227 results about "Electrical distance" patented technology

The invention relates to the technical field of electrical equipment fault diagnosis, in particular to an intelligent fault diagnosis method and system for electrical equipment, and the method comprises the steps: constructing a multi-dimensional tensor model, uniformly fusing the equipment state information, electrical distance weighted connection and phase dynamic coupling relation, and extracting an abnormal propagation mode through high-order singular value decomposition; designing a space-time-frequency coupling interference stripping mechanism, and combining structure guide disturbance deconstruction, multi-scale dictionary learning and sparse low-rank decomposition to accurately separate transmissible and non-transmissible interferences; reconstructing a fault trajectory based on a generative adversarial mechanism, coupling a graph structure dynamic encoder, a topology consistency discriminator and a time controllable generator, and restoring a real propagation path; and finally, tensor semantic compression, a three-view graph neural network and fault label back projection interpretation are integrated through a multi-source semantic fusion mechanism. According to the method, cross-space-time and cross-structure fault diagnosis and traceability are realized, and the accuracy and interpretability are improved.

The invention provides a power system voltage control method and device based on dynamic steady state collaborative correction, and the method comprises the steps: building an electromagnetic transient model for a preset voltage node in electromagnetic transient simulation software PSCAD, simplifying a power grid with the electrical distance to a target region exceeding a preset distance into a dynamic Thevenin equivalent model, initializing load flow calculation in the BPA to obtain a dynamic-steady state hybrid model; updating dynamic Thevenin equivalent parameters of the power system in real time according to the data of the phasor measurement unit of the power system, and synchronizing the dynamic Thevenin equivalent parameters to the BPA; based on the dynamic-steady state hybrid model, the transient overvoltage of the power system is suppressed within the time shorter than the first preset duration, and the steady state voltage of the power system is optimized within the time shorter than the second preset duration in combination with wide-area coordination control, so that the parameter bidirectional correction of the dynamic and steady state models is realized, and the head end voltage prediction error is reduced. And the voltage control robustness is improved.

The invention relates to a power distribution network voltage partition control method and system based on a hierarchical K-means clustering algorithm, and belongs to the technical field of power distribution system voltage partition optimization. According to the technical scheme, power distribution network node parameters are collected in a self-adaptive partition mode, a node sensitivity coefficient and an eigenvector of an electrical distance are constructed, and then a K-means algorithm is used for fine region division; selecting a dominant node: solving a Jacobi matrix through load flow calculation, extracting a voltage sensitivity coefficient, and selecting a node with the maximum sensitivity as a dominant node in each partition; multi-objective optimization: constructing an optimization model with minimum network loss, minimum voltage deviation and highest voltage stability as objectives; and partition cooperative control: accessing wind power and photovoltaic power to the dominant node, adjusting reactive power output in real time according to an optimization result, and realizing partition autonomy and global cooperation. According to the invention, voltage fluctuation and out-of-limit are inhibited, system network loss is reduced, control efficiency and economy are improved, and the method is suitable for complex topology and high permeability scenes.

The invention provides a voltage control strategy modeling and voltage online regulation and control method and system for a power distribution network, and is applied to the technical field of power distribution network regulation and control. The method comprises the steps that region division is carried out on the power distribution network based on the electrical distance between nodes of the power distribution network, multiple regions are obtained, and one region corresponds to one virtual power plant; determining the regional electricity price of each region based on the marginal pricing of the distribution region; taking each region as an object of energy transaction with the power transmission network, and constructing an optimization model by taking profit maximization of each region as a target on the basis of considering the safety of circuit elements in each region; performing optimization strategy modeling on the optimization model based on an observable Markov decision process to obtain an optimization strategy model; and training an optimization strategy model based on the regional electricity price of each region and a maximum entropy reinforcement learning algorithm. The method solves the problem that the complexity of the power distribution network affects the optimality and efficiency of the collaborative optimization problem of a plurality of virtual power plants in the power distribution network.

The invention relates to the technical field of new energy consumption, in particular to a method and equipment for calculating new energy consumption capacity of a regional power grid. Comprising the following steps: processing power grid node data and environmental influence factors through a graph neural network to obtain an electrical distance dynamic index; determining transmission capacity limitation and load distribution according to the index, obtaining a preliminary consumption capacity boundary, and adjusting the boundary based on environmental factors to obtain an optimized consumption capacity boundary; calculating supply and demand matching deviation by combining current actual supply and demand data of the power grid, and formulating a real-time adjustment scheme by fusing historical data and grid connection requirements; power flow calculation and stability evaluation are integrated through a real-time adjustment scheme, and finally an optimized consumption capacity boundary is obtained; and judging the stability of the power grid based on the final consumption capacity boundary, and determining an optimal power distribution path of the power grid in combination with a supply-demand matching model. According to the invention, the new energy consumption capability and the equipment stability of the power grid can be effectively improved, and the method adapts to variable environmental conditions.

The invention is applicable to the field of power demand analysis, and provides a user demand-oriented power transaction matching recommendation method and system. The method comprises the following steps of: acquiring power consumption data of a user, and generating a resonance group and a feature packet with similar power consumption modes and risk tolerance; generating a power utilization comprehensive bidding plan in combination with the resonance group characteristics and the real-time market data; performing transaction matching based on the bidding plan, preferentially selecting the power generation resource with the closest electrical distance, introducing a green energy premium coefficient, and outputting a transaction result; and performing investment portfolio optimization analysis according to a transaction result, and generating a customized power package containing traditional energy, new energy and stored energy in combination with user risk preference. Through multi-dimensional data integration and intelligent algorithm application, accurate matching of power generation resources and user demands is realized, power transaction efficiency and user satisfaction are improved, and new energy consumption and sustainable development of the power market are promoted.

The invention discloses a distributed photovoltaic optimization coordination control system and method, and relates to the technical field of distributed photovoltaic power generation, and the control system comprises a multi-dimensional data collection module, a self-adaptive cluster division module, a robust dominant node election module, a three-dimensional voltage state evaluation module, and a hierarchical coordination control execution module. According to the distributed photovoltaic optimization coordination control system and method, real-time operation data, meteorological prediction data and power grid load prediction data of each node are continuously monitored, comprehensive information support is provided for a control strategy, and when it is detected that voltage abnormity is caused by sudden change of illumination intensity in a certain area, the real-time operation data of each node, meteorological prediction data and power grid load prediction data are monitored. And immediately finishing cluster structure adjustment in an extremely short time by adopting a fuzzy clustering algorithm with constraint conditions based on the electrical distance and the voltage fluctuation trend characteristic value, and ensuring that the node voltage change characteristics in the same cluster are highly consistent.

The invention discloses a distribution network multi-source roof photovoltaic cluster collaborative aggregation regulation and control method, and belongs to the technical field of distribution network large-scale roof photovoltaic aggregation upgrading consumption, and the method comprises the following steps: collecting a power distribution network topological structure and line impedance parameters in real time, calculating the electrical distance modularity between nodes, and calculating the electrical distance modularity between the nodes; taking the reactive voltage sensitivity as a clustering core index, dividing the power distribution network into a plurality of photovoltaic clusters, selecting a node with the highest comprehensive sensitivity as a dominant node for each cluster, and establishing an inter-cluster reactive voltage sensitivity relation matrix; multi-stage collaborative optimization regulation and control are carried out, day-ahead, intra-day and real-time three-stage optimization models are constructed, and a cluster-stage optimization model is established by taking the minimum voltage deviation as a target; and carrying out multi-agent cooperative voltage regulation and strategy verification and updating. According to the method, the power grid topology is collected, node impedance is calculated, clustering is carried out through reactive sensitivity, a target function is solved through day-ahead optimization, intra-day voltage out-of-limit correction is carried out, margins are distributed in real time, and the technical problem of slow voltage regulation response is solved.

The invention discloses a power distribution network cluster local control method and device, equipment and a medium. The method adopts a cloud edge end three-level collaborative architecture, and comprises the following steps: acquiring electrical parameters through a terminal equipment layer; constructing a graph model based on an electrical distance at the edge calculation layer; performing initial cluster division and issuing on the cloud computing layer; dynamically optimizing cluster division in an edge calculation layer through a lightweight deep reinforcement learning model; local control strategies such as voltage reactive power cooperative control, frequency active power balance control and fault rapid isolation and self-healing are executed based on the final division. The system comprises a terminal device layer, an edge computing layer and a cloud computing layer. According to the method, decoupling of global optimization and local real-time control is realized through cloud-side cooperation, the problems of high data processing pressure, high communication delay, expanded local fault influence range and the like of centralized control are effectively solved, and the real-time performance, reliability and disaster resistance of the power distribution network are remarkably improved.

The invention discloses a DC power distribution scene division method and system based on improved K-means, and the method comprises the steps: obtaining the output demands, reactive power regulation capacities and active power regulation capacities of power supply nodes in all time periods, and calculating an operation similarity index between every two power supply nodes; calculating an electrical distance between every two power supply nodes in each time period based on the sensitivity matrix; correcting the operation similarity index by using the electrical distance to obtain the weight of the connection edge of every two power supply nodes in each time period; adopting a modularity method, and establishing a reference measurement index in each time period by utilizing the weight of each connecting edge and the clustering mark variable; in each time period, each power supply node is clustered, and when the maximum difference value between the clustered measurement index and the reference measurement index is less than zero, each cluster center obtained by clustering is used as a core power supply node of each time period, each type of nodes and the core power supply node are clustered, and each DC power distribution and utilization system scene is obtained; and a more accurate and comprehensive scene division effect is realized.

The invention discloses a regional power distribution method and system for distributed new energy consumption, and relates to the technical field of power systems, and the method comprises the steps: obtaining regional power distribution network data, and constructing a power distribution network analysis model; based on the power distribution network analysis model, dividing the regional power distribution network into a plurality of energy autonomous units by calculating the electrical distance and the power sensitivity; calculating an energy complementation index and a load elastic coefficient of each energy autonomous unit, and constructing a unit feature model; dynamically adjusting the active power and reactive power output of the distributed new energy in each energy autonomous unit according to the unit characteristic model; and monitoring the operation state of the energy autonomous units, implementing a cooperative control strategy, and adjusting power exchange between the energy autonomous units. According to the energy autonomous unit division method provided by the invention, the tightly coupled node group can be accurately identified, the nearby consumption and efficient utilization of new energy are realized, and the power transmission and distribution loss is reduced.

The invention relates to the technical field of block chains, and discloses an intelligent power distribution method and system for realizing power supply equipment based on a block chain, and the method comprises the steps: constructing a block chain network of the power supply equipment, analyzing a dynamic mapping relation between input data and output data, and determining a discrete nonlinear function of the input data and the output data; determining a target function required by the power supply equipment, determining power distribution control parameters of the power supply equipment, and integrating a data driving control model of the power supply equipment; calculating an electrical distance between blockchain nodes, and dividing the blockchain network into a plurality of power distribution control areas; determining an area dynamic control mechanism of the multiple power distribution control areas, and determining a coordination control algorithm of the multiple power distribution control areas; and integrating the data driving control model, the regional dynamic control mechanism and the coordination control algorithm into a power distribution control module of the power supply equipment, and executing intelligent power distribution of the power supply equipment. The power distribution efficiency and stability of intelligent power distribution of the power supply equipment can be improved.

The invention relates to the technical field of electric power, and particularly discloses a power distribution branch box monitoring system and method based on a fault indicator, which can compensate for short-time limitation of real-time data by performing compensation and correction through historical load data and operation instruction information, so that a dynamic topological structure diagram at a first moment is more fit with an actual power grid operation state, and the power distribution branch box monitoring accuracy is improved. It is guaranteed that the topological structure of the dynamic topological structure diagram is dynamically updated along with changes of a power grid, the corrected dynamic topological structure diagram can accurately reflect the real connection relation and the electrical distance of the branch box, the quantization result of the branch correlation degree matrix is made to be more suitable for the correlation degree of the actual power grid, and therefore the reliability of the branch correlation degree matrix is improved through dynamic construction logic of the dynamic topological structure diagram. The method can adapt to the dynamic change process of the topological graph of the power distribution network, achieves the effect of dynamically monitoring the fault of the power distribution branch box, and achieves the purpose of reducing the false alarm rate.

The invention provides a Prony algorithm-based cable segment wave velocity acquisition method, device and system, and a medium, and the method comprises the steps: testing a to-be-tested cable, and obtaining a cable signal transfer function; on the basis of the cable signal transfer function, in combination with cable joint distribution, constructing a cable signal approximation function based on a Prony method; constructing a linear prediction model of the cable signal based on the cable signal approximation function; performing denoising processing on the linear prediction model based on a singular value decomposition method to obtain a denoised linear prediction model; solving the denoised linear prediction model to obtain an attenuation coefficient; and calculating the segmented wave velocity of the cable based on the attenuation coefficient. According to the method, the Prony estimation method is combined with the singular value decomposition noise reduction algorithm, high-precision extraction of attenuation constants and segmented wave velocity decoupling are achieved, and then the electrical distance positioning precision is improved.

The invention relates to the technical field of smart power grids, and provides a low-voltage power distribution network transparent fusion perception visual scene construction method and system, and the method comprises the steps: synchronously collecting voltage, current and equipment state data through power line carrier communication, a smart electric meter and a power distribution terminal, and building an annular queue with aligned time marks; a tree topology structure is constructed based on three-phase attributes, a connection matrix is generated, users are divided into visualization hierarchies with different transparencies through electrical distance calculation, and gradient coloring and special effect warning of an overload line are achieved in combination with current saturation mapping. The physical position and the electrical parameters are fused through polar coordinate system conversion, and a dynamic particle flow is generated to visually display current distribution; when the voltage sags, a voltage distortion propagation path is analyzed through waveform similarity backtracking, a disturbance source is positioned, and a pulse diffusion animation is triggered. Transparent fusion sensing of the running state of the low-voltage power distribution network, real-time early warning of line overload and second-level positioning of a disturbance source are achieved, and the intelligent operation and maintenance efficiency is improved.

The invention belongs to the technical field of distributed photovoltaic power prediction and power distribution network operation, and discloses a distributed photovoltaic power ultra-short-term prediction method based on multi-source data fusion. The method comprises the following steps: collecting and aligning historical power and electric parameters of a photovoltaic station, meteorological monitoring, short-term and imminent forecasting, voltage of a power distribution network, power flow and states of a voltage regulating device under a unified time dimension; based on a photovoltaic output mechanism model and a linearized power flow sensitivity model or an equivalent electrical distance model, constructing a power constraint interval and a baseline power track which meet voltage and line thermal stability constraints; and through residual normalization, weighted adjacent matrix and space-time recursion prediction model modeling and prediction of a multi-station residual field, parameter increment is updated in combination with a data quality index and an error threshold, and distributed photovoltaic cluster ultra-short-term power prediction giving consideration to power distribution network security constraints and data quality is realized.

The invention provides a power distribution network partitioning method and device, equipment and a storage medium. The method comprises the steps that firstly, a node voltage-reactive power sensitivity matrix and historical operation data of a distributed power supply are obtained, the structural distance between nodes is calculated, the historical data are normalized, the attribute similarity is obtained in combination with an attribute weight matrix, and the two are added to generate an electrical distance. Resolution parameters are dynamically adjusted according to reverse power flow intensity, and the parameters are increased when the power flow is enhanced to refine clusters. According to the method, the limitation that traditional partition depends on geographical proximity or simple parameters is broken through, accurate partition is achieved by quantifying electrical coupling and resource characteristics, the problem of poor connection in the cluster is solved, the on-site consumption capacity of new energy is effectively improved, the transmission pressure of a main network is reduced, and the method is suitable for large-scale popularization and application. And meanwhile, the fault recovery capability and the calculation efficiency of the power grid are enhanced, and the method is suitable for district power balance optimization in a high-permeability distributed power supply access scene.

The invention discloses a power distribution network branch line fault line load transfer method and system, and relates to the technical field of load transfer, and the method comprises the steps: collecting the voltage and current data of a power distribution network in real time, locating a branch line fault point based on the voltage and current abrupt change characteristics, controlling the nearest upstream and downstream section switches to trip, and isolating a fault section; constructing a multi-layer topological structure by taking the first section switch at the downstream of the fault point as a starting point; on the basis of upstream available section switches, calculating an electrical distance path, screening candidate switches meeting topological connectivity constraints, and selecting the section switch with the shortest electrical distance and meeting the total load requirement as a main transfer supply source; when the capacity of the main transfer supply source is insufficient, a capacity gap is calculated, the suboptimal section switch is selected, and a parallel transfer path of the main transfer supply source and the suboptimal section switch is formed. The method has the advantages that by accurately positioning the fault point, constructing a multi-layer topological structure and intelligently selecting the load transfer source, the load is quickly and reliably transferred, and the emergency response capability of the power distribution network is improved.

The invention discloses a multi-dimensional index-based power network substation target optimization method. The method comprises the following technical steps of 1) performing condition information investigation; 2) based on a complex network theory, constructing a power network weighted topological graph reflecting a network frame topological relation and electrical distance characteristics; 3) based on a graph theory and a graph maximum flow theory, constructing a power network energy flow graph reflecting the carrying capacity of the power network; 4) on the basis of a graph theory and a complex network theory, six transformer substation key quantitative evaluation indexes are sequentially calculated for each transformer substation of the power system in the target region; 5) calculating the entropy value of each key index based on an entropy weight algorithm, and further calculating a multi-index entropy weight, and 6) on the basis of the transformer substation key quantitative evaluation indexes in the step 4) and the index entropy weight in the step 5), carrying out multi-dimensional key index comprehensive evaluation, and arranging the comprehensive evaluation index values from large to small to form an optimal list of power network transformer substation paralysis.

The invention relates to a layered and partitioned distributed power supply and energy storage two-stage planning method considering source storage load, belongs to the technical field of distributed power supply and energy storage capacity planning in a power distribution network, and aims at solving the problem of consumption caused by access of high-proportion renewable energy to the power distribution network and improving the power supply reliability of a power system. The power system operation cost is reduced; the method comprises the following steps: firstly, dividing a voltage regulation area of each distributed power supply on the basis of an electrical distance structural index based on active-reactive voltage sensitivity, secondly, carrying out two-stage planning on the basis of partitioning, constructing a two-stage planning model by taking minimum network loss and optimal economical efficiency as targets, and carrying out solving by adopting a distance-based improved ant lion algorithm; and finally, solving based on an IEEE33 node example, and verifying the effectiveness of the two-stage planning. The method has the advantages that the power complementation characteristic is fully played, the two-stage planning model is constructed, and the power distribution network operates economically, safely and reliably.

The invention relates to the technical field of electric power Internet of Things, in particular to a time-space hierarchical data compression method and system for multi-source heterogeneous data on a power distribution network side, and the method comprises the following steps: S1, carrying out the classification and lightweight compression processing of original data, and outputting intermediate data with a priority identifier; s2, based on the intermediate data obtained in the step S1, a gateway layer carries out topological grouping according to the electrical distance, and then carries out time alignment and weighted fusion on the data in the group to generate a fusion data packet; and S3, based on the fusion data packet obtained in the step S2, the cloud platform performs panoramic insight and value evaluation, generates and dynamically issues an optimization strategy instruction, and the strategy instruction is dynamically issued back to the edge layer and the gateway layer through a control channel. According to the method, the real-time advantage of edge calculation and the big data processing capability of a cloud platform can be fully exerted, modules of all levels work cooperatively, a set of complete power distribution network multi-source heterogeneous data processing solution is formed, and the overall efficiency of the system can be effectively improved.

The invention relates to the field of power quality monitoring of a power system, in particular to a comprehensive power quality monitoring method and system based on an intelligent fusion terminal, and the method comprises the steps: obtaining and preprocessing power quality data of the intelligent fusion terminal, dividing electrical partitions, determining dominant harmonic components, and calculating the electrical distance between terminals in the same partition. And based on density peak clustering, combining feature difference and electrical distance weight fusion to obtain a similarity distance, determining an adaptive cutoff distance by using a low-density region adjustment factor, and drawing a decision diagram to identify a clustering center. Screening clustering results, analyzing electric energy quality characteristic dominance, identifying a mixed cluster and re-clustering, and positioning a disturbance source by using an attenuation law in combination with a significant clustering result and an electrical distance. According to the method, the accuracy of disturbance source positioning is improved through adaptive clustering and mixed cluster analysis, and the operation condition of the power grid and multiple disturbance sources can be accurately identified through the adaptive truncation distance and the adjustment factor of the low-density region.

The invention relates to the technical field of power grid planning, in particular to an intelligent transformer area clustering method considering operation characteristics of distributed resources, and the method comprises the steps: collecting operation data of multiple types of transformer areas, and building an operation characteristic parameter set of the multiple types of distributed resources; generating a characteristic fingerprint database through principal component analysis dimension reduction and clustering processing, and calculating characteristic similarity between different resource characteristics; constructing classification aggregation models of various types of resources, and fusing the classification aggregation models into a transformer area comprehensive load model; according to the topological structure of the power distribution network and the comprehensive load model, calculating an inter-station composite electrical distance index, and extracting load characteristic similarity; and performing two-dimensional clustering by taking minimization of the composite electrical distance and maximization of the load characteristic similarity as double targets, and outputting a transformer area aggregation scheme. According to the method, the problem of collaborative modeling of dynamic characteristic differences of multiple types of resources and electrical coupling strength between the transformer areas is effectively solved, and the transformer area aggregation precision and the engineering adaptability in a distributed energy scene are remarkably improved.

The invention relates to a power grid topology optimization method and device fusing load edge weight characteristics and a storage medium, and the method comprises the steps: S1, building a dynamic graph model according to a power grid structure, and initializing the dynamic edge weight of the dynamic graph model; s2, associating the periodic change of the node load of the power grid with the real-time load rate of the line through a space-time coupling model, and calculating to obtain a first node feature of the dynamic graph model for updating the dynamic load rate; s3, based on the dynamic graph model, hub nodes are determined according to the number of the shortest electrical paths between the power grid nodes, and electrical betweenness distribution of a power grid key transmission corridor is generated according to the dynamic load rate; s4, calculating the topological potential energy of the nodes based on the electrical betweenness distribution and the electrical distance of the power grid nodes, and screening high-potential-energy nodes as fragile nodes; and S5, carrying out power grid topology optimization on the fragile nodes. Compared with the prior art, the method improves the recognition accuracy of the fragile nodes through capturing the operation state of the power grid in real time.

The application relates to the technical field of power distribution networks of power systems, and discloses a fault post-recovery control method for a power distribution network containing flexible soft switches, which comprises the following steps: after a fault occurs, the original main station converter is exited, the active power, the reactive power and the rated capacity of the remaining converters are collected to calculate the dynamic capacity margin, the electrical distance from each converter node to the load center of the system is calculated, the comprehensive score is obtained based on the capacity margin and the electrical distance weighting, the converter with the highest comprehensive score and the capacity margin greater than the preset threshold is selected as the new main station, and the control mode of the new main station is switched; the main station selection mechanism based on the comprehensive evaluation of the dynamic capacity margin and the electrical distance is used to quickly establish a stable voltage frequency reference for the power failure area, the load shedding penalty sub-target and the load hierarchical and phased recovery strategy are used to preferentially guarantee uninterrupted power supply for the first important load under the condition that the transfer supply capacity is limited, and the influence of power failure on sensitive users is effectively reduced.

The invention provides a dynamic grouping method and device for a heterogeneous direct current delivery system, and relates to the technical field of dynamic analysis and control of a power system, and the method comprises the steps: deducing a linear time-varying variation equation which is satisfied by the trajectory sensitivity of a system state trajectory to a system parameter vector based on a parameterized differential-algebraic equation model; calculating the track sensitivity of each device to a system parameter vector, projecting the track sensitivity to a common connection point corresponding to each device, and constructing a unified sensitivity feature vector of each device; calculating the dynamic similarity between the devices based on the unified sensitivity feature vector, and constructing a mixed similarity matrix in combination with the electrical distance similarity between the devices; and feature decomposition and feature vector clustering are carried out based on the mixed similarity matrix, and dynamic clustering of heterogeneous equipment is realized. According to the dynamic grouping method provided by the invention, unified grouping of heterogeneous equipment such as a synchronous machine and a converter can be realized in a heterogeneous power system containing high-proportion new energy and direct-current power transmission.

According to the new energy power generation grid-related frequency modulation capability evaluation method provided by the invention, the electrical distance model is constructed by fusing the node inertia difference and the power disturbance propagation sensitivity, and the time-space correlation characteristics of the power grid frequency response are accurately quantified; key measurement nodes representing regional frequency dynamic states are screened out by combining an improved Spearman correlation coefficient algorithm, the system is divided into partitions with similar frequency responses based on a dynamic allocation mechanism and modularity optimization, the problem of evaluation distortion caused by cross-regional frequency deviation in a traditional method is solved, and under a partition evaluation framework, the evaluation efficiency is improved. A dynamic correction mechanism is designed for the power fluctuation of the new energy unit, random output interference is suppressed through a power fluctuation correction coefficient, the fast response capability and the steady-state support effect are quantified by using double indexes of frequency modulation contribution speed and depth, the new energy frequency modulation evaluation error is reduced, and the node frequency in the partition is improved.

The application is suitable for the field of power demand analysis, and provides a power transaction matching recommendation method and system method facing user demand, which comprises the following steps: obtaining user power consumption data, generating a resonance group and a characteristic package with similar power consumption modes and risk tolerance; combining the resonance group characteristics with real-time market data to generate a power consumption comprehensive bidding plan; performing transaction matching based on the bidding plan, preferentially selecting the power generation resources closest in electrical distance, introducing a green energy premium coefficient, and outputting a transaction result; performing portfolio optimization analysis according to the transaction result, and generating a customized power package containing traditional energy, new energy and energy storage in combination with user risk preferences. Through multi-dimensional data integration and intelligent algorithm application, the application realizes accurate matching of power generation resources and user demand, improves power transaction efficiency and user satisfaction, and promotes new energy consumption and sustainable development of the power market.

This invention provides a power grid partitioning method under the background of high proportion of renewable energy access, including the following steps: Step S1: Based on the perspectives of line power flow and line impedance, an electrical distance index is given, and an electrical distance matrix is ​​constructed; Step S2: Based on a typical renewable energy output scenario set, a correction coefficient is defined to correct the electrical distance matrix, resulting in a full-dimensional electrical distance matrix; Step S3: Based on the electrical distance matrix, a clustering algorithm is used to partition the power grid. This method is of great significance for improving the power grid's ability to cope with the uncertainty of renewable energy output and the level of renewable energy absorption.

The invention provides a flexible power distribution network interconnection device locating and sizing method and system, and belongs to the technical field of flexible power distribution networks. The method comprises the following steps: acquiring cross-court power mutual aid potential and an electrical distance between power distribution network nodes to generate a power distribution network node incidence matrix; carrying out relevance enhancement on the preliminary SOP site selection scheme based on a power distribution network node relevance matrix; a binary particle swarm optimization algorithm is adopted, an optimal SOP site selection scheme and a final power distribution network node incidence matrix are determined by enhancing the SOP site selection scheme, and the minimum mutual aid capacity which needs to be met by each SOP is calculated; and by taking the minimum mutual aid capacity as a constraint, constructing and solving a capacity optimization model taking the minimum full life cycle cost as a target, and outputting an optimal SOP constant volume scheme. According to the method, the long-term load balancing capability of the power distribution network and the cross-court flexible resource mutual aid efficiency are improved, and the intelligent level and the calculation efficiency of the optimization process are improved.