Article
Energy & Fuels
Caishan Guo, Fengji Luo, Zexiang Cai, Zhao Yang Dong, Rui Zhang
Summary: This paper proposes an integrated planning scheme to optimally determine the locations and capacities of interconnected Internet data centers and battery energy storage systems in a smart grid, considering both the computational performance metrics of data centers and the operational criteria of the grid. It uses a Multi-Objective Natural Aggregation Algorithm to solve the model and conducts extensive case studies to demonstrate the reasonability and effectiveness of the proposed method.
Article
Computer Science, Information Systems
Georgios Tsaousoglou, Polyzois Soumplis, Nikolaos Efthymiopoulos, Konstantinos Steriotis, Aristotelis Kretsis, Prodromos Makris, Panagiotis Kokkinos, Emmanouel Varvarigos
Summary: The uncertain and non-dispatchable nature of renewable energy sources makes Demand Response (DR) an essential component of modern electricity distribution systems. This article presents a distributed DR market clearing algorithm based on Lagrangian decomposition, combined with an optimal cloud resource allocation algorithm. Simulations demonstrate the near-optimal performance of this algorithm and its ability to meet the demands of multiple DR requests.
IEEE TRANSACTIONS ON CLOUD COMPUTING
(2022)
Article
Computer Science, Information Systems
Xu Xu, Yuxiao Fan, Xiaohua Wang
Summary: The purpose of this research is to establish a Mass Customization oriented Customer Demand Response service platform based on Cloud Computing and the Internet of Things. By utilizing the edge-cloud collaborative computing method, it can improve resource utilization and reduce operational costs effectively.
Article
Computer Science, Theory & Methods
Shivananda R. Poojara, Chinmaya Kumar Dehury, Pelle Jakovits, Satish Narayana Srirama
Summary: With the growth of IoT devices, the need for efficient data processing and analytics is increasing. This study explores the benefits of using Serverless data pipelines for IoT data analytics and evaluates different approaches for designing such pipelines. The results reveal the suitability of different design methods for different types of applications.
FUTURE GENERATION COMPUTER SYSTEMS-THE INTERNATIONAL JOURNAL OF ESCIENCE
(2022)
Article
Computer Science, Information Systems
Caishan Guo, Fengji Luo, Jiajia Yang, Zexiang Cai
Summary: This paper proposes a two-stage transactive operation framework for a group of geo-distributed IDCs to engage in local energy markets. In the first stage, an ex-ante bidding model is proposed to optimize the IDCs' cyber-energy resources and determine energy trading prices. In the second stage, a real-time energy balancing model is proposed to adjust the IDCs' energy volumes and offer energy balancing services to power distribution networks.
IEEE TRANSACTIONS ON CLOUD COMPUTING
(2023)
Article
Computer Science, Theory & Methods
Yaru Liu, Jia Yu, Ming Yang, Wenqiang Hou, Huaqun Wang
Summary: With the deep integration of cloud computing and Internet of Things, privacy preserving keyword search techniques have gained importance. Forward security and verifiability are two important security properties for privacy preserving keyword search. This study proposes a scheme that simultaneously achieves forward security and full verification in protecting privacy for keyword search.
FUTURE GENERATION COMPUTER SYSTEMS-THE INTERNATIONAL JOURNAL OF ESCIENCE
(2022)
Article
Operations Research & Management Science
R. Dhaya, R. Kanthavel, Kanagaraj Venusamy
Summary: Large data centers and cloud computing frameworks are crucial for providing efficient services to trade, governments, and academic and research institutions. Private cloud computing systems promote collaboration among industries, academic institutions, and research labs, fostering studies in programming, network infrastructure, and technology.
ANNALS OF OPERATIONS RESEARCH
(2023)
Article
Computer Science, Information Systems
Changhee Hahn, Jongkil Kim
Summary: This article investigates two state-of-the-art schemes for verifiable outsourced decryption of encrypted data and identifies their vulnerabilities. It then proposes a securitywise enhanced encoding scheme and conducts a rigorous security analysis. Experimental results show that the proposed method outperforms the other two schemes in terms of encoding computation cost.
IEEE INTERNET OF THINGS JOURNAL
(2022)
Article
Computer Science, Theory & Methods
Kanika Saini, Sheetal Kalra, Sandeep K. Sood
Summary: In this study, an intelligent evacuation system is proposed that integrates IoT, fog layer, and cloud layer to efficiently and accurately guide evacuees to safer locations while significantly reducing direct fire exposure.
FUTURE GENERATION COMPUTER SYSTEMS-THE INTERNATIONAL JOURNAL OF ESCIENCE
(2022)
Article
Computer Science, Theory & Methods
Muhammad Habib Ur Rehman, Chee Sun Liew, Teh Ying Wah, Muhammad Imran, Khaled Salah, Nidal Nasser, Davor Svetinovic
Summary: The paper introduces an adaptive execution model for mobile data stream mining applications in MECC environments, which is successfully integrated with multiple MDSM applications. Evaluations show that the proposed adaptive execution model outperforms static and dynamic execution models in various metrics.
FUTURE GENERATION COMPUTER SYSTEMS-THE INTERNATIONAL JOURNAL OF ESCIENCE
(2021)
Article
Computer Science, Information Systems
Yulei Wu
Summary: The Internet of Things is widely utilized in various critical sectors, requiring efficient data processing. AI-powered cloud-edge orchestration provides crucial computing support for IoT applications.
IEEE INTERNET OF THINGS JOURNAL
(2021)
Article
Computer Science, Information Systems
Dapeng Wu, Meiyu Sun, Puning Zhang, Yanli Tu, Zhigang Yang, Ruyan Wang
Summary: Demand-oriented data service can conveniently and quickly provide physical entity information for IoT users. Traditional cloud-oriented data service architecture is not suitable for state time-varying and privacy-sensitive entity data in IoT. Edge-based architecture lacks global service function but can alleviate problems with cloud services. Existing demand-oriented data service ignores the characteristics of thousands of people have thousands of faces and the implicit intents of users, resulting in limited service quality and weak user experience. To solve these problems, a personalized secure demand-oriented data service scheme is proposed.
IEEE INTERNET OF THINGS JOURNAL
(2023)
Article
Computer Science, Information Systems
Hong-Yen Lo, Wanjiun Liao
Summary: The study focuses on survivability of virtual data centers and proposes the CALM algorithm to minimize network resource usage and ensure survivability after hardware failures.
IEEE TRANSACTIONS ON SERVICES COMPUTING
(2021)
Article
Computer Science, Artificial Intelligence
Bo You, Xiao Xiao
Summary: 5G cloud computing, as a new calculation method, offers convenient and fast services to enterprises and users, with characteristics of stability, reasonableness, and easy operation. However, private cloud storage may not extend its scale, capabilities, and openness to cloud computing platforms. Therefore, hybrid cloud computing is the future trend, and ensuring efficient and secure data storage and information consistency relies on data encryption technology.
Article
Computer Science, Software Engineering
Ramana B. Reddy, M. Indiramma
Summary: Cloud computing is an emerging service that has experienced rapid growth in the past decade. The proposed Efficient Throttled load balancing algorithm improves performance significantly in the data center environment, as demonstrated in experimental results.
CONCURRENCY AND COMPUTATION-PRACTICE & EXPERIENCE
(2022)
Article
Energy & Fuels
Shitong Fang, Houfan Du, Tao Yan, Keyu Chen, Zhiyuan Li, Xiaoqing Ma, Zhihui Lai, Shengxi Zhou
Summary: This paper proposes a new type of nonlinear VIV energy harvester (ANVEH) that compensates for the decrease in peak energy output at low wind speeds by introducing an auxiliary structure. Theoretical and experimental results show that ANVEH performs better than traditional nonlinear VIV energy harvesters under various system parameter variations.
Article
Energy & Fuels
Wei Jiang, Shuo Zhang, Teng Wang, Yufei Zhang, Aimin Sha, Jingjing Xiao, Dongdong Yuan
Summary: A standardized method was developed to evaluate the availability of solar energy resources in road areas, which combined the Analytic Hierarchy Process (AHP) and the Geographic Information System (GIS). By analyzing critical factors and using a multi-indicator evaluation method, the method accurately evaluated the utilization of solar energy resources and guided the optimal location selection for road photovoltaic (PV) projects. The results provided guidance for the application of road PV projects and site selection for route corridors worldwide, promoting the integration of transportation and energy.
Article
Energy & Fuels
Chang Liu, Jacob A. Wrubel, Elliot Padgett, Guido Bender
Summary: The study investigates the effects of coating defects on the performance of the anode porous transport layer (PTL) in water electrolyzers. The results show that an increasing fraction of uncoated regions on the PTL leads to decreased cell performance, with continuous uncoated regions having a more severe impact compared to multiple thin uncoated strips.
Article
Energy & Fuels
Marcos Tostado-Veliz, Xiaolong Jin, Rohit Bhakar, Francisco Jurado
Summary: In this paper, a coordinated charging price mechanism for clusters of parking lots is proposed. The research shows that enabling vehicle-to-grid characteristics can bring significant economic benefits for users and the cluster coordinator, and vehicle-to-grid impacts noticeably on the risk-averse character of the uncertainty-aware strategies. The developed pricing mechanism can reduce the cost for users, avoiding to directly translate the energy cost to charging points.
Article
Energy & Fuels
Duan Kang
Summary: Building an energy superpower is a key strategy for China and a long-term goal for other countries. This study proposes an evaluation system and index for measuring energy superpower, and finds that China has significantly improved its ranking over the past 21 years, surpassing other countries.
Article
Energy & Fuels
Fucheng Deng, Yifei Wang, Xiaosen Li, Gang Li, Yi Wang, Bin Huang
Summary: This study investigated the synergistic blockage mechanism of sand and hydrate in gravel filling layer and the evolution of permeability in the layer. Experimental models and modified permeability models were established to analyze the effects of sand particles and hydrate formation on permeability. The study provided valuable insights for the safe and efficient exploitation of hydrate reservoirs.
Article
Energy & Fuels
Hao Wang, Xiwen Chen, Natan Vital, Edward Duffy, Abolfazl Razi
Summary: This study proposes a HVAC energy optimization model based on deep reinforcement learning algorithm. It achieves 37% energy savings and ensures thermal comfort for open office buildings. The model has a low complexity, uses a few controllable factors, and has a short training time with good generalizability.
Article
Energy & Fuels
Moyue Cong, Yongzhuo Gao, Weidong Wang, Long He, Xiwang Mao, Yi Long, Wei Dong
Summary: This study introduces a multi-strategy ultra-wideband energy harvesting device that achieves high power output without the need for external power input. By utilizing asymmetry, stagger array, magnetic coupling, and nonlinearity strategies, the device maintains a stable output voltage and high power density output at non-resonant frequencies. Temperature and humidity monitoring are performed using Bluetooth sensors to adaptively assess the device.
Article
Energy & Fuels
Tianshu Dong, Xiudong Duan, Yuanyuan Huang, Danji Huang, Yingdong Luo, Ziyu Liu, Xiaomeng Ai, Jiakun Fang, Chaolong Song
Summary: Electrochemical water splitting is crucial for hydrogen production, and improving the hydrogen separation rate from the electrode is essential for enhancing water electrolyzer performance. However, issues such as air bubble adhesion to the electrode plate hinder the process. Therefore, a methodology to investigate the two-phase flow within the electrolyzer is in high demand. This study proposes using a microfluidic system as a simulator for the electrolyzer and optimizing the two-phase flow by manipulating the micro-structure of the flow.
Article
Energy & Fuels
Shuo Han, Yifan Yuan, Mengjiao He, Ziwen Zhao, Beibei Xu, Diyi Chen, Jakub Jurasz
Summary: Giving full play to the flexibility of hydropower and integrating more variable renewable energy is of great significance for accelerating the transformation of China's power energy system. This study proposes a novel day-ahead scheduling model that considers the flexibility limited by irregular vibration zones (VZs) and the probability of flexibility shortage in a hydropower-variable renewable energy hybrid generation system. The model is applied to a real hydropower station and effectively improves the flexibility supply capacity of hydropower, especially during heavy load demand in flood season.
Article
Energy & Fuels
Zhen Wang, Kangqi Fan, Shizhong Zhao, Shuxin Wu, Xuan Zhang, Kangjia Zhai, Zhiqi Li, Hua He
Summary: This study developed a high-performance rotary energy harvester (AI-REH) inspired by archery, which efficiently accumulates and releases ultralow-frequency vibration energy. By utilizing a magnetic coupling strategy and an accumulator spring, the AI-REH achieves significantly accelerated rotor speeds and enhanced electric outputs.
Article
Energy & Fuels
Yi Yang, Qianyi Xing, Kang Wang, Caihong Li, Jianzhou Wang, Xiaojia Huang
Summary: In this study, a novel hybrid Quantile Regression (QR) model is proposed for Probabilistic Load Forecasting (PLF). The model integrates causal dilated convolution, residual connection, and Bidirectional Long Short-Term Memory (BiLSTM) for multi-scale feature extraction. In addition, a Combined Probabilistic Load Forecasting System (CPLFS) is proposed to overcome the inherent flaws of relying on a single model. Simulation results show that the hybrid QR outperforms traditional models and CPLFS exceeds the best benchmarks in terms of prediction accuracy and stability.
Article
Energy & Fuels
Wen-Jiang Zou, Young-Bae Kim, Seunghun Jung
Summary: This paper proposes a dynamic prediction model for capacity fade in vanadium redox flow batteries (VRFBs). The model accurately predicts changes in electrolyte volume and capacity fade, enhancing the competitiveness of VRFBs in energy storage applications.
Article
Energy & Fuels
Yuechao Ma, Shengtie Wang, Guangchen Liu, Guizhen Tian, Jianwei Zhang, Ruiming Liu
Summary: This paper focuses on the balance of state of charge (SOC) among multiple battery energy storage units (MBESUs) and bus voltage balance in an islanded bipolar DC microgrid. A SOC automatic balancing strategy is proposed considering the energy flow relationship and utilizing the adaptive virtual resistance algorithm. The simulation results demonstrate the effectiveness of the proposed strategy in achieving SOC balancing and decreasing bus voltage unbalance.
Article
Energy & Fuels
Raad Z. Homod, Basil Sh. Munahi, Hayder Ibrahim Mohammed, Musatafa Abbas Abbood Albadr, Aissa Abderrahmane, Jasim M. Mahdi, Mohamed Bechir Ben Hamida, Bilal Naji Alhasnawi, A. S. Albahri, Hussein Togun, Umar F. Alqsair, Zaher Mundher Yaseen
Summary: In this study, the control problem of the multiple-boiler system (MBS) is formulated as a dynamic Markov decision process and a deep clustering reinforcement learning approach is applied to obtain the optimal control policy. The proposed strategy, based on bang-bang action, shows superior response and achieves more than 32% energy saving compared to conventional fixed parameter controllers under dynamic indoor/outdoor actual conditions.