@article {1477,
	title = {Evaluation of economically optimal retrofit investment options for energy savings in buildings},
	journal = {Energy and Buildings},
	volume = {49},
	year = {2012},
	pages = {327-334},
	abstract = {<p>In this study, a techno-economic evaluation method for the energy retrofit of buildings is introduced, geared toward finding the economically optimal set of retrofit measures. Split incentives of building owners and users are considered explicitly in a conventional (static) evaluation to identify the investment alternatives maximizing the net present value (NPV). Energy price uncertainty for various distributional assumptions of the stochastic variables is addressed through Monte Carlo simulation. Results from the simulation are used to compute probabilities and expected NPVs. Based on this, a sequential (dynamic) evaluation method is developed, featuring a real options investment appraisal. The real options approach is introduced as an advancement in the practice of economic evaluation of building retrofit investment options. The new method is applied to an office building in Germany, illustrating its performance. The case study results indicate that energy price changes significantly affect the profitability of retrofit investments, and that high price volatility creates a substantial value of waiting, making it more rational to postpone the investment.</p>},
	keywords = {Building energy efficiency, Energy conservation, Net present value, Real options},
	issn = {0378-7788},
	doi = {https://doi.org/10.1016/j.enbuild.2012.02.022},
	url = {https://www.sciencedirect.com/science/article/pii/S0378778812000990},
	author = {G{\"u}rkan Kumbaro{\u g}lu and Reinhard Madlener}
}
@article {1481,
	title = {A real options evaluation model for the diffusion prospects of new renewable power generation technologies},
	journal = {Energy Economics},
	volume = {30},
	year = {2008},
	pages = {1882-1908},
	abstract = {<p>This study presents a policy planning model that integrates learning curve information on renewable power generation technologies into a dynamic programming formulation featuring real options analysis. The model recursively evaluates a set of investment alternatives on a year-by-year basis, thereby taking into account that the flexibility to delay an irreversible investment expenditure can profoundly affect the diffusion prospects of renewable power generation technologies. Price uncertainty is introduced through stochastic processes for the average wholesale price of electricity and for input fuel prices. Demand for electricity is assumed to be increasingly price-sensitive, as the electricity market deregulation proceeds, reflecting new options of consumers to react to electricity price changes (such as time-of-use pricing, unbundled electricity services, and choice of supplier). The empirical analysis is based on data for the Turkish electricity supply industry. Apart from general implications for policy-making, it provides some interesting insights about the impact of uncertainty and technical change on the diffusion of various emerging renewable energy technologies.</p>},
	keywords = {Dynamic programming, Investment planning, Learning curve, Real options, Renewable energy technology diffusion, Turkey},
	issn = {0140-9883},
	doi = {https://doi.org/10.1016/j.eneco.2006.10.009},
	url = {https://www.sciencedirect.com/science/article/pii/S0140988306001241},
	author = {G{\"u}rkan Kumbaro{\u g}lu and Reinhard Madlener and Mustafa Demirel}
}
