A dc bus based microgrid system

Abstract

The application provides a micro-grid system based on a direct current bus, and belongs to the field of new energy micro-grid. The system integrates micro-wind power generation, photovoltaic power generation, energy storage and V2G two-way charging piles, adopts a 750V direct current bus to connect each unit, and reduces energy conversion loss. The efficiency of wind and light power generation is optimized through MPPT technology, so that the power generation unit always operates efficiently; load prediction, dynamic power scheduling are realized by means of an EMS system combined with an AI algorithm, energy storage and V2G two-way charging and discharging are coordinated, and the imbalance between supply and demand caused by the fluctuation of renewable energy output is balanced. The system is suitable for the end of the power grid, no power grid and the scene where capacity cannot be increased, effectively improves the utilization rate, operation stability and economy of new energy, and solves the problems of low conversion efficiency and insufficient stability of the traditional alternating current architecture micro-grid.

Description

Technical Field

[0001] This invention relates to the field of new energy microgrids, specifically to a microgrid system based on a DC bus. Background Technology

[0002] With the continuous development of new energy technologies, distributed energy microgrids are being used more and more widely in remote areas, edge grids, and isolated grids. Traditional microgrid systems mostly use AC architecture, which suffers from significant losses during energy conversion and exhibits poor system stability at the grid's end or in isolated grid scenarios. Meanwhile, the output of renewable energy sources such as wind and solar power is greatly affected by natural conditions, exhibiting strong volatility and easily leading to imbalances in system load supply and demand.

[0003] While energy storage systems and V2G technology can alleviate the supply-demand imbalance to some extent, existing systems mostly employ AC-coupled connections, resulting in low energy conversion efficiency and failing to meet the practical needs of efficient energy management. Therefore, this paper proposes a highly efficient and stable microgrid system for special scenarios such as grid termination, no grid access, and situations where capacity expansion is not possible. This is of great significance for improving renewable energy utilization and enhancing grid operational stability. Summary of the Invention

[0004] The present invention aims to solve the problems mentioned in the background art by providing a microgrid system based on a DC bus.

[0005] The specific technical solution is as follows:

[0006] A microgrid system based on a DC bus includes a DC bus, distributed energy generation units, energy storage units, bidirectional charging and discharging units, and an intelligent energy management unit, wherein:

[0007] The distributed energy generation unit, energy storage unit, and bidirectional charging / discharging unit are all electrically connected to the DC bus. The intelligent energy management unit establishes signal connections with the distributed energy generation unit, energy storage unit, and bidirectional charging / discharging unit, respectively. The DC bus is used to achieve efficient energy transmission between the units. The distributed energy generation unit converts renewable energy into electrical energy and processes it before connecting it to the DC bus. The energy storage unit stores excess electrical energy on the DC bus and releases it to the DC bus when needed to balance supply and demand. The bidirectional charging / discharging unit enables bidirectional energy interaction between electric vehicles and the DC bus. The intelligent energy management unit performs load forecasting and power optimization scheduling based on real-time operating data, enabling the coordinated operation of the distributed energy generation unit, energy storage unit, and bidirectional charging / discharging unit. This system is suitable for scenarios at the end of the grid, without a grid, and where capacity cannot be increased, in order to improve the utilization rate of renewable energy and the stability of grid operation.

[0008] As a preferred embodiment of the present invention, the voltage level of the DC bus is 750V DC, and the electrical energy output or input of the distributed energy generation unit, energy storage unit, and bidirectional charging and discharging unit is matched with the 750V DC voltage after adaptation processing.

[0009] As a preferred embodiment of the present invention, the distributed energy generation unit includes a micro-wind power generation module and a photovoltaic power generation module; the micro-wind power generation module is used to convert wind energy into AC power, which is then rectified by AC-DC and boosted by DC before being connected to the DC bus; the photovoltaic power generation module is used to convert solar energy into DC power, which is then rectified by maximum power point tracking and boosted by DC before being connected to the DC bus.

[0010] In a preferred embodiment of the present invention, the output AC voltage range of the micro-wind power generation module is 13-25V, the AC-DC rectification process converts the AC power into 24V DC power, and the DC-DC boost process boosts the 24V DC power to a voltage level matching the DC bus. The micro-wind power generation module is equipped with a maximum power point tracking control module and an intelligent wind energy prediction module. The maximum power point tracking control module is used to optimize wind energy conversion efficiency, and the intelligent wind energy prediction module is used to predict wind speed changes to optimize the stability of power generation output.

[0011] As a preferred embodiment of the present invention, the output DC voltage range of the photovoltaic power generation module is 300V to 600V. The maximum power point tracking control is used to dynamically adjust the voltage and current of the photovoltaic power generation module so that the photovoltaic power generation module always operates in the maximum power output state. The DC-DC boost processing boosts the DC power output by the photovoltaic power generation module to a voltage level that matches the DC bus. The photovoltaic power generation module is equipped with an irradiance prediction module, which is used to optimize power scheduling in conjunction with the energy storage unit to avoid energy waste.

[0012] In a preferred embodiment of the present invention, the energy storage unit is a lithium battery energy storage system, the voltage level of which is consistent with the voltage level of the DC bus, and the energy storage unit is equipped with a DC-DC bidirectional converter; the DC-DC bidirectional converter is used to maintain the DC bus voltage stability and provide short-time frequency regulation function; under the scheduling of the intelligent energy management unit, the energy storage unit stores excess electrical energy on the DC bus when the system is under low load and releases electrical energy to the DC bus when the system is under high load.

[0013] As a preferred embodiment of the present invention, the bidirectional charging and discharging unit supports bidirectional energy flow between the electric vehicle and the DC bus. It can transfer electrical energy from the DC bus to the electric vehicle for charging, and can also transfer electrical energy stored in the electric vehicle to the DC bus for discharging. The charging and discharging power of the bidirectional charging and discharging unit is not less than 350kW, and it is equipped with a DC-DC converter to realize the conversion between the DC bus voltage and the electric vehicle's adaptable voltage. The adaptable voltage range is 400V DC. The bidirectional charging and discharging unit releases electrical energy to the DC bus when the system is under high load, and obtains electrical energy from the DC bus to replenish the system when the system is under low load.

[0014] As a preferred embodiment of the present invention, the intelligent energy management unit adopts an artificial intelligence optimization algorithm, which is used to process real-time load data, output data of distributed energy generation units, status data of energy storage units, and interactive data of bidirectional charging and discharging units to realize load forecasting and dynamic power scheduling. The intelligent energy management unit combines meteorological forecast data to coordinate the output adjustment of distributed energy generation units, the charging and discharging control of energy storage units, and the energy interaction of bidirectional charging and discharging units, thereby improving the utilization rate of renewable energy.

[0015] As a preferred embodiment of the present invention, the bidirectional charging and discharging unit is further configured with a vehicle travel mode recognition module. The intelligent energy management unit combines the information obtained by the vehicle travel mode recognition module to intelligently decide the discharge timing and discharge power of the bidirectional charging and discharging unit in order to reduce the peak load pressure of the system.

[0016] As a preferred embodiment of the present invention, the intelligent energy management unit also formulates a charging and discharging strategy for the energy storage unit based on electricity price fluctuation data. The energy storage unit obtains electrical energy from the DC bus for charging when the electricity price is low, and releases electrical energy to the DC bus when the electricity price is high, so as to improve the economic efficiency of system operation.

[0017] The present invention has the following beneficial effects:

[0018] 1. By adopting a DC bus architecture instead of the traditional AC architecture, losses during energy conversion are reduced, significantly improving the overall energy utilization efficiency of the system. Distributed energy generation units, coupled with maximum power point tracking control, can fully tap the power generation potential of renewable energy, improve the actual utilization rate of renewable energy, and reduce energy waste.

[0019] 2. The coordinated operation of the intelligent energy management system, energy storage system, and bidirectional charging / discharging unit effectively mitigates the volatility of renewable energy output, balances the system's load supply and demand, and enhances the stability and reliability of the system in special scenarios such as grid termination and off-grid environments. The bidirectional energy flow design of the bidirectional charging / discharging unit further expands the system's energy regulation dimensions, enabling it to better cope with load fluctuations and alleviate peak load pressure.

[0020] 3. The system is adaptable to special scenarios such as the end of the power grid, no power grid, and no possibility of capacity expansion, solving the energy supply problem in such scenarios. At the same time, by combining electricity price fluctuations to optimize the dispatch strategy, the system's operating economy is improved, and it has good application value and promotion prospects. Attached Figure Description

[0021] Figure 1 This is a schematic diagram of the connection relationship of a microgrid system based on a DC bus provided in an embodiment of the present invention. Detailed Implementation

[0022] The technical solution of the present invention will be further described below with reference to the accompanying drawings and specific embodiments.

[0023] The accompanying drawings are for illustrative purposes only and are schematic diagrams, not actual images. They should not be construed as limiting the scope of this application. To better illustrate the embodiments of the present invention, some parts in the drawings may be omitted, enlarged, or reduced, and do not represent the actual dimensions of the product. It is understandable to those skilled in the art that some well-known structures and their descriptions may be omitted in the drawings.

[0024] In the accompanying drawings of the embodiments of the present invention, the same or similar reference numerals correspond to the same or similar components. In the description of the present invention, it should be understood that if terms such as "upper," "lower," "left," "right," "inner," and "outer" indicate the orientation or positional relationship based on the orientation or positional relationship shown in the drawings, they are only for the convenience of describing the present invention and simplifying the description, and do not indicate or imply that the device or element referred to must have a specific orientation, or be constructed and operated in a specific orientation. Therefore, the terms used to describe positional relationships in the drawings are only for illustrative purposes and should not be construed as limiting the present application. For those skilled in the art, the specific meaning of the above terms can be understood according to the specific circumstances.

[0025] In the description of this invention, unless otherwise explicitly specified and limited, the term "connection" or similar designation indicating a connection between components should be interpreted broadly. For example, it can refer to a fixed connection, a detachable connection, or an integral part; it can be a mechanical connection or an electrical connection; it can be a direct connection or an indirect connection through an intermediate medium; it can refer to the internal communication between two components or the interaction between two components. Those skilled in the art can understand the specific meaning of the above terms in this invention based on the specific circumstances.

[0026] Example

[0027] The microgrid system based on a DC bus provided in this embodiment, such as Figure 1 As shown, the system includes: a DC bus, distributed energy generation units, an energy storage unit, a bidirectional charging and discharging unit, and an intelligent energy management unit. The distributed energy generation units, energy storage unit, and bidirectional charging and discharging unit are all electrically connected to the DC bus. The intelligent energy management unit establishes signal connections with the distributed energy generation units, energy storage unit, and bidirectional charging and discharging unit, respectively. The DC bus is used to achieve efficient energy transmission between the units. The distributed energy generation units convert renewable energy into electrical energy, process it, and connect it to the DC bus. The energy storage unit stores excess electrical energy on the DC bus and releases it to the DC bus when needed to balance supply and demand. The bidirectional charging and discharging unit enables bidirectional energy interaction between electric vehicles and the DC bus. The intelligent energy management unit performs load forecasting and power optimization scheduling based on real-time operating data, achieving coordinated operation of the distributed energy generation units, energy storage unit, and bidirectional charging and discharging unit. This system is suitable for scenarios at the end of the grid, without a grid, and where capacity cannot be increased, to improve the utilization rate of renewable energy and the stability of grid operation.

[0028] This solution constructs a connection architecture between the DC bus and various functional units, enabling the coordinated operation of distributed energy generation, energy storage, and bidirectional charging and discharging units. This effectively improves the utilization level of renewable energy, enhances the stability of grid operation, and can adapt to the electricity demand in scenarios such as grid end, no grid, and no capacity expansion, thus solving the energy supply problem in these scenarios.

[0029] Specifically, in this embodiment, the voltage level of the DC bus is 750V DC; the distributed energy generation unit establishes an electrical connection with the DC bus through an adapted power conversion module, the energy storage unit establishes an electrical connection directly with the DC bus, and the bidirectional charging and discharging unit establishes an electrical connection with the DC bus through a dedicated conversion module. The electrical energy output or input of the distributed energy generation unit, the energy storage unit, and the bidirectional charging and discharging unit is matched with the 750V DC voltage after being adapted and processed by each unit; the intelligent energy management unit establishes signal connections with the control modules of the distributed energy generation unit, the energy storage unit, and the bidirectional charging and discharging unit through signal transmission lines, respectively, for transmitting control commands and receiving operating status data.

[0030] The solution clearly defines the voltage matching standard for the DC bus. By setting up the matching module and signal transmission line, it ensures that the output or input electrical energy of each unit matches the bus voltage, ensuring the smoothness of the energy transmission process. At the same time, it realizes efficient communication between the intelligent energy management unit and the control modules of each functional unit, providing reliable support for the transmission of control commands and feedback of operating status, and helping the overall system to operate in a coordinated manner.

[0031] Specifically, in this embodiment, the distributed energy generation unit includes a micro-wind power generation module and a photovoltaic power generation module. The AC output terminal of the micro-wind power generation module is electrically connected to the input terminal of the AC-DC rectifier module, the output terminal of the AC-DC rectifier module is electrically connected to the input terminal of the DC-DC boost module, the output terminal of the DC-DC boost module is electrically connected to the DC bus, and the control terminal of the micro-wind power generation module is signal-connected to the intelligent energy management unit to achieve optimized control of power generation output. The DC output terminal of the photovoltaic power generation module is electrically connected to the input terminal of the maximum power point tracking control module, the output terminal of the maximum power point tracking control module is electrically connected to the input terminal of the DC-DC boost module, the output terminal of the DC-DC boost module is electrically connected to the DC bus, and the control terminal of the photovoltaic power generation module is signal-connected to the intelligent energy management unit to achieve dynamic adjustment of power output.

[0032] This scheme standardizes the composition of distributed energy generation units, as well as the power conversion and access paths. Through the orderly connection of modules such as rectification, boosting, and maximum power point tracking, the energy conversion process is optimized, and the conversion efficiency of distributed energy is improved. At the same time, by leveraging the signal connection between the control terminal and the intelligent energy management unit, precise control of power generation output is achieved, ensuring stable and continuous power access to the DC bus.

[0033] Specifically, in this embodiment, the output AC voltage range of the micro-wind power generation module is 13-25V. The AC-DC rectifier module converts this AC power into 24V DC power, and the DC-DC boost module boosts the 24V DC power to a 750V DC voltage that matches the DC bus before connecting it to the DC bus. The micro-wind power generation module is equipped with a maximum power point tracking control module and an intelligent wind energy prediction module. The maximum power point tracking control module establishes a signal connection with the generator of the micro-wind power generation module to dynamically adjust the generator operating parameters to optimize wind energy conversion efficiency. The intelligent wind energy prediction module establishes a signal connection with the intelligent energy management unit to transmit the predicted wind speed change data to the intelligent energy management unit. The intelligent energy management unit sends adjustment commands to the micro-wind power generation module based on this data to optimize the stability of power generation output.

[0034] This solution optimizes the power conversion link of micro-wind power generation, ensures power matching bus requirements through a specific voltage conversion process, improves wind energy conversion efficiency through the application of a maximum power point tracking control module, and coordinates the intelligent wind energy prediction module with the intelligent energy management unit to anticipate the impact of wind speed changes, reduce fluctuations in power generation output, and improve the stability and energy utilization of micro-wind power generation.

[0035] Specifically, in this embodiment, the output DC voltage range of the photovoltaic power generation module is 300V to 600V. The maximum power point tracking control module establishes a signal connection with the photovoltaic module to dynamically adjust the voltage and current of the photovoltaic module, so that the photovoltaic module always works in the maximum power output state. The DC-DC boost module boosts the DC power output of the photovoltaic power generation module to 750V DC voltage and then connects it to the DC bus. The photovoltaic power generation module is equipped with an irradiance prediction module, which establishes a signal connection with the intelligent energy management unit to transmit the irradiance prediction data to the intelligent energy management unit. The intelligent energy management unit combines this data with the operating status data of the energy storage unit to optimize power scheduling to avoid energy waste.

[0036] This scheme utilizes a maximum power point tracking control module to ensure that photovoltaic modules always maintain a high-efficiency power generation state. The signal interaction between the irradiance prediction module and the intelligent energy management unit can optimize power scheduling based on the trend of changes in sunlight, avoid energy waste caused by power output fluctuations, and further improve the utilization efficiency of photovoltaic power generation and its supporting role in the system's energy supply.

[0037] Specifically, in this embodiment, the energy storage unit is a lithium battery energy storage system, and its voltage level is consistent with the 750V DC voltage level of the DC bus. The energy storage unit is equipped with a DC-DC bidirectional converter. One end of the DC-DC bidirectional converter is electrically connected to the battery pack of the lithium battery energy storage system, and the other end is electrically connected to the DC bus. The control terminal of the DC-DC bidirectional converter is signal connected to the intelligent energy management unit. The intelligent energy management unit sends control commands to the DC-DC bidirectional converter to enable the DC-DC bidirectional converter to achieve stable control of the DC bus voltage and provide short-time frequency modulation function. Under the scheduling of the intelligent energy management unit, the energy storage unit obtains excess electrical energy from the DC bus through the DC-DC bidirectional converter for storage when the system is under low load, and releases electrical energy to the DC bus through the DC-DC bidirectional converter when the system is under high load.

[0038] The design of the lithium battery energy storage system and the DC bus voltage adaptation ensures the smoothness of energy storage and release. The application of the DC-DC bidirectional converter can quickly respond to changes in bus voltage, realize voltage stabilization and short-term frequency regulation functions. Under the scheduling of the intelligent energy management unit, it can accurately match system load changes and balance energy supply and demand. At the same time, reasonable charge and discharge control helps to extend the service life of the energy storage unit.

[0039] Specifically, in this embodiment, the bidirectional charging and discharging unit supports bidirectional energy flow between the electric vehicle and the DC bus, with a charging and discharging power of not less than 350kW. The bidirectional charging and discharging unit is equipped with a DC-DC converter, one end of which is electrically connected to the DC bus, and the other end is electrically connected to the charging interface of the electric vehicle, to realize bidirectional conversion between the 750V DC voltage of the DC bus and the 400V DC adapter voltage of the electric vehicle. The control terminal of the bidirectional charging and discharging unit is connected to the intelligent energy management unit. The intelligent energy management unit sends a control signal to the bidirectional charging and discharging unit according to the system load status, so that the bidirectional charging and discharging unit can transmit the electrical energy stored in the electric vehicle to the DC bus through the DC-DC converter when the system is under high load, and obtain electrical energy from the DC bus and transmit it to the electric vehicle for energy replenishment when the system is under low load.

[0040] The bidirectional energy flow design of the bidirectional charging and discharging unit in this scheme enables flexible energy interaction between the electric vehicle and the system. The dedicated DC-DC converter ensures the adaptation and conversion of different voltage levels. Combined with the charging and discharging control of the system load status, it can supplement energy supply when the system load is high and store excess energy when the load is low, effectively relieving the system load pressure and improving the system's energy regulation flexibility and operational stability.

[0041] Specifically, in this embodiment, the intelligent energy management unit employs an artificial intelligence optimization algorithm. The distributed energy generation unit is equipped with an output monitoring module, the energy storage unit with a status monitoring module, and the bidirectional charging and discharging unit with an interactive monitoring module. All three modules establish signal connections with the intelligent energy management unit to transmit real-time load data, distributed energy generation unit output data, energy storage unit status data, and bidirectional charging and discharging unit interactive data to the intelligent energy management unit. The intelligent energy management unit also establishes a signal connection with a weather forecasting module to acquire weather forecast data. The artificial intelligence optimization algorithm processes these data types to achieve load forecasting and dynamic power scheduling, coordinating the output adjustment of the distributed energy generation unit, the charging and discharging control of the energy storage unit, and the energy interaction of the bidirectional charging and discharging unit, thereby improving the utilization rate of renewable energy.

[0042] In this solution, the intelligent energy management unit integrates data from various monitoring modules with meteorological forecast information, uses optimization algorithms to accurately predict load demand and distributed energy output, dynamically adjusts the operating status of each unit, achieves reasonable power allocation, promotes deep collaboration between distributed energy generation, energy storage, and bidirectional charging and discharging units, further improves the utilization efficiency of renewable energy, and optimizes the overall system operation.

[0043] Specifically, in this embodiment, the bidirectional charging and discharging unit is also equipped with a vehicle travel mode recognition module. The vehicle travel mode recognition module establishes a signal connection with the on-board control system of the electric vehicle to acquire electric vehicle travel-related data and transmit it to the control terminal of the bidirectional charging and discharging unit. At the same time, the control terminal of the bidirectional charging and discharging unit forwards the data to the intelligent energy management unit. The intelligent energy management unit combines the vehicle travel-related data and system load data to send control signals for discharge timing and discharge power to the bidirectional charging and discharging unit. The bidirectional charging and discharging unit interacts with the DC bus through a DC-DC converter according to the control signals to reduce the peak load pressure of the system.

[0044] In this solution, the vehicle travel pattern recognition module can obtain the actual usage information of electric vehicles. The intelligent energy management unit combines this information with the system load status to formulate a discharge strategy, so that the energy interaction of bidirectional charging and discharging is more in line with the actual use scenario, avoiding blind discharge from affecting vehicle use. At the same time, it can more accurately reduce the peak load pressure of the system and improve the system's adaptability to load changes and operational flexibility.

[0045] Specifically, in this embodiment, the intelligent energy management unit also establishes a signal connection with the electricity price data acquisition module. The electricity price data acquisition module is used to acquire real-time electricity price fluctuation data and transmit it to the intelligent energy management unit. The intelligent energy management unit combines the electricity price fluctuation data and system load data to formulate a charging and discharging strategy for the energy storage unit and sends charging and discharging control signals to the DC-DC bidirectional converter. When the electricity price is low, the energy storage unit obtains electrical energy from the DC bus through the DC-DC bidirectional converter to charge itself. When the electricity price is high, it releases electrical energy to the DC bus through the DC-DC bidirectional converter, thereby improving the economic efficiency of system operation.

[0046] In this solution, the intelligent energy management unit combines electricity price fluctuation data to formulate charging and discharging strategies for the energy storage unit, enabling the energy storage unit to store energy when energy costs are low and release energy when costs are high. While ensuring the energy balance of the system, it improves the economic benefits of system operation and achieves synergistic optimization of energy utilization and economic benefits.

[0047] Specifically, in this embodiment, the intelligent energy management unit uses the following dynamic scheduling optimization equation for power allocation:

[0048]

[0049] Let be the optimal power allocation vector of the system at time t;

[0050] The total output of distributed energy generation units, including wind and solar power generation, is affected by natural conditions.

[0051] The charging and discharging power of the energy storage unit; a positive value indicates discharging, and a negative value indicates charging.

[0052] This represents the power exchanged between the bidirectional charging and discharging unit and the bus. A positive value indicates that the vehicle is discharging into the bus, while a negative value indicates that the bus is charging the vehicle.

[0053] The real-time state of charge of the energy storage unit is measured in the range of 20%-90% to avoid overcharging and over-discharging.

[0054] The target state of charge of the energy storage unit is set between 50% and 70% to maintain its regulation capability.

[0055] This represents the maximum state of charge of the energy storage unit, 100%, nominal value.

[0056] Real-time grid electricity price;

[0057] This represents the power exchanged between the system and the power grid; a positive value indicates that electricity is purchased from the grid, and a negative value indicates that electricity is sold to the grid.

[0058] This is the system's rated power;

[0059] The benchmark electricity price is the average electricity price or unit power generation cost in the system's operating area.

[0060] α(t), β(t), and γ(t) are time-varying dynamic weighting coefficients, which are adaptively adjusted by the intelligent energy management unit according to the real-time operating status, meteorological forecast data, and load characteristics, and satisfy α(t) + β(t) + γ(t) = 1.

[0061] α(t) ranges from 0.2 to 0.8 and is adjusted according to wind and solar power fluctuations; β(t) ranges from 0.1 to 0.6 and is adjusted according to SOC deviations; γ(t) ranges from 0.1 to 0.6 and is adjusted according to electricity price fluctuations.

[0062] The derivation of the equation is as follows:

[0063] 1. Establishment of a multi-objective optimization framework

[0064] This system must simultaneously meet three core objectives: power balance, energy storage health, and economy. A multi-objective optimization framework is established as follows:

[0065] ;

[0066] 2. Mathematical expression of each objective function

[0067] (1) Power balance objective: Minimize supply and demand deviation;

[0068] ;

[0069] By adopting a normalized squared form, positive and negative deviations are avoided from canceling each other out, thus enhancing the penalty for imbalance.

[0070] (2) Energy storage health target: Maintain a reasonable state of charge.

[0071] ;

[0072] Guide the SOC to approach the reference value to avoid overcharging and over-discharging.

[0073] (3) Economic objective: Minimize electricity costs;

[0074] ;

[0075] We use the normalized square form to avoid the extreme optimization tendency of the linear terms.

[0076] 3. Weighted summation and dynamic weights

[0077] The weighted method is used to transform multiple objectives into a single objective:

[0078]

[0079] The weights α, β, and γ are dynamically adjusted to adapt to different operating scenarios.

[0080] When there are large fluctuations in the scenery, increase α;

[0081] When the SOC deviates significantly, increase β;

[0082] Increase γ when electricity prices fluctuate greatly;

[0083] Example:

[0084] Scene setting:

[0085] Time: at time t;

[0086] Operating mode: Isolated network operation =0);

[0087] parameter:

[0088] =500kW; =300kW; SOC=60%, =70%, =100%;

[0089] =100kW (discharge); =50kW (discharge); =1000kW;

[0090] Weight: α=0.5, β=0.3, γ=0.2;

[0091] Calculation process:

[0092] 1. Calculate the values ​​of each objective function:

[0093] ;

[0094] ;

[0095] .

[0096] 2. Calculate the overall objective function:

[0097] F=0.5×0.0025+0.3×0.01+0.2×0=0.00125+0.003=0.00425.

[0098] 3. Optimization Solution: The intelligent energy management unit adjusts the solution using optimization algorithms (such as gradient descent). and The goal is to find a power allocation scheme that minimizes F.

[0099] The technical advantages of this solution:

[0100] 1. Improve system stability: By optimizing power distribution in real time, the system power imbalance is reduced by 60%-70%; bus voltage fluctuation is controlled within ±5%, and frequency deviation is ≤0.2Hz;

[0101] 2. Enhanced economic efficiency: In grid-connected scenarios, the electricity purchase and sale strategy is optimized by leveraging electricity price differences; system operating costs are reduced by 18%-22%;

[0102] 3. Extend equipment lifespan: The energy storage system's State of Charge (SOC) is maintained within the optimized range of 50%-70%; cycle life is extended by 20%-30%;

[0103] 4. Improve the utilization rate of renewable energy: increase the utilization rate of wind and solar power generation by 8%-12%; reduce the curtailment rate of wind and solar power to below 5%;

[0104] 5. Highly adaptable: The dynamic weighting mechanism adapts to different operating scenarios; seamless switching between isolated network and grid-connected modes.

[0105] Working principle:

[0106] This microgrid system uses a DC bus as the connection carrier to realize energy transmission and coordinated operation of various functional units. The micro-wind power generation module in the distributed energy generation unit converts wind energy into AC power, which is then rectified and boosted before being connected to the DC bus; the photovoltaic power generation module converts solar energy into DC power, optimizes the output through maximum power point tracking control, and then boosts the output before being connected to the DC bus, ensuring that the two renewable energy sources are efficiently converted into power compatible with the bus.

[0107] The energy storage system employs energy storage devices adapted to the DC bus voltage. Connected to the bus via a bidirectional converter, it can store excess energy under low load and release energy under high load, while simultaneously stabilizing the bus voltage and providing short-term frequency regulation. The bidirectional charging and discharging unit connects to the DC bus and the electric vehicle via a converter, supporting bidirectional energy flow. It can switch between charging the vehicle and feeding energy back to the system based on the system load status.

[0108] As the core of collaborative control, the intelligent energy management system receives operating status data, load data, and meteorological forecast data from each unit. It then uses optimization algorithms to perform load forecasting and dynamic power scheduling, coordinating the output adjustment of distributed energy generation units, the charging and discharging control of energy storage systems, and the energy interaction of bidirectional charging and discharging units, thereby achieving the orderly and collaborative operation of each unit.

[0109] How to use:

[0110] 1. This system is suitable for scenarios at the end of the power grid, without a power grid, and where capacity cannot be increased. When using it, first complete the deployment and connection of each functional unit: connect the micro wind power generation module and photovoltaic power generation module to the DC bus through the corresponding power conversion device to ensure that the power output is adapted to the bus voltage after processing; establish a reliable electrical connection between the energy storage system and the bidirectional charging and discharging unit and the DC bus; establish a signal connection between the intelligent energy management system and the control module of each unit to ensure smooth command transmission and data feedback.

[0111] 2. During system operation, the distributed energy generation units continuously convert renewable energy into electrical energy and connect it to the bus. The intelligent energy management system collects various operational data and weather forecast information in real time to dynamically predict load demand and energy output. When the system load is low and renewable energy output is sufficient, the intelligent energy management system schedules the energy storage system to store excess electrical energy and can simultaneously control the bidirectional charging and discharging unit to charge electric vehicles. When the system load is high and renewable energy output is insufficient, the system schedules the energy storage system to release electrical energy and can simultaneously instruct the bidirectional charging and discharging unit to feed the electrical energy stored in the electric vehicles back to the bus to supplement the energy supply.

[0112] 3. During operation, the intelligent energy management system can also optimize the charging and discharging timing of the energy storage system and the bidirectional charging and discharging unit based on electricity price fluctuations, thereby improving the economic efficiency of system operation. Staff can remotely monitor the system's operating status through the control interface of the intelligent energy management system and make manual intervention adjustments when necessary.

[0113] In summary, the microgrid system based on a DC bus provided in this embodiment has the following advantages:

[0114] 1. By adopting a DC bus architecture instead of the traditional AC architecture, losses during energy conversion are reduced, significantly improving the overall energy utilization efficiency of the system. Distributed energy generation units, coupled with maximum power point tracking control, can fully tap the power generation potential of renewable energy, improve the actual utilization rate of renewable energy, and reduce energy waste.

[0115] 2. The coordinated operation of the intelligent energy management system, energy storage system, and bidirectional charging / discharging unit effectively mitigates the volatility of renewable energy output, balances the system's load supply and demand, and enhances the stability and reliability of the system in special scenarios such as grid termination and off-grid environments. The bidirectional energy flow design of the bidirectional charging / discharging unit further expands the system's energy regulation dimensions, enabling it to better cope with load fluctuations and alleviate peak load pressure.

[0116] 3. The system is adaptable to special scenarios such as the end of the power grid, no power grid, and no possibility of capacity expansion, solving the energy supply problem in such scenarios. At the same time, by combining electricity price fluctuations to optimize the dispatch strategy, the system's operating economy is improved, and it has good application value and promotion prospects.

[0117] In addition, this specific embodiment also provides the following example: DC bus microgrid system in the grid terminal scenario.

[0118] I. Technical Solution

[0119] This example of a DC bus microgrid system includes a DC bus, distributed energy generation units, energy storage units, bidirectional charging and discharging units, and an intelligent energy management unit. The distributed energy generation units include micro-wind power generation modules and photovoltaic power generation modules. The micro-wind power generation modules are equipped with an AC-DC rectifier module, a DC-DC boost module, a maximum power point tracking control module, and an intelligent wind energy forecasting module. The photovoltaic power generation modules are equipped with a maximum power point tracking control module, a DC-DC boost module, and an irradiance forecasting module. The energy storage unit includes a lithium battery energy storage system and a DC-DC bidirectional converter. The bidirectional charging and discharging unit is equipped with a DC-DC converter and a vehicle travel mode recognition module. The intelligent energy management unit is equipped with an output monitoring module, a status monitoring module, an interactive monitoring module, a weather forecasting module, and an electricity price data acquisition module.

[0120] The connections between components are as follows: The DC bus adopts a 750V DC voltage level; the AC output terminal of the micro-wind power generation module is electrically connected to the input terminal of the AC-DC rectifier module, the output terminal of the AC-DC rectifier module is electrically connected to the input terminal of the DC-DC boost module, and the output terminal of the DC-DC boost module is electrically connected to the DC bus; the control terminal of the micro-wind power generation module is signal-connected to the maximum power point tracking control module, and both the maximum power point tracking control module and the intelligent wind energy prediction module are signal-connected to the intelligent energy management unit. The DC output terminal of the photovoltaic power generation module is electrically connected to the input terminal of the maximum power point tracking control module, the output terminal of the maximum power point tracking control module is electrically connected to the input terminal of the DC-DC boost module, and the output terminal of the DC-DC boost module is electrically connected to the DC bus; the control terminal of the photovoltaic power generation module and the irradiance prediction module are signal-connected to the intelligent energy management unit. The lithium battery energy storage system is electrically connected to one end of the DC-DC bidirectional converter, and the other end of the DC-DC bidirectional converter is electrically connected to the DC bus. The control terminal of the DC-DC bidirectional converter is signal-connected to the intelligent energy management unit. The status monitoring module is signal-connected to the lithium battery energy storage system. One end of the DC-DC converter is electrically connected to the DC bus, and the other end is electrically connected to the electric vehicle charging interface. The vehicle travel mode recognition module is signal-connected to the electric vehicle's on-board control system, and also to the control terminal of the bidirectional charging and discharging unit and the intelligent energy management unit. The interactive monitoring module is signal-connected to the bidirectional charging and discharging unit. The output monitoring module is signal-connected to the micro-wind power generation module and the photovoltaic power generation module, respectively. The intelligent energy management unit is signal-connected to the output monitoring module, the status monitoring module, the interactive monitoring module, the weather forecasting module, and the electricity price data acquisition module, respectively.

[0121] II. Working Principle

[0122] During system operation, the micro-wind generator module captures wind energy and converts it into AC power. This AC-DC rectifier module then converts it into DC power, which is further boosted to 750V DC by the DC-DC boost module before being connected to the DC bus. The maximum power point tracking (MPPT) control module dynamically adjusts the operating parameters of the micro-wind generator module to improve wind energy conversion efficiency. The intelligent wind energy prediction module transmits wind speed change prediction data to the intelligent energy management unit, providing a reference for output adjustment. The photovoltaic (PV) generator module converts solar energy into DC power. The MPPT control module dynamically adjusts voltage and current to maintain maximum power output of the PV modules. This DC-DC boost module boosts the voltage to 750V DC before connecting to the DC bus. The irradiance prediction module transmits irradiance prediction data to the intelligent energy management unit.

[0123] The intelligent energy management unit obtains the real-time output data of the micro-wind power generation module and the photovoltaic power generation module through the output monitoring module, obtains the power and health status data of the lithium battery energy storage system through the status monitoring module, obtains the energy interaction data of the bidirectional charge and discharge unit through the interaction monitoring module, combines the meteorological data of the meteorological prediction module and the electricity price data of the electricity price data acquisition module, and performs load forecasting and dynamic power scheduling through an optimization algorithm. When the system load is low, the intelligent energy management unit instructs the DC-DC bidirectional converter to act, enabling the lithium battery energy storage system to store the excess power of the DC bus, and at the same time controlling the bidirectional charge and discharge unit to charge the electric vehicle through the DC-DC converter; when the system load is high, it instructs the DC-DC bidirectional converter to act, enabling the lithium battery energy storage system to release power to the DC bus, and at the same time combining the vehicle travel information obtained by the vehicle travel mode recognition module, instructs the bidirectional charge and discharge unit to feedback the power of the electric vehicle to the DC bus to achieve system supply-demand balance.

[0124] III. Experimental Data

[0125] In the scenario of the power grid end, the system continuously runs for 30 days to carry out performance tests, and the test results are as follows: the wind energy conversion efficiency of the micro-wind power generation module is increased by 12% - 15% compared with the traditional AC architecture microgrid system. In an environment where the wind speed fluctuation range is 3m / s - 8m / s, the output fluctuation range of the micro-wind power generation module is controlled within 8%; the maximum power output retention rate of the photovoltaic power generation module reaches more than 95%, an increase of 8% - 10% compared with the traditional system. Under the condition that the irradiance intensity change range is 200W / m² - 1000W / m², the output response delay time does not exceed 0.5 seconds.

[0126] The DC architecture of the DC bus enables the overall energy utilization efficiency of the system to reach 88% - 92%, an increase of 10% - 13% compared with the traditional AC microgrid system; the coordinated action of the energy storage unit and the bidirectional charge and discharge unit enables the system load fluctuation range to be controlled within ±5%, a reduction of 60% - 70% compared with the traditional system. After the implementation of the charge and discharge strategy combined with the electricity price fluctuation, the economic benefit of the system operation is increased by 18% - 22% compared with the traditional system; the power supply reliability during the continuous operation of the system reaches more than 99.2%, and there is no power supply interruption caused by supply-demand imbalance.

[0127] IV. Technical Effects

[0128] Through the DC architecture design of the DC bus, the loss caused by multiple energy conversions in the traditional AC architecture is avoided, and the smoothness and efficiency of the overall energy transmission of the system are improved. The maximum power point tracking control module supporting the distributed energy generation unit can fully adapt to the fluctuation characteristics of natural energy, tap the power generation potential of wind energy and solar energy, and improve the actual utilization level of renewable energy.

[0129] The intelligent energy management unit integrates various monitoring and forecasting data to achieve precise scheduling of each functional unit, effectively mitigating the volatility of renewable energy output, balancing the system's supply and demand, and enhancing the system's stability and reliability in grid-end scenarios. The bidirectional charging and discharging unit's bidirectional energy flow design, combined with the application of a vehicle travel mode recognition module, makes energy interaction more aligned with actual usage needs, further expanding the system's energy regulation dimensions and effectively alleviating peak load pressure.

[0130] The charging and discharging strategy, formulated in conjunction with electricity price fluctuations, improves the economic efficiency of operation while ensuring the energy balance of the system. It provides a reliable and efficient energy supply solution for special scenarios such as the end of the power grid, and has good practical application value and promotion prospects.

[0131] The above are merely preferred embodiments of the present invention and are not intended to limit the implementation methods and protection scope of the present invention. Those skilled in the art should recognize that any equivalent substitutions and obvious changes made based on the description and illustrations of the present invention should be included within the protection scope of the present invention.

Claims

1. A microgrid system based on a DC bus, characterized in that, It includes a DC bus, distributed energy generation units, energy storage units, bidirectional charging and discharging units, and intelligent energy management units, among which: The distributed energy generation unit, energy storage unit, and bidirectional charging / discharging unit are all electrically connected to the DC bus. The intelligent energy management unit establishes signal connections with the distributed energy generation unit, energy storage unit, and bidirectional charging / discharging unit, respectively. The DC bus is used to achieve efficient energy transmission between the units. The distributed energy generation unit is used to convert renewable energy into electrical energy and connect it to the DC bus after processing. The energy storage unit is used to store excess electrical energy on the DC bus and release electrical energy to the DC bus when needed to balance supply and demand. The bidirectional charging / discharging unit is used to realize bidirectional energy interaction between electric vehicles and the DC bus. The intelligent energy management unit is used to perform load forecasting and power optimization scheduling based on real-time operating data, realizing the coordinated operation of the distributed energy generation unit, energy storage unit, and bidirectional charging / discharging unit. This system is suitable for scenarios at the end of the grid, without a grid, and where capacity cannot be increased, in order to improve the utilization rate of renewable energy and the stability of grid operation. The DC bus voltage level is 750V DC. The electrical energy output or input of the distributed energy generation unit, energy storage unit, and bidirectional charging and discharging unit is matched to the 750V DC voltage after adaptation processing. The energy storage unit is a lithium battery energy storage system with a voltage level consistent with the DC bus voltage level. The energy storage unit is equipped with a DC-DC bidirectional converter. The DC-DC bidirectional converter is used to maintain the DC bus voltage stability and provide short-term frequency regulation function. The intelligent energy management unit adopts an artificial intelligence optimization algorithm. The artificial intelligence optimization algorithm is used to process real-time load data, distributed energy generation unit output data, energy storage unit status data, and bidirectional charging and discharging unit interaction data to realize load forecasting and dynamic power scheduling. The intelligent energy management unit uses the following dynamic scheduling optimization equation for power allocation: In the formula: Let be the optimal power allocation vector of the system at time t; Total output of distributed energy generation units; The charging and discharging power of the energy storage unit; This refers to the power exchange between the bidirectional charging / discharging unit and the bus. Real-time state of charge of the energy storage unit; The target state of charge for the energy storage unit; This represents the maximum state of charge of the energy storage unit. Real-time grid electricity price; This refers to the power exchanged between the system and the power grid. This is the system's rated power; The base price is α(t), β(t), and γ(t) are time-varying dynamic weighting coefficients, which are adaptively adjusted by the intelligent energy management unit based on real-time operating status, meteorological forecast data, and load characteristics, and satisfy α(t) + β(t) + γ(t) = 1.

2. The microgrid system based on a DC bus according to claim 1, characterized in that, The distributed energy generation unit includes a micro-wind power generation module and a photovoltaic power generation module; the micro-wind power generation module is used to convert wind energy into AC power, which is then rectified by AC-DC and boosted by DC-DC before being connected to the DC bus; the photovoltaic power generation module is used to convert solar energy into DC power, which is then rectified by maximum power point tracking and boosted by DC-DC before being connected to the DC bus.

3. The microgrid system based on a DC bus according to claim 2, characterized in that, The output AC voltage range of the micro-wind power generation module is 13-25V. The AC-DC rectification process converts the AC power into 24V DC power, and the DC-DC boost process boosts the 24V DC power to a voltage level matching the DC bus. The micro-wind power generation module is equipped with a maximum power point tracking control module and an intelligent wind energy prediction module. The maximum power point tracking control module is used to optimize wind energy conversion efficiency, and the intelligent wind energy prediction module is used to predict wind speed changes to optimize the stability of power generation output.

4. The microgrid system based on a DC bus according to claim 3, characterized in that, The output DC voltage range of the photovoltaic power generation module is 300V to 600V. The maximum power point tracking control is used to dynamically adjust the voltage and current of the photovoltaic power generation module so that the photovoltaic power generation module always works in the maximum power output state. The DC-DC boost processing boosts the DC power output of the photovoltaic power generation module to a voltage level that matches the DC bus. The photovoltaic power generation module is equipped with an irradiance prediction module, which is used to optimize power scheduling in conjunction with the energy storage unit to avoid energy waste.

5. The microgrid system based on a DC bus according to claim 1, characterized in that, Under the scheduling of the intelligent energy management unit, the energy storage unit stores excess electrical energy on the DC bus when the system is under low load and releases electrical energy to the DC bus when the system is under high load.

6. The microgrid system based on a DC bus according to claim 1, characterized in that, The bidirectional charging and discharging unit supports bidirectional energy flow between the electric vehicle and the DC bus. It can transfer electrical energy from the DC bus to the electric vehicle for charging, and it can also transfer electrical energy stored in the electric vehicle to the DC bus for discharging. The charging and discharging power of the bidirectional charging and discharging unit is not less than 350kW, and it is equipped with a DC-DC converter to realize the conversion between the DC bus voltage and the electric vehicle's adapted voltage. The adapted voltage range is 400V DC. The bidirectional charging and discharging unit releases electrical energy to the DC bus when the system is under high load, and obtains electrical energy from the DC bus to replenish the system when the system is under low load.

7. The microgrid system based on a DC bus according to claim 1, characterized in that, The intelligent energy management unit combines meteorological forecast data to coordinate the output adjustment of distributed energy generation units, the charging and discharging control of energy storage units, and the energy interaction of bidirectional charging and discharging units, thereby improving the utilization rate of renewable energy.

8. The microgrid system based on a DC bus according to claim 6, characterized in that, The bidirectional charging and discharging unit is also equipped with a vehicle travel mode recognition module. The intelligent energy management unit combines the information obtained by the vehicle travel mode recognition module to intelligently decide the discharge timing and discharge power of the bidirectional charging and discharging unit in order to reduce the peak load pressure of the system.

9. The microgrid system based on a DC bus according to claim 5, characterized in that, The intelligent energy management unit also formulates a charging and discharging strategy for the energy storage unit based on electricity price fluctuation data. The energy storage unit obtains power from the DC bus to charge when the electricity price is low, and releases power to the DC bus when the electricity price is high, so as to improve the economic efficiency of the system operation.

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