Digital energy informatization processing and calculating method, device, equipment, medium and product of energy storage system

Abstract

The invention discloses a digital energy informatization processing and calculation method, device and equipment of an energy storage system, a medium and a product, and relates to the technical field of digital energy informatization processing. The method comprises the following steps: firstly, carrying out discretization acquisition on a simulated energy flow of an energy storage system to obtain a plurality of energy fragments; based on the reconfigurable characteristic of the battery network of the energy storage system, the energy fragments are recombined and optimized, and a battery state matrix of the energy storage system under the optimal topology condition is obtained; and controlling a switch array of the energy storage system according to the battery state matrix of the energy storage system under the optimal topology condition. According to the method, the analog energy flow of the energy storage system is discretized into the fine-grained energy fragments, and then the energy fragments are recombined through modeling and control of the information system, so that the same-frequency deep fusion of the energy flow and the information flow is realized, and the digital conversion of the energy storage system is realized; and flexible network-based management, control and operation of the energy storage system are realized.

Description

Technical Field

[0001] The present application relates to the technical field of digital energy information processing, and particularly to a digital energy information processing and calculation method, device, equipment, medium and product for an energy storage system. Background Art

[0002] Traditional energy systems need to achieve the transformation from analog systems to digital systems, that is, physically discretize and digitize the analog energy flow, and then deeply integrate it with the information flow, convert the energy into measurable and computable network resources like computing resources, bandwidth resources, and storage resources, and then flexibly manage, control, and operate it through information Internet technology. Summary of the Invention

[0003] The purpose of the present application is to provide a digital energy information processing and calculation method, device, equipment, medium and product for an energy storage system, so as to achieve the digital transformation of the energy storage system and realize the flexible network management, control, and operation of the energy storage system.

[0004] To achieve the above purpose, the present application provides the following solutions.

[0005] In the first aspect, the present application provides a digital energy information processing and calculation method for an energy storage system. The energy storage system is a power supply system for information energy equipment of communication base stations and data centers applied to communication and information systems. The digital energy information processing and calculation method for the energy storage system includes the following steps:

[0006] Discretely collect the analog energy flow of the energy storage system to obtain multiple energy fragments; the characteristic representations of the energy fragments include the time-domain representation and the frequency-domain representation of the energy fragments;

[0007] Based on the battery network reconfigurable characteristics of the energy storage system, reorganize and optimize the energy fragments to obtain the battery state matrix of the energy storage system under the optimal topology condition;

[0008] Control the switch array of the energy storage system according to the battery state matrix of the energy storage system under the optimal topology condition.

[0009] In the second aspect, the present application provides a digital energy information processing and calculation device for an energy storage system. The digital energy information processing and calculation device for the energy storage system is applied to the digital energy information processing and calculation method for the energy storage system described above. The digital energy information processing and calculation device for the energy storage system includes:

[0010] A discretized acquisition module, configured to discretely collect the analog energy flow of the energy storage system to obtain multiple energy fragments; the characteristic representations of the energy fragments include the time-domain representation and the frequency-domain representation of the energy fragments;

[0011] A reconstruction module, configured to reorganize and optimize energy fragments based on the reconfigurable characteristics of the battery network of the energy storage system, so as to obtain a battery state matrix of the energy storage system under optimal topology conditions;

[0012] A control module, configured to control the switch array of the energy storage system according to the battery state matrix of the energy storage system under optimal topology conditions.

[0013] In a third aspect, the present application provides a computer device, including: a memory, a processor, and a computer program stored on the memory and executable on the processor, where the processor executes the computer program to implement the above digital energy informatization processing and calculation method of the energy storage system.

[0014] In a fourth aspect, the present application provides a computer-readable storage medium, on which a computer program is stored, and when the computer program is executed by a processor, it implements the above digital energy informatization processing and calculation method of the energy storage system.

[0015] In a fifth aspect, the present application provides a computer program product, including a computer program, and when the computer program is executed by a processor, it implements the above digital energy informatization processing and calculation method of the energy storage system.

[0016] According to the specific embodiments provided by the present application, the present application has the following technical effects.

[0017] The present application provides a digital energy informatization processing and calculation method, device, equipment, medium and product for an energy storage system. The present application first discretely collects the analog energy flow of the energy storage system to obtain multiple energy fragments; then based on the reconfigurable characteristics of the battery network of the energy storage system, reorganizes and optimizes the energy fragments to obtain a battery state matrix of the energy storage system under optimal topology conditions; and controls the switch array of the energy storage system according to the battery state matrix of the energy storage system under optimal topology conditions. The present application discretizes the analog energy flow of the energy storage system into fine-grained energy fragments, and then reorganizes the energy fragments through information system modeling and control, thereby realizing the deep fusion of the energy flow and the information flow at the same frequency. The present application realizes the digital transformation of the energy storage system, and further realizes the flexible network management, control and operation of the energy storage system. Description of the Drawings

[0018] In order to more clearly illustrate the technical solutions in the embodiments of the present application or the prior art, the following will briefly introduce the drawings required for use in the embodiments. Obviously, the drawings in the following description are only some embodiments of the present application. For those of ordinary skill in the art, other drawings can be obtained based on these drawings without creative efforts.

[0019] Figure 1 Schematic flowchart of a digital energy informatization processing and calculation method for an energy storage system provided by an embodiment of the present application.

[0020] Figure 2 Schematic diagram of time-division multiplexing energy discretization processing provided by an embodiment of the present application.

[0021] Figure 3 Flowchart showing the discretization process of the simulated energy flow provided by an embodiment of the present application.

[0022] Figure 4 Flowchart of the digital quantization process of the simulated energy flow provided by an embodiment of the present application.

[0023] Figure 5 Schematic diagram of the equivalent circuit model of a single battery cell and a series-parallel battery circuit provided by an embodiment of the present application.

[0024] Figure 6 System architecture diagram of the co-frequency processing of energy flow and information information flow provided by an embodiment of the present application.

[0025] Figure 7 Battery connection topology diagram provided by an embodiment of the present application.

[0026] Figure 8 Logic structure of the energy storage network unit circuit provided by an embodiment of the present application.

[0027] Figure 9 Schematic diagram of the structure of a computer device provided by an embodiment of the present application. Detailed implementation manners

[0028] Next, the technical solutions in the embodiments of the present application will be clearly and completely described in conjunction with the accompanying drawings in the embodiments of the present application. Obviously, the described embodiments are only a part of the embodiments of the present application, rather than all the embodiments. Based on the embodiments in the present application, all other embodiments obtained by those of ordinary skill in the art without creative efforts shall fall within the protection scope of the present application.

[0029] To make the above objects, features, and advantages of the present application more obvious and understandable, the present application will be further described in detail below in conjunction with the accompanying drawings and specific implementation manners.

[0030] Energy informatization technology is the foundation and core of energy information fusion technology, and it is also the core technology for the energy system to improve energy efficiency and achieve multi-energy collaborative complementary utilization.

[0031] Energy informatization is the basis for realizing energy virtualization and also the central link for realizing the networked management and control of the energy Internet. The feasibility of energy informatization depends on the rapid development of advanced power electronics technology and information and communication technology. The physical basis for the integration of cyber-physical systems is the energy informatization processing chip and high-speed power electronic switching devices. The high-speed cyber-physical energy processing system formed by the same frequency of the microprocessor and advanced power electronic semiconductor devices can discretize the traditional analog energy flow into fine-grained energy fragments, and then through information system modeling and control, reorganize the energy fragments and endow them with rich information attributes, so as to realize the deep integration of the energy flow and the information flow at the same frequency.

[0032] This application proposes a digital energy informatization processing and calculation method, device, equipment, medium and product for an energy storage system, to realize the digital energy informatization processing of the energy storage system, the networked management and control with the devices of the energy storage system as the medium, and the same-frequency processing of the integration of the information flow and the energy flow.

[0033] In an exemplary embodiment, as Figure 1 shown, a digital energy informatization processing and calculation method for an energy storage system is provided. The energy storage system is a power supply system for information energy equipment of communication base stations and data centers applied to communication and information systems. The digital energy informatization processing and calculation method for the energy storage system includes the following steps:

[0034] Step 101, discretely collect the analog energy flow of the energy storage system to obtain multiple energy fragments; the characteristic representations of the energy fragments include the time-domain representation and the frequency-domain representation of the energy fragments.

[0035] Step 102, based on the battery network reconfigurable characteristics of the energy storage system, reorganize and optimize the energy fragments to obtain the battery state matrix of the energy storage system under the optimal topology conditions.

[0036] Step 103, control the switch array of the energy storage system according to the battery state matrix of the energy storage system under the optimal topology conditions.

[0037] Implementing the above Step 101 - Step 103 can achieve the digital transformation of the energy storage system, and realize the flexible networked management, control and operation of the energy storage system.

[0038] In another exemplary embodiment, the above Step 101 can be replaced by the following Step 201 - Step 202.

[0039] Step 201, discretely collect the analog energy flow of the energy storage system in a time-division multiplexing manner to obtain the pulsed energy flow of multiple energy fragments.

[0040] Step 202: Sample and quantify the pulse energy flow of each energy fragment using the Dirac function to obtain the time-domain representation and frequency-domain representation of each energy fragment.

[0041] Take the digital battery energy management and control system as an example to illustrate the digital energy information processing and calculation method of this application. As Figure 2 shown, in the digital battery energy management and control system, the analog energy flow is discretized into a group of "energy fragments". By using a program-controlled battery network controller, the "energy fragments" are then recombined and optimized to remove the uncertainties and non-linearities in the generation and use of battery energy, improving the system performance. In addition, battery energy informatization can also attach other information data to the "energy fragments", such as the owner of the battery assets, the battery charge state, the battery health state, etc., making the battery energy become a digital resource, and then seamlessly integrating into the management and control system of the information Internet to support the energy operation based on battery energy storage.

[0042] The idea of energy informatization of this application is also applied to the integration of various traditional industries including the energy industry, and provides an advanced information and communication technology foundation for the Internet revolution in the energy industry and the close integration of the energy physical system and the information system. The future energy system will become a multi-energy structure with priority consumption of renewable energy, based on secondary energy such as electricity, and supplemented by other primary energy, forming a reliable supply mode mainly based on distribution, supplemented by centralization, and coordinated with each other. Advanced information and communication technologies such as the Internet of Things, big data, and cloud computing constitute an information interconnection network. The information flow and the energy flow are tightly coupled through energy informatization devices to achieve information sharing in the energy network, effectively supporting the demand-supply interaction and orderly configuration of energy in the energy network. And the information flow will run through the entire life cycle of the energy Internet, including its planning, design, construction, operation, use, monitoring, maintenance, asset management, and asset evaluation and trading.

[0043] In another exemplary embodiment, the above time-division multiplexing energy discretization processing method is not first proposed in this application. The digital grid home energy management proposed by Kyoto University in Japan in 2010 provides an energy packet scheme. Using the time division multiplexing (TDM) method, the energy of multiple power supplies with different voltages is modulated onto a transmission line, and the energy router in the network demodulates the energy containing various voltage forms and distributes it to the corresponding load according to the IP address. This design scheme also adopts energy discretization processing and directly delivers the informatized energy to the power network. However, the time-division multiplexing method limits the scalability of the network. Due to the discrete energy transfer method, large-capacitance or large-inductance energy storage elements such as capacitors or inductors need to be added on the input side of the load to ensure continuous power supply to the load.

[0044] In the embodiment of the present application, by means of the multi-port converter (switch array) of the energy storage system, multiple renewable energy sources or loads can be connected simultaneously, and multi-directional energy flow can be achieved, overcoming the disadvantages of the time-division multiplexing method in the application of digital grid home energy management.

[0045] In another exemplary embodiment, the energy flow serves as the carrier of the information flow of the Information and Communication Technology (ICT) power supply system (hereinafter referred to as the ICT power supply system). There is an essential homologous relationship between the two. The high-frequency power electronic switching devices realize the discretization of the energy flow, enabling the energy flow to possess the information attributes in the time domain and frequency domain. The degree of informatization / digitization quantization of the energy flow determines the level of integration of the energy flow and the information flow. Affected by the informatization degree of the energy flow generated by the energy source and the circuit components of the ICT power supply system, in order to study the mechanism of energy information integration in the ICT power supply system, it is necessary to carry out research on the method of discretization / digitization of the energy flow assisted by high-frequency power electronic switches; considering that the battery has non-linear characteristics and the energy flow in and out of the battery has different response forms, the method of battery equivalent circuit and circuit analysis is adopted to study the time-domain / frequency-domain informatization characterization of the energy flow under the excitation of "energy fragments", and analyze the information attributes of the energy flow; finally, for the digital sustainable ICT power supply system including batteries, photovoltaics and other renewable energy sources, a circuit model that conforms to the attributes of the components of the digital power supply system is established, and the circuit model after the coupling of the battery and the power electronics is analyzed to realize the energy informatization of the ICT power supply system.

[0046] Regarding the trend of the integration of energy flow and information flow in the digitalization and informatization of the 5G information energy power supply system, studying the mechanism and method of the integration of energy flow and information flow helps to realize the informatization of the power supply system. Given the rapid development of high-voltage and high-power semiconductor devices, using power electronic switch semiconductors in the ICT power supply system makes the digitization of the energy flow possible. Through the circuit composed of high-frequency switching devices, the analog and continuous energy flow is discretized in the time domain to generate energy fragments, and the energy output of all channels is composed of the energy exchange system formed by power electronic switching devices (i.e., the switch array). The discretization process and quantization process of the analog energy flow are as Figure 3 shown.

[0047] After the energy fragments processed by power electronic discretization have quantifiable information under the influence of the power electronic circuit, the informatization characterization of the energy flow is the basis for realizing the integration of the energy flow and the information flow. Therefore, it is necessary to carry out research on the mechanism and method of the discretization process of continuous and analog energy flow. Through the quantization modeling of energy fragments, the information possessed by the discrete energy slices themselves is explored to characterize the time-domain and frequency-domain information contained in the energy fragments.

[0048] Assume that the system is a constant voltage source. The energy fragments after being transformed by the energy exchange system composed of a switch array can be sampled and quantified for the pulse energy flow of each energy fragment by using the Dirac function. The process is as Figure 4 shown, and can be specifically expressed as:

[0049]

[0050] Combined with the spectrum analysis method of the pulse width modulation signal, the frequency domain characterization of the energy fragment can be expressed as:

[0051]

[0052] In the above formulas (1) and (2), S(t) is the time domain characterization of the energy fragment, F(ω) is the frequency domain characterization of the energy fragment, t represents the time variable, ω represents the frequency variable, u(t - kT s ) is the amplitude of the pulse energy flow of the energy fragment at the moment of t - kT s , u(t - kT s - x k T s ) is the amplitude of the pulse energy flow of the energy fragment at the moment of t - kT s - x k T s , T s is the control period, k is the k-th control period, x k is the pulse energy flow of the energy fragment in the k-th control period, and j is the imaginary unit.

[0053] Furthermore, in the digital energy storage system circuit where the battery is coupled with the power electronic circuit, the quantified energy fragment is used as the input of the battery. Determining the output of the energy storage system on the premise of the known input energy flow is one of the key tasks of energy information fusion. In the embodiments of this application, an equivalent circuit model of a single battery cell and a battery module is established, and an equivalent circuit model including a single battery cell and a parallel battery pack based on Figure 5 is proposed.

[0054] Subsequently, considering the influence of factors such as the environmental temperature T, the charge and discharge rate C, the battery life cycle L, and the reconfigurable battery topology connection G, the equivalent battery circuit model and the power electronic switch model are incorporated into the analysis system of energy and information fusion of the digital energy storage system, and a "bottom-up" system that incorporates circuit analysis theory into the energy and information fusion system of the digital energy storage system is established. Circuit transfer models of battery energy storage, power electronic topology, and load are established as G c , G m , G vd , H respectively. Then the energy model of the system output is:

[0055] G0(s) = G c(s)·G m (s)·G vd (s)·H(s) (3)

[0056] Among them, G0(s) is the output energy of the energy storage system, and s is the Laplace variable.

[0057] Finally, based on the advantage that a single battery can be disconnected, a method for estimating the battery SOC (State of Charge) based on open-circuit voltage detection is developed, and the design optimization relationship between the equivalent charge capacity of the battery network topology and the structure of the power electronic switch array is studied. By defining the battery network topology performance evaluation function G = E, S, D (where the array E represents the current and temperature data of the corresponding battery measured by the sensor, the array S represents the power electronic switch state, and the array D represents the connection relationship of the battery network), comprehensively considering the different working conditions of the single battery and the topological connection state structure between them, the design optimization relationship between the equivalent charge capacity of the battery network topology and the structure of the power electronic switch array is quantitatively characterized.

[0058] In another exemplary embodiment, the specific implementation manner of the above step 102 is as follows:

[0059] Since the voltage and capacity of the energy storage unit are low, in order to meet the capacity requirements of the ICT power supply system, multiple batteries need to be recombined for use. In a digital energy storage system where the energy flow and information flow are at high frequencies, a system architecture that integrates the energy flow and information flow is required to achieve efficient scheduling of energy resources. The embodiments of the present application start from a digital battery energy storage system in which a battery is coupled with a power electronic switch (switch array) in the energy storage system, study the design of a flexible connection digital system composed of a power electronic switch and a reconfigurable battery network, and propose a distributed architecture of a digital battery system with power electronic and battery coupling; on the basis of a digital energy storage system composed of a reconfigurable battery network, the theoretical method of digital signal processing is used to represent the analog energy system, establish the characteristic and state mathematical models of a single energy network node, and then adopt a networked digital energy storage resource optimization method to realize the energy and information fusion networked resource scheduling method of the digital energy storage system.

[0060] Different from the fixed battery network system of traditional batteries, the battery network system with battery and power electronic switch coupling creatively uses high-frequency power electronic devices as analog-to-digital conversion (A / D) devices and then constructs an information energy system through digital signal processing theory. The battery and power electronic coupling form a reconfigurable battery system to realize the same-frequency processing of energy flow and information flow. The embodiments of the present application intend to use the theoretical method of digital signal processing to represent the analog energy system, discretize the modeling of the analog energy flow output by the battery, in order to online estimate the battery network characteristics and optimize the control by digital methods. Construct a theoretical framework for energy digitization and information processing, and intend to propose such as Figure 6The system theoretical model for energy informatization processing shown.

[0061] Considering that the digital signal processing theory system cannot be directly applied to the field of energy informatization processing, mainly because of the different properties and differences of signal sources (i.e., the difference between batteries and weak signal sources), the transient and steady-state characteristics inherent in the continuous battery energy flow, and the requirements of the output energy flow of the battery energy storage system to meet the dynamic working conditions in terms of current, voltage, power, etc.

[0062] The embodiments of this application intend to construct a TDM (Time Division Multiplexing) system architecture composed of a mathematical model of a reconfigurable battery network system based on the theoretical basis of energy informatization. It intends to use the switch array as the A / D conversion array, and then study the mapping relationship between battery monomers and signal sources, and the mapping relationship between battery arrays and signal arrays. Through digital signal processing methods, the analog energy flow of each single battery is discretized, and then through digital means, the digitalization, informatization, and network management and control of multiple analog energy flows are achieved. In the reconfigurable battery network, each single battery is connected to the charge and discharge circuit through a controllable high-frequency power electronic switch device. By defining the digital control matrix H of the switch array: the elements in H are 1 or 0, to map the conduction state of each switch in the switch array; define the matrix S k as the battery state matrix in the kth control period; the matrix D k as the battery capacity matrix in the kth control period, and the matrix element D ij represents the capacity of a single battery; the matrix R k as the capacity recovery matrix of the battery when it is idle in the kth control period, and the matrix element R ij represents the self-recovery amount of the capacity of a single battery. Therefore, the battery state matrix S k , the battery capacity matrix D k and the capacity recovery matrix R k are respectively:

[0063]

[0064] Subsequently, a dynamic reconfiguration strategy for the topology of the reconfigurable battery network coupled with power electronic devices is studied. Its purpose is to select the optimal battery network topology to achieve the efficient utilization of the effective capacity in the current reconfiguration period. The high-speed power electronic switch device discretizes and digitalizes the analog energy flow and outputs it in the form of a group of energy slices. That is, through the above digital control matrix, the analog energy signals: D1(t), …, D n*m (t), can be converted into the energy slices C1(n), …, C n*m(n). In a digital energy storage system, for the changing load demands at different times, the system output power demand is: P(k) = V(k) * I(k), where P(k) is the output power demand of the energy storage system in the k-th control period, V(k) is the output voltage demand of the energy storage system in the k-th control period, and I(k) is the output current demand of the energy storage system in the k-th control period. For the load demand L, the effective capacity change provided by the reconfigurable battery network for N reconfiguration periods is:

[0065]

[0066] where, is the Hadamard product operator. Therefore, the reconfigurable battery network can be modeled as: Furthermore, the output characteristics of the reconfigurable battery network can be written as:

[0067]

[0068] where, D k is the battery capacity matrix of the energy storage system in the k-th control period, S k is the battery state matrix of the energy storage system in the k-th control period, S opt is the battery state matrix of the energy storage system under the optimal topology condition, f is the effective battery capacity of the energy storage system under the current topology condition, and f opt is the effective battery capacity of the energy storage system under the optimal topology condition.

[0069] When solving S opt and f opt according to the above formula (6), P(k) can be used as a constraint, and the obtained optimal topology condition needs to satisfy the above output power demand, that is, the output power of the energy storage system under the optimal topology condition is not less than the above output power demand.

[0070] In another exemplary embodiment, to illustrate the application process of the above method, the following specific example is provided.

[0071] For simplicity, only a three-module system is considered. The same concept also applies to systems with a larger number of modules, that is, high-voltage battery systems. The entire converter consists of a mode selector, a boost converter, a mode selector, a regeneration switch, and a charger / backup switch. The mode selector supports reconfiguration and switching between different modes, provides load, balancing, charging, and backup conversion topologies from an external power source, and implements different controls. The battery connection topology is as Figure 7 shown.

[0072] The high-voltage battery system consists of two energy Internet nodes. The first node (hereinafter referred to as Node 1) includes seven energy storage network units, three DC servers, and three AC-DC power supplies. The second node (hereinafter referred to as Node 2) includes one battery energy switch, one set of second-life power lithium batteries retired from electric buses, and one AC-DC power supply.

[0073] The physical topology of the high-voltage battery system adopts a hybrid bus structure to improve efficiency and reduce costs. The specific connection method is as follows:

[0074] Node 1 is connected by a 12V DC bus.

[0075] Node 2 (including one battery energy switch and an AC-DC power supply) is interconnected by a 14.2V DC bus.

[0076] The information communication part of the high-voltage battery system is completed by a local CAN bus and an interconnected CAN bus. The energy storage network units in Node 1 complete communication and collaborative work in the configuration mode of the local CAN bus. Among them, one energy storage network unit is set as the CAN bus host, and the remaining six are slaves. The energy storage network unit host and the battery energy switch are connected to the central energy controller through the interconnected CAN bus, and protocol format conversion and data processing are completed on the energy controller, and access to the Internet is achieved through the Ethernet port.

[0077] The user software communicates with the central energy controller through the Ethernet, and communicates with the energy storage network unit host, the energy storage network unit slaves, and the battery energy switch through the central energy controller.

[0078] The high-voltage battery system has two working modes: the energy Internet simulation and experimental platform mode, and the distributed DC UPS (Uninterruptible Power Supply) system mode.

[0079] In the energy Internet simulation and experimental platform mode, the user software can control the working modes of each energy storage network unit and the battery energy switch through the command instruction set and status instruction set provided by the supplier, and obtain the status of each energy storage network unit, the battery energy switch, and each battery therein.

[0080] In the distributed DC UPS system mode, the energy storage network units and the battery energy switch can automatically detect the on / off of the mains power and enter the corresponding charging or discharging state to ensure continuous power supply to the servers and DC loads. The monitoring software provided by the supplier can obtain and display the status of each energy storage network unit, the battery energy switch, and each battery therein.

[0081] The main technical indicators are as follows:

[0082] The high-voltage battery system includes 2 energy Internet nodes, 1 energy controller, and 1 network switch.

[0083] The devices in the first node are connected through a 12V DC bus system, and the voltage range of the DC bus is 10V - 15V.

[0084] The devices in the second node are connected through a 14.2V DC bus system, and the voltage range of the DC bus is 10V - 16.8V.

[0085] The energy storage network units in the first node are connected by a local CAN bus. One of the energy storage network units is set as the CAN bus master, and the rest are slaves. The master is responsible for coordinating the power-on and power-off of all energy storage network units in the group to ensure the coordinated operation of the energy storage network units in this node.

[0086] The user software communicates with the energy controller through Ethernet and communicates with the master and slave of the energy storage network unit and the battery energy switch through the energy controller. The communication protocol is designed by our company itself, ensuring the security of the system.

[0087] All energy storage network units and battery energy switches can work simultaneously, and the software can independently control the charge and discharge states and currents of each energy storage network unit and battery energy switch.

[0088] In each node, an AC-DC transformer is used to convert 220VAC mains into 12VDC (for energy storage network units) and 14.2VDC (for battery energy switches).

[0089] The master of the energy storage network unit and the battery energy switch are connected to the energy controller through an interconnected CAN bus to complete the conversion of the syntax and semantics of the control protocol and realize the function of the gateway.

[0090] Each device in the high-voltage battery system has protection circuits such as overcurrent, short circuit, and overheating, and has an alarm function.

[0091] The total energy storage capacity of the first node (7 energy storage network units) is greater than 2.6KWh, while the capacity of the second node (i.e., the battery energy switch) is greater than 2.2KWh.

[0092] The maximum input power of the first node is 4.5KW (the maximum input power during charging of 7 energy storage network units is 2.5KW, and the maximum power consumption of the load is 2.0KW). The maximum input power of the second node is 1.5KW (the maximum input power during charging of the battery energy switch is 400W, and the maximum power consumption of the load is 1.1KW).

[0093] The maximum output power of the first node (7 energy storage network units) is 10.5 KW, while the maximum output power of the second node (i.e., the battery energy switch) is 1.7 KW.

[0094] Based on the above indicators, the digital energy informatization processing and calculation device is set as follows.

[0095] (1) Digital energy informatization processing and calculation device.

[0096] The digital energy informatization processing and calculation device is an intelligent power management system containing a battery pack, which is customized for the distributed battery energy control technology demonstration system based on energy informatization. Its functions can be divided into two modes according to the configuration of the monitoring software and the central energy controller: the distributed DC UPS working mode and the energy Internet simulation and experimental platform mode. According to its different functions implemented in the energy storage network unit, it can also be configured as a host or a slave. The host is used to collect the status of itself and its subordinate slaves and the battery information of each node, communicate with the monitoring software through the central energy controller, and at the same time issue instructions from the monitoring software to the subordinate slaves. And provide a synchronization signal to the slaves in the UPS working mode.

[0097] When the digital energy informatization processing and calculation device works in the UPS mode, its function is positioned as a distributed DC uninterruptible energy storage power system, which can automatically detect the external power supply status. When the external power supply is normal, the system charges the battery or battery pack according to the detected battery status; when the external power supply fails, the system provides emergency power supply for the electrical equipment to ensure the data security of the electrical equipment. And the minimum number of discharge units can be configured through the host according to the situation of the external load, which has the advantages of high flexibility and good reliability.

[0098] When the digital energy informatization processing and calculation device works in the energy Internet simulation and experimental platform mode, users can freely configure the opening and closing of the switches of each battery in the energy storage network unit, the charge and discharge switching, and the magnitude of the charging current through the monitoring software, so that it is completely at the free disposal of the users.

[0099] The front panel of the digital energy informatization processing and calculation device is set with status indicators to provide on-site monitoring for users. And an external manual switch is provided to facilitate users to install and maintain the hardware equipment and ensure the personal safety of the maintenance personnel.

[0100] (2) Functions of the digital energy informatization processing and calculation device.

[0101] Since the battery management system is based on a large-scale battery network and the control granularity can reach the single battery, this poses great challenges to the system architecture design of the battery energy control technology based on energy informatization, mainly including the following difficulties:

[0102] A1. Guarantee of information data accuracy.

[0103] The accuracy of information data such as measurement and estimation is the key basis for ensuring the performance of the battery management system. The battery network needs to collect the voltage information of each single battery cell in real time and perform parameter estimation of SOC. The amount of information data for measurement and estimation is huge, which greatly increases the difficulty of ensuring the accuracy of information data.

[0104] A2. Guarantee of control system reliability.

[0105] The battery network needs to realize the topological dynamic adjustment of battery energy management and control by controlling a large-scale switch array. Any control error of a switch may be fatal to the entire battery system. Coupled with other control and protection of charging, discharging, and temperature for each single battery cell, the risk of control error increases sharply.

[0106] A3. Limited component data processing ability.

[0107] Due to the huge amount of data that the battery network system needs to process and the need to achieve real-time and rapid control decisions, the adaptation between the data processing ability of components (processor computing ability and component storage ability) and system requirements, including the selection of the number of processors and the setting of the modules to which the processors belong, is also an important difficulty in the modular design of the system.

[0108] A4. Limited space, power consumption, and cost overhead.

[0109] To solve the above difficulties may lead to an increase in the space occupied by the system, the power consumption of the system itself, and the manufacturing cost of the system. The modular design must fully consider how to maximize the systematicness of energy management and control while meeting the constraints of space, power consumption, and cost overhead.

[0110] The circuit of the energy storage network unit of the above high-voltage battery system includes a main control circuit, a charging circuit, a discharging circuit, a power distribution circuit, and a communication circuit, etc., as Figure 8 shown.

[0111] B1. Main control circuit.

[0112] The main control circuit controls the overall state of the system, coordinates the work between various circuit parts, issues corresponding commands to each part of the circuit according to the system state and user instructions, and collects the state data of each part of the circuit for the decision-making basis of internal control or uploads it to the external monitoring system.

[0113] The core of the main control circuit is a central control chip independently designed by Shandong Yunchu. The central control chip integrates the core algorithms for battery and system management. Furthermore, the implementation process of the digital energy informatization processing and calculation method of the above energy storage system is also integrated in the main control circuit.

[0114] B2. Charging circuit.

[0115] The charging circuit is responsible for the charging management of the battery, determining the start and end of charging and the charging current value according to the instructions of the main control circuit. The charging circuit also detects the fully charged state of the battery, manages the balance of the battery pack during charging, and detects the health status of the battery during charging. The charging circuit also collects data during charging for use by the main control circuit and can upload it to an external monitoring system.

[0116] B3. Discharging circuit.

[0117] The discharging circuit is responsible for the discharging management of the battery, determining the start and end of discharging according to the instructions of the main control circuit. The discharging circuit also detects the cut-off state of the battery, manages the balance of the battery pack during discharging, and detects the health status of the battery during discharging. The discharging circuit also collects data during discharging for use by the main control circuit and can upload it to an external monitoring system.

[0118] B4. Power distribution circuit.

[0119] The power distribution circuit of the energy storage network unit is the interface for the DC input and output of the system, responsible for the safety protection of the input and output. The power distribution circuit can also receive the instructions of the main control circuit to ensure a smooth transition when the system switches between charging and discharging.

[0120] B5. Communication circuit.

[0121] The communication circuit of the energy storage network unit is responsible for controlling the communication between the system and the outside world and processing the communication protocol. The status data uploaded by the system and the user controls received all pass through the communication circuit.

[0122] Based on the above digital energy information processing and calculation method of the energy storage system, a digital energy processing and calculation device is developed. This device has all the above functions. Specifically, this device has functions such as accurate information collection and system reliability protection. The implementation solutions provided by this device to solve problems are similar to the implementation solutions recorded in the above method. Therefore, the specific limitations in one or more embodiments of the digital energy information processing and calculation device of the energy storage system provided below can refer to the limitations on the digital energy information processing and calculation method of the energy storage system in the above text, and will not be elaborated here.

[0123] In an exemplary embodiment, a digital energy information processing and calculation device for an energy storage system is provided, including:

[0124] A discretization acquisition module, used to discretize and acquire the analog energy flow of the energy storage system to obtain multiple energy fragments; the characteristic representations of the energy fragments include the time-domain representation and frequency-domain representation of the energy fragments;

[0125] A reconstruction module, configured to reorganize and optimize energy fragments based on the reconfigurable characteristics of the battery network of the energy storage system, so as to obtain a battery state matrix of the energy storage system under optimal topological conditions;

[0126] A control module, configured to control the switch array of the energy storage system according to the battery state matrix of the energy storage system under optimal topological conditions.

[0127] In an exemplary embodiment, a computer device is provided. The computer device can be a server or a terminal, and its internal structural diagram can be as shown in Figure 9 the figure. The computer device includes a processor, a memory, an input / output interface (Input / Output, abbreviated as I / O), and a communication interface. Among them, the processor, the memory, and the input / output interface are connected through a system bus, and the communication interface is connected to the system bus through the input / output interface. Among them, the processor of the computer device is used to provide computing and control capabilities. The memory of the computer device includes a non-volatile storage medium and an internal memory. The non-volatile storage medium stores an operating system, a computer program, and a database. The internal memory provides an environment for the operation of the operating system and the computer program in the non-volatile storage medium. The input / output interface of the computer device is used to exchange information between the processor and external devices. The communication interface of the computer device is used to communicate with an external terminal through a network connection. When the computer program is executed by the processor, it implements a digital energy information processing and calculation method for an energy storage system.

[0128] Those skilled in the art can understand that Figure 9 the structure shown in is only a block diagram of some structures related to the solution of the present application, and does not constitute a limitation on the computer device to which the solution of the present application is applied. The specific computer device may include more or fewer components than those shown in the figure, or combine certain components, or have different component arrangements. In an exemplary embodiment, a computer device is provided, including a memory and a processor. A computer program is stored in the memory, and when the processor executes the computer program, the steps in the above method embodiments are implemented.

[0129] In an exemplary embodiment, a computer-readable storage medium is provided, storing a computer program, and when the computer program is executed by a processor, the steps in the above method embodiments are implemented.

[0130] In an exemplary embodiment, a computer program product is provided, including a computer program, and when the computer program is executed by a processor, the steps in the above method embodiments are implemented.

[0131] It should be noted that the user information (including but not limited to user device information, user personal information, etc.) and data (including but not limited to data for analysis, stored data, displayed data, etc.) involved in this application are all information and data authorized by the user or fully authorized by all parties.

[0132] Those of ordinary skill in the art can understand that all or part of the processes in the methods of the above embodiments can be completed by instructing relevant hardware through a computer program. The computer program can be stored in a non-volatile computer-readable storage medium. When the computer program is executed, it can include the processes of the embodiments of the above methods. Among them, any reference to a memory, database, or other medium used in the various embodiments provided in this application can include at least one of non-volatile and volatile memories. Non-volatile memory can include read-only memory (ROM), magnetic tape, floppy disk, flash memory, optical memory, high-density embedded non-volatile memory, resistive random access memory (ReRAM), magnetoresistive random access memory (MRAM), ferroelectric random access memory (FRAM), phase change memory (PCM), graphene memory, etc. Volatile memory can include random access memory (RAM) or external cache memory, etc. By way of illustration and not limitation, RAM can be in various forms, such as static random access memory (SRAM) or dynamic random access memory (DRAM), etc.

[0133] The databases involved in the various embodiments provided in this application can include at least one of relational databases and non-relational databases. Non-relational databases can include distributed databases based on blockchain, etc., without limitation. The processors involved in the various embodiments provided in this application can be general-purpose processors, central processors, graphics processors, digital signal processors, programmable logic devices, data processing logics based on quantum computing, etc., without limitation.

[0134] The technical features of the above embodiments can be combined arbitrarily. For the sake of brevity of description, not all possible combinations of the technical features in the above embodiments are described. However, as long as there is no contradiction in the combination of these technical features, it should be considered as the scope recorded in this specification.

[0135] In this text, specific examples are used to elaborate on the principles and implementation manners of this application. The description of the above embodiments is only used to help understand the method and its core idea of this application; at the same time, for those of ordinary skill in the art, according to the idea of this application, there will be changes in the specific implementation manners and application scopes. To sum up, the content of this specification should not be construed as a limitation on this application.

Claims

1. A digital energy information processing and calculation method for an energy storage system, characterized in that, The energy storage system is a power supply system for information energy equipment of communication base stations and data centers applied to communication and information systems. The digital energy information processing and calculation method of the energy storage system includes the following steps: Discretely collect the analog energy flow of the energy storage system to obtain multiple energy fragments; the characteristic representations of the energy fragments include the time-domain representation and the frequency-domain representation of the energy fragments; Based on the battery network reconfigurable characteristic of the energy storage system, reorganize and optimize the energy fragments to obtain the battery state matrix of the energy storage system under the optimal topology condition; Control the switch array of the energy storage system according to the battery state matrix of the energy storage system under the optimal topology condition.

2. The digital energy informatization processing and calculation method of the energy storage system according to claim 1, wherein Discretely collect the analog energy flow of the energy storage system to obtain multiple energy fragments, specifically including: Discretely collect the analog energy flow of the energy storage system in a time-division multiplexing manner to obtain the pulsed energy flow of multiple energy fragments; Sample and quantize the pulsed energy flow of each energy fragment using the Dirac function to obtain the time-domain representation and the frequency-domain representation of each energy fragment.

3. The digital energy informatization processing and calculation method of the energy storage system according to claim 2, wherein, The time-domain representation and the frequency-domain representation of each energy fragment are: Among them, S(t) is the time-domain representation of the energy fragment, F(w) is the frequency-domain representation of the energy fragment, t represents the time variable, w represents the frequency variable, and u(t - kT s ) is the amplitude of the pulsed energy flow of the energy fragment at t - kT s moment, and u(t - kT s - x k T s ) is the amplitude of the pulsed energy flow of the energy fragment at t - kT s - x k T s moment, T s is the control period, k is the kth control period, x k is the pulsed energy flow of the kth control period of the energy fragment, and j is the imaginary unit.

4. The digital energy information processing and calculation method of the energy storage system according to claim 1, characterized in that Based on the battery network reconfigurable characteristic of the energy storage system, reorganize and optimize the energy fragments to obtain the battery state matrix of the energy storage system under the optimal topology condition, specifically including: Based on the battery network reconfigurable characteristic of the energy storage system, construct the following reorganization model: Among them, D k is the battery capacity matrix of the energy storage system in the k-th control cycle, S k is the battery state matrix of the energy storage system in the k-th control cycle, is the Hadamard product operator, S opt is the battery state matrix of the energy storage system under the optimal topology condition, f is the effective battery capacity of the energy storage system under the current topology condition, f opt is the effective battery capacity of the energy storage system under the optimal topology condition; Solve the reorganization model to determine the battery state matrix of the energy storage system under the optimal topology condition.

5. The digital energy informatization processing and calculation method of the energy storage system according to claim 1, characterized in that, The energy fragments are also attached with battery energy information, and the battery energy information includes the owner of the battery assets, the battery charge state, and the battery health state.

6. A digital energy information processing and calculation device for an energy storage system, characterized in that, The digital energy information processing and calculation device of the energy storage system is applied to the digital energy information processing and calculation method of the energy storage system according to any one of claims 1-5. The digital energy information processing and calculation device of the energy storage system includes: A discretization collection module for discretely collecting the analog energy flow of the energy storage system to obtain multiple energy fragments; the characteristic representations of the energy fragments include the time-domain representation and the frequency-domain representation of the energy fragments; A reconstruction module for reorganizing and optimizing the energy fragments based on the battery network reconfigurable characteristic of the energy storage system to obtain the battery state matrix of the energy storage system under the optimal topology condition; A control module for controlling the switch array of the energy storage system according to the battery state matrix of the energy storage system under the optimal topology condition.

7. A computer device, comprising: A memory, a processor, and a computer program stored on the memory and executable on the processor, wherein the processor executes the computer program to implement the digital energy information processing and calculation method of the energy storage system according to any one of claims 1-5.

8. A computer-readable storage medium having a computer program stored thereon, characterized in that, When the computer program is executed by the processor, it implements the digital energy information processing and calculation method of the energy storage system according to any one of claims 1-5.

9. A computer program product, comprising a computer program, characterized in that, When the computer program is executed by the processor, it implements the digital energy information processing and calculation method of the energy storage system according to any one of claims 1-5.

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