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Great Divergence between Modelling and Reality in Energy Supply-Demand - Barış Sanlı


Are numbers a sealed guarantee for arguments to be scientific? Are math and equations a predictor of the future, or is it an abstract language to communicate rational choices? Recently we are more into selling future energy supply-demand visions through numbers that can be confused as scientific facts. These are products of thousands of human assumptions; therefore, they are simulation instruments. On the other hand, science is not fact per se but a never-ending quest to find the truth. There are no full stops in science, even for gravity.


Climate models are atmospheric models, and global warming has a scientific and proven basis. There are several issues with radiance or other minute parts. But this is a physical phenomenon model, like 3D structural simulations. Energy supply-demand modeling is a different beast. Our subject is the latter model.


Recently we have seen a stall in the energy transition. The root problem is the way our world works. We have two realities, bits and atoms. Bits are the currency of electronically produced information of all sorts. Atoms are, on the other hand, the tangible and physical assets we encounter. You can change the design and test a wind turbine in a few days, but the new turbine manufacturing process and implementation will still take months. The only positive part of this energy transition is solar panels, but this is thanks to China’s aggressive industrial and export policies. The world depends on China for solar panels much more than OPEC+ for oil.


The time multiplier between bits and atoms is, unfortunately, huge. For example, training people and engineers for new technologies will take years. A permit takes 4-10 years for clean energy technologies. The infrastructure takes up to 16 years in developed countries. But in a computer simulation, it is a matter of minutes. The solution is easy, integrating physical realities into simulations.


For example, creating digital twins is a good way to have more realistic numerical models. However, most of the energy future models, even the most famous peer-reviewed ones, do not consider permitting times, standard requirements, time to train human beings, and financing issues in developing countries like the quadrupled cost of capital for new investments. These models look as if they first have the cart and try to find the horse.


Like social media acting as a medium for the rapid transmission of disinformation rather than the immediate broadcasting of the truth, the modeling world is more about ideas reflected as numbers than numbers reflecting reality. This is not wrong, and I am not against this. I have seen future scenarios on energy where academicians have no idea how an investment is made or why wind companies are suffering from major losses or a China scenario where clean energy manufacturing prices may rise.


This great divergence between modeling and reality is creating a pseudo-scientific debate about energy futures. These 1000 GWs of investments, those millions of EV cars, behavioral changes that can decrease energy consumption like 20%, water and electricity poor Africa exporting rich countries hydrogen with limited water resources are ideas, not science or reality. We need more of these ideas. But we should understand that these are not facts, the science of laws but ideas and imaginations decorated with numbers and equations.


We are dreamers. One theory says that our dreams are alternative scenarios our brains run when we disconnect from consciousness. Models are more about abstract realities constructed by numbers, and equations pushed into alternative scenarios. We have to dream and use our imagination to the end. But confusing this with reality is not the way to go.


Energy transition needs more technology, engineers, technicians, financing, and infrastructure than we can ever encounter. For models, this is a number tied to an equation fed by some assumptions. This is a long journey for the real world, requiring lots of experimentation, backlashes, and probably the greatest challenge we have seen. We are just scratching the surface.