{"product_id":"modeling-and-forecasting-electricity-loads-and-prices-9780470057537","title":"Modeling and Forecasting Electricity Loads and","description":"\u003cb\u003eBook Synopsis\u003c\/b\u003e\u003cbr\u003eModeling and Forecasting Electricity Loads and Prices is the only book to provide original statistical tools that will enable readers to model electricity loads and prices.   This book presents a common framework for modeling and forecasting two crucial processes for energy companies: electricity loads and prices.\u003cbr\u003e\u003cbr\u003e\u003cb\u003eTable of Contents\u003c\/b\u003e\u003cbr\u003e\u003cb\u003ePreface.\u003c\/b\u003e  \u003cp\u003e\u003cb\u003eAcknowledgments.\u003c\/b\u003e\u003c\/p\u003e \u003cp\u003e\u003cb\u003e1 Complex Electricity Markets.\u003c\/b\u003e\u003c\/p\u003e \u003cp\u003e1.1 Liberalization.\u003c\/p\u003e \u003cp\u003e1.2 The Marketplace.\u003c\/p\u003e \u003cp\u003e1.2.1 Power Pools and Power Exchanges.\u003c\/p\u003e \u003cp\u003e1.2.2 Nodal and Zonal Pricing.\u003c\/p\u003e \u003cp\u003e1.2.3 Market Structure.\u003c\/p\u003e \u003cp\u003e1.2.4 Traded Products.\u003c\/p\u003e \u003cp\u003e1.3 Europe.\u003c\/p\u003e \u003cp\u003e1.3.1 The England and Wales Electricity Market.\u003c\/p\u003e \u003cp\u003e1.3.2 The Nordic Market.\u003c\/p\u003e \u003cp\u003e1.3.3 Price Setting at Nord Pool.\u003c\/p\u003e \u003cp\u003e1.3.4 Continental Europe 13.\u003c\/p\u003e \u003cp\u003e1.4 North America.\u003c\/p\u003e \u003cp\u003e1.4.1 PJM Interconnection.\u003c\/p\u003e \u003cp\u003e1.4.2 California and the Electricity Crisis.\u003c\/p\u003e \u003cp\u003e1.4.3 Alberta and Ontario.\u003c\/p\u003e \u003cp\u003e1.5 Australia and New Zealand.\u003c\/p\u003e \u003cp\u003e1.6 Summary.\u003c\/p\u003e \u003cp\u003e1.7 Further Reading.\u003c\/p\u003e \u003cp\u003e\u003cb\u003e2 Stylized Facts of Electricity Loads and Prices.\u003c\/b\u003e\u003c\/p\u003e \u003cp\u003e2.1 Introduction.\u003c\/p\u003e \u003cp\u003e2.2 Price Spikes.\u003c\/p\u003e \u003cp\u003e2.2.1 Case Study: The June 1998 Cinergy Price Spike.\u003c\/p\u003e \u003cp\u003e2.2.2 When Supply Meets Demand.\u003c\/p\u003e \u003cp\u003e2.2.3 What is Causing the Spikes?.\u003c\/p\u003e \u003cp\u003e2.2.4 The Definition.\u003c\/p\u003e \u003cp\u003e2.3 Seasonality.\u003c\/p\u003e \u003cp\u003e2.3.1 Measuring Serial Correlation.\u003c\/p\u003e \u003cp\u003e2.3.2 Spectral Analysis and the Periodogram.\u003c\/p\u003e \u003cp\u003e2.3.3 Case Study: Seasonal Behavior of Electricity Prices and Loads.\u003c\/p\u003e \u003cp\u003e2.4 Seasonal Decomposition.\u003c\/p\u003e \u003cp\u003e2.4.1 Differencing.\u003c\/p\u003e \u003cp\u003e2.4.2 Mean or Median Week.\u003c\/p\u003e \u003cp\u003e2.4.3 Moving Average Technique.\u003c\/p\u003e \u003cp\u003e2.4.4 Annual Seasonality and Spectral Decomposition.\u003c\/p\u003e \u003cp\u003e2.4.5 Rolling Volatility Technique.\u003c\/p\u003e \u003cp\u003e2.4.6 Case Study: Rolling Volatility in Practice.\u003c\/p\u003e \u003cp\u003e2.4.7 Wavelet Decomposition.\u003c\/p\u003e \u003cp\u003e2.4.8 Case Study: Wavelet Filtering of Nord Pool Hourly System Prices.\u003c\/p\u003e \u003cp\u003e2.5 Mean Reversion.\u003c\/p\u003e \u003cp\u003e2.5.1 R\/S Analysis.\u003c\/p\u003e \u003cp\u003e2.5.2 Detrended Fluctuation Analysis.\u003c\/p\u003e \u003cp\u003e2.5.3 Periodogram Regression.\u003c\/p\u003e \u003cp\u003e2.5.4 Average Wavelet Coefficient.\u003c\/p\u003e \u003cp\u003e2.5.5 Case Study: Anti-persistence of Electricity Prices.\u003c\/p\u003e \u003cp\u003e2.6 Distributions of Electricity Prices.\u003c\/p\u003e \u003cp\u003e2.6.1 Stable Distributions.\u003c\/p\u003e \u003cp\u003e2.6.2 Hyperbolic Distributions.\u003c\/p\u003e \u003cp\u003e2.6.3 Case Study: Distribution of EEX Spot Prices.\u003c\/p\u003e \u003cp\u003e2.6.4 Further Empirical Evidence and Possible Applications.\u003c\/p\u003e \u003cp\u003e2.7 Summary.\u003c\/p\u003e \u003cp\u003e2.8 Further Reading.\u003c\/p\u003e \u003cp\u003e\u003cb\u003e3 Modeling and Forecasting Electricity Loads.\u003c\/b\u003e\u003c\/p\u003e \u003cp\u003e3.1 Introduction.\u003c\/p\u003e \u003cp\u003e3.2 Factors Affecting Load Patterns.\u003c\/p\u003e \u003cp\u003e3.2.1 Case Study: Dealing with Missing Values and Outliers.\u003c\/p\u003e \u003cp\u003e3.2.2 Time Factors.\u003c\/p\u003e \u003cp\u003e3.2.3 Weather Conditions.\u003c\/p\u003e \u003cp\u003e3.2.4 Case Study: California Weather vs Load.\u003c\/p\u003e \u003cp\u003e3.2.5 Other Factors.\u003c\/p\u003e \u003cp\u003e3.3 Overview of Artificial Intelligence-Based Methods.\u003c\/p\u003e \u003cp\u003e3.4 Statistical Methods.\u003c\/p\u003e \u003cp\u003e3.4.1 Similar-Day Method.\u003c\/p\u003e \u003cp\u003e3.4.2 Exponential Smoothing.\u003c\/p\u003e \u003cp\u003e3.4.3 Regression Methods.\u003c\/p\u003e \u003cp\u003e3.4.4 Autoregressive Model.\u003c\/p\u003e \u003cp\u003e3.4.5 Autoregressive Moving Average Model.\u003c\/p\u003e \u003cp\u003e3.4.6 ARMA Model Identification.\u003c\/p\u003e \u003cp\u003e3.4.7 Case Study: Modeling Daily Loads in California.\u003c\/p\u003e \u003cp\u003e3.4.8 Autoregressive Integrated Moving Average Model.\u003c\/p\u003e \u003cp\u003e3.4.9 Time Series Models with Exogenous Variables.\u003c\/p\u003e \u003cp\u003e3.4.10 Case Study: Modeling Daily Loads in California with Exogenous Variables.\u003c\/p\u003e \u003cp\u003e3.5 Summary.\u003c\/p\u003e \u003cp\u003e3.6 Further Reading.\u003c\/p\u003e \u003cp\u003e\u003cb\u003e4 Modeling and Forecasting Electricity Prices.\u003c\/b\u003e\u003c\/p\u003e \u003cp\u003e4.1 Introduction.\u003c\/p\u003e \u003cp\u003e4.2 Overview of Modeling Approaches.\u003c\/p\u003e \u003cp\u003e4.3 Statistical Methods and Price Forecasting.\u003c\/p\u003e \u003cp\u003e4.3.1 Exogenous Factors.\u003c\/p\u003e \u003cp\u003e4.3.2 Spike Preprocessing.\u003c\/p\u003e \u003cp\u003e4.3.3 How to Assess the Quality of Price Forecasts.\u003c\/p\u003e \u003cp\u003e4.3.4 ARMA-type Models.\u003c\/p\u003e \u003cp\u003e4.3.5 Time Series Models with Exogenous Variables.\u003c\/p\u003e \u003cp\u003e4.3.6 Autoregressive GARCH Models.\u003c\/p\u003e \u003cp\u003e4.3.7 Case Study: Forecasting Hourly CalPX Spot Prices with Linear Models.\u003c\/p\u003e \u003cp\u003e4.3.8 Case Study: Is Spike Preprocessing Advantageous?.\u003c\/p\u003e \u003cp\u003e4.3.9 Regime-Switching Models.\u003c\/p\u003e \u003cp\u003e4.3.10 Calibration of Regime-Switching Models.\u003c\/p\u003e \u003cp\u003e4.3.11 Case Study: Forecasting Hourly CalPX Spot Prices with Regime-Switching Models.\u003c\/p\u003e \u003cp\u003e4.3.12 Interval Forecasts.\u003c\/p\u003e \u003cp\u003e4.4 Quantitative Models and Derivatives Valuation.\u003c\/p\u003e \u003cp\u003e4.4.1 Jump-Diffusion Models.\u003c\/p\u003e \u003cp\u003e4.4.2 Calibration of Jump-Diffusion Models.\u003c\/p\u003e \u003cp\u003e4.4.3 Case Study: A Mean-Reverting Jump-Diffusion Model for Nord Pool Spot Prices.\u003c\/p\u003e \u003cp\u003e4.4.4 Hybrid Models.\u003c\/p\u003e \u003cp\u003e4.4.5 Case Study: Regime-Switching Models for Nord Pool Spot Prices.\u003c\/p\u003e \u003cp\u003e4.4.6 Hedging and the Use of Derivatives.\u003c\/p\u003e \u003cp\u003e4.4.7 Derivatives Pricing and the Market Price of Risk.\u003c\/p\u003e \u003cp\u003e4.4.8 Case Study: Asian-Style Electricity Options.\u003c\/p\u003e \u003cp\u003e4.5 Summary.\u003c\/p\u003e \u003cp\u003e4.6 Further Reading.\u003c\/p\u003e \u003cp\u003e\u003cb\u003eBibliography.\u003c\/b\u003e\u003c\/p\u003e \u003cp\u003e\u003cb\u003eIndex.\u003c\/b\u003e\u003c\/p\u003e","brand":"John Wiley \u0026 Sons Inc","offers":[{"title":"Default Title","offer_id":49402274218327,"sku":"9780470057537","price":91.8,"currency_code":"GBP","in_stock":true}],"thumbnail_url":"\/\/cdn.shopify.com\/s\/files\/1\/0817\/1739\/5799\/files\/9780470057537.jpg?v=1730479912","url":"https:\/\/bookcurl.com\/products\/modeling-and-forecasting-electricity-loads-and-prices-9780470057537","provider":"Book Curl","version":"1.0","type":"link"}