Article
Computer Science, Information Systems
Oanh Tran Thi Kim, Tra Huong Thi Le, Michael J. Shin, Vandung Nguyen, Zhu Han, Choong Seon Hong
Summary: With the increasing number of electric vehicles, peer-to-peer energy trading between electric vehicles and mobile charging stations can be utilized to relieve the overload on fixed charging stations and achieve trading benefits. In this paper, an incentive mechanism is designed for the energy trading model. The proposed energy trading scheme achieves critical properties including truthfulness, individual rationality, budget balance, and computational efficiency. Simulation experiments verify the effectiveness of the proposed scheme compared with the baseline.
Article
Energy & Fuels
Shuyu Luo, Qi Li, Yuchen Pu, Xukang Xiao, Weirong Chen, Shukui Liu, Xixuan Mao
Summary: This paper proposes a carbon trading method for CHHP based on a Vickrey auction strategy to fully consider the potential for renewable energy to participate in the carbon trading market. The method includes building a CHHP model, calculating CCERs, using a baseline approach to allocate CEAs, and introducing a trading mechanism based on a Vickrey auction. The results show that the proposed method has advantages in the economy and carbon emissions.
JOURNAL OF ENERGY STORAGE
(2023)
Article
Energy & Fuels
Bidan Zhang, Yang Du, Xiaoyang Chen, Eng Gee Lim, Lin Jiang, Ke Yan
Summary: With the rapid development of Distributed Energy Sources (DERs), Peer-to-Peer (P2P) energy trading has become an effective solution to improve local energy utilization. However, the small-scale prosumers and highly unpredictable intermittent DERs in P2P markets contribute to market uncertainties. This study proposes a novel adaptive penalty mechanism (APM) to enforce compliance of defaulting participants by using a three-dimensional penalty and deviation percentage factors.
Article
Energy & Fuels
Juan Wang, Junjun Zheng, Liukai Yu, Mark Goh, Yunying Tang, Yongchao Huang
Summary: This paper proposes a distributed reputation-distance-driven iterative auction mechanism to promote energy trading among users who commit contracts well and among electrically closer peers. It introduces a reputation-distance index based on historical trading performance and electricity distance, and uses a self-adaption algorithm based on game theory to arrive at a Nash equilibrium. The mechanism can reduce network loss, increase market efficiency, and improve social welfare.
Article
Green & Sustainable Science & Technology
Dewen Liu, Zhao Luo, Jinghui Qin, Hua Wang, Gang Wang, Zhao Li, Weijie Zhao, Xin Shen
Summary: In this paper, a multi-district integrated energy systems scheduling model considering the carbon emission trading and green certificate trading mechanisms is proposed. The feasibility of introducing these mechanisms into the integrated energy system is analyzed, and a joint trading market framework is established using a combinatorial double auction mechanism. The impacts of carbon emission trading, green certificate trading, and changes in natural gas prices on system operating costs are analyzed, and case studies demonstrate the effectiveness of the proposed model.
Article
Green & Sustainable Science & Technology
Jakob Heilmann, Marthe Wensaas, Pedro Crespo del Granado, Naser Hashemipour
Summary: The study investigates how to organize electricity sharing in local electricity markets and the application of trading algorithms in the wholesale market of energy communities. The findings suggest that Peer-to-Peer (P2P) is more economically efficient than Multi-unit Double Auction (MUDA), but also raises concerns about unfair trading.
Article
Chemistry, Analytical
Anchisa Pinyo, Athikom Bangviwat, Christoph Menke, Antonello Monti
Summary: This paper introduces a decentralized business model and a possible trading platform for electricity trading in Thailand's Micro-Grid to deal with the power system transformation. The Hybrid P2P approach is utilized for energy exchange, while a decentralized price mechanism is proposed for Community-based trading. The comparison analysis shows that the decentralized business model outperforms a centralized approach on community and individual levels.
Article
Energy & Fuels
Mohsen Khorasany, Amin Shokri Gazafroudi, Reza Razzaghi, Thomas Morstyn, Miadreza Shafie-khah
Summary: This paper proposes a framework for local energy and flexibility trading, allowing prosumers to trade energy and flexibility with each other through a peer-to-peer market and a flexibility market. Experimental results show that this framework enables the system operator to avoid network constraints violation and reduces energy costs for prosumers.
Article
Computer Science, Information Systems
Olamide Jogunola, Yakubu Tsado, Bamidele Adebisi, Mohammad Hammoudeh
Summary: This article evaluates the importance of factors such as distance charge and network constraints in matching prosumers on peer-to-peer energy trading platforms. A platform-VirtElect based on a double auction market is developed to support the matching interaction between prosumers. Case studies using real microgrid data verify the potential of local energy consumption and show that local energy trading is not only beneficial to the environment but also leads to significant cost savings.
IEEE INTERNET OF THINGS JOURNAL
(2022)
Article
Energy & Fuels
Uyikumhe Damisa, Nnamdi Nwulu, Pierluigi Siano
Summary: The decentralization of power generation driven by the rise in the adoption of distributed energy resources has opened up a new paradigm in grid operations. P2P energy trading benefits both the grid and the connected peers, and blockchain-based smart contracts are well-suited for transparently facilitating trades between energy consumers and producers.
Article
Mathematics
Dongdong Wang, Xinyu Du, Hui Zhang, Qin Wang
Summary: To promote the value circulation of energy resources and enhance energy efficiency, credible energy sharing between IoT devices has been developed. This paper proposes a credible energy transaction model based on blockchain to collect surplus energy resources and enable secure sharing between IoT devices. In addition, a smart contract-based incentive mechanism is proposed to attract long-term energy sharing participation and maximize the social welfare by dynamically allocating energy from multiple IoT devices to a single edge cloud server. Simulation results demonstrate the effectiveness of the proposed mechanism in meeting energy demand and improving social welfare.
Article
Energy & Fuels
Shuang Xu, Yong Zhao, Yuanzheng Li, Yue Zhou
Summary: This study proposes a novel iterative uniform-price auction (IUPA) mechanism for peer-to-peer energy trading in a community microgrid, which divides the market into seller's and buyer's markets to determine a uniform trading price and efficient energy allocation. Competitive prosumers adjust their bids iteratively based on private information and market conditions to reach a Nash equilibrium, differentiating from continuous double auction (CDA) in terms of bidding formats and strategies. The auction market self-adaption algorithm (AMSA) efficiently finds equilibrium in the IUPA, demonstrating effectiveness in fairer trading prices, cost savings, and promotion of local transactions of excess PV energy.
Article
Computer Science, Hardware & Architecture
Ajit Muzumdar, Chirag Modi, G. M. Madhu, C. Vyjayanthi
Summary: This paper proposes a trustworthy and incentivized framework for smart grid energy trading using distributed ledger technology and smart contracts to address challenges in energy trading, such as transparency, data verification, privacy, and incentivization.
JOURNAL OF NETWORK AND COMPUTER APPLICATIONS
(2021)
Article
Energy & Fuels
Chen Zhang, Tao Yang, Yong Wang
Summary: The research proposes a P2P energy trading model based on iterative double auction and blockchain, which achieves maximum social welfare and market equilibrium, improving individual profits. Numerical examples demonstrate the effectiveness of the algorithm, showing a 22.3% increase in social welfare compared to zero-intelligence strategy.
SUSTAINABLE ENERGY GRIDS & NETWORKS
(2021)
Article
Engineering, Electrical & Electronic
Chenxi Zhang, Jing Qiu, Yi Yang, Junhua Zhao
Summary: This paper introduces a two-stage optimization model that combines BESS planning with distribution electricity market optimization to improve energy trading benefits through internal resource allocation and a double-sided auction mechanism, and demonstrates numerical results on a modified IEEE 24-bus system.
INTERNATIONAL JOURNAL OF ELECTRICAL POWER & ENERGY SYSTEMS
(2021)
Article
Computer Science, Information Systems
Ziye Jia, Qihui Wu, Chao Dong, Chau Yuen, Zhu Han
Summary: In this article, a hierarchical aerial computing framework is proposed to provide MEC services for various IoT applications, using high altitude platforms (HAPs) and unmanned aerial vehicles (UAVs). Matching game theory-based algorithms are utilized to handle offloading decisions between IoT devices and UAVs, and a heuristic algorithm is proposed for offloading decisions between UAVs and HAPs. An externality elimination mechanism is introduced to deal with the external effects caused by different IoT devices in the matching. Additionally, an adjustment algorithm is presented to optimize the use of aerial resources. Extensive simulation results demonstrate the efficiency of the proposed algorithms, and the system performances are analyzed based on numerical results.
IEEE INTERNET OF THINGS JOURNAL
(2023)
Article
Engineering, Electrical & Electronic
Yang Liu, Bin Wang, Zeyue Zhang, Yuzhi Zhang, Chau Yuen
Summary: This article proposes a partial repetition extension method for constructing rate-compatible spatially coupled low-density parity-check codes. By adjusting the selection proportions and the repetition times, RC-SCLDPC codes with arbitrary rates and excellent thresholds can be obtained. The decoding complexity can also be significantly decreased using this method.
IET COMMUNICATIONS
(2023)
Article
Automation & Control Systems
Yan Qin, Anushiya Arunan, Chau Yuen
Summary: In order to meet the high safety and reliability requirements in practice, the state of health (SOH) estimation of Lithium-ion batteries (LIBs) has been extensively studied. A digital twin framework is proposed to enable real-time SOH estimation without requiring a complete discharge cycle. The proposed method yields real-time SOH estimation with errors less than 1% for most sampling times in ongoing cycles.
IEEE TRANSACTIONS ON INDUSTRIAL INFORMATICS
(2023)
Article
Automation & Control Systems
Yan Qin, Chau Yuen, Xunyuan Yin, Biao Huang
Summary: To address the data discrepancy across batteries, researchers propose a transferable multistage SOH estimation model that outperforms its competitors in various transfer tasks. By using stage information and an updating scheme to compensate for estimation errors, the model significantly improves estimation accuracy.
IEEE TRANSACTIONS ON INDUSTRIAL INFORMATICS
(2023)
Article
Engineering, Electrical & Electronic
Joel Yeo, Huifei Jin, Armando Rodrigo Mor, Chau Yuen, Norasage Pattanadech, Wayes Tushar, Tapan K. Saha, Chee Seng Ng
Summary: This paper proposes an algorithmic approach that uses a convolutional recurrent neural network (CRNN) to iteratively examine extracted features in order to localize partial discharge (PD) in medium voltage (MV) power cables. The algorithm's performance was evaluated through a case study on 7 selected cables, showcasing the challenges encountered during field testing. Experimental results demonstrate that the proposed concept can successfully identify and locate discharges with significant levels of noise. The main contribution of this methodology lies in its ability to interpret measurements acquired under noisy field constraints.
IEEE TRANSACTIONS ON POWER DELIVERY
(2023)
Article
Engineering, Electrical & Electronic
Kannan Thirugnanam, Chau Yuen, Praveen Kumar, Tareg Ghaoud, Sgouris Sgouridis
Summary: A method for maintaining voltage in a distribution node through controlled and coordinated charging and discharging of EVs is proposed. Fuzzy logic control is used to generate reference power signal and control power flow direction, and an EVCS aggregator is implemented to coordinate a large fleet of EVs. Active and reactive power control methodology is used to maintain the voltage profile within the threshold limits.
Article
Engineering, Electrical & Electronic
Guiqi Sun, Ruisi He, Yaxin Song, Bo Ai, Shuguang Cui, Yong Niu, Haoxiang Zhang, Zhangfeng Ma, Chau Yuen
Summary: In this article, a three-dimensional one-cylinder model is proposed to investigate the effects of different RIS phases on channel statistical properties. The findings provide guidance for establishing intelligent, safe, and controllable propagation conditions in RIS-aided networks.
IEEE ANTENNAS AND WIRELESS PROPAGATION LETTERS
(2023)
Article
Engineering, Electrical & Electronic
Songjie Yang, Wanting Lyu, Zhenzhen Hu, Zhongpei Zhang, Chau Yuen
Summary: In this paper, a low-complexity channel estimation strategy is proposed for XL-RIS-aided mmWave communications. The strategy separates the channel estimation procedure into two phases and utilizes the 3D-M-CS and 3D-D-CS frameworks for parameter estimation. Variants of LAOMP, 3D-M-LAOMP and 3D-D-LAOMP, are developed to solve the proposed CS frameworks.
IEEE TRANSACTIONS ON VEHICULAR TECHNOLOGY
(2023)
Article
Engineering, Electrical & Electronic
Hao Huang, Guan Gui, Haris Gacanin, Chau Yuen, Hikmet Sari, Fumiyuki Adachi
Summary: Millimeter wave (mmWave) systems require beam management for reliable links, but the process is complex and time-consuming. This paper proposes a data-driven deep learning method to predict the beam without coordination between transceivers, improving performance under limited training samples.
IEEE TRANSACTIONS ON VEHICULAR TECHNOLOGY
(2023)
Article
Engineering, Electrical & Electronic
Chunyu Zhou, Yongjun Xu, Dong Li, Chongwen Huang, Chau Yuen, Jihua Zhou, Gang Yang
Summary: This paper investigates a RIS-aided multiple-input single-output SR system and proposes an algorithm to maximize EE by optimizing various parameters. The results show that the proposed algorithm achieves a two times improvement in system EE compared to traditional algorithms.
IEEE TRANSACTIONS ON VEHICULAR TECHNOLOGY
(2023)
Article
Computer Science, Hardware & Architecture
Bo Yang, Xuelin Cao, Jindan Xu, Chongwen Huang, George C. Alexandropoulos, Linglong Dai, Merouane Debbah, H. Vincent Poor, Chau Yuen
Summary: The future 6G wireless networks will integrate communications and computing intelligently to meet various application demands. Reconfigurable intelligent surfaces (RISs), which offer programmable propagation of electromagnetic signals, are a promising technology for realizing smart radio environments. However, conventional RISs' purely reflective nature poses challenges for computation-based applications. New materials, like metamaterials, will be needed to complement existing technologies and enable further electronic diversification and applications.
IEEE WIRELESS COMMUNICATIONS
(2023)
Article
Engineering, Electrical & Electronic
M. Imran Azim, Mollah R. R. Alam, Wayes Tushar, Tapan K. K. Saha, Chau Yuen
Summary: The importance of peer-to-peer (P2P) trading in promoting renewable energy use has been confirmed in scientific literature and pilot projects. However, large-scale implementation of P2P trading in the current electricity market has yet to be achieved due to some factors. Firstly, existing pilot projects mainly focus on communication and settlement, neglecting the impact on distribution networks. Secondly, scientific studies mostly rely on numerical simulations instead of hardware implementation. This paper addresses these gaps by proposing a ready-to-implement P2P energy trading scheme, demonstrating stability, fairness, and adherence to power network constraints. The proposed framework is validated in a real-time digital simulator platform, showing readiness for real-field trials.
IEEE TRANSACTIONS ON SMART GRID
(2023)
Article
Telecommunications
Jing Bai, Yuhao Chi, Chau Yuen
Summary: In this paper, an efficient decoding algorithm based on the generalized Bregman ADMM technique is proposed to improve the convergence speed of MP decoding using ADMM for binary LDPC codes. The G-BADMM algorithm is established by incorporating additional Bregman divergences into the ADMM iterations of MP decoding, and the resulting iterations are solved efficiently. The proposed G-BADMM algorithm is theoretically analyzed, including its decoding performance and computational complexity. Simulation results demonstrate the efficiency of the G-BADMM-based decoding algorithm.
IEEE COMMUNICATIONS LETTERS
(2023)