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Access Type
Open Access
Document Type
thesis
Degree Program
Resource Economics
Degree Type
Master of Science (M.S.)
Year Degree Awarded
2013
Month Degree Awarded
September
Keywords
Wind, wholesale electricity markets, Oak Ridge Competitive Dispatch (ORCED) model, Do Not Exceed dispatch
Abstract
Among renewable energy resources, wind power is poised to contribute most significantly to meeting future wholesale electricity demand. However, the intermittent nature of wind power makes maintaining system reliability a challenge as the share of installed wind capacity on the grid increases. In New England, wind plants are currently unable to receive automatic dispatch instructions from the regional grid operator, but a centralized wind forecasting system under development will enable wind plants to be dispatched by ISO New England’s automatic dispatch software by 2016. Wind plants will receive an upper bound to their production through so-called Do Not Exceed (DNE) dispatch limits. This study evaluates how the automatic dispatch of wind plants in the ISO New England control area will impact wind plant output, emissions, wholesale energy market prices, and the system-wide generation mix.
Wind generation is modeled using 10-minute time-series wind speed data from the National Renewable Energy Laboratory’s Eastern Wind Dataset. Market outcomes for 2020 are then simulated using the spreadsheet-based Oak Ridge Competitive Electricity Dispatch (ORCED) model which mimics the economic dispatch of power plants in deregulated wholesale electricity markets. Results show that imposing DNE dispatch limits reduce total wind generation by a small amount – 6.47% over the course of the study year. The study finds that DNE dispatch limits constrain wind generation often – 28.4% of the year on average – but that the levels of wind generation avoided were typically small – 72.4% of DNE limit curtailment events were at levels below 5% of plant nameplate capacity.
DOI
https://doi.org/10.7275/4523515
First Advisor
Christian Rojas
Second Advisor
Daniel A. Lass