Historical and TMY data through the Solcast API Toolkit

By: Dr. Nick Engerer, Guest Author
Let’s face it. Building a solar farm is a big job. It’s hard work. Getting the job done takes the direct involvement of many tens to hundreds of people. Working behind the scenes are perhaps a thousand or more additional folks.  It starts with finding a suitable site by sifting through available land, local regulations, environmental limitations and increasingly, constraints on the network. Then comes the solar farm design and engineering challenge, including the layout of the plant, optimising it to the topography or shading from vegetation, being up to date on the latest in construction materials….

So when it comes to the process of planning, financing, operationalising and managing not just one solar farm, but many tens, perhaps thousands of these facilities, these challenges can mount in ways that are sometimes overwhelming.  Given the global mandate transitioning electricity generation toward more sustainable sources, making this process an efficient and easy one, is highly important for many reasons. This requires that solar energy generation should not only be affordable, it should also be exceptionally profitable and thereby wildly successful.  But, for that to occur, the deployment and operation of solar power technologies must be a transparent and straightforward investment, which at the least delivers on, and at best exceeds the projected return on investment (ROI) for its financiers.

Solar data services for confident investors

For more than a decade now, solar data services have been a key part of the successful deployment of solar energy generation facilities. Climatological assessments of the expected available solar radiation have underpinned early stage prospecting of the best locations for their deployment.  Historical time-series data of the actual available solar irradiance over the past 2-3 years have been utilised in the investment due diligence process to give investors confidence. Recent or real-time solar radiation data are often used in performance assessments of plant yield to diagnose any shortfall in an expected generation.  These respective categories of analysis are made possible by these solar data services, establishing themselves as clearly important aspects of solar power facility deployment and operations.

However, solar data services have not always delivered on their expected outcomes.  Some low-cost sources of data have become known to contain significant shortfalls in their methodology, lacking real information about cloud cover conditions and instead relying on coarse weather model data and sparse ground measurements.  This leads to inaccurate climatological assessments, solar PV power modelling bias errors and incorrect guidance to investors. Other higher costs sources of information have not delivered on the promise of providing a commensurate high quality in their resource assessment information, and have dysfunctional cost models that do not allow separation of the various categories of solar irradiance data required at individual project stages.  Typical meteorological year data is needed for prospecting and site assessment efforts. Whereas time-series data are needed in the due diligence process (where a 3rd party assesses solar farm developer estimates to ensure investors are getting what they pay for!) or for periodic yield assessments. So why should one customer have to buy both at once? Data acquisition has also been found to take many days or even weeks from order to deliver, with an acute lack of free trial data in the areas of customer interest.

These limitations create significant barriers to the worldwide deployment and operation of solar energy generation, which brings us back to that global mandate for rapid deployment of sustainable electricity production.  Our team at Solcast calls this ‘building the solar-powered future’. And each day, our team rallies around the transformative purpose making it easy for the hard-working folks planning, building, assessing and operating solar energy generation assets, big and small, to get the job done.  As a part of our mission, we’ve recognised the barriers created by the existing providers of climatological and historical solar data services, and developed an entirely new way to test, purchase and acquire TMY (typical meteorological year) and historical time-series data.

It’s all made possible through the Solcast API Toolkit, which is a web interface that contains all of the data products Solcast has to offer (including forecasting and real-time data!).  We’ve built a totally new experience for transacting on solar data services, from scratch, with heaps of user feedback along the way. The result is a smooth, fast, easy to use toolkit for getting the data your solar project requires, quickly, affordably and flexibly. It also has in-build validation tools to make quality assurance a breeze – our mantra: simply, the best data. 

Ease & speed of use.

Within about a minute of a free registration on the Solcast website, users are directed to our API Toolkit. There, users can proceed to make a historical data request for the site(s) of interest.  Historical time-series data? No problem. TMY data? We’ve got you covered. Monthly averages? Those are available too. All available for download within 5-10 minutes of submitting your request. You don’t have to wait until next week for your data any longer!

Of course, it’s not just about accessing the data easily and quickly.  Building the solar-powered future also requires ease of use with respect to integration with existing PV power modelling software.  Here, we’ve also got our users in mind, with file downloads with TMY3, SAM, PVsyst compatibility, along with our own standard CSV format.  When you download your data, all of these options are available to you. They also won’t disappear. Return to the downloads page at anytime, and your data will be waiting for you. Next week. Next year. Next project. It’s always there to grab it again!

Price flexibility

Another important aspect of building the solar-powered future, are the various types of data required at different stages of project development.  Monthly averages and TMY data tend to be used during prospect and early revenue modelling. Once a project is ready for financing or preparing to be sold, historical time-series data are needed.  Until now, users have always had to purchase expensive subscriptions that include all of these data types, regardless of their use case. Solcast has broken through this rigid model to offer users pricing flexibility.  Get what you need. Pay for just that. No forced extras. Purchase the data you require for the current stage of your project, and come back for more later, only if you need it!

Validation & Transparency

No source of solar data services can be trusted without being properly validated against high quality surface weather stations sites.  In mid-2019 extensive analysis was performed comparing Solcast data with publicly available surface measurements from around the world, across all climate types except polar climates. This includes both an independent third-party analysis in Solar Energy journal [1] as well as an internal Solcast analysis, now presented on our website.  We’ve even made it possible for any users to replicate their own validation, by making the relevant time-series data available for download on request.

The most common statistical indicators in the solar industry used to evaluate solar radiation models fall into two categories; bias measures and error measures. We’ve made sure to include both in the validation results, including Mean bias error (MBE) and Root Mean Square Error (RMSE).  MBE (bias) results aggregate difference between the Solcast dataset compared against ground observations, and are high important for properly determining unbiased ROI figure. The RMSE results are representative of accuracy, in particular for operational calculations such as yield assessments or the use of historical time-series data for due diligence exercises.

Global Horizontal Irradiance
Mean Bias Error0.0%
Standard Deviation of Bias±1.7%
Root Mean Square Error16.9%

Closing thoughts

Planning, building and operating solar farms is a tough job. But all around the globe, the hard working folks of the solar energy industry are delivering on many gigawatts of capacity each month, at an ever increasing pace.  At Solcast, we’ve seen many ways in which the challenges arising along the way can become overwhelming, and our team has dedicated ourselves to removing those barriers – so that you can get back to building the solar-powered future. We think that solar energy generation is a common sense investment, and can be highly successful,   but, for that to occur each solar farm needs to be a transparent and straightforward investment. That’s why we aimed our technologies at making the required solar data services easy to access, easy to use, and of the highest quality available. We hope you’ll join with us in building the solar-powered future by giving our API Toolkit a try – there will be free historical data credits waiting for you on sign-up!

Peace, Love and Solar
Dr. Nick Engerer
CTO, Solcast

[1] Bright, J.M. 2019.  Solcast: Validation of a satellite-derived solar irradiance dataset. Solar Energy, 189, 435-449, doi:10.1016/j.solener.2019.07.086.