Latest revision as of 14:11, 3 August 2015

Weather Normalization

Personal Info

My name is Maria Dela Sancha from Zion, Illinois. I am NROTC student at Marquette University majoring in Mathematics with a minor in Computer Science, Class of 2016. I will be researching Weather Normalization for the Gas-Day Lab, with mentors, Dr. Corliss, Dr. Povinelli, and Dr. Brown.

Research Topic

Computing daily, monthly, and yearly gas usage in residential and commercial buildings is crucial for gas companies. When analyzing gas consumption, data analyst must look at all the factors that contribute to this total usage in order to come up with ways to save energy. Examples of these factors are; building structures, the economy, type of heating and cooling system being used, and one of the main factors that needs a lot of research is the weather. The weather is probably one of the main factors affecting consumption, but how can we understand the relationship between weather and consumption when the weather is never normal. When trying to summarize effectiveness of a new energy-saving heating system, one must consider that the weather last year was not the same at it was this year. In order to understand true gains and losses, weather normalization techniques are employed to gas consumption algorithms. To this day there is only a couple algorithms in use and not much research done on them. All of these algorithms also show a general idea of what we expect to see, but we still don't understand how to test for an exact measurement of effectiveness. We also don't understand how to analyze which algorithm is better when they all show similar results and when we still don't understand what complete normal weather looks like.

Weekly Accomplishments

Week 1

• Met with Dr. Brown, Dr. Povinelli, and Dr. Corliss to review research topic
• Introduction to Gas-Day Lab
• Met with Pat Benski (engineering research librarian)
• Thursday Gas-Day Seminar
• Articles read :
  • A Comparison of Weather Normalization Techniques for Commercial Building Energy Use
  • Utility Tracking: The Report Card for Alternative Energy Contractors
  • Defining Normal Weather for Energy and Peak Normalization

Week 2

• Attended open access seminar
• Start looking at specific algorithms
  • Kept notes of advantages, disadvantages, and other detail noticed of each algorithm
  • Met with Dr. Brown to review the Gas-Day algorithm
• Attended Thursday Gas-Day seminar
• Started a blueprint for a potential statistical test
• Articles read
  • An Economic Analysis of Consumer Response to Natural Gas Prices
  • Impact of Higher Natural Gas Prices on Local Distribution Companies and Residential Customers

Week 3

• Met with Dr. Brown and Dr. Povinelli to review test case
• Prepared for seminar presentation
• Started familiarizing with Gas-Day Matlab programs
  • Learn how to get data for specific op areas
• Started coding AGA algorithm to compare to Gas-Day graphs
• Articles read
  • Modeling and weather-Normalization of whole-housed metered data for residential end use load shape estimation
  • Energy Star- Climate and Weather

Week 4

• Met with Dr. Povinelli
• Thursday Seminar
• Continued coding AGA algorithm
  • Familiarized with Gas-Day Matlab programs
• Started working on a new blueprint for statistical test
• Began looking at specifications for IEEE Conference Research Paper

Week 5

• Met with Dr. Povinelli
• Finished up AGA algorithm
  • Code runs through each month of 20 years of data
  • Can compare monthly usage for 20 years
  • Can also compare yearly data for 20 years
• First outline of IEEE conference research paper complete
• Start coding test case
  • Used linear regression
  • Start building CI's and PI's

Week 6

• Articles read
  • Choosing a Base Temperature for Degree Days
  • Load Forecasting Methods
• meeting with Dr. Corliss
• REU lunch meeting
• continue working on draft
• BTP code
• continued working on regression model code
• started poster design for REU

Week 7

• What did I read
  • AN EVALUATION FRAMEWORK FOR PREDICTION INTERVAL ENGINES

FOR ENERGY DEMAND FORECASTS

• • Interpreting Regression Coefficients
• meeting with Dr. Corliss
• REU lunch meeting
• continued working on paper draft outline
• started working on algorithm testing leave-one-out-cross validation
• continued working on poster
• seminar

Week 8

• Meeting with Dr. Corliss
• finish and turn in poster presentation
• continue working on final paper
• complete and turn in abstract for booklets
• start working on formal presentation
• Seminar