Abstract:
An improved model for reducing the cost of long-term monitoring in Clean Development Mechanism
(CDM) lighting retrofit projects is proposed. Cost-effective longitudinal sampling designs use the
minimum number of meters required to report yearly savings at the 90% confidence and 10% relative
precision level for duration of the project (up to 10 years) as stipulated by the CDM. Improvements
to the existing model include a new non-linear Compact Fluorescent Lamp population decay model
based on the results of the Polish Efficient Lighting Project, and a cumulative sampling function
modified to weight samples exponentially by recency. An economic model altering the cost function
to a nett present value calculation is also incorporated.
The search space for such sampling models are investigated and found to be discontinuous and
stepped, requiring a heuristic for optimisation; in this case the Genetic Algorithm was used. Assuming
an exponential smoothing rate of 0.25, an inflation rate of 6.44%, and an interest rate of 10%,
results show that sampling should be more evenly distributed over the study duration than is currently
considered optimal, and that the proposed improvements in model accuracy increase expected project
costs in nett present value terms by approximately 20%. A sensitivity analysis reveals that the expected
project cost is most sensitive to the reporting precision level, coefficient of variance, and reporting
