Engaging Energy

This is an idea that I first aired at the Falmouth Energy Week Conference in the innovation workshop, but that I’ll fully explain here.

There is a problem with new physical machinery in general. It doesn’t work very well.
There is a problem with innovation in the physical machinery of new low carbon energy systems. It costs a lot.
There is a problem with gaining people’s acceptance of new things in their landscape. We fear change and the unknown.

Here’s an idea to address all three issues a little at a time.

In order to increase the efficiency of the new physical machinery of a low carbon energy system it needs to be tested. It needs to be tested under different physical loads, under different environmental conditions and in different locations in order to find the optimum design characteristics such as low environmental impact, high output over as large a set of conditions as possible, low failure rates, etc.
But a lot of that can be done without building full-scale pilots and most of it can be done without building anything physical at all.

There is a common characteristic of many of the low carbon energy flux capture devices and indeed energy efficiency improvements i.e wind turbines, wave devices, tidal devices, high altitude kites, vehicle streamlining, etc, etc. That common characteristic is that their efficiency can be modelled using mathematical techniques called finite element analysis (FEA) and computational fluid dynamics (CFD). These models are difficult to design and take a lot of computing power to run, so only the larger companies and consultancies have their own in-house modelling capabilities.
How about we, the people, pay for a really good modelling tool to be built, but instead of forcing aspiring designers to buy it we give it away. But that’s not all. A key element of this issue is the ability to run lots of simulations to find the most efficient solution before building the damn thing, so we build the modelling tool to run on many, many computers at the same time using another technique called distributed computing. If you’ve seen SETI@Home or any of the other screensaver programs that take a chunk of data and use your home PC to analyse that data before sending the results back to a central point, you known what I mean.

And that’s the third issue dealt with too.

In making the general public part of the design process we automatically build in acceptance. We demystify and educate and empower through the simple act of involvement in the process. In contrast to the shared-ownership models of community acceptance that rely on a certain venality that rankles with many, this would be a genuinely altruistic action that has a side benefit of making sure that every participant had a vested interest, albeit a small and non-monetary one, in seeing these devices work. The designs would be publicly owned, the implementation would be privately done, and could include a portion of community participation if appropriate to the project.

If you wanted to you could have a split between device design and project implementation. If you think about a 3D terrain model (Ordnance Survey already has these) and placing turbines on it to minimise visual impact vs output, or even offshore for lines of sight. You could introduce a genetic algorithm to produce multiple design iterations, for example of a turbine blade and model the efficiency of each iteration to produce an efficiency envelope. You could model vibration modes at different operating speeds to minimise noise and failure rates. Every scenario that you could think of modeling would be accessible to every company.

There you go. Cheaper, community-embedded, device designs with a higher chance of acceptance and therefore a higher chance of implementation.