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@inproceedings{Heuberger:2017,
author = {Heuberger, CF and Rubin, ES and Staffell, I and Shah, N and Mac, Dowell N},
publisher = {Elsevier},
title = {Power Generation Expansion Considering Endogenous Technology Cost Learning},
year = {2017}
}

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TY  - CPAPER
AB  - We present a mixed-integer linear formulation of a long-term power generation capacityexpansion problem including endogenous learning of technology investment cost. Weconsider a national-scale power system composed of up to 2000 units of 15 differentpower supply technologies, including international interconnectors for electricity importand export, and grid-level energy storage. We reformulate the non-convex learning curvemodel into a piecewise linear representation of the cumulative investment cost as a functionof cumulative installed capacity. The model is applied to a power system representativeof Great Britain for the years 2015 to 2050. We find that the consideration oftechnology cost learning rate influences the optimal capacity expansion and has systemicimplications on the profitability of the power units.
AU  - Heuberger,CF
AU  - Rubin,ES
AU  - Staffell,I
AU  - Shah,N
AU  - Mac,Dowell N
PB  - Elsevier
PY  - 2017///
TI  - Power Generation Expansion Considering Endogenous Technology Cost Learning
ER  -

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Professor Niall Mac Dowell FIChemE FRSC

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