1606 results about "Microgrid" patented technology

The invention belongs to the field of data processing, and particularly relates to a dynamic cooperative control system and method for a gas turbine and a micro-grid, and the method comprises the steps: constructing a micro-grid real-time monitoring module, continuously collecting distributed energy real-time output, controllable load demands, bus voltage frequency and equipment state parameters, and carrying out the filtering and noise reduction through a preprocessing unit, thereby guaranteeing the data precision; calculating a real-time power difference value based on the preprocessed data, calling an adaptive neural fuzzy inference system, taking the power difference value, the bus voltage deviation and the frequency deviation as input, and judging whether the power difference value, the bus voltage deviation and the frequency deviation exceed a preset threshold value by means of a fuzzy rule base and a neural network model; if the threshold values are not exceeded, the current states of the gas turbine and the energy storage system are maintained; if any one exceeds the threshold value, a dynamic cooperative control instruction is triggered, precise cooperative control of the gas turbine and the micro-grid is achieved, and the operation stability, the operation efficiency and the reliability of the micro-grid are improved.

To provide a system and an apparatus for implementing a mobile energy system.SOLUTION: In an aspect, a mobile energy system includes a cabinet having an interior space defined by an outer surface of the cabinet, and the interior space can include a battery storage area configured to receive a battery energy storage system having at least 2 kWh of storage capacity. The mobile energy system can also include an item storage area configured to receive and store one or more other items, a connector configured to connect the battery energy storage system located in the battery storage area to an external power source, and a charging cable configured to connect the battery energy storage system to a charging port of an electric vehicle.SELECTED DRAWING: Figure 4

The invention relates to the technical field of voltage control, in particular to a time-delay-containing uncertain AC / DC micro-grid DC bus voltage control method, which comprises the following steps: acquiring load change and DC bus voltage fluctuation data, calculating a load current change rate, analyzing the correlation between voltage fluctuation and load change, and performing voltage adjustment. And time delay characteristics in a load state are identified, voltage fluctuation uncertainty factors are identified, and the time delay compensation amount is adjusted to restore the voltage stability. According to the invention, by adopting linear and nonlinear time-delay compensation strategies, the problem of accuracy of time-delay compensation under different load conditions is effectively solved, various load fluctuations and voltage changes can be dynamically adapted, the problem of uncertainty of voltage fluctuations is solved, and the prediction of voltage fluctuations is optimized by dynamically adjusting the weight of uncertainty factors. The over-reaction to sudden voltage change is reduced, the voltage stability is improved, and the operation stability and the voltage regulation precision of the micro-grid are remarkably improved.

The invention provides a self-adaptive constraint model active mismatch prediction control method based on voltage and current ripple resistance of a power converter in a hybrid energy storage system, and the method comprises the steps: building an island DC micro-grid system model, collecting the voltage and current information of a system, and designing a model prediction control frame of a power loop and a cost function of the model prediction control frame; designing a model predictive control framework of the current loop and a cost function of the model predictive control framework; designing an active model mismatch mechanism to enhance the response capability to dynamic change; determining an optimization problem with a normal value, and designing an adaptive constraint optimization algorithm to dynamically adjust constraint parameters and optimize control performance; and designing a steady-state and dynamic-mode trigger for adapting to the running state of the system. According to the invention, the trajectory tracking precision of the system under dynamic and steady-state working conditions can be significantly improved, current ripples caused by control delay can be effectively eliminated, damage to electrical equipment due to overlarge ripples can be avoided, and the service life of the equipment can be prolonged.

The invention discloses an island detection method based on harmonic dynamic characteristics and reactive slip collaborative identification and a detection system thereof, and relates to the field of new energy island detection. In order to solve the defects of low feature extraction precision, threshold stiffness and insufficient response speed of existing island detection, an operation data set of a micro-grid system is acquired according to a topological structure of the micro-grid system; dynamic characteristic data fusion processing is implemented, and harmonic voltage is calculated; a harmonic voltage break variable is used as a starting criterion of island detection; sequentially judging whether the harmonic voltage break variable, the fundamental voltage amplitude and the offset of each harmonic voltage are out of limit or not so as to judge whether the micro-grid is in an island state or not; and constructing a virtual orthogonal signal to calculate a three-phase reactive slip ratio, judging whether the three-phase reactive slip ratio is out of limit, if not, determining that the microgrid is in a non-islanding state, and if yes, determining that the microgrid is in an islanding state. The method is mainly used for judging whether the microgrid is in the island state or not.

The invention relates to the field of clean energy, and provides a distributed secondary control method based on deep reinforcement learning, and the method comprises the steps: S1, deploying a DDPG intelligent agent in a distributed micro-grid, and enabling the DDPG intelligent agent to be used for secondary control; s2, establishing a communication graph model of the distributed micro-grid based on a graph theory, so that each distributed power supply in the distributed micro-grid only exchanges control signals and voltage information with the adjacent distributed power supplies; and S4, regulating and controlling the output power of the distributed power supply by using the intelligent agent, and dynamically regulating the frequency and voltage secondary control signal according to the decision of the intelligent agent. Therefore, the dynamic adaptability and the system-level reliability of the distributed power system are improved.

The invention discloses an electric vehicle V2G micro-grid energy storage capacity optimization method based on dynamic planning, particularly relates to the technical field of micro-grid energy storage optimization, and aims to solve the problem of energy storage capacity optimization defects caused by spatial dynamic characteristics caused by mobility of an existing electric vehicle. Performing geographic grid division on the node position, generating a space-time matrix by combining with a timestamp, and identifying a high-frequency access node; constructing a state transition equation based on the inter-node impedance matrix, and setting a node-level safety boundary by taking a line capacity change rate as a dynamic constraint; a staged reverse dynamic programming algorithm is adopted, spatial dimension optimization is preferentially executed on the high-frequency access nodes, and charging and discharging constraints fusing voltage deviation and capacity overrun penalty terms are generated; carrying out global optimization by taking the minimization of the total operation cost as a target after the constraints are integrated, and outputting an energy storage capacity configuration strategy of each time period; and finally generating an energy storage deployment scheme.

The invention discloses an energy consumption analysis method and system based on a micro-grid resource physical digital space model, and the method comprises the steps: obtaining first monitoring data of distributed energy equipment and second monitoring data of electric equipment in a micro-grid, and fusing the data to construct the micro-grid resource physical digital space model; constructing a distributed energy transaction platform based on the block chain based on the model; an energy consumption traceability function is integrated in the transaction platform, an energy consumption traceability tree model is constructed, then the energy consumption contribution degree of each distributed energy device and the energy consumption responsibility sharing proportion of each electric device are calculated, and an energy consumption traceability report is generated and is linked for evidence storage; by constructing the energy consumption traceability tree model, fine traceability and responsibility sharing of micro-grid energy flow can be realized, accurate data support is provided for energy consumption analysis and management, and transparency and fairness of micro-grid energy management are remarkably improved.

The invention discloses a new energy access lower harbor area transformer insulation performance and service life evaluation method, which comprises the following steps: firstly, establishing a wind and light storage AC / DC hybrid micro-grid equivalent simulation model, and quantifying a composite action mechanism of new energy fluctuation and harmonic characteristics on dynamic loss and hot-spot temperature rise of a transformer; analyzing a harmonic loss mechanism of the transformer in different operation modes; secondly, constructing a quay crane and field crane operation simulation model, and analyzing the harmonic characteristics of bridge crane equipment and the influence of the harmonic characteristics on the harmonic distortion rate of the power distribution network; then, on the basis of the data, a transformer hot-spot temperature dynamic calculation model is established in combination with bidirectional power flow characteristics; and finally, calculating transient temperature distribution of the transformer through a flow field-temperature field coupling method, and constructing a multi-physical field coupled insulation aging rate model to realize evaluation of the residual life of the transformer. The method solves the problem that the traditional method cannot quantify the bidirectional power flow and harmonic wave composite aging effect.

The invention discloses a distribution network source-load collaborative micro-grid autonomous system and method, relates to the technical field of micro-grids, and realizes interconnection and intercommunication between an intelligent fusion terminal and equipment such as a charging pile, a photovoltaic device, an energy storage device, a low-voltage intelligent switch and the like by utilizing wireless communication technologies such as HPLC (High Performance Liquid Chromatography), 5G (5th Generation) and the like compared with the previous micro-grid autonomous system. By applying intelligent algorithms such as linear regression and machine learning, the platform automatically generates various optimization adjustment strategies, and after the strategies are audited by management personnel, a control command is issued to the terminal equipment through the intelligent fusion terminal; and remote intelligent operations such as energy storage charging and discharging mode adjustment, charging pile output power limit, photovoltaic output flexible regulation and control and automatic switching on and switching off of a low-voltage intelligent switch are realized. And performing whole-process monitoring on strategy execution, determining whether the strategy execution reaches a preset target, outputting a result analysis report, continuously optimizing an intelligent algorithm in combination with field equipment operation parameters, and continuously improving a source-network-load-storage collaborative interaction level.

The invention relates to the technical field of large-scale power grid safety guarantee, in particular to an optimal decentralized coordination control method for a micro-grid in a new energy power system, which comprises the following steps of: performing virtual disconnection verification on key power transmission lines one by one based on online acquired power grid topology and real-time line power flow data, and establishing a whole-grid cascade risk quantitative index. According to the method, power grid topology and line power flow data are acquired in real time, virtual disconnection verification of key power transmission lines is implemented one by one, simulation and analysis of a line fault scene are realized, whole-network cascade risk quantitative indexes are established on the basis, and an initial fault line with the maximum threat to system safety is identified by comparing the indexes with a safety threshold value in real time, so that the safety of the system is improved. A fragile line risk contribution list is generated, and high-risk lines are positioned and prevented in advance; and further directly calculating the power adjustment amount required by the micro-grid group according to the risk contribution list, and forming a forward-looking tide dredging instruction set.

The application discloses a shared energy storage system optimization method and system for comprehensive energy microgrids, which take into account a shared energy storage-multi-microgrid system model invested by a third party. The comprehensive energy microgrids are regional energy systems integrating multiple energy sources and adjustable loads, including CHP, heat storage, power storage and distributed renewable energy. Shared energy storage is invested by a third part, serve as a power price publisher, and is limited by power price boundaries. The method takes into account a carbon emission and trading model to reduce carbon emission. Costs of the microgrids include a power / gas buying cost, a demand response cost, a carbon trading cost, and an operating cost of CHP units. Finally, a minimum cost solution is resolved by a MILP algorithm. The invention realizes microgrid scheduling and improves the economic efficiency and environmental friendliness of the comprehensive energy microgrids.

The invention provides a grid-connected and off-grid seamless switching method and system for a network-constructed energy storage micro-grid, belongs to the technical field of grid-connected and off-grid switching, and realizes rapidity and stability of micro-grid mode switching through multi-stage cooperative control. The method comprises the following steps: a power grid state real-time monitoring stage: acquiring power grid short-circuit capacity, impedance angle, voltage amplitude, frequency and phase parameters through impedance spectrum analysis and phase-locked loop cooperative detection; a pre-synchronization-hybrid control-dynamic damping three-stage switching stage; a steady state maintaining stage: maintaining a system damping ratio gt through a multi-target cooperative controller; and in the whole switching process, the bus voltage fluctuation is less than or equal to 2%, and the frequency deviation is less than or equal to 0.1 Hz. According to the method, MPC pre-synchronization, hybrid control of dynamic weight, virtual impedance adaptive compensation and multi-target collaborative optimization are controlled through model prediction, so that the problems are solved, seamless switching is realized, and the quality of electric energy is improved.

A method for the classification and detection of faults in a microgrid having a distance relay, includes measuring the first plurality of voltage signals and the first plurality of current signals of the microgrid, calculating a plurality of fault-loop impedance signals, comparing the plurality of fault-loop impedance signals and a plurality of reference impedance values, inputting the plurality of difference values to a convolutional neural network (CNN)-gated recurrent unit (GRU) hybrid model, generating a reference tripping signal, defining a deep reinforcement learning (DRL) agent for a deep reinforcement learning (DRL) model. The method further includes processing a second plurality of voltage signals and current signals of microgrid and classifying the one or more fault signals into one or more fault types.

The invention belongs to the technical field of multi-energy micro-grid cooperative regulation and control. The invention discloses a multi-energy micro-grid coordinated regulation and control system based on cross-layer knowledge injection and federated distillation. The system is characterized by comprising a cross-layer knowledge injection network; a federal knowledge distillation module; and the uncertainty map regulation and control module is used for constructing an MEMG uncertainty association map, learning the influence weight of each uncertainty factor on a regulation and control decision through a map attention mechanism, and realizing a dynamic risk avoidance strategy. The invention discloses a multi-energy micro-grid cooperative regulation and control method based on cross-layer knowledge injection and federated distillation. The method is characterized by comprising the following steps: step 1, MEMG topology knowledge coding; 2, cross-layer knowledge injection training is carried out; step 3, federal knowledge distillation optimization; and step 4, performing uncertainty map regulation and control. According to the system and the method, the precision, the robustness and the data privacy protection capability of MEMG regulation and control are improved, and the system and the method are suitable for efficient collaborative optimization of the park-level multi-energy microgrid.

The invention belongs to the technical field of transformer evaluation, and particularly relates to a harbor area transformer bearing capacity evaluation method, which comprises the steps of S1, analyzing voltage and current distribution characteristics and a harmonic component propagation rule of a harbor area microgrid under high-proportion new energy access; analyzing a change rule of a winding leakage magnetic field, an iron core magnetic flux density and winding and iron core loss; s2, calculating the hot spot temperature of the transformer in each historical time period; s3, calculating the predicted residual service life Tb and the predicted actual total service life Tins of the transformer; s4, calculating an aging coefficient B and a primary health index H1 of the transformer; s5, calculating a comprehensive health index Hcom of the transformer; s6, calculating a final health index H of the transformer; s7, if H reaches a preset threshold value, equipment is replaced; and if not, reversely deducing and predicting the residual life Tb1. According to the method, the operation state of the transformer can be accurately evaluated under the working condition of frequent power flow switching.

The invention relates to the technical field of energy storage systems, and provides a self-adaptive power distribution method and system for multiple energy storage units of an island microgrid. According to the invention, a discrete consistency algorithm is adopted to realize coordination control of multiple units, each unit only exchanges information with adjacent units, and power distribution targets of all the units are converged to a consistent value through iterative computation, so that the communication bottleneck and the single-point fault risk of centralized control are avoided; according to the invention, a complete fault-tolerant processing mechanism is designed, the operation state of each energy storage unit is monitored in real time, topology updating and power redistribution are automatically carried out when a unit fault is detected, and the self-healing operation of the system is realized. Experiments show that compared with a traditional method, the method has remarkable advantages in key performance indexes such as capacity balance among energy storage units, system operation efficiency, communication overhead and fault recovery time, and the operation efficiency and reliability of the island microgrid system are remarkably improved.

The invention relates to the technical field of micro-grids, and discloses an inverter output waveform optimization control method, an inverter and a storage medium, and the method comprises the steps: constructing a switching period average model and an output waveform optimization function of a single-phase off-grid inverter, and carrying out the optimization control of the output waveform of the single-phase off-grid inverter based on the output waveform optimization function and the switching period average model, determining a calculation model of a modulation wave compensation signal; acquiring an input signal for controlling the output waveform of the inverter, performing double closed-loop control on the inverter based on the input signal, and outputting an original modulated wave signal; calculating a modulation wave compensation signal based on the input signal, an inductive current reference value generated in double closed-loop control and a modulation wave compensation signal calculation model; and superposing the original modulated wave signal and the modulated wave compensation signal to obtain an optimized modulated wave signal. According to the method provided by the invention, the modulation wave signal is compensated and optimized, and the purpose of optimizing the waveform quality of the output voltage when the single-phase off-grid inverter is loaded with the nonlinear load is achieved.

The invention belongs to the technical field of photovoltaic energy storage charging scheduling, and particularly relates to an intelligent scheduling method and system for a photovoltaic energy storage charging micro-grid system, and the system comprises a photovoltaic power generation detection module, an energy storage equipment detection module, an electric equipment detection module, an upper computer, and an optimization scheduling module. The signal output ends of the photovoltaic power generation detection module, the energy storage equipment detection module and the electric equipment detection module are connected with the upper computer, and the output end of the upper computer is connected with the optimal scheduling module. According to the scheme, based on information collection of the photovoltaic power generation equipment, the energy storage equipment, the power utilization equipment and other equipment, comprehensive information conditions can be obtained, and the power utilization mode is comprehensively scheduled based on the comprehensive information, so that the method can be better suitable for the use environment. The advanced communication technology realizes rapid and reliable data transmission among devices, ensures that a scheduling instruction can be timely and accurately transmitted to each device, and ensures that the acquired data can be fed back to a scheduling center in real time.

A microgrid has a microgrid controller that controls power delivery from two or more energy sources to one or more microgrid loads. A prediction is made as to when a main power grid may lose power. The microgrid controller operates in a prepare for islanding mode when a future loss of power is predicted, during which power received from the main power grid source, a solar power source and / or a wind power source are prioritized over energy costs and CO2 emissions to charge the battery power source to a prepare for islanding charge level. The microgrid controller operates in an islanding mode when the main power grid source loses power, during which power received from the solar power source, the wind power source, the battery power source and / or a diesel generator power source are prioritized to maximize a time that the microgrid can remain powered.

The invention discloses a microgrid stability control method and system based on output characteristic simulation. The method comprises the following steps: acquiring fluctuation characteristic data, meteorological condition data, operation data, load demand data and environmental parameter data; separating the fluctuation characteristic data to obtain a periodic track and a random disturbance component; performing correlation analysis according to the periodic trajectory, the random disturbance component and the meteorological condition data to obtain potential influence data; according to the potential influence data and the operation data, obtaining an adaptability index; if the adaptability index is lower than a preset index threshold value, the energy capacity and the frequency range are adjusted according to the random disturbance component, the operation data and the load demand data, and dynamic response configuration is obtained; according to the dynamic response configuration, in combination with a preset state switching loss parameter and a preset environment adaptability parameter, generating an initial adjustment instruction template; and generating a control instruction set based on the initial adjustment instruction template in combination with the environmental parameter data, the adjustment frequency and the power parameter.

The invention provides a multifunctional heating ventilation air conditioner waste heat utilization method and system, and the method comprises the following steps: 1, obtaining multi-source data of an air conditioner system and an external heat source, carrying out the preprocessing, carrying out the grading collection and preliminary integration of the multi-source waste heat, and dividing the multi-source waste heat into high-temperature waste heat, medium-temperature waste heat and low-temperature waste heat; multi-source data of an air conditioning system and an external heat source are collected, condensation heat of a compressor, industrial waste heat and other multiple types of waste heat are integrated and subjected to staged treatment, and a high-temperature power generation-medium-temperature heat supply-low-temperature heat storage gradient utilization system is constructed; an LSTM neural network thermal load prediction model and an intelligent algorithm are combined to dynamically adjust a waste heat distribution path so as to realize self-adaptive switching of a refrigeration mode, a heating mode and a hot water mode, and meanwhile, a cascade system, photovoltaic energy, geothermal energy and the like are coupled through a direct-current micro-grid to construct a hybrid energy supply system. The problems that in the prior art, waste heat sources are single, energy efficiency is low due to the fact that gradient utilization is lacked, dynamic regulation and control are insufficient, and cooperation with renewable energy sources is not achieved are sequentially solved.

A method of operating a microgrid system includes: obtaining a microgrid dispatch schedule input that includes a schedule of required electrical energy generation for the microgrid system for a given time period; filtering the scheduled dispatch input and converting the scheduled dispatch input into power levels to meet power demands for required electrical energy generation of the dispatch schedule input for the microgrid system; receiving a current load level for the microgrid system based on one or more electrical loads electrically coupled to the microgrid system; comparing the schedule of required electrical energy generation to an actual required electrical energy generation for the microgrid system; and dispatching one or more electrical assets in real time to meet a difference between the scheduled required electrical energy generation and the actual required electrical energy generation.

The invention discloses a method for improving the production quality of electrolytic aluminum based on an electrolytic cell. According to the invention, by systematically optimizing the structure and the production process of the electrolytic cell, the quality and the production sustainability of an electrolytic aluminum product are remarkably improved. In the aspect of environmental protection treatment, dry purification and carbon dioxide mineralization technologies are adopted, and a waste heat gradient utilization system is combined, so that emission of pollutants such as fluorides and carbon dioxide is greatly reduced, waste heat in the production process is converted into reusable steam energy, and enterprises are promoted to be transformed to be green and low-carbon. Meanwhile, the micro-grid integrates application of renewable energy sources, dependence on traditional energy sources is further reduced, an ecological chain of efficient resource circulation is formed, and the development bottleneck of high energy consumption and high pollution in the electrolytic aluminum industry is effectively relieved.

The present application discloses a microgrid control method and apparatus, a microgrid, and a storage medium. A power type energy storage device is connected within a microgrid, and the microgrid control method comprises: when it is determined that the microgrid is in an unplanned islanding mode, controlling the power type energy storage device to enter a power support mode, wherein the power type energy storage device charges and discharges the microgrid in the power support mode; when the power type energy storage device is in the power support mode, carrying out source-load power adjustment on the microgrid; and once the microgrid reaches a source-load power balance, controlling the power type energy storage device to exit the power support mode. According to the microgrid control method, during unplanned islanding of the microgrid, flexible source-load power adjustment can be carried out thereon within a relatively sufficient time frame, thereby ensuring the stable operation of the microgrid.

The invention discloses a source-grid-load-storage integrated coordinated management and control system for an intelligent micro-grid, and relates to the technical field of intelligent micro-grids and comprehensive energy regulation and control. The system comprises the following components: a multi-energy-flow data acquisition unit, a multi-energy-flow coupling modeling and optimizing unit, a multi-energy-flow gradient utilization execution unit, a mode self-adaptive switching unit and a main control unit, according to the invention, through a multi-energy flow coupling modeling and optimization unit, an electric-thermal-gas multi-energy flow coupling model comprising a heat supply network transmission loss calculation sub-model is constructed, a renewable energy consumption constraint sub-model is additionally arranged, and an improved hybrid particle swarm optimization algorithm is adopted to carry out dynamic optimization solution, so that an optimal scheduling strategy is generated; according to the strategy, the consumption rate of renewable energy sources is increased, electricity-heat gradient utilization and efficient configuration are achieved through a heat energy distribution priority regulation and control mechanism and efficiency optimization control of the waste heat recovery module, and dependence of heat loads on electric energy is remarkably reduced.

The invention relates to an island microgrid energy storage optimization configuration method based on load power prediction, and the method comprises the following steps: constructing an energy system model which comprises a wind turbine generator model, a photovoltaic generator set, an energy storage system model and a diesel generator set model; establishing an energy storage optimization configuration model; establishing a load short-term power prediction model and speculating a prediction value; a non-dominated solution elite decision-making mechanism in an NSGA-II algorithm is introduced into a multi-target particle swarm algorithm to serve as a multi-target sorting strategy, and an energy storage optimal configuration scheme is obtained. According to the method, after load prediction is considered, the multi-target hybrid particle swarm optimization algorithm is adopted, optimal parameter selection of the energy storage device can be more efficiently realized, and stable operation of the island microgrid system is realized.

The invention discloses a regional distributed energy storage optimization scheduling method, which comprises the following steps: S1, model construction: constructing a mixed integer nonlinear programming model containing a multi-objective optimization function according to physical characteristics, operation constraints and economic objectives of a regional power distribution network, a micro-grid, an energy storage system and renewable energy; s2, scene generation and processing: adopting a Latin hypercube sampling method to generate a multi-scene data set of renewable energy output, load demand and electricity price fluctuation, performing clustering analysis on scene data, and screening out representative typical scenes so as to reduce calculation complexity; and S3, carrying out optimization solution. In the application, multi-dimensional constraints such as energy storage life attenuation, network loss, carbon emission and the like are added in constraint conditions, the practicability of the model is improved, and the limitation of traditional single-target scheduling is broken through through multi-target optimization and multi-constraint coordination.

A microgrid system includes an electrical bus including at least one electrical load; at least one non-energy storage system asset configured to supply electrical power to the electrical bus; an energy storage system group including: two or more energy storage system assets configured to supply electrical power to the electrical bus, and a system controller operatively coupled to each of the assets on the electrical bus. The system controller is configured to: determine characteristic energy set points and power limits for each of the assets; determine that at least two or more assets have a same priority for power distribution; determine the characteristic power set points for the non-energy storage assets, dispatch the energy storage system assets having the same priority by treating a dispatch for the energy storage system assets as a combined asset.

The invention discloses a distribution network and micro network double-layer collaborative optimization scheduling method and system based on an active power aggregation domain, and the method comprises the steps: obtaining the operation parameters of a distribution network, and constructing the operation constraint of the distribution network; obtaining operation parameters of the micro-grid, and constructing operation constraints of the micro-grid; constructing a mathematical model of a micro-grid active power aggregation domain based on micro-grid operation constraints; solving the mathematical model by using a rank generation algorithm to obtain an operation boundary of the active power aggregation domain of the micro-grid; and submitting the active power aggregation domain of the micro-grid to the distribution network for scheduling, judging whether the active power aggregation domain of the micro-grid meets a distribution network loss minimization criterion or not in combination with the operation constraint of the distribution network, if so, controlling power output at a micro-gateway port by using the operation boundary, otherwise, adjusting the operation boundary of the active power aggregation domain of the micro-grid. And updating the mathematical model of the aggregation domain and solving until the operation boundary meets the target of minimum distribution network loss. According to the method, the scheduling model of the medium-voltage distribution network can be simplified and the scheduling efficiency can be improved under the condition that information interaction is limited.