Energy management method and system for a power and charging system

Abstract

This invention belongs to the field of energy management technology for smart grids and roadside charging piles, and relates to an energy management method and system for power supply and charging systems. The method includes: a controller receiving charging requests from street light nodes and classifying each street light node that generated the charging request as a game participant; constructing a game allocation model based on the internal constraints of each street light node and the capacity limitations of the transmission bus; the controller iteratively calculating the equilibrium allocation point of the game allocation model through its internal hardware acceleration unit; generating a power adjustment command based on the equilibrium allocation point and sending it to the corresponding street light node, so that each street light node adjusts its output power to the corresponding charging interface. This achieves decoupling between concurrent charging demands and the carrying capacity limits of the physical network structure (bus, energy storage devices), actively avoiding the overload danger caused by instantaneous blind fast charging, and effectively preventing voltage oscillations and instantaneous harmonic impacts.

Description

Technical Field

[0001] This invention belongs to the field of energy management technology for smart grids and roadside charging piles, and relates to an energy management method and system for power supply and charging systems. Background Technology

[0002] With the rapid popularization of new energy vehicles, smart light poles integrating charging interfaces are gradually becoming an important carrier for roadside distributed charging. However, in scenarios with multiple vehicles charging simultaneously, the power supply and charging system faces severe challenges of overload and control lag.

[0003] On the one hand, smart streetlights are distributed along roads and have a highly compact physical space, resulting in very limited available capacity for their transmission buses and power grid distribution. Concurrent charging by multiple vehicles can easily lead to overheating of transmission lines and equipment overload. On the other hand, existing management methods mostly rely on centralized cloud control or sequential scheduling based on ordinary microprocessors, which cannot quickly coordinate multi-dimensional constraints such as the charging urgency of each node while ensuring the safety of transmission line temperature rise. Due to the lack of a high-concurrency parallel solution mechanism, the power control response delay is usually over 100 milliseconds, which can easily induce voltage fluctuations and harmonic oscillations in long-distance transmission buses. Summary of the Invention

[0004] The purpose of this invention is to address the aforementioned problems in existing technologies by proposing an energy management method for power supply and charging systems.

[0005] The objective of this invention can be achieved through the following technical solution: an energy management method for a power supply and charging system, applied to the power supply and charging system, the power supply and charging system including an energy storage device, a plurality of street light nodes, a transmission bus connecting the energy storage device and the street light nodes, and a controller, comprising: The controller receives the charging requests from the street light nodes and assigns each street light node that generates the charging request to a game participant. Based on the internal constraints of each street light node and the capability limitations of the transmission bus, a game allocation model is constructed. The controller iteratively calculates the equilibrium allocation point of the game allocation model through its internal hardware acceleration unit. A power adjustment command is generated based on the balance distribution point and sent to the corresponding street light node so that each street light node adjusts its output charging power to the corresponding charging interface.

[0006] As an optional embodiment of the present invention, the utility function of the game allocation model includes a vehicle charging urgency parameter, a historical discharge contribution value parameter, and a temperature status parameter of the transmission bus.

[0007] As an optional embodiment of the present invention, the vehicle charging urgency parameter is calculated and determined based on the vehicle category weight of the vehicle to be charged and the current remaining power; wherein, the vehicle category weight is determined based on the vehicle category priority, and the vehicle category priority is preset based on the urgency of the vehicle category demand; and within the same vehicle category priority, the lower the current remaining power of the vehicle to be charged, the higher the corresponding vehicle charging urgency parameter.

[0008] As an optional embodiment of the present invention, the historical discharge contribution value parameter is determined based on the amount of electricity fed back to the transmission bus by the street light node during a historical time period.

[0009] As an optional embodiment of the present invention, the weight coefficients of each parameter in the utility function are adjusted in real time by the controller based on grid electricity price data and weather forecast data.

[0010] As an optional embodiment of the present invention, it further includes: when the total power of the charging requests of each of the street light nodes exceeds a preset threshold, the controller adjusts the lighting brightness of some of the street light nodes according to the correlation between brightness adjustment and power release, so as to allocate the released electrical energy to other street light nodes that have initiated charging requests.

[0011] As an optional embodiment of the present invention, the adjustment of the charging power output of each street light node to the corresponding charging interface specifically includes: adjusting the duty cycle or phase shift angle of the rectifier circuit switching transistor in the corresponding street light node.

[0012] The present invention also proposes a power supply and charging system for implementing the energy management method described above, comprising: At least one energy storage device, which includes a battery module and an inverter unit; Several street light nodes, each of which integrates a charging interface and a rectifier unit; A transmission bus connects the energy storage device and the street light node. The transmission bus includes power lines for transmitting alternating current and signal lines for data interaction. A controller is communicatively connected to each of the street light nodes, and the controller includes a hardware acceleration unit for calculating the balance allocation point.

[0013] Preferably, the outside of the power line is wrapped with a shielding layer, which is a nanocrystalline ribbon shielding layer or an amorphous alloy shielding layer, and the shielding layer is covered with a cross-linked polyethylene insulation layer.

[0014] The present invention also provides an electronic device, comprising: processor; Memory used to store processor-executable instructions; The processor is configured to implement the energy management method of the power supply and charging system described above when executing executable instructions.

[0015] Compared with the prior art, the present invention achieves the following technical effects: 1) Under the normal operating conditions of energy storage inverters, bus transmission, and node rectification power supply, a game-theoretic allocation model is constructed by mapping street light nodes competing for charging resources as game participants and introducing the capacity limitations of the transmission bus and the internal constraints of the street light nodes. This decouples the demand for concurrent charging from the carrying capacity limits of the physical network structure (bus, energy storage devices), and proactively avoids the overload danger caused by the system's instantaneous and blind fast charging.

[0016] 2) Relying on the hardware acceleration unit built into the controller, the power balance distribution point under the Nash equilibrium state can be calculated iteratively within a very short time, which ensures rapid calculation and response when the vehicle load is dynamically switched on or offline, and effectively avoids bus voltage oscillation and instantaneous harmonic impact caused by control delay in long-distance AC power transmission.

[0017] 3) Compared with the traditional architecture where each light pole is equipped with a large-volume frequency converter / step-down device, this system can share the front-end centralized converter section, which greatly reduces the physical envelope volume of the light pole base and pole body, and solves the problem of limited physical installation space on the roadside.

[0018] 4) The power lines used for power transmission and the signal lines used for data interaction are integrated into a single transmission bus, and a shielding layer is wrapped around the outside of the power lines. This ensures a high degree of integration of the roadside system and simplifies the difficulty of underground laying, while completely eliminating electromagnetic interference and communication noise on the weak current signal lines on the same cable caused by the strong alternating electromagnetic field generated under high-power AC power transmission, thus ensuring high-speed, error-free transmission of system game data. Attached Figure Description

[0019] Figure 1 This is a flowchart of the energy management method of the power supply and charging system according to an embodiment of the present invention. Detailed Implementation

[0020] The following are specific embodiments of the present invention, which are described in conjunction with the accompanying drawings to further illustrate the technical solutions of the present invention. However, the present invention is not limited to these embodiments.

[0021] Example 1 Based on the technical problems highlighted in the background, this embodiment proposes an energy management method for a power supply and charging system. This method is applied to the power supply and charging system, which includes an energy storage device, several street light nodes, a transmission bus connecting the energy storage device and the street light nodes, and a controller. In a power supply state where the energy storage device converts DC power to AC power and transmits it to each street light node via the transmission bus, and each street light node converts the received AC power back to DC power to supply its charging interface, as follows... Figure 1 As shown, the method includes: S1, the controller receives the charging request from the street light node, and assigns each street light node that generates the charging request to a game participant. Based on the internal constraints of each street light node and the capability limitations of the transmission bus, a game allocation model is constructed. S2, the controller iteratively calculates the equilibrium allocation point of the game allocation model through its internal hardware acceleration unit; S3, generate a power adjustment command based on the balance distribution point and send it to the corresponding street light node so that each street light node adjusts its output charging power to the corresponding charging interface.

[0022] In this embodiment, the power supply and charging system uses a centralized energy storage compartment independently deployed in the roadside green belt. The compartment contains an electrochemical battery stack and a first-end inverter module. The battery stack can be an existing chemical energy storage battery stack, such as lead-acid, lithium-ion, or sodium-ion batteries. The first-end inverter module converts the energy storage into AC output. In the actual high-frequency chain energy transmission system, this AC output specifically corresponds to high-frequency, high-voltage AC. The transmission bus connects the centralized energy storage compartment to each street light node, and its spatial orientation is underground along the road, including high-voltage power lines and communication optical fibers. The street light nodes are smart street light poles with integrated charging gun interfaces. Their internal rectifier units normally rectify the high-frequency, high-voltage AC power from the transmission bus into DC power suitable for charging electric vehicles.

[0023] Specifically, in this embodiment, the operating frequency of the high-frequency high-voltage AC power supply is determined to be 1MHz, and the voltage range can be selected from 1000V to 2000V (e.g., 1500V). The determination of the operating frequency mainly considers three aspects: volume requirements, loss balance control, electromagnetic compatibility, and maximizing conversion efficiency. Regarding volume requirements, with an operating frequency of 1MHz, compared to the traditional low-frequency transmission scheme of 100kHz, the physical volume of the LCC resonant cavity and transformer in its power conversion circuit can be significantly reduced by approximately 60%. This greatly reduces the hardware footprint, making it easier to embed in narrow pipe corridors under the roadbed and in the miniature cavities of smart streetlight poles. Regarding loss balance control, compared to ultra-high frequency transmission schemes above 3MHz, the underground composite transmission bus at 1MHz has lower dielectric loss, and the skin effect of the cable is completely within a controllable range, avoiding abnormal cable heating due to ultra-high frequency skin loss. Regarding electromagnetic compatibility, the power lines transmitting AC power are wrapped with a shielding layer, which is either a nanocrystalline ribbon shielding layer or an amorphous alloy shielding layer. Under the effect of the shielding layer, the electromagnetic interference radiation intensity generated by the 1MHz operating electric field can be reduced by more than 30dB. In terms of maximizing conversion efficiency, the 1MHz frequency can precisely match the optimal switching loss range of mainstream silicon carbide (SiC) MOSFET power devices, enabling the system's overall power conversion efficiency to remain at an ultra-high level of ≥96%.

[0024] On the other hand, the wire diameter was also considered. The wire diameter in this embodiment was determined with reference to the thermal stability test results of IEC60287 underground cables. It is preferred to be less than or equal to 16mm². Under the conditions of 1MHz and 1500V, the long-term current carrying capacity of 16mm² XLPE cable does not exceed 120A, and the corresponding power limit is 180kW, which meets the concurrent needs of 10-15 street lights in a typical road section.

[0025] During system operation, when multiple streetlight nodes connect to vehicles at their charging interfaces and request charging, the system risks overload if the maximum power supply is directly applied due to limitations in the transmission bus capacity and the maximum output power constraint of the battery stack. Therefore, this method defines these requesting nodes as independent agents (i.e., "game participants") in game theory through a controller. Each agent tends to maximize its own charging efficiency. The controller acts as an energy manager, establishing a non-cooperative game allocation model and using its built-in dedicated hardware accelerator (such as FPGA) to run the core solution algorithm to quickly find the equilibrium allocation point. The equilibrium allocation point is preferably a Nash equilibrium point, which then outputs PWM or phase shift commands to dynamically limit the rectified power of each streetlight node. This ensures fair and efficient concurrent charging of multiple vehicles on the roadside while guaranteeing the safety of the power grid and cables.

[0026] Preferably, the utility function of the game-theoretic allocation model includes a vehicle charging urgency parameter, a historical discharge contribution value parameter, and a temperature status parameter of the transmission bus.

[0027] In this embodiment, each player in the constructed game allocation model has a utility function to maximize their benefit. The specific expression of this utility function is as follows: in, The urgency parameter for vehicle charging. The parameter represents the historical discharge contribution value. This is for transmitting the temperature status parameters of the bus. This indicates that the i-th street light node has a power allocation of... The comprehensive utility value obtained at a given time reflects the overall gain of that node in the game. Each node engages in non-cooperative game with the goal of maximizing its own utility. The power benefit term reflects user satisfaction resulting from increased charging power. Its logarithmic form ensures diminishing marginal returns, aligning with the psychological model that user satisfaction with power increases gradually plateaus, while simultaneously guaranteeing that the utility function... It exhibits good mathematical convergence within the interval ≥0. The power opportunity cost item, of which This represents the maximum allowed output power for this node. This term characterizes the opportunity cost of unused power margin, penalizing power waste and encouraging nodes to efficiently utilize their allocated power quotas. For temperature penalty items, among which The bus safety temperature threshold (preferably 70°C) is set. This is for transmitting real-time temperature monitoring values ​​of the bus. When the bus real-time temperature... Exceeding the safety threshold At this time, this item increases sharply, which strongly constrains the overall utility and forces the controller to reduce the charging power allocation of each node, thereby preventing the bus from overheating, aging, or even melting. The maximum permissible temperature rise (preferably 20°C) is preset by the system based on cable specifications, installation environment, and safety margin, and is used for system threshold judgment and alarm triggering. When the system determines that the bus is in a dangerous temperature rise range, it will forcibly trigger the power limiting or lighting energy release emergency mode. , , These are the weighting coefficients for each part. The contribution weight of balancing vehicle charging urgency, Balance the incentive weights for historical discharge contributions. The constraint weights for the temperature penalty term are determined by the controller, which dynamically adjusts these three values ​​in real time based on grid electricity price data and weather forecast data. Specifically, the adjustment strategy is to increase the penalty weights during periods of high electricity prices or when solar power generation is insufficient on cloudy or rainy days. The value is to tighten power allocation; during periods of abundant sunshine or low electricity prices, the power allocation is increased. and To unleash the system's carrying capacity.

[0028] By incorporating constraints from three dimensions—vehicle charging urgency parameter, historical discharge contribution value parameter, and temperature state parameter of the transmission bus—into the utility function, the rectified power of each lamp post node is calculated. This achieves multi-variable collaborative optimization of vehicle charging demand, node historical contribution incentive mechanism, and underground physical power supply line temperature rise safety, thereby improving user satisfaction while ensuring the thermal safety of the transmission bus.

[0029] Preferably, the vehicle charging urgency parameter is calculated and determined based on the vehicle category weight and the current remaining battery power of the vehicle to be charged; wherein, the vehicle category weight is determined based on the vehicle category priority, and the vehicle category priority is preset based on the urgency of the vehicle category demand; and within the same vehicle category priority, the lower the current remaining battery power of the vehicle to be charged, the higher the corresponding vehicle charging urgency parameter.

[0030] This embodiment pre-sets priorities for various vehicle types within the system. For example, special vehicles (ambulances, flood control vehicles, etc.) have a higher priority than public service vehicles (buses, taxis, ride-hailing vehicles, etc.), and public service vehicles have a higher priority than ordinary vehicles (private cars, etc.). Higher priority vehicles correspond to higher vehicle category weights, with the weights based on... This embodiment sets the vehicle category weight for special vehicles to 1.5; the vehicle category weight for public service vehicles to 1.2; and the vehicle category weight for ordinary vehicles to 1.0. The calculation expression for the vehicle charging urgency parameter is as follows: in, This represents the current remaining battery percentage of the vehicle. This formula reflects that, within the same vehicle category priority, the lower the current remaining battery level of a vehicle waiting to be charged, the higher its charging urgency parameter. The urgency index increases linearly, and the model uses this to optimize resource allocation, preventing severely depleted vehicles from becoming paralyzed on the roadside due to the inability to recharge in time.

[0031] By setting different levels of urgency based on vehicle usage attributes and battery state of charge, public emergency vehicles can be given priority access to power, while emergency charging for vehicles in low-battery crisis is also guaranteed, significantly improving the social utility of the roadside public charging network.

[0032] Preferably, the historical discharge contribution value parameter is determined based on the amount of electricity fed back to the transmission bus by the street light node during a historical time period.

[0033] In this embodiment, the system supports V2G (Vehicle-to-Grid) interaction. The historical discharge contribution value parameter reflects the cumulative contribution of each street light node to the grid-connected current during previous historical time periods. For example, the historical calculation period is set to yesterday's peak electricity price period (18:00 to 20:00). During this period, the electric vehicle connected to street light node A transmitted 50kWh of electricity back to the system's transmission bus through its bidirectional charging converter in response to grid peak shaving and leveling; while street light node B did not make any reverse power transmission contribution at this time, and the cumulative reverse power supply for the day was recorded as 0.

[0034] When charging demand surges at midday, and both Node A and Node B simultaneously initiate vehicle charging requests while the system's available power is limited, the controller reads yesterday's historical records and sets a higher historical discharge contribution value parameter for Node A. This allows Node A to obtain a greater positive total utility gain in today's game theory calculation, resulting in it being allocated more abundant charging power or being allowed to enter a higher power charging level. By quantifying rewards based on historical discharge contribution values, this effectively drives and encourages users to actively participate in roadside V2G reverse discharge during peak grid load periods, strengthening the distributed energy storage network's role in peak shaving, valley filling, and flexible regulation of the regional power grid.

[0035] Preferably, the weight coefficients of each parameter in the utility function are adjusted in real time by the controller based on grid electricity price data and weather forecast data.

[0036] Before running the game theory algorithm, the controller reads the current "real-time electricity price data" from the cloud or the local power grid system, and "weather forecast data" from the meteorological API interface. When it detects that the current period is a high electricity price period, or that the predicted weather is cloudy or rainy, which will lead to insufficient future solar power generation to supplement the system, the controller will automatically increase the weight of the economic benefits of energy storage itself in the utility function, or decrease the overall weight coefficient of charging priority. It uses the game theory allocation mechanism to tighten the charging power allocation, so as to encourage the energy storage compartment to discharge less or delay charging, and prioritize the protection of the local power grid stability. During periods of sufficient sunshine (surplus solar power generation) or low electricity prices, the weight coefficient of charging experience is increased, and the total carrying capacity of the system is increased. By introducing the linkage between dynamic market electricity price information and macroscopic parameters of weather environment into the internal decision-making calculation of game theory, the overall power supply operation cost of distributed charging stations in complex economic and weather cycle environments is effectively reduced and optimized.

[0037] Preferably, when the total power of the charging requests from all the street light nodes exceeds a preset threshold, the controller adjusts the lighting brightness of some of the street light nodes according to the correlation between brightness adjustment and power release, so as to distribute the released electrical energy to other street light nodes that have initiated charging requests.

[0038] When encountering a localized surge in traffic charging—that is, when the total power of parallel charging requests from all streetlight nodes plus the normal illumination power of each streetlight exceeds the system's set safety threshold—the controller will activate the lighting energy release emergency mode. The controller will search for streetlights located on secondary roads not belonging to the city's core arterial roads, or streetlights on roads where traffic flow detectors historically indicated low traffic volume at specific times. It will then reduce the output power of their LED light sources to decrease the brightness of the normal illumination (during this phase, the lighting output power can be reduced by 20% to 50% via the dimming control board). The dimming amplitude and the release power satisfy the following linear quantization relationship: in, The total power released by all street light nodes participating in dimming is the power released; M is the total number of street light nodes participating in dimming. Let be the rated lighting power of the k-th street light node; This is the current brightness scaling factor for the k-th street light node (value range 0~1, for example, when the brightness drops from 100% to 30%). =0.3). The electrical energy saved by dimming the lights is the release power, which is added back to the game's adjustable power pool to absorb the overload peak of vehicle charging power.

[0039] For example, when the total concurrent charging load plus the conventional lighting load reaches 120kW (assuming the system's converter capacity threshold is 100kW), the controller reads the current pedestrian and vehicle traffic conditions on each road segment and determines that smart streetlights No. 1 and No. 2 are located on secondary roads or auxiliary roads in residential areas with sparse pedestrian traffic. Based on the conversion relationship between brightness and released electrical energy, the controller adjusts the dimming controllers at the bottom of the two streetlights, reducing their LED lighting brightness from the usual 100% to 30% of its operating level. Since these two dimming points release approximately 15kW of lighting power, this "released power" is then redistributed by the controller to the fast-charging streetlights No. 3 and No. 4, which are experiencing high charging demand, achieving dynamic energy balance in the system.

[0040] Preferably, adjusting the charging power output of each street light node to the corresponding charging interface specifically includes: adjusting the duty cycle or phase shift angle of the rectifier circuit switching transistor in the corresponding street light node.

[0041] After the controller calculates the power allocation scheme corresponding to the optimal game-theoretic equilibrium point, it sends high-frequency phase shift or pulse width modulation fine-tuning commands to each lamp post node.

[0042] When the node rectifier unit operates in pulse width modulation (PWM) mode, the average voltage output to the DC terminal of the vehicle battery is changed by adjusting the duty cycle of the silicon carbide MOSFET switching element in the bridge rectifier circuit, thus controlling the rise and fall of the charging current. When the node circuit is a resonant phase-shifting buck converter, the phase shift angle of the primary and secondary switch control square wave signal generated in the control chip is changed, thereby altering the output energy by changing the phase difference of the waveforms on both sides of the inductor, achieving fine-tuning of power. By directly utilizing the converter's duty cycle or phase-shift control command, the complex intermediate cascade transformer or bypass disconnection hardware is omitted, enabling microsecond-level, low-damping, and contact-loss-free fine-tuning of stepless charging power.

[0043] In this embodiment, the hardware acceleration unit is a field-programmable gate array (FPGA) chip, and its iterative calculation time for the equilibrium allocation point is limited to within ten milliseconds. This is because the solution complexity of the game model is extremely high. If only ordinary microprocessors (MCUs) or general-purpose CPUs are used, the calculation time for the equilibrium allocation point may reach hundreds of milliseconds or even seconds when there are many nodes and complex constraint dimensions (temperature, SOC, etc.). This cannot cope with the transient power fluctuations caused by dynamic fluctuations in vehicle-end load, and can easily cause AC oscillations or reverse impacts on the bus. By utilizing the hardware-level high-concurrency parallel computing characteristics of FPGAs, the convergence iteration time of high-order games is reduced to the order of microseconds to tens of milliseconds, fundamentally preventing voltage flicker and bus current resonance in power transmission lines caused by control lag, and maintaining the dynamic and safe operation of the power topology.

[0044] This method achieves the following technical effects: 1) Under the normal operating conditions of energy storage inverters, bus transmission, and node rectification power supply, a game-theoretic allocation model is constructed by mapping street light nodes competing for charging resources as game participants and introducing the capacity limitations of the transmission bus and the internal constraints of the street light nodes. This decouples the demand for concurrent charging from the carrying capacity limits of the physical network structure (bus, energy storage devices), and proactively avoids the overload danger caused by the system's instantaneous and blind fast charging.

[0045] 2) Relying on the hardware acceleration unit built into the controller, the power balance distribution point under the Nash equilibrium state can be calculated iteratively within a very short time, which ensures rapid calculation and response when the vehicle load is dynamically switched on or offline, and effectively avoids bus voltage oscillation and instantaneous harmonic impact caused by control delay in long-distance AC power transmission.

[0046] Example 2 This embodiment proposes a power supply and charging system for implementing the energy management method described in Embodiment 1, including: At least one energy storage device, which includes a battery module and an inverter unit; Several street light nodes, each of which integrates a charging interface and a rectifier unit; A transmission bus connects the energy storage device and the street light node. The transmission bus includes power lines for transmitting alternating current and signal lines for data interaction. A controller is communicatively connected to each of the street light nodes, and the controller includes a hardware acceleration unit for calculating the balance allocation point.

[0047] In terms of hardware configuration, the energy storage device in this embodiment consists of multiple battery arrays equipped with battery management systems, which can be built using existing energy storage technology architectures. The DC output power is connected to the internal inverter unit. The rectifier units built into each street light node employ bidirectional converters, supporting V2G.

[0048] In terms of soft-switching control of the circuit, the inverter unit and the rectifier unit of each lamp post node all include LCC inductor-capacitor resonant cavities connected in series or in parallel in the topology, which are used in conjunction with soft-switching (zero voltage turn-on ZVS and zero current turn-off ZCS) operation to control the switching transistor to turn on and off.

[0049] Because the system operates at a special high frequency of 1MHz, conventional magnetic core transformers and shielding would be difficult to install in the confined space of long-distance power transmission corridors and street light bases. This system uses a composite encapsulation of the main high-voltage transmission cable and optical fiber as a "transmission bus" placed underground. To mitigate radiation from long-distance high-frequency power transmission, a closed "shielding layer" surrounds the power line.

[0050] Preferably, the outside of the power line is wrapped with a shielding layer, which is a nanocrystalline ribbon shielding layer or an amorphous alloy shielding layer, and the shielding layer is covered with a cross-linked polyethylene insulation layer.

[0051] For the high-density electromagnetic leakage generated by underground high-frequency power transmission, traditional copper mesh braiding or ordinary aluminum-plastic tape exhibits severe skin effect and poor shielding effectiveness against magnetic fields at frequencies above 10kHz. In this embodiment, the "shielding layer" employs a multi-layered, interlocked winding of a "nanocrystalline tape shielding layer" or an "amorphous alloy shielding layer" with high permeability and low iron loss. Preferably, the nanocrystalline tape has a thickness of 18~25μm, a relative permeability ≥50000, and a saturation magnetic induction intensity Bs ≥1.2T. The shielding layer uses a semi-overlapping winding process, achieving a coverage rate ≥85%, and providing a common-mode rejection ratio ≥60dB in the 100kHz-10MHz frequency band. The insulation layer uses cross-linked polyethylene (XLPE), with a long-term temperature tolerance of -40℃ to +90℃ and a power frequency withstand voltage ≥3kV / mm. Through this design, the leakage of external electromagnetic radiation from underground high-frequency energy transmission pipelines and the losses caused by the high-frequency skin effect are significantly suppressed, while ensuring high-voltage insulation safety in extreme underground environments.

[0052] The system has the following technical advantages: 1) Compared to the traditional architecture where each light pole is equipped with a large-volume frequency converter / step-down device, this system can share the front-end centralized converter section, which greatly reduces the physical envelope volume of the light pole base and pole body, and solves the problem of limited physical installation space on the roadside.

[0053] 2) The power lines used for power transmission and the signal lines used for data interaction are integrated into a single transmission bus, and a shielding layer is wrapped around the outside of the power lines. This ensures a high degree of integration of the roadside system and simplifies the difficulty of underground laying, while completely eliminating electromagnetic interference and communication noise on the weak current signal lines on the same cable caused by the strong alternating electromagnetic field generated under high-power AC power transmission, thus ensuring high-speed, error-free transmission of system game data.

[0054] Example 3 Furthermore, an electronic device is proposed, comprising: processor; Memory used to store processor-executable instructions; The processor is configured to implement an energy management method for a power supply and charging system according to Embodiment 1 when executing executable instructions.

[0055] It should be noted that all directional indications (such as up, down, left, right, front, back, etc.) in the embodiments of the present invention are only used to explain the relative positional relationship and movement of each component in a certain specific posture (as shown in the figure). If the specific posture changes, the directional indication will also change accordingly.

[0056] Furthermore, it should be noted that the use of terms such as "first," "second," and "a" in this invention is for descriptive purposes only and should not be construed as indicating or implying their relative importance or implicitly specifying the number of technical features indicated. Therefore, a feature defined as "first" or "second" may explicitly or implicitly include at least one of that feature. In the description of this invention, "a plurality of" means at least two, such as two, three, etc., unless otherwise explicitly specified. The terms "connection," "fixed," etc., should be interpreted broadly. For example, "fixed" can mean a fixed connection, a detachable connection, or an integral part; it can mean a mechanical connection or an electrical connection; it can mean a direct connection or an indirect connection through an intermediate medium; it can mean the internal communication of two elements or the interaction between two elements, unless otherwise explicitly specified. Those skilled in the art can understand the specific meaning of the above terms in this invention according to the specific circumstances.

[0057] Furthermore, the technical solutions of the various embodiments of the present invention can be combined with each other, but only if they are feasible for those skilled in the art. If the combination of technical solutions is contradictory or cannot be implemented, it should be considered that such combination of technical solutions does not exist and is not within the scope of protection claimed by the present invention.

[0058] The specific embodiments described herein are merely illustrative of the spirit of the invention. Those skilled in the art to which this invention pertains may make various modifications or additions to the described specific embodiments or use similar methods to substitute them, without departing from the spirit of the invention or exceeding the scope defined by the appended claims.

Claims

1. An energy management method for a power supply and charging system, applied to the power supply and charging system, the power supply and charging system comprising an energy storage device, a plurality of street light nodes, a transmission bus connecting the energy storage device and the street light nodes, and a controller; characterized in that, In a power supply state where the energy storage device converts direct current (DC) to alternating current (AC) and transmits it to each of the street light nodes via the transmission bus, and each of the street light nodes converts the received AC to DC to power its charging interface, the method includes: The controller receives the charging requests from the street light nodes and assigns each street light node that generates the charging request to a game participant. Based on the internal constraints of each street light node and the capability limitations of the transmission bus, a game allocation model is constructed. The controller iteratively calculates the equilibrium allocation point of the game allocation model through its internal hardware acceleration unit. A power adjustment command is generated based on the balance distribution point and sent to the corresponding street light node so that each street light node adjusts its output charging power to the corresponding charging interface.

2. The method according to claim 1, characterized in that, The utility function of the game-theoretic allocation model includes parameters such as vehicle charging urgency, historical discharge contribution, and temperature status of the transmission bus.

3. The method according to claim 2, characterized in that, The vehicle charging urgency parameter is calculated and determined based on the vehicle category weight and the current remaining battery power of the vehicle to be charged; wherein, the vehicle category weight is determined based on the vehicle category priority, and the vehicle category priority is preset based on the urgency of the vehicle category demand; and within the same vehicle category priority, the lower the current remaining battery power of the vehicle to be charged, the higher the corresponding vehicle charging urgency parameter.

4. The method according to claim 2, characterized in that, The historical discharge contribution value parameter is determined based on the amount of electricity fed back to the transmission bus by the street light node during the historical time period.

5. The method according to claim 2, characterized in that, The weighting coefficients of each parameter in the utility function are adjusted in real time by the controller based on grid electricity price data and weather forecast data.

6. The method according to claim 1, characterized in that, Also includes: When the total power of the charging requests from all the street light nodes exceeds a preset threshold, the controller adjusts the lighting brightness of some of the street light nodes according to the correlation between brightness adjustment and power release, so as to distribute the released electrical energy to other street light nodes that have initiated charging requests.

7. The method according to claim 1, characterized in that, The adjustment of the charging power output of each street light node to the corresponding charging interface specifically includes: adjusting the duty cycle or phase shift angle of the rectifier circuit switching transistor in the corresponding street light node.

8. A power supply and charging system, characterized in that, For implementing the energy management method as described in any one of claims 1 to 7, comprising: At least one energy storage device, which includes a battery module and an inverter unit; Several street light nodes, each of which integrates a charging interface and a rectifier unit; A transmission bus connects the energy storage device and the street light node. The transmission bus includes power lines for transmitting alternating current and signal lines for data interaction. A controller is communicatively connected to each of the street light nodes, and the controller includes a hardware acceleration unit for calculating the balance allocation point.

9. The system according to claim 8, characterized in that, The power line is wrapped with a shielding layer, which is a nanocrystalline ribbon shielding layer or an amorphous alloy shielding layer, and the shielding layer is covered with a cross-linked polyethylene insulation layer.

10. An electronic device, characterized in that, include: processor; Memory used to store processor-executable instructions; The processor is configured to implement the energy management method of the power supply and charging system according to any one of claims 1-7 when executing executable instructions.

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