507 results about "Grid system" patented technology

The invention provides a micro-grid cooperative scheduling method and device, and relates to the technical field of smart grids, and the method comprises the steps: obtaining historical operation data and real-time operation data of a micro-grid system, and data of an external information system; generating load demand and energy equipment output prediction information based on the historical operation data and the data of the external information system; constructing a layered multi-time-scale decision architecture, and performing decision optimization on each layer of agents by adopting a reinforcement learning algorithm; constructing a plurality of heterogeneous agents, and carrying out cooperative scheduling on the plurality of heterogeneous agents by adopting a centralized training and distributed execution multi-agent reinforcement learning algorithm; inputting the prediction information and the real-time operation data into a decision framework, and outputting a real-time control instruction; and setting a security constraint condition, and realizing optimization of the security constraint in combination with a Lyapunov function, a Lagrange multiplier method, a security layer mechanism and a reinforcement learning algorithm. According to the method provided by the invention, the safe, efficient and reliable operation of the micro-grid in the grid-connected / off-grid mode can be realized.

The invention relates to the technical field of micro-grid energy optimization, in particular to a distributed federal reinforcement learning-based hydrogen-containing micro-grid energy scheduling method, which comprises the steps of constructing a multi-region hydrogen-containing micro-grid system model, designing a state space, an action space and a reward function of an intelligent agent, constructing an Actor-Critic network and an experience pool, and completing environment initialization. The intelligent agent inputs the operation state of the equipment into the Actor network, updates the state of the equipment according to the output action, verifies the constraint and outputs a reward value; tuples are extracted from the experience pool to update local network parameters, and the exploration rate is updated regularly; when a federation interaction period is reached, exchanging Critic network parameters and updating federation parameters; and when the training round arrives, outputting an equipment operation plan, deploying the model to the local hydrogen-containing micro-grid in the island mode, and outputting an equipment output value. According to the scheme, strategy sharing and learning collaboration are realized through neighborhood collaboration and local communication among the regional intelligent agents, so that dependence on a central node is avoided.

The invention relates to the field of clean energy, and provides a distributed secondary control method for an island micro-grid system based on event triggering, which comprises the following steps: S1, connecting adjacent distributed units in an island micro-grid through a local communication link, and constructing a distributed control architecture to eliminate dependence on a central controller; s2, triggering communication of the local communication link based on a preset threshold value, and transmitting a secondary control signal when the system state deviation exceeds the threshold value; s3, performing cooperative calculation on the secondary control signal by using the distributed control architecture, adjusting frequency and voltage deviation, and shielding original power data; and S4, connecting a newly added distributed unit to the distributed control architecture through the local communication link, thereby reducing high communication burden and single-point fault of centralized control of the island microgrid.

The invention discloses a multi-microgrid system distributed optimization scheduling method based on an electric power-carbon market, and the method comprises the steps: constructing an energy consumption equipment model and a carbon quota transaction model based on the energy flow and carbon quota transaction process in a microgrid; a dynamic collaborative pricing model is constructed based on the power and carbon quota market supply-demand relationship; constructing an operation cost optimization model of a single micro-grid system based on the above models, and constructing a multi-micro-grid collaborative optimization scheduling problem with the goal of minimizing the total operation cost of all micro-grids based on a Nash bargaining game framework; and solving by adopting an accelerated prediction-correction alternating direction multiplier method algorithm to obtain an optimal scheduling scheme based on power-carbon market coupling, thereby realizing energy operation scheduling of the multi-microgrid. Through power-carbon market coupling, dynamic pricing, game theory optimization and an efficient distributed algorithm, the operation cost of the micro-grid system is reduced, and the reduction of the operation cost assists in improving the operation income of the micro-grid system.

The invention relates to an artificial precipitation enhancement operation area identification method and system based on multi-source data, and relates to the technical field of meteorological intervention operation, and the method comprises the steps: building a multi-resolution dynamic data grid system, and enabling a coarse-grained grid layer to cover the whole operation area, and to be used for bearing the macro data of a satellite cloud picture and a conventional radar; the fineness grid layer is used for receiving and mapping real-time data provided by the high-resolution radar; receiving real-time data of all cloud blocks, mapping the real-time data to corresponding grid layers, and projecting the data collected at different time points to a unified time reference frame to obtain a cloud system state view; predictive interpolation is carried out by using the latest data of the conventional radar and the macroscopic trend of the satellite cloud picture in combination with the motion vector and confidence weighting so as to obtain cloud system information; and forming a visual cloud system three-dimensional view, identifying and tracking a target cloud block with an artificial precipitation enhancement potential, and generating an operation instruction. The method has the effect that the target cloud block with the operation value can be identified and tracked to generate the accurate operation instruction.

The invention provides an indoor navigation and path planning method, device and equipment. Comprising the steps that path planning request parameters are acquired, and the request parameters at least comprise a starting point, an ending point, a time context, a user portrait and a scene template of path planning; generating a runtime snapshot reflecting the traffic state at the current moment in combination with a pre-constructed static grid system, a knowledge graph and a dynamic grid system generated in real time; according to an indoor structure mask and guide identification information in the static grid system, generating a search domain limit of path planning on the runtime snapshot; judging whether the starting point and the ending point are on the same floor; performing path search by adopting a same-layer search strategy or a cross-layer search strategy; and dynamically injecting constraints to the result of the path search and calculating the path cost to generate a path plan. According to the embodiment of the invention, the indoor space can be uniformly expressed, the multi-source dynamic information can be fused in real time, and the path planning scheme can be quickly generated, so that the navigation requirement in a modern complex indoor scene can be met.

The invention discloses a micro-grid system based on a direct current bus and a control method, the micro-grid system comprises the direct current bus, an energy management unit and a plurality of power conversion modules, when the micro-grid system is in an independent adjusting mode, each power conversion module controls the direct current bus to operate according to bus operation parameters of the direct current bus; and when the micro-grid system is in a centralized regulation mode, the energy management unit issues a control instruction to coordinate the output power and / or the input power of each power conversion module. According to the technical scheme, a unified direct current bus framework is constructed, the photovoltaic energy unit, the energy storage energy unit, the commercial power energy unit, the direct current load and other loads are directly connected to the direct current bus, direct current direct supply and direct current direct charging are achieved, the energy link structure is simplified, the power conversion link is reduced, the overall energy efficiency of the system is improved, and the system cost is reduced. And the phenomena of multiple energy conversion and energy loss caused by dependence on an alternating current bus in the prior art are avoided.

The invention discloses a high-order direct-current micro-grid system multi-loss synchronous convergence modeling method based on an improved physical information neural network. The method comprises the steps that S1, a physical information neural network model is initialized; s2, calculating physical loss and updating parameters of the physical information neural network model; s3, reflecting parameters of the physical information neural network model around physical optimization result points; s4, calculating data loss by using the reflected parameters and updating parameters of the physical information neural network model; s5, using the parameters obtained in S2 and S4 to update the parameters of the physical information neural network model through the iterative operation of Douglas-Rachford splitting; and S6, iterating the parameter updating process to solve the physical information neural network model. Different from a traditional physical information neural network which is difficult to converge for high-order system training, the method can realize synchronous convergence of physical loss and data loss in high-order direct-current micro-grid system fitting, and has important significance for mastering an internal operation rule of a direct-current micro-grid system in real time and establishing a physically interpretable data driving model.

The invention discloses a diesel-storage intelligent micro-grid system. A diesel generator charges an energy storage unit or cooperatively supplies power when power supply is insufficient; the battery energy storage unit stores electric energy and supplies power to a load; the micro-grid energy management system dynamically coordinates the output proportion, and a harmonic suppression module suppresses harmonic interference; the load prediction module predicts load power change; the transient response control module deals with transient power impact; the power distribution system is connected to a main power supply and is switched to a diesel generator power supply mode when power supply of the main power supply does not meet requirements; when the diesel generator supplies power, the bidirectional converter converts electric energy into charging current of the energy storage unit and inhibits harmonic interference; when the energy storage unit supplies power, the direct current is converted into the alternating current required by the load. According to the invention, seamless switching of multiple energy sources, active stabilization of power fluctuation, flexible conversion of electric energy forms, optimization of energy distribution efficiency and comprehensive improvement of the survivability of the micro-grid can be realized.

The invention discloses a heterogeneous graph neural network-based microgrid cooperative scheduling prediction and security check method. The method comprises the steps of constructing a heterogeneous graph model; different micro-grid operation scene graphs are generated through analogue simulation; solving an optimal collaborative scheduling strategy vector for each scene graph to serve as an optimal scheduling label, generating a training data set of a'scene graph-optimal scheduling label 'data pair, and completing offline training of the graph neural network model; dynamically generating an instantiated heterogeneous graph; taking the instantiated heterogeneous graph as the input of the trained graph neural network model, carrying out first forward reasoning, and outputting a predicted collaborative scheduling strategy vector; and injecting a virtual fault, generating a virtual fault heterogeneous graph, inputting the virtual fault heterogeneous graph and the predicted cooperative scheduling strategy vector into the trained graph neural network model, carrying out second forward reasoning, predicting the state of the faulty micro-grid system, obtaining the predicted fault node voltage, and carrying out safety check on the predicted cooperative scheduling strategy vector.

The invention belongs to the technical field of load prediction, and discloses an off-grid micro-grid system load prediction method and system based on a neural network. The method comprises the following steps: constructing an equipment fault diagnosis model, an energy scheduling model and a load prediction model by using a neural network algorithm; carrying out data acquisition and preprocessing to obtain preprocessed real-time area monitoring data; performing equipment fault diagnosis by using the equipment fault diagnosis model; if the real-time equipment fault diagnosis result is that a fault exists, entering an energy scheduling step, otherwise, entering a load prediction step; performing energy scheduling by using the energy scheduling model, executing the obtained real-time energy scheduling scheme, and returning to the data acquisition step; and performing load prediction by using the load prediction model. According to the method, the problems of data island, insufficient model generalization ability, limited fault diagnosis precision and efficiency, insufficient energy scheduling strategy optimization and poor load prediction precision and robustness in the prior art are solved.

The invention provides an off-grid synthetic ammonia park electrolytic bath column level-energy storage-hydrogen storage collaborative optimization method based on rolling optimization, and relates to the technical field of energy storage and hydrogen storage collaboration. The method comprises the following steps: constructing an off-grid system architecture comprising wind-solar power generation, a plurality of rows of electrolytic cells, energy and hydrogen storage equipment and a synthesis ammonia device; a multi-device collaborative optimization strategy based on an eight-hour rolling time domain is designed, the system operation state is divided into high, medium and low working conditions through a working condition recognition mechanism, a current device operation scheme is actively adjusted according to wind and light power information of a next scheduling period, and collaborative regulation and control of energy storage and hydrogen storage are achieved. Compared with a traditional scheduling strategy, the collaborative optimization strategy provided by the invention improves the consumption rate of renewable energy sources of the system, reduces abandoned wind and light, improves the yield of synthetic ammonia, and verifies the effectiveness of the strategy.

The invention discloses a micro-grid optimization scheduling method based on an improved Loueer fox algorithm, relates to the technical field of micro-grid operation, and realizes collaborative optimization scheduling of a distributed power supply, an energy storage device, a load and the like in a micro-grid system by simulating various perception and behavior strategies of the Loueer fox. Aiming at the demand of distributed power supply system micro-grid optimization scheduling, the micro-grid system operation economy is taken as a main target, a function corresponding to a micro-power supply scheduling scheme is constructed, improvement is carried out based on an RFO algorithm, and a quantum fractal annealing disturbance strategy, a hyperbolic tangent self-adaptive olfactory disturbance strategy and a Riemannian metric accumulation disturbance strategy are introduced, so that the optimal scheduling of the micro-power supply system is realized. Through the fusion of the triple innovation strategies, the defects of poor population diversity, easy premature convergence, insufficient balance capability, low precision and the like when the original RFO algorithm and the traditional intelligent algorithm are used for solving the complex optimization problem are solved, and the efficient solution of the micro-grid optimization scheduling scheme is realized.

An inertia cooperative control method of an integrated optical storage alternating current and direct current hybrid micro-grid comprises the steps that firstly, according to static and dynamic power capacities of energy storage units in direct current sub-grids and allowed direct current voltage deviation, sub-grid equivalent virtual resistance and virtual capacitance are calculated; secondly, RC + R type parallel virtual impedance parameters are distributed according to the power proportion of each energy storage unit, and multi-energy-storage cooperative response power disturbance according to the capacity is achieved; then, a phase angle is generated based on the mapping relation between direct-current side voltage and frequency, an alternating-current voltage amplitude instruction is determined in combination with reactive power droop control and feeder impedance voltage drop compensation, and a dq-axis voltage instruction is generated through virtual impedance compensation; normalized three-phase modulation waves are obtained through voltage-current double closed-loop control and dq / abc coordinate transformation, and six paths of PWM signals are generated to drive an interconnection converter after the normalized three-phase modulation waves are compared with triangular carrier waves. The method does not need to depend on external communication, has the capabilities of autonomous inertia support, voltage and frequency coordinated regulation and reasonable multi-source power distribution, and improves the stability and dynamic response performance of the system under island operation.

The invention discloses a method, a system, equipment and a medium for evaluating stable operation capability of an isolated network of a regional power grid. The method comprises the following steps: acquiring related data of an isolated network system; based on related data of the isolated network system, initial equivalent inertia and initial power deviation are obtained through calculation; based on the frequency deviation value of the isolated network system, operating equipment of the isolated network system is adjusted, and equivalent inertia and power deviation are calculated and updated; calculating a disturbance frequency change rate according to the equivalent inertia and the power deviation; and judging a corresponding relation between the power deviation and the disturbance frequency change rate, and obtaining an evaluation result of the stable operation capability of the isolated network system. According to the isolated network stability quantitative evaluation method constructed based on the frequency change rate, only two core parameters of the system inertia and the new energy proportion are needed, complex modeling and time-consuming simulation are not needed, and the evaluation efficiency is improved through a dynamic parameter updating mechanism of high-frequency generator tripping and low-frequency load shedding in combination with a simplified frequency response model; whether the isolated network is endangered to collapse is determined in real time, and an emergency control decision basis is provided for power grid personnel.

The invention discloses an optical storage and charging integrated micro-grid system, relates to the technical field of optical storage and charging integration, and aims to solve the problem that the storage and charging effect of optical energy is unstable and unsafe. Different control instructions are generated according to different scenes, various conditions in the operation process of the micro-grid can be comprehensively covered, fine management and control of the micro-grid are achieved, a corresponding load distribution strategy is formulated, the system can be flexibly adjusted according to actual conditions, the electric energy utilization efficiency and the stability of the system are improved, and the system is suitable for popularization and application. When the photovoltaic power generation power is insufficient, energy storage discharging and photovoltaic electric energy combined power supply are started, reasonable storage and flexible allocation of electric energy are achieved, the power supply reliability and flexibility of the system are enhanced, an electric energy dynamic scheduling strategy comprises four scenes of charging, discharging, balance and safety, flexible switching can be achieved according to the actual operation condition, and the power supply efficiency is improved. The method adapts to operation requirements of the micro-grid under different working conditions, and has relatively high flexibility and adaptability.

The invention discloses a forest fire carbon emission and carbon sequestration collaborative quantification method and system, and the method comprises the steps: obtaining forest multi-dimensional data including fire point data, and constructing a multi-scale collaborative database; constructing a carbon source-carbon sink dynamic coupling model according to the multi-scale collaborative database; obtaining a forest multi-remote sensing index collaborative weight, and correcting the carbon source-carbon sink dynamic coupling model; and generating a forest spatialization decision map based on the multi-scale collaborative database and the carbon source-carbon sink dynamic coupling model. According to the technical scheme provided by the invention, by fusing forest multi-scale data, a nationwide unified grid system is constructed, and accurate quantification of large-scale forest fire carbon emission and carbon sequestration is realized; a carbon source-carbon sink dynamic coupling model is provided, and cooperative diagnosis of multiple remote sensing indexes is combined, so that the monitoring precision of the fire influence is remarkably improved; and finally, a spatial decision map of forest carbon emission and carbon sequestration is generated, carbon sink protection area delimitation is supported, and a scientific basis is provided for policy formulators.

The invention belongs to the technical field of multi-energy micro-grid system optimization scheduling, and particularly relates to a multi-energy micro-grid distribution robust low-carbon economic scheduling method based on deep learning, electronic equipment and a medium. According to the method, a mathematical model of a multi-energy micro-grid system is established according to coupling characteristics of various energy sources among power systems. In order to improve the economical efficiency and the low-carbon property of the system, a load demand response mechanism and a carbon transaction mechanism are adopted, and an electric heating load demand response model and a reward and punishment type stepped carbon transaction model are constructed. In order to solve the wind and light uncertainty of the integrated energy system and improve the robustness of the system, a scene set of uncertain variables is generated by using a conditional generative adversarial network in deep learning, and the generated scenes are clustered by using a K-means clustering method to obtain typical scenes. In order to obtain more real probability distribution, a fluctuation range of a typical scene is constrained by using a comprehensive norm, and a probability distribution fuzzy set of uncertain variables is obtained. And based on the constructed fuzzy set, the demand response model and the reward and punishment type stepped carbon transaction model, a two-stage distribution robust low-carbon economic optimization model of the multi-energy microgrid is established, in the first stage, an energy storage equipment start-stop plan of the system is determined, and in the second stage, an initial plan is adjusted and supplemented after uncertainties are revealed. And finally, carrying out iterative solution on the established model by utilizing a column and constraint generation method to obtain an optimal scheduling scheme, thereby ensuring the low-carbon property, the economical efficiency and the robustness of the system.

The invention discloses an artificial intelligence-based agricultural waste carbon emission reduction scenario simulation method and system, and the method comprises the steps: obtaining multi-source geographic space data of a target region, uniformly fusing the multi-source geographic space data into a grid system with a preset resolution, and carrying out the calculation of the multi-source geographic space data based on a space weighted distribution model, the statistical yield of provincial agricultural products is distributed to each grid of a grid system, and the theoretical resource quantity and the high-precision spatial distribution diagram of the agricultural wastes are obtained in combination with a grass-grain ratio database. Method for determining carbon emission and carbon sink quantitative parameters of agricultural wastes under various utilization paths through dynamic accounting model, simulating carbon emission reduction potential and spatial distribution under different resource utilization scenes based on artificial intelligence model according to carbon emission and carbon sink quantitative parameters of agricultural wastes under various utilization paths, and planting front-end crops and structure and space layout is optimized. A quantifiable and visual scientific decision-making tool is provided for regional low-carbon agricultural planning, and the accuracy and feasibility of an emission reduction strategy are remarkably improved.

The invention provides a power cooperative control method, device and system based on load removal and a medium. The method is applied to a micro-grid configuration flexible interconnection device for micro-grid fault protection. After the fault is positioned, a VSG low-voltage ride-through strategy is adopted to carry out current limiting, an importance quantification model is constructed for loads, and according to a real-time operation condition, a shearable load with the minimum influence on the system is screened to carry out priority removal; and dynamic power transmission adjustment of the flexible interconnection device is synchronously triggered, a micro-grid power flow path is reconstructed, and finally a fault is removed based on a current limiting and directional element protection method. According to the invention, system protection is realized by fusing intelligent load removal and flexible power adjustment, and the fault isolation speed and the stability of the microgrid system are effectively improved.

The invention discloses a coastal zone planning method and system based on MaXent and hotspot analysis, and relates to the technical field of coastal zone planning. Comprising the following steps: S1, collecting environment variable data, species distribution data and development intensity data, constructing a unified space-time grid system, and realizing time sequence expression of the data through data preprocessing; s2, constructing a quarterly time sequence maximum entropy model, and performing time sequence evaluation on each grid habitat state to form a habitat evolution type; s3, identifying time sequence significant hot spots and hot spot persistence and intensity features, constructing ecological development relationship comprehensive representation, and identifying ecological development conflict types; and S4, spatially superposing the habitat evolution type and the ecological development conflict type to form a self-adaptive access rule, and generating differentiated planning suggestions according to regions. The problem that planning lacks dynamic adaptability due to the fact that coastal zone habitat suitability and development intensity depend on static time point data for a long time and a time sequence evolution rule cannot be recognized is solved.

The invention discloses an island micro-grid distributed cooperative control method based on local information and a storage medium, and belongs to the technical field of micro-grids, and an island micro-grid system comprises a converter of network construction type control and network following type control. And according to local information, the network tracking type control adopts a maximum power point tracking point tracking (MPPT) algorithm to control power output. The reactive power of the network construction type control parallel converter is output and distributed according to the fixed voltage regulation droop coefficient; and the active power of the network construction type control parallel converter is output and distributed according to the frequency modulation droop coefficient adaptively updated based on local information. According to the method, power instruction distribution of island micro-grid and network type control and network construction type control is generated by local information, instruction distribution of upper-layer centralized control does not need to be carried out, plug and play, flexible reconfiguration and decentralized control of an island micro-grid inverter can be realized, and the method has relatively good practicability.

The invention relates to the technical field of micro-grids, and discloses a control method of a distributed power supply in a plant micro-grid, and the method comprises the steps: S1, constructing a multi-source collaborative micro-grid system; s2, executing real-time power dynamic allocation; s3, working condition power balance control; s4, active regulation of bidirectional power flow and the like. Based on a real-time AGC instruction and plant load data, a hierarchical coordination mechanism is adopted, charging and discharging power is dynamically adjusted by means of stored energy to track the AGC instruction, and constant power output of wind power is maintained in combination with a wind power prediction model; when a thermal power generating unit is subjected to deep peak regulation, shutdown or fault, the system absorbs excess wind power through energy storage charging, synergistically improves the hydrogen production load power, guarantees dynamic matching of the load and power generation, and actively adjusts energy storage charging and discharging and hydrogen production loads by monitoring the power flow directions of a thermal power generating unit section and a desulfurization section in real time according to voltage fluctuation caused by bidirectional power flow. And the voltage deviation is dynamically compensated, and the system voltage stability is greatly improved.

The invention relates to an off-grid photovoltaic air conditioner self-adaptive control system and method based on rolling self-learning, and aims to solve the problems of low power supply reliability, large battery loss, inflexible temperature control, weak adaptability and the like caused by poor matching between an existing off-grid photovoltaic system and an air conditioner load. The method mainly comprises the steps that parameters are collected in real time, loads are calculated, and air conditioning unit operation frequency bands of the off-grid system are dynamically divided based on the temperature difference; constructing a multi-target model for guaranteeing power supply, prolonging the service life of the battery and optimizing the thermal comfort of the off-grid system, and adaptively adjusting the target by utilizing a dynamic weight coefficient; the optimal sequence is solved through rolling time window optimization, and the off-grid regulation and control strategy is adjusted in real time in combination with temperature gradient feedback. According to the method, the energy dynamic matching efficiency in the off-grid supply and demand system can be improved, power supply is guaranteed, fine adjustment of temperature control is achieved, harmful charging and discharging are limited based on state optimization, loss is reduced, the service life is prolonged, and compared with a traditional regulation and control strategy, the method has remarkable advantages in reliability, comfort and economical efficiency.

The invention discloses an unmanned aerial vehicle path planning navigation method and system based on a layer-by-layer grid map, and the method comprises the steps: S1, constructing a rasterized navigation map, and marking flight avoidance factor data affecting the flight of an unmanned aerial vehicle on the rasterized navigation map; s2, task targets from the flight starting point to the flight ending point of the unmanned aerial vehicle are set in the rasterized navigation map, m layers of sub-grid systems are constructed step by step according to the upper layer and the lower layer in the rasterized navigation map, and the front m-1 layers of sub-grid systems sequentially execute grid route chain search of the accumulated heuristic task targets of the front layer and the rear layer and output route chains; and S3, performing optimal path search and optimization by using the path chain to obtain a fine planning path of the unmanned aerial vehicle. According to the method, search guidance of front and rear layer accumulated heuristic task targets is realized, and a refined route chain is obtained through rapid search of a multi-layer sub-grid system, so that the search calculation amount and complexity are reduced, the flight path planning efficiency of the unmanned aerial vehicle is improved, and the safe navigation capability and planning decision-making capability of the unmanned aerial vehicle are improved.

The invention discloses a new energy micro-grid distributed rolling collaborative optimization control method and related equipment, and the method comprises the steps: building a centralized rolling optimization model of a new energy micro-grid system in each rolling optimization period based on a predetermined optimization target and system constraints; wherein the preset optimization target comprises port voltage deviation minimization of the micro-grid node, operation degradation cost minimization of an energy storage device in the micro-grid node, and light abandoning rate minimization of a photovoltaic unit in the micro-grid node; the system constraints comprise a power flow balance constraint and a droop control constraint of each micro-grid node, and a charge state constraint of an energy storage device; the centralized rolling optimization model is decoupled into distributed sub-problems corresponding to the micro-grid nodes; and a distributed alternating direction multiplier method is adopted, information interaction is carried out through each micro-grid node and adjacent nodes, and each distributed sub-problem is solved in parallel, so that an optimal control strategy of all micro-grid nodes in the next control period is obtained. The method does not need to build a complex and high-cost communication network to transmit a large amount of data, reduces the dependence on a complex communication platform and line, improves the control reliability, and avoids the control failure of the whole micro-grid when a communication system breaks down. Meanwhile, the calculation burden in a large-scale network is relieved, and the control response speed is increased.

The invention discloses a forest carbon flux statistical method and system under the influence of a wildfire, and the method comprises the steps: obtaining forest multi-dimensional data including fire point data, and constructing a multi-scale collaborative database; constructing a carbon source-carbon sink dynamic coupling model according to the multi-scale collaborative database; obtaining a forest multi-dimensional remote sensing index, and constructing a correlation matrix; correcting the carbon source-carbon sink dynamic coupling model according to the correlation matrix; and generating a forest spatialization decision map based on the multi-scale collaborative database and the carbon source-carbon sink dynamic coupling model. According to the technical scheme provided by the invention, by fusing forest multi-scale data, a nationwide unified grid system is constructed, and large-scale forest fire carbon flux statistics and accurate quantification are realized; a carbon source-carbon sink dynamic coupling model is constructed, a forest multi-dimensional remote sensing index is used for correction, and the monitoring precision of the fire influence is remarkably improved; and the emission factors are dynamically calibrated, so that the inter-region difference is reduced, and the universality of the method is enhanced.

The invention provides a multi-microgrid energy collaborative optimization method and system. The method comprises the following steps: S1, establishing an energy collaborative network topology structure comprising a plurality of microgrid nodes; s2, constructing an energy balance model based on the real-time power demand, the new energy output prediction and the power grid dispatching instruction; s3, taking the minimization of the total operation cost of the multi-microgrid system as a target to form an optimization function; s4, an improved whale optimization algorithm is adopted to solve the optimization function, and an energy scheduling scheme of each microgrid in each time period is obtained; s5, regulating and controlling an energy storage device, a charging pile and an adjustable load in each micro-grid according to the energy scheduling scheme, and coordinating the energy flow direction and the transmission power between the micro-grids; and S6, monitoring the actual operation state and the energy interaction effect of each micro-grid, and when it is detected that the predicted deviation exceeds a preset threshold value, re-executing the steps S2 to S5 based on the real-time data. According to the invention, energy collaboration among multiple microgrids can be realized, the new energy consumption capability is improved, the operation cost is reduced, and the economy and stability of power grid operation are enhanced.

The invention provides a micro-grid system supply and demand balance and green energy scheduling optimization method and system, which can accurately match the user side power demand and green energy production, and can call an energy storage system to release stored electric energy or buy electricity through a main power grid to complement power vacancy when there is a supply and demand electric quantity difference in a power generation trough and a power consumption peak period; in the peak period of solar power generation, photovoltaic electric energy is preferentially used for meeting the load requirement, when the total power generation amount is larger than the total power consumption amount, redundant power can be used for charging an energy storage device, efficient consumption of renewable energy sources is achieved, meanwhile, the stable and continuous characteristics of wind power generation are utilized, basic power is provided for loads in the whole time period day and night, and energy is saved. And in the solar valley stage and the load valley stage, the energy storage system is matched to carry out charging and discharging scheduling and stabilize power fluctuation, challenges caused by load peak-valley difference and renewable energy intermittency can be effectively handled through multi-energy cooperative control logic, and the reliability, economical efficiency and clean energy permeability of micro-grid operation are improved.

The invention relates to a territorial space purpose control data processing method based on a space-time knowledge graph. The method comprises the steps that map entities and semantic relations between the map entities are configured in a mode layer, and the categories of the map entities comprise space-time entities used for representing space-time slice states and event entities used for representing human activities generating actual or potential influences on land states; establishing a grid system comprising a plurality of grids based on Geohash coding, associating administrative division and multi-source heterogeneous data with the grid system respectively, and constructing a grid layer; extracting territorial space purpose control data, carrying out entity and entity relationship initialization according to the mode layer and the grid layer, and constructing a graph layer; and establishing an application layer based on the map layer and the grid layer. Compared with the prior art, the method can support reasoning and prediction of geographic phenomena, introduces multi-dimensional information features, and effectively supports business application.