Article
Chemistry, Multidisciplinary
Moises Cordeiro-Costas, Daniel Villanueva, Andres E. Feijoo-Lorenzo, Javier Martinez-Torres
Summary: A method is proposed in this paper to synthetically generate sequences of wind speed values satisfying statistical distributions and imposing spatial and temporal correlations. The method was successfully checked under different scenarios, with high accuracy in the results.
APPLIED SCIENCES-BASEL
(2021)
Article
Green & Sustainable Science & Technology
Fabio Sandro dos Santos, Kerolly Kedma Felix do Nascimento, Jader da Silva Jale, SilvioFernando Alves Xavier Junior, Tiago A. E. Ferreira
Summary: With increasing concerns about the greenhouse effect and carbon dioxide levels, it is necessary to curtail the use of fossil fuels. In this study, a Weibull-Weibull distribution mixture was applied to adjust wind speed data from 575 weather stations, and wind energy generation was predicted. The model performed well and provided suitable fits for different regions in Brazil.
RENEWABLE & SUSTAINABLE ENERGY REVIEWS
(2024)
Article
Green & Sustainable Science & Technology
Biao Li, Tao Wang, Zhen Dong, Qian Geng, Yi Sun
Summary: The asset wall (AW) model is widely used by energy companies for equipment retirement size forecasting. However, this model ignores technological improvements and price fluctuations. In this paper, a modified model called WMCAW is proposed, which incorporates Weibull distribution and Monte Carlo stochastic simulation to determine the retirement age of each equipment. The study also investigates the assetization of equipment replacement size. The results show that the WMCAW model provides smoother and more stable forecasting compared to AW.
Article
Thermodynamics
Ali Akbar Abdoos, Hatef Abdoos, Javad Kazemitabar, Mohammad Mehdi Mobashsher, Hooman Khaloo
Summary: This article presents a probabilistic intelligent method for wind power prediction to minimize the risk caused by the uncertainty of the generated power. The method includes analyzing wind power time series signals, creating training patterns, training patterns using machine learning, and making probabilistic predictions based on Monte-Carlo simulation. The results show that the method accurately predicts wind power generation in 10-minute intervals and can be effectively applied to both deterministic and probabilistic predictions.
Article
Mechanics
Da Gao, Bijiao He, Chenggeng Wu, Guobiao Cai, Lihui Liu
Summary: This study compares the energy distribution of the chemical reaction C O-2 + O ? CO + O-2 using the Larsen-Borgnakke (L-B) and Q-K methods, and finds that only the Q-K method achieves detailed balance. The study also indicates that detailed balance is reached only when the collision temperature is used to adjust the activation energy, rather than the translational temperature.
Article
Energy & Fuels
Yantai Lin, Tianyao Ji, Yuzi Jiang, Q. H. Wu
Summary: This paper proposes a novel non-parametric copula method, MGKC, to describe the dependence structure of wind speeds among multiple wind farms. Wind speed scenarios are sampled from the MGKC and applied to solve the stochastic economic dispatch problem. Simulation studies demonstrate the effectiveness of the proposed method.
CSEE JOURNAL OF POWER AND ENERGY SYSTEMS
(2022)
Article
Computer Science, Interdisciplinary Applications
Alessandro De Carlo, Elena Maria Tosca, Nicola Melillo, Paolo Magni
Summary: Pharmacometrics (PMX) is a quantitative discipline that utilizes Modeling and Simulations (M&S) to characterize and predict the behavior and effect of drugs. The introduction of correlation structure between model parameters in PMX simulations poses challenges. The mvLognCorrEst R package presented in this paper addresses these challenges by providing a sampling strategy and estimation methods for correlated lognormal distributions.
COMPUTER METHODS AND PROGRAMS IN BIOMEDICINE
(2023)
Article
Materials Science, Ceramics
Yoshito Ikarashi, Toshio Ogasawara, Shin-ichi Okuizumi, Takuya Aoki, Ian J. Davies, Jacques Lamon
Summary: This study evaluated the tensile strength distributions of five types of silicon carbide fibers using monofilament and multifilament tow tensile testing methods. The Weibull parameters were estimated and compared between the two methods. The results showed similar Weibull scale parameters for both methods, but the Weibull shape parameter obtained from multifilament tow testing tended to be greater. Monte-Carlo simulations were conducted to investigate the effect of diameter variation within individual fibers on the multifilament tow test results, and the simulation results showed good agreement with the monofilament test results.
JOURNAL OF THE EUROPEAN CERAMIC SOCIETY
(2022)
Article
Computer Science, Information Systems
Xiaoxuan Guo, Haibo Bao, Jing Xiao, Shaonan Chen
Summary: The paper proposes an interval power flow model that considers wind power correlation and utilizes affine transformation technique for decorrelating wind power output. The results demonstrate the effectiveness and feasibility of the method in simulations.
Article
Mathematics
Sajid Hussain, Muhammad Sajid Rashid, Mahmood Ul Hassan, Rashid Ahmed
Summary: Here, a new method is recommended to characterize a new continuous distribution class, named the generalized alpha exponent power family of distributions (GAEPFDs). The basic statistical properties of GAEPFDs, such as ordinary moments, entropy measures, and moment generating functions, were explored. The ML technique was used for parameter estimation and the effectiveness of GAEPFDs was demonstrated through lifetime data.
Article
Management
Joseph L. Breeden, Yevgeniya Leonova
Summary: This article develops a Monte Carlo method that estimates the loss distribution for a single loan, allowing for a better understanding of the risk distribution due to modelling and macroeconomic uncertainty. The study finds that the Monte Carlo simulation results fit well with a Lognormal distribution. Additionally, the feasibility of using quantum computers for the calculations is explored, showing potential for significant speed enhancement, albeit with the need for further quantum algorithm development for the full analysis of competing risks.
JOURNAL OF THE OPERATIONAL RESEARCH SOCIETY
(2023)
Article
Thermodynamics
Gyeongmin Kim, Jin Hur
Summary: The article proposes a probabilistic modeling approach for wind energy potential in grid expansion planning and validates the model's effectiveness through empirical data.
Editorial Material
Operations Research & Management Science
Hon Keung Tony Ng
Summary: Specifying prior distributions in Bayesian analysis is a complex problem, especially without a conjugate prior. Tian et al. (Appl Stoch Models Bus Ind; 2023) address this issue for reliability data and propose coherent approaches. The focus of this discussion is on specifying prior distributions based on aging behavior or hazard function and examining the impact of mis-specifying informative priors. A Monte Carlo simulation study using Type 2 censored data from Weibull distribution demonstrates the performance of estimation procedures based on informative and non-informative priors.
APPLIED STOCHASTIC MODELS IN BUSINESS AND INDUSTRY
(2023)
Article
Thermodynamics
Dohyung Jang, Kilwon Kim, Kyong-Hwan Kim, Sanggyu Kang
Summary: This study presents a techno-economic analysis of three offshore wind power plant arrangements, indicating that the distributed hydrogen production case is the most competitive due to the absence of expensive equipment, although it is necessary to maintain capacity factor. Sensitivity analysis shows it is necessary to maintain capacity factor.
ENERGY CONVERSION AND MANAGEMENT
(2022)
Article
Green & Sustainable Science & Technology
Duong Minh Ngoc, Kuaanan Techato, Le Duc Niem, Nguyen Thi Hai Yen, Nguyen Van Dat, Montri Luengchavanon
Summary: A novel small-scale vertical axis wind turbine tree was designed with Darrieus and Savonius blades, and economic viability was tested using wind data from Surat Thani, Thailand. Results showed that the prototype had potential economic feasibility at locations with higher wind speeds, such as Chiang Mai, while showing a lack of economic viability at the specific Surat Thani location.
Article
Energy & Fuels
Siyu Tao, Andres Feijoo, Jiemin Zhou, Gang Zheng
Article
Green & Sustainable Science & Technology
Vartika Paliwal, Aniruddha D. Ghare, Ashwini B. Mirajkar, Neeraj Dhanraj Bokde, Andres Elias Feijoo Lorenzo
Review
Energy & Fuels
Aditya Dinesh Gupta, Prerna Pandey, Andres Feijoo, Zaher Mundher Yaseen, Neeraj Dhanraj Bokde
Article
Engineering, Electrical & Electronic
Siyu Tao, Qingshan Xu, Andres Feijoo, Gang Zheng
Summary: A bi-level multi-objective optimization framework is proposed in this study to design the configuration of wind turbines and the topology of the electrical collector system in an offshore wind farm for better performance. The outer-layer model optimizes the daily profit rate, daily average capacity factor, and power quality, while the inner layer models determine the electrical system topology and generation schedule of other generators.
IEEE TRANSACTIONS ON SMART GRID
(2021)
Review
Energy & Fuels
Manisha Sawant, Sameer Thakare, A. Prabhakara Rao, Andres E. Feijoo-Lorenzo, Neeraj Dhanraj Bokde
Summary: Over the past few decades, extensive research has been carried out in the field of wind energy technology, leading to the publication of numerous state-of-the-art review works that cover a wide range of research proposals. These review works serve as valuable resources for researchers, providing a comprehensive overview of achievements and guiding them towards the most meaningful works. This paper proposes to present a review of state-of-the-art review works on wind-energy-related issues, categorizing them into different main topics in the field of energy research and analyzing and commenting on them.
Article
Chemistry, Multidisciplinary
Moises Cordeiro-Costas, Daniel Villanueva, Andres E. Feijoo-Lorenzo, Javier Martinez-Torres
Summary: A method is proposed in this paper to synthetically generate sequences of wind speed values satisfying statistical distributions and imposing spatial and temporal correlations. The method was successfully checked under different scenarios, with high accuracy in the results.
APPLIED SCIENCES-BASEL
(2021)
Article
Chemistry, Multidisciplinary
Moises Cordeiro-Costas, Daniel Villanueva, Pablo Eguia-Oller
Summary: This paper presents a method for optimizing building storage system management using machine learning techniques to model and predict electrical demand, aiming to reduce electricity expenses in buildings.
APPLIED SCIENCES-BASEL
(2021)
Review
Chemistry, Multidisciplinary
Daniel Villanueva, Moises Cordeiro-Costas, Andres E. Feijoo-Lorenzo, Antonio Fernandez-Otero, Edelmiro Miguez-Garcia
Summary: This paper examines the impact of integrating batteries into domestic installations on energy efficiency and proposes various strategies to improve overall system efficiency, such as using DC suppliers, increasing the use of DC home devices, and utilizing devices based on renewable energy sources.
APPLIED SCIENCES-BASEL
(2021)
Editorial Material
Energy & Fuels
Andres E. Feijoo-Lorenzo
Article
Energy & Fuels
Manisha Sawant, Mayur Kishor Shende, Andres E. Feijoo-Lorenzo, Neeraj Dhanraj Bokde
Summary: Clouds are mass of water vapor in the atmosphere with variable height that influence weather. Meteorological behavior is crucial for human activities like agriculture. Cloud detection methods involve thresholding techniques and machine-learning algorithms for tracking.
Article
Chemistry, Multidisciplinary
Daniel Villanueva, Diego San-Facundo, Edelmiro Miguez-Garcia, Antonio Fernandez-Otero
Summary: This paper presents a method to predict household appliance consumption by modeling and simulating, using statistical distribution evaluation. The results demonstrate high accuracy in simulating and predicting household appliance consumption with this method.
APPLIED SCIENCES-BASEL
(2022)
Article
Chemistry, Multidisciplinary
Moises Cordeiro-Costas, Daniel Villanueva, Pablo Eguia-Oller, Enrique Granada-Alvarez
Summary: This paper compares different Machine Learning and Deep Learning models to determine the most appropriate techniques for forecasting rooftop photovoltaic production. The results show that these models can accurately forecast photovoltaic production in buildings with low error rates and high R-2 values.
APPLIED SCIENCES-BASEL
(2022)
Article
Green & Sustainable Science & Technology
Siyu Tao, Chaohai Zhang, Andres Feijoo, Victor Kim
Summary: This paper proposes an optimization framework for wind farm repowering, considering factors such as power generation, economic cost, and aesthetic. The study applies a 3-D Gaussian wake model to calculate wake deficits inside the wind farm, taking into account height differences among new wind turbines. A harmony pattern metric is used to assess the visual impact of the reconstructed wind farm. The optimization problem is solved using an integer particle swarm optimization algorithm, with wind data predicted by an auto-regressive model. Case study results validate the effectiveness of the proposed method and the superiority of predicted wind data for repowering optimization.
IET RENEWABLE POWER GENERATION
(2023)
