Chapter 1Management and Energy

Optimization

ByI Wayan Widhiada,ST, MSc, PhD

• Instructor: I WAYAN WIDHIADA, S.T,MSc, PhD• E-mail : widhiwyn@yahoo.com• Phone: 0361-3608029/ 081338300256• Office: Ruang Dosen Teknik Mesin, Kampus

Bukit Jimbaran Bali• Office hours: 8.00- 12.00 Monday to Friday or• By Appoitment

INSTRUCTOR INFORMATION

• How to create the mathematical model by Steady State Methods

• How to create the model into simulation in MATLAB/Simulink

• How to analyze the steady response• How to optimize the energy system

Course Descriptions

1. Fourer, R., D. M. Gay, B. W. Kernighan, AMPL: A Modeling Language for Math Programming Package, Duxbury Press, 1999.

2. Loucks, D. P., J. R. Stedinger and D. A. Haith, Water Resources Systems Planning and Analysis, Prentice Hall, Englewood Cliffs, 1981

3. Schrage, L., Optimization Modeling with LINGO, Lindo Systems, 1999.

4. Katsuhiko Ogata, Modern Control Engineering

Reference Book

SOFTWARE

Simulink Design OptimizationSimulink Design Optimization™ provides interactive tools, functions, and Simulink® blocks for estimating and tuning Simulink model parameters using numerical optimization. An interactive tool lets you automatically estimate model parameters such as friction and aerodynamic coefficients from test data to increase model accuracy. You can preprocess test data, select model parameters to estimate, start an optimization, and validate estimation results.

• Course works : 15%• Presentation : 15%• Attendance : 5%• Mid Term : 30%• Final Examination : 35%

Evaluation

1. INTRODUCTION1.1 SYSTEMS APPROACH A critical element of sustainable economic development

(Planning, management and desIgn) To critically analyze the true economic costs, benefits and

environmental consequences of projects Systems analysis involves the construction and linkage of

mathematical models of the physical and economic subsystems associated with resource allocation systems

Most systems models are based on statements of basic conservation laws (mass, energy, and momentum), but they can also be empirical or statistical.

Systems analysis models are generally broken down into two categories: simulation models and optimization models.

GENERAL DIAGRAM OF THE SYSTEM

ENERGY SYSTEM

INPUT OUTPUT

POLICIES

PARAMETERS

1.2 SIMULATION AND OPTIMIZATION MODELS

Simulation models are used to predict a system’s response to a given design configuration with great accuracy and detail, and to identify the probable costs, benefits, and impacts of a project (predicts the outcome of a single, specified set of design or policy variables)

Optimization models provide a means of reducing the number of alternatives which need to be simulated in detail, i.e., screening them. Optimization models are generally used for preliminary evaluation or screening of alternatives and to identify important data needs prior to

extensive data collection and simulation modeling activities.

1.3 Model Building Process The process of developing the mathematical simulation and

optimization models which represent the system under investigation consists of several steps :

1. The first step, problem identification2. a general outline and purpose of the model must be

established3. The analyst will need to identify the appropriate type of

model for the system4. In the next step, conceptualization and development

(appropriate computational techniques are also determined and implemented for the problem)

5. Calibration of the mathematical model is then performed to determine reliable estimates of the model parameters

General diagram of the steps in the model building process