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25 Result(s)
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Zhigang **
Artificial Intelligence
Power Electronics, Electrical Machines and Networks
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Book
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Chapter
Prospects of Future Research Issues
We have mentioned the difficulty of smart grid forecast and dispatch mainly lies in the strong uncertainty, curse of dimensionality and the trouble of establishing the accurate model. Fortunately, as one of th...
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Introduction for Smart Grid Forecast and Dispatch
As a novel generation of power systems, smart grid is devoted to achieving a sustainable, secure, reliable and flexible energy delivery through the bidirectional power and information flow.
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Uncertainty Characterization of Power Grid Net Load of Dirichlet Process Mixture Model Based on Relevant Data
The net load of the power grid is the active power difference between the electricity demand of power users and renewable energy generation.
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Multi-objective Optimization Approach for Coordinated Scheduling of Electric Vehicles-Wind Integrated Power Systems
It is well recognized that renewable energy and electric vehicles are widely deployed for adapting to our society in an environmental way [1–4].
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Chapter
Many-Objective Distribution Network Reconfiguration Using Deep Reinforcement Learning-Assisted Optimization Algorithm
In recent years, energy and environmental crises have been significant obstacles to the sustainable development of our society. In order to lessen these crises, renewable energy (RE) has been paid more attenti...
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Review for Smart Grid Forecast
Accurate, effective and reliable forecasting techniques are essential for the development of the smart grid.
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Deep Learning-Based Densely Connected Network for Load Forecast
As we know, load forecasting plays an important role in various power system decision-making problems, such as unit commitment and economic dispatch.
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Chapter
Dense Skip Attention-Based Deep Learning for Day-Ahead Electricity Price Forecasting with a Drop-Connected Structure
The fluctuation of electricity prices affects the allocation and dispatch of power resources in the electricity market [1–3].
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Chapter
Extreme Learning Machine for Economic Dispatch with High Penetration of Wind Power
In recent years, renewable energy has been paid more attention and utilized more extensively throughout the world [1].
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Chapter
Federated Multi-agent Deep Reinforcement Learning for Multi-microgrid Energy Management
In recent years, renewable energy (RE) has been widely deployed, such as wind power and photovoltaic. Unlike traditional energy, RE resources are usually distributed.
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Review for Smart Grid Dispatch
As a novel generation of power systems, smart grid is devoted to achieving a sustainable, secure, reliable and flexible energy delivery through the bidirectional power and information flow.
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Chapter
Reinforcement Learning Assisted Deep Learning for Probabilistic Charging Power Forecasting of EVCS
As one of the most essential actions, the carbon emission reduction has been adopted to address the problem of climate change.
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Book
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Chapter
Overview of Flexible Load Control
Flexible load control refers to the ability to manage and adjust the consumption of electrical loads in response to changing energy supply and demand conditions.
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Chapter
Data Center Flexible Load Control for Renewable Energy Integration
Data center microgrids (DCMGs) have been recently established to address the above challenging issues of electricity cost and environmental impact. Therein, various work have contributed to reduce the cost of ...
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Chapter
Collaborative Response of Data Center Coupled with Hydrogen Storage System for Renewable Energy Absortion: A Global Interval Optimization Approach
To replace the conventional thermal power on the supply side, the connection of high-capacity renewable energy, such as wind power (WP) is considered to be one of the effective methods.
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Chapter
Demand–Supply Cooperative Responding Strategy in Power System with High Renewable Energy Penetration
Currently, human development is significantly constrained by energy and environmental crises. Renewable energy (RE) is considered as the solution for replacing conventional energy, because it is more environme...
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Chapter
Electric Vehicle Flexible Charging Load Control for Comprehensive Energy System Operation with Renewable Energy
In the present day, the sustainable development of modern society is threatened by the energy crisis and global warming. Efficient use of renewable generations (RGs) such as wind turbines (WT) and photovoltaic...
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Chapter
Data-Driven Distributionally Robust Scheduling of Community Comprehensive Energy Systems Considering Integrated Load Control
Recently, the depletion of fossil fuels and escalating environmental pollution have emerged as primary challenges confronting human civilization. The advent and progression of renewable generations (RGs) prese...
