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Article
Energy & Fuels
Samy Aittahar et al.
Summary: This paper proposes a generic formulation for redistributing electricity generated by community members using repartition keys, and optimizes both controllable assets and repartition keys to minimize the combined total value of electricity bills. The results show that simultaneous optimization of controllable assets and repartition keys greatly reduces the electricity bills of community members.
FRONTIERS IN ENERGY RESEARCH
(2023)
Article
Computer Science, Artificial Intelligence
Adrien Bolland et al.
JOURNAL OF ARTIFICIAL INTELLIGENCE RESEARCH
(2022)
Article
Computer Science, Artificial Intelligence
B. D. Deebak et al.
Summary: The rapid development of information technologies has led to the transition towards intelligent manufacturing, with the application of digital-twin technology playing a key role. Industrial manufacturers are aiming to transform equipment into fully automated systems to meet future market demands. This article proposes a digital-twin-assisted fault diagnosis using deep transfer learning, showcasing the accuracy of an intelligent tool-holder in optimizing cutting tool operations.
INTERNATIONAL JOURNAL OF INTELLIGENT SYSTEMS
(2022)
Article
Energy & Fuels
Timothe Gronier et al.
Summary: Hydrogen is considered a promising vector for energy storage, particularly in heavy mobility applications. This paper examines the relevance of hydrogen in two storage applications and uses optimization methods to evaluate their performance. The study finds that hydrogen is not competitive with electrochemical storage in domestic power-to-power applications, but is more relevant and cost-effective in power-to-gas applications for mobility.
Article
Chemistry, Analytical
Jinsong Sang et al.
Summary: Microgrids face challenges such as small-scale volatility, uncertainty, intermittency and demand-side uncertainty of distributed energy resources (DERs). Traditional microgrids are unable to meet the flexible energy dispatch between complex demands and microgrids. This paper proposes an overall environment approach for microgrid control, which ensures power supply for flexible loads and minimizes input costs by considering the response priority of each component.
Article
Energy & Fuels
Yanhong Yang et al.
Summary: This article proposes a microgrid energy management strategy based on deep reinforcement learning, which utilizes a novel action exploration mechanism to learn about power output, electricity trading prices, and power load in microgrids. The simulation results demonstrate that the UCB-A3C learning-based strategy outperforms conventional PPO, actor-critic, and A3C algorithms.
FRONTIERS IN ENERGY RESEARCH
(2022)
Review
Engineering, Industrial
Fei Tao et al.
Summary: This paper provides a systematic research on the current studies of digital twin modeling and conducts a comprehensive and insightful analysis of digital twin models. It also investigates and summarizes the enabling technologies and tools for digital twin modeling and presents observations and future research recommendations.
JOURNAL OF MANUFACTURING SYSTEMS
(2022)
Article
Computer Science, Artificial Intelligence
Alessio Petrozziello et al.
Summary: In this study, the profitability of a deep LSTM Neural Network for forecasting stock market volatility is investigated. The results demonstrate the superiority of the LSTM over traditional parametric models in predicting high volatility.
Article
Construction & Building Technology
M. Z. Naser
Summary: This paper presents a framework that integrates explainable and anomalous machine learning algorithms into a digital twin for fine-tuning concrete mixtures. The framework has been rigorously examined on three case studies and has shown the capability to identify vulnerable concrete mixtures and achieve desired performance.
CEMENT & CONCRETE COMPOSITES
(2022)
Review
Energy & Fuels
Valery Vodovozov et al.
Summary: This paper discusses the challenges and development of fuel cell electric vehicles, specifically focusing on hydrogen-fueled buses in cities and urban environments. It identifies the key innovations and challenges in the field and evaluates approaches and errors using data from important energy sources. The study highlights the importance of energy consumption, efficiency, and production in the development of fuel cell electric buses. It also emphasizes the significance of using renewable energy sources for effective deployment.
Article
Engineering, Electrical & Electronic
Haodong Lu et al.
Summary: This paper proposes a framework for detecting anomalies in industrial robotic sensors, and improves the detection accuracy by using an improved GANs to generate fake anomaly samples. The effectiveness of the framework is demonstrated through extensive experiments.
IEEE SENSORS JOURNAL
(2022)
Article
Engineering, Industrial
Qinglin Qi et al.
Summary: Digital twin is revolutionizing industry by mirroring almost every facet of a product, process or service in the digital space. However, realizing their full potential is a complex process as researchers need to model different parts of objects or systems, collect and merge varied types of data, and struggle with determining the technologies and tools to be used. The 5-dimension digital twin model provides guidance for understanding and implementing digital twin technologies.
JOURNAL OF MANUFACTURING SYSTEMS
(2021)
Review
Engineering, Industrial
Mengnan Liu et al.
Summary: Engineering software and digitalized equipment are widely used in the industrial product lifecycle, generating massive data. The concept of digital twin has gained much attention and sparked debates. A comprehensive review of 240 academic publications reveals the research status, key technologies, and industrial applications of digital twin.
JOURNAL OF MANUFACTURING SYSTEMS
(2021)
Article
Engineering, Industrial
Min Xia et al.
Summary: The intelligent fault diagnosis framework based on DT and deep transfer learning enables accurate machine fault diagnosis with limited measured data. This method outperforms other state-of-the-art data-driven methods in achieving intelligent fault diagnosis.
RELIABILITY ENGINEERING & SYSTEM SAFETY
(2021)
Review
Energy & Fuels
Amrutha Raju Battula et al.
Summary: To address the increasing complexity of demand, conventional grids are incorporating communication technology like advanced metering with sensors, demand response, energy storage systems, and electric vehicles. Microgrids are proposed to maintain local energy balance and reliability, providing resilient operation and intelligent energy management techniques to control power exchange. This paper gives an overview of microgrids, their operations, energy management approaches, and the key role of energy management systems in maintaining balance and contributing to profit.
Article
Computer Science, Artificial Intelligence
Ioannis Boukas et al.
Summary: The paper proposes a novel modeling framework for the strategic participation of energy storage in the European continuous intraday market, aiming to maximize profits over the entire trading horizon while considering operational constraints. The Markov Decision Process is used to model the decision-making problem, with an asynchronous version of the fitted Q iteration algorithm chosen for solving it efficiently. Historical data is utilized for generating artificial trajectories to address exploration issues during the learning process, with the resulting policy back-tested against benchmark strategies to evaluate the impact of storage characteristics on total revenues.
Review
Green & Sustainable Science & Technology
Meiling Yue et al.
Summary: This paper reviews the current progress and outlook of hydrogen technologies and their application in power systems, highlighting the importance of hydrogen in clean energy and pointing out the technical and economic challenges that need to be addressed.
RENEWABLE & SUSTAINABLE ENERGY REVIEWS
(2021)
Review
Green & Sustainable Science & Technology
Saif Jamal et al.
Summary: In recent years, researchers have shown significant interest in managing energy and power through distributed generation systems, focusing on energy efficiency and global emission goals. They have conducted a comparative and critical review of recent developments in EMSs and PMSs, discussing various methods for reviewing MG and NG systems.
Article
Energy & Fuels
Wei He et al.
Summary: Current power systems heavily rely on fossil fuels, but the transition to renewable energy sources requires more efficient and widespread use of Electrical Energy Storage (EES) technologies. This review paper examines the challenges and opportunities in implementing EES in power systems, highlighting the need for accelerated uptake to decarbonize the power sector.
ADVANCES IN APPLIED ENERGY
(2021)
Review
Energy & Fuels
Sadaqat Ali et al.
Summary: The depletion of fossil fuels and the need for environmental protection have led to an energy crisis. Scientists have made positive developments in the past decade, introducing renewable energy sources and the concept of microgrids. While DC microgrids are appreciated for their efficiency and reliability, they are still relatively new in terms of grid architecture and control systems. Energy management systems are essential for optimizing the use of distributed energy resources in a secure, reliable, and intelligent manner.
Review
Computer Science, Information Systems
Maulshree Singh et al.
Summary: Digital Twin (DT) serves as a virtual copy of physical entities, interconnected in real time through data exchange, with wide applications and expected exponential growth. The complexity of Industry 4.0 system data generation adds to the confusion and lack of consensus surrounding DT terminology and types. Understanding the characteristics and types of DT, and weighing its pros and cons, is crucial for investors and industries.
APPLIED SYSTEM INNOVATION
(2021)
Review
Computer Science, Interdisciplinary Applications
Francisco Chinesta et al.
ARCHIVES OF COMPUTATIONAL METHODS IN ENGINEERING
(2020)
Article
Green & Sustainable Science & Technology
Fabian Dembski et al.
Review
Computer Science, Interdisciplinary Applications
Itxaro Errandonea et al.
COMPUTERS IN INDUSTRY
(2020)
Article
Computer Science, Information Systems
Adil Rasheed et al.
Article
Computer Science, Artificial Intelligence
Yu Zheng et al.
JOURNAL OF AMBIENT INTELLIGENCE AND HUMANIZED COMPUTING
(2019)
Article
Computer Science, Information Systems
Yan Xu et al.
Article
Meteorology & Atmospheric Sciences
Ronald Gelaro et al.
JOURNAL OF CLIMATE
(2017)
Article
Energy & Fuels
Rodolfo Dufo-Lopez et al.
Article
Agricultural Engineering
Jianbang Gan et al.
BIOMASS & BIOENERGY
(2011)
