TY - THES
TI - Improving the value of wind energy through geographic diversity of wind farms
AU - Pawlenchuk, T
AB - Wind farms are often concentrated geographically as they are cited in areas with strong resources. While this maximizes energy generation, it can decrease the value of that energy, particularly as the relative amount of wind increases in the overall system. Wind energy is growing rapidly in Alberta, and this research evaluates the potential to increase the value of the energy for new wind farms by building them in regions with lower annual wind speeds but less correlation to the rest of the fleet to capture higher market prices. The research identifies a trend between the deviation of the location’s potential generation output from the fleet’s average and the average annual energy revenue for a wind farm at that location based on data from existing wind farms. This trend is applied to predict the average annual energy revenue, payback periods, and internal rate of return for twelve candidate wind farm sites in the northern portion of the province. This prediction suggests that these locations have competitive payback periods between 5 and 9 years and internal rates of return between 15% and 33%. Alberta’s electricity market was also simulated with seven of these candidate locations added as potential new wind farms using Energy Exemplar’s Aurora software. The simulation built wind energy capacity at each of the seven hypothetical sites, for a total of 4727 MW of a possible 7000 MW. The simulation was also repeated withrenewable energy emissions credits removed, and although there was significantly less wind energy built, two of the hypothetical sites had capacity built for a total of 1020 MW, and made up a larger portion of the wind energy additions, suggesting that geographically diverse wind farms may be economical in Alberta’s electricity market.
DA - 2023/01//
PY - 2023
SP - 90
PB - University of Alberta
UR - https://era.library.ualberta.ca/items/f03e1956-5ed6-43c9-b1f0-b14ece0dd659
LA - English
M3 - Master's Thesis
KW - Wind Energy
KW - Human Dimensions
KW - Marine Spatial Planning
ER -