Application of Monte Carlo
simulation in a study of viability
of a renewable energy project.
Manuel Carmona
Palisade Corporation
 Manuel Carmona, sales manager for Southern Europe,
London and Scandinavia.
 Palisade are leaders since 1984 in desktop, risk and
decision support software applications, with nearly
200,000 users worldwide!
 Nearly 30 years as providers of general purpose
quantitative decision-making tools and services.
 Leading distributor of analytical software and books.
 Headquartered in Ithaca, New York, with offices in
London, Sydney, Sao Paulo and Tokyo.
 Palisade products are taught in more than
 150 MBA programs worldwide and are used by
 the majority of Fortune 500 companies.
 To access interesting content about risk analysis visit our
website: www.palisade.com
Agenda
 Introduction
 Palisade Corporation
 Who are our customers
 We need to value the risk of a renewable
energy project.
 There are some uncertainties we need to
analyze before entering into contracts.
Famous projects
Project
Cost overrun
(# times )
Suez canal
20
Sydney opera
15
Concorde
12
4
Getting Answers with Probabilistic Modeling
• Probabilistic modeling can answer questions such as:
Which project has the highest chance of success and should
receive the funding?
What is the likelihood that my project will be completed on time and
on budget?
What are our chances to still make a deadline ?
How realistic are the contingencies for our cost estimate?
What is the effect of a given mitigation policy on my project?
How likely are my costs to overrun?
Which tasks are likely to make my total cost to overrrun?
Where does it make more sense to mitigate?
Renewable energy project
» To reduce manufacturing costs , we need
to estimate output of a renewable energy
plant.
We need an installation that consistently
delivers an output of at least 8MW.
Renewable energy project
» Solar power uncertainties
• Output depends on cloud coverage.
• Works only 12 h /day.
• Temperature of panels also has an impact on
output.
» Wind power uncertainties
• Output depends on a given wind speed range
• Location or wind generators
Building a risk model:Traditional
Approach vs. Monte Carlo Simulation
• Single point estimates (usually mean values)
• Best case / worst case scenario‘s
• Incremental “what if“ analyses
With traditional (deterministic) approaches, you lack the
ability to know the full range of possible outcomes and their
likelihood of occurrence!
Monte Carlo Simulation
 We use probability distributions to drive the collection of
random number samples.
 Thousands of possible scenarios and their likelihood of
occurence are calculated in a few seconds.
 We will obtain advanced analyses and features such as
tornado charts, scatter plots, input to output sensitivities,
effect of correlation, stress analyses, scenario analysis
etc.
Monte Carlo Simulation
 We need to infer distributions:
 From data or observations.
 From expert knowledge.
 Distributions should reflect as much as possible the
variables to be measured, but a good approximation is
usually good enough.
 Models should be algorithmically robust, and as simple as
possible, but no simpler.
 Simulation is one more tool in the risk/project manager
toolbox.
Benefits of Monte Carlo Risk Analysis model
» We can simulate output with a certain degree of accuracy
» We can optimize the cost of the installation against expected
average output, and other variables such as electricity prices.
» We can calculate probabilistic expected revenues of selling excess
power to the grid.
Palisade DecisionTools Suite 6.0
Monte Carlo Simulation
for Excel and MsProject
Simulation &Optimization with
Genetic Algorithms
Decision Tree Analysis
Statistical, Neural Network
& Data mining packages
Palisade Customers
Unilever
Shell
ExxonMobil
Statoil
Fluor
Norsk Hydro
Produksjon
Infineon
Petro Canada
Siemens Wind
Power AS
Conoco
Chevron
Network Rail UK
Grosvenor
BP
Conoco Phillips
Norway
Marathon Oil
Areva
Worley Parsons
EON
Lundin Norway AS
Endesa
DNV Norway
Enbridge
ENI
Transcanada
DONG
Bovis Lend Lease
Telenor ASA
Norway
Siemens
Schlumberger
EDF
Saudi Aramco
Centrica Energy
Norway
El Paso Energy
Halliburton
Technip
Enmax
Aker Kvaerner
Questions?