# InfoCoBuild

## Design and Optimization of Energy Systems

Design and Optimization of Energy Systems. Instructor: Prof. C. Balaji, Department of Mechanical Engineering, IIT Madras. This course provides an introduction to design and optimization of energy systems. Topics covered in this course include introduction to system design; regression analysis and curve fitting; modeling of thermal equipment; system simulation (successive substitution, Newton-Raphson method); Lagrange multipliers, search methods, linear programming, geometric programming; simulated annealing, genetic algorithms; examples applied to heat transfer problems and energy systems such as gas and steam power plants, refrigeration systems, heat pumps and so on. (from nptel.ac.in)

 Introduction to Optimization

 Lecture 01 - Introduction to Optimization Lecture 02 - System Design and Analysis Lecture 03 - Workable System Lecture 04 - System Simulation Lecture 05 - Introduction to Flow Diagrams Lecture 06 - Successive Substitution Method Lecture 07 - Successive Substitution Method (cont.) Lecture 08 - Successive Substitution Method and Newton-Raphson Method Lecture 09 - Newton-Raphson Method (cont.) Lecture 10 - Convergence Characteristics of Newton-Raphson Method Lecture 11 - Newton-Raphson Method for Multiple Variables Lecture 12 - Solution of System of Linear Equations Lecture 13 - Introduction to Curve Fitting Lecture 14 - Example for Lagrange Interpolation Lecture 15 - Lagrange Interpolation (cont.) Lecture 16 - Best Fit Lecture 17 - Least Square Regression Lecture 18 - Least Square Regression (cont.) Lecture 19 - Least Square Regression (cont.) Lecture 20 - Nonlinear Regression (Gauss-Newton Algorithm) Lecture 21 - Optimization: Basic Ideas Lecture 22 - Properties of Objective Function and Cardinal Ideas in Optimization Lecture 23 - Unconstrained Optimization Lecture 24 - Constrained Optimization Problems Lecture 25 - Mathematical Proof of the Lagrange Multiplier Method Lecture 26 - Test for Maxima/Minima Lecture 27 - Handling Inequality Constraints Lecture 28 - Kuhn-Tucker Conditions Lecture 29 - Unimodal Function and Search Methods Lecture 30 - Dichotomous Search Lecture 31 - Fibonacci Search Method Lecture 32 - Reduction Ratio of Fibonacci Search Method Lecture 33 - Introduction to Multivariable Optimization Lecture 34 - The Conjugate Gradient Method Lecture 35 - The Conjugate Gradient Method (cont.) Lecture 36 - Linear Programming Lecture 37 - Dynamic Programming Lecture 38 - Genetic Algorithms Lecture 39 - Genetic Algorithms (cont.) Lecture 40 - Simulated Annealing and Summary

 References Design and Optimization of Energy Systems Instructor: Prof. C. Balaji, Department of Mechanical Engineering, IIT Madras. This course provides an introduction to design and optimization of energy systems.