Introduction to Renewable Project Simulation
A 1-day introduction to how 'System Advisor Model' and other software can forecast energy, IRR, NPV and other key parameters for renewable projects
25 April 2012, London, United Kingdom
- A brief review of renewable project modelling principles
- An introduction to various freely available tools, online resources and software packages
- The opportunity to see and try for yourself some basic renewable project modelling, plus a look at how this can be taken to more advanced levels of complexity
This one-day course informs attendees of some of the available software tools for modelling and simulating renewable energy projects in different segments (including Solar PV & CSP, Wind Power, Solar Heating and Geothermal). We introduce the basic principles involved and the varied capabilities of freely-available software tools, particularly NREL's "System Advisor Model (SAM)", illustrating the different levels of complexity available to suit different user needs. By analysing the results of such models and the variables which most affect them, we discuss the implications for renewable energy business models.
The course is accessible to business people from various job functions and company types, including:
- Business & Strategy Development, Financial & Investment Planning, Policymaking, Project Planning & Management, Senior Corporate Management (including Legal and Financial)
- Project Developers, Utilities and Power Generating Companies, Governments, Banks and other Investors, Grid Operators, Technology Supplies and Equipment Vendors
Level & Style
To get the most benefit from the course, attendees should have a basic knowledge of one or more renewable energy technologies and the basic parameters governing their operation. Although the key terms and principles will be explained, a basic knowledge of concepts such as feed-In-tariffs and other policy incentives, plus key financial parameters such as IRR, NPV and so on will also be helpful. Please ask in advance if you are in any doubt or need guidance.
This will be a highly interactive day, with attendees getting a chance to try out modelling tools for themselves. Thus attendees are required to bring their own laptop computer. We will advise on registration as to any full on-the-day requirements, including freely-available software.
(include lunch plus morning and afternoon refreshment breaks):
09:00 - 17:30
About your trainer
Daniel Norton holds a Bachelor’s degree in Mechanical Engineering from Carleton University and a Master’s Degree in Power Engineering with a focus on renewable energy from the Aachen University of Applied Sciences. Daniel has experience working for an EPC contractor involved in both Solar PV and Solar CSP power plant projects, where he analyzed (using computer models) the economic feasibility of potential projects and assisted in the preparation of project proposals and bids. Prior to this experience, he worked as a research assistant in the Juelich Solar Institute, where he developed material for university level courses for engineering students studying renewable energy systems. He currently works as a consultant for the German CleanTech Institute, where he assists investors with their search for the optimal renewable energy projects. He is a member of the German Association of Engineers (VDI) and speaks fluent English, German and Japanese.
“Very solid introduction from a very knowledgeable instructor”
“Rich in discussion”
“Good balance between theoretical and interactive”
A brief review of the key principles in renewable project modelling
- Cash flow variables, including energy production, costs, policy incentives, financing and so on
- Levelised Cost, its method of calculation and a critique of its usefulness
- The other outputs that are needed from a model: IRR, NPV, ROE, payback time etc.
Where to start: an introduction to example solutions
- Simple web-based tools
- Freely downloadable spreadsheets and software tools
- System Advisor Model (SAM)
Introducing SAM in more detail
- Understanding and navigating the user interface
- Input variables: the variety of complexities available
- Generating or finding location-specific data (e.g. climate data)
- Using and modifying pre-set models
The results of the model
- Running example project models
- Understanding the results
- Using real examples to compare models with published data: do they differ and, if so, why?
- Displaying and exporting a variety of results in a variety of ways
- Comparing complex model outputs with simpler counterparts
Sensitivity analysis and real-world project planning
- How do different variable affect the results of the model(s)?
- The significance of different financing choices
- The impact of factors such as location, technology cost changes and policy support mechanisms
- Implications for planning real renewable energy projects: on what does the business case most depend?