Wind Energy Due Diligence
Driven by Weather Modeling
A weather solution to a weather challenge
Our Approach to Validation
A robust and innovative wind energy assessment methodology is central to wind project due diligence, but accuracy is what matters most to developers and investors. Clients rely on our wind energy analysis to make major project investment decisions and it is critical that we provide estimates they can trust. Since our innovative approach based on weather modeling is unique to the wind sector, as a responsible participant in the industry, we continuously compare pre-construction energy estimates to actual production data. In one of the world’s largest wind assessment validation studies, Vaisala's estimates exhibited near zero mean bias error.
Our accuracy and approach to validation
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Briefing on how Vaisala simultaneously achieves stability and innovation through intelligent use of validation.
This industry-leading validation study examines 30 wind farms and a total of 127 wind farm years to demonstrate that Vaisala's energy estimates are calibrated with respect to actual production data, exhibiting near zero mean bias error.
Developers and investors need energy estimates that provide confidence and accuracy. Yet these goals can be at odds with each other since one is achieved through familiarity with a stable approach and the other achieved through innovation. Article...
Modeling: A Science Driven Approach to Wind Assessment
Numerical Weather Prediction (NWP) modeling, also called mesoscale modeling, uses current weather conditions to simulate future weather or provide proxy information when direct observations are not available. This methodology models the entire atmosphere using complex, physics-based equations that require powerful supercomputers to create realistic weather data.
In the wind industry, NWP models have been used to predict energy production for more than two decades. The technique was first introduced because it provides wind data anywhere in the world – even before observations are collected. It also captures long-term wind variability and can be customized to the application. For example, spatial resolutions are tailored to developer needs, course data for prospecting within a large region or fine-scale data for micro-siting and due diligence.
NWP makes it possible to model wind anywhere worldwide and forms the backbone of Vaisala's wind resource assessment methodology. It allows for far more accuracy in resource assessment than previous approaches. The 3TIER Services team at Vaisala pioneered and continues to innovate this approach to wind resource assessment, now widely used throughout the industry.
Managing Uncertainty in Wind Investment and Financing
How do you accurately quantify performance uncertainty? If you are evaluating two wind projects with similar wind production profiles and one has an energy estimate uncertainty of 10% and the other has 8%, you will likely choose the one with lower uncertainty. But how were those numbers calculated? Can you actually trust the energy estimates coming across your desk?
Some level of uncertainty is introduced at every step of the wind due diligence process from the measurements collected during the met campaign to the work done by analysts to calculate the final P50 and P90 values.
Vaisala’s comprehensive due diligence approach evaluates hundreds of sources of uncertainty throughout every step of the assessment process and presents risk in understandable, intuitive terms using our proprietary Energy Risk Framework.
In depth - "Avoiding Surprises at the Investment Table" (written by Vaisala's Matthew Hendrickson and published by Windpower Engineering & Development) discusses advanced approaches to uncertainty modeling.
A Weather Modeling Pioneer and Industry Innovator
Vaisala is not just another wind energy consultant. While our approach follows many industry standard best practices, we pioneered the broad integration of NWP (Numerical Weather Prediction) models into the wind assessment process as well as a number of other advancements.
Our methodology incorporates all of the leading climate indices and numerous observational data inputs to better capture the influence of surrounding weather effects as well as project-specific losses, such as wakes. Vaisala also takes an advanced approach to calculating project uncertainty through its proprietary Error Risk Framework model, which allows clients to objectively make decisions between projects and better justify investments.
Our team is different too. Our analysts are trained atmospheric scientists with access to one of the world's largest super-computing centers dedicated to renewable energy. This expertise and infrastructure allows our team to run the most sophisticated weather models at a higher spatial and temporal resolution than anyone else in the industry.