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

Wang et al., 2023 - Google Patents

Intelligent load frequency control for improving wind power penetration in power systems

Wang et al., 2023

View HTML
Document ID
6022374727319706812
Author
Wang Z
Li D
Lyu X
Gao S
Fu C
Zhu S
Wang B
Publication year
Publication venue
Energy Reports

External Links

Snippet

After wind power is connected to the grid, because the power of wind power will fluctuate greatly, the frequency deviation of the grid will increase with access to wind power generation, then the challenge of frequency control in power grid is also increasing. The …
Continue reading at www.sciencedirect.com (HTML) (other versions)

Classifications

    • G—PHYSICS
    • G05—CONTROLLING; REGULATING
    • G05B—CONTROL OR REGULATING SYSTEMS IN GENERAL; FUNCTIONAL ELEMENTS OF SUCH SYSTEMS; MONITORING OR TESTING ARRANGEMENTS FOR SUCH SYSTEMS OR ELEMENTS
    • G05B13/00—Adaptive control systems, i.e. systems automatically adjusting themselves to have a performance which is optimum according to some preassigned criterion
    • G05B13/02—Adaptive control systems, i.e. systems automatically adjusting themselves to have a performance which is optimum according to some preassigned criterion electric
    • G05B13/0265—Adaptive control systems, i.e. systems automatically adjusting themselves to have a performance which is optimum according to some preassigned criterion electric the criterion being a learning criterion
    • G05B13/027—Adaptive control systems, i.e. systems automatically adjusting themselves to have a performance which is optimum according to some preassigned criterion electric the criterion being a learning criterion using neural networks only
    • Y—GENERAL TAGGING OF NEW TECHNOLOGICAL DEVELOPMENTS; GENERAL TAGGING OF CROSS-SECTIONAL TECHNOLOGIES SPANNING OVER SEVERAL SECTIONS OF THE IPC; TECHNICAL SUBJECTS COVERED BY FORMER USPC CROSS-REFERENCE ART COLLECTIONS [XRACs] AND DIGESTS
    • Y02—TECHNOLOGIES OR APPLICATIONS FOR MITIGATION OR ADAPTATION AGAINST CLIMATE CHANGE
    • Y02E—REDUCTION OF GREENHOUSE GASES [GHG] EMISSION, RELATED TO ENERGY GENERATION, TRANSMISSION OR DISTRIBUTION
    • Y02E60/00—Enabling technologies or technologies with a potential or indirect contribution to GHG emissions mitigation
    • Y02E60/70—Systems integrating technologies related to power network operation and communication or information technologies mediating in the improvement of the carbon footprint of electrical power generation, transmission or distribution, i.e. smart grids as enabling technology in the energy generation sector not used, see subgroups
    • Y02E60/76—Computer aided design [CAD]; Simulation; Modelling
    • Y—GENERAL TAGGING OF NEW TECHNOLOGICAL DEVELOPMENTS; GENERAL TAGGING OF CROSS-SECTIONAL TECHNOLOGIES SPANNING OVER SEVERAL SECTIONS OF THE IPC; TECHNICAL SUBJECTS COVERED BY FORMER USPC CROSS-REFERENCE ART COLLECTIONS [XRACs] AND DIGESTS
    • Y04—INFORMATION OR COMMUNICATION TECHNOLOGIES HAVING AN IMPACT ON OTHER TECHNOLOGY AREAS
    • Y04S—SYSTEMS INTEGRATING TECHNOLOGIES RELATED TO POWER NETWORK OPERATION, COMMUNICATION OR INFORMATION TECHNOLOGIES FOR IMPROVING THE ELECTRICAL POWER GENERATION, TRANSMISSION, DISTRIBUTION, MANAGEMENT OR USAGE, i.e. SMART GRIDS
    • Y04S40/00—Communication or information technology specific aspects supporting electrical power generation, transmission, distribution or end-user application management
    • Y04S40/20—Information technology specific aspects
    • Y04S40/22—Computer aided design [CAD]; Simulation; Modelling
    • G—PHYSICS
    • G05—CONTROLLING; REGULATING
    • G05B—CONTROL OR REGULATING SYSTEMS IN GENERAL; FUNCTIONAL ELEMENTS OF SUCH SYSTEMS; MONITORING OR TESTING ARRANGEMENTS FOR SUCH SYSTEMS OR ELEMENTS
    • G05B13/00—Adaptive control systems, i.e. systems automatically adjusting themselves to have a performance which is optimum according to some preassigned criterion
    • G05B13/02—Adaptive control systems, i.e. systems automatically adjusting themselves to have a performance which is optimum according to some preassigned criterion electric
    • G05B13/04—Adaptive control systems, i.e. systems automatically adjusting themselves to have a performance which is optimum according to some preassigned criterion electric involving the use of models or simulators
    • Y—GENERAL TAGGING OF NEW TECHNOLOGICAL DEVELOPMENTS; GENERAL TAGGING OF CROSS-SECTIONAL TECHNOLOGIES SPANNING OVER SEVERAL SECTIONS OF THE IPC; TECHNICAL SUBJECTS COVERED BY FORMER USPC CROSS-REFERENCE ART COLLECTIONS [XRACs] AND DIGESTS
    • Y04—INFORMATION OR COMMUNICATION TECHNOLOGIES HAVING AN IMPACT ON OTHER TECHNOLOGY AREAS
    • Y04S—SYSTEMS INTEGRATING TECHNOLOGIES RELATED TO POWER NETWORK OPERATION, COMMUNICATION OR INFORMATION TECHNOLOGIES FOR IMPROVING THE ELECTRICAL POWER GENERATION, TRANSMISSION, DISTRIBUTION, MANAGEMENT OR USAGE, i.e. SMART GRIDS
    • Y04S10/00—Systems supporting electrical power generation, transmission or distribution
    • Y04S10/50—Systems or methods supporting the power network operation or management, involving a certain degree of interaction with the load-side end user applications
    • Y04S10/54—Management of operational aspects, e.g. planning, load or production forecast, maintenance, construction, extension
    • G—PHYSICS
    • G06—COMPUTING; CALCULATING; COUNTING
    • G06N—COMPUTER SYSTEMS BASED ON SPECIFIC COMPUTATIONAL MODELS
    • G06N3/00—Computer systems based on biological models
    • G06N3/02—Computer systems based on biological models using neural network models
    • G—PHYSICS
    • G05—CONTROLLING; REGULATING
    • G05B—CONTROL OR REGULATING SYSTEMS IN GENERAL; FUNCTIONAL ELEMENTS OF SUCH SYSTEMS; MONITORING OR TESTING ARRANGEMENTS FOR SUCH SYSTEMS OR ELEMENTS
    • G05B17/00—Systems involving the use of models or simulators of said systems
    • G05B17/02—Systems involving the use of models or simulators of said systems electric
    • Y—GENERAL TAGGING OF NEW TECHNOLOGICAL DEVELOPMENTS; GENERAL TAGGING OF CROSS-SECTIONAL TECHNOLOGIES SPANNING OVER SEVERAL SECTIONS OF THE IPC; TECHNICAL SUBJECTS COVERED BY FORMER USPC CROSS-REFERENCE ART COLLECTIONS [XRACs] AND DIGESTS
    • Y02—TECHNOLOGIES OR APPLICATIONS FOR MITIGATION OR ADAPTATION AGAINST CLIMATE CHANGE
    • Y02E—REDUCTION OF GREENHOUSE GASES [GHG] EMISSION, RELATED TO ENERGY GENERATION, TRANSMISSION OR DISTRIBUTION
    • Y02E10/00—Energy generation through renewable energy sources
    • Y02E10/70—Wind energy
    • Y02E10/76—Power conversion electric or electronic aspects
    • Y—GENERAL TAGGING OF NEW TECHNOLOGICAL DEVELOPMENTS; GENERAL TAGGING OF CROSS-SECTIONAL TECHNOLOGIES SPANNING OVER SEVERAL SECTIONS OF THE IPC; TECHNICAL SUBJECTS COVERED BY FORMER USPC CROSS-REFERENCE ART COLLECTIONS [XRACs] AND DIGESTS
    • Y02—TECHNOLOGIES OR APPLICATIONS FOR MITIGATION OR ADAPTATION AGAINST CLIMATE CHANGE
    • Y02E—REDUCTION OF GREENHOUSE GASES [GHG] EMISSION, RELATED TO ENERGY GENERATION, TRANSMISSION OR DISTRIBUTION
    • Y02E30/00—Energy generation of nuclear origin

Similar Documents

Publication Publication Date Title
Li et al. Coordinated load frequency control of multi-area integrated energy system using multi-agent deep reinforcement learning
Cao et al. Data-driven multi-agent deep reinforcement learning for distribution system decentralized voltage control with high penetration of PVs
Arya A novel CFFOPI-FOPID controller for AGC performance enhancement of single and multi-area electric power systems
Jiang et al. Combined economic and emission dispatch problem of wind‐thermal power system using gravitational particle swarm optimization algorithm
Wang et al. Intelligent load frequency control for improving wind power penetration in power systems
Wadi et al. Load frequency control in smart grids: A review of recent developments
CN113872213B (en) Autonomous optimization control method and device for power distribution network voltage
Badihi et al. Active power control design for supporting grid frequency regulation in wind farms
Jood et al. Performance assessment of a neuro-fuzzy load frequency controller in the presence of system non-linearities and renewable penetration
Yin et al. Mode-decomposition memory reinforcement network strategy for smart generation control in multi-area power systems containing renewable energy
Yu et al. Hierarchical correlated Q-learning for multi-layer optimal generation command dispatch
Zheng et al. Deep reinforcement learning based active disturbance rejection load frequency control of multi-area interconnected power systems with renewable energy
Vidyarthi et al. A modified tilt controller for AGC in hybrid power system integrating forecasting of renewable energy sources
Li et al. Distributed quantum multiagent deep meta reinforcement learning for area autonomy energy management of a multiarea microgrid
Zeng et al. A multi-level fuzzy switching control method based on fuzzy multi-model and its application for PWR core power control
Li et al. Data‐driven cooperative load frequency control method for microgrids using effective exploration‐distributed multi‐agent deep reinforcement learning
Yin et al. Expandable deep width learning for voltage control of three-state energy model based smart grids containing flexible energy sources
Bhagat et al. Application of inertia emulation control strategy with energy storage system in multi-area hydro-thermal system using a novel metaheuristic optimized tilt controller
Qin et al. Optimal constant power control of wind turbine generators based on Takagi-Sugeno fuzzy model
Kuang et al. A review of control strategies for automatic generation control in power systems with renewable energy
Liu et al. An AGC dynamic optimization method based on proximal policy optimization
Lu et al. Advances in Model Predictive Control for Large-Scale Wind Power Integration in Power Systems: A Comprehensive Review
Chen et al. Emergency load-shedding optimization control method based on reinforcement learning assistance
Liu et al. Deep reinforcement learning-based voltage control method for distribution network with high penetration of renewable energy
Chen et al. Optimal combined wake and active power control of large‐scale wind farm considering available power