LEADER 05600nam 2200709 a 450 001 9911004824503321 005 20200520144314.0 010 $a9786612738098 010 $a9781282738096 010 $a1282738097 010 $a9780123815446 010 $a0123815444 035 $a(CKB)2550000000014092 035 $a(EBL)566740 035 $a(OCoLC)643053601 035 $a(SSID)ssj0000416614 035 $a(PQKBManifestationID)12190789 035 $a(PQKBTitleCode)TC0000416614 035 $a(PQKBWorkID)10435681 035 $a(PQKB)10235012 035 $a(MiAaPQ)EBC566740 035 $a(PPN)170601617 035 $a(FR-PaCSA)88812178 035 $a(FRCYB88812178)88812178 035 $a(EXLCZ)992550000000014092 100 $a20091209d2010 uy 0 101 0 $aeng 135 $aur|n|---||||| 181 $ctxt 182 $cc 183 $acr 200 10$aElectrical load forecasting $emodeling and model construction /$fSoliman Abdel-hady Soliman, Ahmad M. Al-Kandari 210 $aBurlington, MA $cButterworth-Heinemann$dc2010 215 $a1 online resource (441 p.) 300 $aDescription based upon print version of record. 311 08$a9780123815439 311 08$a0123815436 320 $aIncludes bibliographical references and index. 327 $aFront Cover; Half Title Page; Title Page; Copyright; Dedication; Table of Contents; Acknowledgments; Introduction; Outline of the Book; Chapter 1. Mathematical Background and State of the Art; 1.1 Objectives; 1.2 Matrices and Vectors; 1.3 Matrix Algebra; 1.3.1 Addition of Matrices; 1.3.2 Matrix Subtraction (Difference); 1.3.3 Matrix Multiplication; 1.3.4 Inverse of a Matrix (Matrix Division); 1.4 Rank of a Matrix; 1.5 Singular Matrix; 1.6 Characteristic Vectors of a Matrix; 1.7 Diagonalization; 1.8 Partitioned Matrices; 1.9 Partitioned Matrix Inversion; 1.10 Quadratic Forms 327 $a1.11 State Space Representation1.12 Difference Equations; 1.13 Some Optimization Techniques; 1.13.1 Unconstrained Optimization; 1.13.2 Constrained Optimization; 1.14 State of the Art; References; Chapter 2. Static State Estimation; 2.1 Objectives; 2.2 The Static Estimation Problem Formulation; 2.2.1 Linear Least Error Squares Estimation; 2.2.2 Weighted Linear Least Error Squares (WLES) Estimation; 2.2.3 Constrained Least Error Squares (CLES) Estimation; 2.2.4 Recursive Least Error Squares (RLES) Estimation; 2.2.5 Nonlinear Least Error Squares (NLLES) Estimation 327 $a2.3 Properties of Least Error Squares Estimation2.4 Least Absolute Value Static State Estimation; 2.4.1 Historical Perspective; 2.4.2 Least Absolute Value of Error Estimation; 2.4.3 Least Absolute Value Based on Linear Programming; 2.4.4 Schlossmacher Iterative Algorithm; 2.4.5 Sposito and Hand Algorithm; 2.4.6 Soliman and Christensen Algorithm; 2.5 Constrained LAV Estimation; 2.6 Nonlinear Estimation Using the Soliman and Christensen Algorithm; 2.7 Leverage Points; 2.8 Comparison between LES Estimation and LAV Estimation Algorithms; References 327 $aChapter 3. Load Modeling for Short-Term Forecasting3.1 Objectives; 3.2 Introduction; 3.3 Base Load; 3.4 Weather-Dependent Load; 3.4.1 Temperature; 3.4.2 Wind Speed; 3.4.3 Humidity; 3.4.4 Illumination; 3.5 Residual Load; 3.6 Short-Term Load Models; 3.6.1 Multiple Linear Regression; 3.6.2 General Exponential Smoothing; 3.6.3 Stochastic Time Series; 3.6.4 Qualities of Forecasting Models; 3.7 Special Load-Forecasting Models; 3.7.1 Model A: Multiple Linear Regression Model; 3.7.2 Model B: Harmonics Model; 3.7.3 Model C: Hybrid Model; References 327 $aChapter 4. Fuzzy Regression Systems and Fuzzy Linear Models4.1 Objectives; 4.2 Fuzzy Fundamentals; 4.3 Fuzzy Sets and Membership; 4.3.1 Membership Functions; 4.3.2 Basic Terminology and Definitions; 4.3.3 Support of a Fuzzy Set; 4.3.4 Normality; 4.3.5 Convexity and Concavity; 4.3.6 Basic Operation; 4.4 Fuzzy Linear Estimation; 4.4.1 Nonfuzzy Output (Yj =mj); 4.4.2 Fuzzy Output Systems; 4.5 Fuzzy Short-Term Load Modeling; 4.5.1 Multiple Fuzzy Linear Regression Model: Crisp Data; 4.5.2 Multiple Fuzzy Linear Regression Model: Fuzzy Data; 4.5.3 Fuzzy Load Model B; 4.5.4 Fuzzy Load Model C 327 $a4.6 Conclusion 330 $aSuccinct and understandable, this book is a step-by-step guide to the mathematics and construction of electrical load forecasting models. Written by one of the world's foremost experts on the subject, Electrical Load Forecasting provides a brief discussion of algorithms, their advantages and disadvantages and when they are best utilized. The book begins with a good description of the basic theory and models needed to truly understand how the models are prepared so that they are not just blindly plugging and chugging numbers. This is followed by a clear and rigorous exposition of the 606 $aElectric power-plants$xLoad$xForecasting$xMathematics 606 $aElectric power systems$xMathematical models 606 $aElectric power consumption$xForecasting$xMathematics 615 0$aElectric power-plants$xLoad$xForecasting$xMathematics. 615 0$aElectric power systems$xMathematical models. 615 0$aElectric power consumption$xForecasting$xMathematics. 676 $a333.793/213015195 700 $aSoliman$b S. A$025588 701 $aAlkandari$b Ahmad M$01823147 712 02$aScienceDirect (Servicio en línea) 801 0$bMiAaPQ 801 1$bMiAaPQ 801 2$bMiAaPQ 906 $aBOOK 912 $a9911004824503321 996 $aElectrical load forecasting$94389643 997 $aUNINA