Energy storage system based on intelligent overcharge station

Abstract

The invention relates to the technical field of energy storage, and discloses an energy storage system based on an intelligent over-charging station, which comprises an intelligent scheduling module, an Internet of Things monitoring module, a fault early warning module, a power supply module, a power supply module, a power supply module, a power supply module, a power supply module and a power supply management module according to the state information of the energy storage system, the working state information of a charging pile and the charging demand information of a vehicle, the fault early warning module is connected with the Internet of Things monitoring module, and the remote maintenance module is connected with the fault early warning module and used for carrying out remote diagnosis and maintenance operation on fault equipment after receiving the fault early warning signal. Efficient distribution and management of energy are achieved through the intelligent dispatching module, vehicle braking energy can be effectively recycled in combination with the energy recycling module, the energy utilization efficiency is improved, the charging power can be dynamically adjusted, stable operation of the energy storage system can be ensured, meanwhile, the charging process is optimized, the energy utilization efficiency is improved, and the energy utilization efficiency is improved. And the condition of over-charging or over-discharging is avoided.

Description

Technical Field

[0001] The present invention relates to the field of energy storage technology, and specifically to an energy storage system based on a smart supercharging station. Background Art

[0002] With the accelerated transformation of the global automotive industry to the field of new energy, the electric vehicle market has shown explosive growth. However, problems such as electric vehicle range anxiety and long charging time are still key factors restricting its further popularization. Smart supercharging stations have emerged as an important infrastructure to solve this dilemma, but their development currently faces many challenges.

[0003] The energy storage systems of existing supercharging stations still have shortcomings in energy management. In terms of energy distribution, there is a lack of intelligent scheduling mechanism, and it is impossible to reasonably distribute energy according to the actual situation of charging piles and energy storage systems, which easily leads to uneven power distribution in the energy storage system. Moreover, most existing systems do not consider vehicle braking energy recovery, have low energy utilization, and cannot dynamically adjust power during charging, which cannot ensure the stable operation of the energy storage system. Summary of the invention

[0004] In view of the deficiencies in the prior art, the present invention provides an energy storage system based on a smart supercharging station, which solves the problems of unreasonable energy distribution and imperfect power adjustment function of the existing supercharging station energy storage system.

[0005] To achieve the above objectives, the present invention is implemented through the following technical solutions: an energy storage system based on a smart supercharging station, comprising:

[0006] Intelligent scheduling module, which is used to allocate and manage energy using a preset scheduling algorithm based on the status information of the energy storage system, the working status information of the charging pile and the charging demand information of the vehicle to ensure efficient use of energy;

[0007] The Internet of Things monitoring module is connected to the energy storage system and the charging pile to collect the operating parameters and status information of the energy storage system and the charging pile in real time and transmit it to the intelligent scheduling module;

[0008] A fault warning module is connected to the Internet of Things monitoring module, and is used to receive the operating parameters and status information, and determine whether there is a fault risk in the energy storage system and the charging pile according to a preset fault judgment rule, and if so, issue a fault warning signal;

[0009] The remote maintenance module is connected to the fault warning module and is used to perform remote diagnosis and maintenance operations on the faulty equipment after receiving the fault warning signal.

[0010] Preferably, the scheduling algorithm in the intelligent scheduling module is:

[0011]

[0012] Among them, E 分配 is the energy allocated to charging pile i, P i is the rated power of the charging pile, T i is the estimated charging time of the vehicle at the charging pile, n is the number of charging piles, k is the adjustment coefficient determined according to the remaining power of the energy storage system and the charging and discharging efficiency, and 0<k≤1.

[0013] Preferably, the Internet of Things monitoring module includes multiple sensors, including but not limited to current sensors, voltage sensors, temperature sensors and power sensors, which are used to collect current, voltage, temperature and power information of the energy storage system and the charging pile respectively.

[0014] Preferably, the fault judgment rules in the fault warning module include: when the temperature of the energy storage system exceeds a preset temperature threshold, or the voltage fluctuation exceeds a preset voltage fluctuation range, or the output current of the charging pile is abnormal, it is determined that there is a fault risk.

[0015] Preferably, the remote maintenance module includes a remote diagnosis unit and a remote operation unit, the remote diagnosis unit is used to perform fault analysis and location on the faulty device, and the remote operation unit is used to perform parameter adjustment, software upgrade and control instruction sending operations on the faulty device according to the diagnosis result.

[0016] Preferably, it also includes an energy recovery module for recovering energy of the vehicle during braking and storing the recovered energy in an energy storage system. The energy recovery module is connected to an intelligent scheduling module, and the intelligent scheduling module manages the storage and distribution of the recovered energy according to the power status of the energy storage system and the characteristics of the recovered energy.

[0017] Preferably, the energy recovery module adopts a maximum power point tracking algorithm to improve energy recovery efficiency. The maximum power point tracking algorithm formula is:

[0018]

[0019] Among them, P m is the maximum power recovered, U oc is the open circuit voltage, I sc is the short-circuit current, R l is the load resistance, R s is the equivalent series resistance.

[0020] Preferably, the energy storage system adopts one or more energy storage technologies selected from lithium batteries, supercapacitors and flywheel energy storage, and the intelligent scheduling module optimizes the distribution and management of energy according to the charging and discharging characteristics and states of different energy storage technologies.

[0021] Preferably, the energy dispatching method of the energy storage system based on the smart supercharging station includes the following steps:

[0022] Step 1: After the vehicle is connected to the charging pile, the charging pile sends the vehicle's charging demand information to the intelligent scheduling module, including the vehicle's battery type, remaining power and expected charging time;

[0023] Step 2: The intelligent scheduling module calculates the charging power and charging time allocated to the vehicle based on the received charging demand information, combined with the current power and status of the energy storage system and the working conditions of other charging piles, using a preset scheduling algorithm, and sends a control instruction to the charging pile;

[0024] Step 3: During the charging process, the IoT monitoring module collects the status information of the energy storage system and the charging pile in real time and transmits it to the intelligent scheduling module. The intelligent scheduling module dynamically adjusts the charging power and time according to the real-time information;

[0025] Step 4: When the vehicle is fully charged, the charging pile sends a charging end signal to the intelligent scheduling module, and the intelligent scheduling module updates the power and status information of the energy storage system.

[0026] Preferably, the method by which the intelligent scheduling module dynamically adjusts the charging power and time is:

[0027]

[0028] Among them, P t is the adjusted charging power, P0 is the initially allocated charging power, ΔS is the change in the energy storage system capacity, S0 is the initial capacity of the energy storage system, ΔT is the difference between the charged time and the expected charging time, and T0 is the expected charging time.

[0029] The present invention provides an energy storage system based on a smart supercharging station. It has the following beneficial effects:

[0030] 1. The present invention realizes efficient distribution and management of energy through the intelligent scheduling module, and can effectively recover vehicle braking energy in combination with the energy recovery module, thereby improving energy utilization efficiency.

[0031] 2. The present invention can dynamically adjust the charging power according to the change in the amount of electricity in the energy storage system and the deviation in the charging time, which helps to ensure the stable operation of the energy storage system, while optimizing the charging process, improving energy utilization efficiency, and avoiding overcharging or over-discharging.

[0032] 3. Through the setting of the Internet of Things monitoring module and the fault warning module, the present invention can monitor the operating status of the energy storage system and the charging pile in real time, discover faults in time and issue warnings, thereby ensuring the safe operation of the system. The remote maintenance module facilitates remote diagnosis and maintenance operations of faulty equipment, thereby reducing maintenance costs. BRIEF DESCRIPTION OF THE DRAWINGS

[0033] Figure 1 is a system block diagram of the present invention;

[0034] Figure 2 This is a flow chart of the energy scheduling method of the present invention. DETAILED DESCRIPTION

[0035] The following will be combined with the drawings in the specification of the present invention to clearly and completely describe the technical solutions in the embodiments of the present invention. Obviously, the described embodiments are only 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 are within the scope of protection of the present invention.

[0036] Example:

[0037] Please refer to the attached Figure 1 , an embodiment of the present invention provides an energy storage system based on a smart supercharging station, comprising:

[0038] The intelligent scheduling module is used to allocate and manage energy based on the status information of the energy storage system, the working status information of the charging piles and the charging demand information of the vehicle, using a preset scheduling algorithm to ensure efficient use of energy. The intelligent scheduling module can accurately allocate energy according to the charging needs of different vehicles and the status of the energy storage system. Without such intelligent scheduling, some charging piles may allocate too much energy, causing the energy storage system to be quickly exhausted, while other charging piles have insufficient energy. Through the scheduling of this module, energy waste is avoided, the electric energy in the energy storage system is fully and reasonably utilized, and the energy utilization efficiency of the entire charging station is improved. Reasonable energy allocation can not only reduce the charging waiting time of the vehicle, but also avoid irreversible damage to the battery in the energy storage system caused by excessive charging and discharging. The scheduling algorithm in the intelligent scheduling module is:

[0039]

[0040] Among them, E 分配 is the energy allocated to charging pile i, P i is the rated power of the charging pile, T i is the estimated charging time of the vehicle at the charging pile, n is the number of charging piles, k is the adjustment coefficient determined according to the remaining power of the energy storage system and the charging and discharging efficiency, and 0<k≤1;

[0041] The Internet of Things monitoring module is connected to the energy storage system and the charging pile, and is used to collect the operating parameters and status information of the energy storage system and the charging pile in real time, and transmit it to the intelligent scheduling module. The Internet of Things monitoring module includes multiple sensors, including but not limited to current sensors, voltage sensors, temperature sensors and power sensors, which are used to collect the current, voltage, temperature and power information of the energy storage system and the charging pile respectively. The electrical signals collected by the sensors are converted into digital signals through analog-to-digital conversion. These digital signals are transmitted to the intelligent scheduling module via wireless communication methods such as industrial Ethernet or ZigBee, Wi-Fi and 4G / 5G. By collecting the operating parameters of the energy storage system and the charging pile in real time, potential safety hazards can be discovered in time. When the current sensor detects that the current of the charging pile increases abnormally, it may indicate that there is a short circuit or overload. When the temperature sensor detects that the battery temperature of the energy storage system is too high, it may indicate that the battery is at risk of thermal runaway. If the problem is discovered in time, corresponding measures can be taken to avoid equipment damage and safety accidents.

[0042] The fault warning module is connected to the Internet of Things monitoring module, and is used to receive operating parameters and status information, and judge whether there is a fault risk in the energy storage system and the charging pile according to the preset fault judgment rules. If there is, a fault warning signal is issued. The fault judgment rules in the fault warning module include: when the temperature of the energy storage system exceeds the preset temperature threshold, or the voltage fluctuation exceeds the preset voltage fluctuation range, or the output current of the charging pile is abnormal, it is determined that there is a fault risk. Once the fault warning module determines that there is a fault risk, it will immediately issue a fault warning signal. This signal can be an audible and visual alarm signal to remind on-site staff; it can also be an electronic alarm signal sent to the remote monitoring center through the network so that maintenance measures can be taken in time. By timely warning and handling of faults, the degree of damage to the equipment can be reduced and the maintenance cost can be reduced;

[0043] The remote maintenance module is connected to the fault warning module and is used to perform remote diagnosis and maintenance operations on the faulty equipment after receiving the fault warning signal. The remote maintenance module includes a remote diagnosis unit and a remote operation unit. The remote diagnosis unit is used to perform fault analysis and location on the faulty equipment. The remote operation unit is used to adjust parameters, upgrade software and send control instructions to the faulty equipment according to the diagnosis results. There is no need for on-site maintenance personnel to go to the site to troubleshoot and handle the faults. Through remote operation, the faulty equipment can be quickly diagnosed and repaired. For charging stations distributed in different geographical locations, remote maintenance can greatly save the transportation time and cost of maintenance personnel and improve the response speed and efficiency of maintenance;

[0044] The energy recovery module is used to recover the energy of the vehicle during braking and store the recovered energy in the energy storage system. The energy recovery module is connected to the intelligent scheduling module. The intelligent scheduling module manages the storage and distribution of the recovered energy according to the power status of the energy storage system and the characteristics of the recovered energy. By recovering the energy during the vehicle braking process, the originally wasted kinetic energy can be converted into electrical energy and stored, realizing the reuse of energy and improving the energy utilization rate of the entire energy system. It not only helps to reduce energy waste, but also can alleviate the charging pressure of the energy storage system to a certain extent. During peak hours, the recovered energy can supplement the power of the energy storage system to ensure that the charging station has enough energy to charge the vehicle. The energy recovery module adopts the maximum power point tracking algorithm to improve the efficiency of energy recovery. The maximum power point tracking algorithm formula is:

[0045]

[0046] Among them, P m is the maximum power recovered, U oc is the open circuit voltage, I sc is the short-circuit current, R l is the load resistance, R s is the equivalent series resistance.

[0047] The energy storage system uses one or more energy storage technologies including lithium batteries, supercapacitors and flywheel energy storage. The intelligent scheduling module optimizes the allocation and management of energy according to the charging and discharging characteristics and status of different energy storage technologies.

[0048] Please refer to the attached Figure 2 , an energy dispatching method of an energy storage system based on a smart supercharging station, comprising the following steps:

[0049] Step 1: After the vehicle is connected to the charging pile, the charging pile sends the vehicle's charging demand information to the intelligent scheduling module, including the vehicle's battery type, remaining power and expected charging time;

[0050] Step 2: The intelligent scheduling module calculates the charging power and charging time allocated to the vehicle based on the received charging demand information, combined with the current power and status of the energy storage system and the working conditions of other charging piles, using a preset scheduling algorithm, and sends a control instruction to the charging pile;

[0051] Step 3: During the charging process, the IoT monitoring module collects the status information of the energy storage system and the charging pile in real time and transmits it to the intelligent scheduling module. The intelligent scheduling module dynamically adjusts the charging power and time according to the real-time information;

[0052] Step 4: When the vehicle is fully charged, the charging pile sends a charging end signal to the intelligent scheduling module, and the intelligent scheduling module updates the power and status information of the energy storage system.

[0053] The method by which the intelligent scheduling module dynamically adjusts the charging power and time is as follows:

[0054]

[0055] Among them, P t is the adjusted charging power, P0 is the initially allocated charging power, ΔS is the change in the energy storage system capacity, S0 is the initial capacity of the energy storage system, ΔT is the difference between the charging time and the expected charging time, T0 is the expected charging time, It reflects the impact of energy storage system power changes on power adjustment. If ΔS>0, that is, the energy storage system power increases, is a positive value, This indicates that when the storage system charge increases, more energy is available, potentially allowing for higher charging power.

[0056] On the contrary, if ΔS<0, the energy storage system power is reduced. is a negative value, This indicates that when the energy storage system power decreases, the charging power needs to be reduced to avoid over-discharge; It reflects the impact of charging time deviation on power adjustment. If ΔT>0, the actual charging time exceeds the expected charging time. is a positive value, This indicates that the charging power needs to be reduced because the charging process is longer than expected and the energy may need to be released more slowly. On the contrary, if ΔT < 0, that is, the actual charging time is shorter than the expected charging time, is a negative value, This indicates that the charging power can be increased because the charging process is faster than expected and there is a certain margin to speed up the charging. The system can dynamically adjust the charging power P according to the change in the energy storage system's power and the deviation in the charging time. t， This dynamic adjustment helps ensure the stable operation of the energy storage system, while optimizing the charging process, improving energy efficiency, and avoiding overcharging or over-discharging.

[0057] Although embodiments of the present invention have been shown and described, it will be appreciated by those skilled in the art that various changes, modifications, substitutions and variations may be made to the embodiments without departing from the principles and spirit of the present invention, and that the scope of the present invention is defined by the appended claims and their equivalents.

Claims

1. The energy storage system based on the smart supercharging station is characterized by: include: Intelligent scheduling module, which is used to allocate and manage energy using a preset scheduling algorithm based on the status information of the energy storage system, the working status information of the charging pile and the charging demand information of the vehicle to ensure efficient use of energy; The Internet of Things monitoring module is connected to the energy storage system and the charging pile to collect the operating parameters and status information of the energy storage system and the charging pile in real time and transmit it to the intelligent scheduling module; A fault warning module is connected to the Internet of Things monitoring module, and is used to receive the operating parameters and status information, and determine whether there is a fault risk in the energy storage system and the charging pile according to a preset fault judgment rule, and if so, issue a fault warning signal; The remote maintenance module is connected to the fault warning module and is used to perform remote diagnosis and maintenance operations on the faulty equipment after receiving the fault warning signal.

2. The energy storage system based on the smart supercharging station according to claim 1 is characterized in that: The scheduling algorithm in the intelligent scheduling module is: Among them, E 分配 is the energy allocated to charging pile i, P i is the rated power of the charging pile, T i is the estimated charging time of the vehicle at the charging pile, n is the number of charging piles, k is the adjustment coefficient determined according to the remaining power of the energy storage system and the charging and discharging efficiency, and 0<k≤1.

3. The energy storage system based on the smart supercharging station according to claim 1 is characterized in that: The Internet of Things monitoring module includes multiple sensors, including but not limited to current sensors, voltage sensors, temperature sensors and power sensors, which are used to collect current, voltage, temperature and power information of the energy storage system and the charging pile respectively.

4. The energy storage system based on the smart supercharging station according to claim 1 is characterized in that: The fault judgment rules in the fault warning module include: when the temperature of the energy storage system exceeds a preset temperature threshold, or the voltage fluctuation exceeds a preset voltage fluctuation range, or the output current of the charging pile is abnormal, it is determined that there is a fault risk.

5. The energy storage system based on the smart supercharging station according to claim 1 is characterized in that: The remote maintenance module includes a remote diagnosis unit and a remote operation unit. The remote diagnosis unit is used to analyze and locate the fault of the faulty device, and the remote operation unit is used to adjust parameters, upgrade software and send control instructions to the faulty device according to the diagnosis result.

6. The energy storage system based on the smart supercharging station according to claim 1 is characterized in that: It also includes an energy recovery module for recovering the energy of the vehicle during braking and storing the recovered energy in the energy storage system. The energy recovery module is connected to the intelligent scheduling module, and the intelligent scheduling module manages the storage and distribution of the recovered energy according to the power status of the energy storage system and the characteristics of the recovered energy.

7. The energy storage system based on the smart supercharging station according to claim 6 is characterized in that: The energy recovery module adopts a maximum power point tracking algorithm to improve energy recovery efficiency. The maximum power point tracking algorithm formula is: Among them, P m is the maximum power recovered, U oc is the open circuit voltage, I sc is the short-circuit current, R l is the load resistance, R s is the equivalent series resistance.

8. The energy storage system based on the smart supercharging station according to claim 1 is characterized in that: The energy storage system adopts one or more energy storage technologies including lithium batteries, super capacitors and flywheel energy storage, and the intelligent scheduling module optimizes the distribution and management of energy according to the charging and discharging characteristics and states of different energy storage technologies.

9. The energy dispatching method of the energy storage system based on the smart supercharging station according to claim 1 is characterized in that: The following steps are involved: Step 1: After the vehicle is connected to the charging pile, the charging pile sends the vehicle's charging demand information to the intelligent scheduling module, including the vehicle's battery type, remaining power and expected charging time; Step 2: The intelligent scheduling module calculates the charging power and charging time allocated to the vehicle based on the received charging demand information, combined with the current power and status of the energy storage system and the working conditions of other charging piles, using a preset scheduling algorithm, and sends a control instruction to the charging pile; Step 3: During the charging process, the IoT monitoring module collects the status information of the energy storage system and the charging pile in real time and transmits it to the intelligent scheduling module. The intelligent scheduling module dynamically adjusts the charging power and time according to the real-time information; Step 4: When the vehicle is fully charged, the charging pile sends a charging end signal to the intelligent scheduling module, and the intelligent scheduling module updates the power and status information of the energy storage system.

10. The energy dispatching method of the energy storage system based on the smart supercharging station according to claim 9 is characterized in that: The method by which the intelligent scheduling module dynamically adjusts the charging power and time is: Among them, P t is the adjusted charging power, P0 is the initially allocated charging power, ΔS is the change in the energy storage system capacity, S0 is the initial capacity of the energy storage system, ΔT is the difference between the charged time and the expected charging time, and T0 is the expected charging time.

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