In order to deliver the best design outcome in any situation, the problem and opportunity must first be truly understood.
Faraday Grid use a robust design methodology, developed by its founders, called Design by Rationalised ConstraintTM (DbRC). This has enabled us to truly understand problems, and then work from fundamentals to define the area within the constraints in which the optimal design solution must exist.
This is how we established our unique solution to the energy trilemma.
‘Traditional’ approaches to systems design
Engineering as a profession has gradually moved toward a methodology of design by precedence. At the core of this commercially driven approach is the desire to limit risk by trying to understand and quantify factors – such as schedule and cost – as early as possible in the process. Ultimately, this leads business to disproportionately value ‘known knowns’ and pre-existing design solutions.
However, as no two circumstances can be exactly alike, it verges on the statistical impossible for a predetermined solution to be the best outcome – even when it may have ‘worked’ previously. The gap between the best solution and the predetermined solution is defined as ’opportunity cost’.
The academic approach takes an inverse approach, seeking to discover new ideas, methods and outcomes. This has been central to many important and significant discoveries over time.
However, academia is not always aligned with commercial requirements - economic or otherwise - and new solutions can be left trying to find an application, or are abandoned entirely. This is epitomised in the classic criticism - “a solution looking for a problem”.
Ultimately both approaches suffer a similar requirement for the problem’s parameters to adapt to their solution. Simply, the world doesn’t easily adapt to human ideas, but human imagination can easily adapt to the universe. We just need to get ourselves out of the way of the solution.
Design by Rationalised Constraint
When we apply DbRC to a complex system like an electricity grid, we must first define the problem we are trying to solve for. Rather than focussing on resolutions to the symptoms from which the grid is suffering such as blackouts or brownouts, understanding why the grid behaves in certain ways is key. These behaviours can be expressed in the form of system constraints.
These constraints include things like the laws of physics, policy and environmental regulations, system economics, and even social license. For example, the electricity grid cannot be switched off for an extended period while we resolve issues.
Once we have defined all the constraints on the system and how they interact we have, in fact, created a solution envelope. By definition, the optimal solution to the problem must lie within these boundaries. The closer the definition, statistically the more optimal the solution and the lower the risk.
Rather than presupposing a solution based on a set of assumptions – whether they be calculated or arbitrary – Faraday Grid use DbRC, the tools of advanced simulation and data analysis to identify the optimum design of a solution.
As the constraint model is built up from fundamentals, the inherent error introduced by assumptions is limited, and can be further reduced by testing the constraint boundaries. Understanding what the solution cannot be allows us to understand the location of possible solutions. The optimal solution emerges
How does all of this apply to electricity grids?
By using the principles of Design by Rationalised Constraint, it is clear that the present and future requirements society has of electricity grid are beyond its original design intentions. This is a function of the radical change underway in how we generate electricity and how we use it.
Simply adding complexity to resolve the symptoms for example, introducing even more variable renewable energy to resolve a single leg of the energy trilemma, severely limits our design choices and ability to adequately resolve the delicate balance of affordability + sustainability + reliability.
Faraday Grid designed our technical solution to rebalance electricity networks by analysing and understanding the constraints of the current system as they are, not as they are perceived.
That is why Faraday Grid presents a more economical and technically viable solution for the energy transition.