Electric Power System Applications Of Optimization - Second Edition-..

Features •Introduces the optimization of concepts to market, new investigated systems applications, and estimation and control concepts •Extends classical optimization theories to linear and non-linear programming, integer programming, and dynamic programming •Discusses state estimation, optimal power flow, pricing, and unit commitment applications •Describes the application of optimization to pricing and markets in a competitive environment Summary As the demand for energy continues to grow, optimization has risen to the forefront of power engineering research and development. Continuing in the bestselling tradition of the first edition, Electric Power System Applications of Optimization, Second Edition presents the theoretical background of optimization from a practical power system point of view, exploring advanced techniques, new directions, and continuous application problems. The book provides both the analytical formulation of optimization and various algorithmic issues that arise in the application of various methods in power system planning and operation. The second edition adds new functions involving market programs, pricing, reliability, and advances in intelligent systems with implemented algorithms and illustrative examples. It describes recent developments in the field of Adaptive Critics Design and practical applications of approximate dynamic programming. To round out the coverage, the final chapter combines fundamental theories and theorems from functional optimization, optimal control, and dynamic programming to explain new Adaptive Dynamic Programming concepts and variants. With its one-of-a-kind integration of cornerstone optimization principles with application examples, this second edition propels power engineers to new discoveries in providing optimal supplies of energy. Introduction Structure of a Generic Electric Power System Power System Models Power System Control Power System Security Assessment Power System Optimization as a Function of Time Review of Optimization Techniques Applicable to Power Systems Electric Power System Models Complex Power Concepts Three-Phase Systems Per Unit Representation Synchronous Machine Modeling Reactive Capability Limits Prime Movers and Governing Systems Automatic Gain Control Transmission Subsystems Y-Bus Incorporating the Transformer Effect Load Models Available Transfer Capability Illustrative Examples Power-Flow Computations Types of Buses for PF Studies General Form of the PFEs Practical Modeling Considerations Iterative Techniques for PF Solution Practical Applications of PF Studies Illustrative Examples Constrained Optimization and Applications Theorems on the Optimization of Constrained Functions Procedure for Optimizing Constrained Problems (Functions) Karush–Kuhn Tucker Condition Illustrative Problems Power Systems Application Examples Illustrative Examples Linear Programming and Applications Mathematical Model and Nomenclature in LP LP Solution Techniques Duality in LP Khun–Tucker Conditions in LP Mixed-Integer Programming Sensitivity Methods for Postoptimization in LP Power Systems Applications Illustrative Examples Interior Point Methods Karmarkar’s Algorithm Projective-Scaling Method Dual Affine Algorithm Primal Affine Algorithm Barrier Algorithm Extended IP Method for LP Problems FI Sequence Extended Quadratic Programming Using IP Method Illustrative Examples Nonlinear Programming Classification of NLP Problems Sensitivity Method for Solving NLP Variables Algorithm for Quadratic Optimization Illustrative Example (Barrier Method for Solving NLP) Illustrative Examples Dynamic Programming Characteristics of DP Concept of Suboptimization and the Principle of Optimality Formulation of DP Backward and Forward Recursion Computational Procedure in DP Computational Economy in DP Systems with More Than One Constraint Conversion of a Final Value Problem into an Initial Value Problem Illustrative Examples Lagrangian Relaxation Concepts Subgradient Method for Setting the Dual Variables Setting tk Comparison with LP-Based Bounds Improved Relaxation Summary of Concepts Past Applications Summary Illustrative Examples Decomposition Method Formulation of the Decomposition Problem Algorithm of the Decomposition Technique Illustrative Example of the Decomposition Technique State Estimation Historical Perspective of State Estimation Simple Mathematical Background State Estimation Techniques Applications to Power Network Illustrative Examples Optimal Power Flow OPF—Fuel Cost Minimization OPF—Active Power Loss Minimization OPF—VAr Planning OPF—Adding Environmental Constraints Commonly Used Optimization Technique (LP) Commonly Used Optimization Technique (NLP) Illustrative Examples Pricing Marginal Pricing Marginal Costing Marginal Revenue Pricing Policies for Regulated Systems and Markets Pricing Methods Economic Basis of Shadow Prices in Linear Programming (LP) LMP Alternative OPF Formulation for Pricing Using Duality in LP Unit Commitment Formulation of Unit Commitment Optimization Methods Illustrative Example Updating ln(t) in the Unit Commitment Problem Unit Commitment of Thermal Units Using Dynamic Programming Illustrative Problems Genetic Algorithms Definition and Concepts Used in Genetic Computation GA Approach Theory of GAs Schemata Theorem General Algorithm of GAs Application of GAs Application to Power Systems Illustrative Examples Functional Optimization, Optimal Control, and Adaptive Dynamic Programming System Performance Evaluation and Optimization of Functionals Solving the Optimal Control Problem Selected Methods of Determining the Control Functions for Convergence of Optimum Principle Adaptive Critics Design (ACD) and ADP Architecture of ACDs [] Typical Architectures of Variants or ADP (Critics Illustrations) Applications of DSOPF to Power Systems Problems Index Each chapter includes an introduction, conclusion, and problem set