05870nam 2200685 a 450 991087660620332120200520144314.01-118-67336-01-280-74001-997866107400170-470-05999-0(CKB)1000000000356733(EBL)284347(OCoLC)476034339(SSID)ssj0000203953(PQKBManifestationID)11199585(PQKBTitleCode)TC0000203953(PQKBWorkID)10174646(PQKB)11456878(MiAaPQ)EBC284347(EXLCZ)99100000000035673320060823d2006 uy 0engur|n|---|||||txtccrModeling and forecasting electricity loads and prices a statistical approach /Rafa WeronChichester, England ;Hoboken, NJ John Wiley & Sonsc20061 online resource (194 p.)Wiley finance seriesDescription based upon print version of record.0-470-05753-X Includes bibliographical references (p. [157]-170) and index.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 Summary1.7 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 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 Decomposition2.4.5 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 Applications2.7 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 Identification3.4.7 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 Variables4.3.6 Autoregressive GARCH ModelsThis 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 ForecaWiley finance series.Electric power consumptionForecastingStatistical methodsElectric utilitiesRatesForecastingStatistical methodsElectric power consumptionForecastingStatistical methodsCase studiesElectric utilitiesRatesForecastingStatistical methodsCase studiesElectric power consumptionForecastingStatistical methods.Electric utilitiesRatesForecastingStatistical methods.Electric power consumptionForecastingStatistical methodsElectric utilitiesRatesForecastingStatistical methods333.793/213015195Weron Rafa1756484Wiley Online Library (Servicio en línea)MiAaPQMiAaPQMiAaPQBOOK9910876606203321Modeling and forecasting electricity loads and prices4200272UNINA