173 results about "Tie line" patented technology

The invention discloses a distribution-micro collaborative operation simulation optimization method, which belongs to the technical field of simulation optimization, and comprises the steps of preprocessing grid-connected point voltage data, tie line power data and communication time delay data, constructing a power distribution network power flow physical network following a Kirchhoff's law, outputting a source load power prediction curve by using a long short-term memory network algorithm, and calculating the distribution-micro collaborative operation according to the source load power prediction curve. And a distribution-micro collaborative simulation optimization model is obtained based on residual error rolling correction tie line impedance parameters, a delay penalty term is set in a target function in combination with the preprocessed communication delay data, a power regulation instruction is obtained by using a particle swarm optimization algorithm, and a dynamic simulation video stream is generated. According to the invention, through rolling correction of the tie line impedance parameters and setting of the delay penalty term positively correlated with the time delay, the problem of control failure caused by physical deviation caused by model parameter solidification and communication time delay accumulation is solved, and the defects of voltage deviation calculation distortion and inaccurate network loss evaluation are eliminated. And the simulation precision and the operation stability of distribution-micro cooperation are improved.

The invention provides a cascade AGC (Automatic Gain Control) frequency modulation regulation control optimization method, which comprises the following steps: acquiring frequency deviation and tie line power deviation in a power system in real time, calculating a regional control error ACE based on the two deviations, and decomposing the ACE into a frequency deviation component and a tie line power deviation component; calculating a ratio coefficient of the frequency deviation component in the ACE and a ratio coefficient of the tie line power deviation component in the ACE; acquiring a climbing rate and an adjustable capacity of each frequency modulation unit, and performing normalization processing on the climbing rate and the adjustable capacity; calculating the rate-capacity double weight of each unit through a dynamic weight formula in combination with the ratio coefficient, the normalized climbing rate and the normalized adjustable capacity, and distributing frequency modulation power to each unit according to the normalized weight; in the operation process, on-line self-adaptive adjustment is carried out on dynamic weight calculation and unit adjustment related parameters according to system performance indexes.

The invention provides a cross-day two-stage random scheduling method for an industrial park integrated energy system, and the method comprises the steps: fitting the output fluctuation characteristics of new energy power generation equipment in a cross-day time scale based on historical data, and constructing an uncertainty scene set containing a new energy prediction error; establishing a cross-day two-stage stochastic programming model; according to the two-stage model, an optimal scheduling scheme is solved so as to minimize the overall operation cost, and the operation cost comprises the demand electric charge, the electricity purchase electric charge, the new energy power abandoning cost, the unit start-stop cost and the standby penalty cost; and on the basis of tie line power constraint and dynamic response characteristics of the multi-energy coupling equipment, feasibility verification and rolling optimization adjustment are performed on the scheduling scheme. According to the method, the new energy consumption capability of the industrial park integrated energy system under the cross-day time scale can be effectively improved, the total operation cost is reduced, and collaborative scheduling of demand cost optimization and spot market participation is realized.

The invention discloses an energy storage cross-regional cooperation AGC optimization control method and equipment considering conditional SOC equalization, and the method comprises the steps: firstly evaluating the equivalent charge state and dynamic frequency modulation capability of an energy storage system in each region in real time, and judging whether a cross-regional cooperation condition is satisfied or not; if yes, a multi-objective optimization model is established, and the model takes a plurality of objective functions as optimization objectives, including enabling the equivalent state of charge to be balanced, minimizing inter-region tie line transmission power and maximizing the residual frequency modulation capability, and meanwhile, takes power grid operation parameters as constraint conditions. And by solving the model, obtaining an optimal output instruction of the energy storage system in each region in the next AGC control period, and issuing the optimal output instruction to the corresponding energy storage system for execution. The invention aims to support other regions through the tie line when the frequency modulation margin of the energy storage system in the interconnected region is sufficient, avoid frequency fluctuation caused by over-limit of the energy storage SOC and insufficient frequency modulation of a thermal power generating unit, improve the safety and reliability of energy storage frequency modulation, effectively stabilize the frequency fluctuation of a power grid, and enhance the anti-disturbance capability of a power system.

The invention discloses an AGC information physical system reliability verification method and system, and relates to the technical field of power dispatching automation. The problems that an existing AGC system only adopts a static operation mode and an ideal communication condition in a simulation test, and coupling response of continuous operation and sudden disturbance of a power grid under a long time scale is difficult to reproduce truly are solved. The state evolution under event driving is realized by constructing three types of simulation event sources of a time sequence operation sample, a master station control instruction and external disturbance and setting a priority mechanism of external disturbance gt, master station instruction gt and time sequence propulsion; an uplink channel fault model is introduced to simulate on-off, delay and errors of measurement data, and a downlink channel fault model is introduced to simulate transmission abnormity of a control instruction; closed-loop simulation of frequency response and electrical quantity updating is realized by combining promotion of a rotor motion equation and dynamic load flow calculation; and finally, by analyzing indexes such as frequency deviation, tie line deviation and control response delay, comprehensive reliability evaluation of the AGC system in a complex information physical environment is completed.

The invention provides a power grid dispatching control method based on renewable energy source and energy storage collaborative optimization, which comprises the following steps: S1, acquiring the power of a tie line of a regional power grid and a main power grid, determining the real-time fluctuation ratio of the power of the tie line, and determining a virtual power plant configuration according to the real-time fluctuation ratio; s2, the renewable energy units and the energy storage units used for building a virtual power plant are screened out according to the operation parameters of the renewable energy units and the energy storage units, and the virtual power plant is built according to the virtual power plant configuration; acquiring a real-time operation state of an energy storage unit in the virtual power plant; dividing the energy storage units into different control groups according to the real-time operation states of the energy storage units, and configuring charging and discharging control parameters for each control group; s3, inputting the topological structure of the virtual power plant into the digital twin system, simulating the operation of the virtual power plant in the digital twin system, and operating according to the charge and discharge control parameters configured in the step S2; and S4, constructing a virtual power plant operation comprehensive evaluation model, determining an optimal value of the evaluation model by adopting a genetic algorithm, and taking the charging and discharging control parameters corresponding to the optimal value as power grid dispatching control parameters.

A computing system for functional integration with a distributed power grid having one or more inverters. The computing system includes processing device(s) to control operation of an inverter by executing a feedback controller with a grid-tied line, of the distributed power grid, treated as a plant and including a unified algebraic control system operating based on a pair of closed-loop variables carried in closed-loop signals of the unified algebraic control system. The processing device(s) control, using the feedback controller, transitions of the inverter between a plurality of operating modes by adjusting a magnitude of the closed-loop signals, which correspond to the pair of closed-loop variables, towards a setpoint of a plurality of setpoints. Each setpoint corresponds to a different operating mode of the plurality of operating modes.

The invention relates to a traveling wave device stationing and fault positioning method suitable for a load transfer operation mode, and belongs to the technical field of power system fault distance measurement. The method comprises the following steps: obtaining a branch forest in a normal operation mode based on a line topological structure; obtaining a branch forest in a load transfer operation mode according to the load transfer operation of the two connection lines; if the topological tree structures and leaf nodes of the two branch forests under the same root node change, preferentially arranging traveling wave devices at the leaf nodes appearing in the two different topological trees under the same root node, otherwise, calculating the weight coefficient of each branch in the topological tree structures, and arranging traveling wave devices at the branch nodes with high weight coefficients; when a single-phase earth fault occurs on the line, the distance between each traveling wave device and the fault point is calculated, fault section tracing is carried out, and the position of the earth fault point is determined. The objective of the invention is to solve the technical problem that the prior art cannot adapt to a new topological structure after load transfer.

The invention discloses a reinforcement learning-based virtual power plant multi-energy cooperative scheduling method and system, and the method comprises the steps: obtaining a real-time operation state index of a virtual power plant, and building a state space; establishing a basic action space based on the energy storage adjustment action, and establishing an electric vehicle action space based on the charging power adjustment action; establishing a reward function based on the response standard reaching reward, the power grid reverse discharge income excitation, the tie line power deviation penalty, the photovoltaic prediction deviation penalty, the electric vehicle charging demand unsatisfied penalty and the energy storage cycle life penalty; establishing a prediction model based on a deep Q network; establishing a strategy model based on an experience playback mechanism; the minimum change rate of a reward function in a virtual power plant response frequency modulation scene and the maximum reward function in a virtual power plant response energy market scene are taken as optimization objectives, a basic action space and an electric vehicle action space are determined to obtain an energy storage power instruction and an EV charging power instruction, and intelligent and real-time generation of a virtual power plant adjustment strategy is realized.

The invention discloses a multi-micro-grid power distribution system two-stage robust collaborative optimization method and device, and belongs to the technical field of multi-micro-grid power distribution system optimization scheduling, and the method comprises the steps: inputting the obtained basic operation data and uncertainty characterization parameters of a multi-micro-grid power distribution system into a pre-constructed multi-micro-grid economic scheduling model, solving the model by adopting a column and constraint generation algorithm to obtain a day-ahead scheduling plan of the multi-microgrid power distribution system in the worst scene considering the space-time correlation; inputting the day-ahead scheduling plan, the obtained basic operation data of the multi-microgrid power distribution system and the tie line power coupling constraint between the power distribution network and the multiple microgrids into a pre-constructed double-layer collaborative optimization model, and solving the model in a distributed manner by adopting an alternating direction multiplier method, an intra-day optimization scheduling scheme meeting the requirement of good cooperative operation of the power distribution network and the multi-micro network friends is obtained; according to the method, the optimization result in the worst scene meets the robustness requirement, and meanwhile, the economical efficiency of the system is guaranteed.

The invention discloses an emergency control method and an emergency control system considering network construction type energy storage power fast regulation, and belongs to the technical field of power systems and automation thereof. Operation information of a tie line is collected in real time, energy storage adjustable capacity is evaluated, when it is detected that the tie line is broken due to a fault, power vacancy is calculated based on an equal-capacity cutting-off principle, and the energy storage power fast regulation is completed. For a power receiving system, network construction type energy storage is preferentially called to carry out power fast adjustment, and load removal is carried out cooperatively when the energy storage capability is insufficient; and for a power delivery system, the new energy unit with the corresponding capacity is directly cut off. Through issuing a power adjusting instruction and an emergency control instruction, energy storage is driven to execute large-step fast adjustment and self-response fine adjustment, and finally fast and stable operation of the isolated network is realized. According to the method, the problem of frequency stability when the high-proportion new energy is connected to the isolated grid for operation is effectively solved, and the toughness and the safe operation level of the high-proportion new energy connected to the grid are remarkably improved.

The invention discloses a probabilistic power supply guarantee capability assessment method considering new energy uncertainty, which comprises the steps of obtaining historical statistical data of new energy in different time periods, constructing a new energy output probability density function based on the historical statistical data, and determining new energy probability density distribution; time sequence production simulation calculation is carried out based on the source network load storage calculation boundary in the target research area, and a conventional unit output curve, a tie line power exchange curve, a pumped storage energy output curve and a demand side response working curve are obtained; based on the conventional unit output curve, the tie line power exchange curve, the pumped storage energy output curve, the demand side response working curve and the load demand curve, constructing a power demand curve which needs to be satisfied by new energy output; and based on the power demand curve and the new energy probability density distribution which need to be satisfied by the new energy output, obtaining the power gap probability and the power shortage expectation of the target time period, and carrying out supply guarantee capability evaluation based on the power gap probability and the power shortage expectation.

The application discloses a kind of energy storage collaborative control method and device for power grid primary frequency modulation and secondary frequency modulation, method includes: the regional equivalent frequency response model of multi-region interconnected power grid is constructed;According to the command of energy storage primary and secondary frequency modulation of regional tie-line exchange power and regional equivalent frequency response model same direction condition is obtained, and based on fuzzy logic and centroid defuzzification obtains energy storage response priority;According to energy storage response priority and command same direction condition distribution primary and secondary frequency modulation power.The method of the application can make full use of the multi-scene output characteristics of energy storage, optimize its output under the premise of meeting the safe operation of power system, and improve the economy.

This invention discloses a calculation process and speed-up method for remote coordinated adjustment of various power electronic devices, including the following steps: 1) acquiring input power system data and establishing physical models of various power electronic devices; 2) calculating a modular local sensitivity matrix based on the physical models of the power electronic devices; 3) calculating the target physical quantity y; 4) obtaining the minimum change Δu of the control parameters of the power electronic devices during the k-th alternating iteration through pseudo-inverse calculation based on the modular local sensitivity matrix and the target physical quantity y. (k) and update the control parameter u (k+1) =u (k) +Δu (k) 4) Determine whether the active power of the tie line and the alternating iterative power flow both satisfy the convergence criterion at the k-th iteration. If so, output the control parameters of the power electronic equipment; otherwise, return to step 2). This invention can reuse the calculation results of the alternating iterative method and directly obtain the local sensitivity calculation, thus improving the solution efficiency of the remote coordinated adjustment strategy.

The invention discloses a method and a device for positioning a low-frequency oscillation source of a wind-thermal bundling system. The method comprises the following steps: acquiring multi-source signals of the wind-thermal bundling system; carrying out adaptive wavelet threshold anti-noise preprocessing; carrying out adaptive noise intensity set empirical mode decomposition; screening a wind-fire coupling key mode; calculating a wind-fire adaptive dissipated energy flow; and oscillation source determination based on phase coupling: constructing a multi-condition fusion determination logic in combination with a phase coupling relationship between a dissipated energy flow trend and a wind-fire key mode and a phase coupling relationship between the dissipated energy flow trend and an electric energy transmission signal so as to realize oscillation source type identification. According to the invention, accurate identification of oscillation sources (a wind power side, a thermal power side and a tie line) in a frequency band of 0.1-2Hz is realized, and both positioning accuracy and engineering real-time performance are considered.

The application discloses a kind of distributed intelligent power grid optimization scheduling method and terminal, for each independent dispatching area of distributed intelligent power grid, with the minimum operating cost of each independent dispatching area as target, establish the local power distribution network optimization scheduling model corresponding to each independent dispatching area, then with the voltage of adjacent independent dispatching area tie line two sides as consistency variable, using local power distribution network optimization scheduling model constructs global distributed intelligent power grid optimization scheduling model, using alternating direction multiplier method to solve standard alternating iteration problem, to obtain the scheduling strategy of distributed intelligent power grid. Therefore each independent region only and adjacent region carry out the interaction of voltage information, can well meet the privacy of source load information and operating information in each independent operation subject, and consider distributed power supply, switchable capacitor, on-load voltage regulating transformer tap and other intelligent power grid regulation measures, can better realize distributed optimization scheduling.

The present application relates to the field of power system and automation, in particular to a multi-level coordination method for cross-provincial reserve sharing considering uncertain channel capacity, the steps are as follows: a dynamic security interval calculation model of cross-provincial tie-line is constructed considering the uncertainty of new energy physical prediction and market behavior, and the dynamic security transmission capacity interval is determined; a cross-provincial reserve coordination transaction optimization model covering the market clearing of grid dispatch cross-provincial reserve and the safety check of provincial dispatch under accident scenario is established respectively, and a cross-provincial reserve coordination optimization model covering the dispatch of national dispatch cross-provincial reserve and the safety check of grid dispatch under accident scenario is established; a multi-level coordination solving model is established based on the alternating direction multiplier method, the two reserve coordination optimization models are solved with the dynamic security transmission capacity interval as the constraint, and the cross-provincial reserve coordination operation scheme is generated. The present application can maximize the release of reserve sharing benefit under the premise of ensuring the safety of power grids at all levels, and improve the system's resilience and economic level.

The application discloses a wind-solar-thermal-storage automatic power generation control method based on closed-loop rolling optimization and belongs to the technical field of new energy grid connection and automatic power generation control. The method collects system frequency deviation, tie-line exchange power deviation and wind power, photovoltaic and thermal power station operation states in real time, establishes a wind-solar-thermal-storage coupling state space prediction model, takes the system frequency deviation and power increment of each power generation unit as a prediction output, takes a control increment as a decision variable, constructs a model prediction control objective function, and solves the control sequence under the constraints of active power balance, output boundary and thermal power unit climbing to realize closed-loop AGC control, improve the collaborative frequency modulation capability and operation stability of the multi-energy complementary system.

The invention discloses a multi-regional power grid reserve planning method and device adopting three-stage decomposition coordination acceleration time sequence production simulation, and relates to the field of power grid reserve planning. Under each planned reserve rate scheme, for each partition, constructing a regional independent optimization model by taking the minimum regional cost as a target, and solving to obtain the total inflow power of the tie line; taking each partition as a node, and obtaining an equivalent node parameter of each partition; constructing a global coordinated optimization model by taking the minimum total load shedding capacity of the system as a target, and solving to obtain the transmission power of the tie line; updating system constraints according to the tie line transmission power; and a regional feedback optimization model is constructed by taking the minimum total cost of the system as a target, the target total cost of the target system of each planning reserve rate scheme is solved under the new constraint, and then the target planning reserve rate scheme is determined. By implementing the method, the problem of long calculation time consumption of an existing centralized optimization method is solved, and high efficiency of large-scale power grid optimization is realized.

This invention provides a method, device, system, and medium for power grid load frequency control based on large-scale multi-agent deep meta-reinforcement learning. It constructs a cooperative load frequency control (CC-LFC) framework by mimicking a squid distributed neural network, modeling each regional controller and power distributor as agents. A large-scale counterfactual multi-agent deep meta-policy gradient (LSCMA-DMPG) algorithm is proposed, integrating centralized training with distributed execution and meta-reinforcement learning to achieve multi-task collaborative learning. Validated using a microgrid model of the four districts of Sansha Island in the Southern Power Grid, this method outperforms existing deep reinforcement learning algorithms and traditional centralized strategies in reducing frequency deviation, suppressing tie-line power fluctuations, and lowering power generation costs, significantly improving the reliability and economy of multi-regional microgrid operation.

The application discloses a main-distribution coordination power grid operation optimization method based on data analysis and belongs to the technical field of power grid operation control. The method collects the bus voltage on each side of a main grid transformer, tie line power, and the output of a distributed power source of a distribution grid, the state of charge of energy storage, and the interruptible capacity of a flexible load, and constructs a boundary power exchange characteristic vector of the main-distribution grid; according to the correlation degree of the characteristic vector and the over-limit risk of each node voltage of the distribution grid, a boundary coupling node set is screened, a virtual power injection equivalent device is arranged at the set, and the support capacity of the main grid to the distribution grid is quantified as an adjustable power interval of the boundary node; the adjustable power interval and the regulation dead zone of each distributed power source in the distribution grid are subjected to intersection operation to generate an initial feasible region of main-distribution coordination regulation and control; and the on-load voltage regulating switch position of the main grid transformer, the capacity of the capacitor bank, and the charging and discharging power of the energy storage of the distribution grid and the flexible load reduction amount are subjected to joint iterative optimization with the feasible region as a constraint, so that the regulation and control reliability is improved.

The present application relates to the technical field of electric power engineering, and discloses a wind power heterogeneous DC networking sending-out topology and a control method and device thereof, comprising: a DC sending-out system is configured for each period of wind farm, wherein the sending end of each period of DC sending-out system is respectively connected to a sending end AC bus, the receiving end of each period of DC sending-out system is respectively connected to a receiving end AC bus, and weak electrical connection is realized between each sending end AC bus through an AC tie line; the first period of DC sending-out system adopts a flexible DC converter topology, and other periods of sending-out system can adopt a contained diode DC sending-out topology. The first period of system provides a power back sending channel and a wind power sending-out channel under a near-zero power scenario for subsequent periods of heterogeneous DC topology. The present application meets the demand of offshore wind power development in pieces, promotes the engineering landing of diode DC lightweight and efficient sending-out technology, solves the operation problems of black start, no wind / weak wind and the like, and reduces the construction cost of wind power DC sending-out system.

The invention relates to a regional integrated energy system online optimization scheduling method based on imitation learning, and the method comprises the steps: obtaining the operation environment of a regional integrated energy system, and extracting the prediction data of a day-ahead load and wind and light according to the operation environment; establishing a day-ahead objective function with economic benefit optimization as a day-ahead constraint condition, making a day-ahead scheduling plan by using the prediction data, and determining a reference tie line power; taking the prediction data as disturbance to generate an intra-day operation scene, establishing an intra-day objective function with the lowest implementation cost of a day-ahead scheduling plan and combining the intra-day objective function with an intra-day constraint condition, making an intra-day scheduling plan by using the intra-day operation scene, and constructing a state-action training set; and training an IL agent approximated by a DNN model based on the state-action training set, predicting an energy storage action through the trained IL agent, and performing single-step MILP to calculate other equipment actions.

The invention provides a line blocking risk quantification method and system based on a tie line probability feasible region, and belongs to the field of power system operation scheduling. According to the method, by considering uncertainty distribution of prediction deviation variables, a construction method of a tie line probability feasible region is provided; constructing an operation point safety margin and blocking probability correction model by using the safety distance and the corresponding probability of the operation point in the probability feasible region; measurement indexes including expected loss and tail risk loss are considered, and more comprehensive line blocking risk quantification is realized. Through a technical route of'probability feasible region construction-safety level measurement-blockage risk quantification ', tie line transmission capability description and line blockage risk measurement under the action of source load prediction deviation uncertainty are realized.

The invention discloses a source-network-load-storage multi-time-scale interactive layered and partitioned optimal scheduling method, which comprises the following steps: S1, an integrated energy system is divided into a plurality of functional partitions according to geographical and operating characteristics, and each partition comprises a local power supply, a flexible load and energy storage; s2, in a day-ahead layer, making a scheduling plan of each partition by taking the minimum operation cost and carbon emission as a target, and constraining the power of a cross-region tie line; s3, in an intra-day layer, performing rolling correction on a day-ahead plan by adopting a dynamic prediction time length, and minimizing deviation of power, an energy storage state and voltage; and S4, in a real-time layer, performing frequency spectrum decomposition on the unbalanced power of each partition, and allocating adjustment resources with different response speeds according to the frequency, thereby realizing rapid power balance. By means of layered time scale optimization, space partition cooperation, spectrum resource matching, dynamic cross-region support and the like, the comprehensive performance of the comprehensive energy system in the aspects of economy, safety, low-carbon performance and flexibility is comprehensively improved.

This invention discloses a three-phase adaptive reclosing method for photovoltaic grid-connected tie lines, comprising: acquiring a tie line with three phases disconnected by a circuit breaker; connecting the tie line to a fast grounding switch and continuously for a preset connection time; briefly applying photovoltaic power to the tie line and then injecting a three-phase fundamental frequency AC signal, continuously for a preset connection time; acquiring the voltage and current values ​​generated on the disconnected line, and determining whether the voltage and current values ​​are less than preset voltage and current setting values, respectively. This method can quickly and reliably determine various faults occurring on the tie line, unaffected by the location of the fault or the magnitude of the transition resistance. Furthermore, when it is determined that there is no fault on the tie line, the tie line can quickly and successfully reclose; when it is determined that there is a fault on the tie line, the tie line can be reliably blocked, successfully preventing the tie line from reclosing to the fault.

The invention discloses a green electricity-green certificate-carbon collaborative transaction system and an implementation method thereof, and belongs to the technical field of electricity market transaction. The system comprises an inter-province / intra-province unified market balancing module, a green certificate market clearing module, a green certificate-carbon linkage deduction module and a data interaction and settlement module. Based on an inter-province / intra-province unified market equilibrium model, inter-province tie line power is incorporated into a unified optimization variable, and a physical network and multi-element market integrated decision is realized; establishing a green certificate market clearing mechanism based on the generalized Nash game, dynamically forming fair green certificate prices, and optimizing environmental value distribution; a green certificate-carbon market linkage deduction mechanism is designed, and linkage connection of green certificates and carbon quotas is achieved; and a transaction closed loop of electric energy, green certificate and carbon quota is completed through joint settlement. According to the method, the inter-provincial market barrier is effectively broken, and the problems that high-proportion new energy transmission end areas are limited in thermal power transmission economy, low in new energy consumption rate, uneven in environmental value distribution and the like are solved.

The invention discloses a multi-time-scale microgrid economic dispatching method based on relative entropy inverse reinforcement learning, and the method comprises the steps: obtaining a day-ahead dispatching plan and a tie line dispatching plan according to a day-ahead prediction information set of a microgrid; superposing disturbance on the day-ahead scheduling plan to carry out dimension expansion, and generating an expert strategy for inverse reinforcement learning; according to the expert strategy, a reward function is constructed by adopting a relative entropy inverse reinforcement learning algorithm, and the reward function is obtained by minimizing the relative entropy of trajectory distribution and solving a corresponding Lagrange duality function; according to the reward function, adopting a depth deterministic strategy gradient algorithm to train an intra-day scheduling agent to obtain a trained intra-day scheduling model; obtaining ultra-short-term prediction information based on the tie line scheduling plan; and inputting the ultra-short-term prediction information into an intra-day scheduling model to obtain an intra-day scheduling strategy.

The application provides a tie line power fluctuation flattening method and system based on an electric vehicle, comprising the following steps: determining a target change value of total output power of a plurality of electric vehicle clusters based on a real-time fluctuation rate of a tie line and real-time power of the tie line; determining a target change value of output power of each electric vehicle cluster based on the target change value of total output power of the plurality of electric vehicle clusters, total capacity of batteries of the electric vehicle cluster and output power of the batteries of the electric vehicle cluster; determining a target value of output power of each electric vehicle in each electric vehicle cluster based on the target change value of output power of each electric vehicle cluster and an SOC state of each electric vehicle; and calculating actual power of the tie line after flattening based on the target value of output power of each electric vehicle in each cluster. The application comprehensively considers information such as a battery state of charge of an electric vehicle and output power of the electric vehicle, optimizes charging and discharging behaviors of users on the basis of guaranteeing demands of the users for energy and travel.

The invention relates to an island separation control method and device, equipment and a medium. The method comprises the steps of obtaining operation data corresponding to a preset load node of a to-be-separated island in a power distribution network; according to the operation data, determining whether the to-be-separated island has an instability risk; setting a control mode of a current converter connected between the to-be-separated island and a main power grid as a constant-voltage and constant-frequency control mode under the condition that the to-be-separated island has an instability risk; in the constant-voltage and constant-frequency control mode, the separation time is determined according to the exchange power data of the interconnection line; wherein the interconnection line is a connection line between the to-be-separated island and the main power grid; and controlling the to-be-separated island to be separated from the main power grid at the separation time. According to the invention, stable switching of the to-be-separated island from the grid-connected state to the island state can be realized.