User-side multi-power-supply and multi-energy-storage unified control method and system

Abstract

The invention relates to a user-side multi-power-supply and multi-energy-storage unified control method and system. The method comprises the following steps: acquiring energy management data; based on the energy management data, judging whether the generating capacity of the user side meets the power demand or not, if so, entering a self-sufficiency + residual power networking / storage mode to make a decision, and if not, entering a consumption mode to make a decision; in a self-sufficiency and surplus power internet access / storage mode, the surplus power is decided to be sold or stored by comparing the power selling income and the power storage cost; in the consumption mode, the user side generating capacity and the storage capacity are preferentially utilized to meet the power demand, and if the user side generating capacity and the storage capacity cannot meet the power demand, insufficient power is purchased from the power grid; and controlling the user-side power distribution network according to a decision result. Compared with the prior art, the system has the advantages of improving the energy efficiency, enhancing the system stability and the like.

Description

Technical Field

[0001] The present invention relates to the technical field of user side distribution network control, and in particular to a method and system for unified control of multiple power sources and multiple energy storages on the user side. Background Art

[0002] The penetration rate of renewable energy power generation on the user side is gradually increasing, and the optimization and operation of the distribution network on the user side is complex. How to achieve economic and technical optimization and operation that meet the needs of all parties has become a difficult problem. Therefore, how to achieve safe, efficient, low-carbon and economic operation of the distribution network on the user side and ensure win-win cooperation among the power grid, renewable energy and users in the distribution network on the user side has become the key to the optimization and operation of the distribution network on the user side.

[0003] The hybrid energy storage control method and device for improving the transient performance of DC microgrids provided by Chinese Patent Application No. CN202310219587.4, the coordinated control method and system of a DC microgrid based on multiple energy storage units provided by Chinese Patent Application No. CN202211478416.5, and the energy management method for grid-connected operation of a DC microgrid based on droop control provided by Chinese Patent Application No. CN202310706303.4, etc., only involve a single microgrid or a single system control technology solution, and do not provide a control method for a cluster intelligent control device, and cannot maximize the energy utilization efficiency of the system.

[0004] The current user-side distribution network has the following main problems:

[0005] (1) System isolation: Existing multiple power sources and energy storage devices usually operate independently and lack unified coordinated control, resulting in low energy utilization efficiency.

[0006] (2) Insufficient flexibility: Existing technologies make it difficult to flexibly dispatch according to real-time load and power generation conditions, which affects the economy and reliability of system operation.

[0007] (3) Lack of optimization strategy: The existing solutions lack control algorithms for the coordinated optimization of multiple power sources and multiple energy storage systems, and are unable to fully tap the comprehensive benefits of the system.

[0008] In summary, there is currently a lack of a control method and system for the user-side distribution network to solve or partially solve the aforementioned problems. Summary of the invention

[0009] The purpose of the present invention is to overcome the defects of the above-mentioned prior art and provide a user-side multi-power supply and multi-energy storage unified control method and system to solve or partially solve the problems of unsatisfactory energy utilization efficiency and system stability and inflexible scheduling.

[0010] The purpose of the present invention can be achieved by the following technical solutions:

[0011] One aspect of the present invention provides a method for unified control of multiple power sources and multiple energy storages at a user side, comprising the following steps:

[0012] Access energy management data;

[0013] Based on the energy management data, determine whether the power generation on the user side meets the power demand. If so, enter the self-sufficiency + surplus power access / storage mode to make a decision; if not, enter the consumption mode to make a decision;

[0014] In the self-sufficiency + surplus power grid / storage mode, the decision to sell or store excess power is made by comparing the power sales income and the power storage cost;

[0015] In the consumption mode, the power generation and storage capacity on the user side are used to meet the power demand first. If the power generation and storage capacity on the user side cannot meet the power demand, the shortfall will be purchased from the power grid.

[0016] Based on the decision results, the user-side distribution network is controlled.

[0017] As a preferred technical solution, after obtaining energy management data, it also includes:

[0018] Detecting abnormal data in the energy management data and correcting the abnormal values;

[0019] removing noise from the energy management data using a filter;

[0020] Fill in the missing data in the energy management data.

[0021] As a preferred technical solution, the judgment of whether the power generation on the user side meets the power demand is implemented by the following formula:

[0022] Pself=∑(i=1,…,n)Pgen,i-Pdemand

[0023] Among them, Pself is the self-sufficient electricity, Pgen,i is the power generation of the ith subsystem, and Pdemand is the total electricity demand.

[0024] As a preferred technical solution, the electricity sales income and electricity storage cost are obtained by the following formula:

[0025] Csell=Psurplus×Pmarket

[0026] Cstore=Psurplus×Cstorage

[0027] Among them, Csell is the income from selling electricity, Pmarket is the electricity market price, Cstore is the cost of storing electricity, Cstorage is the storage cost per unit of electricity, and Psurplus is the surplus electricity.

[0028] As a preferred technical solution, when deciding to sell or store excess electricity, if Csell>Cstore, the excess electricity is sold, otherwise the excess electricity is stored.

[0029] As a preferred technical solution, the process of deciding whether to sell or store excess electricity by comparing the electricity sales income and the electricity storage cost is implemented by the following formula:

[0030] Pgrid=Pdemand-∑(i=1,…,n)Pgen,i

[0031] Among them, Pgrid is the electricity that needs to be purchased from the grid, Pgen,i is the power generation of the i-th subsystem, and Pdemand is the total power demand.

[0032] As a preferred technical solution, the energy management data includes status information of building loads, distributed generation and energy storage equipment.

[0033] Another aspect of the present invention provides a user-side multi-power supply and multi-energy storage unified control system for implementing the aforementioned user-side multi-power supply and multi-energy storage unified control method, the control system comprising:

[0034] Data collection equipment to obtain energy management data;

[0035] A data processing device is used to determine whether the power generation on the user side meets the power demand based on the energy management data. If so, enter the self-sufficiency + surplus power access / storage mode to make a decision. If not, enter the consumption mode to make a decision. In the self-sufficiency + surplus power access / storage mode, by comparing the power sales income and the power storage cost, a decision is made to sell or store the surplus power. In the consumption mode, the power generation and storage on the user side are preferentially used to meet the power demand. If the power generation and storage on the user side cannot meet the power demand, the shortfall is purchased from the power grid;

[0036] The energy manager is used to control the user-side distribution network based on the decision results.

[0037] As a preferred technical solution, the data acquisition device includes:

[0038] The sensor module is installed on the multi-power node, energy storage device node, energy conversion device node and energy distribution node, and is used to configure the collection frequency according to the importance of the device under test and collect operating parameters;

[0039] A communication module, connected to the sensor module and connected to the control center via wired or wireless means;

[0040] A data processing unit, used to correct outliers, filter noise and fill missing values ​​in the collected data;

[0041] The power supply module supplies power to the device through an independent power supply or busbar.

[0042] As a preferred technical solution, multiple power sources and energy storage devices are connected to the bus through a DC / DC or DC / AC interface. The DC / DC interface is connected to the DC energy storage device to adjust the voltage and power flow to ensure that the energy storage device matches the bus voltage. The DC / AC interface is used to connect to the AC power supply equipment, convert DC power into AC power through an inverter, synchronize with the bus voltage, and adapt to the AC bus requirements.

[0043] Compared with the prior art, the present invention has at least one of the following beneficial effects:

[0044] (1) Improve energy efficiency: The unified control of the present invention gives priority to the use of distributed energy and feeds back excess power to the grid under appropriate conditions to optimize energy flow.

[0045] (2) Enhance system stability: Through flexible control and fault isolation between devices, single point failures can be prevented from affecting overall operation.

[0046] (3) Promote green energy application: Promote the widespread application of green energy on the user side through an efficient energy management system. BRIEF DESCRIPTION OF THE DRAWINGS

[0047] Figure 1 Schematic diagram of unified control of multiple power sources and multiple energy storages on the user side in an embodiment;

[0048] Figure 2 Schematic diagram of a system in which a household-side distribution network has multiple power sources, multiple energy storages and multiple users in an embodiment;

[0049] Figure 3 Schematic diagram of centralized control of user-side distribution network in an embodiment. DETAILED DESCRIPTION

[0050] The following will be combined with the drawings in the embodiments of the present invention to clearly and completely describe the technical solutions in the embodiments of the present invention. Obviously, the described embodiments are part of the embodiments of the present invention, not all of the embodiments. Based on the embodiments of the present invention, all other embodiments obtained by ordinary technicians in this field without creative work should fall within the scope of protection of the present invention.

[0051] Example 1

[0052] In view of the problems existing in the above-mentioned prior art, this embodiment provides a unified control method of multiple power sources and multiple energy storages at the user side, which is applied to Figure 2 The household-side distribution network shown in the figure, which has multiple power sources, multiple energy storage systems and multiple user systems, aims to achieve intelligent regulation and optimization of energy through modeling and algorithm design. This method is designed for the "user side". Compared with the traditional control method focusing on the "grid side", it pays more attention to the coordinated management and efficient utilization of energy in the actual user usage scenarios.

[0053] See also Figure 1 , the method comprises the following steps:

[0054] Step S1, obtaining energy management data.

[0055] Real-time collection of energy management data of each subsystem, including but not limited to the status information of building load, distributed power generation (such as photovoltaic, wind power), energy storage and other equipment. Specifically, it can include: ① the power generation and status parameters of multiple power supply equipment (such as solar energy, wind power, etc.); ② the charge and discharge status, capacity and health status of multiple energy storage equipment (such as battery packs); ③ the energy demand, load conditions and energy use mode of the user end; ④ environmental parameters (such as temperature, weather conditions, etc.).

[0056] Preferably, after collecting energy management data, a data preprocessing step is also included. Specifically, considering that the collected data may be affected by noise or outliers, the data are first cleaned. The specific steps include: ① Outlier detection and processing: using statistical methods (such as Z scores, box plots) or machine learning algorithms to detect data anomalies, and using interpolation or historical data to correct outliers; ② Data denoising: using filters (such as Kalman filtering, sliding average method) to remove random noise in the data; ③ Missing value processing: for data lost by sensors, interpolation, regression analysis or prediction methods based on historical data can be used to fill in the gaps.

[0057] Step S2, based on the energy management data, determine whether the power generation on the user side meets the power demand. If so, enter the self-sufficiency + surplus power access / storage mode to make a decision. If not, enter the consumption mode to make a decision.

[0058] Specifically, the following formula is used to determine whether the power generation meets the power demand:

[0059] Pself=∑(i=1,…,n)Pgen,i-Pdemand

[0060] Among them, Pself is the self-sufficient electricity, Pgen,i is the power generation of the ith subsystem, and Pdemand is the total electricity demand.

[0061] Step S3, in the self-sufficiency + surplus power grid access / storage mode, by comparing the electricity sales income and the electricity storage cost, a decision is made to sell or store the surplus electricity.

[0062] In the self-sufficiency + surplus power access / storage mode, the system manager determines that the cluster system is able to achieve power self-sufficiency, and the intelligent control system and architecture utilize the distributed power generation of each subsystem. For the surplus power, the system intelligently decides whether to sell the excess power to the grid or store it for emergency use based on the demand and price of the electricity market.

[0063] Economic evaluation:

[0064] Csell=Psurplus×Pmarket

[0065] Cstore=Psurplus×Cstorage

[0066] Among them, Csell is the income from selling electricity, Pmarket is the electricity market price, Cstore is the cost of storing electricity, and Cstorage is the storage cost per unit of electricity.

[0067] decision making:

[0068] If Csell>Cstore, the excess electricity is sold.

[0069] Otherwise, store excess electricity.

[0070] Step S4, in the consumption mode, the power generation and storage capacity on the user side are preferentially used to meet the power demand. If the power generation and storage capacity on the user side cannot meet the power demand, the shortfall is purchased from the power grid.

[0071] In the absorption mode, when the system manager determines that the cluster system cannot achieve power self-sufficiency, the intelligent control system and architecture give priority to the use of distributed power generation of each subsystem, and then the grid supplements the remaining power demand.

[0072] Specifically, the following formula is used to calculate the electricity demand supplemented from the power grid:

[0073] Electricity needs met:

[0074] Pgrid=Pdemand-∑(i=1,…,n)Pgen,i

[0075] Among them, Pgrid is the electricity that needs to be purchased from the grid.

[0076] decision making:

[0077] If Pgrid>Pstore, then power is purchased from the grid, where Pstore is the available energy storage discharge power.

[0078] Otherwise, no grid support is required.

[0079] Step S5: Control the user-side distribution network according to the decision result.

[0080] Example 2

[0081] Based on Example 1, this embodiment provides a user-side multi-power supply and multi-energy storage unified control system for implementing the user-side multi-power supply and multi-energy storage unified control method of claim 1, see Figure 3 , which mainly include:

[0082] (1) Data acquisition equipment, used to obtain energy management data.

[0083] The installation location of the data acquisition equipment is detailed in the attached Figure 2 , responsible for real-time collection of energy management data of each subsystem, including but not limited to the status information of building load, distributed generation (such as photovoltaic, wind power), energy storage and other equipment. These data will be transmitted to the data processing equipment in real time to achieve energy management and coordinated operation of each subsystem.

[0084] The control components in the data acquisition device include a microprocessor or PLC (programmable logic controller) connected to the data acquisition device, which is responsible for receiving data and performing preliminary processing and analysis according to preset control strategies and algorithms. The core function is to intelligently adjust the system operation status based on real-time data to optimize energy distribution and utilization.

[0085] The control component in the data acquisition device is connected to the DC / DC converter of each subsystem, and can control the disconnection between the subsystem and the cluster bus when necessary. Specifically, when a certain (or more) subsystem fails or requires maintenance, the system can disconnect the subsystem from the cluster bus through the DC / DC converter of the subsystem to avoid affecting the entire system, thus realizing the connection management between the subsystem and the cluster bus in the cluster system.

[0086] See also Figure 2 ,Data acquisition equipment is installed at the key nodes of multiple power ,power and energy storage equipment to collect real-time operation data.

[0087] Among them, in the multi-power supply and energy storage equipment system, the key nodes usually include the following categories: ① Multi-power supply nodes: such as photovoltaic power generation output end, wind power output end, fuel cell interface, micro gas turbine interface, etc.; ② Energy storage equipment nodes: such as battery pack input and output ends, supercapacitor interface, flywheel energy storage port, etc.; ③ Energy conversion equipment nodes: such as converter DC side and AC side, bidirectional inverter interface, etc.; ④ Energy distribution nodes: such as AC / DC bus collection point, load distribution switch interface.

[0088] Among them, the data acquisition equipment mainly includes the following modules: ① Sensor module: installed on key nodes, used to measure operating parameters such as current, voltage, power, temperature, frequency, etc.; ② Communication module: supports wired (such as RS485, CAN bus) or wireless (such as ZigBee, Wi-Fi, LoRa) communication, and is connected to the control center in real time; ③ Data processing unit: has data preprocessing functions (such as filtering, anomaly detection) to improve data accuracy and reliability; ④ Power supply module: powered by an independent battery, or directly obtains power from the system bus.

[0089] Among them, the installation of data acquisition equipment mainly includes the following steps: ①Sensor installation: Install current transformers and voltage sensors at the input and output ends of the power supply and energy storage equipment to monitor the real-time current and voltage data of each device. Install temperature sensors inside or on the surface of the energy storage equipment to monitor the operating environment and the thermal state of the equipment. Install power sensors at energy conversion nodes (such as converters) to obtain energy flow information. ②Fix data acquisition equipment: Use insulating brackets or special fixing devices to install data acquisition equipment near the power supply and energy storage equipment to ensure that the equipment is shockproof, moisture-proof, and electromagnetic interference-proof. Modular design is adopted to facilitate later maintenance and replacement. ③Communication connection: The wired method connects the acquisition equipment to the centralized controller through a shielded cable to avoid electromagnetic interference; the wireless method ensures that the signal is stable within the coverage range by installing a wireless communication module at the node, and a relay device can be deployed when necessary. ④Equipment debugging: Ensure that the acquisition equipment can accurately and quickly collect and transmit data by calibrating the sensor and testing the communication link. After connecting to the control center, the real-time data of the node is verified to ensure the real-time and integrity of the acquisition.

[0090] Among them, the data collection and transmission mechanism mainly includes the following contents: ① Data collection frequency: The collection frequency is set according to the operating characteristics of the equipment. Key nodes (such as busbar collection points) can use high-frequency sampling, and ordinary nodes use lower frequencies; ② Data transmission protocol: Use standardized protocols (such as Modbus, MQTT) to transmit data to ensure compatibility with the control system; ③ Real-time monitoring and storage: After the collected data is preliminarily analyzed by the data processing unit, it is transmitted to the control center in real time and stored in the cloud.

[0091] (2) A data processing device for determining, based on the energy management data, whether the power generation on the user side meets the power demand. If so, the device enters a self-sufficient + surplus power grid-connected / storage mode to make a decision. If not, the device enters a consumption mode to make a decision. In the self-sufficient + surplus power grid-connected / storage mode, the device determines whether to sell or store the surplus power by comparing the power sales income and the power storage cost. In the consumption mode, the power generation and storage on the user side are preferentially used to meet the power demand. If the power generation and storage on the user side cannot meet the power demand, the device purchases the shortfall from the power grid.

[0092] The installation location of data processing equipment is detailed in the attached Figure 2 , responsible for collecting data from the corresponding data acquisition devices of each subsystem, including information provided by sensors and measuring instruments. These data provide the basis for the intelligent decision-making and optimized control of the system.

[0093] Data processing equipment includes but is not limited to servers, network equipment, databases, etc. Through these facilities, the collected data is analyzed and processed in real time, and control instructions are output to each subsystem.

[0094] The data processing equipment cleans and analyzes the collected data and outputs optimized control instructions in real time.

[0095] Among them, the data processing equipment collects various data in the system operation in real time through intelligent sensors and communication modules, including: ① the power generation and status parameters of multiple power supply equipment (such as solar energy, wind energy, etc.); ② the charging and discharging status, capacity and health status of multiple energy storage devices (such as battery packs); ③ the energy demand, load conditions and energy usage mode of the user end; ④ environmental parameters (such as temperature, weather conditions, etc.).

[0096] Among them, the collected data may be affected by noise or outliers, so the data processing equipment first cleans these data. The specific steps include: ① Outlier detection and processing: Use statistical methods (such as Z scores, box plots) or machine learning algorithms to detect data anomalies, and use interpolation or historical data to correct outliers; ② Data denoising: Use filters (such as Kalman filtering, sliding average method) to remove random noise in the data; ③ Missing value processing: For data lost by the sensor, interpolation, regression analysis or prediction methods based on historical data can be used to fill it.

[0097] Among them, the cleaned data is input into the optimization control model for analysis and processing. The specific steps include: ① Real-time state modeling: Use mathematical modeling or data-driven algorithms (such as deep learning, decision trees) to establish a real-time state model of multiple power sources and multiple energy storage systems to predict the working status and energy demand trend of each device. ② Optimization algorithm execution: Use an optimization algorithm based on an objective function (such as linear programming, nonlinear programming) for multi-objective optimization. The goals may include maximizing energy utilization efficiency, minimizing operating costs, balancing energy supply and demand, etc. And consider dynamic adjustments under different operating modes (such as peak and valley electricity price mode, off-grid mode).

[0098] Among them, based on the output results of the optimization algorithm, the data processing device generates real-time control instructions and sends them to the control terminal of each device through the communication module, including: ① Multi-power device scheduling: optimize the output power of each power device to ensure that user needs are met while reducing energy waste. Dynamically adjust the coordination between different power sources according to real-time needs, such as giving priority to the use of renewable energy. ② Energy storage equipment management:

[0099] Determine the charging and discharging time and rate of energy storage equipment to avoid overcharging and overdischarging, extend the life of the equipment, release energy during peak loads, and store excess energy during low loads. ③ Load optimization: Provide energy allocation suggestions to the user side, optimize the operating time of high-energy-consuming equipment, and balance the load.

[0100] Among them, the feedback optimization mechanism for control instructions mainly includes the following steps: ① Real-time monitoring of equipment response, comparison with expected results, and evaluation of the effectiveness of control instructions. ② By comparing actual operation data with model prediction values, self-learning algorithms (such as reinforcement learning) are used to continuously optimize the control model to improve the accuracy and efficiency of future decisions.

[0101] Multiple power supplies and energy storage devices are connected to the bus through a DC / DC or DC / AC interface, and the data processing device can switch the working mode of different devices according to the operating status instructions.

[0102] Among them, the DC / DC interface is used to connect DC energy storage devices (such as lithium batteries and supercapacitors), adjust the voltage and power flow, and ensure that the energy storage device matches the bus voltage. The DC / AC interface is used to connect AC power supply equipment (such as wind turbines or photovoltaic inverters), converting DC power into AC power through the inverter, synchronizing with the bus voltage, and adapting to the AC bus requirements.

[0103] The busbar is the core power transmission path of the system, connecting various energy sources (such as photovoltaic, wind power, and energy storage batteries) and loads. The busbar can be divided into DC busbar and AC busbar. Different configurations can be selected according to user needs to achieve more efficient energy distribution.

[0104] Among them, multiple power sources (such as photovoltaics, wind power) and energy storage devices are connected to the bus in parallel through interfaces to ensure that each device can operate simultaneously and complement each other. The power converter of the DC / DC or DC / AC interface will monitor the bus status in real time and adjust the input / output power according to the optimization control algorithm to maintain the bus voltage and power balance.

[0105] (3) Energy manager, used to control the user-side distribution network based on the decision results.

[0106] The workflow of the system provided in this embodiment is as follows:

[0107] (1) In the self-sufficient mode, priority is given to the consumption of distributed energy generation.

[0108] (2) In the grid coordination mode, energy storage and grid power are used to meet load demand.

[0109] (3) Real-time data exchange and command transmission between devices are carried out through the communication network to ensure the efficiency and stability of system operation.

[0110] The present invention realizes the coordinated management and efficient utilization of various energy forms (such as electricity and energy storage) through unified modeling and optimization control algorithms. The model obtains real-time information through an intelligent data acquisition and processing system, and uniformly dispatches and controls multiple power sources and energy storage devices, which can achieve optimal energy allocation and stable operation under different operating modes. The invention can be widely used in scenarios such as regional energy systems and building integrated energy systems, effectively improving energy utilization efficiency and enhancing system stability.

[0111] The present invention is designed for the "user side". Compared with the traditional control method that focuses on the "grid side", it pays more attention to the coordinated management and efficient utilization of energy in the actual user usage scenarios. Through the intelligent data acquisition and processing system, real-time information on the user side is accurately obtained, and multiple power sources and energy storage equipment are uniformly scheduled and optimized to achieve flexible allocation and stable operation of energy to meet the diverse needs of users. Especially in distributed application scenarios such as regional energy systems and building integrated energy systems, the present invention can significantly improve energy utilization efficiency, enhance the autonomy and reliability of system operation, and thus provide users with more efficient and stable energy management solutions.

[0112] In summary, the present invention has the following characteristics:

[0113] (1) Improve energy efficiency: The unified control model prioritizes the use of distributed energy and feeds back excess power to the grid under appropriate conditions to optimize energy flow.

[0114] (2) Enhance system stability: Through flexible control and fault isolation between devices, single point failures can be prevented from affecting overall operation.

[0115] (3) Economic optimization: Effectively reduce users’ energy costs based on real-time load and grid price adjustment strategies.

[0116] (4) Promote the application of green energy: Promote the widespread application of green energy on the user side through an efficient energy management system.

[0117] The above is only a specific embodiment of the present invention, but the protection scope of the present invention is not limited thereto. Any technician familiar with the technical field can easily think of various equivalent modifications or replacements within the technical scope disclosed by the present invention, and these modifications or replacements should be included in the protection scope of the present invention. Therefore, the protection scope of the present invention shall be based on the protection scope of the claims.

Claims

1. A unified control method for multiple power sources and multiple energy storages at the user side, characterized in that: The steps include: Access energy management data; Based on the energy management data, determine whether the power generation on the user side meets the power demand. If so, enter the self-sufficiency + surplus power access / storage mode to make a decision; if not, enter the consumption mode to make a decision; In the self-sufficiency + surplus power grid / storage mode, the decision to sell or store excess power is made by comparing the power sales income and the power storage cost; In the consumption mode, the power generation and storage capacity on the user side are used to meet the power demand first. If the power generation and storage capacity on the user side cannot meet the power demand, the shortfall will be purchased from the power grid. Based on the decision results, the user-side distribution network is controlled.

2. A user-side multi-power supply and multi-energy storage unified control method according to claim 1, characterized in that: After acquiring energy management data, it also includes: Detecting abnormal data in the energy management data and correcting the abnormal values; removing noise from the energy management data using a filter; Fill in the missing data in the energy management data.

3. A user-side multi-power supply and multi-energy storage unified control method according to claim 1, characterized in that: The judgment of whether the power generation on the user side meets the power demand is implemented by the following formula: Pself=∑(i=1,…,n)Pgen,i-Pdemand Among them, Pself is the self-sufficient electricity, Pgen,i is the power generation of the ith subsystem, and Pdemand is the total electricity demand.

4. A user-side multi-power supply and multi-energy storage unified control method according to claim 1, characterized in that: The electricity sales income and electricity storage cost are obtained by the following formula: Csell=Psurplus×Pmarket Cstore=Psurplus×Cstorage Among them, Csell is the income from selling electricity, Pmarket is the electricity market price, Cstore is the cost of storing electricity, Cstorage is the storage cost per unit of electricity, and Psurplus is the excess electricity that can be used for storage.

5. A user-side multi-power supply and multi-energy storage unified control method according to claim 4, characterized in that: When the decision is to sell or store excess electricity, if Csell>Cstore, the excess electricity is sold, otherwise the excess electricity is stored.

6. A user-side multi-power supply and multi-energy storage unified control method according to claim 1, characterized in that: The process of deciding whether to sell or store excess electricity by comparing the electricity sales income and the electricity storage cost is implemented by the following formula: Pgrid=Pdemand-∑(i=1,…,n)Pgen,i Among them, Pgrid is the electricity that needs to be purchased from the grid, Pgen,i is the power generation of the i-th subsystem, and Pdemand is the total power demand.

7. A user-side multi-power supply and multi-energy storage unified control method according to claim 1, characterized in that: The energy management data includes status information of building loads, distributed generation and energy storage equipment.

8. A unified control system of multiple power sources and multiple energy storage systems at the user side, characterized in that: Used to implement the unified control method of multiple power sources and multiple energy storages on the user side as described in any one of claims 1 to 7, the control system includes: Data collection equipment to obtain energy management data; A data processing device is used to determine whether the power generation on the user side meets the power demand based on the energy management data. If so, enter the self-sufficiency + surplus power access / storage mode to make a decision. If not, enter the consumption mode to make a decision. In the self-sufficiency + surplus power access / storage mode, by comparing the power sales income and the power storage cost, a decision is made to sell or store the surplus power. In the consumption mode, the power generation and storage on the user side are preferentially used to meet the power demand. If the power generation and storage on the user side cannot meet the power demand, the shortfall is purchased from the power grid; The energy manager is used to control the user-side distribution network based on the decision results.

9. A user-side multi-power supply and multi-energy storage unified control system according to claim 8, characterized in that: The data acquisition device comprises: The sensor module is installed on the multi-power node, energy storage device node, energy conversion device node and energy distribution node, and is used to configure the collection frequency according to the importance of the device under test and collect operating parameters; A communication module, connected to the sensor module and connected to the control center via wired or wireless means; A data processing unit, used to correct outliers, filter noise and fill missing values ​​in the collected data; The power supply module supplies power to the device through an independent power supply or busbar.

10. A user-side multi-power supply and multi-energy storage unified control system according to claim 8, characterized in that: Multiple power supplies and energy storage devices are connected to the bus through a DC / DC or DC / AC interface. The DC / DC interface is connected to the DC energy storage device to adjust the voltage and power flow to ensure that the energy storage device matches the bus voltage. The DC / AC interface is used to connect to the AC power supply equipment and convert DC power into AC power through an inverter, which is synchronized with the bus voltage to meet the AC bus requirements.

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