of regional coordination mechanism leads to a large amount of light abandonment. For example, in a highland village photovoltaic power station group, regional voltage out-of-limit often occurs due to the lack of cross-village coordination during the noon light peak period;

[0004] 2. Intra-group response delay: the coordinated control response speed of photovoltaic, energy storage and load within a single village is slow, which is difficult to respond to sudden changes in light intensity in rainy weather. For example, when sudden cloud cover occurs, the local weather forecast accuracy is insufficient, resulting in frequent power oscillation.

[0005] These problems seriously restrict the consumption efficiency and power supply reliability of rural distributed photovoltaic. In the prior art, there is no system that can simultaneously realize "intra-group rapid autonomy" and "inter-group dynamic coordination", and a new double-layer collaborative control scheme is urgently needed. SUMMARY

[0006] The purpose of the present application is to provide a distributed photovoltaic double-layer collaborative control system based on inter-group coordination and intra-group autonomy to solve the problems of lack of inter-group coordination and intra-group response delay in the background art.

[0007] To achieve the above purpose, the present application provides a distributed photovoltaic double-layer collaborative control system based on inter-group coordination and intra-group autonomy, which comprises an intra-group autonomous control layer, an inter-group coordination control layer, a data acquisition module, a communication module, an energy storage management module and a load prediction module.

[0008] The data acquisition module is used to acquire real-time output data of each photovoltaic group, energy storage state of charge, load demand data and weather data;

[0009] The communication module is used to realize data interaction between the intra-group autonomous control layer and the inter-group coordination control layer;

[0010] The energy storage management module is used to dynamically adjust the energy storage charging and discharging strategy according to the state of charge.

[0011] The load forecasting module is used to predict short-term load fluctuations based on historical data.

[0012] The inter-group coordination control layer is used to realize power mutual assistance and voltage coordinated regulation among multiple photovoltaic groups, specifically:

[0013] Data Acquisition and Preprocessing: Real-time acquisition of the current photovoltaic output of each photovoltaic cluster. Adjustable power of energy storage Load demand and key node voltage measurement values ;

[0014] Calculate the power surplus value of each photovoltaic cluster. For each photovoltaic cluster, according to the formula Calculate the power surplus value of each photovoltaic cluster. ;

[0015] Determine the trigger condition for cross-group power mutual assistance: preset threshold Check the power surplus of adjacent photovoltaic clusters. Does it exceed the preset threshold at the same time? ,like At the same time, exceeding If the power surplus is found to be excessive in the region, cross-group power exchange will be triggered, and priority will be assigned to prioritize the photovoltaic group with the largest power surplus to supply power to the group with the power deficit.

[0016] The autonomous control layer within the group is used to realize real-time coordinated control of photovoltaic units, energy storage units and loads within a single photovoltaic group.

[0017] As a further improvement to this technical solution, the specific steps for priority sorting are as follows:

[0018] Calculate the voltage deviation of the regional power grid ;

[0019] According to the formula Calculate the regulation margin of each photovoltaic cluster. ;

[0020] according to The values ​​are sorted from largest to smallest, and the photovoltaic clusters with the largest scheduling margin are given priority to participate in mutual assistance.

[0021] As a further improvement to this technical solution, the regional power grid voltage deviation The calculation formula is:

[0022]

[0023] in, For the first Real-time voltage measurements at key nodes, This is the rated voltage of the power grid. For the first The weight coefficients of key nodes are allocated according to the importance of node load or geographical location. The weight of the main transformer outlet node is 0.5, the weight of the village access point is 0.3, and the weight of the energy storage grid connection point is 0.2.

[0024] As a further improvement to this technical solution, the voltage coordination adjustment judgment needs to be performed simultaneously with the priority sorting, specifically as follows:

[0025] Preset threshold To reduce the voltage deviation of the regional power grid With preset threshold To make a comparison, if If the voltage exceeds the limit, it is determined to be a voltage overrun, triggering reactive power compensation regulation to suppress the voltage overrun.

[0026] As a further improvement to this technical solution, the specific operation steps of the reactive power compensation adjustment are as follows:

[0027] Based on the direction of voltage deviation, dynamically adjust the reactive power output of each photovoltaic cluster inverter:

[0028] During overvoltage: increase inductive reactive power to suppress voltage rise;

[0029] Under voltage conditions: Increase capacitive reactive power to support voltage recovery;

[0030] The adjustment amount is allocated proportionally, with priority given to photovoltaic clusters located near voltage over-limit nodes for regulation.

[0031] As a further improvement to this technical solution, the specific operation method for the autonomous control layer within a single photovoltaic cluster to achieve real-time coordinated control of photovoltaic units, energy storage units, and loads is as follows:

[0032] Real-time monitoring of light intensity abrupt change rate : Through the data acquisition module at fixed time intervals Collect the light intensity at the current moment and the light intensity at the previous moment According to the formula Calculate the abrupt change rate of light intensity ;

[0033] Determine if sudden changes in illumination exceed limits: Preset threshold The calculated light intensity abrupt change rate With preset threshold To make a comparison, when > When a significant change in light intensity occurs, the energy storage charging and discharging strategy is adjusted.

[0034] Calculate energy storage power adjustment: Obtain the current state of charge of the energy storage unit. and maximum state of charge According to the formula Calculate the adjustment amount of energy storage charging and discharging power. ,in, This is an adjustment coefficient used to balance the rate of change in light intensity with the energy storage response capability;

[0035] Dynamically optimize the photovoltaic output curve: Utilize the short-term load forecast results generated by the load forecasting module to obtain load demand for future periods. Combined with the current photovoltaic output Energy storage charging and discharging power adjustment amount and load demand in the future period Dynamically optimize photovoltaic power output target value To satisfy By adjusting the output power of the photovoltaic inverter, the actual output power can be made closer to that of the photovoltaic inverter. .

[0036] As a further improvement to this technical solution, the specific operation steps of the load forecasting module in predicting short-term load fluctuations based on historical data are as follows:

[0037] Obtain current load demand data and meteorological data, and obtain meteorological forecast data for future periods;

[0038] A feature matrix is ​​constructed using a long short-term memory network model. Its input layer contains lagged load values, meteorological data, and time-coded features, its hidden layer contains stacked LSTM units and learned time-series patterns, and its output layer contains load values ​​for predicted future periods.

[0039] Input the features into the trained model, output the load forecast curve for the short term, and obtain the load demand in the future period.

[0040] As a further improvement to this technical solution, the energy storage management module is also used for safety protection, specifically:

[0041] If the current state of charge ≥ Maximum state of charge If the charging is stopped, it will be forcibly stopped to prevent overcharging;

[0042] If the current state of charge Maximum state of charge If the discharge is stopped, it will be forcibly stopped to avoid over-discharge.

[0043] Compared with the prior art, the application has the beneficial effects:

[0044] 1. In the distributed photovoltaic double-layer collaborative control system based on inter-group coordination and intra-group autonomy, the current photovoltaic output, adjustable power of energy storage, load demand and key node voltage measurement value of each photovoltaic group are collected in real time through the inter-group coordination control layer, and the power surplus value is calculated. When the power surplus values of adjacent photovoltaic groups exceed the preset threshold value at the same time, the system triggers cross-group power mutual aid, performs priority sorting, and preferentially dispatches the photovoltaic group with the largest power surplus to supply power to the insufficient group, effectively solving the light abandonment problem caused by the lack of cross-group coordination in the traditional system, and improving the utilization efficiency of photovoltaic energy.

[0045] 2. In the distributed photovoltaic double-layer collaborative control system based on inter-group coordination and intra-group autonomy, when the regional power grid voltage deviation exceeds the preset threshold value, reactive power compensation adjustment is triggered, and the reactive power output of each photovoltaic group inverter is dynamically adjusted, so that the system can suppress voltage rise or support voltage recovery, effectively prevent voltage overrun, and improve the safety of the power grid. BRIEF DESCRIPTION OF DRAWINGS

[0046] Figure 1 The figure is a principle block diagram of the distributed photovoltaic double-layer collaborative control system based on inter-group coordination and intra-group autonomy. DETAILED DESCRIPTION

[0047] The technical solutions in the embodiments of the application will be described clearly and completely below with reference to the drawings in the embodiments of the application. Obviously, the described embodiments are only part of the embodiments of the application, rather than all the embodiments. Based on the embodiments in the application, all other embodiments obtained by those skilled in the art without creative work fall within the scope of protection of the application.

[0048] In a specific embodiment, as shown in Figure 1 a distributed photovoltaic double-layer collaborative control system based on inter-group coordination and intra-group autonomy includes an intra-group autonomous control layer, an inter-group coordination control layer, a data acquisition module, a communication module, an energy storage management module and a load prediction module.

[0049] The data acquisition module is used to collect output data, energy storage state of charge, load demand data and meteorological data of each photovoltaic group in real time. The communication module is used to realize data interaction between the intra-group autonomous control layer and the inter-group coordination control layer.

[0050] The energy storage management module is used to dynamically adjust the energy storage charging and discharging strategy according to the state of charge, and is also used for safety protection, specifically:

[0051] If the current state of charge ≥ maximum state of charge , then forcibly stop charging to prevent overcharging;

[0052] If the current state of charge < maximum state of charge , then forcibly stop discharging to avoid over-discharge.

[0053] The load forecasting module is configured to predict short-term load fluctuations based on historical data, specifically:

[0054] The load demand data and weather data at the current time are obtained, and weather forecast data for the future period is obtained;

[0055] A long short-term memory network model is used to construct a feature matrix, the input layer of which includes lagged load values, weather data, and time encoding features, the hidden layer of which includes stacked LSTM units and learning time series patterns, and the output layer of which includes predicted load values for the future period;

[0056] The features are input into the trained model, and a future short-term load prediction curve is output, obtaining the load demand in the future period.

[0057] The inter-group coordination control layer is configured to achieve power mutual aid and voltage collaborative regulation between multiple photovoltaic groups, specifically:

[0058] Step 1, data acquisition and preprocessing: real-time acquisition of real-time current photovoltaic output of each photovoltaic group , adjustable power of energy storage , load demand , and key node voltage measurement value ;

[0059] Step 2, calculate the power surplus value of each photovoltaic group : for each photovoltaic group, calculate the power surplus value of each photovoltaic group according to the formula ;

[0060] Step 3, determine the cross-group power mutual aid trigger condition: preset threshold , check whether the power surplus values of adjacent photovoltaic groups simultaneously exceed the preset threshold , if simultaneously exceed , then it is determined that the regional power is excessive, triggering cross-group power mutual aid, and the photovoltaic group with the largest power surplus is preferentially dispatched to supply power to the deficient group.

[0061] Step 4, perform priority sorting: calculate the regional grid voltage deviation according to the formula , where is the first ​Real-time voltage measurements at key nodes, This is the rated voltage of the power grid. For the first The weight coefficients of key nodes are allocated based on the importance of the node load or its geographical location. The weight of the main transformer outlet node is 0.5, the weight of the village access point is 0.3, and the weight of the energy storage grid connection point is 0.2, according to the formula. Calculate the regulation margin of each photovoltaic cluster. ,according to The values ​​are sorted from largest to smallest, and the photovoltaic clusters with the largest margin are prioritized for mutual assistance.

[0062] Step 5: Perform voltage coordination adjustment judgment: preset threshold To reduce the voltage deviation of the regional power grid With preset threshold To make a comparison, if If the voltage deviation exceeds a preset threshold, it is considered a voltage over-limit, triggering reactive power compensation regulation to suppress voltage over-limit. By using a preset voltage collaborative regulation threshold, when the regional grid voltage deviation exceeds the preset threshold, reactive power compensation regulation is triggered to dynamically adjust the reactive power output of each photovoltaic group inverter, suppressing voltage rise or supporting voltage recovery to prevent voltage over-limit.

[0063] Step 6: Perform reactive power compensation adjustment: Based on the direction of voltage deviation, dynamically adjust the reactive power output of each photovoltaic group inverter: When overvoltage occurs: increase inductive reactive power to suppress voltage rise; when undervoltage occurs: increase capacitive reactive power to support voltage recovery; the adjustment amount is distributed proportionally, and photovoltaic groups closer to the voltage over-limit node are given priority to participate in the adjustment.

[0064] Through the inter-group coordination control layer, the power surplus value of each photovoltaic group is collected and calculated in real time, triggering cross-group power mutual assistance. The photovoltaic group with the largest power surplus is prioritized to supply power to the group with a power deficit, effectively solving the problem of curtailment caused by the lack of cross-group coordination.

[0065] The specific operational method for the autonomous control layer within a photovoltaic group to achieve real-time coordinated control of photovoltaic units, energy storage units, and loads within a single photovoltaic group is as follows:

[0066] Step 1: Real-time monitoring of light intensity abrupt change rate : Through the data acquisition module at fixed time intervals Collect the light intensity at the current moment and the light intensity at the previous moment According to the formula Calculate the abrupt change rate of light intensity ;

[0067] Step 2: Determine if sudden changes in light intensity exceed limits: Preset threshold The calculated light intensity abrupt change rate with a preset threshold value When > , it is determined that the illumination intensity has a significant mutation, triggering the adjustment of the energy storage charging and discharging strategy.

[0068] Third step, calculate the energy storage power adjustment amount: obtain the current state of charge and the maximum state of charge of the energy storage unit, calculate the energy storage charging and discharging power adjustment amount according to the formula , wherein is the adjustment coefficient, used to balance the illumination mutation rate and the energy storage response ability;

[0069] Dynamic optimization of photovoltaic output curve: call the short-term load prediction result generated by the load prediction module to obtain the load demand in the future period , combined with the current photovoltaic output , the energy storage charging and discharging power adjustment amount and the load demand in the future period , dynamically optimize the photovoltaic output target value to meet , by adjusting the photovoltaic inverter output power, the actual output tends to . The group autonomous control layer monitors the illumination intensity mutation rate in real time, dynamically adjusts the energy storage charging and discharging strategy, and optimizes the photovoltaic output curve combined with the load prediction result, which improves the collaborative control response speed of photovoltaic, energy storage and load in the group, and effectively deals with the sudden change of illumination intensity in the sudden rain weather.

[0070] Working principle:

[0071] In the specific application process, the data acquisition module collects the illumination intensity at the current time and the illumination intensity at the previous time at fixed time intervals , and calculates the illumination intensity mutation rate according to the formula , then transmits the calculated illumination intensity mutation rate to the group autonomous control layer, and the group autonomous control layer compares the calculated illumination intensity mutation rate with a preset threshold value , when > , it is determined that the illumination intensity has a significant mutation, and transmits instructions to the energy storage management module, triggering the adjustment of the energy storage charging and discharging strategy, and at the same time, the strategy adjustment result is reported to the inter-group coordination control layer through the communication module.

[0072] Meanwhile, the short-term load prediction result generated by the load prediction module is called by the group autonomous control layer to obtain the load demand in the future period , combined with the current photovoltaic output , the energy storage charging and discharging power adjustment amount and the load demand in the future period , the photovoltaic output target value is dynamically optimized to meet , by adjusting the photovoltaic inverter output power, the actual output is close to , so as to dynamically optimize the photovoltaic output, and the optimization result is reported to the inter-group coordination control layer through the communication module.

[0073] In addition, the inter-group coordination control layer collects the current photovoltaic output , the energy storage adjustable power , the load demand and the key node voltage measurement value of each photovoltaic group in real time, and calculates the power surplus value of each photovoltaic group according to the formula for each photovoltaic group , while presetting a threshold value , checking whether the power surplus values of adjacent photovoltaic groups exceed the preset threshold value at the same time , if exceeds the preset threshold value at the same time , it is determined that the regional power is excessive, and the cross-group power mutual aid is triggered, the priority is sorted, and the photovoltaic group with the largest power surplus is preferentially dispatched to supply power to the shortage group.

[0074] At the same time, the data acquisition module collects real-time voltage measurement values, and calculates the regional power grid voltage deviation according to the formula , and inputs the calculated regional power grid voltage deviation to the inter-group coordination control layer, and compares the regional power grid voltage deviation with the preset threshold value , if , it is determined that the voltage is out of limit, and the reactive power compensation adjustment is triggered to suppress the voltage out of limit.

[0075] ​The above shows and describes the basic principles, main features and advantages of the present application. Those skilled in the art should understand that the present application is not limited to the above-mentioned embodiments, and the above-mentioned embodiments and descriptions in the specification are only preferred examples of the present application and are not intended to limit the present application. Various changes and improvements can be made to the present application without departing from the spirit and scope of the present application, and these changes and improvements all fall within the scope of the claimed present application. The scope of protection of the present application is defined by the appended claims and their equivalents.

Claims

1. A distributed photovoltaic double-layer collaborative control system based on inter-group coordination and intra-group autonomy, characterized in that, The system comprises an intra-group autonomous control layer, an inter-group coordinated control layer, a data acquisition module, a communication module, an energy storage management module and a load prediction module; The data acquisition module is configured to acquire output data of each photovoltaic group, state of charge of energy storage, load demand data and meteorological data in real time; The communication module is configured to realize data interaction between the intra-group autonomous control layer and the inter-group coordinated control layer; The energy storage management module is configured to dynamically adjust the charging and discharging strategy of the energy storage according to the state of charge; The load prediction module is configured to predict short-term load fluctuation based on historical data; The inter-group coordinated control layer is configured to realize power mutual aid and voltage collaborative regulation among a plurality of photovoltaic groups, specifically as follows: Data acquisition and pre-processing: real-time acquisition of the current photovoltaic output of each photovoltaic group , adjustable power of energy storage , load demand and key node voltage measurement ; calculating power surplus values for each photovoltaic cluster : for each photovoltaic cluster, calculating power surplus values for each photovoltaic cluster ;​ Determine the cross-group power mutual assistance trigger condition: preset threshold Check if the power surplus value of the adjacent photovoltaic group exceeds the preset threshold at the same time If exceeds the preset threshold at the same time , it is determined that the regional power is excessive, the cross-group power mutual assistance is triggered, and the photovoltaic group with the largest power surplus is preferentially dispatched to supply power to the group with the largest power shortage. The intra-group autonomous control layer is configured to realize real-time collaborative control of photovoltaic units, energy storage units and loads in a single photovoltaic group. 2.The distributed photovoltaic double-layer collaborative control system based on inter-group coordination and intra-group autonomy according to claim 1, characterized in that, The specific operation steps of the priority sorting are as follows: Computing regional grid voltage deviation ; According to the formula Calculate the regulation margin of each photovoltaic cluster. ; According to The values are sorted from large to small, and the photovoltaic group with the largest margin is preferentially dispatched to participate in mutual aid. 3.The distributed photovoltaic double-layer collaborative control system based on inter-group coordination and intra-group autonomy according to claim 2, characterized in that, The regional power grid voltage deviation The calculation formula is: wherein, is the real-time voltage measurement value of the th key node, is the grid rated voltage, is the weight coefficient of the th key node, which is assigned according to the importance of node load or geographical location, and the weight of the main transformer outlet node is 0.5, the weight of the village access point is 0.3, and the weight of the energy storage grid connection point is 0.

2.

4. The distributed photovoltaic double-layer collaborative control system based on inter-group coordination and intra-group autonomy according to claim 3, characterized in that, The priority sorting needs to be accompanied by voltage collaborative regulation, specifically as follows: Pre-set threshold value The regional power grid voltage deviation is compared with the pre-set threshold value If , it is determined that the voltage is out of limit, triggering reactive power compensation adjustment for suppressing voltage out of limit.

5. The distributed photovoltaic double-layer collaborative control system based on inter-group coordination and intra-group autonomy according to claim 4, characterized in that, The specific operation steps of the reactive power compensation regulation are as follows: According to the voltage deviation direction, the reactive power output of the inverter of each photovoltaic group is dynamically adjusted: When overvoltage occurs: increase inductive reactive power to suppress voltage rise; When under-voltage occurs: increase capacitive reactive power to support voltage recovery; The adjustment amount is distributed in proportion, and photovoltaic groups close to the voltage out-of-limit node are preferentially selected to participate in regulation.

6. The distributed photovoltaic double-layer collaborative control system based on inter-group coordination and intra-group autonomy according to claim 1, characterized in that, The specific operation method of the intra-group autonomous control layer to realize real-time collaborative control of photovoltaic units, energy storage units and loads in a single photovoltaic group is as follows: Real-time monitoring of light intensity mutation rate : through the data acquisition module at fixed time intervals acquire the light intensity at the current time and the light intensity at the previous time , according to the formula , calculate the light intensity mutation rate ; Determine whether the light intensity mutation is over limit: preset threshold The calculated light intensity mutation rate is compared with the preset threshold When > , it is determined that the light intensity has a significant mutation, and the energy storage charging and discharging strategy adjustment is triggered. Calculate the energy storage power adjustment amount: obtain the current state of charge of the energy storage unit and the maximum state of charge , calculate the energy storage charge and discharge power adjustment amount according to the formula , wherein is the adjustment coefficient, used to balance the sudden change rate of light and the response ability of energy storage;​ Dynamic optimization of photovoltaic output curve: call the short-term load forecasting result generated by the load forecasting module to obtain the load demand in the future period , combined with the current photovoltaic output , the energy storage charging and discharging power adjustment amount and the load demand in the future period , dynamically optimize the photovoltaic output target value so as to meet , and by adjusting the photovoltaic inverter output power, the actual output approaches .

7. The distributed photovoltaic double-layer collaborative control system based on inter-group coordination and intra-group autonomy according to claim 1, characterized in that, The specific operation steps of the load prediction module to predict short-term load fluctuation based on historical data are as follows: Obtain load demand data and meteorological data at the current time, and obtain meteorological prediction data for the future period; Use a long short-term memory network model to construct a feature matrix, the input layer of which includes lag load values, meteorological data and time encoding features, the hidden layer of which includes stacked LSTM units and learning time series patterns, and the output layer of which includes predicted load values for the future period; Input the features into the trained model to output a short-term load prediction curve for the future period, and obtain the load demand in the future period. 8.The distributed photovoltaic double-layer collaborative control system based on inter-group coordination and intra-group autonomy according to claim 6, characterized in that, The energy storage management module is also configured to perform safety protection, specifically as follows: If the current state of charge ≥ maximum state of charge then the charging is forcibly stopped for preventing overcharging; If the current state of charge < Maximum state of charge then the discharge is forced to stop for avoiding over-discharge.

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