Dynamic energy distribution system and method

Abstract

The invention discloses an energy dynamic distribution system, which comprises an energy dynamic distribution center and a plurality of micro-grids, the energy dynamic distribution center is in communication connection with the micro-grids, the micro-grids are in communication connection, and each micro-grid comprises an equipment layer, an energy distribution layer and a control layer, the system comprises a non-renewable energy power generation device, a renewable energy power generation device, a battery energy storage device and a load. The equipment monitoring layer is used for collecting and storing data; the centralized management layer is used for formulating the power range of energy exchange at the next scheduling moment; the information interaction layer is used for realizing information interaction between the centralized management layer and the energy dynamic distribution center; and the equipment control layer is used for controlling the equipment layer to adjust the output power so as to dynamically distribute energy among the plurality of micro-grids. According to the invention, through information interaction between the micro-grids and between the micro-grids and the power distribution network, energy flow between the micro-grids can be coordinated, the energy utilization efficiency is improved, and the energy cost is reduced.

Description

Technical Field

[0001] The present invention relates to the technical field of microgrids. More specifically, the present invention relates to an energy dynamic distribution system and method. Background Art

[0002] A microgrid refers to a small power generation and distribution system composed of distributed power sources, energy storage devices, energy conversion devices, related loads, and monitoring and protection devices according to a certain topological structure. It can achieve self-control, protection, and management, and can operate independently or be connected to the external power grid in parallel. It is an important part of the smart grid. Developing and extending microgrids can fully promote the large-scale access of distributed power sources and renewable energy, and achieve high-reliability supply of multiple energy forms to loads. It is an effective way to realize an active distribution network and to transition the traditional power grid to a smart grid.

[0003] The access of microgrids has changed the situation of unidirectional power flow in traditional distribution networks and increased the complexity of energy scheduling and operation management of distribution networks. Existing hierarchical coordinated control methods for multi-microgrids can guide the collaborative planning and optimal control research of multi-microgrids, but they do not monitor the power generation situation of renewable energy power generation equipment and the load situation, making it difficult to analyze and research the future energy exchange capacity of microgrids, and reducing the energy distribution capacity of distribution networks to microgrids. In addition, when the load changes, the energy exchange capacity of the microgrid also changes accordingly. Clarifying the energy exchange capacity helps reduce risks and promote the independent and stable operation of the microgrid. Summary of the Invention

[0004] The present invention provides an energy dynamic distribution system and method, which coordinates the energy flow between each microgrid through information interaction between each microgrid and between the microgrid and the distribution network, improves energy utilization efficiency, and reduces energy costs.

[0005] To achieve these and other advantages in accordance with the present invention, there is provided an energy dynamic distribution system, which includes an energy dynamic distribution center and a plurality of microgrids. The energy dynamic distribution center and the plurality of microgrids are communicatively connected, and the plurality of microgrids are communicatively connected to each other. The microgrid includes: an equipment layer, which includes non-renewable energy power generation equipment, renewable energy power generation equipment, battery energy storage equipment, and loads;

[0006] An equipment monitoring layer, which collects and stores renewable energy power generation data, battery energy storage data, and load data of the equipment layer;

[0007] A centralized management layer, which performs renewable energy power generation prediction and load prediction based on the data stored in the equipment monitoring layer, and formulates the power range of energy exchange at the next scheduling moment according to the prediction results and the battery energy storage situation;

[0008] An information interaction layer that realizes information interaction between the centralized management layer and the energy dynamic distribution center. The energy dynamic distribution center formulates an energy dynamic distribution plan according to the power range of energy exchange of each microgrid, sends an energy dynamic distribution instruction, and issues it to the centralized management layer through the information interaction layer;

[0009] A device control layer that, according to the energy distribution instruction of the centralized management layer, controls the device layer to adjust the output power, so as to realize dynamic energy distribution among multiple microgrids.

[0010] Preferably, the power range of energy exchange of the microgrid is (P min , P max ).

[0011] P min = P NRE + P ES-max-C - P LD

[0012] P max = P NRE + P RE + P ES-max-DC - P LD

[0013] Among them, P NRE represents the output power of non-renewable energy power generation equipment at the next scheduling moment, P RE represents the output power of renewable energy power generation equipment at the next scheduling moment, P ES-MAX-C represents the maximum charging power of the battery energy storage equipment at the next scheduling moment, and a negative number indicates that the battery energy storage equipment is charging, P ES-MAX-DC represents the maximum discharging power of the battery energy storage equipment at the next scheduling moment, and a positive number indicates that the battery energy storage equipment is discharging, P LD represents the load consumption power at the next scheduling moment;

[0014] The constraint conditions are:

[0015] P NRE + P RE + P ES-DC = P LD + P Loss

[0016] 0 ≤ P NRE ≤ P NRE-max

[0017] P ES-max-C ≤ P ES-DC ≤ P ES-max-DC

[0018] SOC min ≤ SOC ≤ SOC max

[0019] f min f ≤ f ≤ f max

[0020] U min U ≤ U ≤ U max

[0021] Among them, P ES-DC being negative represents the charging power of the battery energy storage device, and P ES-DC being positive represents the discharging power of the battery energy storage device at the next scheduling moment, P Loss represents the circuit transmission loss power, and P NRE-max represents the maximum output power of the non-renewable energy power generation device. SOC represents the state of charge of the battery, SOC min represents the lower safety limit value of the battery state of charge, and SOC max represents the lower safety limit value of the battery state of charge.

[0022] Preferably, the power range of the energy exchange of the microgrid is (P’ min , P’ max ),

[0023] P’ min = γ1(P NRE + P ES-max-C - P LD-B ) + γ2(P NRE + P ES-max-C - P LD-F )

[0024] P’ max = γ3(P NRE + P RE + P ES-max-DC - P LD-B ) + γ4(P NRE + P RE + P ES-max-DC - P LD-F )

[0025] Among them, P LD-B represents the load consumption power at the next scheduling moment during busy hours, and P LD-F represents the load consumption power at the next scheduling moment during idle hours. γ1, γ2, γ3, and γ4 are all weighting factors. The moment when the load exceeds the threshold is the busy hour, and the moment when the load does not exceed the threshold is the idle hour.

[0026] Preferably, the energy dynamic distribution center determines the constraint conditions with the aim of improving the utilization rate of renewable energy and minimizing the energy dynamic distribution cost as the objective function according to the power range of the energy exchange of each microgrid, forms an energy dynamic distribution plan, and sends an energy dynamic distribution instruction;

[0027]

[0028] F i = C NRE + C ES + C disp

[0029] Among them, F total represents the operating cost of each microgrid, N represents the number of microgrids, and F i represents the operating cost of the i-th microgrid, and C NRE represents the power generation cost of the non-renewable energy power generation equipment of the i-th microgrid, and C ES represents the cost of the battery energy storage equipment of the i-th microgrid, and C disp represents the cost of the i-th microgrid for energy dispatching to other microgrids;

[0030] The constraint conditions are:

[0031]

[0032] The alternating direction multiplier method is used to constrain the non-linear optimization during the optimization calculation.

[0033] Preferably, the device layer adjusts the output power. Specifically: obtain the current output power of the microgrid and compare it with the output power issued by the energy dynamic distribution center. If the current output power of the microgrid meets the requirements of the output power issued by the energy dynamic distribution center, it remains unchanged until the next scheduling moment; if the current output power of the microgrid does not meet the requirements of the output power issued by the energy dynamic distribution center, calculate the difference and adjust the output power according to the difference, and adjust it in the priority order of renewable energy power generation equipment, battery energy storage equipment, and non-renewable energy power generation equipment to meet the energy dynamic distribution requirements.

[0034] . The energy dynamic distribution method includes:

[0035] Step 1: Construct the energy dynamic distribution system described above;

[0036] Step 2: Determine the power range of energy exchange for a single microgrid;

[0037] According to the power range of energy exchange of each microgrid, with the aim of improving the utilization rate of renewable energy and minimizing the energy dynamic distribution cost as the objective function, determine the constraint conditions to form an energy dynamic distribution plan.

[0038] The present invention has at least the following beneficial effects:

[0039] First, by adopting the energy dynamic distribution system and method of the present invention, the power generation situation of renewable energy power generation equipment and the load situation are monitored. Each microgrid reports the power range of energy exchange. The energy dynamic distribution center formulates an energy dynamic distribution plan based on the power range of energy exchange reported by each microgrid. By analyzing and researching the future energy exchange capacity of the microgrid, the efficiency of the distribution network in distributing energy to the microgrid is improved, the energy flow between each microgrid is coordinated, the energy utilization efficiency is improved, and the energy cost is reduced.

[0040] Second, by adopting the energy dynamic distribution system and method of the present invention, the dynamic change of the load is further considered. That is, in addition to the load necessary for production and life, the increase in load caused by peak electricity consumption periods or increased seasonal electricity consumption needs to be considered. When the load increases, the energy exchange capacity of the microgrid is further clarified, and the outward exchange power is restricted. Conversely, if the self-generated electricity is not enough to meet the load, other surplus microgrids can exchange power inward to mainly meet the load of the microgrid itself and supply outward as a supplement, adjust the load demand, reduce risks, and promote the independent and stable operation of the microgrid.

[0041] Other advantages, objectives, and features of the present invention will be partially reflected by the following description and partially understood by those skilled in the art through the research and practice of the present invention. Brief Description of the Drawings

[0042] Figure 1 It is a schematic diagram of an energy dynamic distribution system for a technical solution of the present invention. Detailed Embodiments

[0043] The following further detailed description of the present invention is made in conjunction with the drawings so that those skilled in the art can implement it with reference to the text of the specification.

[0044] It should be understood that terms such as "having", "comprising", and "including" used herein do not exclude the presence or addition of one or more other elements or their combinations.

[0045] It should be noted that the experimental methods described in the following embodiments are all conventional methods unless otherwise specified, and the reagents and materials can be obtained from commercial channels unless otherwise specified. Therefore, it cannot be understood as a limitation to the present invention.

[0046] Such as Figure 1As shown in the figure, the present invention provides an energy dynamic distribution system, which includes an energy dynamic distribution center and multiple microgrids. The distribution network is equipped with an energy dynamic distribution center, which is responsible for issuing energy dynamic distribution instructions to the microgrids. The energy dynamic distribution center and the multiple microgrids are connected through communication, and the multiple microgrids are connected through communication. The communication method is the fieldbus protocol or the power system communication protocol. The microgrid includes:

[0047] The device layer, which includes non-renewable energy power generation devices, renewable energy power generation devices, battery energy storage devices, and loads. The non-renewable energy power generation devices include gas turbines and diesel generators, etc. The renewable energy power generation devices include wind power generation devices and photovoltaic power generation devices, etc. The device layer is configured with protection devices for equipment and line protection, etc. When the power generation of the renewable energy power generation devices in the microgrid is insufficient, the non-renewable energy power generation devices are enabled to assist in power generation;

[0048] The device monitoring layer, which collects and stores the renewable energy power generation data, battery energy storage data, and load data of the device layer, such as the wind and solar power generation data, power consumption data, battery storage capacity, and maximum possible charge and discharge power within the past 24 hours, etc. The database receives data in real time and stores historical data, and displays and manages the data through monitoring devices;

[0049] The centralized management layer, which conducts renewable energy power generation prediction and load prediction based on the data stored in the device monitoring layer, and formulates the power range of energy exchange at the next scheduling moment according to the prediction results and the battery energy storage situation, such as the wind and solar power generation data, power consumption data, battery storage capacity, and maximum possible charge and discharge power within the future 24 hours, etc.;

[0050] The information interaction layer, which realizes the information interaction between the centralized management layer and the energy dynamic distribution center, uploads the power data, load data of the distribution network, and the power range of energy exchange at the next scheduling moment to the energy dynamic distribution center. The energy dynamic distribution center formulates an energy dynamic distribution plan according to the power range of energy exchange of each microgrid. The energy dynamic distribution plan can be an energy dynamic distribution curve drawn with time as the abscissa (finely divided into 24 hours), that is, an energy dynamic distribution instruction for collaborative control between microgrids obtained by comprehensively evaluating various performance indicators for future power generation situations. The energy dynamic distribution instruction is sent and issued to the centralized management layer through the information interaction layer;

[0051] The device control layer, which controls the device layer to adjust the output power according to the energy distribution instruction of the centralized management layer, so as to realize the energy dynamic distribution between multiple microgrids.

[0052] Furthermore, the device layer adjusts the output power, which can divide the energy dynamic distribution curve into multiple scheduling moments to form a corresponding energy dynamic distribution plan. Specifically:

[0053] Obtain the current output power of the microgrid and compare it with the output power issued by the energy dynamic distribution center to determine whether the requirements are met. If the current output power of the microgrid meets the requirements of the output power issued by the energy dynamic distribution center, it remains unchanged until the next scheduling moment;

[0054] If the current output power of the microgrid does not meet the requirements of the output power issued by the energy dynamic distribution center, calculate the difference and adjust the output power according to the difference. According to the renewable energy power generation prediction, load prediction, and battery energy storage situation, adjust in the priority order of non-renewable energy power generation equipment, battery energy storage equipment, and renewable energy power generation equipment to meet the energy dynamic distribution requirements.

[0055] Specifically, by calculating the power range of the energy exchange of the microgrid within the next scheduling moment (e.g., the next 24h), report it to the energy dynamic distribution center for the energy dynamic distribution center to conduct energy dynamic distribution and receive instructions for energy scheduling. The power range of the energy exchange of the microgrid is (P min ,P max ),

[0056] P min =P NRE +P ES-max-C -P LD

[0057] P max =P NRE +P RE +P ES-max-DC -P LD

[0058] Among them, P NRE represents the output power of the non-renewable energy power generation equipment at the next scheduling moment, P RE represents the output power of the renewable energy power generation equipment at the next scheduling moment, P ES-MAX-C represents the maximum charging power of the battery energy storage equipment at the next scheduling moment. A negative number indicates that the battery energy storage equipment is charging, P ES-MAX-DC represents the maximum discharging power of the battery energy storage equipment at the next scheduling moment. A positive number indicates that the battery energy storage equipment is discharging, P LD represents the power consumption of the load at the next scheduling moment;

[0059] The constraint conditions include:

[0060] P NRE +P RE +PES-DC = P LD + P Loss

[0061] 0 ≤ P NRE ≤ P NRE-max

[0062] P ES-max-C ≤ P ES-DC ≤ P ES-max-DC

[0063] SOC min ≤ SOC ≤ SOC max

[0064] f min ≤ f ≤ f max

[0065] U min ≤ U ≤ U max

[0066] Among them, P ES-DC being negative represents the charging power of the battery energy storage device, and P ES-DC being positive represents the discharging power of the battery energy storage device at the next scheduling moment, P Loss represents the power loss of circuit transmission, and P NRE-max represents the maximum output power of the non-renewable energy power generation device. SOC represents the state of charge of the battery, SOC min represents the lower safety limit of the state of charge of the battery, and SOC max represents the lower safety limit of the state of charge of the battery.

[0067] The constraint conditions include power balance limitation, output power limitation of the non-renewable energy power generation device, maximum charging power limitation of the battery energy storage device, state of charge limitation of the battery, frequency limitation for the normal operation of the microgrid, and voltage limitation for the normal operation of the microgrid. The constraint conditions are ensured by a pre-set control strategy, and instructions are sent to the device control layer according to the execution result of the control strategy to control the device layer to adjust the output power.

[0068] The load is dynamically changing. When it is within the normal range, the power range of the energy exchange of the microgrid can be directly reported. When it is in the non-normal range of overloading, for example, if the above method is still used to determine the power range of the energy exchange of the microgrid, large deviations may occur. In another technical solution, the load is divided into peak-hour load and off-peak-hour load, corresponding to different moments and different historical data. By measuring the energy exchange capabilities during peak hours and off-peak hours, the power range of the energy exchange of the microgrid is further accurately limited, which helps to reduce risks and promote the independent and stable operation of the microgrid. The power range of the energy exchange of the microgrid is (P' min , P'max )

[0069] P’ min = γ1(P NRE + P ES-max-C - P LD-B ) + γ2(P NRE + P ES-max-C - P LD-F )

[0070] P’ max = γ3(P NRE + P RE + P ES-max-DC - P LD-B ) + γ4(P NRE + P RE + P ES-max-DC - P LD-F )

[0071] where P LD-B represents the load consumption power at the next scheduling moment during peak hours, P LD-F represents the load consumption power at the next scheduling moment during off-peak hours, and γ1, γ2, γ3, and γ4 are all weighting factors;

[0072] The calculation includes the following steps:

[0073] 1) Obtain historical data as input, and set the function loop termination value according to the prediction results of renewable energy power generation, load prediction, and battery energy storage status;

[0074] 2) Set the load thresholds for peak and off-peak hours, group the input data into peak-hour data and off-peak-hour data, and perform iterative calculations respectively according to the above functions and constraints;

[0075] Let k be 0, and perform optimization calculations according to the function P’ min to update P NRE , P ES-max-C , P LD-B during peak hours and P NRE , P ES-max-C , P LD-B during off-peak hours. Calculate the difference before and after the update. If it is less than the loop termination value, then determine γ1 and γ2. If it is greater than the loop termination value, then let k = k + 1, and repeat 3) until it is less than the loop termination value;

[0076] 4) Let the iteration count k be 0, and perform optimization calculations according to the function P’ max to update P NRE , P ES-max-C , P LD-B during peak hours and P NRE , P ES-max-C , P LD-B, calculate the difference before and after the update. If it is less than the loop termination value, then determine γ3 and γ4. If it is greater than the loop termination value, then let k = k + 1, and repeat 4) until it is less than the loop termination value.

[0077] Furthermore, based on the power range of the energy exchange of each microgrid, with the aim of improving the utilization rate of renewable energy and minimizing the energy dynamic distribution cost as the objective function, the energy dynamic distribution center determines the constraint conditions, forms an energy dynamic distribution plan, and sends an energy dynamic distribution instruction;

[0078]

[0079] F i = C NRE + C ES + C disp

[0080] Among them, F total represents the operating cost of each microgrid, N represents the number of microgrids, F i represents the operating cost of the i-th microgrid, C NRE represents the power generation cost of the non-renewable energy power generation equipment of the i-th microgrid, C ES represents the cost of the battery energy storage equipment of the i-th microgrid, C disp represents the cost of the i-th microgrid for energy scheduling to other microgrids;

[0081] The constraint conditions are:

[0082]

[0083] The alternating direction multiplier method is used to constrain the non-linear optimization during the optimization calculation.

[0084] In order to improve the utilization rate of renewable energy and maximize the utilization of renewable energy, on the premise that various power data and loads in the microgrid can meet the requirements, if there is still a surplus in the power generation of renewable energy in a single distribution network, according to the instruction of the energy dynamic distribution center, the renewable energy can be maximally utilized under the existing power generation plan, reducing the energy consumed by non-renewable energy power generation. With the minimum energy dynamic distribution cost as the objective function, the constraint conditions are determined, including power balance limitations, to minimize the overall operating cost of multiple microgrids and ensure the supply-demand balance of the microgrid operation.

[0085] The energy dynamic distribution method includes:

[0086] Step 1, construct the above-mentioned energy dynamic distribution system;

[0087] Step 2, determine the power range of the energy exchange of a single microgrid;

[0088] Step 3: Based on the power range of energy exchange of each microgrid, aiming to improve the utilization rate of renewable energy and taking the minimization of the dynamic energy distribution cost as the objective function, determine the constraints to form an energy dynamic distribution plan.

[0089] By using the energy dynamic distribution method of the present invention, monitor the power generation situation of renewable energy power generation equipment and the load situation. Each microgrid reports the power range of energy exchange. The energy dynamic distribution center formulates an energy dynamic distribution plan according to the power range of energy exchange reported by each microgrid. By analyzing and studying the future energy exchange capacity of the microgrid, the energy distribution efficiency of the distribution network for the microgrid is improved, the energy flow between each microgrid is coordinated, the energy utilization efficiency is improved, and the energy cost is reduced.

[0090] By using the energy dynamic distribution method of the present invention, further consider the dynamic change of the load, that is, in addition to the load necessary for production and life, it is also necessary to consider the increase in load caused by the peak electricity consumption period or the increase in seasonal electricity consumption. When the load increases, further clarify the energy exchange capacity of the microgrid and limit the outward exchange power. On the contrary, if the self-generated power is not enough to meet the load, other surplus microgrids can exchange power inward to mainly meet the load of the microgrid itself and supply outward as a supplement, adjust the load demand, reduce risks, and promote the independent and stable operation of the microgrid.

[0091] The number of devices and the processing scale described here are used to simplify the description of the present invention. The application, modification, and variation of the present invention are obvious to those skilled in the art.

[0092] Although the embodiments of the present invention have been disclosed above, it is not limited to the applications listed in the specification and the embodiments. It can be fully applied to various fields suitable for the present invention. For those familiar with the field, additional modifications can be easily achieved. Therefore, without departing from the general concept defined by the claims and the equivalent scope, the present invention is not limited to the specific details and the illustrated and described examples here.

Claims

1. An energy dynamic distribution system, which includes an energy dynamic distribution center and multiple microgrids. The energy dynamic distribution center and the multiple microgrids are connected through communication, and the multiple microgrids are connected through communication. It is characterized in that, The microgrid includes: an equipment layer, which includes non-renewable energy power generation equipment, renewable energy power generation equipment, battery energy storage equipment, and loads; an equipment monitoring layer, which collects and stores the renewable energy power generation data, battery energy storage data, and load data of the equipment layer; a centralized management layer, which conducts renewable energy power generation prediction and load prediction based on the data stored in the equipment monitoring layer, and formulates the power range of energy exchange for the next scheduling moment according to the prediction results and the battery energy storage situation; an information interaction layer, which realizes the information interaction between the centralized management layer and the energy dynamic distribution center. The energy dynamic distribution center formulates an energy dynamic distribution plan based on the power range of energy exchange of each microgrid, sends an energy dynamic distribution instruction, and issues it to the centralized management layer through the information interaction layer; an equipment control layer, which controls the equipment layer to adjust the output power according to the energy distribution instruction of the centralized management layer, so as to realize the energy dynamic distribution among multiple microgrids.

2. The energy dynamic distribution system according to claim 1, characterized in that, The power range of the energy exchange of the microgrid is (P min , P max ), P min = P NRE + P ES-max-C - P LD P max = P NRE + P RE + P ES-max-DC - P LD Among them, P NRE represents the output power of the non-renewable energy power generation equipment at the next scheduling moment, P RE represents the output power of the renewable energy power generation equipment at the next scheduling moment, P ES-MAX-C represents the maximum charging power of the battery energy storage equipment at the next scheduling moment, and a negative number indicates that the battery energy storage equipment is charging, P ES-MAX-DC represents the maximum discharging power of the battery energy storage equipment at the next scheduling moment, and a positive number indicates that the battery energy storage equipment is discharging, P LD represents the load consumption power at the next scheduling moment; The constraint conditions are as follows: P NRE +P RE +P ES-DC =P LD +P Loss 0 ≤ P NRE ≤ P NRE-max P ES-max-C ≤P ES-DC ≤P ES-max-DC SOC min ≤SOC≤SOC max f min ≤f≤f max U min ≤U≤U max Among them, P ES-DC being negative represents the charging power of the battery energy storage device, and P ES-DC being positive represents the discharging power of the battery energy storage device at the next scheduling moment, P Loss represents the power loss of circuit transmission, and P NRE-max represents the maximum output power of the non-renewable energy power generation device, SOC represents the state of charge of the battery, and SOC min represents the lower safety limit of the state of charge of the battery, and SOC max represents the lower safety limit of the state of charge of the battery.

3. The energy dynamic distribution system according to claim 2, wherein The power range of the energy exchange of the microgrid is (P’ min , P’ max ), P’ min = γ1(P NRE + P ES-max-C - P LD-B ) + γ2(P NRE + P ES-max-C - P LD-F ) P’ max = γ3(P NRE + P RE + P ES-max-DC - P LD-B ) + γ4(P NRE + P RE + P ES-max-DC - P LD-F ) Among them, P LD-B represents the load consumption power at the next scheduling moment during the busy period, and P LD-F represents the load consumption power at the next scheduling moment during the idle period. γ1, γ2, γ3, and γ4 are all weighting factors. The moment when the load exceeds the threshold is the busy period, and the moment when the load does not exceed the threshold is the idle period.

4. The energy dynamic distribution system according to claim 2 or 3, characterized in that The energy dynamic distribution center determines the constraint conditions with the aim of improving the utilization rate of renewable energy and minimizing the energy dynamic distribution cost as the objective function according to the power range of energy exchange of each microgrid, forms an energy dynamic distribution plan, and sends an energy dynamic distribution instruction; F i = C NRE + C ES + C disp Among them, F total represents the operating cost of each microgrid, N represents the number of microgrids, and F i represents the operating cost of the i-th microgrid, C NRE represents the power generation cost of the non-renewable energy power generation equipment of the i-th microgrid, C ES represents the cost of the battery energy storage equipment of the i-th microgrid, C disp represents the cost of the i-th microgrid for energy dispatching to other microgrids; The constraint conditions are as follows: The alternating direction multiplier method is used to constrain the non-linear optimization during the optimization calculation.

5. The energy dynamic distribution system according to claim 1, wherein The adjustment of the output power by the equipment layer is specifically as follows: obtain the current output power of the microgrid, and compare it with the output power issued by the energy dynamic distribution center. If the current output power of the microgrid meets the requirements of the output power issued by the energy dynamic distribution center, it remains unchanged until the next scheduling moment; if the current output power of the microgrid does not meet the requirements of the output power issued by the energy dynamic distribution center, calculate the difference, and adjust the output power according to the difference, and adjust it in the priority order of renewable energy power generation equipment, battery energy storage equipment, and non-renewable energy power generation equipment to meet the requirements of energy dynamic distribution.

6. Energy dynamic allocation method, characterized in that, It includes: Step 1: Construct the energy dynamic distribution system described in Claim 5; Step 2: Determine the power range of energy exchange of a single microgrid; Step 3: Determine the constraint conditions with the aim of improving the utilization rate of renewable energy and minimizing the energy dynamic distribution cost as the objective function according to the power range of energy exchange of each microgrid, and form an energy dynamic distribution plan.

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