[go: up one dir, main page]
More Web Proxy on the site http://driver.im/

Acurio et al., 2022 - Google Patents

Design and implementation of a machine learning state estimation model for unobservable microgrids

Acurio et al., 2022

View PDF
Document ID
14410640656075924609
Author
Acurio B
Barragán D
Amezquita J
Rider M
Da Silva L
Publication year
Publication venue
IEEE Access

External Links

Snippet

An observable microgrid may become unobservable when sensors are at fault, sensor data is missing, or data has been tampered by malicious agents. In those cases, state estimation cannot be performed using traditional approaches without pseudo-measurements. To …
Continue reading at ieeexplore.ieee.org (PDF) (other versions)

Classifications

    • GPHYSICS
    • G06COMPUTING; CALCULATING; COUNTING
    • G06FELECTRICAL DIGITAL DATA PROCESSING
    • G06F17/00Digital computing or data processing equipment or methods, specially adapted for specific functions
    • G06F17/50Computer-aided design
    • G06F17/5009Computer-aided design using simulation
    • GPHYSICS
    • G06COMPUTING; CALCULATING; COUNTING
    • G06NCOMPUTER SYSTEMS BASED ON SPECIFIC COMPUTATIONAL MODELS
    • G06N99/00Subject matter not provided for in other groups of this subclass
    • G06N99/005Learning machines, i.e. computer in which a programme is changed according to experience gained by the machine itself during a complete run
    • GPHYSICS
    • G06COMPUTING; CALCULATING; COUNTING
    • G06FELECTRICAL DIGITAL DATA PROCESSING
    • G06F2217/00Indexing scheme relating to computer aided design [CAD]
    • GPHYSICS
    • G06COMPUTING; CALCULATING; COUNTING
    • G06FELECTRICAL DIGITAL DATA PROCESSING
    • G06F11/00Error detection; Error correction; Monitoring
    • GPHYSICS
    • G01MEASURING; TESTING
    • G01RMEASURING ELECTRIC VARIABLES; MEASURING MAGNETIC VARIABLES
    • G01R31/00Arrangements for testing electric properties; Arrangements for locating electric faults; Arrangements for electrical testing characterised by what is being tested not provided for elsewhere
    • GPHYSICS
    • G06COMPUTING; CALCULATING; COUNTING
    • G06QDATA PROCESSING SYSTEMS OR METHODS, SPECIALLY ADAPTED FOR ADMINISTRATIVE, COMMERCIAL, FINANCIAL, MANAGERIAL, SUPERVISORY OR FORECASTING PURPOSES; SYSTEMS OR METHODS SPECIALLY ADAPTED FOR ADMINISTRATIVE, COMMERCIAL, FINANCIAL, MANAGERIAL, SUPERVISORY OR FORECASTING PURPOSES, NOT OTHERWISE PROVIDED FOR
    • G06Q10/00Administration; Management

Similar Documents

Publication Publication Date Title
Chen et al. Efficient identification method for power line outages in the smart power grid
Ho et al. A robust statistical approach to distributed power system state estimation with bad data
Yu et al. Parameter identification of photovoltaic models using a sine cosine differential gradient based optimizer
Massignan et al. Tracking power system state evolution with maximum-correntropy-based extended Kalman filter
Matavalam et al. Critical comparative analysis of measurement based centralized online voltage stability indices
Chen et al. Uncertainty level of voltage in distribution network: an analysis model with elastic net and application in storage configuration
Habib et al. Deep statistical solver for distribution system state estimation
Acurio et al. Design and implementation of a machine learning state estimation model for unobservable microgrids
Gnetchejo et al. Optimal design of the modelling parameters of photovoltaic modules and array through metaheuristic with Secant method
Shi et al. A novel distribution system state estimator based on robust cubature particle filter used for non‐gaussian noise and bad data scenarios
Parpaei et al. Rational random walk‐based optimal placement of phasor measurement units to enhance the initializing and guiding the optimization processes
Akrami et al. Event-triggered distribution system state estimation: Sparse kalman filtering with reinforced coupling
Yu et al. A robust distribution network state estimation method based on enhanced clustering Algorithm: Accounting for multiple DG output modes and data loss
Kirincic et al. A two‐step hybrid power system state estimator
Li et al. A method for parameter identification of distribution network equipment based on sequential model‐based optimization
Zhang et al. Deep multi-fidelity bayesian data fusion for probabilistic distribution system voltage estimation with high penetration of pvs
Lin et al. Hpt-rl: Calibrating power system models based on hierarchical parameter tuning and reinforcement learning
CN107204616B (en) Power system random state estimation method based on self-adaptive sparse pseudo-spectral method
Rezaeian Koochi et al. Locating minimum number of PMUs for pre‐and post‐disturbance monitoring of power systems
Azuma et al. Modified Brain Storm Optimization for Load Adjustment Distribution State Estimation Using Correntropy
Sarić et al. Information geometry for model identification and parameter estimation in renewable energy–DFIG plant case
Zhang et al. Multi-fidelity gaussian process for distribution system voltage probabilistic estimation with pvs
Eser et al. A computationally efficient topology identifiability analysis of distribution systems
Dkhichi Parameter extraction of photovoltaic module model by using Levenberg-Marquardt algorithm based on simulated annealing method
Algikar et al. A robust data-driven process modeling applied to time-series stochastic power flow