Solar power is widely acknowledged to be the fastest-growing energy industry in the world. As technological improvements steadily progress toward the erasure of cost and efficiency barriers, two issues are coming to the forefront of public discourse on solar energy—variability and reliability. Solar-project developers and their financiers are increasingly scrutinizing the accuracy of long-term resource projections; as well, grid operators’ concerns about variable short-term power generation are growing. These issues have made the field of solar forecasting and resource assessment pivotally important, and to date, there has been no comprehensive single text devoted to it. This volume aims to become the authoritative work on solar forecasting and resource assessment, incorporating contributions from internationally recognized researchers from both industry and academia whose focus is on applying information from underlying scientific fundamentals to practical industry needs, and on emphasizing the latest technological developments driving this discipline forward.
The audience for the book comprises scientists and engineers working in the power-utility or renewable-energy industry and other, related energy fields, as well as in atmospheric science and meteorology. Solar-energy professionals are particularly targeted, including research scientists, project developers, system operators, planners and engineers, and investors in and financiers of solar-energy projects. This book is the only one dedicated to the short-term forecast and assessment of solar-resource bankability and variability, providing readers with a complete understanding of the state of the art.
Chapters 2 and 3 address the semi-empirical and physically-based methods developed for estimating surface solar-radiation resources using satellite observations of clouds and atmospheric aerosols. Satellite solar resource estimates are increasingly capable of replacing or at least complementing ground – based observations for solar power prospecting. The financial risks to solar – energy projects, the statistical analysis of temporal and spatial variations in solar-radiation resources, and the impacts of resource variability on electrical – power generation are presented in Chapters 4, 5, 6 and 7.
The ability to forecast solar resources for the range of time intervals important for managing the electrical-power grid and its markets is an active area of research and development. Chapter 8 provides an overview of solarforecasting methods and evaluation metrics. Chapter 9 describes short-term solar-resource forecasts based on surface observations of clouds from sky
Preface
imagery. Chapters 10 and 11 describe hour-ahead forecasting methods based on satellite data for grid operators in the United States and Europe.
Background, data assimilation, and case studies of Numerical weather prediction (NWP) models applied to day-ahead solar forecasting are addressed in Chapters 12, 13, and 14. Stochastic-learning methods for improving all types of solar-resource forecasts are presented in Chapter 15.
My gratitude goes to all contributors and to my sponsors (California Public Utilities Commission, California Energy Commission, Panasonic Corporation, US Department of Energy) and undergraduate and doctoral students who embrace the philosophy of lab-to-market research. May our joint work enable seamless and economical integration of large amounts of solar power in the electric grid.
The images in this book appear in black and white and are repeated in color in the color plate section near the middle of the book.
