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A blockchain based peer-to-peer trading framework integrating energy and carbon markets

Applied energy, 2020-12, Vol.279, p.115539, Article 115539

2020

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Blockchain and Artificial Intelligence Technologies for Smart Energy Systems

1, 2024

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Mesoporous Zeolite-Supported Ruthenium Nanoparticles as Highly Selective Fischer-Tropsch Catalysts for the Production of C5-C11 Isoparaffins

Angewandte Chemie (International ed.), 2011-05, Vol.50 (22), p.5200-5203

International ed. in English, 2011

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Photosynthesis, chlorophyll fluorescence characteristics, and chlorophyll content of soybean seedlings under combined stress of bisphenol A and cadmium

Environmental toxicology and chemistry, 2014-11, Vol.33 (11), p.2455-2462

2014

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Featured chemical industrial parks in China: History, current status and outlook

Resources, conservation and recycling, 2012-06, Vol.63, p.43-53

2012

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Stackelberg game‐theoretic model for low carbon energy market scheduling

IET smart grid, 2020-02, Vol.3 (1), p.31-41

2020

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The development and application of two chlorine recycling technologies in polyurethane industry

Journal of cleaner production, 2013-02, Vol.41, p.97-104

2013

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Blockchain technologies empowering peer‐to‐peer trading in multi‐energy systems: From advanced technologies towards applications

IET smart grid, 2022-08, Vol.5 (4), p.219-222

2022

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Reinforcement learning for electric vehicle applications in power systems:A critical review

Renewable & sustainable energy reviews, 2023-03, Vol.173, p.113052, Article 113052

2023

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Applications of blockchain and artificial intelligence technologies for enabling prosumers in smart grids: A review

Renewable & sustainable energy reviews, 2022-06, Vol.161, p.112308, Article 112308

2022

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Windfall profit-aware stochastic scheduling strategy for industrial virtual power plant with integrated risk-seeking/averse preferences

Applied energy, 2024-03, Vol.357, p.122460, Article 122460

2024

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Planning integrated energy systems coupling V2G as a flexible storage

Energy (Oxford), 2022-01, Vol.239, p.122215, Article 122215

2022

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Consumer-centric decarbonization framework using Stackelberg game and Blockchain

Applied energy, 2022-03, Vol.309, p.118384, Article 118384

2022

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A novel deep learning based probabilistic power flow method for Multi-Microgrids distribution system with incomplete network information

Applied energy, 2023-04, Vol.335, p.120716, Article 120716

2023

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Blockchain Enabled Decentralized Local Electricity Markets With Flexibility From Heating Sources

IEEE transactions on smart grid, 2023-03, Vol.14 (2), p.1607-1620

2023

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Cost-efficient decarbonization of local energy systems by whole-system based design optimization

Applied energy, 2022-11, Vol.326, p.119921, Article 119921

2022

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Assessing long-term future climate change impacts on extreme low wind events for offshore wind turbines in the UK exclusive economic zone

Applied energy, 2024-01, Vol.354, p.122218, Article 122218

2024

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Mesoporous Zeolite‐Supported Ruthenium Nanoparticles as Highly Selective Fischer–Tropsch Catalysts for the Production of C 5 –C 11 Isoparaffins

Angewandte Chemie International Edition, 2011-05, Vol.50 (22), p.5200-5203

2011

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Digital twin based reinforcement learning for extracting network structures and load patterns in planning and operation of distribution systems

Applied energy, 2023-07, Vol.342, p.121128, Article 121128

2023

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Application of Distributed Ledger Technology in Distribution Networks

Proceedings of the IEEE, 2022-12, Vol.110 (12), p.1963-1975

2022

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Blockchain-enabled renewable energy certificate trading: A secure and privacy-preserving approach

Energy (Oxford), 2024-03, Vol.290, p.130110, Article 130110

2024

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Reinforcement learning for active distribution network planning based on Monte Carlo tree search

International journal of electrical power & energy systems, 2022-06, Vol.138, p.107885, Article 107885

2022

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Data-driven prosumer-centric energy scheduling using convolutional neural networks

Applied energy, 2022-02, Vol.308, p.118361, Article 118361

2022

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Sensitivity analysis of distributed photovoltaic system capacity estimation based on artificial neural network

Sustainable Energy, Grids and Networks, 2024-09, Vol.39, p.101396, Article 101396

2024

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Mesoporous Beta Zeolite-Supported Ruthenium Nanoparticles for Selective Conversion of Synthesis Gas to C 5 –C 11 Isoparaffins

ACS catalysis, 2012-03, Vol.2 (3), p.441-449

2012

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A blockchain based peer-to-peer trading framework integrating energy and carbon markets

Blockchain and Artificial Intelligence Technologies for Smart Energy Systems

Mesoporous Zeolite-Supported Ruthenium Nanoparticles as Highly Selective Fischer-Tropsch Catalysts for the Production of C5-C11 Isoparaffins

Photosynthesis, chlorophyll fluorescence characteristics, and chlorophyll content of soybean seedlings under combined stress of bisphenol A and cadmium

Featured chemical industrial parks in China: History, current status and outlook

Stackelberg game‐theoretic model for low carbon energy market scheduling

The development and application of two chlorine recycling technologies in polyurethane industry

Blockchain technologies empowering peer‐to‐peer trading in multi‐energy systems: From advanced technologies towards applications

Reinforcement learning for electric vehicle applications in power systems:A critical review

Applications of blockchain and artificial intelligence technologies for enabling prosumers in smart grids: A review

Windfall profit-aware stochastic scheduling strategy for industrial virtual power plant with integrated risk-seeking/averse preferences

Planning integrated energy systems coupling V2G as a flexible storage

Consumer-centric decarbonization framework using Stackelberg game and Blockchain

A novel deep learning based probabilistic power flow method for Multi-Microgrids distribution system with incomplete network information

Blockchain Enabled Decentralized Local Electricity Markets With Flexibility From Heating Sources

Cost-efficient decarbonization of local energy systems by whole-system based design optimization

Assessing long-term future climate change impacts on extreme low wind events for offshore wind turbines in the UK exclusive economic zone

Mesoporous Zeolite‐Supported Ruthenium Nanoparticles as Highly Selective Fischer–Tropsch Catalysts for the Production of C 5 –C 11 Isoparaffins

Digital twin based reinforcement learning for extracting network structures and load patterns in planning and operation of distribution systems

Application of Distributed Ledger Technology in Distribution Networks

Blockchain-enabled renewable energy certificate trading: A secure and privacy-preserving approach

Reinforcement learning for active distribution network planning based on Monte Carlo tree search

Data-driven prosumer-centric energy scheduling using convolutional neural networks

Sensitivity analysis of distributed photovoltaic system capacity estimation based on artificial neural network

Mesoporous Beta Zeolite-Supported Ruthenium Nanoparticles for Selective Conversion of Synthesis Gas to C 5 –C 11 Isoparaffins

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