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The integration of renewable energy resources into the electricity grid presents an important challenge. This book provides a review and analysis of the technical and policy options available for managing variable energy resources such as wind and solar power. As well as being of value to government and industry policy-makers and planners, the volume also provides a single source for scientists and engineers of the technical knowledge gained during the 4-year RenewElec (renewable electricity) project at Carnegie Mellon University, the University of Vermont, Vermont Law School, and the Van Ness Feldman environmental law firm. The first part of the book discusses the options for large scale integration of variable electric power generation, including issues of predictability, variability, and efficiency. The second part presents the scientific findings of the project. In the final part, the authors undertake a critical review of major quantitative regional and national wind integration studies in the United States. Based on comparisons among these studies, they suggest areas where improvements in methods are warranted in future studies, areas where additional research is needed to facilitate future improvements in wind integration studies and how the research can be put into practice.
This book introduces and explains the statistical methods used to describe, analyze, test, and forecast atmospheric data. It will be useful to students, scientists, and other professionals who seek to make sense of the scientific literature in meteorology, climatology, or other geophysical disciplines, or to understand and communicate what their atmospheric data sets have to say. The book includes chapters on exploratory data analysis, probability distributions, hypothesis testing, statistical weather forecasting, forecast verification, time(series analysis, and multivariate data analysis. Worked examples, exercises, and illustrations facilitate understanding of the material; an extensive and up-to-date list of references allows the reader to pursue selected topics in greater depth.Key Features* Presents and explains techniques used in atmospheric data summarization, analysis, testing, and forecasting* Includes extensive and up-to-date references* Features numerous worked examples and exercises* Contains over 130 illustrations
Smart Energy and Electric Power Systems: Current Trends and New Intelligent Perspectives reviews key applications of intelligent algorithms and machine learning techniques to increasingly complex and data-driven power systems with distributed energy resources to enable evidence-driven decision-making and mitigate catastrophic power shortages. The book reviews foundations towards the integration of machine learning and smart power systems before addressing key challenges and issues. The work then explores AI- and ML-informed techniques to rebalancing of supply and demand. Methods discussed include distributed energy resources and prosumer markets, electricity demand prediction, component fault detection, and load balancing. Security solutions are introduced, along with potential solutions to cyberattacks, security data detection and critical loads in power systems. The work closes with a lengthy discussion, informed by case studies, on integrating AI and ML into the modern energy sector. - Helps improve the prediction capability of AI algorithms to make evidence-based decisions in the smart supply of electricity, including load shedding - Focuses on how to integrate AI and ML into the energy sector in the real-world, with many chapters accompanied by case studies - Addresses a number of proven AI and ML- informed techniques in rebalancing supply and demand
Renewable Energy Forecasting: From Models to Applications provides an overview of the state-of-the-art of renewable energy forecasting technology and its applications. After an introduction to the principles of meteorology and renewable energy generation, groups of chapters address forecasting models, very short-term forecasting, forecasting of extremes, and longer term forecasting. The final part of the book focuses on important applications of forecasting for power system management and in energy markets. Due to shrinking fossil fuel reserves and concerns about climate change, renewable energy holds an increasing share of the energy mix. Solar, wind, wave, and hydro energy are dependent on highly variable weather conditions, so their increased penetration will lead to strong fluctuations in the power injected into the electricity grid, which needs to be managed. Reliable, high quality forecasts of renewable power generation are therefore essential for the smooth integration of large amounts of solar, wind, wave, and hydropower into the grid as well as for the profitability and effectiveness of such renewable energy projects. - Offers comprehensive coverage of wind, solar, wave, and hydropower forecasting in one convenient volume - Addresses a topic that is growing in importance, given the increasing penetration of renewable energy in many countries - Reviews state-of-the-science techniques for renewable energy forecasting - Contains chapters on operational applications
Wind energy’s bestselling textbook- fully revised. This must-have second edition includes up-to-date data, diagrams, illustrations and thorough new material on: the fundamentals of wind turbine aerodynamics; wind turbine testing and modelling; wind turbine design standards; offshore wind energy; special purpose applications, such as energy storage and fuel production. Fifty additional homework problems and a new appendix on data processing make this comprehensive edition perfect for engineering students. This book offers a complete examination of one of the most promising sources of renewable energy and is a great introduction to this cross-disciplinary field for practising engineers. “provides a wealth of information and is an excellent reference book for people interested in the subject of wind energy.” (IEEE Power & Energy Magazine, November/December 2003) “deserves a place in the library of every university and college where renewable energy is taught.” (The International Journal of Electrical Engineering Education, Vol.41, No.2 April 2004) “a very comprehensive and well-organized treatment of the current status of wind power.” (Choice, Vol. 40, No. 4, December 2002)
In recent years, several projects and studies have been launched towards the development and use of new methodologies, in order to assess, monitor, and support clean forms of energy. Accurate estimation of the available energy potential is of primary importance, but is not always easy to achieve. The present Special Issue on ‘Renewable Energy Resource Assessment and Forecasting’ aims to provide a holistic approach to the above issues, by presenting multidisciplinary methodologies and tools that are able to support research projects and meet today’s technical, socio-economic, and decision-making needs. In particular, research papers, reviews, and case studies on the following subjects are presented: wind, wave and solar energy; biofuels; resource assessment of combined renewable energy forms; numerical models for renewable energy forecasting; integrated forecasted systems; energy for buildings; sustainable development; resource analysis tools and statistical models; extreme value analysis and forecasting for renewable energy resources.