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Supervised Machine Learning In Wind Forecasting And Ramp Event Prediction
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Book Synopsis Supervised Machine Learning in Wind Forecasting and Ramp Event Prediction by : Harsh S. Dhiman
Download or read book Supervised Machine Learning in Wind Forecasting and Ramp Event Prediction written by Harsh S. Dhiman and published by Academic Press. This book was released on 2020-01-20 with total page 216 pages. Available in PDF, EPUB and Kindle. Book excerpt: Supervised Machine Learning in Wind Forecasting and Ramp Event Prediction provides an up-to- date overview on the broad area of wind generation and forecasting, with a focus on the role and need of Machine Learning in this emerging field of knowledge. Various regression models and signal decomposition techniques are presented and analyzed, including least-square, twin support and random forest regression, all with supervised Machine Learning. The specific topics of ramp event prediction and wake interactions are addressed in this book, along with forecasted performance. Wind speed forecasting has become an essential component to ensure power system security, reliability and safe operation, making this reference useful for all researchers and professionals researching renewable energy, wind energy forecasting and generation. Features various supervised machine learning based regression models Offers global case studies for turbine wind farm layouts Includes state-of-the-art models and methodologies in wind forecasting
Book Synopsis Renewable Energy Optimization, Planning and Control by : Anita Khosla
Download or read book Renewable Energy Optimization, Planning and Control written by Anita Khosla and published by Springer Nature. This book was released on 2021-09-28 with total page 188 pages. Available in PDF, EPUB and Kindle. Book excerpt: This book gathers selected high-quality research papers presented at International Conference on Renewable Technologies in Engineering (ICRTE 2021) organized by Manav Rachna International Institute of Research & Studies, Faridabad, Haryana, India, during 15–16 April 2021. The book includes conference papers on the theme “Computational Techniques for Renewable Energy Optimization”, which aims to bring together leading academic scientists, researchers and research scholars to exchange and share their experiences and research results on all aspects of renewable energy integration, planning, control and optimization. It also provides a premier interdisciplinary platform for researchers, practitioners and educators to present and discuss the most recent innovations, trends and concerns as well as practical challenges encountered and solutions adopted in the fields of renewable energy and resources.
Book Synopsis Soft Computing Applications by : Valentina Emilia Balas
Download or read book Soft Computing Applications written by Valentina Emilia Balas and published by Springer Nature. This book was released on 2020-08-14 with total page 460 pages. Available in PDF, EPUB and Kindle. Book excerpt: This book presents the proceedings of the 8th International Workshop on Soft Computing Applications, SOFA 2018, held on 13–15 September 2018 in Arad, Romania. The workshop was organized by Aurel Vlaicu University of Arad, in conjunction with the Institute of Computer Science, Iasi Branch of the Romanian Academy, IEEE Romanian Section, Romanian Society of Control Engineering and Technical Informatics – Arad Section, General Association of Engineers in Romania – Arad Section and BTM Resources Arad. The papers included in these proceedings, published post-conference, cover the research including Knowledge-Based Technologies for Web Applications, Cloud Computing, Security Algorithms and Computer Networks, Business Process Management, Computational Intelligence in Education and Modelling and Applications in Textiles and many other areas related to the Soft Computing. The book is directed to professors, researchers, and graduate students in area of soft computing techniques and applications.
Book Synopsis Corrosion and Corrosion Protection of Wind Power Structures in Marine Environments by : Andreas Momber
Download or read book Corrosion and Corrosion Protection of Wind Power Structures in Marine Environments written by Andreas Momber and published by Academic Press. This book was released on 2024-04-07 with total page 756 pages. Available in PDF, EPUB and Kindle. Book excerpt: Corrosion and Corrosion Protection of Wind Power Structures in Marine Environments: Volume 2: Corrosion Protection Measures offers the first comprehensive review on corrosion and corrosion protection of offshore wind power structures. The book extensively discusses corrosion phenomena and corrosion types in different marine corrosion zones, including the modeling of corrosion processes and interactions between corrosion and structural stability. The book addresses important design issues, namely materials selection relevant to their performance in marine environments, corrosion allowance, and constructive design. Active and passive corrosion protection measures are emphasized, with special sections on cathodic corrosion protection and the use of protective coatings. Seawater related issues associated with cathodic protection, such as calcareous deposit formation, hydrogen formation, and fouling, are discussed. With respect to protective coatings, the book considers, for the first time, complete loading scenarios, including corrosive loads, mechanical loads, and special loads, and covers a wide range of coating materials. Problems associated with fouling and bacterial-induced corrosion are extensively reviewed. The book closes with a chapter on recent developments in maintenance strategies, inspection techniques, and repair technologies. The book will be of special interest to materials scientists, materials developers, corrosion engineers, maintenance engineers, civil engineers, steel work designers, mechanical engineers, marine engineers, chemists, and coating specialists. Offshore wind power is an emerging renewable technology and a key factor for a cleaner environment. Offshore wind power structures are situated in a demanding and challenging marine environment. The structures are loaded in a complex way, including mechanical loads and corrosive loads. Corrosion is one of the major limiting factors to the reliability and performance of the technology. Maintenance and repair of corrosion protection systems are particularly laborious and costly. Explores the literature between 1950 and 2020 and contains over 2000 references Offers the most complete monograph on the issue Covers all aspects of corrosion protection in detail, including coatings, cathodic protection, corrosion allowance, constructive design, as well as maintenance and repair Delivers the most complete review on corrosion of metals in marine/offshore environments Focuses on all aspects of offshore wind power structures, namely foundations, towers, internal sections, connection flanges, and transformation platforms
Book Synopsis Wind Power Ensemble Forecasting by : André Gensler
Download or read book Wind Power Ensemble Forecasting written by André Gensler and published by kassel university press GmbH. This book was released on 2019-01-16 with total page 216 pages. Available in PDF, EPUB and Kindle. Book excerpt: This thesis describes performance measures and ensemble architectures for deterministic and probabilistic forecasts using the application example of wind power forecasting and proposes a novel scheme for the situation-dependent aggregation of forecasting models. For performance measures, error scores for deterministic as well as probabilistic forecasts are compared, and their characteristics are shown in detail. For the evaluation of deterministic forecasts, a categorization by basic error measure and normalization technique is introduced that simplifies the process of choosing an appropriate error measure for certain forecasting tasks. Furthermore, a scheme for the common evaluation of different forms of probabilistic forecasts is proposed. Based on the analysis of the error scores, a novel hierarchical aggregation technique for both deterministic and probabilistic forecasting models is proposed that dynamically weights individual forecasts using multiple weighting factors such as weather situation and lead time dependent weighting. In the experimental evaluation it is shown that the forecasting quality of the proposed technique is able to outperform other state of the art forecasting models and ensembles.
Book Synopsis Grid and Market Integration of Large-Scale Wind Farms Using Advanced Wind Power Forecasting: Technical and Energy Economic Aspects by : Ümit Cali
Download or read book Grid and Market Integration of Large-Scale Wind Farms Using Advanced Wind Power Forecasting: Technical and Energy Economic Aspects written by Ümit Cali and published by kassel university press GmbH. This book was released on 2011 with total page 174 pages. Available in PDF, EPUB and Kindle. Book excerpt:
Book Synopsis Probabilistic Wind Power Ramp Forecasting Based on a Scenario Generation Method: Preprint by :
Download or read book Probabilistic Wind Power Ramp Forecasting Based on a Scenario Generation Method: Preprint written by and published by . This book was released on 2017 with total page 0 pages. Available in PDF, EPUB and Kindle. Book excerpt: Wind power ramps (WPRs) are particularly important in the management and dispatch of wind power, and they are currently drawing the attention of balancing authorities. With the aim to reduce the impact of WPRs for power system operations, this paper develops a probabilistic ramp forecasting method based on a large number of simulated scenarios. An ensemble machine learning technique is first adopted to forecast the basic wind power forecasting scenario and calculate the historical forecasting errors. A continuous Gaussian mixture model (GMM) is used to fit the probability distribution function (PDF) of forecasting errors. The cumulative distribution function (CDF) is analytically deduced. The inverse transform method based on Monte Carlo sampling and the CDF is used to generate a massive number of forecasting error scenarios. An optimized swinging door algorithm is adopted to extract all the WPRs from the complete set of wind power forecasting scenarios. The probabilistic forecasting results of ramp duration and start time are generated based on all scenarios. Numerical simulations on publicly available wind power data show that within a predefined tolerance level, the developed probabilistic wind power ramp forecasting method is able to predict WPRs with a high level of sharpness and accuracy.
Book Synopsis Spatio-Temporal Data Analytics for Wind Energy Integration by : Lei Yang
Download or read book Spatio-Temporal Data Analytics for Wind Energy Integration written by Lei Yang and published by Springer. This book was released on 2014-11-14 with total page 86 pages. Available in PDF, EPUB and Kindle. Book excerpt: This SpringerBrief presents spatio-temporal data analytics for wind energy integration using stochastic modeling and optimization methods. It explores techniques for efficiently integrating renewable energy generation into bulk power grids. The operational challenges of wind, and its variability are carefully examined. A spatio-temporal analysis approach enables the authors to develop Markov-chain-based short-term forecasts of wind farm power generation. To deal with the wind ramp dynamics, a support vector machine enhanced Markov model is introduced. The stochastic optimization of economic dispatch (ED) and interruptible load management are investigated as well. Spatio-Temporal Data Analytics for Wind Energy Integration is valuable for researchers and professionals working towards renewable energy integration. Advanced-level students studying electrical, computer and energy engineering should also find the content useful.
Book Synopsis Advances in Computational Intelligence by : Ignacio Rojas
Download or read book Advances in Computational Intelligence written by Ignacio Rojas and published by Springer. This book was released on 2013-06-21 with total page 687 pages. Available in PDF, EPUB and Kindle. Book excerpt: This two-volume set LNCS 7902 and 7903 constitutes the refereed proceedings of the 12th International Work-Conference on Artificial Neural Networks, IWANN 2013, held in Puerto de la Cruz, Tenerife, Spain, in June 2013. The 116 revised papers were carefully reviewed and selected from numerous submissions for presentation in two volumes. The papers explore sections on mathematical and theoretical methods in computational intelligence, neurocomputational formulations, learning and adaptation emulation of cognitive functions, bio-inspired systems and neuro-engineering, advanced topics in computational intelligence and applications
Book Synopsis Probabilistic Day-ahead Forecasting Using an Analog Ensemble Approach for Wind Farm Grid Services by : Andrew Kumler
Download or read book Probabilistic Day-ahead Forecasting Using an Analog Ensemble Approach for Wind Farm Grid Services written by Andrew Kumler and published by . This book was released on 2021 with total page 17 pages. Available in PDF, EPUB and Kindle. Book excerpt:
Download or read book Windsense Project written by Rob Kamisky and published by . This book was released on 2016 with total page 98 pages. Available in PDF, EPUB and Kindle. Book excerpt:
Book Synopsis Key technologies for hybrid energy system planning and operation by : Chengguo Su
Download or read book Key technologies for hybrid energy system planning and operation written by Chengguo Su and published by Frontiers Media SA. This book was released on 2024-05-14 with total page 129 pages. Available in PDF, EPUB and Kindle. Book excerpt:
Book Synopsis Wind Forecasting in Railway Engineering by : Hui Liu
Download or read book Wind Forecasting in Railway Engineering written by Hui Liu and published by Elsevier. This book was released on 2021-06-17 with total page 364 pages. Available in PDF, EPUB and Kindle. Book excerpt: Wind Forecasting in Railway Engineering presents core and leading-edge technologies in wind forecasting for railway engineering. The title brings together wind speed forecasting and railway wind engineering, offering solutions from both fields. Key technologies are presented, along with theories, modeling steps and comparative analyses of forecasting technologies. Each chapter presents case studies and applications, including typical applications and key issues, analysis of wind field characteristics, optimization methods for the placement of a wind anemometer, single-point time series along railways, deep learning algorithms on single-point wind forecasting, reinforcement learning algorithms, ensemble single-point wind forecasting methods, spatial wind, and data-driven spatial-temporal wind forecasting algorithms. This important book offers practical solutions for railway safety, by bringing together the latest technologies in wind speed forecasting and railway wind engineering into a single volume. Presents the core technologies and most advanced developments in wind forecasting for railway engineering Gives case studies and experimental designs, demonstrating real-world applications Introduces cutting-edge deep learning and reinforcement learning methods Combines the latest thinking from wind engineering and railway engineering Offers a complete solution to wind forecasting in railway engineering for the safety of running trains
Book Synopsis Machine Learning Models for Predicting Wind Speed and Power by : Oscar Andrés Clavijo Ospina
Download or read book Machine Learning Models for Predicting Wind Speed and Power written by Oscar Andrés Clavijo Ospina and published by . This book was released on 2019* with total page pages. Available in PDF, EPUB and Kindle. Book excerpt: Wind speed and power forecasting is one of the most challenging problems for energy generation and energy control systems. Given significant uncertainties in the behaviour of the wind speed, non-stationarity and high variance, probabilistic forecasting provides a solution for future values of wind speed and power accurately. This work proposes a copula autoregressive model and compares it with another three novel models to directly develop a forecast for wind speed in the short-term horizon, evaluating the different assumptions, constraints, advantages and failures of each of them. The proposed comparison uses three main error metrics to evaluate the accuracy of the model, performing an adequate backtesting process to ensure that both training and validation process are consistent beyond all the models. Case studies using real wind farms data from Colombia have been conducted. Copula autoregressive model, along with other high-flexible models demonstrate the high efficiency and reliability of their developed approaches.
Book Synopsis Data Science for Wind Energy by : Yu Ding
Download or read book Data Science for Wind Energy written by Yu Ding and published by CRC Press. This book was released on 2019-06-04 with total page 400 pages. Available in PDF, EPUB and Kindle. Book excerpt: Data Science for Wind Energy provides an in-depth discussion on how data science methods can improve decision making for wind energy applications, near-ground wind field analysis and forecast, turbine power curve fitting and performance analysis, turbine reliability assessment, and maintenance optimization for wind turbines and wind farms. A broad set of data science methods covered, including time series models, spatio-temporal analysis, kernel regression, decision trees, kNN, splines, Bayesian inference, and importance sampling. More importantly, the data science methods are described in the context of wind energy applications, with specific wind energy examples and case studies. Please also visit the author’s book site at https://aml.engr.tamu.edu/book-dswe. Features Provides an integral treatment of data science methods and wind energy applications Includes specific demonstration of particular data science methods and their use in the context of addressing wind energy needs Presents real data, case studies and computer codes from wind energy research and industrial practice Covers material based on the author's ten plus years of academic research and insights
Book Synopsis WIND POWER ANALYSIS AND FORECASTING USING MACHINE LEARNING WITH PYTHON by : Vivian Siahaan
Download or read book WIND POWER ANALYSIS AND FORECASTING USING MACHINE LEARNING WITH PYTHON written by Vivian Siahaan and published by BALIGE PUBLISHING. This book was released on 2023-07-09 with total page 229 pages. Available in PDF, EPUB and Kindle. Book excerpt: In this project on wind power analysis and forecasting using machine learning with Python, we started by exploring the dataset. We examined the available features and the target variable, which is the active power generated by wind turbines. The dataset likely contained information about various meteorological parameters and the corresponding active power measurements. To begin our analysis, we focused on the regression task of predicting the active power using regression algorithms. We split the dataset into training and testing sets and preprocessed the data by handling missing values and performing feature scaling. The preprocessing step ensured that the data was suitable for training machine learning models. Next, we trained several regression models on the preprocessed data. We utilized algorithms such as Linear Regression, Decision Tree Regression, Random Forest Regression, and Gradient Boosting Regression. Each model was trained on the training set and evaluated on the testing set using performance metrics like mean squared error (MSE) and R-squared score. After obtaining regression models for active power prediction, we shifted our focus to predicting categorized active power using machine learning models. This involved converting the continuous active power values into discrete categories or classes. We defined categories based on certain thresholds or ranges of active power values. For the categorized active power prediction task, we employed classification algorithms. Similar to the regression task, we split the dataset, preprocessed the data, and trained various classification models. Common classification algorithms used were Logistic Regression, Support Vector Machines (SVM), K-Nearest Neighbors (KNN), Decision Trees, Random Forests, Gradient Boosting, Extreme Gradient Boosting, Multi-Layer Perceptron, and Light Gradient Boosting models. During the training and evaluation of classification models, we used performance metrics like accuracy, precision, recall, and F1-score to assess the models' predictive capabilities. Additionally, we analyzed the classification reports to gain insights into the models' performance for each category. Throughout the process, we paid attention to feature scaling techniques such as normalization and standardization. These techniques were applied to ensure that the features were on a similar scale and to prevent any bias or dominance of certain features during model training. The results of predicting categorized active power using machine learning models were highly encouraging. The models demonstrated exceptional accuracy and exhibited strong classification performance across all categories. The findings from this analysis have significant implications for wind power forecasting and monitoring systems, allowing for more effective categorization and management of wind power generation based on predicted active power levels. To summarize, the wind power analysis and forecasting session involved dataset exploration, active power regression using regression algorithms, and predicting categorized active power using various machine learning models. The regression task aimed to predict continuous active power values, while the classification task aimed to predict discrete categories of active power. Preprocessing, training, evaluation, and performance analysis were key steps throughout the session. The selected models, algorithms, and performance metrics varied depending on the specific task at hand. Overall, the project provided a comprehensive overview of applying machine learning techniques to analyze and forecast wind power generation.
Book Synopsis Development of an Offshore Specific Wind Power Forecasting System by : Melih Kurt
Download or read book Development of an Offshore Specific Wind Power Forecasting System written by Melih Kurt and published by kassel university press GmbH. This book was released on 2017-01-01 with total page 200 pages. Available in PDF, EPUB and Kindle. Book excerpt: This study explains the data preparation processes, plausibility checking of meteorological parameters, correction of met-mast wind speed, and also the determination of the nominal power of a wind farm using met-mast measurements. The wind speed correction of met-mast FINO1 is evaluated from the perspective of power produced by alpha ventus by using uncorrected and corrected measurements from this met-mast. Afterwards this data is used for the determination of nominal power for alpha ventus.
