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1. |
Record Nr. |
UNINA9910146625903321 |
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Autore |
Hutter Kolumban |
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Titolo |
Electromagnetic field matter interactions in thermoelastic solids and viscous fluids / / Kolumban Hutter, Alfons A.F. van de Ven, Ana Ursescu |
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Pubbl/distr/stampa |
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Berlin ; ; Heidelberg : , : Springer, , [2006] |
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©2006 |
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ISBN |
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1-280-80038-0 |
9786610800384 |
3-540-37240-7 |
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Edizione |
[1st ed. 2006.] |
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Descrizione fisica |
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1 online resource (421 p.) |
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Collana |
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Disciplina |
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Soggetti |
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Thermoelasticity |
Field theory (Physics) |
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Lingua di pubblicazione |
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Formato |
Materiale a stampa |
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Livello bibliografico |
Monografia |
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Note generali |
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Second and substantially enlarged edition of: Field matter interactions in thermoelastic solids, 1978. |
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Nota di contenuto |
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General Introduction -- General Introduction -- Basic Concepts -- Equivalence of Different Electromagnetic Formulations in Thermoelastic Solids -- A Survey of Electromagneto-Mechanical Interaction Models -- Equivalence of the Models -- Material Description -- Linearization -- Applications Magnetoelastic (In)stability and Vibrations Electrorheological Fluids -- Magnetoelastic (In)stability and Vibrations -- Electrorheological Fluids. |
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Sommario/riassunto |
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This book in two parts delivers a thorough derivation of nonrelativistic interaction models of electromagnetic field theories with thermoelastic solids and viscous fluids, the intention being to derive unique representations for the observable field quantities. Part I, a revised and updated version of LNP 88 "Field Matter Interactions in Thermoelastic Solids," investigates the foundations and the equivalence of various formulations of the interaction of the electromagnetic field with thermoelastic solids in the classical continuum physics limit, while Part II extensively surveys two major fields of applications, namely, magnetoelastic instabilities and vibrations, and electrorheological fluids. This volume is intended for and will be useful to students and |
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researchers working on all aspects of electromagneto-mechanical interactions in the materials sciences of complex solids and fluids. |
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2. |
Record Nr. |
UNINA9910829923303321 |
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Autore |
Weron Rafał |
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Titolo |
Modeling and forecasting electricity loads and prices [[electronic resource] ] : a statistical approach / / Rafał Weron |
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Pubbl/distr/stampa |
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Chichester, England ; ; Hoboken, NJ, : John Wiley & Sons, c2006 |
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ISBN |
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1-118-67336-0 |
1-280-74001-9 |
9786610740017 |
0-470-05999-0 |
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Descrizione fisica |
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1 online resource (194 p.) |
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Collana |
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Disciplina |
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333.793/213015195 |
333.793213015195 |
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Soggetti |
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Electric power consumption - Forecasting - Statistical methods |
Electric utilities - Rates - Forecasting - Statistical methods |
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Lingua di pubblicazione |
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Formato |
Materiale a stampa |
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Livello bibliografico |
Monografia |
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Note generali |
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Description based upon print version of record. |
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Nota di bibliografia |
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Includes bibliographical references (p. [157]-170) and index. |
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Nota di contenuto |
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Modeling and Forecasting Electricity Loads and Prices; Contents; Preface; Acknowledgments; 1 Complex Electricity Markets; 1.1 Liberalization; 1.2 The Marketplace; 1.2.1 Power Pools and Power Exchanges; 1.2.2 Nodal and Zonal Pricing; 1.2.3 Market Structure; 1.2.4 Traded Products; 1.3 Europe; 1.3.1 The England and Wales Electricity Market; 1.3.2 The Nordic Market; 1.3.3 Price Setting at Nord Pool; 1.3.4 Continental Europe; 1.4 North America; 1.4.1 PJM Interconnection; 1.4.2 California and the Electricity Crisis; 1.4.3 Alberta and Ontario; 1.5 Australia and New Zealand; 1.6 Summary |
1.7 Further Reading2 Stylized Facts of Electricity Loads and Prices; 2.1 Introduction; 2.2 Price Spikes; 2.2.1 Case Study: The June 1998 Cinergy Price Spike; 2.2.2 When Supply Meets Demand; 2.2.3 What is Causing the Spikes?; 2.2.4 The Definition; 2.3 Seasonality; 2.3.1 Measuring Serial Correlation; 2.3.2 Spectral Analysis and the Periodogram; 2.3.3 |
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Case Study: Seasonal Behavior of Electricity Prices and Loads; 2.4 Seasonal Decomposition; 2.4.1 Differencing; 2.4.2 Mean or Median Week; 2.4.3 Moving Average Technique; 2.4.4 Annual Seasonality and Spectral Decomposition |
2.4.5 Rolling Volatility Technique2.4.6 Case Study: Rolling Volatility in Practice; 2.4.7 Wavelet Decomposition; 2.4.8 Case Study: Wavelet Filtering of Nord Pool Hourly System Prices; 2.5 Mean Reversion; 2.5.1 R/S Analysis; 2.5.2 Detrended Fluctuation Analysis; 2.5.3 Periodogram Regression; 2.5.4 Average Wavelet Coefficient; 2.5.5 Case Study: Anti-persistence of Electricity Prices; 2.6 Distributions of Electricity Prices; 2.6.1 Stable Distributions; 2.6.2 Hyperbolic Distributions; 2.6.3 Case Study: Distribution of EEX Spot Prices; 2.6.4 Further Empirical Evidence and Possible Applications |
2.7 Summary2.8 Further Reading; 3 Modeling and Forecasting Electricity Loads; 3.1 Introduction; 3.2 Factors Affecting Load Patterns; 3.2.1 Case Study: Dealing with Missing Values and Outliers; 3.2.2 Time Factors; 3.2.3 Weather Conditions; 3.2.4 Case Study: California Weather vs Load; 3.2.5 Other Factors; 3.3 Overview of Artificial Intelligence-Based Methods; 3.4 Statistical Methods; 3.4.1 Similar-Day Method; 3.4.2 Exponential Smoothing; 3.4.3 Regression Methods; 3.4.4 Autoregressive Model; 3.4.5 Autoregressive Moving Average Model; 3.4.6 ARMA Model Identification |
3.4.7 Case Study: Modeling Daily Loads in California3.4.8 Autoregressive Integrated Moving Average Model; 3.4.9 Time Series Models with Exogenous Variables; 3.4.10 Case Study: Modeling Daily Loads in California with Exogenous Variables; 3.5 Summary; 3.6 Further Reading; 4 Modeling and Forecasting Electricity Prices; 4.1 Introduction; 4.2 Overview of Modeling Approaches; 4.3 Statistical Methods and Price Forecasting; 4.3.1 Exogenous Factors; 4.3.2 Spike Preprocessing; 4.3.3 How to Assess the Quality of Price Forecasts; 4.3.4 ARMA-type Models; 4.3.5 Time Series Models with Exogenous Variables |
4.3.6 Autoregressive GARCH Models |
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Sommario/riassunto |
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This book offers an in-depth and up-to-date review of different statistical tools that can be used to analyze and forecast the dynamics of two crucial for every energy company processes-electricity prices and loads. It provides coverage of seasonal decomposition, mean reversion, heavy-tailed distributions, exponential smoothing, spike preprocessing, autoregressive time series including models with exogenous variables and heteroskedastic (GARCH) components, regime-switching models, interval forecasts, jump-diffusion models, derivatives pricing and the market price of risk. Modeling and Foreca |
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