Energy Education At AUB - Texas A&M Universitypeople.qatar.tamu.edu/shehab.ahmed/NSF Presentations...ECE Core Courses: EECE 200, EECE 210, EECE 230, EECE 290, EECE 310, EECE 311, EECE

Energy Education At AUB

NSF Workshop on Electrical Energy

Education & Research

14-16 December 2009

Sami Karaki

American University of Beirut

Department of Electrical and Computer Engineering

About the University

Founded in 1866, the American University of Beirut bases its educational

philosophy, standards, and practices on the American liberal arts model of

higher education. A teaching-centered research university, AUB has 606 full-

time faculty members and a student body of more than 7,500 students.

The University

encourages freedom of

thought and expression

and seeks to graduate

men and women

committed to creative

and critical thinking, life-

long learning, personal

integrity, civic

responsibility, and

leadership.

About the University - 2

The University was granted accreditation in

June 2004 by the Commission on Higher

Education of the Middle States Association of

Colleges and Schools in the United States.

It includes six faculties: Agricultural and Food

Sciences, Arts and Sciences, Engineering and

Architecture, Health Sciences, Medicine

(including the Hariri School of Nursing) and

the Suliman S. Olayan School of Business.

AUB currently offers more than 100

programs leading to the bachelor's, master's,

MD, and PhD degrees. Its student body is 52

percent male and 48 percent female. The

language of instruction is English, except for

courses in the Arabic Department.

ECE Mission Statement

The mission of the ECE program is to impart a

basic understanding of electrical and computer

engineering built on a foundation of

mathematics, physical sciences, and technology;

to expose students to practical and major

design experiences; and to provide students

with a global perspective and an awareness of

their leadership role in regional development.

This preparation is augmented by the liberal

arts education offered to all undergraduates at

the American University of Beirut.

ECE Program Requirements

Mathematics: MATH 201, MATH 202, MATH 211, MATH 218 or 219, STAT 230, and

one of MATH 210, 224, 227, 251

Sciences: PHYS 210, PHYS 210L, CHEM 201 or 202, CHEM 203 or 205, and one

additional science elective

General Education: Arabic course, ENGL 206 and one other English course, two

social sciences courses, three humanities courses, one ethics course, and ENMG 400

ECE Core Courses: EECE 200, EECE 210, EECE 230, EECE 290, EECE 310, EECE

311, EECE 320, EECE 321, EECE 330, EECE 340, EECE 370, EECE 380

ECE Laboratories: EECE 310L, EECE 321L, and three additional laboratory electives

Restricted Electives: Six courses from the following list

Integrated Circuits: EECE 411 or 412, Computer Architecture: EECE 421

Software 1: EECE 430, 431, 432 or 433, Communication Systems: EECE 442

Computer Networks: EECE 450, Control Systems: EECE 460, Power Systems: EECE

471, Power Electronics: EECE 473

Electives: Six courses, at least two of which should be in ECE

Approved Experience: EECE 500

Final Year Project: EECE 501 and EECE 502

ECE Electric Energy Courses and Research Undergraduate

• Fundamentals of Electric Machines (EECE 370, 3 cr.)

• Electric Machines Lab (EECE 470L, 1 cr.)

• Power Systems Analysis Fundamentals (EECE 471, 3 cr.)

• Power Systems Lab (EECE 471L, 1 cr.)

• Power Electronics (EECE 473, 3 cr.)

• Electric Drives (EECE 474, 3 cr.)

• Power Electronics & Drives Lab (EECE 473L, 1 cr.)

• Industrial Electrification (EECE 475, 3 cr.)

• Power System Protection and Switchgear (EECE 476, 3 cr.)

• Undergraduate Research (EECE 499, 3 cr.)

ECE Electric Energy Courses Graduate

• Power System Planning (EECE 670, 3 cr.)

• Environmental Aspects of Energy Systems (EECE 671, 3 cr.)

• Energy Policy and Planning (EECE 672, 3 cr.)

• Renewable Energy Systems (EECE 675, 3 cr.)

• Electric Power System Operation & Control (EECE 677, 3 cr.)

• Advanced Power Systems Analysis (EECE 678, 3 cr.)

• Special Topics (EECE 698, 3 cr.)

Electric Energy Research

• Funded Research

• Open Gain (Funded by EU $220,000)

• Graduate

• Optimal Scheduling of Hybrid Renewable Energy Systems using

Load and Resource Forecasts (Master’s Thesis)

• Undergraduate

• Renewable Energy Lab Development

• Renewable Energy Supply with Hydrogen

• Renewable Energy in Lebanon

• Maximum Power Point Tracking under Uneven Solar Irradiance

• Maximum Efficiency Control of Induction Motors

Open Gain

Hybrid Renewable Energy System

11 kW Load

Proven 15 kW Wind Turbine

EMS

on/ off

mode

BT/ LD

mode

PV 4 kW RO Plant

Dump

SMC 5000x3

WB 6000x3

on/

off

GFM 185 27×3 Vm= 36.2V Im= 5.11 A Pm= 185W

SI 5048x3 SI 5048x3

P

20 kW Diesel

EMS Objectives

Provide resources to ensure balance power supply and

demand and consequently a good quality of supply

Minimize fuel consumption

Reduce components fatigue

◦ Battery charge-discharge cycles

◦ Battery sulfation and stratification

◦ Diesel engine start ups

Control Hierarchy

Supervisor

◦ Forecast and modeling functions

◦ Optimize decision set on status of diesel engine,

battery mode, load shedding, dump load, and RO

plant output

EMS

◦ Dispatch as per Optimum Decision set or a Basic

Logic , and data logging.

Low level Controllers

◦ Maximum power point tracking, AVR, governor,

battery charging, and RO plant operation.

◦ Stable and autonomous operation of components

EMS Commands

Turn on and off the diesel engine

Specify batteries charge/discharge level

Connect and disconnect loads (i.e. load shed)

Connect or disconnect dump load

Specify the grid forming unit

Specify RO plant output

Basic EMS Logic

“State: 1”

If (PRE >= PLD + PRO)

SDE= 0; SBT= -1; SDL= 1;

PDL= PRE – (PLD + PRO) – PBT;

“State: 2”

If (PRE + PBTD >= PLD + PRO)

SDE= 0; SBT= 1; SDL= 0;

“State: 3”

If (PRE + PDE >= PLD + PRO)

SDE= 1; SBT= 0; SDL= 0;

If (CBT <= k CBT,MAX ) SBT= 0;

Basic EMS Logic Continued“State: 4”

If (PRE + PBTD + PDE >= PLD + PRO)

SDE= 1; SBT= 1; SDL= 0;

“State: 5”

If (PSUP = PRE + PBTD + PDE >= PRO)

SDE= 1; SBT= 1; SDL= 0;

PLS= PRO + PLD - PSUP;

“State: 6”

If (PSUP = PRE + PBTD + PDE < PRO)

SDE= 1; SBT= 1; SDL= 0;

PLS= PLD;

ARO= PSUP;

Real-Time Implementation of EMS

Driver/DAQ

RS 232/RS 485

SMA

PLC

RO Plant

Hub

Forecast/ Optimization –Data Logging:

Matlab

PC/ Windows

RO Plant Model: Ecosimpro

XPC Real-time Platform

XPC -Host

OPC

TCP/ IP

TCP/ IP

EMS

YASDI

Simulink code

Renewable Energy Lab – System Layout

RS485

Sunny

Web Box

Computer

Windy Boy

1100LV

Sunny Boy 1100

Load

Wind Turbine

PV Cells

MotorDrive

Ethernet Cable

Switch

Sunny Island

2012/2224

Electric Utility

Batteries Charge/

Discharge

HTTP

TCP/IP

RPC

EMS

Renewable Energy Lab – Basic EMS Logic

To Control an Energy Management System, where the logic is donein the EMS and communication between devices is done using aRemote Procedure Protocol (RPC)

The values of each device (i.e. Power, Voltage & current) are readconstantly

Based on these values, the parameters of each device are set to beable to extract the maximum power from the Wind Turbine & PVCells at each instant

If the available renewable energy generation is higher than thedemand, then the batteries are charged

If the available renewable energy generation is lower than thedemand, then energy is extracted from the batteries

If the energy available in the batteries is not enough, then energy isextracted from the grid.

Renewable Energy with Hydrogen

Production and StorageLayout

Renewable Energy with Hydrogen

Production and StorageLayout

Given the weather data for a typical day.

Calculate available wind and solar power.

Determine load from given profile.

If there is excess renewable energy, use it to produce

hydrogen.

Else if there is a shortage, we use stored hydrogen in

order to produce power using the available fuel cell.

Optimal Scheduling of Hybrid Renewable

Energy Systems Cost Functional

Fuel cost of the power produced by DE in time interval Δt

Startup cost of the generator

Cost of load shedding

Battery cost of cycling and prolonged discharge

BTBT

M

j j

Cj

i

iiLSLSiiiDEDEiDEDEi

CN

N

tSOCktPCuuuStPHFu

1 0

24

1

1

1

)1()(

Constraints

chargingfor )1.0,min( BTBT

R

CONVBT VPPP

gdischarginfor )2.0,min( BTBT

R

CONVBT VPPP

R

DEDE

R

DE PPP 6.0

0.14.0 BTSOC

LDLS PP 0

LSBTDEDLROLD PPPPPP

Ingredients of Optimizer and Forecaster Optimization method: genetic algorithm, dynamic programming,

game theory, ordinal optimization.

◦ Wind speed forecast: uses half-daily forecast from weather stations,

and past data points (-5, -4, -3, -2, -1, 0, 4, 8) and weighted least

squares over a third order polynomial.

Solar irradiance (G in W/m2) forecast: use weather forecast to

predict cloud cover and find reduction ratio in irradiance:

Csky is the cloud cover index with values from 0 to 8.

Load forecast uses an ARIMA model accounting for weekly and

daily periodicity in the base load and weather sensitive component:

9.187.01 sky

clear

CG

G

)16824()168()24()(ˆ 321 tBctBctBctB

Simulation Results – Winter Week

If-Then-Else EMS Logic

Diesel engine power (red)

and battery power (blue)

Simulation Results – Typical Winter Week

If-Then-Else EMS Logic

Simulation Results – Winter Week

Optimal EMS Logic

Diesel engine power (red)

and battery power (green)

Simulation Results – Typical Winter Week

Optimal EMS Logic

Simulation Results

Typical Winter and Spring Weeks

EMS Type Energy

Demand

(kWh)

Renewable

Energy

(kWh)

Dump

Load

(kWh)

DE Energy

Produced

(kWh)

Fuel

(liters)

Diesel

Engine

Start Ups

Battery

Cycles

If-Then-Else 1959 2085 462 391 127.1 5 5

Optimal 1959 2085 463 389 129.5 15 1

EMS Type Energy

Demand

(kWh)

Renewable

Energy

(kWh)

Dump

Load

(kWh)

DE Energy

Produced

(kWh)

Fuel

(liters)

Diesel

Engine

Start Ups

Battery

Cycles

If-Then-Else 1959 1023 88.8 1181 384.2 12 12

Optimal 1959 1023 62.3 1105 367.7 16 7

Simulation Results Summary

Spring and Winter Weeks

A 50% reduction in the number of charge-discharge

batteries cycles

Reduction in fuel consumption

Acceptable number of DE starts (~2 per day)

Renewable Energy for Lebanon: Wind Data Analysis - Atlas Climatique du Liban

Average Wind

Speed

Elevation

(m/s)

Tower Height

(m)

Qlayaat 5.81 7 17

Tripoli 5.43 2 15

Beirut 5.15 35 12

Khalde 4.32 7 16

Cedars 4.29 1915 15

Dahr El Baidar 5.70 1512 16

Rayak 5.12 911 22

Ksara 5.04 918 13

Marjeyoun 5.95 775 13

Renewable Energy for Lebanon: Fundamental Data

Emission 525 g/kWh

Electricity Tariff 0.16 $/kWh

Price per Ton of CO2 10 $/ton

Land Value 25 $/ m2

Interest rate 10 %

Life 25 years

Renewable Energy for Lebanon: Wind Energy Site Evaluation

Wind Turbine System

WT

Number

Size

(MW)

Cost

($/kW)

O&M

($/kW/

year)

Area

(m2/WT

)

Total

(MW)

Marjeyoun 30 2.05 1350 34.8 1500 61.5

Akkar 40 2.05 1350 34.8 1500 82.0

Ksara 40 2.05 1350 34.8 1500 82.0

Wind Turbine System

Capacity Factor

Energy

(GWh)

Invest.

(M$)

O&M

(M$/

year)

Annuity

(M$)

Cost

($/kWh)

Marjeyoun 0.49 263.983 84.2 2.1 11.411 0.043

Akkar 0.40 287.328 112.2 2.9 15.214 0.053

Ksara 0.30 215.496 112.2 2.9 15.214 0.071

Totals 766.807 308.6 7.8 41.840 0.055

Economic Evaluation of

Wind Power Electricity

Wind Energy 767 GWh

Reduction in CO2 402 573 tonnes

Value of CO2 4.026 M$

Total Yearly Revenues 122.689 M$

Carbon Trading Revenues 4.026 M$

Total Annual Costs 41.840 M$

Net Profit with Carbon Trading 84.875 M$

Simple Payback Period 3.6 years

Renewable Energy for Lebanon: Wind Farm Layout

Each wind turbine will slow down the wind behind it as it pulls energy out

of it and converts it to electric energy.

Ideally, we would like the wind turbines to be spaced as far as possible in

the prevailing wind direction.

However the construction costs restrict us in placing them close together.

An example of installing the turbines:

Renewable Energy for Lebanon: Noise Level Assessment of Wind Turbines

Usual practice in designing wind farms is that turbine noise levels should

be kept to 40 dB. Therefore wind farms are to be installed more than

350m away from residential areas.

Power

(W)

Series

Cells

VOC

(V)

ISC

(A)

Maximum

dc Voltage

NOCT

(C)

Sharp 230 60 37 8.24 600 47

Kyocera 200 54 32.9 8.21 600 47

GE 200 54 32.9 8.21 600 45

Renewable Energy for Lebanon: PV Modules Assessed

Renewable Energy for Lebanon: Practical Inverter Data

PV

Number

Size

(kW)

Cost

($/kW)

O&M

($/kW/year)

Area

(m2/Unit)

Total

(MW)

Solar Electricity System 328 497 4500 13 3348 163

Capacity

Factor

Energy

(GWh)

Invest.

(M$)

O&M

(M$/year)

Annuity

(M$)

Cost

($/kWh)

Solar Electricity System

0.175 249.803 760.730 2.118 85.9 0.344

Renewable Energy for Lebanon: Photovoltaic Data

Solar Electric Energy 250 GWh

Reduction in CO2 131147 Tonnes

Value of CO2 1.311 M$

Total Yearly Revenues 39.968 M$

Carbon Trading Revenues 1.311 M$

Total Annual Costs 85.927 M$

Net Profit with Carbon Trading -44.647 M$

Simple Payback Period -17.0 years

Renewable Energy for Lebanon: Economics of Photovoltaic Electricity

Renewable Energy for Lebanon: Conclusions

System designed to produce 1000GWh from renewable energy sources.

750GWh from wind turbines, 250GWh from solar cell modules.

Best locations for wind generation are Marjayoun, Ksara and Akkar based on

energy generation and capacity factor.

The Enercon E82 wind turbine was used in this assessment based on an

approximate economical study, but more accurate data could reveal that other

turbines are also viable. The costs of production were ¢4.3/ kWh for Marjeyoun,

¢5.3/ kWh for Akkar, and ¢7.1/ kWh for Ksara.

For photovoltaic electricity production the cost was ¢34.4/ kWh, which makes it

uneconomical even if carbon trading is included when compared with a cost of

electric energy of ¢16/ kWh from fossil fuel.

The wind energy (767 GWh) will displace 403 000 tonnes of CO2 valued at $4.03

millions, and the solar energy (250 GWh) will displace 131100 tonnes valued at

$1.3 millions.

Conclusions:

Curriculum is broad enough to prepare students to go to the work place,

where with minimum training they are able to contribute and soon take

leading positions.

Many of our students go to leading graduate schools in Europe and the US

where they perform very well.

Energy education is delivered through of series of elective courses offered

by four faculty members.

Research is an important element of the knowledge building in the

undergraduate program through senior year design projects and a

specialized course structure.

Graduate research has been mainly in the thesis work of students at the

master’s level and recently at the PhD levels.

Plan to introduce a new elective on “Energy Conversion Principles” to

cater for a deficiency in thermal science and fluid mechanics and their

applications.