Household energy center system and control method thereof

Abstract

The invention provides a household energy center system and a control method thereof, and relates to the technical field of energy control, and the system comprises a first photovoltaic part, a household energy storage cabinet, a grid-connected module, a bidirectional ammeter, and a cloud module. The first photovoltaic piece is electrically connected with the household energy storage cabinet, the household energy storage cabinet is electrically connected with the grid-connected module, the bidirectional ammeter, the cloud module and the household grid-connected load, and the bidirectional ammeter is electrically connected with the grid-connected module and the household grid-connected load. According to the invention, through the design of the hot-pluggable heterogeneous battery compartment group, compatibility with different capacities is realized, new and old batteries operate cooperatively, the capacity expansion cost is reduced, and the battery utilization rate is improved.

Description

Technical Field

[0001] This invention relates to the field of energy control technology, and in particular to a home energy center system and its control method. Background Technology

[0002] Current home energy systems generally suffer from three major drawbacks: difficulties in compatibility with heterogeneous batteries, delayed off-grid switching, and insufficient accuracy in photovoltaic forecasting. Traditional energy storage cabinets, due to their fixed battery specifications, cannot support the mixed operation of battery packs with different capacities, and forced mixing will lead to severe circulating current losses. When the grid is interrupted, the system relies on a single energy storage unit for response, resulting in a long switching delay, which can cause damage to critical loads such as refrigerators and medical equipment. Grid-connected photovoltaic systems are slow to respond to sudden weather changes, and existing forecasting models do not integrate real-time weather warnings. When encountering short-term severe convective weather, the inverter is easily tripped due to drastic power fluctuations, threatening grid voltage stability.

[0003] Therefore, a home energy center system and its control method are proposed. Summary of the Invention

[0004] This manual provides a home energy center system and its control method. Through a hot-swappable heterogeneous battery compartment design, it is compatible with different capacities and allows new and old batteries to operate together, reducing expansion costs and improving battery utilization.

[0005] This manual provides a home energy center system, including: a first photovoltaic element, a home energy storage cabinet, a grid-connected module, a bidirectional meter, and a cloud module; The first photovoltaic element is electrically connected to the household energy storage cabinet, and the household energy storage cabinet is electrically connected to the grid-connected module, the bidirectional meter, the cloud module, and the household grid-connected load. The bidirectional meter is electrically connected to the grid-connected module and the household grid-connected load.

[0006] Optionally, the grid-connected module includes: a second photovoltaic element and a grid-connected inverter; The second photovoltaic element is electrically connected to the grid-connected inverter, and the grid-connected inverter is electrically connected to the household energy storage cabinet, the bidirectional meter, and the household grid-connected load.

[0007] Optionally, the cloud module includes: a cloud platform, a home storage operation and maintenance backend, and a home storage APP; The home energy storage cabinet is electrically connected to the cloud platform, and the cloud platform is electrically connected to the home energy storage operation and maintenance backend and the home energy storage APP.

[0008] Optionally, the home energy storage cabinet includes a hot-swappable heterogeneous battery compartment that supports the mixed operation of a 3kWh standard battery pack and a 0.5kWh portable battery pack.

[0009] Optionally, the home energy storage cabinet may further include a dynamic impedance matching unit; The internal resistance ratio of the 3kWh standard battery pack and the 0.5kWh portable battery pack is calculated in real time. The PWM duty cycle of the parallel branch is dynamically adjusted based on the internal resistance ratio, so that the discharge current of battery packs of different specifications is inversely proportional to the internal resistance. When the insertion of the 0.5kWh portable battery pack is detected, the output power of the 3kWh standard battery pack is automatically reduced in order to suppress circulating current.

[0010] Optional features also include: an off-grid emergency control module; When a power outage is detected and the home energy storage cabinet switches to off-grid mode, all the 0.5kWh portable battery packs that are in a dormant state are awakened to form a parallel power array; Based on the critical load priority list, disconnect the power supply circuits for unnecessary loads; The output response time of the parallel power array is accelerated to prioritize compensation for high-frequency power deficiency; the portable battery pack's available time countdown and load classification suggestions are pushed to the user through the home storage APP.

[0011] This manual provides a control method for a home energy center system, including: The home energy storage cabinet obtains real-time data on the power generation of the first photovoltaic device, the power of the home load, and the grid signal. Based on the power generation of the first photovoltaic device and the household load power, the net load fluctuation value in the future time period is predicted by a time series prediction model. Determine whether the net load fluctuation value in the future time period exceeds the preset rated power of the energy storage system; When the net load fluctuation value of the future time period exceeds the preset rated power of the energy storage system, the hybrid control strategy is activated.

[0012] Optionally, the activation of the hybrid control strategy includes: The home energy storage cabinet obtains real-time data from the bidirectional electricity meter; The virtual inertia response unit of the home energy storage cabinet is activated based on the real-time data of the bidirectional meter to adjust the output power. The home energy storage cabinet uploads dynamic adjustment logs to the cloud, triggering real-time energy efficiency alarms from the home storage app.

[0013] Optionally, the time series prediction model is a CNN-BiLSTM hybrid neural network model.

[0014] Optionally, the time series prediction model synchronously receives gridded meteorological early warning data sent from the cloud; The meteorological warning data is fused with the power generation of the first photovoltaic device using wavelet transform to generate a power fluctuation prediction value with a weather correction factor. When the predicted power fluctuation value with weather correction factor exceeds the rated power of the energy storage, the reactive power compensation mode of the grid-connected inverter is immediately activated.

[0015] This invention achieves a comprehensive performance improvement for home energy systems through innovative design: It adopts a hot-swappable heterogeneous battery compartment architecture, effectively solving the circulating current loss problem when using batteries of different specifications, supporting the coordinated operation of new and old batteries and reducing expansion costs; a modular grid connection interface ensures seamless compatibility with existing photovoltaic equipment, avoiding overall system modification; an integrated CNN-BiLSTM hybrid neural network-based net load forecasting system combined with a virtual inertia response unit can quickly correct power fluctuations and achieve millisecond-level grid frequency regulation response, significantly improving the accuracy of dynamic inertia simulation; a cloud-based operation and maintenance platform, through real-time energy efficiency alarms and dynamic adjustment log analysis, dynamically adjusts charging and discharging strategies based on battery health status, extending battery life and reducing the frequency of deep discharge; a dual-power fast switching device and load priority scheduling algorithm ensure zero-aware power outages for critical equipment, preventing damage to precision instruments; a photovoltaic output forecasting engine based on multi-source data fusion effectively copes with sudden weather changes, reducing the risk of inverter grid disconnection and improving photovoltaic absorption capacity. The overall solution forms a systematic technical advantage in terms of compatibility, reliability, response speed, and intelligent management. Attached Figure Description

[0016] To more clearly illustrate the technical solutions in the embodiments of this application, the accompanying drawings used in the description of the embodiments will be briefly introduced below. Obviously, the accompanying drawings described below are only some embodiments of this application. For those skilled in the art, other drawings can be obtained based on these drawings without creative effort.

[0017] Figure 1 This specification provides a schematic diagram of the structure of a home energy center system as an embodiment. Figure 2 This is a schematic diagram illustrating the principle of a control method for a home energy center system provided in an embodiment of this specification.

[0018] Attached diagrams: 10, First photovoltaic element; 20, Home energy storage cabinet; 30, Grid-connected module; 31, Second photovoltaic element; 32, Grid-connected inverter; 40, Bidirectional meter; 50, Cloud module; 51, Cloud; 52, Home energy storage operation and maintenance backend; 53, Home energy storage APP. Detailed Implementation

[0019] The following description is intended to disclose the present invention and enable those skilled in the art to implement it. The preferred embodiments described below are merely examples, and other obvious variations will occur to those skilled in the art. The basic principles of the invention defined in the following description can be applied to other embodiments, modifications, improvements, equivalents, and other technical solutions that do not depart from the spirit and scope of the invention.

[0020] The following is in conjunction with the appendix Figure 1-2 Exemplary embodiments of the invention will be described more fully here. However, exemplary embodiments can be implemented in many forms and should not be construed as limiting the invention to the embodiments set forth herein. Rather, these exemplary embodiments are provided to make the invention more comprehensive and complete, and to facilitate a full communication of the inventive concept to those skilled in the art. The same reference numerals in the figures denote the same or similar elements, components, or parts, and therefore repeated descriptions of them are omitted.

[0021] Subject to the technical concept of this invention, the features, structures, characteristics or other details described in a particular embodiment may be combined in one or more other embodiments in a suitable manner.

[0022] In the description of specific embodiments, the features, structures, characteristics, or other details described in this invention are intended to enable those skilled in the art to fully understand the embodiments. However, it is not excluded that those skilled in the art can practice the technical solutions of this invention without one or more of the specific features, structures, characteristics, or other details.

[0023] The flowcharts shown in the accompanying drawings are merely illustrative and do not necessarily include all content and operations / steps, nor do they necessarily have to be performed in the described order. For example, some operations / steps can be broken down, while others can be combined or partially combined; therefore, the actual execution order may change depending on the specific circumstances.

[0024] The block diagrams shown in the accompanying drawings are merely functional entities and do not necessarily correspond to physically independent entities. That is, these functional entities can be implemented in software, in one or more hardware modules or integrated circuits, or in different network and / or processor devices and / or microcontroller devices.

[0025] The terms “and / or” or “and / or” include all combinations of any one or more of the listed items.

[0026] Figure 1 A schematic diagram of a home energy center system provided in the embodiments of this specification includes: a first photovoltaic element 10, a home energy storage cabinet 20, a grid-connected module 30, a bidirectional meter 40, and a cloud module 50; The first photovoltaic element 10 is electrically connected to the household energy storage cabinet 20. The household energy storage cabinet 20 is electrically connected to the grid-connected module 30, the bidirectional meter 40, the cloud module 50, and the household grid-connected load. The bidirectional meter 40 is electrically connected to the grid-connected module 30 and the household grid-connected load.

[0027] In the specific implementation of this specification, the home energy system consists of a photovoltaic power generation unit, an energy storage module, a grid connection device, metering components, and an intelligent management platform. The photovoltaic power generation unit uses high-efficiency monocrystalline silicon modules, which are connected to the DC input terminal of the energy storage module through a standardized interface. The energy storage module is equipped with multiple hot-swappable battery compartments, supporting the coordinated operation of lithium-ion batteries of different capacities and in different states of use. A built-in dynamic balancing management system ensures balanced current distribution when multiple battery packs are connected in parallel.

[0028] The AC output of the energy storage module is connected to the grid-connected device, the metering unit, and the household loads. The grid-connected device integrates an inverter unit and an energy management unit to convert DC to AC and facilitate grid interaction. The metering unit simultaneously monitors the grid-connected power flow and household electricity consumption data. When a grid power outage is detected, the system automatically switches power to the energy storage module for critical loads via a dual-power switching device, and, in conjunction with a load priority scheduling algorithm, ensures continuous power supply to important loads such as medical equipment.

[0029] The intelligent management platform connects to the main control board of the energy storage module via a wireless communication module, collecting real-time data on power generation, energy storage, and electricity consumption. It then generates short-term load forecast curves based on a hybrid neural network model. During system operation, photovoltaic power is prioritized for household loads, with any remaining power stored in the energy storage module. When photovoltaic output is insufficient, the energy storage module dynamically adjusts its discharge strategy based on battery health status, sending power correction commands to the grid-connected device via virtual inertial response technology to achieve rapid frequency regulation response. After the electricity data recorded by the metering components is uploaded to the management platform, it combines meteorological warning information to generate energy efficiency optimization suggestions, automatically adjusting battery charge and discharge thresholds to reduce the frequency of deep discharges.

[0030] By reducing system expansion costs through heterogeneous battery compatibility design and improving equipment adaptability through modular grid-connected structure, combined with intelligent prediction and dynamic control technology, the system effectively solves the problems of circulating current loss, switching lag and insufficient prediction accuracy in traditional home energy systems, significantly improves the renewable energy absorption capacity and grid interaction performance, while extending battery life and ensuring the power supply reliability of critical loads.

[0031] Optionally, the grid-connected module 30 includes: a second photovoltaic element 31 and a grid-connected inverter 32; The second photovoltaic element 31 is electrically connected to the grid-connected inverter 32, and the grid-connected inverter 32 is electrically connected to the household energy storage cabinet 20, the bidirectional meter 40, and the household grid-connected load.

[0032] In the specific embodiments described in this specification, the first photovoltaic element 10 is a balcony photovoltaic system, and the second photovoltaic element 31 is a rooftop photovoltaic system. Lightweight flexible photovoltaic modules (such as 300W perovskite photovoltaic films) are installed on the balcony railings or facade of the residence, secured with rail-mounted clips, and connected to the MPPT controller of the home energy storage cabinet 20 via a miniature anti-backflow protector. The module's tilt angle is adjustable to adapt to the building facade's lighting characteristics, and a shadow optimizer (such as a Tigo TS4-AO) is configured to mitigate localized shading. Simultaneously, the home energy storage cabinet 20 includes a built-in inverter.

[0033] Optionally, the cloud module 50 includes: cloud 51, home storage operation and maintenance backend 52, and home storage APP 53; The home energy storage cabinet 20 is electrically connected to the cloud platform 51, and the cloud platform 51 is electrically connected to the home energy storage operation and maintenance backend 52 and the home energy storage APP 53.

[0034] In the specific implementation of this specification, a LORA communication terminal (such as the Semtech SX1278 chipset) is integrated inside the home energy storage cabinet 20, configured with a frequency band of 470MHz (compliant with China's unlicensed frequency band specifications). A bidirectional meter 40 (such as the Wasion DDS3319) is equipped with a LORA slave module (using Class A communication protocol), forming a star network with the energy storage cabinet's host module. Every 30 seconds, the energy storage cabinet sends real-time charging and discharging power commands (data packets include CRC16 checksums) to the bidirectional meter 40 via LORA. Simultaneously, it receives parameters such as grid interaction power and voltage harmonic distortion rate from the meter. Communication messages are encrypted using AES-128, with the key dynamically distributed by the cloud module 50 (rotating daily) to prevent data tampering. A channel eavesdropping mechanism (such as CAD detection) is deployed between the energy storage cabinet and the meter to automatically avoid Wi-Fi channel interference. An adaptive rate switching function (SF7-SF12 spreading factor dynamically adjusted) is configured to automatically increase receiving sensitivity when the signal weakens. If LORA communication is interrupted for more than 5 minutes, the energy storage cabinet switches to a local caching strategy, performing charging and discharging control based on historical load curves, and simultaneously pushes a communication anomaly alarm to the home storage APP 53 via the cloud module 50. An RS485 wired communication interface is reserved on the meter side as an emergency backup channel, directly connected to the energy storage cabinet's BMS system.

[0035] Of course, communication between the home energy storage cabinet 20 and the first bidirectional meter 40 can also be achieved via RS485 wired connection, which will not be elaborated here.

[0036] Optionally, the home energy storage cabinet 20 includes a hot-swappable heterogeneous battery compartment that supports the mixed operation of a 3kWh standard battery pack and a 0.5kWh portable battery pack.

[0037] Optionally, the home energy storage cabinet 20 further includes a dynamic impedance matching unit; The internal resistance ratio of the 3kWh standard battery pack and the 0.5kWh portable battery pack is calculated in real time. The PWM duty cycle of the parallel branch is dynamically adjusted based on the internal resistance ratio, so that the discharge current of battery packs of different specifications is inversely proportional to the internal resistance. When the insertion of the 0.5kWh portable battery pack is detected, the output power of the 3kWh standard battery pack is automatically reduced in order to suppress circulating current.

[0038] In the specific implementation described in this specification, the dynamic impedance matching unit integrated inside the home energy storage cabinet 20 continuously collects the internal impedance parameters of the standard battery pack and the portable battery pack. A dedicated metering chip calculates the ratio of their internal resistances in real time, and dynamically adjusts the duty cycle of the PWM modulation signal in each parallel branch of the batteries based on this ratio, ensuring that the discharge current is automatically distributed according to the inverse ratio of internal resistance. When the portable battery pack is inserted into the cabinet, the control unit immediately reduces the power output of the standard battery pack, eliminating ineffective energy circulation caused by internal resistance differences through a preset circulating current suppression algorithm. This achieves natural characteristic adaptation of heterogeneous batteries, significantly reducing circulating current losses in the hybrid system, extending the overall battery life, and improving discharge efficiency.

[0039] Optional features also include: an off-grid emergency control module; When a power grid outage is detected and the home energy storage cabinet 20 switches to off-grid mode, all the 0.5kWh portable battery packs that are in a dormant state are awakened to form a parallel power array; Based on the critical load priority list, disconnect the power supply circuits for unnecessary loads; The output response time of the parallel power array is accelerated to prioritize compensation for high-frequency power deficiency; the portable battery pack's available time countdown and load classification suggestions are pushed to the user through the home storage APP53.

[0040] In the specific implementation described in this manual, when the off-grid emergency control module detects a power outage signal, it immediately sends a high-voltage wake-up pulse to all dormant portable battery packs, causing them to form a parallel output array within milliseconds. Simultaneously, it triggers a hardware-level load tripper, cutting off unnecessary load circuits based on a pre-programmed list of critical load priorities (e.g., medical equipment > lighting > air conditioning). The parallel array employs high-frequency direct-drive technology, prioritizing millisecond-level power demands such as refrigerator compressor startup, and graphically displays the estimated battery life of the portable packs and suggested recoverable load levels to the user via the Home Storage APP53. This ensures uninterrupted operation of critical loads under extreme power outage scenarios, utilizing the cluster characteristics of portable battery packs to instantly fill power gaps, significantly improving the resilience of home power supply.

[0041] Figure 2 A schematic diagram illustrating the principle of a control method for a home energy center system provided in this specification, comprising: S110: The home energy storage cabinet obtains the power generation of the first photovoltaic device, the power of the home load, and the grid signal in real time; S120: Based on the power generation of the first photovoltaic device and the household load power, predict the net load fluctuation value for a future time period using a time series prediction model; S130: Determine whether the net load fluctuation value in the future time period exceeds the preset rated power of the energy storage system; S140: When the net load fluctuation value of the future time period exceeds the preset rated power of the energy storage system, the hybrid control strategy is activated.

[0042] In the specific implementation of this specification, the home energy storage cabinet synchronously collects real-time power generation from the balcony photovoltaic system, total household load power, and frequency and voltage signals from the grid. It acquires photovoltaic inverter output data and smart meter load information through a local communication interface, filters and normalizes the raw data, and stores it in a buffer for subsequent analysis. Based on historical photovoltaic power generation and load power data, a hybrid neural network model is used to predict the net load fluctuation trend for future periods. After filtering and correction, the model output identifies the peak fluctuation and compares it with the rated power of the energy storage system. If the confidence level of the prediction result is insufficient, it switches to a backup prediction model and triggers an alarm. When the predicted fluctuation value exceeds the system's rated power, multi-level control is executed. A dynamic power threshold command is sent to the bidirectional meter via wireless communication to limit power fluctuations fed into the grid; the virtual synchronous control unit of the energy storage cabinet is activated to simulate the inertia characteristics of a synchronous generator, adjusting the output power in real time to smooth grid frequency deviations; the output ratio of different battery packs is dynamically allocated according to the battery health status, prioritizing the use of high-health batteries to respond to high-frequency power demands, while simultaneously controlling logs and revenue feedback through cloud synchronization. During control, battery status and system temperature are continuously monitored. If an abnormal state is detected, the control strategy is automatically downgraded, prioritizing power supply to the basic load and discontinuing auxiliary services. All command transmissions are encrypted and verified to ensure communication security and control reliability.

[0043] Optionally, S140 includes: The home energy storage cabinet obtains real-time data from the bidirectional electricity meter; The virtual inertia response unit of the home energy storage cabinet is activated based on the real-time data of the bidirectional meter to adjust the output power. The home energy storage cabinet uploads dynamic adjustment logs to the cloud, triggering real-time energy efficiency alarms from the home storage app.

[0044] In the specific implementation described in this manual, the home energy storage cabinet establishes a wireless link with the bidirectional electricity meter via a communication module to obtain real-time data from the bidirectional meter. In the event of communication failure, it switches to a locally preset strategy and triggers an alarm. Simultaneously, the energy storage cabinet activates a virtual inertia response unit, simulating the inertia characteristics of a synchronous generator based on the grid frequency change rate. It dynamically adjusts the output power through the inverter, automatically switching control modes based on battery status and grid demand to ensure adjustment accuracy and equipment safety. During adjustment, the system encrypts and uploads data such as power correction records, inertia output curves, and battery status to the cloud. The cloud module analyzes the data and triggers tiered alarms (APP pop-ups, SMS notifications, or emergency network disconnection). The system also displays the frequency regulation service benefits and fluctuation suppression effects in real-time through the home energy storage APP. All command transmissions employ bidirectional encryption verification, and the virtual inertia unit is equipped with an independent hardware protection mechanism to prevent unauthorized tampering or control failure, achieving safe and reliable dynamic energy management.

[0045] Optionally, the time series prediction model is a CNN-BiLSTM hybrid neural network model.

[0046] In the specific implementation of this specification, a time-series training set is constructed using historical photovoltaic power generation, household load, and grid frequency data. After data cleaning and normalization, convolutional layers are used to extract local fluctuation features, bidirectional LSTM layers learn long-term and short-term time-series dependencies, and an attention mechanism is combined to strengthen the influence weights of key time nodes. During model training, an adaptive optimization algorithm and regularization strategy are used to balance fitting ability and generalization. During deployment, a lightweight model is embedded into the edge computing unit of the energy storage cabinet to achieve low-latency real-time prediction. The prediction results are filtered and corrected to drive the control strategy, while supporting periodic incremental updates of model parameters in the cloud to adapt to seasonal changes. If the prediction confidence is insufficient or the edge computing is abnormal, the system automatically switches to the backup prediction model and triggers an alarm to ensure the continuity and reliability of the control logic.

[0047] Optionally, the time series prediction model synchronously receives gridded meteorological early warning data sent from the cloud; The meteorological warning data is fused with the power generation of the first photovoltaic device using wavelet transform to generate a power fluctuation prediction value with a weather correction factor. When the predicted power fluctuation value with weather correction factor exceeds the rated power of the energy storage, the reactive power compensation mode of the grid-connected inverter is immediately activated.

[0048] In the specific implementation described in this specification, the cloud pushes gridded early warning data (such as thunderstorm cloud movement vectors and irradiance abrupt change thresholds) issued by the meteorological department to the local prediction model in real time. The model uses a wavelet transform algorithm to decompose the meteorological data and the photovoltaic power generation time series signal into a multi-scale decomposition, and fuses them in a specific frequency band to generate a weather disturbance correction factor. When the corrected power fluctuation prediction value exceeds the capacity limit of the energy storage system, the reactive power compensation function of the grid-connected inverter is immediately triggered, injecting capacitive reactive current into the grid to stabilize the voltage at the point of common coupling. This significantly improves the adaptability of photovoltaic fluctuation prediction to sudden weather events and effectively prevents grid voltage over-limit accidents through proactive reactive power compensation.

[0049] This invention achieves a comprehensive performance improvement for home energy systems through innovative design: It adopts a hot-swappable heterogeneous battery compartment architecture, effectively solving the circulating current loss problem when using batteries of different specifications, supporting the coordinated operation of new and old batteries and reducing expansion costs; a modular grid connection interface ensures seamless compatibility with existing photovoltaic equipment, avoiding overall system modification; an integrated CNN-BiLSTM hybrid neural network-based net load forecasting system combined with a virtual inertia response unit can quickly correct power fluctuations and achieve millisecond-level grid frequency regulation response, significantly improving the accuracy of dynamic inertia simulation; a cloud-based operation and maintenance platform, through real-time energy efficiency alarms and dynamic adjustment log analysis, dynamically adjusts charging and discharging strategies based on battery health status, extending battery life and reducing the frequency of deep discharge; a dual-power fast switching device and load priority scheduling algorithm ensure zero-aware power outages for critical equipment, preventing damage to precision instruments; a photovoltaic output forecasting engine based on multi-source data fusion effectively copes with sudden weather changes, reducing the risk of inverter grid disconnection and improving photovoltaic absorption capacity. The overall solution forms a systematic technical advantage in terms of compatibility, reliability, response speed, and intelligent management.

[0050] The specific embodiments described above further illustrate the purpose, technical solution, and beneficial effects of the present invention. It should be understood that the present invention is not inherently related to any specific computer, virtual device, or electronic device, and various general-purpose devices can also implement the present invention. The above descriptions are merely specific embodiments of the present invention and are not intended to limit the present invention. Any modifications, equivalent substitutions, improvements, etc., made within the spirit and principles of the present invention should be included within the protection scope of the present invention.

[0051] The various embodiments in this specification are described in a progressive manner. The same or similar parts between the various embodiments can be referred to each other. Each embodiment focuses on describing the differences from other embodiments.

[0052] The foregoing is merely an embodiment of the present application and is not intended to limit the present application. For those skilled in the art, the present application may have various changes and variations. Any modifications, equivalent replacements, improvements, etc. made within the spirit and principles of the present application should all be included within the scope of the claims of the present application.

Claims

1. A home energy center system, characterized in that, include: First photovoltaic component (10), household energy storage cabinet (20), grid-connected module (30), two-way meter (40), cloud module (50); The first photovoltaic element (10) is electrically connected to the household energy storage cabinet (20), and the household energy storage cabinet (20) is electrically connected to the grid-connected module (30), the bidirectional meter (40), the cloud module (50), and the household grid-connected load, respectively. The bidirectional meter (40) is electrically connected to the grid-connected module (30) and the household grid-connected load, respectively.

2. The home energy center system as described in claim 1, characterized in that, The grid-connected module (30) includes: a second photovoltaic element (31) and a grid-connected inverter (32); The second photovoltaic element (31) is electrically connected to the grid-connected inverter (32), and the grid-connected inverter (32) is electrically connected to the household energy storage cabinet (20), the bidirectional meter (40), and the household grid-connected load, respectively.

3. The home energy center system as described in claim 2, characterized in that, The cloud module (50) includes: cloud (51), home storage operation and maintenance backend (52), and home storage APP (53); The home energy storage cabinet (20) is electrically connected to the cloud (51), and the cloud (51) is electrically connected to the home energy storage operation and maintenance backend (52) and the home energy storage APP (53).

4. The home energy center system as described in claim 3, characterized in that, The home energy storage cabinet (20) includes a hot-swappable heterogeneous battery compartment that supports the mixed operation of a 3kWh standard battery pack and a 0.5kWh portable battery pack.

5. The home energy center system as described in claim 4, characterized in that, The home energy storage cabinet (20) also includes a dynamic impedance matching unit; The internal resistance ratio of the 3kWh standard battery pack and the 0.5kWh portable battery pack is calculated in real time. The PWM duty cycle of the parallel branch is dynamically adjusted based on the internal resistance ratio, so that the discharge current of battery packs of different specifications is inversely proportional to the internal resistance. When the insertion of the 0.5kWh portable battery pack is detected, the output power of the 3kWh standard battery pack is automatically reduced in order to suppress circulating current.

6. The home energy center system as described in claim 5, characterized in that, Also includes: Off-grid emergency control module; When a power grid outage is detected and the home energy storage cabinet (20) switches to off-grid mode, all the 0.5kWh portable battery packs that are in a dormant state are awakened to form a parallel power array; Based on the critical load priority list, disconnect the power supply circuits for unnecessary loads; The output response time of the parallel power array is accelerated to compensate for the high-frequency power deficiency; the portable battery pack's available time countdown and load classification suggestions are pushed to the user through the home storage APP (53).

7. A control method for a home energy center system, characterized in that, include: The home energy storage cabinet obtains real-time data on the power generation of the first photovoltaic module and the power of the household load. Based on the power generation of the first photovoltaic device and the household load power, the net load fluctuation value in the future time period is predicted by a time series prediction model. Determine whether the net load fluctuation value in the future time period exceeds the preset rated power of the energy storage system; When the net load fluctuation value of the future time period exceeds the preset rated power of the energy storage system, the hybrid control strategy is activated.

8. The control method for a home energy center system as described in claim 7, characterized in that, The startup hybrid control strategy includes: The home energy storage cabinet obtains real-time data from the bidirectional electricity meter; The virtual inertia response unit of the home energy storage cabinet is activated based on the real-time data of the bidirectional meter to adjust the output power. The home energy storage cabinet uploads dynamic adjustment logs to the cloud, triggering real-time energy efficiency alarms from the home storage app.

9. The control method for a home energy center system as described in claim 8, characterized in that, The time series prediction model is a CNN-BiLSTM hybrid neural network model.

10. The control method for a home energy center system as described in claim 9, characterized in that, The time series prediction model synchronously receives gridded meteorological early warning data from the cloud. The meteorological warning data is fused with the power generation of the first photovoltaic device using wavelet transform to generate a power fluctuation prediction value with a weather correction factor. When the predicted power fluctuation value with weather correction factor exceeds the rated power of the energy storage, the reactive power compensation mode of the grid-connected inverter is immediately activated.

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