Distributed power access unit, intelligent fusion terminal and electric energy meter for photovoltaic accommodation

Abstract

The present invention relates to the technical field of electrical variable measurement, and specifically discloses a distributed power source access unit, an intelligent fusion terminal and an electric energy meter for photovoltaic accommodation, which are used to solve the problem that the existing distributed photovoltaic accommodation system only relies on one-time linkage scheduling and is difficult to take into account the multi-time sequence requirements of millisecond-level dynamic support, second-level closed-loop compensation and minute-level economic scheduling. It includes a distributed power source access unit, an intelligent fusion terminal and an electric energy meter; based on a closed-loop scheme of multi-level control, dual-ring network logic and virtual unit aggregation, the present invention realizes the rapid response, economic optimization and reliable operation of a high-penetration photovoltaic system.

Description

Technical Field

[0001] The present invention relates to the technical field of electrical variable measurement, and particularly to a distributed power access unit, an intelligent fusion terminal, and an electric energy meter for photovoltaic accommodation. Background Art

[0002] The Chinese invention patent with the application number 2022112524977 discloses a distribution network for distributed power penetration and a photovoltaic accommodation method. Through the collaborative switching of a dual-loop network structure and an energy storage station, and the linkage dispatching based on the historical power consumption curve and the power generation prediction model, the spatio-temporal matching of photovoltaic output and power consumption demand is achieved, the local photovoltaic accommodation efficiency is improved, and the light abandonment loss is reduced. However, this invention only optimizes in terms of one-time linkage dispatching and has the following deficiencies: In traditional power operation systems, steady-state and transient control are usually divided into primary control (millisecond-second level voltage / power support), secondary control (second-minute level energy balance), and tertiary control (minute-hour level economic dispatching). The three-level dispatching framework has become an industry convention to ensure the dynamic stability and economy of the power grid. Once the photovoltaic output suddenly changes, the primary control needs to instantaneously provide power support to suppress voltage dips. Subsequently, the secondary control needs to dispatch energy storage or adjustable loads within a short time to restore power balance. Finally, the tertiary control optimizes the overall power grid operation plan and interfaces with the market mechanism according to electricity prices, costs, and equipment constraints. However, in distributed photovoltaic accommodation, in terms of transient support, the use of local energy storage and adjustable loads to provide power or voltage support at the millisecond-second level is not considered, and it still relies on the mechanical action of loop switching. In terms of short-term energy balance, the dispatching is only completed through one-time model prediction + switch switching, lacking a second-minute level closed-loop compensation and rapid correction strategy. In terms of economic dispatching, it also fails to cooperate with intra-day / daily-ahead market dispatching and cannot dynamically adjust the output strategy at the minute-hour scale. Therefore, in a high-penetration, multi-energy coupled distributed photovoltaic system, the lack of control strategies adapted to the three-level dispatching framework of the power grid not only weakens the rapid response ability to sudden power fluctuations but also makes it difficult to balance long-term economy and real-time stability, seriously restricting the system dispatching flexibility and operation reliability. It is urgent to propose a distributed power access unit, an intelligent fusion terminal, and an electric energy meter for photovoltaic accommodation. Summary of the Invention

[0003] The technical problem to be solved by the present invention is to provide a distributed power access unit, an intelligent fusion terminal, and an electric energy meter for photovoltaic accommodation, and to realize the rapid response, economic optimization, and reliable operation of a high-penetration photovoltaic system based on a closed-loop scheme of multi-level control, dual-loop network logic, and virtual unit aggregation.

[0004] To achieve the above object, the present invention provides the following technical solutions:

[0005] Distributed power access unit for photovoltaic accommodation, including fast ring network and economic ring network topologies, and a tie switch located between the fast ring network and the economic ring network. Both the fast ring network and the economic ring network are connected to a resource aggregation module. The fast ring network, the economic ring network, and the resource aggregation module are all connected to a hierarchical control module. The fast ring network, the economic ring network, and the tie switch are all connected to a fault collaborative processing module. The fast ring network is used for primary / secondary control support in milliseconds to seconds, and responds to sudden changes in photovoltaic output by switching the power flow of the two ring network segments through reconstruction. The economic ring network is used for tertiary economic dispatch in minutes to hours, and coordinates with the energy storage station by switching the economic ring network segments to perform cost-optimal output allocation.

[0006] The hierarchical control module is used to coordinate the switching timing of the two ring networks, send second-level circuit breaker / reclosing commands to the fast ring network, and send switching and energy storage collaborative dispatch commands in minutes to hours to the economic ring network.

[0007] The resource aggregation module collects and summarizes the real-time output and status of photovoltaic, energy storage, heating, cooling, and electrical equipment in real time, and aggregates the obtained heterogeneous resources into a unified controllable virtual unit.

[0008] The fault collaborative processing module monitors the status of the two ring networks and the tie switch, and when detecting abnormalities in the ring network / equipment, realizes isolation in milliseconds to seconds through the local switch of the fast ring network, and completes minute-level energy reallocation through coordination with the economic ring network and the energy storage station.

[0009] As a further solution of the present invention, under the condition of meeting the set deployment cost budget, the resource aggregation module constructs the Jacobian matrix of the power-voltage equation based on the distribution network power flow model, linearizes the Jacobian matrix, obtains the sensitivity coefficients of the power injection change at each bus node to the node voltage and the power flow of adjacent branches. All candidate measurement points are sorted from high to low according to the sensitivity coefficients. Core layer measurement points are arranged among several candidate measurement points within the preset ranking number, and respond to primary / secondary control in milliseconds to seconds with a sampling frequency greater than or equal to 2kHz and a voltage / current accuracy of ±0.5%FS. For the remaining candidate measurement points, they are sorted from large to small according to the cost-benefit ratio, and positions are added in turn until the cumulative cost is less than or equal to the preset threshold, and these measurement points are identified as auxiliary layer measurement points, and respond to tertiary economic dispatch in minutes to hours with a sampling frequency greater than or equal to 200Hz and less than 2kHz and a voltage / current accuracy of ±1%FS. Portable PMUs are deployed as needed in the remaining network area to respond to the tertiary control of economic dispatch in minutes to hours with a sampling frequency greater than or equal to 50Hz and less than 200Hz.

[0010] As a further solution of the present invention, the hierarchical control module includes a main control sub-module, a secondary control sub-module, and a tertiary control sub-module. The main control sub-module monitors the voltage and frequency on the fast ring network bus side in real time at a sampling frequency greater than or equal to 2 kHz. When the detected frequency deviation exceeds ±0.02 Hz / voltage deviation exceeds ±1%, it automatically calls the local energy storage device and adjustable load, calculates and issues a millisecond-second level transient power support command through a preset droop control curve. The droop coefficient used is configured online within 0.02 pu - 0.05 pu to respond to sudden changes in photovoltaic output. The secondary control sub-module uses 1 s as the update period, continuously calculates the average power error within the recent 10 s sliding window, and generates a power increment command through a proportional-integral controller based on this. The proportional gain ranges from 0.1 to 1.0, and the integral gain ranges from 0.01 to 0.1. This command is issued to the energy storage device and adjustable load through the tie switch for second-minute level energy balance adjustment. The tertiary control sub-module uses 5 min as a scheduling cycle, establishes an economic optimal scheduling model based on the cost curves of each distributed resource, and solves the cost minimization problem through numerical algorithms such as the interior point method on the premise of ensuring that the total output is equal to the predicted load, the output of each resource meets the upper and lower limit constraints, and the network power flow is safe. The obtained minute-hour level scheduling result is converted into a closing switch action and energy storage device charge and discharge commands for execution.

[0011] As a further solution of the present invention, in the hierarchical control module, the main control sub-module monitors the voltage and frequency on the fast ring network bus side in real time at a sampling frequency greater than or equal to 2 kHz. When the detected frequency deviation exceeds ±0.02 Hz / voltage deviation exceeds ±1%, it automatically calls the local energy storage device and adjustable load, calculates and issues a millisecond-second level transient power support command through a preset droop control curve. The droop coefficient used is configured online within 0.02 pu - 0.05 pu to respond to sudden changes in photovoltaic output; the secondary control sub-module uses 1 s as the update period, continuously calculates the average power error within the recent 10 s sliding window, and generates a power increment command through a proportional-integral controller based on this. The proportional gain ranges from 0.1 to 1.0, and the integral gain ranges from 0.01 to 0.1. This command is issued to the energy storage device and adjustable load through the tie switch for second-minute level energy balance adjustment; the tertiary control sub-module uses 5 min as a scheduling cycle, establishes an economic optimal scheduling model based on the cost curves of each distributed resource, and solves the cost minimization problem through numerical algorithms such as the interior point method on the premise of ensuring that the total output is equal to the predicted load, the output of each resource meets the upper and lower limit constraints, and the network power flow is safe. The obtained minute-hour level scheduling result is converted into a closing switch action and energy storage device charge and discharge commands for execution.

[0012] The intelligent fusion terminal for PV accommodation is connected to the distributed power access unit for PV accommodation described above, and includes a multi-sensor fusion unit. The multi-sensor fusion unit is connected to an edge preprocessing unit, and the edge preprocessing unit is connected to an execution feedback unit. The multi-source sensor fusion unit is used to synchronously collect the operating parameters on the bus sides of the fast ring network and the economic ring network. The edge preprocessing unit is used to perform band-pass filtering, noise suppression, data compression and local caching on the data collected by the multi-source sensor fusion unit at a sampling frequency greater than or equal to 1 kHz. The execution feedback unit is used to receive the primary / secondary / tertiary control instructions issued by the distributed power access unit, and to control the adjustable load and energy storage device in real time through the local relay / communication interface.

[0013] As a further solution of the present invention, the edge preprocessing unit stores the preprocessed data in a ring buffer with a capacity of greater than or equal to 10 MB, encrypts the cached data, and batches uploads the encrypted cached data after detecting the restoration of the communication link with the distributed power access unit.

[0014] As a further solution of the present invention, a two-way interaction mechanism is provided between the execution feedback unit and the edge processing unit, including:

[0015] Parameter issuing: After receiving the sampling strategy instruction, the execution feedback unit writes the new upper and lower limits of band-pass filtering, sampling frequency and compression ratio parameters into the edge preprocessing module through the internal bus / communication interface;

[0016] Status feedback: The edge preprocessing unit dynamically adjusts the signal processing flow based on the received parameters, and reports the buffer utilization rate, signal-to-noise ratio of the filtered signal, and data processing delay to the execution feedback unit in real time;

[0017] Closed-loop verification: The execution feedback unit monitors the buffer utilization rate, signal-to-noise ratio of the filtered signal, and data processing delay fed back by the edge preprocessing unit. If it is found that at least one of the buffer utilization rate exceeds 90%, SNR is lower than 20 dB, or processing delay exceeds 10 ms, it automatically issues a new sampling frequency and filter bandwidth adjustment instruction, or triggers a fault recovery plan;

[0018] Timeout protection: The execution feedback unit verifies the response delay of the edge preprocessing unit every 1 s. If no status feedback is received for three consecutive times, it starts the local standby filtering and compression configuration.

[0019] As a further solution of the present invention, the above intelligent fusion terminal further includes a self-diagnosis unit, and the self-diagnosis unit is connected to both the execution feedback unit and the edge preprocessing unit.

[0020] As a further solution of the present invention, the working process of the self-diagnosis unit includes:

[0021] Step 1, calibration signal injection: Inject a known calibration signal with an amplitude of 1V and a frequency of 1kHz into the edge preprocessing unit at a period of 1Hz.

[0022] Step 2, output monitoring value: Collect the output of the calibration signal after band-pass filtering and compression from the edge preprocessing unit, and measure its amplitude deviation and signal-to-noise ratio.

[0023] Step 3, anomaly determination and post-processing: When the measured amplitude deviation of the calibration signal exceeds ±0.5% or the signal-to-noise ratio is lower than 25dB, it is determined that the preprocessing unit is abnormal. After the anomaly is determined, the self-diagnosis unit immediately sends a fault alarm to the execution feedback unit, and at the same time instructs the execution feedback unit to switch to the preset standby filtering upper and lower limits and compression parameters.

[0024] An electricity meter includes at least one of the above-mentioned distributed power access unit for photovoltaic accommodation or the above-mentioned intelligent fusion terminal for photovoltaic accommodation, and measures and reports the power on the grid side, cooling and heating energy consumption, and production load energy data in real time, receives the primary / secondary / tertiary hierarchical control instructions and demand response signals issued by the distributed power access unit, and automatically adjusts the start / stop state of local load devices or controls the charge and discharge actions of the energy storage unit according to the received control instructions, so as to realize the closed-loop dynamic coupling and optimized accommodation of photovoltaic output and multiple loads.

[0025] Technical effects of the distributed power access unit, intelligent fusion terminal, and electricity meter for photovoltaic accommodation proposed by the present invention:

[0026] The present invention constructs a hierarchical control architecture covering millisecond-second primary / secondary control, second-minute secondary energy balance, and minute-hour tertiary economic dispatching, combines the fast ring network and economic ring network logical topologies and tie switches of the double-ring network, and realizes millisecond-level power / voltage support and minute-level economic switching for sudden changes in high-penetration distributed photovoltaic output; and unifies heterogeneous devices such as photovoltaic, energy storage, cooling and heating, and electricity into controllable virtual units, and relies on the two-ring network bus measurement points and adaptive measurement point layout strategies to ensure the accurate triggering and fast closed-loop compensation of primary / secondary control; at the same time, it integrates local cache encryption, execution feedback, and self-diagnosis mechanisms, enabling the intelligent fusion terminal to achieve real-time response and online correction for dynamic sampling, fault plans, and control instructions; and uses numerical algorithms such as the interior point method to parallel update the tertiary economic dispatching plan, complete the coordinated linkage with the day-ahead / intra-day market, improve the system's response speed to photovoltaic power fluctuations and voltage stability, optimize the economy of resource dispatching, and enhance the reliability of fault recovery and the flexibility and robustness of the overall operation of the distribution network. Description of the Drawings

[0027] Figure 1 It is a block diagram of the distributed power access unit of the present invention.

[0028] Figure 2 Block diagram of the intelligent fusion terminal of the present invention;

[0029] Figure 3 Physical installation diagram of the electric energy meter of the present invention;

[0030] Figure 4 Statistical table of test data for buffer occupancy analysis;

[0031] Figure 5 Statistical table of test data for delay analysis;

[0032] Figure 6 Statistical analysis table of test data for signal-to-noise ratio analysis;

[0033] Figure 7 Statistical analysis table of test data for voltage support response; Detailed implementation manners

[0034] Next, the technical solutions in the embodiments of the present invention will be clearly and completely described in conjunction with the accompanying drawings in the embodiments of the present invention. Obviously, the described embodiments are only a part of the embodiments of the present invention, rather than all the embodiments. Based on the embodiments of the present invention, all other embodiments obtained by those of ordinary skill in the art without creative efforts shall fall within the protection scope of the present invention.

[0035] Embodiment 1

[0036] As Figure 1 shown, the distributed power access unit for photovoltaic accommodation proposed by the present invention includes a fast ring network and an economic ring network topology, as well as a tie switch located between the two ring networks. Both ring networks are connected to a resource aggregation module, both ring networks and the resource aggregation module are connected to a hierarchical control module, both ring networks and the tie switch are connected to a fault collaborative processing module. The fast ring network is used for primary / secondary control support in the millisecond-second level, and responds to sudden changes in photovoltaic output by switching the power flow of the two ring network segments. The economic ring network is used for tertiary economic dispatch in the minute-hour level, and coordinates with the energy storage station by switching the ring network segments to perform the most cost-effective output allocation. The hierarchical control module is used to coordinate the switching timing of the two ring networks, send a second-level circuit breaker / reclosing instruction to the fast ring network, and send a minute-hour level switch switching and energy storage collaborative dispatch instruction to the economic ring network. The resource aggregation module collects and summarizes the real-time output and status of photovoltaic, energy storage, heating, cooling, and electrical equipment in real time, and aggregates the obtained heterogeneous resources into a unified controllable virtual unit. The fault collaborative processing module monitors the status of the two ring networks and the tie switch, and when detecting ring network / equipment abnormalities, realizes millisecond-second isolation through the local switch of the fast ring network, and completes minute-level energy reallocation through the coordination of the economic ring network and the energy storage station.

[0037] Compared with the invention patent mentioned in the background art of the present invention, the present invention has achieved a leap from "one-time linkage" to three-level hierarchical control of "second-minute-hour" in the control architecture, shortening the support delay during sudden changes in PV output and enhancing the dynamic response ability to transient power / voltage fluctuations. Aiming at the radial grid structure and two-way power flow characteristics of the distribution network, the present invention uses a fast loop network logical topology to achieve millisecond-level fault isolation and voltage support, effectively suppressing the bus overvoltage caused by reverse current; at the minute-hour level, through the economic loop network mode combined with cost optimization and network power flow security constraints, economic dispatch and line loss minimization are completed. The resource aggregation module uniformly models multi-source heterogeneous devices such as PV, energy storage, heating, cooling, and adjustable loads as controllable virtual units (visible as virtual power plants in the prior art), which not only simplifies the dispatching scale but also enhances flexibility. The overall solution fully addresses the operation difficulties such as voltage over-limit, three-phase imbalance, and excessive harmonic content in the distribution network, realizing the stable and reliable operation and economic and efficient consumption of high-penetration distributed PV.

[0038] It should be noted that, under the premise of meeting the set deployment cost budget, the resource aggregation module constructs the Jacobian matrix of the power-voltage equation based on the distribution network power flow model, linearizes the Jacobian matrix, and obtains the sensitivity coefficients of the power injection change at each bus node to the node voltage and the power flow of adjacent branches. All candidate measurement points are sorted from high to low according to the sensitivity coefficients, and core layer measurement points are arranged among several candidate measurement points within the preset ranking number. With a sampling frequency greater than or equal to 2 kHz and a voltage / current accuracy of ±0.5% FS, it responds to primary / secondary control at the millisecond-second level. For the remaining candidate measurement points, they are sorted from large to small according to the cost-benefit ratio, and positions are added in sequence until the cumulative cost is less than or equal to the preset threshold. These measurement points are identified as auxiliary layer measurement points, with a sampling frequency greater than or equal to 200 Hz and less than 2 kHz and a voltage / current accuracy of ±1% FS, responding to minute-hour level economic dispatch. Portable PMUs are deployed as needed in the remaining network area, responding to the three-level control of minute-hour level economic dispatch with a sampling frequency greater than or equal to 50 Hz and less than 200 Hz.

[0039] Adopt optimization of measuring point layout and adaptive monitoring based on power flow sensitivity to greatly improve network observability, accurately locate faults and quickly perform closed-loop compensation. On the premise of meeting the deployment cost budget, based on the linearized sensitivity coefficient of the power flow Jacobian matrix of the distribution network, construct the core layer measuring points and the auxiliary layer measuring points hierarchically and supplement them with mobile PMUs to achieve high-precision and low-latency observation of the primary / secondary control trigger of the fast loop network in the millisecond to second level and the tertiary economic dispatch of the economic loop network in the minute to hour level. At the same time, greatly improve the network observability and fault location accuracy, ensure both the rapid response to the sudden change of photovoltaic output and the bus voltage stability, and support hierarchical economic dispatch and precise energy storage coordination. While reducing the measuring point deployment cost and communication bandwidth pressure, realize the multi-time sequence and multi-energy coordinated closed-loop efficient operation for the high-penetration distributed photovoltaic system.

[0040] For example, in a fast loop network of a certain distribution network with a total length of about 4 km and 16 feeder branch nodes, each node is a candidate measuring point. If the total cost corresponding to the measuring point deployment budget does not exceed 100,000 yuan, the resource aggregation module first constructs a power-voltage Jacobian matrix based on the power flow model of the distribution network and calculates the sensitivity coefficients of the injection power change of each node to the node voltage and the power flow of adjacent branches. Among them, the sensitivities of nodes 3, 7, 10, and 14 are the highest; select the top 4 nodes 3, 7, 10, and 14 in terms of sensitivity, and install voltage / current sensors with an accuracy of ±0.5%FS respectively. The sampling rate is set to 2 kHz. In the scenario of a sudden drop in photovoltaic output, it only takes 5 ms to detect a 2% voltage drop at node 7, and immediately trigger the local energy storage device to inject 50 kW of power into the bus, quickly restoring the voltage to above 0.98 pu; among the remaining 12 candidate nodes, sort them in descending order according to the ratio of sensitivity coefficient to cost, and successively select a total of 5 nodes 2, 5, 8, 12, and 15. The sampling rate is set to 500 Hz, ±1%FS. During the minute-level economic dispatch, through the measuring point data of nodes 5 and 12, the prediction load error is reduced from the original ±8% to ±2%, significantly improving the accuracy and economy of energy storage dispatch; deploy 2 mobile PMUs for the remaining nodes, each with a coverage radius of 500 m and a sampling rate of 100 Hz, for short-term fault drills and blind area observation. When a fault occurs between lines 12 - 13, the mobile PMU completes fault location within 3 s and assists the fast loop network to isolate the faulty branch section, reducing voltage disturbances in the non-fault area.

[0041] It should be noted that the hierarchical control module includes a primary control sub-module, a secondary control sub-module, and a tertiary control sub-module. The primary control sub-module monitors the voltage and frequency on the fast ring network bus side in real time at a sampling frequency greater than or equal to 2 kHz. When the detected frequency deviation exceeds ±0.02 Hz or the voltage deviation exceeds ±1%, it automatically calls the local energy storage device and adjustable load, calculates and issues a millisecond-second level transient power support command through a preset droop control curve. The droop coefficient used is configured online within the range of 0.02 pu - 0.05 pu to respond to sudden changes in photovoltaic output. The secondary control sub-module takes 1 s as the update period, continuously calculates the average power error within the recent 10 s sliding window, and generates a power increment command through a proportional-integral controller based on this. The proportional gain ranges from 0.1 to 1.0, and the integral gain ranges from 0.01 to 0.1. This command is issued to the energy storage device and adjustable load through the tie switch for second-minute level energy balance adjustment. The tertiary control sub-module takes 5 min as a scheduling cycle, establishes an economic optimal scheduling model based on the cost curves of various distributed resources, and solves the cost minimization problem through numerical algorithms such as the interior point method while ensuring that the total output is equal to the predicted load, the output of each resource meets the upper and lower limit constraints, and the network power flow is safe. The obtained minute-hour level scheduling result is converted into a closed-loop switch action and energy storage device charge and discharge command for execution.

[0042] In the scenario of high - penetration distributed photovoltaic (PV) grid connection, due to the significant impact of meteorological conditions on PV output, its power fluctuations include both millisecond - to - second - level transient disturbances, and second - to - minute - level short - term deviations and minute - to - hour - level load / electricity price dynamic changes. Traditional single - level scheduling (one - time model prediction + loop network switching) is difficult to balance the response requirements of different time scales, resulting in support delays when the system responds to sudden large - scale output fluctuations, and it is difficult to quickly adjust strategies to synchronize with market signals at the economic scheduling level. Therefore, a hierarchical control architecture that includes master (primary / secondary) control sub - modules, secondary control sub - modules, and tertiary control sub - modules is set up. Specifically for the multi - time - series characteristics of the dynamic coupling between distributed PV output and distribution network load, it integrates the control rhythms of millisecond - to - second - level, second - to - minute - level, and minute - to - hour - level in a classified manner. The master control sub - module issues transient power support commands immediately when the voltage deviation is ±1% or the frequency deviation is ±0.02 Hz by means of high - speed sampling at ≥2 kHz and online - adjustable droop coefficients, reducing the support delay to <10 ms, effectively stabilizing the bus voltage and preventing voltage dips caused by reverse power flow. The secondary control sub - module updates every 1 s, with a 10 - s sliding window and PI control, accurately allocating energy storage and adjustable loads, and completing the balance within 5 - 15 s after the occurrence of short - term power deviations, significantly reducing the frequency fluctuations caused by energy mismatch. The tertiary control sub - module has a 5 - min scheduling cycle, combines the cost curves of various resources and the network power flow security constraints, quickly generates an optimal scheduling plan through the interior - point method, and automatically switches the closed - loop switch and the energy storage charge - discharge to ensure the minimum operating cost and the lowest line loss under dynamic electricity prices and load changes. This hierarchical control strategy aims at the multi - time - series dynamic characteristics of the distribution network, improving both the fast response ability of the system and taking into account the economy and security of long - term operation.

[0043] Specifically, in the hierarchical control module, the main control sub-module monitors the voltage and frequency of the fast ring network bus side in real time at a sampling frequency greater than or equal to 2 kHz. When the detected frequency deviation exceeds ±0.02 Hz / voltage deviation exceeds ±1%, it automatically calls the local energy storage device and adjustable load, calculates and issues a millisecond-second level transient power support command through a preset droop control curve. The droop coefficient used is configured online within 0.02 pu - 0.05 pu to respond to sudden changes in photovoltaic output; the secondary control sub-module takes 1 s as the update period, continuously calculates the average power error within the sliding window of the last 10 s, and generates a power increment command through a proportional-integral controller on this basis. The proportional gain ranges from 0.1 to 1.0, and the integral gain ranges from 0.01 to 0.1. This command is sent to the energy storage device and adjustable load through the tie switch for second-minute level energy balance adjustment; the tertiary control sub-module takes 5 min as a scheduling cycle, establishes an economic optimal scheduling model based on the cost curves of each distributed resource, and under the premise of ensuring that the total output is equal to the predicted load, the output of each resource meets the upper and lower limit constraints and the network power flow is safe, solves the cost minimization problem through numerical algorithms such as the interior point method, and converts the obtained minute-hour level scheduling result into a closed-loop switch action and energy storage device charge and discharge command for execution.

[0044] This hierarchical control strategy significantly improves the dynamic response speed and economic scheduling efficiency of the high-penetration distributed photovoltaic system: First, the main control sub-module realizes the millisecond-second level precise support for the voltage / frequency of the fast ring network bus side through ultra-high frequency real-time monitoring of ≥2 kHz and an online-configurable droop coefficient of 0.02 pu–0.05 pu. It can suppress the voltage drop amplitude within ±0.5% and restore the frequency deviation to within ±0.01 Hz within 10 ms after a sudden change in photovoltaic output, thus avoiding protection maloperation and voltage instability caused by reverse current or transient disturbance; Second, the secondary control sub-module uses the PI algorithm with a 1 s update period and a 10 s sliding window, which can narrow the power deviation from ±10% to within ±2% within 20 s, realize the fast closed-loop compensation for the energy storage and adjustable load, and significantly reduce the system frequency oscillation and energy mismatch; Finally, the tertiary control sub-module optimizes based on the interior point method of each resource cost curve and network power flow security constraints with a 5 min scheduling cycle. It not only seamlessly docks with the day-ahead / intra-day market signals, but also can reduce the overall operating cost by about 5% and reduce the line loss by about 8%, taking into account the supply-demand balance and economy. This solution effectively solves the contradiction between traditional one-time scheduling in fast response, fault recovery and economic optimization through multi-time sequence coordination of primary-secondary-tertiary levels, and comprehensively enhances the stability, reliability and economy of the distribution network under high-penetration photovoltaic conditions.

[0045] Embodiment 2

[0046] The difference between Embodiment 2 and Embodiment 1 of the present invention lies in that this embodiment introduces an intelligent fusion terminal for photovoltaic accommodation.

[0047] As Figure 2 shown, the intelligent fusion terminal for photovoltaic accommodation proposed by the present invention is connected to the above-mentioned distributed power access unit for photovoltaic accommodation, and includes a multi-sensor fusion unit. The multi-sensor fusion unit is connected to an edge preprocessing unit, and the edge preprocessing unit is connected to an execution feedback unit. The multi-source sensor fusion unit is used to synchronously collect the operating parameters of the fast ring network and the economic ring network busbars. The edge preprocessing unit is used to perform band-pass filtering, noise suppression, data compression and local caching on the data collected by the multi-source sensor fusion unit at a sampling frequency greater than or equal to 1 kHz. The execution feedback unit is used to receive the primary / secondary / tertiary control instructions issued by the distributed power access unit, and to control the adjustable load and energy storage device in real time through the local relay / communication interface.

[0048] By integrating multi-source sensing, edge preprocessing and local execution feedback, the intelligent fusion terminal of the present invention can achieve "full-link" low-latency and autonomous closed-loop control on-site. The specific technical effects include:

[0049] High-fidelity fast response: The multi-sensor fusion unit synchronously captures the operating parameters such as voltage, current, and temperature on the fast ring network and the economic ring network side at an ultra-high sampling rate of ≥1 kHz, ensuring "zero blind spot" real-time perception of millisecond-level power fluctuations;

[0050] Local intelligent filtering and data compression: The edge preprocessing unit completes band-pass filtering, noise suppression and data compression locally, effectively removing useless information and reducing the communication volume by more than 50%. This not only improves the measurement accuracy but also reduces the network load of the superior dispatching center;

[0051] Autonomous closed-loop execution: After receiving the primary / secondary / tertiary control instructions, the execution feedback unit issues them to the adjustable load and energy storage device in milliseconds through the local relay or communication interface, without relying on the remote central control frequently, significantly shortening the control latency and enhancing the local autonomy ability during communication interruption;

[0052] Disturbance resistance and reliability enhancement: The local caching mechanism ensures the data integrity during disconnection. The execution feedback and self-diagnosis work together, and can automatically switch to the backup strategy when sensing or communication anomalies are detected, ensuring the continuous and stable operation of the system under high-penetration photovoltaic fluctuations and network interference.

[0053] It should be noted that the edge preprocessing unit stores the preprocessed data in a ring buffer of more than 10 MB and encrypts the cached data. After detecting the restoration of the communication link with the distributed power access unit, it uploads the encrypted cached data in batches.

[0054] Network jitter or link interruption often occurs at the power distribution site. A ring buffer with a capacity of ≥10MB can continuously cache high-frequency preprocessed data locally for hours or even days, ensuring that critical operation information is not lost after the network is restored. The cached data is encrypted at the AES-256 level to prevent tampering or theft during local storage or batch upload, meeting the strict requirements of operation and maintenance and compliance for data privacy and confidentiality. After the link is restored, data is uploaded in batches, which can not only make full use of the available bandwidth but also avoid network congestion and the processing pressure on the dispatching center caused by frequent small-packet transmissions. The combination of ring buffer and batch upload can preserve the complete order and timestamp of the data, facilitating subsequent anomaly diagnosis, fault backtracking, and precise energy balance analysis.

[0055] Specifically, a two-way interaction mechanism is provided between the execution feedback unit and the edge processing unit, including:

[0056] Parameter distribution: After receiving the sampling strategy instruction, the execution feedback unit writes the new upper and lower limits of band-pass filtering, sampling frequency, and compression ratio parameters into the edge preprocessing module through the internal bus / communication interface;

[0057] Status feedback: Based on the received parameters, the edge preprocessing unit dynamically adjusts the signal processing flow and reports the buffer utilization rate, signal-to-noise ratio of the filtered signal, and data processing delay to the execution feedback unit in real time;

[0058] Closed-loop verification: The execution feedback unit monitors the buffer utilization rate, signal-to-noise ratio of the filtered signal, and data processing delay fed back by the edge preprocessing unit. If it is found that at least one of the buffer utilization rate exceeds 90%, SNR is lower than 20dB, or processing delay exceeds 10ms, a new sampling frequency and filter bandwidth adjustment instruction is automatically issued, or a fault recovery plan is triggered;

[0059] Timeout protection: The execution feedback unit verifies the response delay of the edge preprocessing unit every 1s. If no status feedback is received for three consecutive times, the local standby filtering and compression configuration is activated.

[0060] Through parameter distribution, the edge preprocessing module can switch the band-pass filter bandwidth, sampling frequency, and compression ratio in real time according to different output fluctuations and network environments to maintain the optimal filtering and data accuracy during high-frequency jitter or low-frequency trend changes. Status feedback ensures that the execution feedback unit always grasps key indicators such as buffer utilization rate, signal-to-noise ratio (SNR), and processing delay. When any of these indicators exceeds the limit, the system can automatically adjust the sampling and filtering parameters at the millisecond-second level or trigger a fault recovery plan to ensure data stream continuity and measurement reliability. The timeout protection mechanism can quickly switch to the preset standby filtering and compression configuration in case of link or module anomalies, avoiding data missing or control instruction delay caused by communication interruption or hardware jamming, and enhancing the on-site autonomy ability.

[0061] Under laboratory conditions, simulate the periodic packet loss and delay jitter of the IEC61850 / MQTT link, record the buffer occupancy, SNR, and delay change curves of the edge preprocessing module under different sampling strategy instructions; test the recovery duration and amplitude of the performance indicators after parameter adjustment after the closed-loop verification is triggered. Apply stepwise load surges and drops to the fast ring network, and send different droop coefficients, sampling frequencies, and filtering bandwidths in real time to evaluate the support delay and recovery accuracy of the system for voltage / frequency deviation, and verify the role of the adaptive sampling strategy in primary / secondary control. Deliberately close the communication of the edge preprocessing unit or simulate a processor overload scenario, observe the behavior of the execution feedback unit switching to standby parameters under timeout protection conditions, and evaluate the data continuity and measurement accuracy after the switch. As Figures 4 - 7 As shown in the data, under the condition of simulating 15% packet loss and an average round-trip delay jitter of 100 ms, the peak buffer occupancy is 92%. After adjusting the sampling frequency and filtering bandwidth through closed-loop verification, the peak is reduced to 75%, and the average is maintained below 65%. The SNR of the filtered signal in the initial state is 15 dB; after issuing new band-pass filtering parameters, the SNR is increased to 28 dB (an increase of 13 dB). The average end-to-end delay of the edge preprocessing module is reduced from 22 ms to 7 ms, and the peak delay is reduced from 45 ms to 12 ms. When applying a ±200 kW step power disturbance to the fast ring network bus, a support command is issued within 5 ms after detecting a voltage drop of 0.05 pu (i.e., 5%), and the voltage is restored to 0.99 pu (the origin is 1.00 pu) within 10 ms. The disturbance causes a frequency deviation of ±0.04 Hz, and the main control sub-module is restored to within ±0.01 Hz within 8 ms; the secondary control reduces the power deviation from the initial ±12% to ±2% within 12 s. The circular buffer can cache ≥30,000 samples (corresponding to 10 MB), and no samples are missed during a 3 s network disconnection. After the execution feedback unit has no status feedback for 3 consecutive seconds, it completes the issuance and loading of the standby filtering / compression parameters for the edge preprocessing module within 2 s. After the connection is restored, the encrypted data uploaded in batches is decrypted and compared, and the head and tail timing error is less than 1 ms, and the packet loss rate is 0.

[0062] It should be noted that the above intelligent fusion terminal further includes a self-diagnosis unit, and the self-diagnosis unit is connected to both the execution feedback unit and the edge preprocessing unit. The working process of the self-diagnosis unit includes:

[0063] Step 1, calibration signal injection: Inject a known calibration signal with an amplitude of 1 V and a frequency of 1 kHz into the edge preprocessing unit at a period of 1 Hz;

[0064] Step 2, output monitoring value: Collect the output of the calibrated signal after band-pass filtering and compression from the edge preprocessing unit, and measure its amplitude deviation and signal-to-noise ratio;

[0065] Step 3, abnormality determination and post-processing: When the measured calibration signal amplitude deviation exceeds ±0.5% or the signal-to-noise ratio is lower than 25dB, the preprocessing unit is determined to be abnormal. After the abnormality is determined, the self-diagnosis unit immediately sends a fault alarm to the execution feedback unit, and at the same time instructs the execution feedback unit to switch to the preset backup filter upper and lower limits and compression parameters.

[0066] By regularly injecting known calibration signals and monitoring their filtered output, the performance degradation or module failure of the edge preprocessing unit can be accurately identified within a 1Hz rhythm, avoiding long-term blind zone operation. Once the amplitude deviation exceeds ±0.5% or the SNR is lower than 25dB, the fault alarm is immediately triggered and the execution feedback unit is instructed to switch to the preset backup filtering and compression parameters, so that the continuity of the data processing link can be maintained without manual intervention. Through real-time calibration and automatic switching, it is ensured that the measurement data uploaded to the distributed power access unit always meets the accuracy and signal-to-noise ratio requirements, providing reliable and high-fidelity basic data for subsequent primary / secondary / tertiary control. The self-diagnosis and automatic switching mechanism greatly shortens the fault location and recovery time, reduces the frequency of on-site maintenance, effectively reduces the operation and maintenance costs, and enhances the anti-disturbance capability in complex power grid environments. Combined with multi-level closed-loop control, the real-time health monitoring and automatic recovery capabilities of the self-diagnosis unit further improve the overall stability and robustness of the distribution network when the photovoltaic output fluctuates violently.

[0067] Example 3

[0068] Different from Embodiment 1 and Embodiment 2, this embodiment specifically introduces an electric energy meter proposed by the present invention.

[0069] like Figure 3 As shown, an electric energy meter proposed in the present invention is installed in an electric energy meter box, including at least one of the above-mentioned distributed power access unit for photovoltaic consumption or the above-mentioned intelligent fusion terminal for photovoltaic consumption, real-time measurement and reporting of grid-side electric energy, cold and hot energy consumption and production load energy data, receiving primary / secondary / tertiary level control instructions and demand response signals issued by the distributed power access unit, and automatically adjusting the start and stop status of local load equipment or controlling the charging and discharging actions of the energy storage unit according to the received control instructions, so as to realize the closed-loop dynamic coupling and optimized consumption of photovoltaic output and multiple loads.

[0070] In summary, according to the technical solutions of the present invention described in Embodiments 1 to 3, the present invention constructs a hierarchical control architecture covering millisecond-second level primary / secondary control, second-minute level secondary energy balance, and minute-hour level tertiary economic dispatch, combines the fast ring network and economic ring network logical topologies and tie switches of the dual-ring network, and realizes millisecond-level power / voltage support and minute-level economic switching for sudden changes in the output of high-penetration distributed photovoltaics; and unifies heterogeneous devices such as photovoltaics, energy storage, heating / cooling, and electricity into adjustable virtual units, and relies on the two-ring network bus measurement points and adaptive measurement point layout strategies to ensure the precise triggering and fast closed-loop compensation of primary / secondary control; at the same time, integrates local cache encryption, execution feedback, and self-diagnosis mechanisms, enabling the intelligent fusion terminal to achieve real-time response and online correction for dynamic sampling, fault plans, and control instructions; and uses numerical algorithms such as the interior point method to parallelly update the tertiary economic dispatch plan, complete the coordinated linkage with the day-ahead / intra-day market, improve the response speed of the system to photovoltaic power fluctuations and voltage stability, optimize the economy of resource dispatch, and enhance the reliability of fault recovery and the flexibility and robustness of the overall operation of the distribution network.

[0071] The above is only the specific implementation manner of the present application, but the protection scope of the present application is not limited thereto. Any person skilled in the art can easily think of changes or substitutions within the technical scope disclosed in the present application, and all such changes or substitutions should be covered within the protection scope of the present application. Therefore, the protection scope of the present application shall be subject to the protection scope of the claims.

[0072] Finally: The above is only the preferred embodiment of the present invention and is not used to limit the present invention. Any modification, equivalent replacement, improvement, etc. made within the spirit and principle of the present invention shall be included within the protection scope of the present invention.

Claims

1. Distributed power source access unit for photovoltaic accommodation, characterized in that It includes a fast ring network and an economic ring network topology, as well as a connection switch located between the fast ring network and the economic ring network. Both the fast ring network and the economic ring network are connected to a resource aggregation module. The fast ring network, the economic ring network, and the resource aggregation module are all connected to a hierarchical control module. The fast ring network, the economic ring network, and the connection switch are all connected to a fault collaborative processing module. The fast ring network is used for primary / secondary control support in the millisecond - second level, and responds to sudden changes in photovoltaic output by switching the power flow of the two ring network segments for reconstruction; the economic ring network is used for tertiary economic dispatch in the minute - hour level, and coordinates with the energy storage station by switching the economic ring network segments to perform cost - optimal output allocation; The hierarchical control module is used to coordinate the switching timing of the two ring networks, send second - level circuit breaker / reclosing commands to the fast ring network, and send minute - hour level switch switching and energy storage collaborative dispatch commands to the economic ring network; The resource aggregation module collects and summarizes the real - time output and status of photovoltaic, energy storage, heating, cooling, and electrical equipment in real time, and aggregates the obtained heterogeneous resources into a unified controllable virtual unit; The fault collaborative processing module monitors the status of the two ring networks and the connection switch, and when detecting abnormalities in the ring network / equipment, realizes millisecond - second level isolation through the local switch of the fast ring network, and completes minute - level energy redistribution through the coordination of the economic ring network and the energy storage station.

2. The distributed power source access unit for photovoltaic accommodation according to claim 1, wherein Under the condition of meeting the set deployment cost budget, the resource aggregation module constructs the Jacobian matrix of the power - voltage equation based on the distribution network power flow model, linearizes the Jacobian matrix, and obtains the sensitivity coefficients of the power injection change at each bus node to the node voltage and the power flow of adjacent branches. All candidate measurement points are sorted from high to low according to the sensitivity coefficients. Several candidate measurement points within the preset ranking number are arranged as core - layer measurement points, and they respond to primary / secondary control in the millisecond - second level with a layout method of a sampling frequency greater than or equal to 2kHz and a voltage / current accuracy of ±0.5%FS. For the remaining candidate measurement points, they are sorted from large to small according to the cost - benefit ratio, and are added to the positions in turn until the cumulative cost is less than or equal to the preset threshold, and these measurement points are identified as auxiliary - layer measurement points, and they respond to minute - hour level economic dispatch with a layout method of a sampling frequency greater than or equal to 200Hz and less than 2kHz and a voltage / current accuracy of ±1%FS. Mobile PMUs are deployed as needed in the remaining network areas to respond to the tertiary control of minute - hour level economic dispatch with a sampling frequency greater than or equal to 50Hz and less than 200Hz.

3. The distributed power source access unit for photovoltaic accommodation according to claim 1, characterized in that The hierarchical control module includes a primary control sub-module, a secondary control sub-module, and a tertiary control sub-module; the primary control sub-module monitors the voltage and frequency on the fast loop network bus side in real time at a sampling frequency greater than or equal to 2 kHz. When the detected frequency deviation exceeds ±0.02 Hz / voltage deviation exceeds ±1%, it automatically invokes the local energy storage device and adjustable load, calculates and issues a millisecond-second level transient power support command through a preset droop control curve, and the droop coefficient used is configured online within 0.02 pu - 0.05 pu to respond to sudden changes in photovoltaic output. The secondary control sub-module takes 1 s as the update period, continuously calculates the average power error within the recent 10 s sliding window, and generates a power increment command through a proportional-integral controller based on this. The proportional gain ranges from 0.1 to 1.0, and the integral gain ranges from 0.01 to 0.

1. This command is sent to the energy storage device and adjustable load through the tie switch for second-minute level energy balance adjustment. The tertiary control sub-module takes 5 min as a scheduling cycle, establishes an economic optimal scheduling model based on the cost curves of various distributed resources, solves the cost minimization problem through numerical algorithms such as the interior point method on the premise of ensuring that the total output is equal to the predicted load, the output of each resource meets the upper and lower limit constraints, and the network power flow is safe, and converts the obtained minute-hour level scheduling result into a loop closing switch action and energy storage device charge and discharge commands for execution.

4. The distributed power source access unit for photovoltaic accommodation according to claim 3, wherein, In the hierarchical control module, the primary control sub-module monitors the voltage and frequency on the fast loop network bus side in real time at a sampling frequency greater than or equal to 2 kHz. When the detected frequency deviation exceeds ±0.02 Hz / voltage deviation exceeds ±1%, it automatically invokes the local energy storage device and adjustable load, calculates and issues a millisecond-second level transient power support command through a preset droop control curve, and the droop coefficient used is configured online within 0.02 pu - 0.05 pu to respond to sudden changes in photovoltaic output; the secondary control sub-module takes 1 s as the update period, continuously calculates the average power error within the recent 10 s sliding window, and generates a power increment command through a proportional-integral controller based on this. The proportional gain ranges from 0.1 to 1.0, and the integral gain ranges from 0.01 to 0.

1. This command is sent to the energy storage device and adjustable load through the tie switch for second-minute level energy balance adjustment; The tertiary control sub-module takes 5 min as a scheduling cycle, establishes an economic optimal scheduling model based on the cost curves of various distributed resources, solves the cost minimization problem through numerical algorithms such as the interior point method on the premise of ensuring that the total output is equal to the predicted load, the output of each resource meets the upper and lower limit constraints, and the network power flow is safe, and converts the obtained minute-hour level scheduling result into a loop closing switch action and energy storage device charge and discharge commands for execution.

5. The intelligent fusion terminal for photovoltaic accommodation is characterized in that Connect to the distributed power access unit for photovoltaic accommodation described in any one of claims 1 to 4, and include a multi-sensor fusion unit. The multi-sensor fusion unit is connected to an edge preprocessing unit, and the edge preprocessing unit is connected to an execution feedback unit. The multi-source sensor fusion unit is used to synchronously collect the operating parameters on the bus sides of the fast ring network and the economic ring network. The edge preprocessing unit is used to perform band-pass filtering, noise suppression, data compression, and local caching on the data collected by the multi-source sensor fusion unit at a sampling frequency greater than or equal to 1 kHz. The execution feedback unit is used to receive the primary / secondary / tertiary control instructions issued by the distributed power access unit, and to control the adjustable load and energy storage device in real time through the local relay / communication interface.

6. The intelligent fusion terminal for photovoltaic accommodation according to claim 5, characterized in that The edge preprocessing unit stores the preprocessed data in a ring buffer with a capacity of greater than or equal to 10 MB, and encrypts the cached data. After detecting the restoration of the communication link with the distributed power access unit, it uploads the encrypted cached data in batches.

7. The intelligent fusion terminal for photovoltaic accommodation according to claim 6, wherein There is a two-way interaction mechanism between the execution feedback unit and the edge processing unit, including: Parameter distribution: After receiving the sampling strategy instruction, the execution feedback unit writes the new upper and lower limits of band-pass filtering, sampling frequency, and compression ratio parameters into the edge preprocessing module through the internal bus / communication interface; Status feedback: The edge preprocessing unit dynamically adjusts the signal processing flow based on the received parameters, and reports the buffer utilization rate, signal-to-noise ratio of the filtered signal, and data processing delay to the execution feedback unit in real time; Closed-loop verification: The execution feedback unit monitors the buffer utilization rate, signal-to-noise ratio of the filtered signal, and data processing delay fed back by the edge preprocessing unit. If it is found that at least one of the buffer utilization rate exceeds 90%, SNR is lower than 20 dB, or processing delay exceeds 10 ms, it automatically issues new sampling frequency and filter bandwidth adjustment instructions, or triggers a fault recovery plan; Timeout protection: The execution feedback unit verifies the response delay of the edge preprocessing unit every 1 s. If the status feedback is not received three times in a row, it starts the local standby filtering and compression configuration.

8. The intelligent fusion terminal for photovoltaic accommodation according to claim 5, wherein It further includes a self-diagnosis unit, which is connected to both the execution feedback unit and the edge preprocessing unit.

9. The intelligent fusion terminal for photovoltaic accommodation according to claim 8, wherein The working process of the self-diagnosis unit includes: Step 1, calibration signal injection: Inject a known calibration signal with an amplitude of 1 V and a frequency of 1 kHz into the edge preprocessing unit at a period of 1 Hz; Step 2, output monitoring value: Collect the output of the calibration signal after band-pass filtering and compression from the edge preprocessing unit, and measure its amplitude deviation and signal-to-noise ratio; Step 3, abnormality determination and post-processing: When the measured amplitude deviation of the calibration signal exceeds ±0.5% or the signal-to-noise ratio is lower than 25 dB, it is determined that the preprocessing unit is abnormal. After the abnormality is determined, the self-diagnosis unit immediately sends a fault alarm to the execution feedback unit, and at the same time instructs the execution feedback unit to switch to the preset standby filter upper and lower limits and compression parameters.

10. An electric energy meter, characterized in that, It includes the distributed power access unit for photovoltaic accommodation described in any one of claims 1 to 4, which measures and reports in real time the electric energy, cooling and heating energy consumption, and production load energy data on the grid side, receives the primary / secondary / tertiary hierarchical control instructions and demand response signals sent by the distributed power access unit, and automatically adjusts the start / stop state of local load devices or controls the charge / discharge actions of the energy storage unit according to the received control instructions, so as to realize the closed-loop dynamic coupling and optimal accommodation of photovoltaic output and diversified loads.

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