Article
Energy & Fuels
Sho Cremers, Valentin Robu, Peter Zhang, Merlinda Andoni, Sonam Norbu, David Flynn
Summary: With the emergence of energy communities, the fair allocation of benefits becomes increasingly important. This paper reviews the use of Shapley value in energy-related applications and the efforts to compute or approximate it. A new method, called the stratified expected value approximation, is proposed for approximating the Shapley value in community energy settings. The performance of this method is compared with other existing methods, and the results show that it is comparable to the state-of-the-art method with a significantly lower computation cost for large communities.
Article
Computer Science, Hardware & Architecture
K. P. Naveen, Rajesh Sundaresan
Summary: The study examines a double-auction mechanism in the context of rate allocation in mobile data-offloading and network slicing markets, discussing strategic behaviors of agents (users and link-suppliers) and efficiency losses in different scenarios. A modified Stackelberg game approach is proposed to address efficiency losses, establishing a game between link-suppliers and users through bidding and response mechanisms.
IEEE-ACM TRANSACTIONS ON NETWORKING
(2021)
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
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
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
Automation & Control Systems
Liyang Han, Thomas Morstyn, Malcolm McCulloch
Summary: This paper investigates a cooperative game theory framework for peer-to-peer energy markets and adapts a stratified sampling method for Shapley value estimation, proposing a multi-step sampling strategy to improve scalability. The selected case studies demonstrate that the proposed method effectively scales up the game from 20 players to 100 players.
INTERNATIONAL JOURNAL OF CONTROL AUTOMATION AND SYSTEMS
(2021)
Article
Mathematics
Riya Kakkar, Rajesh Gupta, Smita Agrawal, Pronaya Bhattacharya, Sudeep Tanwar, Maria Simona Raboaca, Fayez Alqahtani, Amr Tolba
Summary: This paper proposes a scheme that combines blockchain and a truthful double auction strategy to address the energy management problem in electric vehicles. By using the Interplanetary File System and Fifth Generation networks, scalability and communication latency can be improved. Simulation results show that the scheme outperforms traditional methods in terms of reliability, scalability, and cost-efficiency.
Article
Engineering, Electrical & Electronic
Kosala Yapa Bandara, Subhasis Thakur, John Breslin
Summary: This study introduces a trading algorithm based on flocking behavior and distributed double auction for peer-to-peer trading of renewable energy within neighborhoods. Mathematical analysis and experimental results demonstrate that the algorithm has a high success rate and fast convergence, ensuring trading within neighborhoods.
INTERNATIONAL JOURNAL OF ELECTRICAL POWER & ENERGY SYSTEMS
(2021)
Article
Energy & Fuels
Simon Voswinkel, Jonas Hoeckner, Abuzar Khalid, Christoph Weber
Summary: As energy generation becomes more decentralized, congestion management across grid voltage levels is increasingly necessary. This study proposes using the Shapley value to allocate congestion costs among grid elements, offering fair sharing of costs among operators. Two novel simplification approaches are introduced to reduce computational complexity, resulting in significant reductions in time and resources. These methods have the potential for application in other games with similar properties.
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
Computer Science, Information Systems
Jiandong Wang, Hao Liu, Xuewen Dong, Yulong Shen, Xinghui Zhu, Bin Wang, Feng Li
Summary: This article proposes a double MCS auction mechanism with a personalized location privacy incentive, which can meet the competition requirement of task requesters and the task preference variance of workers. The mechanism introduces the concept of privacy budget, allowing workers to decide how much location information to disclose to the platform for personalized location privacy protection. In addition, each worker can offer multiple bids for interested tasks and perform a subset of tasks in a bid if wins. Experimental results validate that the mechanism satisfies budget balance, individual rationality, and 2-D-truthfulness.
IEEE INTERNET OF THINGS JOURNAL
(2023)
Article
Operations Research & Management Science
Sylvain Beal, Adriana Navarro-Ramos, Eric Remila, Philippe Solal
Summary: This study considers the cost sharing issue in the maintenance of a hazardous waste transportation network and introduces the Liability rule, which is axiomatically characterized. It is shown that the Liability rule coincides with the Priority Shapley value on an appropriate domain of multi-choice games arising from hazardous waste transportation problems. Furthermore, the Priority Shapley value on the full domain of multi-choice games is axiomatized.
ANNALS OF OPERATIONS RESEARCH
(2023)
Article
Energy & Fuels
Yuekuan Zhou
Summary: This study proposes a spatiotemporal energy network in the Guangdong-Hong Kong-Macao Greater Bay Area, which addresses the regional imbalance distribution, dynamic intermittence, and fluctuation of renewable resources through smart transportation for energy sharing. By implementing advanced energy pricing policies and energy interaction modes, stakeholders' participation willingness can be economically incentivized.
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
Energy & Fuels
Daniele Porcu, Sonia Castro, Borja Otura, Paula Encinar, Ioannis Chochliouros, Irina Ciornei, Lenos Hadjidemetriou, Georgios Ellinas, Rita Santiago, Elisavet Grigoriou, Angelos Antonopoulos, Nicola Cadenelli, Nicola di Pietro, August Betzler, Inmaculada Prieto, Fabrizio Battista, Dimitrios Brodimas, Ralitsa Rumenova, Athanasios Bachoumis
Summary: With the increasing complexity of electric systems, 5G mobile network technology offers a promising solution for smart grids to address grid performance issues by enabling higher data exchange, high availability of telecommunication infrastructure, and low latency. This article presents the vision of the Smart5Grid project on how 5G can support the energy industry in deploying innovative digital services quickly, showcasing four real-life 5G-enabled demonstrators.
Article
Computer Science, Information Systems
Ioannis Zenginis, John Vardakas, Nikolaos E. Koltsaklis, Christos Verikoukis
Summary: This article presents a reinforcement-learning based real-time energy management scheme for smart homes. The scheme aims to minimize electricity cost and residents' thermal discomfort through the appropriate scheduling of storage devices and HVAC systems. The study's main contribution is the development of a clustering process that partitions the training data set into more homogeneous subsets, allowing for more efficient energy schedules.
IEEE INTERNET OF THINGS JOURNAL
(2022)
Article
Engineering, Electrical & Electronic
Hatim Chergui, Luis Blanco, Christos Verikoukis
Summary: The paper introduces a new statistical federated learning (SFL) model that can learn non-independent identically distributed datasets in an offline fashion while respecting slice-level service level agreement (SLA) statistical constraints. By considering resource SLA metrics and constraints, and using the proxy-Lagrangian framework for smooth approximation, SFL significantly reduces overhead while enabling SLA enforcement.
IEEE TRANSACTIONS ON WIRELESS COMMUNICATIONS
(2022)
Article
Engineering, Electrical & Electronic
Behnam Ojaghi, Ferran Adelantado, Angelos Antonopoulos, Christos Verikoukis
Summary: This paper discusses the challenges and open issues of joint slicing and functional splitting, taking into account the complexity introduced by multiple slices and different functional splits. Depending on the density of RAN deployment, the additional complexity may be justified by the potential benefits.
IEEE COMMUNICATIONS MAGAZINE
(2022)
Article
Computer Science, Information Systems
Behnam Ojaghi, Ferran Adelantado, Angelos Antonopoulos, Christos Verikoukis
Summary: 5G mobile networks are designed to support new vertical services with different performance requirements. Slicing in the radio access network offers an efficient solution for diverse 5G network needs by separating base station functionality between the CU and distributed remote radio heads. The proposed MIP framework and heuristic algorithm optimize throughput by slicing RAN, achieving near-optimal solutions in a short computing time.
IEEE SYSTEMS JOURNAL
(2022)
Article
Computer Science, Information Systems
Massimiliano Maule, John S. Vardakas, Christos Verikoukis
Summary: Network slicing is crucial for 5G and future networks, enabling independent execution environments for logical networks with different functionalities. This article introduces a real-time NS management framework for 5G New-Radio, which achieves slice resource management through dynamic evaluation of user quality of service and tenant service level agreements.
IEEE SYSTEMS JOURNAL
(2022)
Article
Engineering, Electrical & Electronic
Farhad Rezazadeh, Lanfranco Zanzi, Francesco Devoti, Hatim Chergui, Xavier Costa-Perez, Christos Verikoukis
Summary: Network slicing allows for the instantiation and customization of multiple virtual networks to meet the diverse requirements of 5G and beyond network deployments. Current solutions face scalability issues when dealing with numerous slices, as centralized controllers need a comprehensive view of resource availability and consumption across various networking domains. To address this challenge, we propose a hierarchical architecture that manages network slice resources in a federated manner. By employing traffic-aware local decision agents (DAs) in the radio access network (RAN), which leverage the advancements in deep reinforcement learning (DRL) schemes and the Open RAN (O-RAN) paradigm, our approach achieves better resource efficiency by adapting resource allocation policies to the underlying traffic dynamics and reducing interactions with centralized controllers.
IEEE TRANSACTIONS ON VEHICULAR TECHNOLOGY
(2023)
Article
Engineering, Electrical & Electronic
Behnam Ojaghi, Ferran Adelantado, Christos Verikoukis
Summary: Next-Generation (NG) mobile networks are expected to revolutionize wireless communication systems, facilitating the deployment of critical applications.
IEEE TRANSACTIONS ON VEHICULAR TECHNOLOGY
(2023)
Article
Engineering, Electrical & Electronic
Massimiliano Maule, John S. Vardakas, Christos Verikoukis
Summary: In this paper, a novel radio access network orchestrator that combines network function placement and resource allocation techniques is proposed. The results show significant improvements in performance and resource utilization compared to traditional schemes.
IEEE TRANSACTIONS ON VEHICULAR TECHNOLOGY
(2023)
Article
Engineering, Civil
Anestis Dalgkitsis, Luis A. Garrido, Farhad Rezazadeh, Hatim Chergui, Kostas Ramantas, John S. Vardakas, Christos Verikoukis
Summary: The development of SDN and NFV has brought about challenges in network management. Dynamic service orchestration and adaptive resource allocation are necessary to handle the growth of users and data-intensive applications. The impact of network automation on energy consumption and operating costs is often neglected. This paper focuses on reducing latency and improving energy efficiency in beyond-5G networks through zero-touch Service Function Chain (SFC) orchestration, and proposes a distributed Reinforcement Learning (RL) based framework.
IEEE TRANSACTIONS ON INTELLIGENT TRANSPORTATION SYSTEMS
(2023)
Article
Engineering, Electrical & Electronic
Roshan Sedar, Charalampos Kalalas, Francisco Vazquez-Gallego, Luis Alonso, Jesus Alonso-Zarate
Summary: Recent advancements in V2X communication have improved connectivity and driving autonomy. However, there are security vulnerabilities and threats. This paper provides a comprehensive review of security enhancements, classifies V2X attacks, and explores the potential of AI-based security approaches. It also summarizes open challenges and future research directions.
IEEE OPEN JOURNAL OF THE COMMUNICATIONS SOCIETY
(2023)
Article
Computer Science, Information Systems
Ioannis Zenginis, John Vardakas, Nikolaos E. Koltsaklis, Christos Verikoukis
Summary: In this study, a reinforcement learning-based method for energy scheduling in smart homes is proposed, aiming to minimize electricity cost, residents' thermal discomfort, and EV users' range anxiety. The results show significant improvement compared to other RL-based approaches in existing literature.
IEEE SYSTEMS JOURNAL
(2023)
Proceedings Paper
Computer Science, Artificial Intelligence
Ioannis P. Chochliouros, Daniele Porcu, Dimitrios Brothimas, Nikolaos Tzanis, Nikolay Palov, Ralitsa Rumenova, Angelos Antonopoulos, Nicola Cadenelli, Markos Asprou, Lenos Hadjidemetriou, Sonia Castro, Pencho Zlatev, Bogdan Bogdanov, Thanassis Bachoumis, Antonello Corsi, Helio Simeao, Michalis Rantopoulos, Christina Lessi, Pavlos Lazaridis, Zaharias Zaharis, Anastasia S. Spiliopoulou
Summary: The deployment of smart grids can be greatly supported and enhanced by the expansion of 5G infrastructures, particularly at the distribution side where the number of monitoring devices and automation equipment exponentially increases. This article focuses on two selected use cases in the energy vertical sector, namely millisecond level precise distributed generation monitoring and realtime wide area monitoring. The need for including 5G facilities is emphasized.
ARTIFICIAL INTELLIGENCE APPLICATIONS AND INNOVATIONS. AIAI 2022 IFIP WG 12.5 INTERNATIONAL WORKSHOPS
(2022)
Proceedings Paper
Computer Science, Artificial Intelligence
Ioannis P. Chochliouros, Daniele Porcu, Sonia Castro, Borja Otura, Paula Encinar, Antonello Corsi, Irina Ciornei, Rita Santiago, Angelos Antonopoulos, Nicola Cadenelli, Nicola di Pietro, August Betzler, Inmaculada Prieto, Fabrizio Batista, Elisavet Grigoriou, Georgios Ellinas, Lenos Hadjidemetriou, Dimitrios Brothimas, Ralitsa Rumenova, Athanasios Bachoumis, Anastasia S. Spiliopoulou, Michalis Rantopoulos, Christina Lessi, Dimitrios Arvanitozisis, Pavlos Lazaridis
Summary: This paper examines fundamental features of the Smart5Grid platform that can affect the implementation of 5G and NetApps. The specific context of smart energy grids, cloud native environment, and MEC environment are evaluated compared to the state of the Smart5Grid platform. A preliminary framework for defining NetApps is proposed based on the incorporation of these essential features in the project processes.
ARTIFICIAL INTELLIGENCE APPLICATIONS AND INNOVATIONS. AIAI 2022 IFIP WG 12.5 INTERNATIONAL WORKSHOPS
(2022)
