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RESEARCH PAPERS

A Real Options Methodology for Evaluating Risk and Opportunity of Natural Ventilation

[+] Author and Article Information
Lara V. Greden

 The Weidt Group, Inc., 5800 Baker Road, Minnetonka, MN 55345larag@twgi.com

Leon R. Glicksman

 Massachusetts Institute of Technology, Building Technology, Departments of Architecture and Mechanical Engineering, 77 Massachusetts Avenue, Rm. 5-418, Cambridge, MA 02139glicks@mit.edu

Gabriel Lopez-Betanzos

 Massachusetts Institute of Technology, Department of Computer Science and Electrical Engineering, 77 Massachusetts Avenue, Cambridge, MA 02139galb@alum.mit.edu

For example, because chiller equipment price depends partially on the price of steel, which has a high volatility, sometimes contracts are created to lock-in prices for future delivery of equipment at current prices to protect against the possibility of price increases.

It is not necessarily true that more energy efficient buildings have increased first costs, particularly if an integrated, whole building design process is used from the start (29).

J. Sol. Energy Eng 128(2), 204-212 (Dec 08, 2005) (9 pages) doi:10.1115/1.2188959 History: Received June 09, 2005; Revised December 08, 2005

The variable, uncertain nature of climate imposes risk in using solar and building technologies, such as natural ventilation (NV). To maximize the potential benefit from NV while reducing risk, a building could be designed for NV along with the “real option” to install mechanical cooling in the future, if needed. Traditional evaluation procedures use expected values, which fail to acknowledge the value of uncertainty when system performance is a nonlinear function of the uncertain variable. A real options methodology is proposed to evaluate the flexible building design under climate uncertainty. A building energy simulation is used to obtain probability distributions of the cost savings of the option-based NV strategy and of the time when (if) the mechanical cooling system is installed. A simplified stochastic temperature generator is used, and it may be used to evaluate real options for other technologies sensitive to future climate. The results of a real options analysis provide information to project investors on (a) the likelihood of exercising the option, and (b) the improved financial value of the technology when implemented with a flexible strategy.

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Copyright © 2006 by American Society of Mechanical Engineers
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Figures

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Figure 4

Timeline illustration of the modes in which the option-based NV building can exist

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Figure 11

Sample result of the frequency distribution of option value. The highest value is realized in the cases where exercise never occurs.

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Figure 3

By delaying, and potentially never requiring, the costs of mechanical cooling equipment, the option-based NV building may cost less than a hybrid building, assuming the flexible design provides for future installation of MC equipment at reasonable cost

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Figure 1

Payoff of a call option, with illustration of the probability distribution of possible future stock prices

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Figure 2

Stacks facilitate airflow in this naturally ventilated building at Nottingham University's campus in the United Kingdom (source: Brian Dean)

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Figure 5

Option value is defined by subtracting probabilistic NVO energy and equipment (i.e., exercise) costs from the total costs of the baseline MC building

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Figure 6

Real options simulation model for the option to install mechanical cooling in a naturally ventilated building subject to stochastic climate input

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Figure 7

Zonal mean, yearly temperature for the 35° latitude band calculated with data from MIT's Integrated Global Climate Model (24)

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Figure 8

Illustration of stochastic sample paths of hourly outdoor temperature for Chicago produced by the stochastic weather generation model

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Figure 9

In this illustrative figure of the sliding window decision rule, the window is 10h long and the maximum allowable temperature is 28°C. If a maximum of 5h within the 10-h window are allowed to be at or above 28°C, the option to install mechanical cooling is exercised in the second window shown.

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Figure 10

Illustration of the frequency distribution of the exercise date

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