41 results about "Distributed source" patented technology

The invention relates to a distributed source-load collaborative optimization method based on high-order topology and multi-scale attention, and the method comprises the steps: firstly providing a high-order graph construction method driven by structural interaction, and achieving the structural embedded expression of a physical interaction relation between multi-source equipment through a hyperedge-line graph mapping mechanism and functional attribute coding; secondly, a graph feature extraction method based on a multi-scale joint attention mechanism is designed, topology and state information are fused, and the inter-node adjustment collaboration recognition capability is improved; further constructing a source-load collaborative optimization scheduling model, introducing a particle swarm optimization algorithm to obtain an initial feasible strategy, and establishing a state-action mapping relation based on a deep reinforcement learning framework driven by graph embedding to realize autonomous learning and rolling optimization of a distributed control strategy; and finally, constructing an operation feedback closed loop mechanism, and introducing a graph structure migration and strategy adaptive updating method to enhance the response capability of the system to topological change and dynamic disturbance.

The invention relates to the technical field of power systems, and discloses a new energy power control method and device based on distributed power supply access, and the method comprises the steps: constructing a unified topology model comprising distributed source loads, energy storage equipment and charging piles based on an access mode of a distributed power supply; acquiring operation data of the distributed power supply through the unified topology model, and performing data preprocessing on the operation data to generate a standardized operation data set; monitoring the real-time operation state and operation index of the power grid in real time based on the standardized operation data set, dynamically generating a corresponding power control instruction, and issuing the power control instruction to the distributed power supply to execute a power regulation task; and generating a power balance instruction after the occurrence of the power grid abnormal event is detected, decomposing the power balance instruction based on the unified topology model and the standardized operation data set, and executing a power balance task. According to the invention, real-time monitoring and dynamic power adjustment of the distributed power supply can be realized, and the power grid stability and the power balance capability are improved.

Various methods and processing systems for the effective management of network traffic and facilitating data forwarding within distributed computing environments. Network components may be configured to amalgamate the Border Gateway Protocol (BGP) with Source Network Address Translation (SNAT) or network address port translation (NAPT) technologies to facilitate dynamic notification of network address accessibility and use port index identifiers to augment the precision and resilience of routing. A distributed SNAT / NAPT virtual network function (VNF) or cloud-native network function (CNF) may collaborate with LEAF switches or server aggregation devices to refine data transmission via adaptable address mapping and forwarding and enhance network scalability and resilience.

The invention discloses an intelligent scheduling platform oriented to a distributed source network load storage system, and compared with a current traditional power scheduling means which mostly depends on a static model and an artificial rule, the intelligent scheduling platform adopts a closed-loop structure of'perception-prediction-optimization-decision-control-evolution '. Various advanced technologies such as edge cloud collaboration, incremental learning and elastic optimization are fused, and higher real-time performance, intelligence and adaptability are achieved. The platform can actively identify system risks, accurately predict weather changes, dynamically adjust an energy storage strategy and continuously iterate and optimize a model, the scheduling efficiency and the system stability are effectively improved, an autonomous area control architecture with edge intelligence is constructed, so that the scheduling system has a distributed autonomous capability, and the service life of the scheduling system is prolonged. Not only are the scheduling robustness and security significantly improved, but also the real-time response and independent operation capability of each local system is enhanced.

The present invention discloses a method for direction finding of incoherently distributed sources under strong impulse noise. The method comprises the following steps: first, obtaining snapshot sampling data, performing de-impact preprocessing, and constructing a generalized Capon space spectrum function; second, initializing the quantum position of each arrow and setting parameters to construct a fitness function; third, dividing the arrow group into sub-arrow groups, and performing fitness function evaluation on all arrows. The quantum position of the arrow with the best fitness in each sub-arrow group is selected as the optimal quantum position; fourth, updating the quantum position of each arrow according to the shooting mechanism; fifth, mapping the updated quantum position of each arrow to a position, calculating the updated fitness function value, and updating the optimal quantum position of each sub-arrow group; and sixth, returning to step three, looping and iterating until the maximum number of iterations is reached, outputting the optimal quantum position set, and transforming it into the central azimuth and angular spread estimates of the incoherently distributed source through mapping. The method is robust and high-performance under strong impulse noise conditions.

This invention discloses a distribution network power grid partitioning method based on an improved Leuven algorithm. The method includes the following steps: Step 1: Extract typical daily time-series scenarios based on historical wind power, photovoltaic, and load data within the distribution network power grid using an optimized extraction model; Step 2: Based on the typical time-series scenarios, and aiming for optimal comprehensive indicators, obtain the optimal power grid partitioning scheme for each typical day using an improved Leuven algorithm incorporating a tree structure pruning step; Step 3: Establish a grid partitioning scheme evaluation index system that includes generality indicators of partitioning results, rationality indicators of simulation operation, and representativeness indicators of cluster extraction, and select the optimal grid partitioning scheme in the form of a radar chart. This method can provide guidance for the partitioning of distribution network power grids into distribution network power supply units, promoting the standardized grid connection of distributed source, load, and storage resources and efficient collaboration among power supply units.

The invention discloses a source-load-storage coordinated two-stage industrial town energy scheduling method, which comprises the following steps of: constructing a mathematical model comprising photovoltaic power generation, an interruptible load, battery energy storage and a diesel generator based on data such as energy supply and demand states of an industrial town and a micro-grid and distributed source-load-storage operation; on this basis, a day-ahead-intra-day two-stage industrial town energy scheduling model is constructed, a layered energy scheduling optimization method is adopted in the day-ahead stage, and rolling optimization is introduced to determine an intra-day scheduling strategy with the industrial town extra cost caused by the minimum prediction deviation as the target in the intra-day stage; the two-stage industrial town energy scheduling model is solved through a linear optimization method, the industrial town and each micro-grid execute a scheduling strategy and update operation data, data are collected again after a scheduling period is finished, and then industrial town energy scheduling of the next scheduling period is carried out. According to the method, the key problems of difficulty in source-load-storage cooperative scheduling, lag in real-time supply and demand deviation adjustment, low complex model solving efficiency and the like are solved.

The invention relates to the field of antenna measurement, in particular to a multi-probe test system and method based on a distributed source / receiver, and the system comprises a receiver unit which comprises a first power divider, a second power divider and a multi-port receiver which is connected with probes, a reference auxiliary port of the multi-port receiver is connected with a shunt port of the first power divider, a reference signal port of the multi-port receiver is connected with a shunt port of the second power divider, and a main port of the second power divider is connected with a first output end of the clock distributor; the antenna link unit comprises an antenna, a directional coupler and an amplifier unit, and the directional coupler is connected with a main path port of the first power divider; and the antenna transceiving unit comprises a first dual-port transceiving module, a reference signal port of the first dual-port transceiving module is connected with the second output end of the clock distributor, a receiving port of the first dual-port transceiving module is connected with a shunt port of the first power divider, and a transceiving port of the first dual-port transceiving module is connected with the amplifier unit.

The application provides a communication system based on forward error correction coding modulation, at a sending end, a uniformly distributed source sequence is subjected to Polar code coding, and then bit selection and redundancy insertion are performed on a polar code word through a BCDM algorithm, so that the symbol occurrence probability is adjusted, and shaping gain is obtained.The code word after the Polar code coding is sent to an 8-PAM modulator, so that three continuous bits are mapped into one 8-PAM symbol; and the modulated symbol with a target probability distribution is transmitted through an AWGN channel.At a receiving end, a demodulator demodulates the symbol probability into a bit Log-Likelihood Ratio (LLR); meanwhile, the inverse transformation of the BCDM algorithm is used to delete the redundant information in the bit LLR sequence, and a Polar code decoder corresponding to the Polar code encoder is used for decoding and estimating information bits; and the provision of the system guarantees the shaping gain of the coding modulation scheme, and realizes a low bit error rate.

The invention provides a power distribution network edge intelligent regulation and control system and device, and relates to the technical field of power distribution network automation control, and the system comprises a hardware module, a software module and a core regulation and control module. The hardware module adopts a modular structure design; the software module comprises an operating system layer and an application software layer; the core regulation and control module is based on a fuzzy opportunity constraint planning method of quantum state coding, and the types and the number of modules are dynamically configured according to user side resource types, so that hardware resource maximization utilization and cost minimization control under different load control scenes are realized. The method solves the calculation and communication problems of a distributed source network load storage system in the prior art, has efficient hardware resource utilization and cost control capabilities, and improves the operation efficiency, safety and intelligent level of a power distribution network.

The present application relates to the non-coherent distributed source DOA estimation method based on generalized array flow pattern under color noise, and the method is: the array signal receiving model based on generalized array flow pattern under the uniform linear array is established; the sample covariance matrix of array receiving signal is calculated, and the covariance difference matrix is further obtained by using difference operation; the eigenvalue decomposition and subarray division are carried out on the covariance difference matrix, and the signal subspace corresponding to two subarrays is obtained; the non-coherent distributed source DOA estimation is obtained based on matrix reduction criterion by using the phase relationship corresponding to two signal subspaces; the present application method has very good applicability to the multipath transmission under Toeplitz structure color noise and fast fading channel, can provide higher resolution and DOA estimation accuracy, and only needs one-dimensional spectrum peak search, and the calculation efficiency is high.

The invention discloses an equipment access and control method and system for an off-grid micro-grid supporting plug and play and rapid power regulation. The method comprises the following steps: unifying information of distributed source and load end equipment, and standardly describing type characteristics, operating parameters, communication interfaces and control capability of the distributed source and load end equipment; the method comprises the following steps of: actively initiating a registration process after distributed source-load end equipment is accessed to an off-grid micro-grid, completing equipment identification, function registration and topology updating, and constructing a dynamic self-adaptive communication network at the same time; and when the system is disturbed, the distributed source-load end equipment cooperatively executes two local control mechanisms of frequency-power droop control and virtual synchronous power generation control according to modeling information and communication feedback so as to adjust the output power of the distributed source-load end equipment. The device plug-and-play capability, the system adjustment response speed and the operation stability of the off-grid micro-grid are effectively improved, and the method is suitable for off-grid micro-grids such as remote areas, novel energy islands and electric vehicle energy complementing stations.

The application discloses a robust non-coherent distributed source two-dimensional direction of arrival estimation method under an L-shaped array, which establishes a generalized array flow type receiving model under the L-shaped array, the L-shaped array is composed of two uniform linear arrays respectively located on the x-axis and the z-axis of the xoz plane; the data output by the uniform linear arrays on the x-axis and the z-axis is sampled at N moments; statistical average operation and conjugate symmetry strategy are used to construct aperture expansion array mutual covariance vectors corresponding to the uniform linear arrays on the x-axis and the z-axis; according to the two aperture expansion array mutual covariance vectors, all direction angle estimation values with the x-axis as a reference and all direction angle estimation values with the z-axis as a reference are obtained, and then pairing is performed to obtain all two-dimensional direction of arrival estimation values; the method is not only suitable for uniform and non-uniform noise scenes, but also does not depend on prior information of the number of signal sources, and the practicability and flexibility of the algorithm are improved.

Various embodiments of the present technology generally relate to systems and methods for providing a data preparation engine for curating secure and compliant data collections from distributed storage systems. In an aspect, a data preparation engine receives a query from a client device and determines files from one or more distributed sources based on the query. The data preparation engine determines sensitive data within the files and anonymizes the sensitive data while preserving context and integrity of the underlying information. The data preparation engine generates a data collection including the files with anonymized sensitive data. The data collection may then be deployed to downstream applications or workflows, such as used to generate curated data sets for training of artificial intelligence applications. Once deployed, the data preparation engine may continuously monitor the distributed sources for changes to data within the files and automatically update data collections in real-time.

The invention belongs to the technical field of power systems, and discloses a power quality situation deduction model evaluation method, system and device and a medium. The method comprises the following steps: acquiring power quality monitoring data, and forming a data set containing reference data and to-be-predicted data; constructing a deep learning situation deduction model based on the obtained data set, and constructing a performance evaluation framework of the deep learning situation deduction model based on a Taylor graph; performing skill score calculation on the performance indexes of the obtained performance evaluation framework to obtain skill score values, sorting the skill score values, and determining a deep learning situation deduction model with the highest score; and based on the deep learning situation deduction model with the highest score, evaluating the influence of the distributed source load power fluctuation on the power quality index of each node in the power distribution network system. According to the invention, accurate reverse traceability of the power quality problem and accurate positioning of the key source load are realized, and scientific decision support is provided for prevention and control and responsibility division of the power quality problem of the power distribution network.

The invention relates to the technical field of radiation shielding, in particular to a Monte Carlo-discrete longitudinal beacon coupling calculation method based on a distributed source item, which comprises the following steps of: acquiring Monte Carlo particle track information by utilizing Monte Carlo simulation, and converting the Monte Carlo particle track information into grid particle angular density in a discrete longitudinal beacon; performing fitting processing on the direction distribution of the angular density of the grid particles by using a spherical harmonic function to obtain a low-storage-capacity-level source item file; performing discrete longitudinal scaling method simulation based on the low-storage-magnitude source item file to obtain a discrete longitudinal scaling method simulation result; and combining a Monte Carlo simulation result with the discrete longitudinal standard method simulation result to obtain a final simulation result. Source items are arranged in a calculation area, and a space coupling calculation mode can realize source item distribution in a combined surface form, and is suitable for processing a coupling surface under a geometric complex condition. And calculation of an energy coupling mode can be carried out, and the method is suitable for processing different calculation methods and different energy conditions. Transmission and interaction of particles in a complex geometric structure can be simulated more accurately, so that the accuracy of a calculation result is improved.

The application belongs to the technical field of signal processing, and relates to a near-field incoherent distributed source positioning method, which comprises the following steps: receiving a near-field incoherent distributed source signal by using a sensor array, and estimating a covariance estimation quantity of the near-field incoherent distributed source signal; constructing a covariance model of the near-field incoherent distributed source signal according to the covariance estimation quantity; discretizing the angle and distance distribution of the near-field incoherent distributed source to obtain a near-field incoherent distributed source signal covariance model containing a spatial spectrum matrix; constructing a low-rank minimization problem of spatial spectrum estimation according to the near-field incoherent distributed source signal covariance model; solving the low-rank minimization problem to obtain a spatial spectrum estimation quantity; extracting key parameters of the angle and distance distribution of the near-field distributed source in the spatial spectrum according to the spatial spectrum estimation quantity, and obtaining the position of the near-field incoherent distributed source according to the key parameters; the application does not need a parameterized model of the spatial distribution of the near-field incoherent distributed source, and can directly position and estimate the angle and distance distribution of the source.

The present invention discloses a two-dimensional parameter estimation method for broadband incoherent distributed sources based on spectrum matching, comprising the following steps: decomposing the direction of arrival (DOA) estimation problem of a two-dimensional broadband incoherent distributed source into two one-dimensional estimation problems by decomposing an L-shaped array into two orthogonal uniform linear arrays; recovering two angular frequency spatial spectrum matrices from the array receiving covariance matrix based on the received signal in combination with a low-rank recovery method; and extracting two sets of key parameters from the two angular frequency spatial spectrum matrices for matching; proposing a spectrum matching-based method for determining the two-dimensional DOA of a broadband incoherent distributed source based on the frequency domain parameter invariance of the distributed source in space; and directly estimating the joint angle and spectrum to obtain the joint parameters. The present invention also eliminates the need for prior knowledge of the distributed source and can directly estimate the two-dimensional angle based on the angular frequency spatial spectrum.

The present application belongs to the field of energy consumption and multi-source load collaborative control, and particularly relates to a distributed source-load end-to-end matching control method, device, equipment and medium. The method comprises: acquiring power data of all power sources and loads in a target area, and calculating a correlation coefficient between each power source and each load based on the power data; generating a correlation coefficient matrix based on the calculated correlation coefficients; sorting the correlation coefficients in the correlation coefficient matrix, and matching the sources and loads according to the sorting result; and generating an instruction for power interaction according to the result of source-load matching. The distributed source-load end-to-end matching control method provided by the present application proposes a source-load correlation-based method, comprehensively considers the correlation between different sources and loads in a distribution network, reflects the correlation degree between different sources and loads through the correlation, and determines the source-load matching order according to the source-load correlation degree level, so as to reasonably guide the orderly matching between distributed sources and loads.

The present invention belongs to the field of new energy consumption and power trading, and specifically relates to a distributed source-load end-to-end transaction optimization control method taking into account user intentions. An original source-load end-to-end model is established; based on the original source-load end-to-end model, a distributed source-load end-to-end optimization control model with user intentions is established; based on the distributed source-load end-to-end optimization control model with user intentions in the second step, a distributed end-to-end optimization control model with network constraints and user intentions is established. By using an endogenous application load vector matrix, the intermediate flow calculation is simplified and it is ensured that bilateral transactions meet network constraints. The augmented Lagrange multiplier method is used to include network constraints in the objective function, reducing the constraints of the objective function; the introduction of user intentions is conducive to the reasonable control of transactions.

The application discloses a kind of source network load flexibility resource integration's hybrid energy storage optimization method and system, it is related to distributed source network load storage planning field, for solving the problem that centralized energy storage planning ignores terrain hydrology and distribution network difference causes site distortion and scale expansion, is by first in terrain and water body information screen out with upper and lower reservoir conditions pumped storage candidate point, again mapping distribution and transmission network and according to energy path and tidal flow sensitivity cutting access position, so that energy storage is located close to load concentration area rather than limited to a few nodes in transmission level, from source to inhibit long-distance transmission loss and invalid expansion demand;On this basis, pumped storage undertakes slow change power movement, electrochemical energy storage undertakes fast change peak valley regulation, and the apportioned result is embedded in power generation, line opening, demand response and other multi-side joint model, so that spatial constructability and operation flexibility synergize in the same optimization framework;Therefore, avoid the expansion of energy storage capacity caused by ignoring flexible resources.

The invention discloses a data detection method and device, equipment and a storage medium, and relates to the technical field of data processing. According to the method, distributed source data corresponding to a query field in a data source table is obtained according to a data detection request, data detection is used for detecting whether the query field in the data source table is repeated or not, and in the data repetition detection process, the distributed source data can be divided into multiple batches of source data; source data of each batch is divided into N data blocks, single data blocks are scheduled in batches for data processing through block numbers of the data blocks so as to reduce the memory utilization rate, and most of non-repeated data of the current batch are rapidly filtered in combination with a target hash bitmap, so that the data processing efficiency is improved. The key fields are accurately verified only by using the second dictionary tree object of the front batch for a small part of repeated data, so that the data volume of accurate verification can be effectively reduced, two-layer repeated detection can be passed while data repeated detection is improved, and the accuracy of data repeated detection is improved.

The invention discloses a distributed source-load collaborative strategy optimization method oriented to supply and demand mutual assistance of production and consumer of a micro-grid. The method comprises the following steps: constructing a production and consumer source-load physical state and energy storage time sequence constraint model; constructing a mutual aid power physical boundary; defining a virtual potential energy state quantity; constructing a delivery and disappearing person supply and demand mutual aid collaborative decision-making model; performing linearization processing on the alternating current power flow equation; solving a node voltage amplitude and a line power flow disturbance vector; converting the node voltage amplitude disturbance vector into a mutual aid power matrix; establishing a network physical constraint feasible region; establishing a global mutual aid matching model; constructing an asynchronous driving and joint optimization loop; virtual congestion potential energy is calculated; performing robust sensing extreme scene verification and cross-scene residual quantization on the mutual aid power matrix, and tightening the upper bound of a network physical constraint feasible region; and when the indexes converge, outputting a mutual aid power matrix and a scheduling instruction. According to the method, the problems that existing network constraint embedding lags behind, asynchronous negotiation convergence is insufficient, and cross-scene feasibility of extreme scenes is lacked can be solved.

The application discloses a kind of high proportion distributed source and load area power supply method based on modular energy storage, the system using this method includes modular energy storage system, distributed source and load integration system, power supply strategy system, central control system, real-time monitoring system and intelligent fusion terminal, first by the real-time data acquisition of real-time monitoring system, then under the unified coordination of central control system, by modular energy storage system and distributed source and load integration system according to the indication of power supply strategy system complete substation power generation, power supply and the dynamic collaborative power supply work of energy storage, during through intelligent fusion terminal stable power supply, can make substation have substation side power over-limit control, prevent reverse sending, voltage reactive power control, source network load storage coordination optimization etc. Function, reach the purposes of improving substation voltage and power factor qualified rate, distributed power load bearing capacity and load access ability, reduce comprehensive line loss rate etc., improve the overall power supply level and power supply quality of substation, guarantee the smooth development of substation power grid.

The application discloses a kind of distributed source network load storage micro-grid systems, comprising: intelligent micro-grid, multiple distributed intelligent charging control terminal, dispatching control system;Wherein, distributed intelligent charging control terminal, including: central controller, wireless communication module, controllable inverter, controllable rectifier, DC charging load, distributed photovoltaic power supply, low-temperature superconducting thin film capacitor energy storage system;Wherein, low-temperature superconducting thin film capacitor energy storage system includes multiple energy storage modules arranged in underground low-temperature airtight metal cabin, and energy storage module is composed of multiple low-temperature superconducting thin film capacitors in parallel;Wherein, the refrigeration system of metal cabin adopts semiconductor refrigeration technology, and temperature and humidity monitor and thin film capacitor voltage monitoring system are arranged in metal cabin;The electric energy generated by distributed photovoltaic power supply in real time is stored in low-temperature superconducting thin film capacitor energy storage system, for distributed intelligent charging control terminal use.

The invention belongs to the technical field of integrated energy systems, and particularly relates to a multi-agent-based multi-level cooperative control method for an integrated energy system. Comprising the following steps: constructing a multi-level intelligent agent cooperative control framework of the comprehensive energy system; carrying out mass distributed flexible resource virtual aggregation controllable-adjustable characteristic analysis and modeling; establishing an efficient and rapid cooperative control model of the agent layer distributed controllable resources; according to the method, intelligent agents which are in one-to-one correspondence with physical system level nodes and have autonomous intelligent decision making functions are established, and a cross-platform integrated energy system multi-level intelligent agent cooperative control framework which adapts to distributed resource efficient access is constructed; analyzing a space-time uncertainty change rule, and constructing a mass distributed source-load-storage controllable resource virtual aggregation'controllable-adjustable 'characteristic model; on the basis, a control normal form of hierarchical interaction and autonomous cooperation among edge, edge and end, and end is established, and efficient suppression of power flow fluctuation under'plug and play 'energy impact is realized in real time.

This invention discloses a hybrid distributed source DOA estimation method based on the rank deficiency principle. First, a distributed source model is established where circular and non-circular signals are simultaneously incident on an array antenna. Second, the received signal is augmented using the conjugate of the received signal, and its covariance matrix is ​​calculated. Next, eigenvalue decomposition is performed on the covariance matrix to obtain the noise subspace under hybrid source conditions. Finally, based on the rank deficiency principle, a cost function is derived, and direction-of-arrival estimation is completed through one-dimensional spectral peak search. This method is applicable to scenarios where both circular and non-circular sources exist simultaneously in space. Compared to algorithms requiring two-dimensional search, this algorithm effectively reduces computational complexity while maintaining good angle estimation performance.

The invention discloses a power distribution network consumption capability improving method and system based on multi-type resources, and belongs to the technical field of intelligent power grids, and the method comprises the steps: constructing a distributed source load output model, obtaining the real-time operation data of a power distribution network, determining the adjustable power and rolling adjustment time window of each single device, and obtaining the power distribution network consumption capability. A distributed power supply, a flexible load and a capacitor bank are taken as regulation and control objects, peak valley difference stabilization, cost minimization and network loss minimization are taken as targets, power balance and safe operation are taken as constraints, and a multi-type flexible resource collaborative optimization scheduling model is constructed; and the regulation and control model is simplified through linear processing, and a commercial solver is used for rapid solving, so that regulation and control instructions of all the objects are obtained. And issuing the regulation and control instruction to various types of adjustable and controllable equipment in the power distribution network, indicating to execute operation and updating the state of the equipment. According to the invention, by optimizing the collaborative scheduling of flexible resources, the consumption capability of the power distribution network is improved, so that the power distribution network can efficiently cope with the increased power consumption demand and quickly respond to the changing load.

The invention discloses a source-network-load flexible resource integrated hybrid energy storage optimization method and system, relates to the field of distributed source-network-load storage planning, and is used for solving the problems of site selection distortion and scale expansion caused by neglecting topographic hydrological and distribution network differences in centralized energy storage planning. According to the method, pumped storage candidate points with reservoir loading and unloading conditions are screened out from terrain and water body information, power distribution and power transmission networks are mapped, and access positions are cut according to energy paths and tidal current sensitivity, so that energy storage is located close to a load concentration area instead of being limited to a few nodes of a transmission level; long-distance transmission loss and invalid capacity expansion requirements are inhibited from the source; on the basis, pumped storage is carried out with slow-change power transfer, electrochemical energy storage is carried out with fast-change peak-valley adjustment, and an apportionment result is embedded into a multi-side joint model of power generation, line on-off, demand response and the like, so that the space buildability and the operation flexibility have a synergistic effect in the same optimization framework; therefore, energy storage capacity expansion caused by neglecting flexible resources is avoided.

Dynamic Digital Immune Systems / Processes (DDIS) improve data integrity and quality in Explainable AI (XAI) systems. Operating in real time, it monitors data from distributed sources during federated training, detecting and flagging corrupted, poisoned, or low-quality data with dynamic anomaly detection algorithms. The system includes automated data cleaning to remove redundant and irrelevant data, enhancing AI model performance. It features dynamic encryption that adapts to data sensitivity, ensuring robust security. Swarm intelligence-based task distribution allows decentralized auditing of data integrity, while a traceability matrix tracks data lineage for transparency. The DDIS also incorporates a self-healing mechanism that automatically corrects identified anomalies, ensuring continuous reliability of AI outputs. This comprehensive system protects against data corruption, enhances processing efficiency, and safeguards the accuracy and integrity of XAI systems in high-stakes environments.