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Apportioned-Time Intermediate and Long-term Data Analysis (ATILDA) is time data analysis method that converts massive amounts of time-series data into a mathematical equation which can be more readily used by and interpreted by humans.
The methodology can be used for anlayzing data concerning human utilization of resources such as electricity, water, gas, communication etc. It is also used to understand weather patterns and their relation to resource utilization.
ATILDA's origins are in electric utility system capacity planning and is extremely well suited for this purpose.
ATILDA is particularly well suited for analyzing utility AMI and SCADA data. The method was originally invented to calculate growth on electric utility stations, transformers, and circuits. It has evolved to be used to:
evaluate weather sensitivity of load data
forecast load (intermediate and long-term)
load growth
base load growth
new business
characterize loads (customer, feeder, transformer, station)
evaluate risk
un-served energy
loss of load probability
analyze load usage
analyze distributed generation
Root 3 LLC has filed for a patent on the ATILDA methodology.
The ATILDA method processes raw data and converts it to a mathematical function. One year of raw data from hourly SCADA data (8760 data points) or one year of AMI data (~35,000 data points) can be represented with good accuracy with a simple mathematical equation.
The blue curve above is the original raw data. The red curve is the data calculated using the ATILDA method. Notice how well the calculated data represents the raw data.
The blue curve above represents the original raw data in which there are gaps (missing data values) in the data. The ATILDA method can be used to fill the gaps in the original data (red curve above).
Christopher Sticht (inventor)
Christopher Sticht is a consulting and R&D engineer. His work focuses on electric power systems, mathematics programming and machine learning. Mr. Sticht invented ATILDA, a revolutionary technique for load forecasting, weather adjustment and load growth algorithms. He is an authority in utility system planning, load analysis, planning software, renewables integration, and smart grid. During his tenure in the electric power industry, he has been involved with numerous aspects of power delivery.
He holds a MSEE from the University of Washington and a BSEE from Georgia Tech both with a concentration in power systems. His experience includes government research, consulting, contracting, work at two power flow software companies, and at three major US utilities, as well as contracting/consulting with numerous other utilities.
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