The economics of storage, transmission and drought: integrating variable wind power into spatially separated electricity grids
AbstractTo mitigate the high variability of wind and make it a more viable renewable energy source, observers recommend greater integration of spatially-separated electrical grids, with high transmission lines linking load centers, scattered wind farms and hydro storage sites. In this study, we examine the economics of integrating large-scale wind energy into a grid characterized by fossil fuel thermal generation (Alberta) that is only weakly linked to one characterized by hydroelectric assets and the ability to store power behind hydro dams (British Columbia). We use a mathematical programming model to investigate the impact of increasing the capacity of the transmission link between the two disparate grids, which has not been done previously, and thereby shedding light on the issue of greater grid integration as a means of addressing intermittent renewable power. We find that, as wind capacity increases, costs of reducing CO2 emissions fall with increased transmission capacity between the grids, although this does not hold in all cases. Costs of reducing CO2 emissions are lowest during periods of drought. Over all scenarios, emission reduction costs vary between $20 and $60/t of CO2.
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Bibliographic InfoArticle provided by Elsevier in its journal Energy Economics.
Volume (Year): 34 (2012)
Issue (Month): 2 ()
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Web page: http://www.elsevier.com/locate/eneco
Wind power; Carbon costs; Electrical grids; Mathematical programming;
Find related papers by JEL classification:
- Q54 - Agricultural and Natural Resource Economics; Environmental and Ecological Economics - - Environmental Economics - - - Climate; Natural Disasters
- Q41 - Agricultural and Natural Resource Economics; Environmental and Ecological Economics - - Energy - - - Demand and Supply; Prices
- C61 - Mathematical and Quantitative Methods - - Mathematical Methods; Programming Models; Mathematical and Simulation Modeling - - - Optimization Techniques; Programming Models; Dynamic Analysis
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