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Advances in Electric Power and Energy : Forecasting in Electric Power Systems.
A comprehensive review of state-of-the-art approaches to power systems forecasting from the most respected names in the field, internationally Advances in Electric Power and Energy Systems is the first book devoted exclusively to a subject of increasing urgency to power systems planning and operatio...
| Clasificación: | Libro Electrónico |
|---|---|
| Autor principal: | |
| Formato: | Electrónico eBook |
| Idioma: | Inglés |
| Publicado: |
New York :
John Wiley & Sons, Incorporated,
2013.
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| Colección: | IEEE Press Series on Power Engineering Ser.
|
| Temas: | |
| Acceso en línea: | Texto completo |
MARC
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| 049 | |a UAMI | ||
| 100 | 1 | |a El-Hawary, Mohamed E. | |
| 245 | 1 | 0 | |a Advances in Electric Power and Energy : |b Forecasting in Electric Power Systems. |
| 260 | |a New York : |b John Wiley & Sons, Incorporated, |c 2013. | ||
| 300 | |a 1 online resource (326 pages) | ||
| 336 | |a text |b txt |2 rdacontent | ||
| 337 | |a computer |b c |2 rdamedia | ||
| 338 | |a online resource |b cr |2 rdacarrier | ||
| 490 | 1 | |a IEEE Press Series on Power Engineering Ser. | |
| 588 | 0 | |a Print version record. | |
| 505 | 0 | |a Advances in Electric Power and Energy Systems; Contents; Preface and Acknowledgments; Contributors; 1 Introduction; Prelude; Forecasting: General Considerations; Forecasting in Electric Power Systems; Load Forecasting in Electric Power Systems; Electricity Price Forecasting in Electric Power Systems; Time Series Analysis; Multiplicative and Additive Models; Occams Razor, the Principle of Parsimony; The Stationarity Concept; The Autoregressive (AR) Process; Moving Average Processes; Autoregressive Moving Average Processes; Integrated Processes and ARIMA Models. | |
| 505 | 8 | |a Seasonality and Seasonal ARIMA ModelsArtificial Neural Networks; Radial Basis Function Networks; Overview of Chapters; References; 2 Univariate Methods for Short-Term Load Forecasting; Introduction; Intraday Load Data; Univariate Methods for Load Forecasting; Simplistic Benchmark Methods; Seasonal ARMA; Periodic AR; Exponential Smoothing for Double Seasonality; Intraday Cycle Exponential Smoothing; A Method Based on Principal Components Analysis; Empirical Forecasting Study; Extensions of the Methods; Very Short-Term Forecasting with Minute-by-Minute Data. | |
| 505 | 8 | |a Recently Developed Exponentially Weighted MethodsTriple Seasonal Methods for Multiple Years of Intraday Data; Summary and Concluding Comments; Acknowledgments; References; 3 Application of the Weighted Nearest Neighbor Method to Power System Forecasting Problems; Introduction; Background; Data Mining Techniques and Time Series Analysis; Demand and Price Forecasting in Power Systems; Weighted Nearest Neighbors Methodology; Determination of the Weighting Coefficients; Tuning the Model; Performance assessment; Application to aggregated load forecasting; Description of the Data Base; Test Results. | |
| 505 | 8 | |a Comparison with ARApplication to pool energy price forecasting; Characterization of Spanish Electricity Market Prices; Test Results; Comparison with Other Techniques; Application to customer-level forecasting; Characterization and Processing of Data Records; Test Results; Comparison with an AR Model; Conclusions; References; 4 Electricity Prices as a Stochastic Process; Introduction; Characteristics of Electricity Prices; Stochastic Process Models for Electricity Prices; From Random Walk to Brownian Motion; Brownian Motion with Drift; Ito Process; Geometric Brownian Motion. | |
| 505 | 8 | |a Mean Reversion ProcessProperties of a Lognormal Distribution; Risk-Adjusted Price; Electricity Price with Spikes; Time Series Methods for Electricity Prices; Autoregressive (AR) Model; Autoregressive Moving Average (ARMA) Model; Volatility of Prices; Numerical Examples; Estimate Parameters of Mean Reversion Process by AR Model; Numerical Examples of AR Model; Numerical Examples of ARMA Model; Conclusions; Acknowledgment; References; 5 Short-Term Forecasting of Electricity Prices Using Mixed Models; Introduction and Problem Statement; State of the Art; Models Presented in this Chapter. | |
| 500 | |a Time Series Analysis and Arima Models. | ||
| 520 | |a A comprehensive review of state-of-the-art approaches to power systems forecasting from the most respected names in the field, internationally Advances in Electric Power and Energy Systems is the first book devoted exclusively to a subject of increasing urgency to power systems planning and operations. Written for practicing engineers, researchers, and post-grads concerned with power systems planning and forecasting, this book brings together contributions from many of the world's foremost names in the field who address a range of critical issues, from forecasting power system load to power system pricing to post-storm service restoration times, river flow forecasting, and more. In a time of ever-increasing energy demands, mounting concerns over the environmental impacts of power generation, and the emergence of new, smart-grid technologies, electricity price forecasting has assumed a prominent role within both the academic and industrial arenas. Short-run forecasting of electricity prices has become necessary for power generation unit schedule, since it is the basis of every maximization strategy. This book fills a gap in the literature on this increasingly important topic. Following an introductory chapter offering background information necessary for a full understanding of the forecasting issues covered, this book: . Introduces advanced methods of time series forecasting, as well as neural networks. Provides in-depth coverage of state-of-the-art power system load forecasting and electricity price forecasting . Addresses river flow forecasting based on autonomous neural network models. Deals with price forecasting in a competitive market. Includes estimation of post-storm restoration times for electric power distribution systems. Features contributions from world-renowned experts sharing their insights and expertise in a series of self-contained chapters Advances in Electric Power and Energy Systems is a valuable resource for practicing engineers, regulators, planners, and consultants working in or concerned with the electric power industry. It is also a must read for senior undergraduates, graduate students, and researchers involved in power system planning and operation. | ||
| 590 | |a ProQuest Ebook Central |b Ebook Central Academic Complete | ||
| 650 | 0 | |a Electric power systems. | |
| 650 | 6 | |a Réseaux électriques (Énergie) | |
| 650 | 7 | |a Electric power systems |2 fast | |
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| 776 | 0 | 8 | |i Print version: |a El-Hawary, Mohamed E. |t Advances in Electric Power and Energy : Forecasting in Electric Power Systems. |d New York : John Wiley & Sons, Incorporated, ©2013 |z 9781118171349 |
| 830 | 0 | |a IEEE Press Series on Power Engineering Ser. | |
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