Automating renewables project development to scale the energy transition
We need to act fast to avoid the most severe impacts of global warming. Currently the world is on track for 2.9°C of warming, versus a Paris Climate summit target of 1.5°C.
Renewable energy project development needs to speed up and a key goal of COP28 was to triple global renewable energy capacity from 3,500 GW to 11,000 GW by 2030. Under the current trajectory, DNV predicts global installed renewables capacity to triple by 2035, with a seven times growth in wind and 13 times growth in solar by 2050. This means that engineering teams must process a minimum of three times more capacity in each of the next three decades than they have in all the last three decades combined! Some of this will come from a larger workforce and faster manufacturing and construction processes, but much will need to come from higher speed feasibility and engineering processes.
To achieve this required high speed project development, we need to find efficiencies throughout the development lifecycle but particularly right at the start. The faster you can determine where your project will be and what it will look like, the faster you can begin detailed design. Intelligent automation of most site selection, technology selection, and pre-FEED concept design processes is a major step towards this goal. Automation tools, such as DNV’s Renewables.Architect, have been developed for precisely this purpose.
Renewables.Architect is a software platform which contains a wide variety of engineering and cost models that can be linked together into multidisciplinary workflows that optimize project concept design, minimize levelized cost of energy (LCoE) and accelerate project development by performing complex analyses in minutes. Using automation tools during different stages of a project development lifecycle could look like this:
1. Site selection and LCoE comparison
Start by evaluating high level LCoE for a range of potential sites (they could be onshore, offshore fixed, or floating). Renewables.Architect will generate a concept turbine design of any size (including scaling to future turbine properties), concept foundation design, automatically generate a farm layout and select and lay out array and export cables. Installation, transportation, and operations costs, and a rapid energy yield calculation based on DNV’s WindFarmer algorithms are calculated and then fed into a project balance sheet that provides comparative LCoE figures in minutes. Many inputs are unknown or uncertain at this stage, so Renewables.Architect includes simplistic models with reduced sets of inputs to enable these high-level analyses to be performed.
2. Pre-FEED concept design
Once a site has been selected, higher fidelity models in Renewables.Architect’s modelling suite will be selected to rapidly generate and optimize site-specific concept designs. Renewables.Architect’s advanced loads models adapt loading estimates to site-specific conditions. The load components generated for the turbine feed into design optimization models for the support structure and foundations. Jacket footprint optimization and member sizing, pile embedment and sizing calculations (based on soil profile), gravity base sizing optimization and floater concept design (generic semi-sub, spar or TLP), based on motion response and stability checks are key features of Renewables.Architect’s fully automated concept design models. DNV’s foundation clustering algorithms allows a finite number of foundation designs to be determined and costed to deal with varying water depths and soil conditions across a site. These designs can then be used as a basis for more detailed design in dedicated design tools, for example DNV’s Bladed and SESAM software.
3. Design optimization
In the detailed design stage, automation tools can still be of use. Cost effective component design requires a thorough understanding of the impact that changing one component has on the surrounding system. Renewables.Architect was built to support high fidelity, holistic design optimization and its interconnected models can be used to aid designers in understanding the impact of individual component design choices on the bigger system, expanding their design “horizon” and ensuring optimal system design is maintained.
Sensitivity and risk analysis
At all stages, understanding project risk is key to robust development. Analysts should run multi-level probabilistic analyses to fully understand the knock-on impact and uncertainty on key performance indicators. Typical studies may look at varying commodity prices, material properties, labour rates, uncertainty in port facilities or site conditions, such as water depths and soil profiles. A key example of these multi-level analyses would be a Monte Carlo analysis, where single value inputs are replaced with probability distributions which are then sampled over thousands of simulations to give probabilistic outputs. Probabilistic outputs are already well established in energy production assessments (think of the commonly used “P50” and “P90” figures) but their use should be encouraged across all key performance indicators.
Good data on the appropriate probability distributions for inputs can be hard to come by so simpler scenario-based sensitivity studies can be used. Consider what the possible ranges on key inputs could be and then run analyses using a number of values from across those ranges. While these are much easier to perform than Monte Carlo approaches, they can still run to tens or hundreds of simulations. Therefore, intelligent automation is critical.
Tools like Renewables.Architect can provide powerful and flexible frameworks that allow users to simply enter the probability distributions or expected ranges for key inputs and then the software automatically does the hard work of sampling the inputs, running the simulations and post processing the results into the key output distributions or sensitivity metrics. Deeper understanding of project risk can be achieved in days rather than months and should be the target in all project development.
Our UK Energy Transition Outlook 2024 highlights that electricity demand in the UK will increase by a factor of 2.3 by 2050 compared to today. This demonstrates the significant scaling of the nation’s energy system by 2050 and the pressure that industry will be under to deliver.
The power of intelligent automation through software like Renewables.Architect is to free engineering teams. Desktop studies using bespoke spreadsheets that used to take months to complete are now generated in less time and provide adaptable tools that allow you to identify the optimal choices, understand risks and sensitivities, so that they can progress to the next stage of the project lifecycle.