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Activity Number:
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130
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Type:
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Contributed
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Date/Time:
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Monday, August 3, 2009 : 8:30 AM to 10:20 AM
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Sponsor:
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Business and Economic Statistics Section
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| Abstract - #304614 |
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Title:
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Modeling Hourly Day-Ahead Electricity Demand in the MISO Market
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Author(s):
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V. A. Samaranayake*+ and Prasenjit Shil and Asitha Edirisingha
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Companies:
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Missouri University of Science and Technology and Ameren Services and Missouri University of Science and Technology
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Address:
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Department of Mathematics & Statistics, Rolla, MO, 65409-0020,
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Keywords:
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Time Series ; Electricity Market ; High Frequency Data ; Cyclical Components ; Forecasting
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Abstract:
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Traders in the electricity market use "in-house" models to predict the hourly demand for electricity for the next day, based on weather forecasts as well as information about potential problems in power generation and transmission. This information is then used by traders to offer bids to purchase and sell units of electricity for the next day. We investigate how well this trader generated day-ahead demand values can be modeled using publicly available data. We also investigate how well this day-ahead demand values predict the actual real-time electricity load in the Midwest Independent Transmission System Operator's (MISO) footprint.
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