«Best optical to thermal model in the industry» Leading Lender’s Technical Advisor


«Best optical to thermal model in the industry» Leading Lender’s Technical Advisor


«Best optical to thermal model in the industry» Leading Lender’s Technical Advisor

About Sunntics


Sunntics' mission is to make Concentrated Solar Power competitive through better tooling

by providing the first integrated commercial toolset for optimised design and operation of CSP plants. Our toolset helps drive LCoE down. It enables all parties involved in the project life cycle to create optimised solar field designs, optimise solar field operations, and assess expected plant performance at all stages of development.

Concentrated Solar Power is a utility-scale power generation technology. The use of thermal storage makes it dispatchable and hence complementary to solar photovoltaic (PV) generation. CSP is an increasingly important part of the generation mix in sun-rich countries. The International Energy Agency forecasts that it will account for 11% of world power generation by 2050. But to do so it must be competitive.

CSP needs a step change in engineering outcomes and productivity

Up till now the engineering of the solar side of CSP tower plants has been an inefficient, labour-intensive process. Typical issues include:

  • Tedious, repetitive tasks
  • Modelling techniques not fit for purpose
  • Limited ranges in time and space
  • Multiple specialists, each with their own tools

Project management of such efforts often suffers from several factors that increase complexity: multiple locations, multiple vendors providing information on the basis of different assumptions as well as multiple offtaker contract structures.

Finally, information technology is often an obstacle. The models used may have licences that are tied to one desk-bound workstation, hence creating a bottleneck resource. Even partial analyses sometimes run for days, hence often only a few runs are possible. Many results are thus achieved by extrapolation and interpolation instead of by modelling or simulation.

The consequences of all this are painful and include inconsistent results, with solutions only evaluated for specific moments in the year
Reliable, detailed yield projections for a whole year are typically not possible and sensitivity analyses are thus often «a nightmare”. This situation is not only ineffective, it is also inefficient and consumes large amounts of engineers’ time.

Our toolset is a game-changer, optimising both plant design and operations

The creation of CSP tower plants is still an immature market. Up till now there were no commercially available tools to optimise the design and operation of a tower plant solar field. Large design margins are thus often employed to achieve warranted performance. This practice leads to over-dimensioning and lack of balance, and hence to higher Capex and Opex, giving a Levelised Cost of Electricity (LCoE) that is higher than it need be. Our toolset helps developers and engineers create highly competitive plants.

Our modelling and simulation approach delivers a revolution in tool capability...

Our toolset delivers a revolution in modelling capability in four ways:

  1. Improved translation of physics to numbers: we employ and combine state of the art models to obtain the best and most accurate representation of real world phenomena;
  2. Integrated technical and economic optimisation: we balance the optical and TES design with the conventional power block;
  3. Optimised heliostat aiming: we get maximum thermal output while minimising thermal stresses and and thereby lowering risk for each moment of the year (non-convex problem);
  4. Leveraging AI/Machine Learning and cloud power: we use ArtificiaI Intelligence driven optimization routines, using machine learning and the vast number of calculations we can easily make by scalable use of computing power.

The result maximises investment yield, minimises LCoE and reducing technical and economical uncertainty and risks.

...and our platform delivers scalable, ‘use anywhere’ capability with an easy-to-learn interface

Our SunnSaaS toolset can be used on any platform with a web browser. It provides a secure cloud-based customer environment that can be used from any location, with state-of the art security and access control. It is ideal for consultants and engineers working from home or a remote location.

SunnSaaS uses advanced database management with algorithms in ‘workers’ that are launched on demand, giving fully scalable computing.

SunnSaaS has a clean, user-friendly, intuitive interface that is easy to learn. As a consequence, less specialised staff can be used to perform modelling tasks. This enables better leverage of scarce specialised staff, and enables scale-up to handle multiple large projects at once.

CSP tower plant schematic

Practical stories

We’ve collected a few practical examples of how customers use SunnSaaS to drive their CSP projects. Click on one of the titles to see how.

Screening a new CSP project for my fund in just a few days...

Life is tough as a fund manager in clean energy investments. Lots of money is looking for good projects, but returns on new solar PV and wind farms are pretty thin. The market noise about storage doesn’t translate into real world opportunities: most are battery based with poor returns or involve risky new technology. A couple of recent developments that didn’t make headlines amid all the COVID noise may change the clean energy investment game and make my life a whole lot more interesting.NREL CSP Best Practices Study

The first is a recent report on CSP Best Practices by the US National Renewable Energy Laboratory (NREL). CSP (Concentrated Solar Power) has been temporarily eclipsed by the rapid success of solar PV. Its high costs and perceived technology risks made CSP unattractive to investors. However, it is actually complementary: modern CSP plants use thermal storage that is BIG and cheap, enabling large scale solar generation after sunset.

The NREL report shows that despite typical early adopter issues over the past few years, CSP is now a proven technology with no unresolved technical problems; many mishaps were caused by poor project management. The challenge now is to do CSP projects better, faster and cheaper, often as hybrids with solar PV.

Power Output exampleThe second development is a CSP toolset developed by Sunntics that helps do just that. Screening opportunities and getting parties together on a CSP project has been a painful process up to now, as there were no good tools to do so. Projects were put together in a piecemeal fashion in a slow process using lots of specialist engineering hours. Slow progress and high upfront costs put the brakes on from the start, and designs tended to be overdimensioned and suboptimal.

What Sunntics’ SunnSaaS tool does for me is enable me to assess a CSP project opportunity in a matter of hours instead of weeks. I just feed it a location, a power profile, meteo data and some component information and within a few hours it produces an optimised design with predicted yields and costings. I can explore alternative locations and technology options in parallel if I want. The tool produces beautiful clean graphics that I can put straight into a prospectus. So now I can really build momentum, getting from an idea to a ‘hot’ project proposal that investors will sign up to in a few days. And of course these projects have what everybody wants: storage! And it’s BIG!

See how easy it is to assess a potential project with SunnSaaS. <link to video>

Getting our power auction bid over the line...

Bidding a renewable power project to a big copper mining company is nail biting work. The mine runs 24 hours per day, 365 days a year, so it wants cheap power all the time. Burning carbon to generate electricity is no longer an option as this South American country has committed to a drastic reduction in the carbon intensity of mining operations by 2030. So we are bidding power from a hybrid solar PV-CSP plant with a lot of thermal storage.

We are bidding into a reverse auction. In the first round we have to show the mine that our plant will deliver to any agreed power schedule. I need to demonstrate that our design predicts what power can be delivered when and guarantees that delivery.  The next two rounds are “just” about price. To win we need to be the cheapest qualifying bidder.

We also need to choose a builder. Several consortia are keen to build the plant and have submitted tenders based on technologies that have been proven elsewhere. However, all of these plants were designed piecemeal and have oversized subsystems to meet delivery guarantees. One large plant has a tower that is too high, a receiver that is too big and more heliostats than it needs. However, overdimensioning doesn’t always help; in practice the plant only just achieves the warranted performance.

I have to ensure that our bid dimensions the plant optimally. Submitting a bid based on oversized subsystems will make our bid too expensive. Reducing subsystem sizes increases delivery risks. Winning the auction and then failing to deliver will cost us a LOT of money.

In the past there were no commercially available tools to optimise plant dimensions. We have built some of our own, but they only solve parts of the problem and are rather labour-intensive.

So to get to a winning bid we have started using SunnSaaS, a revolutionary new tool that uses artificial intelligence and cloud-based supercomputing to optimise CSP tower plant design.

SunnSaaS ensures that tower, receiver, storage and heliostat field are properly matched to deliver a required level of thermal output and thus electrical power. It creates a design using component cost and performance data as well as financial parameters and simulates plant performance for every hour of a typical year. SunnSaaS iterates this process until it finds a design that minimises LCoE. Outcomes include detailed yield predictions, dimensioning of solar components and cost estimates as well as heliostat aiming patterns. We can derisk our bid by repeating the process using non-typical meteorological years and other scenarios.

SunnSaaS gives me confidence that we can not only submit a winning bid but also deliver against our promises. This doesn’t just help us, it also helps the mine and our country reach their decarbonisation targets. Using SunnSaaS also helps our reputation: a leading Lender’s Technical Adviser recently described SunnSaaS as the “best optical to thermal model in the industry”.

See how easy it is to assess a design option with SunnSaaS <link to video>

Re-evaluating the solar generation mix in Saudi Arabia

Sunntics’ SunnSaaS toolset was used to support a re-evaluation of the solar generation mix in Saudi Arabia, in co-operation with the King Fahd University of Petroleum and Minerals. The study compared the yield and costs of three solar generation technologies (PV, parabolic trough and tower) at three different locations in Saudi Arabia with different meteorological characteristics and with differing amounts of storage. Each plant had a nominal rated capacity of 150MW.

The background to the study was Saudi Arabia’s published Vision 2030 plans for 58.7 GW of renewable generation: 16 GW of wind, 40 GW of solar PV and 2.7 GW of CSP.

The study showed that while PV is the cheapest technology if storage is not considered, it becomes steadily less attractive as storage is added. In contrast, a CSP tower plant is the most expensive option if it has no storage, but it is the cheapest option if 9 hours of storage is required. The implication is that it is worth reconsidering the relative share of PV and CSP in the 2030 plans.

The graph charts Average Load Supply Factor (ALSF: a yield measure) against the Levelised Cost of Electricity (LCoE) for the three technologies, with differing amounts of storage, at Tabuk.

LCOE and ALSF - Tabuk

Sunntics algorithms have many uses in the CSP project life cycle

Sunntics’ algorithms can be used for many tasks in the project life cycle by a wide variety of stakeholders. Our software enables a lightning-fast turnaround on initial concept or site studies, supports developers in negotiating a power purchase agreement, helps fine tune operations and gives fast, accurate analyses to support due diligence on CSP assets. An overview of typical applications is shown below.

Suitable for: ◼︎ Sponsor/Owner |◼︎ EPC/Technology Supplier |◼︎ Operator |◼︎Financier  and their advisors


  • Concept and Site Studies ◼︎
  • Design Optimisation for PPA/ Auction ◼︎ 
  • Detailed Design ◼︎
  • Tender Evaluation and Negotiation ◼︎◼︎
  • Technical Due Diligence ◼︎

Project execution & construction

  • Performance Assessment ◼︎◼︎◼︎
  • Plant Control ◼︎

Commercial Operation

  • Performance Assessment ◼︎◼︎◼︎◼︎
  • Production Forecasting ◼︎◼︎
  • Plant Control ◼︎
  • Technical Due Diligence ◼︎◼︎


SunnSaaS workflow for a Concept or Site Study

Accurate, rapid, report-ready results

SunnSaaS for Sunntics is a browser-based tool that provides accurate results fast.

Its core is a set of algorithms that optimise CSP tower plant design and operation to minimise the Levelised Cost of Electricity. The algorithms use Artificial Intelligence techniques and scalable cloud computing to create optimal designs for multiple scenarios in parallel.

SunnSaaS produces clear, easy to read graphics and overviews that can be incorporated directly into a report, as well as comprehensive outputs that can be fed into other tools for further processing.


Maximum leverage from your scarce resources

The neat, uncluttered interface enables novice users to achieve rapid results while enabling more experienced engineers to access advanced features. SunnSaaS enables you to gain maximum leverage and productivity from assigned engineers as well as freeing up workstations required to run conventional on-site tools.

Sunntics gives highly accurate yield estimates that de-risk projects

The weak link in classic yield assessment is the efficiency factor simplifications used to model solar field performance.

Classic EYA workflow

Solar field efficiency varies with every hour of the operating year. A single efficiency factor (or a limited set) does not capture this variation in efficiency => despite the use of 10 minute timesteps to model transients, the results are inherently inaccurate.

Even if overall electricity production over the year is ‘about right’, detailed predictions will inevitably be wrong; experienced professionals report errors up to 30% at a daily level. This level of inaccuracy carries serious risks for an output prediction.

SunnSaaS’ advanced scalable computing overcomes these problems by taking an integral approach to each day and each hour of the year, giving accurate detailed predictions of thermal output.

Optical efficiency per heliostat

Accurate detailed predictions of thermal output enable reliable prediction of electricity generation capacity for the whole year, and thus de-risk the project.

Getting the full potential from capital spend on CSP

CSP will play an important role in reaching the 2050 decarbonisation goals. IEA estimates 11% of global electricity generation will use CSP. However, built-in storage, balancing intermittency and continuous supply only gets CSP technology so far. So, we aimed for a target not seen in other renewable energy systems: accelerated optimisation at an early stage of industry maturity.

To solve current and future CSP challenges, drastically improve performance and disrupt conventional wisdom, we have redesigned CSP design and operation from the inside out. The result? Two SaaS products we’re incredibly proud of.

SaaS heading

SunnSaaS for AI-based optimised design and assessment of CSP projects

  •  Feasibility assessment of potential sites and technology options
  • Detailed design, performance and cost modelling for tendering & evaluation
  • Presented on an intuitive, user-friendly interface.

AIRO control module optimising heliostat aiming to maximise thermal output

  • Continuous optimisation of heliostat positions to maximise solar-to-thermal energy transfer
  • Real-time optimisation of the aiming regime and solar flux distribution to maximise energy transfer
  • Enhanced receiver reliability and durability.



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