Instructor

Rick Watson
Skype: rtw30606
Class: Tues/Thurs 12:30 - 1:45 pm in Correll 116

Course description

Energy Informatics involves analyzing, designing, and implementing systems to increase the efficiency of energy demand and supply systems. This requires the collection and analysis of data used to optimize energy distribution and consumption networks. Students will leverage the necessary information systems competencies and multi-disciplinary knowledge to increase societal energy efficiency.

General

Sustainability is usually defined as “meeting the needs of the current generation without compromising the ability of future generations to meet their own needs.” Sustainability is currently one of the most important issues facing our world, and will continue to be so for decades as it will take a long time to reverse some adverse environmental changes. Information System (IS) and Information Technology (IT) play a critical role in sustainable development, and Energy Informatics is an approach to addressing sustainability by reducing energy consumption. By learning about Energy Informatics, students enrolled in this class will leverage the necessary computing competencies and multi-disciplinary knowledge to contribute to creating a sustainable future.

The teaching approach will be a blend of interactive lectures, discussions, presentations, case studies, and in-class activities.

The course syllabus is a general plan for the course; deviations announced to the class by the instructor may be necessary.

Prerequisites, co-requisites

MIST2090 or equivalent

You need to be familiar with and competent in using personal computers, software productivity packages (word processor, presentation software, spreadsheet), and the Web. This prerequisite will be assumed by the instructor, since you are registered in this course.

Objectives

Students completing the course will

Topics

  1. Sustainability
  2. The energy industry
  3. Dominant logic
  4. Energy Informatics
  5. Data visualization
  6. Optimization methods

Text

Watson, R. T., & Boudreau, M.-C. (2011). Energy Informatics. Athens, GA: Green ePress. (Available in Kindle format from Amazon)

R & RStudio

R is a statistics package, and RStudio is the interface to R. Download the latest versions of both for your operating system.

Academic honesty

As a University of Georgia student, you have agreed to abide by the University's academic honesty policy, "A Culture of Honesty, " and the Student Honor Code. All academic work must meet the standards described in "A Culture of Honesty." Lack of knowledge of the academic honesty policy is not a reasonable explanation for a violation. Questions related to course assignments and the academic honesty policy should be directed to the instructor.

Team work

In this class, you will work in teams. As a result, review a short report on team effectiveness and establish a team agreement (sample agreement) for use by the team.

Laptop policy

Students are welcome to use laptops in class for note taking and completing class exercises, exclusively. If you plan to take notes, please advise and email a copy of the notes at the end of each class.

Attendance

Attendance and participation are required for this course. Excessive unexcused absences (i.e., greater than 4) will result in a Drop or Withdrawal for Non-Attendance according to UGA policy.

Group work

As there are 50 students in the class, and 8 people seeking graduate credit, we will have 8 teams. Each team will have at most 7 members, and the graduate will be the team leader. The same teams will be used for all group assignments. Please notify the instructor by 11:59pm of 8/22 of the composition of your group.

Assignments

Due dates are shown on the schedule

Energy efficiency and related issues in today's world (20 points) (Individual)

  1. The class will read a variety of recent articles on topics on energy and related issues. Each student will present a synopsis of one article and take the class beyond the confines of the article. For example, there could a presentation of a related article, a short video related to the article, a presentation of data related to the article (either for or against the author's argument) or a set of questions posed to the class to generate discussion about the article. Two thirds of the assessment will be based on the update. Each presentation should be limited to 5 minutes, and those exceeding the time limit risk a reduction in their grade. Articles have been assigned by the instructor (3 points)
  2. Also, each student is expected to identify one relevant article to add to the reading list. These additions are due by the end of the semester. All additions should be posted to the Discussion list on eLC titled "Energy Informatics reading list additions" with a paragraph justifying the choice, the article's title, and its URL. (2 points)
  3. There is an eLC-based quiz with two questions for each article (15 points).

Solutions to global climate change (10 points) (Group)

Possible solutions to global climate change will be presented in class as per the schedule. Presentation will be no more than 10 minutes.

Topic Group Date
Geothermal    
Wind Colin O'Leary, Nick Oney, Clay Fortin, Gregg Thompson, Daniel Helsing, Fernando Cruz, Adam Russo (4) 8/29
Nuclear fusion Samantha Clark, Imran Doraney, Ishani Podder, Joe Mahoney, Marah Korth, Van Ha Huynh (7) 8/31
Geo-engineering Coby Horton, Collin Abell, Ji Ahn, Lindsey Harnack, Sheridan Nulty, Vira Ogdanets, Jungwoo Park (2) 8/29
Non-chemical batteries    
Photo voltaic cells Dalton Corbin, Allison Brodsky, Gunjeet Gambhir, Hunter Ziegler, Shawn Myers, Dylan Patel, Kevin Sullivan (5) 8/31
Hydroelectric Zachary Kammer, Fabrice Kengne, Jonathan Diaz, Nicole Anglace, Preston Elam, Sebastian Rendon, Tal Botnar (6) 8/31
Chemical batteries    
Biomass    
Thorium reactor Adeyinka Joseph, Matthew Allen, Trey Bonham, Nate Bryant, Nick Efird, Jessica Kim, Reginald Mosley (1) 8/29
Tidal Charles Fragakis, Minsoo Kim, Ellen Barrow, Ashley Marshall, Alisha Merchant (8) 8/29
Bio fuels Robert Falciglia, Madeline Hanley, Natalie Raia, Devan Clark, Aalok Patel (3) 8/31

Systems Dynamics (10 points) (Group)

The advent of autonomous electric cars will have many implications for energy supply and demand, as well as many other aspects of the economy. One way to explore and identify these many implications is to develop a conceptual Systems Dynamics model using Insight Maker. You will learn the principles of systems dynamics and then apply them to develop a comprehensive model. Background reading.

National energy and sustainability policy (10 points) (Group)

Some nations have taken leadership in creating sustainable societies, and their actions are an opportunity for us to learn. Groups will be asked to give a 10-15 minute report on the policies of a country. You should focus on what actions are being taken to apply the principles of Energy Informatics, if at all. To avoid replication, get approval for your country from the instructor before proceeding. The following table lists the current status of presentations.

Country Group leader Date
China Coby Horton (2) 11/28
Switzerland Colin O'Leary (4) 11/28
Singapore Charles Fragakis (8) 11/28
Germany Zachary Kammer (6) 11/28
India Dylan Patel (5) 11/30
Australia Samantha Clark (7) 11/30
France Adeyinka Joseph (1) 11/30
USA Robert Falciglia (3) 11/30

Controlled environmental agriculture (10 points) (Group)

Based on the class discussion of Green greenhouses and the use of LED lighting, answer the following questions.

  1. If the lights are left on continually for 20 hours per day, what is the annual cost per light?
  2. If lettuces require at least 3 ETR moles/day, how many days of the year are LEDs required?
  3. The plant grower intends to operate the facility 20 hours each day. What operational hours would you recommend (e.g., 2am to 10pm)?
  4. Describe a strategy for operating the LEDs that will meet growth targets while minimizing electricity cost. Amend the R program to evaluate this strategy.

The electricity and solar radiation files can be downloaded in feather format using a right-click. You should put these files in your project directory.

Energy University courses (8 points) (Individual)

There are four Schneider Electric Energy University courses to complete. You will need to sign up for the courses.

Select the following courses from the catalog. If you wish, you can suggest substitutes. Consult the instructor first.

  1. Energy efficiency fundamentals
  2. Financial Analysis of Projects I
  3. Financial Analysis of Energy Efficiency Projects II
  4. Strategic Energy Planning
Dropbox the certificate of completion for each course by the due date listed on the class schedule.

R assignments (30 points) (Individual)

Course evaluation (2 points) (Individual)

Grading

Item Points
Total 100
Energy efficiency and related issues 20
Solutions to global climate change 10
Systems dynamics 10
National energy and sustainability policy 10
Controlled environment agriculture 10
Energy university courses 8
R assignments 30
Course evaluation completion 2
If you are unable to complete an exercise on time or take an exam at the specified time, please advise the instructor as soon as possible so that alternative arrangements can be made.

Schedule

Class Day Date Topic Assignment or additional material
1 Tuesday 08-15 How global warming works (CC)
The secret to rising sea levels - thermal expansion (CC)
Ocean acidification by the alliance for climate education (CC)
Climate and war (CC)
Biodiversity loss (Text only)
More about the problem
The changing state of the climate (CC)
Rising sea levels (CC)
Acid test: The global challenge of ocean acidification (CC)
Climate change is happening. Here's how we adapt (CC)
Human activities that affect biodiversity (CC)
2 Thursday 08-17 The problem (slides)
Energy Informatics (slides) (Introduction)
Energy efficiency fundamentals
3 Tuesday 08-22 Energy Informatics
Introduction to R (slides)
 
4 Thursday 08-24 Introduction to R Financial Analysis of Projects I
5 Tuesday 08-29 Solutions to the problem presentations  
6 Thursday 08-31 Solutions to the problem presentations  
7 Tuesday 09-05 Data visualization with R (slides)  
8 Thursday 09-07 Data visualization with R Financial Analysis of Projects II
9 Tuesday 09-12 Smart Grid, Smart Buildings
(Dr. Thomas Lawrence)
London conference
10 Thursday 09-14 Digial data streams (slides) R1
11 Tuesday 09-19 Time series analysis with R (slides) Strategic Energy Planning
12 Thursday 09-21 Time series analysis with R  
13 Tuesday 09-26 Sustainability and IS strategy (slides)
 
14 Thursday 09-28 Design principles of Energy Informatics (slides) Swidget™
R2

15 Tuesday 10-03 Systems dynamics (Dr. Dan Everett) Advanced Practices Council
16 Thursday 10-05 Systems dynamics (Dr. Dan Everett)  
17 Tuesday 10-10 Optimization with R (slides) R3
18 Thursday 10-12 Optimization with R  
19 Tuesday 10-17 Demand response systems  
20 Thursday 10-19 Deloitte presentation (Ed Thomas)  
21 Tuesday 10-24 Controlled environment agriculture (slides)  
22 Thursday 10-26 Kevin Kirsche R4
Systems dynamics
23 Tuesday 10-31 Green IS & IT & General model for the grid
The shift in dominant logic
 
24 Thursday 11-02 Digitization of capital (slides)
 
25 Tuesday 11-07 Maritime Informatics (case 1) (case 2) (case 3)
Autonomous shipping
26 Thursday 11-09 Maritime Informatics
Green steaming
 
27 Tuesday 11-14 Spatial-temporal data analytics (slides) Controlled environment agriculture
28 Thursday 11-16 Dashboards (slides)  
29 Tuesday 11-21 Thanksgiving  
30 Thursday 11-23 Thanksgiving  
31 Tuesday 11-28 National policy reports R5
32 Thursday 11-30 National policy reports  

Notes

  1. “What makes subjects like biology and climate science so hard is not just that they involve so many variables; it’s that the crucial phenomena in them occur over such a wide range of scales. Biologists need to contend with everything from nano-size DNA molecules on up to cells, organs, organisms and ecosystems. For climate scientists the relevant scales go from the molecular (the photochemistry of ozone) to the global (the fluid mechanics of the jet stream). Many of the great scientific puzzles of our time have this multiscale character.” (http://opinionator.blogs.nytimes.com/2012/10/15/visualizing-vastness/)